Compare repeated measures variables

krajcsi edited this page Jun 7, 2018 · 1 revision

From the Analysis menu choose Compare repeated measures variables, and choose the variables you want to compare, then hit OK.

  • Only the cases where all variables are available are used.
  • Variables to be compared have to have the same measurement levels.

The following results will be calculated (see also the common elements of the results):

Raw data

Result For interval variables For ordinal variables For nominal variables
Sample size Number of valid cases Number of valid cases Number of valid cases
Raw data Plot with individual data Plot with individual data Mosaic plot

For individual data plots values of a single case are connected.

Sample properties

Result For interval variables For ordinal variables For nominal variables
Descriptive data (Most of them new in v1.7) Means, Standard deviations, Maximums, Upper quartiles, Medians, Lower quartiles, Minimums (Most of them new in v1.7) Maximums, Upper quartiles, Medians, Lower quartiles, Minimums Contingency table
Graphs of the data Box plot with individual data Box plot with individual data

For individual data plots values of a single case are connected.

Population properties

Result For interval variables For ordinal variables For nominal variables
Graphs of the population parameters Graph with mean and 95% CI
Hypothesis test for two variables If the data are normal (measured with Shapiro-Wilk test) paired t-test

Otherwise paired Wilcoxon test (see CogStat specific details)
Paired Wilcoxon test (see CogStat specific details) If the variables are dichotomous, then McNemar's test

Otherwise no test is provided by CogStat
Hypothesis test for more than two variables If the data are normal (measured with Shapiro-Wilk test) repeated measures ANOVA
For ANOVA, sphericity is checked with Mauchly's sphericity test. If sphericity is violated, Greenhouse-Geisser correction is applied.
If ANOVA is significant, Holm-Bonferroni corrected post-hoc tests are run.

For non-normal variables Friedman test
Friedman test If the variables are dichotomous, then Cochran Q-test

Otherwise no test is provided by CogStat

Limitations

  • CogStat only supports one-way comparisons at the moment.
  • Hypothesis test for non dichotomous nominal variable comparison is missing.
  • No post-hoc tests for Friedman's test yet.
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