Whitehead [ 16] has derived a method for estimating sample sizes for ordinal data and suggested the odds ratio (OROrdinal), which is the odds of a subject being in a given category or lower in one group compared with the odds in the other group, as an effect size.
Independent samples t-tests (for ordinal data) and Fisher's exact tests (for nominal data) were used to assess differences between commercial and noncommercial websites.
The Pearson's Chi-squared test was applied to assess heterogeneity between the samples for nominal and ordinal data, and Mann–Whitney non-parametric heterogeneity tests are to be used for continuous variables.
Student t-tests (for continuous variables with normal distribution), Fisher's exact test (for nominal data, small sample size), and Mann Whitney U test (for ordinal or continuous data without normal distribution) will be used to determine differences between the intervention and control group at baseline.
p values for the comparison between groups with and without metabolic syndrome by independent samples t-test for continuous variables, Mann-Whitney U test for ordinal data or by Pearson χ2 for nominal variables.
A Metropolis-Hastings scheme with the proposal distribution of truncated normal, which was presented by Cowles [ 29], was used to generate the samples for elements of τ in the ordinal setting.
χ tests were used for analyzing categorical data; for ordinal or interval scale data, given the small sample size, Mann–Whitney U tests were used for comparisons between groups.
Because the study was exploratory, the sample size was calculated to provide a satisfying precision in the worst situation for ordinal data (rate of 50%).
The Mann-Whitney test was used for statistical analyses of differences between the groups for ordinal data (numerical rating scales and quality of life) and the independent two sample t-test was used for analysing days in pain.
Post-intervention comparisons between the decision aid and control groups were done using the independent sample t test for continuous variables, χ test for categorical variables, and non-parametric Mann-Whitney test for ordinal variables.
