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Research Design Exam II
Research Design Exam II
303
Psychology
Graduate
04/19/2013

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Term
Inductive reasoning
Definition
Process of reasoning in which the premises of an argument support the conclusion, but do not ensure it.  It is used to ascribe properties or relations to types based on limited observations of particular tokens; or to formulate laws based on limited observations of recurring phenomenal patterns.
Term
When do you use inductive reasoning?
Definition
In specific propositions, such as initial observations or general propositions.
Term
What is an example of an initial observation in inductive reasoning?
Definition
The ice is cold.  The ball moves when you throw it.
Term
What is an example of a general proposition in inductive reasoning?
Definition
All ice is cold.  For each action, there is an equal and opposite reaction.
Term
In inductive reasoning, specific instances lead to...
Definition
General propositions.
Term
What is deductive reasoning?
Definition
Inference in which the conclusion is of no greater generality than the premises, as opposed to abductive and inductive reasoning, where the conclusion is of greater generality than the premises.
Term
What are some examples of valid deductive reasoning?
Definition

The picture is above the desk, the desk is above the floor, therefore, the picture is above the floor.

All birds have wings, a cardinal is a bird, therefore, a cardinal has wings.

Term
In deductive reasoning, general propositions lead to...
Definition
Specific instances.
Term
What are some examples of invalid deductive reasoning?
Definition

Lemons are a citrus fruit, my car is a lemon, therefore, my car is a citrus fruit.

All baby goats are kids, I have a kid, therefore, I have a baby goat.

