# Shared Flashcard Set

biostats
test III
66
Health Care
Professional
04/10/2008

## Additional Health Care Flashcards

Term
 If a null hypothesis is true, but you reject it, you have made what type of error?
Definition
 type I
Term
 If a null hypothesis is not true, and you do not reject it, then you have made what type of error?
Definition
 type II
Term
 As alpha goes up, beta goes         ?
Definition
 down
Term
 As beta goes up, power goes       ?
Definition
 down; Remember that power is 1 - beta
Term
 As alpha goes up, power goes        ?
Definition
 up
Term
 Choose: anova F-tests are always/sometimes one sided/two sided for determining a p-value.
Definition
 always; one-sided
Term
 What are the 5 assumptions for calculating ANOVA?
Definition
 Random samples-are required to be unbiased Indepedent samples If they're dependent (or repeated), you have to use repeated measures ANOVA.Independent observations w/in groups Normal distribution - (aka normal population)Equal variances (homogeneity)
Term
 When calculating ANOVA, if you have unequal variances, you have to                  the data.  Name three ways that you would do this to your data.
Definition
 transform; log, natural log, square root
Term
 is the sum of squares (SS) What is SSB? What are other names for SSB? What is SSW? What are other names for SSW? Choose: The signal/noise should be > than the signal/noise, otherwise, we won't be able to detect the signal/noise.
Definition
 Variance; It is the variance b/w groups (it is the difference of each mean from the overall mean); SS(treatment) or SS(effects) or signal; It is the variance w/in groups; SS(error) or noise. signal-noise-signal
Term
 What is the MSB?
Definition
 It is the mean square b/w groups
Term
 SSB = 43.21SSW = 50.68T or F: the error is greater than the treatmentWhy or why not?
Definition
 False, b/c you still have to divide by the df. The SSB will have a much smaller df (eg, 2) than the SSW (eg, 39). After dividing the SSB and SSW by their respective df's, you get MSB = 21.61 and MSW = 1.30.
Term
 If a comparison is not planned ahead of time, you must use                even if only one post-hoc comparison was performed. However, you usually perform all comparisons.
Definition
 multiple comparisons
Term
 If comparisons are selected a priori, what does c =?If comparisons are selected post hoc, what does c =?
Definition
 a priori: c = number of comparisons to be madepost hoc: c = total number of possible comparisons
Term
 What is the point of the Bonferroni method?
Definition
 It's like an adjusted alpha, labeled alpha'. It increases the CL for each CI in order to ensure a specific overall CL.  Table 11.4 shows how conservative the bonferroni method is.
Term
 When should you use bonferroni? When should you use tukey?
Definition
 The bonferroni method should be used when comparisons are selected a priori.The Tukey method should be used when ALL comparisons are selected - it doesn't matter if they're selected a priori or post hoc.If comparisons are selected post hoc, use the Tukey method.
Term
 The same three factors that affect statistical outcomes affect ANOVA results. What are they?
Definition
 Treatment effects (differences b/w means)Variance (SSB compared to SSW)# of subjects
Term
 What are the 4 assumptions of the regression model?
Definition
 NICL Normal distributionIndependence (y observations are independent of each other)Constancy of variance (the sd of y is constant for each x)Linear relationship (as opposed to exponential, curvilinear, etc)
Term
 What is residual analysis used to test?
Definition
 The assumptions of linear regression.
Term
 Correlation analysis uses pearson, r. What are the 3 assumptions of pearson?
Definition
 1) Both the ind & dep variables must b continuous.2) Dependent variable must be rational3)No multicollinearity (meaning ind variables cant be related to other ind variables)
Term
 What are the assumptions of B?
Definition
 1) Each y observation is independent2) All potential y values are normally distributed for each x value3) The std deviation of y is constant for each x4) The sampling distribution of b is normal
Term
 What are the 4 assumptions for r?
Definition
 1) Each y observation is independent2) The sampling distribution of both x and y are normal.3) The std deviation of y is constant for each x4) The sampling distribution of r is normal.
Term
 If all population means are              , the sample means will be very close to each other and close to the                 . The weighted square differences will be               , and a                    F will be calculated.
Definition
 equal; grand mean; small; small
Term
 ANOVA T or F: Variance cannot be negative
Definition
 True. If it is, there is too much error.
Term
 If some population means are quite different, corresponding sample means will be                than each other and the               . Corresponding weighted squares will be                 , the                and                will be small, and the F will be               .
Definition
 quite different; grand mean; large; SSB; MSB; large
Term
 As alpha increases, Fcrit               .
Definition
 decreases
Term
 When is one-way ANOVA used?
Definition
 When you need to compare more than two means. More specifically, when you have one factor w/ more than two levels of the factor (ie, Drug A, Drug B, and DrugC).
Term
 What is error slippage?
Definition
 Error slippage occurs when you try to do a bunch of t-tests when you really should have done ANOVA.  You'll think you have significant differences, but you really don't, b/c the alpha is slipping from 0.5 to 1.
Term
 Explain what X32 means.
Definition
 It means group 3, observation 2.
Term
 If you had two or more independent variables, what type of ANOVA would you use?
Definition
 Factorial ANOVA. The different factors may be Drugs A, B, & C (1st factor), Age (second factor), & gender (third factor).
Term
 When would you use one-way ANOVA? Name a requirement of ANOVA.
Definition
 Use one-way ANOVA when you have one factor and more than two levels. The samples in the different levels must be independent of each other.
Term
 When do you use post-hoc analysis?
Definition
 When the null has been rejected and you're trying to find out which mean(s) are different.
Term
 When do you use repeated measures ANOVA?
Definition
 If measures are dependent (or repeated), you use a crossover design called repeated measures ANOVA.
