Statistical package for social sciences software spss for windows version 25

The IBM Statistical Package for Social Sciences Software (SPSS) for Windows, version 25.0, was used to analyze the collected data. Descriptive statistics, including frequencies and percentages, were used for presenting tables. Chi-square analysis was used to present cross-tabulation between violence, drug addiction, and school-related variables. A p-value of ≤0.05 was considered to be significant.

The characteristics of participants were described using frequency and percentage for categorical variables and mean ± standard deviation for continuous variables. A chi-square test or Fisher’s exact test was used to assess the association between categorical variables, whereas continuous variables were analyzed by the Student’s t-test or ANOVA. These tests were used to figure out the differences between the T2DM patients’ group and the non-diabetic subjects’ group. To investigate factors associated with thyroid dysfunction among T2DM patients, chi-square test or Fisher’s exact test, and Student’s t-test or ANOVA were conducted to compare differences between groups with and without thyroid dysfunction among T2DM patients. A binary logistic regression model was used to assess the risk factors for the development of thyroid dysfunction among T2DM patients after adjusting for age, gender, obesity, smoking, anemia, goiter, T2DM disease duration, and glycemic control. Odds ratio (OR) and their 95% confidence intervals (95% CI) were reported. A p-value of less than 0.05 was considered statistically significant. The IBM Statistical Package for Social Sciences Software (SPSS) for Windows, version 25.0 was used for data processing and analysis.

The IBM Statistical Package for Social Sciences Software (SPSS) for Windows, version 25.0, was used for data processing and analysis. Patients’ characteristics were described using frequencies and percentages for categorical variables. Continuous variables were presented as medians with interquartile ranges (IQRs) as they were not normally distributed. Bivariate correlation using the Pearson correlation coefficient (r) was conducted to test the relationships between two-time pertinent findings of COVID-19 patients. Using the measured median VCT in our study of 13 days, univariate and multivariate analyses were performed to detect the predictors of prolonged VCT as defined by a duration of equal or more than 14 days. A chi-square test or Fisher’s exact test was used to assess the categorical variables, whereas continuous variables were analyzed by the nonparametric Mann–Whitney U-test and Kaplan–Meier test. After that, a binary logistic regression analysis test was conducted with adjusting for the significant factors selected by univariate analysis to tease out the independent predictors for prolonged VCT. Odds ratio (OR) and their 95% confidence intervals (95% CI) were reported. A p-value of less than 0.05 was considered statistically significant.