Term
With regard to reasoning, a question you may want to ask yourself for grants/theses is, "Are your hypothesis...
Definition
Dependent on one another?"
Term
What is infinite regress?
Definition
In a series of propositions, arises if the truth of the proposition in P1 requires the support of proposition P2, and for any proposition in the series Pn, the truth of Pn requires the support for Pn+1, because the infinite series needed to provide such support could not be completed.
Term
What is a tautological argument?
Definition
Otherwise known as a circular argument, that is, one that begins by assuming the very thing that is meant to be proven by the argument itself.  Tautological arguments are not really arguments at all; they assume facts yet not in evidence.
Term
What is tautology?
Definition
The use of redundant language in speech or writing (e.g., saying the same thing twice).
Term
What are some examples of tautologies?
Definition
Non-cognate synonyms (e.g., helpful assistance, a three-part trilogy) or repetition of an abbreviated word (e.g., ATM machine, PIN number).
Term
Science proceeding from the bottom up is _____ --> _____, whereas science that proceeds from the top down is _____ --> _____.
Definition
Observations --> theories; Theories --> observations.
Term
Popper argues that science proceeds through _____ methods.
Definition
Deductive.
Term
What are Hume's four arguments about science?
Definition
(1) Beliefs through general laws are attained by inductive inference, (2) Inductive inference is unjustified because inferences can be disproven, (3) If a belief is not justified, then it does not count as knowledge, and (4) As a result, we cannot have knowledge about general laws.
Term
What are Popper's arguments in response to Hume?
Definition
(1) Denies that scientists use inductive methods at all, (2) Theories are conjectural and development of theories is not necessarily a logical matter, (3) The testing of a theory, on the other hand, can proceed along logical lines, and (4) Illogical theories can be systematically tested?
Term
According to Popper, along which four lines does the evaluation of a theory proceed?
Definition
(1) Logical comparison of conclusions yielded by the theory (evaluation of internal consistency), (2) Investigation of the logical form of the theory (empirical? truly scientific? tautology?, logical forms can sometimes be circular), (3) Comparison with other theories (is it an advance? paradigm shifts? theory cannot explain everything), and (4) testing theory through empirical means (does new theory explain better than old and explain issues the old could not?)
Term
Thomas Kuhn: Science is like...
Definition
Politics because (a) your theory cannot explain everything despite infinite alterations, and (b) paradigm shifts.
Term
Experiments will yield statements that either _____ or _____ the theory.
Definition
Support (verify); Do not support (falsify).
Term
If a theory withstands a host of empirical tests, it should not be...
Definition
Supplanted.
Term
Two good reasons for discarding a theory?
Definition
(1) Replacement of a theory or attendant hypothesis by another hypothesis that can account for results better, or (2) Falsification of one of the consequences of the hypothesis.
Term
True or false: Corroboration and verification are the same thing as saying the theory is true in any meaningful sense.
Definition
False, corroboration is testing the individual elements of a theory; no theory can ever be completely "true," only supported.
Term
True or false: There could always be better theories to account for facts.
Definition
True.
Term
True or false: No other variables can alter our conclusions besides what we are already taking into account.
Definition
False, other variables may alter our conclusions and we may not always be taking these into account.
Term
Popper: No conclusive _____ of a theory can ever be produced.
Definition
Disproof.
Term
In the example given during lecture, Galton developed a theory of inherited intelligence and success.  Based on the science of theories, what did he do wrong?
Definition
Galton forgot to take into account monetary advantages.  He did not consider all the variables that may alter conclusions.
Term
If the aim of science is to provide true theories that have been verified, what is the best way of doing this?
Definition
Generalizations cannot be conclusively verified, but can be conclusively falsified.
Term
Trying to "confirm" theories by observing more and more positive inferences does...
Definition
Nothing toward proving a theory.  Theories can never be proven, just supported or falsified.
Term
What is the cornerstone of Popper's approach?
Definition
Falsification, unlike verification, can weed out false theories, which is done by trying our best to falsify or refute them.
Term
Popper's perspective is the opposite of...
Definition
An inductivist perspective.
Term
What does an inductivist believe?
Definition
Allow into body of knowledge only those theories which one has good reason to believe to be true.
Term
What does a falsificationist believe?
Definition
The way to truth is to allow any theory into one's body of knowledge and then expel the false ones.
Term
What distinguishes science from non-science?
Definition
Falsifiability.  Statements about theories are falsifiable, not the theories themselves.
Term
Popper's claim regarding falsifiability:
Definition
"A theory is scientific if, and only if, it is falsifiable by empirical evidence."
Term
Determining falsifiability always involves methods of...
Definition
Observation.
Term
True or false: You cannot infer from a statement of theory whether it is a scientific statement.
Definition
True.
Term
How are falsifiability and scientific vigor related?
Definition
They have a positive relationship.
Term
Theoretical "patches" (e.g., alterations to your theory) decrease falsifiability.  What does this mean for the quality of your theory?
Definition
It decreases the quality of your theory.
Term
True or false: The proponents of a method do not have a way of falsifying it, making this a scientific theory.
Definition
False, if the proponents of a method CAN falsify it, then it is a scientific theory.
Term
According to Popper, Marxism, Adlerian psychology, and Freudian psychoanalysis are _____ because...
Definition
Unscientific; proponents of the theories refuse to count any possible observation as refutation.
Term
True or false: An unfalsifiable theory might still be true, it's just not scientific.
Definition
True.
Term
The basic aim of science is
Definition
Theory.
Term
What are theories built upon?
Definition
Description, classification, observations of functional relations/co-variations, and speculations of causality.
Term
According to Popper, it is impossible to evaluate the truthfulness of a theory, so what do we do instead?
Definition
We evaluate individual statements derived from the theory/hypothesis provided those statements are expressed in such a way that they can be falsified.
Term
Define theory.
Definition
A set of interrelated constructs, definitions, and propositions that present a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting phenomena.
Term
Do we truly understand phenomena?
Definition
Our degree of understanding is never truly known.
Term
What is the chief goal of the scientist?
Definition
Prediction and control.
Term
Two primary ways of evaluating theories:
Definition
(1) Falsifiability of statements (good theories cannot fit all possible explanations and certain events should disprove propositional statements consistent with the theory), and (2)  Parsimony (when both a simple and complex theory account for the facts equally well, the simplest explanation is preferred).
Term
What is Occam's Razor?
Definition
The principle of parsimony, which states that when both a simple and complex theory account for the facts equally well, the simplest explanation is preferred.
Term
How do we test propositional statements?
Definition
Propositional statements imply a relationship between variables, so we test the relationship between variables, not the variables themselves.  We test the functional relation that is hypothesized, which sometimes may be assumed to be a causal relation.
Term
Propositional statements are...
Definition
Implications from hypotheses (not direct hypotheses) or experimental hypotheses test proxies.  They are typically deduced from broader hypotheses.
Term
If your hypothesis is not supported and your theory is falsified, what could be the problem?
Definition
Issues in methods or you need to make ad hoc changes to your model (especially good to make these changes if they increase falsifiability).
Term
A good problem statement should...
Definition
Express a relation between two or more variables (under certain conditions, with certain variables, etc.), be stated clearly/unambiguously in question form, and imply possibility of empirical testing (e.g., you should be able to deduce the analyses to be run).
Term
Hypothesis testing implies the notion that...
Definition
The test can be failed, which is crucial, otherwise is it not really a test.
Term
What were the primary methods for data analysis in the 19th century?
Definition
Graphing data and implying differences between groups in that way.
Term
Galton developed the notion of...
Definition
Covariation.
Term
Pearson develop the...
Definition
Correlation.
Term
How did Galton utilize covariations?
Definition
By repeatedly graphing things.  This was similar to multiple regression inferential statistics in that graphing also found interaction effects.
Term
Why do many researchers question the utility of inferential statistics?
Definition
Because many long-lasting contributions to psychology were made by those who did not use inferential statistics (e.g., Freud, Skinner, Piaget).
Term
Define cause.
Definition
An insufficient but non-redundant part of an unnecessary but sufficient condition.  We wanted to see the effects of interventions, which is why we created inferential statistics.
Term
Define counterfactual.
Definition
Knowledge of what would have happened but for the occurrence of something (hypothetically speaking, your intervention can be the cause or counterfactual).
Term
Define effect.
Definition
The difference between what did happen and what would have happened.
Term
In causal relationships, which requirements do you need to say that A caused B?
Definition
Cause preceded effect, cause was related to effect, and there is no plausible alternative explanation.
Term
Define confound.
Definition
A systematic covariation of two independent variables.
Term
How is causality assessed?
Definition
Begin by holding all other causal variables constant.  You assess the level of a variable, implement experimental manipulation, and assess level of variable post-manipulation (basically, the pretest-posttest design).
Term
What are two comparisons that can be made when assessing a level of a trait pre- and post-manipulation of the experimental group?
Definition
(1) Compare across groups (e.g., same at pretest, different at posttest) and (2) Compare across time (e.g., changes in experimental group and not in control group).
Term
What is the cost of pre- and post-manipulation of experimental groups and leaving everything else constant?
Definition
Generalizability, because in reality, patients choose the type of treatment they would like to receive.
Term
Why is generalizability compromised in some experiments?
Definition
To achieve enhanced internal validity.
Term
What are the two steps to generalizability?
Definition
Random sampling and random group assignment.
Term
What is the two-step process of random sampling?
Definition
Random selection and random assignment.
Term
What are three types of random sampling?
Definition
Simple random sampling, cluster sampling, and stratified random sampling.
Term
What is simple random sampling?
Definition
Assume random selection but rarely happens because it is impossible to enumerate everyone in the population.  This type of sampling assumes all members are accounted for and they all have an equal probability of being selected.
Term
What is cluster sampling?
Definition
Dividing the population into clusters and randomly and proportionately drawing from the clusters.  It requires that you know something about your population.
Term
What is stratified random sampling?
Definition
Dividing the universe into relevant strata based on demographic variables.  It requires that you know something about your population.
Term
Clustering _____ estimates of the population parameters.
Definition
Decreases.
Term
Stratifying _____ estimates of the population parameters.
Definition
Increases.
Term
True or false: Random sampling frequently occurs.
Definition
False: Random sampling rarely occurs.
Term
According to the textbook, the two-step model of random sampling followed by random assignment cannot be advocated as the model of...
Definition
Generalized causal inference.
Term
The best way to design a study is to...
Definition
Randomize the selection and assignment.
Term
What is the alternative to the goal of producing findings that generalize to different people, settings, treatments, or measurement variables?
Definition
Understanding why findings do not generalize to different people, settings, treatments, or measurements variables caste within a general theory.
Term
True or false: You are more interested in your population than your sample.
Definition
True.
Term
Define validity.
Definition
Approximations of truth regarding causal inferences.  In the generalizability context, it is that your beliefs that A causes B are valid.
Term
Define construct validity.
Definition
The degree to which inferences can legitimately be made from the operationalizations in your study to the theoretical constructs on which whose operationalizations were based.
Term
According the theory of generalizability, what are the components of a theory?
Definition
Cause construct --> Cause-effect construct --> Effect construct.
Term
According to the theory of generalizability, what are the components of an observation?
Definition
Program/intervention --> Intervention-outcome relationship --> Observations/test scores
Term
According to the theory of generalizability, how do the components of a theory relate to the components of an observation?
Definition
Cause construct is related to program/intervention, cause-effect construct is related to intervention-outcome relationship, and effect construct is related to observations/test scores.
Term
Define external validity.
Definition
The extent to which our findings generalize to other persons, settings, treatments, or outcomes.
Term
What are the five principles of generalized causal inference?
Definition
(1) Surface similarity, (2) Ruling out irrelevancies, (3) Making discriminations, (4) Interpolating and extrapolating, and (5) Causal explanation.
Term
What is an example of surface similarity?
Definition
Since similar is knowing if findings generalize, an example would be Seligman generalizing his research findings of learned helplessness in rats to humans.
Term
What is an example of ruling out irrelevancies?
Definition
Determining that the height of felames does not matter for treatment success of depression.
Term
What is an example of making discriminations?
Definition
Since it is the opposite of ruling out irrelevancies, an example of making irrelevancies would be saying that treatment worked for women of varying heights, but will be ineffective for men.
Term
What is interpolating?
Definition
Extending hypotheses in the range of the measure.
Term
What is extrapolating?
Definition
Extending beyond assessed range.
Term
What is a causal explanation?
Definition
A causal explanation involves mechanisms of action and explanatory theories that will hold under a variety of conditions.
Term
According to the textbook, the five principles of generalized causal inference have implications for which two types of validity?
Definition
Construct and external.
Term
What are some threats to construct validity?
Definition
Person, setting, treatment, outcome, different types of constructs, being a scholar in isolation (versus an independent scholar).
Term
What is an inadequate explication of a construct?
Definition
A threat to construct validity that occurs when there is a mismatch between what you want to measure and the operations used to measure it.
Term

What is construct confounding?

