Statistical analyses
vomit, nausea, MSAQ
Statistical analyses performed included Pearson correlations, one-way analysis of variance (ANOVA), empirical cumulative distribution functions (ECDF), and two-sample Kolmogorov–Smirnov tests (K-S test). To evaluate the relationship between mean scores across questionnaires, analyses were anchored to the global PGI-S and compared to the motion-sickness-specific questionnaires (MSSS and MSAQ).There were four core elements of the validation study. Within the analytic sample (placebo group, n = 62), first, Pearson correlation coefficients were calculated to estimate the linear association between MSSS scores and each of PGI-S and MSAQ scores. Second, in subpopulations stratified by the five PGI-S severity levels (none, mild, moderate, severe, very severe), within-group differences in mean MSSS and MSAQ scores were evaluated using a one-way ANOVA [There were two additional exploratory analyses of the validation study. First, we evaluated the Pearson correlation between the MSSS and subscales of the MSAQ, including items conceptually directly related to MSSS scores (i.e., the vomit [item 11] and nausea [item 15] MSAQ items) and the group of gastrointestinal MSAQ items. Second, we calculated Pearson’s correlation of MSSS and PGI-S and MSAQ scores on the overall Motion Sifnos Study population (treatment and placebo groups, n = 125). The purpose of this analysis was to evaluate whether correlations differed with the expanded study population that included a group on an investigational antiemetic therapeutic.The significance level of all tests was set at α = 0.05 given that the statistical tests were performed for different purposes and nonduplicative. Multiple statistical measures were used without thresholds to characterize the performance of the MSSS relative to established measures.Pearson’s correlation coefficient is a measurement of association between two variables. The strength of association between variables is described by -1.0≤r≤+1.0 where -1.0 represents a perfect negative correlation and +1.0 represents a perfect positive correlation. Pearson’s correlation was chosen rather than Spearman’s correlation to assess the relationship between continuous rather than ranked scale scores. Using guidelines established for appropriate use of correlation for medical research, a threshold of r ≥│0.70│was used to interpret correlations as high (│0.70│≤r ≤│0.90│) or very high (r>│0.90│) [A one-way analysis of variance (ANOVA) was used to compare MSSS (or MSAQ) in subgroups corresponding to consecutive and ascending PGI-S severity levels. Statistically significant increases in mean scores accompanying ascending PGI-S levels would be indicative of an association between the MSSS (or MSAQ) and the validated questionnaires.An empirical cumulative distribution function (ECDF) of a sample is an ascending function ranging from 0 to 1 over all possible values. At each point The Kolmogorov-Smirnov test (K-S test) serves as a nonparametric test to compare two samples. K-S tests were applied to MSSS scores corresponding to increasing PGI-S severity levels. The underlying hypothesis of the K-S test is that the two ECDFs were generated from the same population-level Cumulative Distribution Function (CDF). Statistically significant K-S test results between MSSS score ECDFs at increasing PGI-S severity levels would indicate that MSSS scores between PGI-S severity levels were likely sampled from different distributions and that MSSS scores are differentiated by PGI-S severity level.