Power Analysis for One and Two Groups
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Questions and Answers

What is the power of a statistical test when the probability of Type II error is 20%?

  • 90%
  • 70%
  • 80% (correct)
  • 60%

    • What is the primary purpose of power analysis?

  • To determine the alpha level of a study
  • To determine the effect size of a study
  • To determine the type of statistical test to use
  • To determine the sample size required for a study (correct)

    • What is the minimal clinically important difference (MCID)?

  • The smallest statistically significant difference
  • The smallest meaningful change perceived by patients (correct)
  • The largest clinically significant difference
  • The average difference between groups

    • What is the purpose of a pilot study in power analysis?

    <p>To obtain estimates of the effect size</p> Signup and view all the answers

    What is the relationship between alpha and Type I error?

    <p>Alpha is the probability of Type I error</p> Signup and view all the answers

    What is the purpose of power analysis in a study?

    <p>To determine the required sample size for a study</p> Signup and view all the answers

    What is the effect size in power analysis?

    <p>A measure of the difference between groups</p> Signup and view all the answers

    How many types of power analysis are there?

    <p>4</p> Signup and view all the answers

    What is a necessary step to take before choosing a statistical test for quantitative data?

    <p>Checking for normality</p> Signup and view all the answers

    What is the primary purpose of a one-sample t-test?

    <p>To compare the mean of a sample to a standard value</p> Signup and view all the answers

    Which of the following designs is an example of a paired design?

    <p>Split-mouth design</p> Signup and view all the answers

    What is the primary distinction between a paired t-test and a Wilcoxon signed-rank test?

    <p>The assumption of normality</p> Signup and view all the answers

    Which statistical test is used to compare the means of more than two groups?

    <p>One-way ANOVA</p> Signup and view all the answers

    What is the purpose of checking for homogeneity of variances among groups?

    <p>To meet the assumption of equal variances for certain statistical tests</p> Signup and view all the answers

    Which statistical test is used to compare the means of two independent groups?

    <p>Independent t-test</p> Signup and view all the answers

    What is the purpose of a Mann-Whitney U test?

    <p>To compare the distributions of two independent groups</p> Signup and view all the answers

    Study Notes

    Power Analysis

    • Power analysis involves four parameters: alpha (α), power, sample size (n), and effect size (ES).
    • Alpha (α) is typically set to 0.05.
    • Power is equal to 100% - Beta (β), and is often set to 80% (100 - 20).

    Types of Power Analysis

    • There are four types of power analysis: a priori, post-hoc, criterion, and sensitivity.
    • A priori analysis computes the sample size (n) given alpha, power, and effect size (ES).
    • Post-hoc analysis computes the power given alpha, sample size (n), and effect size (ES).
    • Criterion analysis computes alpha given power, effect size (ES), and sample size (n).
    • Sensitivity analysis computes the effect size (ES) given alpha, power, and sample size (n).

    Effect Size

    • Effect size quantifies the differences between groups.
    • Minimal clinically important difference (MCID) is the smallest meaningful change or the smallest difference in score that patients perceive as beneficial.

    Obtaining Effect Size

    • Effect size can be obtained through pilot study results, published findings, field-defined meaningful effects, or expert opinion.

    Tests for Quantitative Data

    • Before choosing a statistical test, check for normality and homogeneity of variances among groups.
    • Tests for quantitative data include:
      • One-sample t-test (compares with a standard value)
      • Paired t-test (parametric, compares before and after values)
      • Wilcoxon signed-rank test (non-parametric, compares before and after values)
      • Independent t-test (parametric, compares two groups)
      • Mann-Whitney U test (non-parametric, compares two groups)
      • One-way ANOVA (parametric, compares more than two groups)
      • Kruskal-Wallis test (non-parametric, compares more than two groups)

    Designs for Quantitative Data

    • Paired designs include split-mouth design and matched pairs.

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    Description

    This quiz covers the basics of power analysis, statistical tests for one and two group comparisons, and their applications in biostatistics and healthcare quality management.

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