 

Definition
A threat to construct validity that occurs because our operations are rarely a pure representation of what we are interested in.
Term
What is a mono-operation bias?
Definition
A threat to construct validity that occurs when facets that are over- or underrepresented are measured in multiple ways.  This can include several measures of a given construct.  If these findings are not congruent, you may present both findings or exclude one of them.
Term
What is a mono-method bias?
Definition
A threat to construct validity that occurs when presentation (e.g., administration of treatment) produces an effect.
Term
How is confounding constructs with levels of constructs a threat to construct validity?
Definition
Because results differ with the level of the construct studied.
Term
What is a treatment-sensitive factorial structure?
Definition
A threat to construct validity that is a way of conceptualizing treatment effects.  Treatment affects the presence of a construct and factor structure.  This type of structure is like a second wave CFA in that there is a different factor structure across groups (e.g., changes in the level of the construct presented).
Term
What are some other more specific threats to construct validity?
Definition
Inadequate explication of a construct, construct confounding, mono-operation bias, mono-method bias, confounding constructs with levels of constructs, treatment sensitive factorial structure, reactivity to self-report changes, reactivity to experimental changes, and experimenter effects, mismatching cause construct and program/intervention, mismatching effect construct and observations, reactivity confounds (novelty and disruption effects, compensatory equalization, compensatory rivalry, resentful demoralization, treatment diffusion), interactions of the causal relationship (with units, over treatment variations, with outcomes, and with settings), context dependent mediation, constancy of effect size, constancy of causal direction, and purposive sampling.
Term
What occurs in an interaction of the causal relationship with units?
Definition
Effects found for some units are not found in other units.
Term
What is an example of an interaction of the causal relationship over treatment variations?
Definition
One medication alone versus one medication in combination with other medications have different effects on individuals.
Term
What is an interaction of the causal relationship with outcomes?
Definition
Cause-and-effect may not generalize across outcomes (e.g., are treatments equally effective in treating different facets of constructs?).
Term
What is an interaction of the causal relationship with settings?
Definition
Some effects occur in some settings and not in others.
Term
Why is context-dependent mediation important?
Definition
Identification is a necessary process in order to transfer an effect.
Term
What are some things to consider when you want to sample to get diversity?
Definition
Persons, settings, treatments, and outcomes.
Term
Define statistical conclusion validity.
Definition
Inference made about the covariation between treatment and outcome.
Term
Define internal validity.
Definition
Impact of treatment on outcome.
Term
What are threats to statistical conclusion validity?
Definition
Low statistical power, violated assumptions of statistical tests, alpha inflation due to data fishing, unreliability of measures, restriction of range, unreliability of treatment implementation, extraneous variance in experimental setting, heterogeneity of units, and inaccurate effect size estimation.
Term
What are some ways to increase power?
Definition
Using matching/stratifying/blocking, measure and correct for covariates, use larger samples, use equal cell sample sizes, improve measurement, increase strength of treatment or the extent to which groups differ, increase variability of treatment.
Term
Poor measurement leads to poor
Definition
Outcomes.
Term
How do you increase the strength of a treatment?
Definition
Tightened construct measures with low standard error.  If you tighten these measures, you will see smaller standard deviations via the narrower normal distribution.
Term
What is a common reason for why people violate the assumptions of their statistical test?
Definition
They forget what they are.
Term
How do you correct for alpha inflation due to data fishing?
Definition
Use an adjustment statistic (e.g., Bonferroni).
Term
How does unreliability of a measure threaten statistical conclusion validity and what is a way to prevent this?
Definition
It attenuates the bivariate correlation between variables.  To prevent this, disentangle variances and look at different levels of the construct (can be done through SEM).
Term
How does restriction of range threaten statistical conclusion validity?
Definition
It reduces the power and attenuates the bivariate correlation between variables.
Term
What types of studies are susceptible to unreliability of treatment implementation?
Definition
Large studies or studies with administration at different sites.
Term
How does extraneous findings in the experimental setting threaten statistical conclusion validity?
Definition
They produce covariate findings that are inaccurate due to the setting (distractions, noise, change of location, etc.).
Term
Besides threatening statistical conclusion validity, what happens if units are too heterogeneous in the dependent variable?  How do you control for this?
Definition

Standard deviation increases and significance of the treatment effect decreases.

Control for this by creating a statistical control for relevant covariates or using confounds as blocking variables.

