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Understanding Measures of Reliability and Multivariate Analysis

Explore kappa statistic calculation, reliability measures, and multivariate analysis objectives with examples and statistical methods for hypothesis testing. Learn about prevalence impact on Kappa scores and association analyses in research.

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Understanding Measures of Reliability and Multivariate Analysis

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  1. Measures of Reliabilityand Multivariate Analysis

  2. Objectives • To discuss measures of reliability • To discuss multivariate analysis

  3. Kappa Statistic • po = observed probability of concordance between the two surveys • pe = expected probability of concordance between the two surveys • The standard error of the Kappa statistic is calculated by: • To test the hypothesis Ho:k=0 vs. H1:k>0, use the test statistic:

  4. Percent agreement

  5. Figure 1. Association of average faculty performance rating (from 1, bottom 20%, to 5, top 20%) and absolute rank on the National Resident Matching Program (NRMP) list (r = 0.19; P =.11).

  6. Table 1. Discrepancy Between the DIS and SCAN for the Lifetime Occurrence of Depressive Disorder in the Baltimore ECA Follow-up*

  7. Table 1-Comparison of WHO and ADA diagnostic categories for undiagnosed diabetes From:   Lee: Diabetes Care, Volume 23(2).February 2000.181-186

  8. Kappa score calculation

  9. Kappa and prevalence • You have two populations of 1000 each being compared by interview A and interviewer B • One has a prevalence of 5 and the other has a prevalence of 40 • Sensitivities and specificities for observer A and B are .90 and .90 and .80 and .95 respectively • Create a table for each population

  10. Prevalence and Kappa • Kappa tends toward 0 as the prevalence approaches either 0 or 1 • High values of kappa can be obtained when the marginals of the contingency table are unbalanced. (tends to be higher when the positivity prevalence is different between A and B

  11. Kappa scores for table 8-18

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