Spss version 25

The prevalence of DFV was derived from univariate analyses using frequencies and percentages. Odds ratios, 95% confidence intervals (CI) and P-values were employed to assess the likely size of the association between demographic and other variables with categories of abuse. Quantitative data was imported, cleaned and coded using SPSS (version 25) [43 ] and analysed with STATA (version 15) [44 ]. Ethics approval for the project was granted by the University of Melbourne Human Research and Ethics Committees (Ethics ID: 1953826).

We used SPSS (version 25) for data cleaning and Stata (version 15 for Windows) [43 ] for all the statistical analyses. The survey datasets were weighted to correct for over or under sampling of some areas. Descriptive statistics were produced using means, standard deviations, frequencies, and percentages to present the demographic characteristics of the respondents and observations of probable depression and no depression. We fitted adjusted and unadjusted models to examine individual, family/friend, and community levels correlate of probable depression among pregnant and parenting girls. A p-value < 0.05 was considered statistically significant, and 95% confidence intervals were estimated. Model 1 is the unadjusted model showing the effect of each variable on the study outcome, and Model 2 is the adjusted model showing the effect of each variable after controlling for covariates. We dropped living with both parents and orphanhood status from the multivariable analysis because of multicollinearity. Living with both parents and orphanhood status significantly correlate with parental support.

Data collected from the field was analyzed with the aid of SPSS (version 25) using Stata version 6.0 for entry and analysis. Results are presented in tables, graphs, and charts representing the major findings relative to the objectives of this study. A chi-square correlational test was used to determine the association between a prescribers’ knowledge level and demographic characteristics using 95 % confidence interval, a P-value of less than 0.05 was considered significant in this study.

Participants were contacted via email for recruitment by sending a direct link to the online survey to complete all self-report measures. Upon completion of the survey, data was deidentified by providing each participant a generic unique identifier. Data analysis was conducted using Statistical Package for the Social Sciences (SPSS) version 25 and Stata version 12. First, descriptive statistics and zero-order correlations were generated using SPSS. The descriptive statistics for the SWFL scale, GAD-7, CES-D, and self-reported health were used to establish baseline statistics for the family emotional climate, psychological health and physical health of seminary students. Finally, structural equation modeling analysis was conducted using Stata. Several goodness of fit indices was subsequently examined to test the adequacy of the proposed models. Specifically, in keeping with previously published guidelines established by Kline (2011) , a model was considered a good fit for the data if Chi-Square (χ²) was p > 0.05, root mean squared error of approximation (RMSEA) was <0.05 90% CI left 0.00, upper <0.10, and comparative fit index (CFI) was >0.95.

All statistical analyses and graph presentation were performed using four kinds of software including SPSS version 25, Stata version 16, R version 3.6.3 (http://www.r-project.org/), and GraphPad Prism version 7.0. The quantitative data were presented as means ± SD. Comparison between two groups was performed using an independent Student's t-test (two-tailed) and chi-square test (χ² test). The survival curves of PC patients were calculated using Kaplan-Meier method, and the differences in OS between high and low DUOX2 expression groups were calculated using logrank test. Univariate and multivariate analyses of these variables were performed using Cox proportional hazard regression model to calculate the relative risk among all the affecting factors. A two-sided P value of <0.05 was considered to be statistically significant.