Term
What is the implication for inaccurate effect size estimation and what is an example in which this could occur?
Definition
Inaccurate effect size estimation threatens statistical conclusion validity and decreases effect size dramatically.  An example of this could be having many outliers that deviate from normality.
Term
What is an alternative to null hypothesis testing?
Definition
Computing confidence intervals.  This helps to distinguish between situations of low statistical power, and hence wider confidence intervals, and situations with precise, but small effect sizes.
Term
What are threats to internal validity?
Definition
Ambiguous temporal sequence, selection, history, maturation, regression (to the mean), controls, attrition, testing, instrumentation, and additive/interactive effects of threats to internal validity.
Term
Internal validity is the sin qua non of...
Definition
Experimental science (changes are a direct consequence of intervention).
Term
What is ambiguous temporal sequence?  How do you prevent this?
Definition
Order of the variables in the causal relationship is unknown.  Prevent this by using experimental designs.
Term
How does selection threaten internal validity?  What is a way to prevent this threat?
Definition
People on different conditions differ at the start of the experiment.  Random assignment may increase comparability, but this isn't guaranteed.
Term
How does history threaten internal validity and how is this threat prevented?
Definition
Anything occurring between the beginning of treatment (pretest) and posttest could have produced a desired outcome.  Prevent this by using the Solomon-4 group design (a quasi-experimental design), which increases duration and the probability that this will happen.
Term
How does maturation threaten internal validity?  How do you control for this?  How do you prevent it?
Definition
People change over time and this change can be assumed to be due to intervention when it happened outside of intervention.  It can be controlled for by sampling different geographical regions or using a cross-sequential design.  It can be prevented altogether by using the Solomon-4 group design.
Term
What occurs in a regression to the mean and how can it be prevented from threatening internal validity?
Definition
A regression to the mean occurs because when extreme-scoring units are selected, they will often have fewer extreme scores on other variables, which could be misconstrued as a treatment effect.  This is prevented by obtaining a large set of extreme scorers and randomly assigning them to different treatments to regression will occur equally across groups.
Term
What are some ways to increase reliability of assessment?
Definition
Use longer more reliable instruments, use multivariate function, and averaging scores over two assessment points.
Term
What is the three time method and what does it allow for?
Definition
Selection based on time 1, implementation of treatment in time 2, and final assessment in time 3.  It allows for comparisons of T2 and T3 versus T1 and T3.
Term
What is attrition, how can it be prevented from threatening internal validity, and how is it problematic?
Definition
Attrition is the loss of units after randomization has taken place which can produce effects if the loss is systematically correlated with the conditions of the experiment.  It can be prevented by using a pretest-posttest control group design.  It is problematic when those who remain differ from those who drop out and if it is due to the treatment (e.g., side effects).
Term
How can testing threaten internal validity and how can this be prevented?
Definition
Exposure to a test/items can affect scores on the exposed items (practice effects), producing an effect mirroring intervention.  To prevent this, use IRT or Solomon-4 group design.
Term
How does instrumentation threaten internal validity and how can this be prevented?
Definition
Changes in an instrument over time can mimic treatment effects.  Prevent this by calibrating instruments, especially if you switch instruments.
Term
What are the additive/interactive effects of threats to internal validity?
Definition
The impact of one threat can add to the impact of another threat, depending on severity.
Term
If you accept the null hypothesis and it is true...
Definition
You correctly failed to reject the null hypothesis.
Term
If you reject the null hypothesis and it is false...
Definition
You correctly rejected the null hypothesis, increasing power.
Term
If you accept the null hypothesis and it is false...
Definition
You incorrectly fail to reject the null hypothesis, leading to Type II error.
Term
If you reject the null hypothesis and it is true...
Definition
You incorrectly reject the null hypothesis, leading to Type I error.
Term
What is Type I error and what is the probability of it?
Definition
Type I error is concluding that the null hypothesis is false (or should be rejected) when it is actually true (and should not be rejected).  The probability of Type I error is alpha.
Term
What is Type II error and how is probability of it determined?
Definition
Type II error is concluding that the null hypothesis is true (and should not be rejected) when it is actually false (and should be rejected).  This is represented by beta and is the complement of power.  The probability of Type II error is determined by many factors, one of which is its reciprocal relationship with Type I error.
Term
How are Type I error and Type II error related?
Definition
They have a reciprocal relationship.
Term
What is raw effect size?
Definition
The raw magnitude of an effect.  In t-tests, it is the observed mean difference between groups on a measure.  In the simplest of terms, it is the difference between groups.
Term
_____ effects are more impressive than _____ effects.
Definition
Big; small.
Term
What are advantages of using a raw effect size?
Definition
Expected value is independent of sample size and it is expressed directly in terms of the units of scale of the dependent variable.
Term
What are disadvantages of using raw effect size?
Definition
With small-ish samples, you may be able to obtain an effect without being able to reject the null hypothesis, dangerous to judge effect size in isolation from p-value, investigator must be comfortable/experienced with scale of measurement.
Term
What is standardized effect size?
Definition
Effect size in standard deviation units (scale-independent), it is the raw effect size divided by the standard deviation of scores (within groups) on the response scale.
Term
What are advantages of using standardized effect size?
Definition
Independence of response scale if combining studies with different response scales (e.g., meta-analyses) - useful if you want to compare effectiveness of various/different measures/interventions and can take advantages of percentage calculations based on normal distributions.
Term
What are disadvantages of using standardized effect size?
Definition
Cannot tell us whether the null hypothesis can be rejected and depends on sample size.
Term
What is a way in which effect size can be better than a p-value?
Definition
Effect size gives us some better feel for the magnitude of treatment effects; p-value does not.
Term
Sometimes, small effect sizes are impressive when
Definition
Not much effort went into the manipulation.
Term
The magnitude of the effect can be modified by
Definition
Many variables.
Term
We find results interesting when the manipulation of the independent variable is minor and
Definition
The effect is large.
Term
What is subjective causal efficacy?
Definition
Effect size based on topic (how important it is).
Term
Methodological rigor and importance can increase
Definition
Effect size.
Term
Define power.
Definition
The probability that a significance test will lead to the rejection of the null hypothesis when the null hypothesis is indeed false.  It is the complement of Type II error (one minus beta).
Term
What are ways of increasing power?
Definition
Significance level adopted, effect size, reliability of sample data (standard error of mean differences), homogeneous groups (you want tx and control to be as different as possible!), "approaching" significance (BAD), unconventional cut-offs (also BAD).
Term
What is the formula for the standard error of mean differences?
Definition
Sxbar-ybar = √(1/n1 + 1/n22, where Sxbar-ybar is the standard error of the difference between two means and σ2 is the pooled estimate of the (assumed equal) population variances.
Term
Standard error of the mean difference has an inverse relationship with
Definition
Sample size and power.
Term
Standard error of the mean is similar to variability in that as your variability increases, your distance to the critical value (mean) ______ in order for you to have a significant effect.
Definition
Increases.
Term
What does randomization do?
Definition
(1) Reduces plausibility of alternative explanations for treatment effects, (2) Yields unbiased estimates of the average treatment effects, (3) Allows counterfactual inferences, (4) Ensures cause precedes effect, and (5) Tests for significant differences between groups.
Term
What are limitations of randomization?
Definition
(1) The only internal validity threat it controls is selection bias and (2) It doesn't prevent or control things like regression to the mean, maturation, etc.
Term
How does randomization work?
Definition
(1) Increases probability that alternative causes are not confounded with the unit's treatment condition, (2) Reduces the plausibility of threats to validity by "disturbing" them randomly across conditions, (3) Allows the researcher to know and model the selection process, (4) Allows computation of a valid estimates of the error of variance and is orthogonal to treatment, and (5) Equates groups on the expected value of all variables present at pretest (whether they're measured or not).
Term
You want groups to be the same at pretest because
Definition
You will equally distribute potential confounds between groups.
Term
What is the formula explaining how randomization works?  Explain what this formula actually means.
Definition
Yi = U + βZi + ei, with Yi being the dependent variable, U being the constant, β being the regression coefficient, Z being the independent variable, and e containing the potential confounds.  Since randomization tries to guarantee the probability that the correlation between beta and erorr is zero, this assumes that the dependent variable is equal to the constant at pretest.  This formula demonstrates exposure versus placebo.  Randomization estimates error variance (variability within group not attributable to treatment = error).
Term
What are types of controls
Definition
No treatment, dose-response, placebo, wait-list, expectancy, and deconstructed elements of total treatment.
Term
What is dose-response control?
Definition
Controls for the magnitude or salience of treatment (drug amount, number of sessions, etc.).
Term
What is placebo control?
Definition
Controls for inert aspects of intervention.
Term
What is wait-list control?
Definition
Controls for time passage.
Term
What is expectancy control?
Definition
Systematically manipulates the beliefs about treatment.
Term
What are the deconstructed elements of total treatment?
Definition
When the control is a portion of the treatment (e.g., dismantling studies), it is essential to consider what you're trying to control for (covariates, the causal agent in the intervention).
Term
Basic randomized design comparing two treatments is the alternative to ______ and it is used when...
Definition
Basic design; developing a new treatment you believe is more effective than an existing "gold standard" treatment by comparing the treatments (one of which must be established).
Term
What does no pretreatment assessment do and what are advantages/disadvantages of this design?
Definition
No pretreatment assessment compares those who drop out from different conditions and compares those who do and do not drop out.  It is used when both treatments are not established and you need a control.  Advantages to this is that it circumvents problem of sensitization and the pretest would mirror intervention.  A disadvantage to this is that it can't assess reasons for attrition.
Term
What are some characteristics of pretest/posttest control group design?
Definition
Both types of this design differ in whether testing occurs before or after assignment.  This type of design copes with attrition as a threat to internal validity and has statistical advantages.  It is the most commonly used randomized field design.  It allows you to analyze/reject the null hypothesis.  You want to make the pretest as similar as possible to the posttest (IRT is alternative to this).  Matched groups design.
Term
For alternative-treatment with pretest and multiple treatment with controls and pretest, if no group differences exist...
Definition
Examine the pretest and the posttest to see if both groups got better or if there was no change.  If there was a slight decline, it is likely that there was a regression of the mean.
Term
What does the Solomon-4 group design test for and what does it control for?
Definition
It is a very important and advantageous design that tests for the effect of maturation and history.  It controls for sensitizing effects by including groups just assessed at posttest.
Term
What are some characteristics of factorial designs?
Definition
Composed of two or more independent variables each with at least two levels, require fewer subjects, test treatment combinations easily, allow for testing of interactions or moderators, and filling all cells increases power.
Term
What is a fractional factorial design?
Definition
Not all the cells are filled because a combination doesn't make sense or is not important.  Other than that, it is very similar to a regular factorial design.
Term