Term
 What is the proper term used when your putting variances into groups? What is another name for variance?
Definition
 Partitioning  Sums of Squares
Term
 SSB & SSW are weighted by the                 .
Definition
 Sample size
Term
 Choose: When p-Value is greater/lesser than or equal to alpha, H0 cannot be rejected.
Definition
 greater
Term
 Which is worse: a type I or type II error?
Definition
 type I
Term
 A type I error is aka               A type II error is aka
Definition
 alphabeta
Term
 Define alpha  What does it mean when we set out alpha to 0.05?
Definition
 It is the probability that a difference does not exist when the study shows that a difference does exist.  If a study was repeated 100 times, we would be willing to be wrong 5 times. We would conclude 5 times that a difference exists when in fact it does not.
Term
 T or F:A rejection region will be larger for a one-tail alpha than a two-tail alpha
Definition
 true
Term
 Define beta
Definition
 It is the percent chance that a difference b/w experimental grps does exist even though the study concludes no difference.
Term
 T or F:We usually look at beta after an experiment, to find out why we DIDN'T reject the null. Beta is usually set at the beginning of an experiment. Where should it be set, and why do we set it?
Definition
 True  Beta should be less than or equal to 0.2.  We set beta, b/c we want a certain power (at least 80% or 0.80). Notice that this isn't as strict as alpha. Remember, that we are more willing to be wrong on a type II than a type I error.
Term
 What are 3 reasons for a type II error? Which is the most common?
Definition
 Better response rate in the comparator grp Increased varianceToo few subjects (most common)
Term
 If type I & type II error are inversely related, how can we reduce the chance of a type I error w/o increasing the type II error?
Definition
 Increase the sample size
Term
 What is power?   How do you calculate power?
Definition
 It is the percent chance that if a difference b/w grps exists that your study will detect it statistically.  power = 1 - beta
Term
 Name the 3 factors that affect power
Definition
 Size of treatment effect, alpha, and variability.
Term
 The size of treatment is aka
Definition
 effect size
Term
 Power is affected by the "effect size". If there is a large effect, the difference is easy/difficult  to detect and power is high/low.
Definition
 easy; high
Term
 Power is affected by the effect size. If there is a small effect, the difference will be easy/difficult to detect, type II error will be higher/lower, and power will be higher/lower.
Definition
 difficult; higher; lower
Term
 A larger variance will result in a lower/higher power
Definition
 lower
Term
 Why is it that an increased sample size increases power?
Definition
 Because it increases df, and it controls variance (ie, SEM goes down, b/c SEM = s / sq root of n)
Term
 Why should power (and beta) be calculated a priori ?
Definition
 To determine the sample size needed for a study.
Term
 When does power not have to be calculated?
Definition
 When there is a significant difference.
Term
 T or F:Statistical significance does not equal clinical significance
Definition
 true
Term
 When do you have to do post-hoc analysis?
Definition
 If the null is rejected, you have to do post-hoc analysis. Otoh, if the null accepted, the analysis is complete, b/c the variances are equal.
Term
 What is linear regression?
Definition
 To test for associations b/w variables. If independent values are given, we can use linear regression to predict the dependent variable.
Term
 Why is the simple regression equation different from the sample regression equation?
Definition
 B/c simple regression deals w/ population, which means error is included in the equation. Error is not included in the sample linear regression equation.
Term
 Least squares regression is often used to calculate linear regression.  What is the least squares regression line used for?
Definition
 it sums the squared distance of the actual values to make them as close to what is predicted as possible.
Term
 If you see the least squares line equation, y = 560 + 0.14X, what does it mean?
Definition
 A 0.14 change in x will bring about a 1 unit change in Y.
Term
 What is a residual?
Definition
 It's the difference between the actual y-value and the estimated y-value.
Term
 What is a residual analysis used for?
Definition
 To test the assumptions of linear regression. It basically diagnoses problems w/ a model.
Term
 If you got a curve shaped residual scatter plot, would this be good or bad? Why?
Definition
 This would be bad. It would reveal that our data is not linear. We would have to transform the data.
Term
 What are the 2 problems w/ the funnel shaped residual scatter plot?
Definition
 1) The funnel reveals a problem w/ independence.2) There is a constancy of variance. We have heteroscedasticity when we want homoscedasticity.
Term
 Why is the coefficient of determination important?  The closer r2 is to           , the better the regression model.
Definition
 It reveals how much variation is explained by the regression line.
Term
 What is the difference b/w the coefficient of determination and the correlation coefficient?
Definition
 The coefficient of determination is the variance accounted for by a whole model. It includes the y-variables, whereas the correlation coefficient doesn't. The correlation coefficient lets you know if 2 variables are associated.  The correlation coefficient b/w dependent and independent variables will generally be less than the coefficient of determination, b/c the model, which has y-variables will account for more variance.
Term
 What is multiple linear regression and what makes it different than correlation?
Definition
 It's used when you want to fit multiple independent variables to one dependent variable.  Fe, the dependent variable is a students fall semester GPA. The independent variables could be GPA, ACT, ethnicity, gender, age, etc.  It's different than a correlation, b/c it has predictive abilities. Fe, it can predict a dependent variable from one or more independent variables.
Term
 Statistical significance is best evaluated w/                  . Clinical significance is best evaluated w/                  .
Definition
 correlation coefficient (r)  coefficient of determination (r2)
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