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EBM - Week 3
Introduction to Basic Statistical Concepts, Hypothesis Testing, etc.
4
Medical
Professional
09/09/2010

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What are the steps to hypothesis testing?

Definition
  1. State the research hypothesis
    1. Null hypothesis: H01 = μ2
    2. Alternative hypothesis: H1: μ1 ≠ μ2
  2. Decide on the appropriate statistical test.
    1. Depending on the type of measurement (nominal, ordinal, or continuous), will determine the type of test (chi-squared, Mann-Whitney or Wilcoxon, t-test, ANOVA)
  3. Select the level of significance for the statistical test.
    1. Type I error (false positive) - Incorrectly reject H0 when indeed it is true.
      1. How to avoid: (1) conduct appropriate test, and (2) select p value.
    2. Type II error (false negative) - Failure to reject H0 when indeed it is not true.
      1. How to avoid: increase power, by increasing sample size.
  4. Perform the calculation
  5. Draw and (re)state the conclusion.
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3 Search Strategies for Pubmed

Definition
  1. Single best search term
    1. Therapy (Randomized Controlled Trial) - Clinical trial [publication type]
    2. Diagnosis (Cross-Sectional Study) - Sensitivity [text word]
    3. Prognosis (Cohort Study) - Cohort Studies
    4. Etiology (Cohort Study or Cross-sectional) - Risk [text word]
  2. Using "clinical queries" and search with "Clinical Study Categories"
  3. Using limits and going to "Type of Article" and clicking on "Clinical Trial"
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What is a Type I error and how to avoid?

Definition
  1. Type I error (false positive) - Incorrectly reject H0 when indeed it is true. (Positive because you concluded p < .05, when indeed no difference exists)
    1. How to avoid: (1) conduct appropriate test, and (2) select p value. (3) Conduct a Intetntion-to-treat analysis, which answers: who should I give therapy? (as opp. to efficacy of the treatment in PPA).
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What is a Type II error and how to avoid?

 

 

 

 

 

 

Definition

 

  1. Type II error (false negative) - Failure to reject H0 when indeed it is not true. (Negative because you concluded p > .05, but indeed a difference exists).
    1. How to avoid: increase power, by increasing sample size.
      1. Increase power by conducting a per protocol analysis, which includes only patients who adhered to the protocol, e.g. the treatment. Excludes those who did not adhere, or died. Answers: how effective was the treatment? (once given, as opp. to who should I give in ITT).
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