What are some issues in factorial design?
Definition
Sample sizes and potential problems with needing to recruit large sample sizes and nesting versus crossed designs.
Term
What is a nested design?
Definition
Some levels of one factor are not exposed to all levels of another factor.  This may not yield unconfounded statistical tests of all main effects and interactions.  In fact, it usually won't.
Term
What is a crossed design?
Definition
Each level of a factor is exposed to all levels of other factors.  It yields unconfounded statistical tests of all main effects and interactions.
Term
We are interested in...
Definition
Interactions.
Term
SStxgroups/SStotal =
Definition
Partial eta squared.
Term
What is partial eta squared?
Definition
Effect size, the proportion of total variance attributable to the factor, partialling out other factors.
Term
Treatment implementation involves
Definition
Delivery (fidelity issues, sending the message you need to send), receipt (message understood), and adherence (desired behavior).
Term
What are ways to enhance treatment delivery (treatment fidelity)?
Definition
Use of treatment manuals (universal), (directly) train service providers (researchers), provide continuing training experiences (like supervision), and video/audiotaping and reviewing.
Term
What are ways to measure treatment delivery (treatment fidelity)?
Definition
Scoring or reviewing the video/audiotapes (independent raters of fidelity in tapes) and discuss progress at informal staff or research meetings (meet regularly).
Term
What are ways to enhance treatment receipt?
Definition
Give written handouts to participants (delivery of message in multiple ways), summarize key treatment or study elements, use repetition of message (make sure message is made clear), ask participant questions to improve information encoding (make sure delivery is credible), and use a researcher/delivery person who is attractive or seems like an expert (enhance credibility).
Term
What are ways to measure treatment receipt?
Definition
Use manipulation checks, give written tests, and monitor changes (cognitive, physiological, attitudinal, etc.) that should be observed if the treatment is effective.
Term
What are ways to enhance treatment adherence?
Definition
Make it personal (anytime you want to see someone on multiple occasions), reduce amount of time needed (make it simple), incorporate frequent reminders, make certain to recognize successes early in treatment, create homework assignments that can be done in a variety of locations, use family members and friends to encourage participant, use tape recordings or other AV aids, and raffle tickets/incentives.
Term
What are ways to measure treatment adherence?
Definition
Regularly monitor each enhancement, and use bio assays if possible (classically used in smoking cessation).
Term
What is intent to treat analysis?
Definition
A type of analysis based on the amount of treatment received and if you plan on treating all participants as if they received the full package of the experiment.  It assumes unbiased estimators if the dropouts are random.  With dropouts, it takes the last observed value during participation and carries it forward through the rest of the experiment.  This is a quasi-random design because it preserves the advantages of random assignment.
Term
What is post-assignment attrition and how can it occur?
Definition
Any loss of response from participants that occurs after participants are randomly assigned to conditions.  It may happen due to a failure to answer a single question or completely dropping out.  The participant or research may initiate the drop, but it is rarely a good idea to deliberately drop participants after assignment.
Term
Moderate to high attrition is common particularly when...
Definition
Treatment is aversive, disorder is particularly prone to high rates of relapse (e.g., substance abuse), treatment demands are high (a lot of work on participants), and the assessment demands are high or the population is highly mobile.
Term
Attrition is less often "random" and more often biased because...
Definition
People may drop out of one treatment more than another or those who drop out may differ from those who remain.
Term
The burden of proof is on the researcher to prove that attrition is which two things?
Definition
(1) Not treatment-related, and (2) Did not influence the apparent outcome.
Term
True or false: Sometimes, dropping a subject is inevitable.
Definition
True.
Term
Retention and tracking strategies to prevent post-assignment attrition involve collecting demographic information of...
Definition
Participants, relatives, collaterals, and professionals in the community with whom they have contact.
Term
Front-end demographics are used for...
Definition
Retention or comparing sample with dropouts.
Term
What is the real problem with attrition?
Definition
How to handle dropouts and/or missing data.
Term
What is a common strategy for replacing dropouts and how is this strategy effective?
Definition
Replacing dropouts with randomly selected persons drawn from the same pool, which retains power/sample size.  This strategy is only effective if attrition and replacement are random (unlikely), and both the former and replacements have the same latent characteristics (measured and unmeasured).  This is unfortunately not a very good strategy.
Term
What are some things simple descriptive statistics can tell us about attrition?
Definition
Overall attrition rate, differential attrition rates for groups, whether completers and non-completers differ on important characteristics, whether those who completed the treatment differed from those who did not, and whether those who completed placebo differed from those who did not.
Term
Prior to analyzing the data, what are some ways to look for patterns of attrition?
Definition
Whether different groups have different patterns of attrition, whether different measures have different attrition patterns, and whether subsets of respondents or sites have complete data that could be used to salvage some randomized comparisons.
Term
How can you account for attrition when estimating effects?
Definition
Impute values for missing data, bracket possible effects of attrition on effect estimates, and compute effect estimates that are adjusted for attrition without using imputed data.
Term
What are some deletion strategies for dealing with missing data? (Note: these techniques are not recommended)
Definition
Replacing dropouts with randomly selected persons drawn from the same pool, listwise deletion, pairwise deletion, and plugging in some sort of mean.
Term
What is listwise deletion?
Definition
Only analyzed subjects provide complete data.  This deletion strategy applies to any statistical analysis and does not require additional statistical tests, but this is because less information is optimally used, making standard error increase, power decrease, and generalizability decrease.
Term
What is pairwise deletion?
Definition
Excluding based on the variable (cases with missing values).  This deletion strategy is powerful, but underestimates variability.
Term
In deletion strategies, what does it mean to plug in some sort of mean?
Definition
Using the mean from elsewhere in the analysis to fill in missing data.  This is not a good strategy and should be used as a last resort; it underestimates the true variability.
Term
What are the mechanisms of missingness?
Definition
Missing completely at random, missing at random, and missing not at random.
Term
What does it mean for data to be missing completely at random?
Definition
No pattern or cause is attributable to the missing data that originates from information in the data or how it was obtained.  This produces unbiased estimators of population parameters, and is ignorable because it does not change the analyses/data/results.
Term
What does it mean for data to be missing at random?
Definition
It is missing because of something you assessed or didn't assess, but not the variable itself.  This produces biased estimates of population parameters and is not ignorable.
Term
What does it mean for data to not be missing at random?
Definition
It is missing because of what you have assessed and related to a demographic.  It produces biased estimates of population parameters and is not ignorable.
Term
What are some imputation methods that are used for missing data?
Definition
Hotdeck, multiple, dummy coding, and estimated maximum algorithm likelihood (EMA).
Term
What is hotdeck imputation?
Definition
An imputation strategy that identifies cases that are most similar to the one with missing values and randomly draws from among this group a participant value to replace the missing value.  This is used by the census bureau and is simple, maintains the level of measurement, and completes the data at the end.  However, the definition of "similar" is subjective.
Term
What is multiple imputation?
Definition
The process of replacing each missing data point with a set of m>1 plausible values to generate m complete datasets.  These datasets are then analyzed by standardized statistical software, and the results combined, to give parameter estimates and standard errors that take into account the uncertainty due to missing data values.  This is not usually used because mean substitution decreases the true variable estimate.  It gives you a mean and standard error of the mean for each missing data and means of datasets can be combined to determine an overall effect.
Term
What is dummy coding?
Definition
Substituting a constant for missing data.  This creates an estimate that provides information for analysis but is a less accurate estimate of the variability.
Term
What is EMA (estimated maximum likelihood algorithm)?
Definition
Stepwise estimated value imputed mean based on other variables in the analysis (minus the bandwidth surrounding that value).  This strategy is far superior to other strategies, but many outliers would skew the bandwidth surrouding the value.
Term
What are some things SPSS does in order to account for missing data?
Definition
It describes a pattern of missingness through univariate statistics (e.g., decreases in N mean that the data is not provided), estimating the mean, standard deviations, covariances, and correlations, or imputing values.
Term
What are some ways of estimating means, standard deviations, covariances, and correlations for missing data?
Definition
Listwise, pairwise, estimated maximization (EM) method, or regression.
Term
When estimating means, standard deviations, covariances, and correlations for missing data using a listwise approach, which types of cases are included?
Definition
Only complete cases.
Term
When estimating means, standard deviations, covariances, and correlations for missing data using a pairwise approach, what is required of the participants?
Definition
That they completed data on two variables.
Term
What is the estimated maximization (EM) method for estimating means, standard deviations, covariances, and correlations of missing data?
Definition
Condition probable of value given existing values.  Expected values are temporarily substituted (estimated), maximum likelihood estimates are computed sa if the values are plugged into the missing spots (maximization).
Term
How is regression used in estimating means, standard deviations, covariances, and correlations of missing data?
Definition
Estimated value for missing participant using random effects of the coefficient.
Term
True or false: Missingness can be ignored.
Definition
False: missingness cannot be ignored.
Term
What does SPSS's missing variable analysis do to impute missing values?
Definition
It creates a new file (when run) with missing values imputed throughout.  If done with estimated maximization, it was save the completed data.
Term
Give an example of a situation in which you may not want to impute a value.
Definition
Presence of a partner.
Term
How does purposeful missing data occur on the part of the researcher?  On the part of the participant?
Definition
Researchers may structure a survey with items like "If 'no' to #2, then skip to #6."  A participant can purposefully miss data by refusing to answer questions or blindly circling the same answer throughout without reading the question.
Term
Values can be imputed when missingness is not related to...
Definition
Any characteristics of the person and is completely at random.
Term
The causal inference from any quasi-experiment requires that...
Definition
Cause precedes effect, cause covaries with effect, and alternative explanations for the causal relationship are implausible.
Term
How do quasi-experimental designs and randomized experiments compare?
Definition
Both manipulate treatment so cause precedes effect and both assess covariance statistically.  However, randomized experiments rule out alternative explanations by distributing these alternatives across conditions, whereas quasi-experiments use alternative techniques.  Quasi-experiments do not use random assignment.
Term
What are some stragies of quasi-experiments to rule out alternative causes? (Note: none offer the elegant statistical rationale of randome assignment)
Definition
Identify and study plausible threats to internal validity, control these threats by design (and statistically by covarying out the causal agents; design is better), and coherent pattern matching (specific predictions of patterns of results unlikely to occur by chance).
Term
What are the quasi-experimental designs without control groups?
Definition
One group posttest only, one group posttest only with multiple posttests, one group pretest posttest, one group pretest-posttest design using double pretest, one group pretest-posttest design using nonequivalent dependent variable, removed treatment design, and repeated treatment design.
Term
What are advantages/disadvantages of the one group posttest only design?
Definition

