Statistical analysis
REGRESSION
The QOL-MAC study’s sample size was determined based on the main purpose (i.e., the mapping algorithms’ development) and feasibility. Hence, no sample size calculation for the order effects’ evaluation was conducted.We employed two analysis populations: the eligible and the completed EQ-5D-5L. The former included all enrolled and suitable patients; it was used for the statistical analysis of the missing EQ-5D-5L indexes. The latter comprised all participating and eligible patients whose EQ-5D-5L indexes were calculated; it was utilized for the statistical analysis of the EQ-5D-5L items and index.The patients were classified into three groups based on the EQ-5D-5L’s placement in the questionnaire booklets: Groups 1, 2, and 3 consisted of the two booklet types that had the EQ-5D-5L in the first, second, and last places, respectively. The differences in the responses of this scale’s each item between the groups were examined using the Wilcoxon rank sum test. Furthermore, the differences in the mean EQ-5D-5L indexes between the groups were estimated using analysis of variance with the EQ-5D-5L’s order as the only explanatory variable. Additionally, we conducted multivariable analysis and analysis with inverse probability weighting (IPW) (see Additional file Using a linear binomial regression (also called linear probability model) with the EQ-5D-5L’s order as the only explanatory variable, we compared the proportions of those patients whose EQ-5D-5L were incomplete due to some reason; who failed to return the questionnaire booklets to the data center; who submitted the questionnaire booklets unanswered; and who returned these booklets with some incomplete responses. Additional details regarding the statistical analysis including multivariable analysis and analysis of proportions of the FACT-G and the EORTC QLQ-C30 with missing subscales are provided in Additional file Each p-value was two-tailed, and p < 0.05 was considered to be nominally statistically significant. All statistical analyses were conducted using SAS software, version 9.4 (SAS Institute).