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Ped Rheum Boards

Important Statistical Tests

Suitable for binary data in unpaired samples: The 2 × 2 table is used to compare treatment effects or the frequencies of side effects in two treatment groups Fisher's exact test
Similar to Fisher’s exact test (albeit less precise). Can also compare more than two groups or more than two categories of the outcome variable. Preconditions: sample size ca. >60; expected number in each field 5 chi-square test
Preconditions similar to those for Fisher’s exact test, but for paired samples McNemar test
Test for continuous data. Investigates whether the expected values for two groups are the same, assuming that the data are normally distributed. The test can be used for paired or unpaired groups student's t-test
Test preconditions as for the unpaired t-test, for comparison of more than two groups. The methods of analysis of variance are also used to compare more than two paired groups analysis of variance
Test for ordinal or continuous data. In contrast to Student’s t-test, does not require the data to be normally distributed. This test too can be used for paired or unpaired data Wilcoxon rank test
Test preconditions as for the unpaired Wilcoxon rank sum test for comparing more than two groups Kruskall-Wallis test
Comparison of more than two paired samples, at least ordinal scaled data Friedman test
Test of survival time analysis to compare two or more independent groups log rank test
Tests whether two continuous normally distributed variables exhibit linear correlation Pearson correlation test
Tests whether there is a monotonous relationship between two continuous, or at least ordinal, variables Spearman correlation test
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