Advantages: reduce plausibility of alternative explanations for treatment effects, yield unbiased estimates of the average treatment effects, and reasonable if you know a lot about the variable and the demographics of the population from which you have drawn.

Disadvantages: only internal validity threat it controls is selection bias, doesn't prevent/control things like regression to the mean, maturation, etc., and not a strong design.

Term
What are advantages/disadvantages of the one group posttest only with multiple posttests design?
Definition

Advantage: allows for pattern matching.

Disadvantages: only internal validity threat it controls is selection bias, doesn't prevent/control things like regression to the mean, maturation, etc., not a strong design, adding multiple posttests can increase Type I errors, and caveat regarding pattern matching (cannot do posttest or look at the data first).

Term
What are advantages/disadvantages of the one group pretest posttest design?
Definition

Advantage: adding the pretest provides some counterfactual information.

Disadvantages: counterfactual information is weak because of the many internal validity threats and threats to internal validity are a disadvantage (history, testing, attrition, etc.).

Term
What is an advantage to the one group pretest-posttest design using double pretest?
Definition
Reduces plausibility of maturation and regression.
Term
What occurs in a one group pretest-posttest design using nonequivalent dependent variable?
Definition
A changes with treatment and B does not, but they both measure similar constructs.
Term
What are advantages/disadvantages of the removed treatment design?
Definition

Advantages: good example of coherent pattern matching and outcome should rise/fall with presence/absence of treatment.

Disadvantages: treatment effect has to dissipate quickly and there can be some ethical issues.

Term
What are advantages/disadvantages of the repeated treatment design?
Definition

Advantages: very few threats to internal validity could explain this pattern (treatment would have to covary with introduction/removal of treatment, which is unlikely) and it is good with transient effects or unobtrusive treatment or long intervals.

Disadvantage: possible threat to internal validity - cyclical maturation (unfortunately, this type of design is easy to pair with cyclical patterns).

