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, BSCS, BIS/BAS were assessed by linear mixed model. Group, time, and group-by-time interaction terms were included as fixed effects and within-subject factor was considered as a random effect. In addition, within-group changes were examined for each
, BSCS, BIS/BAS were assessed by linear mixed model. Group, time, and group-by-time interaction terms were included as fixed effects and within-subject factor was considered as a random effect. In addition, within-group changes were examined for each
symptom severity in SDQ-PR, DIKJ, SIAS, and PHOKI showing small to medium effect sizes. Table 2. Results of fixed effects parameters for change in IUD symptoms and secondary outcomes Variable Parameter Estimate SE t value P value d Primary
size, ROE, leverage and investment opportunity. Table 5 shows the results of pool, fixed effects and random effects models regression. The pool model refers to a model without distinction of the data heterogeneity over time or individual groups; the
Pearson's correlation coefficient. Otherwise, the fixed effects model would be used. Subgroup analyses were completed based on geographic location, students' specialty (medical students or not), sampling strategy (random sampling or not), sample size (≥500
