Stata se 15

Univariate analysis was conducted to compare medical cost and hospital utilization between hemophilia A and hemophilia B inpatients. Descriptive variables included age, region, city level, insurance type, hospital level, number of hospitalizations, length of stay, total inpatient cost per patient, total medication cost per patient, total coagulation factor cost per patient and total non-pharmacy cost per patient. Percentages of consumption and cost for different coagulation factor products were presented. Category variables were presented as absolute frequencies and percentages and tested by Pearson Chi-square test. The differences between medical cost and hospital utilization of hemophilia A and B inpatients were tested by the Mann-Whitney test based on median and interquartile range (IQR). Multiple regression analysis based on a generalized linear model was conducted, with logarithm of total inpatient costs as the dependent variable and hemophilia type as an independent variable, with age, number of hospitalizations, length of stay, region, city level, insurance type, hospital level, and years as control variables. A P value of less than 0.05 was considered statistically significant. Descriptive analysis and the Mann-Whitney test were performed using SPSS 24.0 for Window (IBM Corp., Armonk, NY, USA), and a multiple regression analysis was performed by STATA/SE 15.

Statistical analysis was performed using SPSS 24.0 for Windows (IBM Corp., Armonk, NY, USA) and STATA/SE 15. Descriptive analysis and independent-sample Kolmogorov–Smirnov test were performed by SPSS 24.0. The median and interquartile ranges of the medical expenditures of patients with hemophilia were calculated via descriptive analysis. An independent-sample Kolmogorov–Smirnov test was carried out to compare medical expenditure of patients with hemophilia covered by the two types of health insurance schemes. Quantile regression analysis was performed with STATA/SE 15 to explore the factors that affect medical expenditure of patients with hemophilia. Statistical significance was considered at p < 0.05.

The data were analyzed using IBM SPSS Statistics 23.0 and StataSE 15.0. p values < 0.05 were considered statistically significant. Continuous variables are presented as mean ± standard deviation, and categorical variables are presented as number and percentage. Differences between myopic and non-myopic students were determined using the chi-square test. Taking into account differences in the rate of onset and progression of myopia in children of different ages, two-level logistic regression models were used to assess the association between school management measures and myopia onset and myopic progression among 8- and 9-year-olds, 10- and 11-year-olds, respectively, after adjusting for confounding factors of baseline age, sex, and parental high myopia.