Exact(4)
χ Test was used for testing proportions in categorical variables.
This will provide an 80% power at the 95% significance level to see an absolute difference of 12% in testing proportions between the two arms.
For several measures, including A1C, LDL cholesterol, and microalbuminuria testing, proportions are approaching 90%, at least in commercial health maintenance organizations and Veterans Administration populations.
Legler et al. added to our understanding of the role of PSA testing on prostate cancer incidence rates by showing that first time PSA testing proportions, not the overall PSA proportion, track closely with prostate cancer incidence rates [ 20].
Similar(56)
Chi-square analyses will be used to test proportions.
Continuous variables compared using t tests; proportions compared using chi-squared tests.
*p <.001; p-values are based on Chi-square tests (proportions) and ANOVAS (means).
* P<0.05 Medication users compared to non-users, χ2 test (proportions), Mann Whitney U test (non-parametric), independent sample t-test (parametric).
We compared continuous variables with the Wilcoxon test, proportions with Fisher's exact test, and rates with exact methods.
Continuous variables were tested using the nonparametric Wilcoxon test, proportions were tested using the Fisher's exact test, and survival was tested using the Log-Rank test.
Continuous repeated measurements were compared using the t-test, Wilcoxon test, or Friedman test; proportions were compared using the McNemar test or Cochran test.
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