Term
What are the quasi-experimental designs with a control group but no pretest?
Definition
Posttest only with nonequivalent groups, posttest only design using an independent pretest sample, and posttest only using proxies for pretests.
Term
What is the posttest only with nonequivalent groups design?
Definition
A design that adds a control group to the one group posttest only design.  This is used when you're called in late.  This is used if the pretest would have a sensitizing effect.
Term
What are advantages of the posttest only design using an independent pretest sample?
Definition
It is useful when pretest measures are reactive, when it is too difficult or expensive to do a longitudinal study, or when one wishes to study intact communities whose members change over time.  It also draws its second sample from the same population as the treatment group.
Term
What are some characteristics of the posttest only design using proxies for pretests?
Definition
Variables are conceptually related to and correlated with posttest within treatments.  Preferably, these proxies should be conceptually related to the outcome, not just readily accessible measures (e.g., age, race, etc.).  Matching procedures are also used.
Term
What are the matching procedures used for the posttest only design using proxies for pretests?
Definition
Exact (same score, twin, etc.), caliper (matched person falls within bandwidth of other persons selected), index, and benchmark (examples of propensity matching, select controls close to treatment group based on multivariate distance).
Term
What are the quasi-experimental designs with a control group and pretest?
Definition
Untreated control group with dependent pretest and posttest samples, untreated control group with dependent pretest and posttest using double pretest, untreated control group with dependent pretest and posttest using switching replications, untreated control group with dependent pretest and posttest using reversed treatment control group, and cohort designs.
Term
What are some characteristics of the untreated control group with dependent pretest and posttest samples design (also called nonequivalent comparison group design)?
Definition
Pretest/comparison group examine threats to validity easier.  Groups are nonequivalent by definition and selection bias is assumed present.  Pretest - magnitude assessment, selection bias direction, attrition, no pretest - doesn't mean selection bias is not present.  When pretest differences, selection may be combined with other threats.
Term
What are some graphical representations of the untreated control group with dependent pretest and posttest sample design?
Definition
Both groups grow apart in the same direction, no changes in control group, initial pretest differences favoring treatment group diminish over time, and outcomes cross over in the direction of relationships.
Term
What are some characteristics of the untreated control group with dependent pretest and posttest samples design when both groups grow apart in the same direction (fan-spread interaction)?
Definition
If group mean differences are a result of the selection-maturation threat, then differential growht between groups should be occurring within groups.  Test this by a series of within-group analyses.  Selection maturation threat is associated with posttest within-group variances that are greater than the corresponding greatest variances.  Plot pretest scores against hypothesized maturational variable for the experimental and control groups separately.  If regression lines differ, differential growth rates are likely.
Term
What are some of the characteristics of the untreated control group wtih dependent pretest and posttest samples design when there are no changes in the control group?
Definition
The critic must explain why spontaneous growth occurred only in the treatment group and sometimes, within-group analyses can shed light on such between-group threats.  For example, treatment group matured faster because they were older, in the treatment group, divided people based on age.
Term
What are some characteristics of the untreated control group with dependent pretest and posttest samples design when initial pretest differences favoring the treatment group diminish over time?
Definition
This is a characteristic pattern hypothesized in compensatory programs.  Outcome is subject to typical scaling (selection-instrumentation) and history (selection-history) threats.  It is important when you have this type of finding to thoroughly investigate the reasons for the initial differences.
Term
What are some characteristics of the untreated control group with dependent pretest and posttest samples design when outcomes cross over in the direction of relationships?
Definition
The pattern is particularly amenable to causal interpretations.  The plausibility of selection-maturation is reduced becuase it is the best interaction to have.  Selection-maturation threats are less likely because crossover interaction maturation patterns are not widely expected.  The outcome renders a regression threat is less likely.  The caveat to this is the power to detect a statistically reliable interaction is low.
Term
What are the characteristics of the untreated control group with dependent pretest and posttest using double pretest design?
Definition
The double pretest allows the researcher to understand possible biases in the main treatment analysis and permits assessment of selection-maturation threat on the assumption that rates between O1 and O2 will continue between O2 and O3.  This assumption is only testable for the untreated group.  It also allows for an analysis of regression effects.  However, within-group rates will be fallibly estimated (measurement error) and instrumentation shifts could make measured growth between O1 and O2 unlike that between O2 and O3.
Term
What are the characteristics of the untreated control group with dependent pretest and posttest using switching replications design?
Definition
Strong design but 2nd phase is not exact replication both historically and because treatment was removed from the 1st group - second introduction of the treatment is best be thought of as a modified replication that probes the internal and external validity of whether this new context changes the treatment effect.  Only a pattern of change that mimics the sequence of treatment introductions can serve as an alternative interpretation.  This design makes very clear predictions about treatment effects.
Term
What are characteristics of the untreated control group with dependent pretest and posttest using reversed treatment-control group design?
Definition
X+ represents treatment expected to produce an effect in one direction and X- represents a conceptually opposite treatment effect.  This design has special construct validity advantages.
Term
What are the cohort designs?
Definition
Cohort control group design and cohort control group design with pretest from each group.
Term
What is a cohort?
Definition
Successive groups that go through a process.
Term
What are characteristics of cohort designs?
Definition
A critical assumption with cohorts is that selection differences are smaller between cohorts than would be the case between non-cohort comparison groups.
Term
When are cohorts useful as control groups?
Definition
One cohort experiences a given treatment and earlier or later cohorts do not, cohorts differ in only minor ways from their contiguous cohorts (IMPORTANT), organizations insist that a treatment be given to everybody, thus precluding simultaneous controls making possible only historical controls, an organization's archival records can be used for constructing and comparing cohorts, and it is important to assume that cohorts together are fairly similar.
Term
How do cohort control group design and cohort control group design with pretest from each group compare?
Definition
Both are examples of cohort control group designs and history is a threat in both designs.  In cohort control group design with pretest from each group, there is a math advantage allowing for better assessment of maturation and regression.  Also, this design measures proxies for pretests and these variables are conceptually related to and correlated with the posttest within treatments.
Term
What are the types of quasi-experiments?
Definition
Quasi-experiments with no control groups, quasi-experiments with no pretest, and quasi-experiments with both controls and pretests.
Term
What are the contrasts that can be done if you do not have a control group?
Definition
Regression extrapolation contrasts, normed comparisons contrasts, and secondary source contrasts.
Term
What are characteristics of regression extrapolation contrasts?
Definition
Compare obtained posttest scores of tx group with the score that would've been predicted based on other information.  Assumes reliable estimates of true scores.  W/O full knowledge of threats to validity, predicted scores rarely yield valid counterfactual inferences.  Depends on stable estimates estimation using reliable measures and large samples.  Only worth doing when no other control group is possible or adjunct another procedure.
Term
What are characteristics of normed comparison contrasts?
Definition
Performance of the treatment group at pretest and posttest is compared with available published norms that shed light on counterfactual inferences.  Normed contrast provides weak counterfactual information and the comparison is also threated by selection, history, testing, regression, and maturation.  Sometimes, you can resolve some of these concerns by using "local" normative samples.
Term
What are characteristics of secondary source contrasts?
Definition
Construct opportunistic contrasts using secondary sources, such as records of cases treated prior to the advent of the new treatment.  The use of such archival or history data is challenging practically and some of the same conceptual issues that are problematic of normative contrasts apply here.  It is the most common contrast and easy to examine threats of validity.  There is no random assignment, so there is a selection bias.  Look for attrition reason in pretest.
Term
In a general sense, what are ethics?
Definition
What is best for the individual and society.
Term
True or false: ethics can be situational or universal.
Definition
True.
Term
A common question regarding ethics may be is what is right or wrong a function of...
Definition
The end product.
Term
What are the three types of ethics commonly identified?
Definition
Metaethics, normative ethics, and applied ethics.
Term
