For the maternal demographics, chi-square was used for nominal data.
For comparison of prevalence rates among the respondents by selected demographic variables, Chi-square test was used to test the statistical significance.
First, we compared sample demographics using chi square statistics for categorical variables and t-test or one-way analysis of variance (ANOVA) for continuous variables.
Due to small samples size; non-parametric statistical tests will be used to determine the relationships and differences between disease and demographic variables: Chi-square for categorical variables and Mann-Whitney U test for continuous variables.
In hierarchic multiple regression analysis, the medical and psychological variables contributed significantly to the variance in sleep-disturbances scores, adding an additional 23.9% to the overall R 2 beyond that accounted for by demographic variables (R-square, 8.5%), resulting in a final R of 42.6%.
In the multivariate regression analysis, the psychological variables contributed significantly to the variance in BASFI scores, adding an additional 24% to the overall R-square beyond that accounted by demographic and medical variables (R-square 32%), resulting in a final R-square of 56%.
Student t test was used to compare demographic characteristics, while Chi Square independent test or Fischer's exact test was used to compare categorical developmental data (developmental delay, yes or no).
In addition to diversity (fractionalisation) and the share of migrants, standard demographic variables (age, age squared, gender, marital status) are included as control variables.
Personal characteristics, besides personality variables, include general demographics (age and its square, sex dummy), dummies for being a student or a disabled, immigrant background and education level (only where mismatch is measured by the mean-based criterion).
Independent samples t-tests were used to compare continuous demographic data, while Chi-square or Mann-Whitney tests were used to determine group differences in ordinal and nominal demographic data.
aSignificant difference (P < .05) between PR and No PR for this demographic subgroup by chi-square test.