What are some characteristics of metaethics and common questions it considers?
Definition
What does ethical mean?  Does it exist?  Do ethics represent universal truths?  Moral absolute - religious code (morals are not equivalent to ethics).  The big questions, existential and epidemiological concerns.  Immoral contradiction of principles and moral attitudes, ethical codes.
Term
What is an ethical code?
Definition
A universal set of rules adhered to by a professional group.  These do not recognize metaphysical entity.
Term
What are characteristics of normative ethics?
Definition
Bridge the gap between metaethics and applied ethics.  Practical moral standard, theory of conduct, and theory of value.
Term
What are practical moral standards?
Definition
Arrive at moral standards telling us right from wrong and how to live life (basically, normative ethics).
Term
What is theory of conduct?
Definition
Knowing the difference between right and wrong and what our obligations are.
Term
What is theory of value?
Definition
Determine if there is value in anything, including our decisions - intrinsically good.
Term
What are characteristics of applied ethics?
Definition
Ethics specifically applied, like normative ethics applied to controversial issues.
Term
What role did the Nazi doctors play in the development of the 20th century ethical codes?
Definition
The behavior of Nazi doctors and the wide range of appalling experiments done in the name of medical science (e.g., high altitude experiments, incendiary bomb experiments, experiments in freezing water, and experiments on women and children) began the development of ethical codes.
Term
What happened in Nuremberg?
Definition
23 Nazi doctors were tried for murders and crimes.  16 were found guilty and 7 were sentenced to death.
Term
What does the Nuremberg Code (1947) state regarding ethical practices that laid the groundwork for our ethical guidelines?
Definition
Participants must have the legal capacity to give consent, exercise free power of choice, no element of force, nature/duration/purpose of the experiment should be known, all inconveniences and hazards should be explained, duty/responsibility for disclosing information rests on the person initiating research, your experiment should yield results that are good for society that cannot be obtained another way, and risk has to be justified.
Term
Some examples of unethical studies?
Definition
Tuskegee Syphilis study, Milgram study, Belmont Report.
Term
What are the three basic principles of the Belmont Report?
Definition
Respect for persons, beneficence, and justice.
Term
According to Bersoff (1994), what are some recruitment issues that may exist and some things IRB focuses on with regard to issues in research design?
Definition
Recruitment issues include hyperclaiming and causism.  IRB may ask the question, "If no fruits are produced, how can the means be greater than the end?"
Term
What are some institutional safeguards IRB considers in the Policy for Protection of Human Subjects (U.S. Department of Health and Human Services)?
Definition
Required, diversity, scientific/nonscientific base, independence.
Term
What is the criteria for IRB approval?
Definition
Risks to subjects minimized/reasonable, equitable selection of subjects, informed consent/appropriate documentation, data monitoring, and privacy of subjects.
Term
What are the requirements for informed consent?
Definition
Statement of purpose/explanation, description of procedures, forseeable risks, benefits, alternative procedures, statement of confidentiality, compensation if more than minimal risk, voluntary refusal, and contact person.
Term
What are some issues surrounding informed consent?
Definition
What exactly is "informed" consent?  Drug trials imply knowledge of placebo condition for informed consent.  The irony of providing too much detail can elicit paranoid ideation or become too difficult for a participant to read.
Term
Research involving more than minimal risk is approved contingent upon...
Definition
Anticipated benefit (absolute benefit and relative to alternative treatments) and generalizability of benefit.
Term
What are some critiques of IRBs?
Definition
Wield a lot of power, overly cautious/conservative (trade-off of scientific advances for excessive ethical concerns), appropriate role (humane treatment of subjects versus watchdog of methodology), politics and research (sociopolitical implications), and APA's lack of enforcement.
Term
Key rational for animal research?
Definition
CARE policy statement (APA's Committee on Animal Research and Ethics): animal research advances animal and human welfare.  Psychologists do research to learn more about behavior and how knowledge of behavior can be used to advance the welfare of people and animals.  Identification of characteristics unique to different species has yielded information that contributes to understanding and advancing the welfare of animals and people.
Term
How has animal research contributed significantly to our knowledge of behavior?
Definition
Knowledge of beasic learning processes/motivational systems (hunger, thirst, reproduction).  Critical info about sensory processes (vision, taste, hearing, pain perception).  Connections between stress and disease.  Suggested psychological interventions for coping with stress more effectively.  Understanding of drug abuse/physical dependence.  Critical to efforts to develop effective pharmacologic treatments for drug dependence and cognitive deficits of aging/Alzheimer's disease.
Term
How has animal research helped to explain the central nervous system?
Definition
Experiences in the world shape behavior, understanding how nervous system works critical to complete understanding of behavior, including behaviors problematic in mental illness, memory disorders, drug addictions.  Process of recovery after neural damage: (1) Biological correlates of fear, anxiety, and other forms of stress, (2) Subjective and dependence-producing effects of psychotropic drugs, and (3) Mechanisms that control eating and other motivational processes.
Term
What are some human subject projects and alternatives to live subjects that have been proposed?
Definition
Use of plants/tissue cultures or computer simulations (lack central nervous systems).  All who do research with animals are required, legally and ethically, to consider the possibility of using alternatives to nonhuman animals (e.g., observing animals in natural environment - psychologists observe/study animals in natural environments; for many investigations, the lab is only setting in which causal variables can be isolated with sufficient precision to generate meaningful conclusions.
Term
How do animals in psychology research vary?
Definition
7-8% og psychology research involves the use of animals.  90% of animals used have been rodents and birds, primarily rats, mice, and pigeons.  5% of the animals are monkeys and other primates.  Use of dogs or cats is rare.
Term
What are some things that are done to be sure that humane care and use of animals in research is ensured?
Definition
Many safeguards exist to assure that laboratory animals receive humane and ethical treatment.  Care and use of animals in research are regulated and monitored by various government agencies.  Institutions in which research with animals is conducted have federally mandated review committees.
Term
What are some federal regulations and guidelines that exist for using animals in research?
Definition
Animal Welfare Act (most recently amended, 1985) governs the care and use of many research animals.  The U.S. Department of Agriculture is responsible for enforcing the act and conducting periodic unannounced inspections of animal research facilities, both public and private.  Institutions that conduct research using animals covered by the act are required to have an Institutional Animal Care and Use Committee (IACUC) to review each research protocol.
Term
How does the scientific community set standards with regards to the use of animals in research?
Definition
The American Association for the Accreditation of Laboratory Animal Care (AAALAC) is nationally and internationally recognized for its institutional accreditation program.  It sets the "gold standard" for laboratory animal care and serves as a guide for those research facilities seeking to assure the best conditions for their research animals.  Once accreditation is obtained, thorough inspections are conducted every 3 years to determine whether an institution may retain its accreditation.
Term
What are the APA ethics code and other guidelines that cover treatment of research animals?
Definition
APA Ethical Principles of Psychologists/Code of Conduct includes principles for humane/ethical treatment of research animals.  APA members are committed to uphold principles.  Failure to do so can lead to expulsion from association.  APA's Guidelines for Ethical Conduct in the Care and Use of Animals sets comprehensive standards for psychologists using animals in research.  Those who publish in APA journals are required to conduct research with animals in accordance with guidelines.
Term
What are some key principles of the new APA guidelines (2003) for animal research?
Definition
Acquire/care for/use/dispose of animals in compliance w/federal/state/local laws/regulations w/professional standards.  Ensure those under supervision using animals received instruction in research methods and in care/maintenance/handling of species, to extent appropriate to role.  Reasonable efforts to minimize discomfort/infection/illness/pain of animals.  Use procedure subjecting animals to pain/stress/privation only when alternative unavailable and goal is justified by prospective scientific/educational/applied value.  Perform surgery under appropriate anesthesia/follow techniques to avoid infection/minimize pain during/after.  Proceed rapidly when appropriate that an animal's life be ended, w/effort to minimize pain in accordance with procedures.
Term
What was the Tuskegee Syphilis study and what role did it play in research ethics?
Definition
Longitudinal study (1932-72) of syphilis.  Tx for syphilis available in 1947 but researchers never told participants they had syphilis nor did they tx them for it.  Participants given pink aspirin.  No informed consent.  Participants uneducated/illiterate.  399 black participants, 28 died of syphilis, 100 died of other complications, 40 women infected by participants, and 19 children born with syphilis.  Led to regulations of research ethics being enforced and development of Belmont Report.
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