Spss statistics for window

Descriptive statistics, including the mean, maximum and minimum values, and standard deviation (SD), were used to describe the continuous variables. Percentages were calculated for categorical variables. Continuous variables were assessed with the Student’s t-test. P value < 0.05 was considered significant. Statistical analysis was performed with the SPSS version 20 statistical software (IBM SPSS Statistics for Windows, version 20.0, IBM Corp., Armonk, NY). Data were collected and analyzed using the Statistical Package for Social Sciences (IBM SPSS Statistics for Windows, version 20.0, IBM Corp.).

Inter-personal Communication Skills Test includes 19 five-choice questions with a score range of 19–95. The options for each question are very low, low, satisfactory, good, and very good, which are graded from 1 to 5. A score <45 means an acute communication problem, a score of 46–65 is indicative of a communication problem, and 66–95 shows a person's ability to communicate. Validity and reliability of this test have been confirmed by Agha Mohammad Hasan et al. with a Cronbach's alpha of 0.82.[23 ]
The collected data and demographic variables were analyzed using descriptive statistics and standard deviation. Data were analyzed by SPSS Statistics for Windows, Version 22.0 (IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp). Pearson's correlation test was utilized to determine the correlation between variables, and a multi-variate linear regression test analyzed the predictors for dimensions of family communication patterns on behavioral health of students. The significance level was considered to be <0.05.

Data are reported as mean and standard deviation (SD) for continuous variables and number and proportions for discrete variables. We present data as mean ± SD for continuous variables and proportions for categorical variables. Data were analyzed using SPSS Statistics for Windows, Version 23.0 (IBM SPSS Statistics for Windows, Version 23.0 Armonk, NY: IBM Corp). Mean values of variables were compared by paired or independent sample t-test, and P values <0.05 were considered statistically significant.

Clinical characteristics at baseline were summarized using descriptive statistics, stratified by antibiotic strategies. Differences between antibiotic groups were compared with χ² testing for categorical variables, one-way analysis of variance for continuous variables, and Mann-Whitney U tests for nonnormally distributed continuous variables. Kaplan-Meier curves were constructed to report outcome by the different antibiotic groups. Patients were counted as failure if PJI was the direct cause of death. Patients were censored at the time of death if they died during follow up due to an event not related to PJI. A Cox proportional hazards regression model was used to investigate whether differences in outcome were associated with baseline differences between groups. Variables in the multivariate model were selected based on the univariate regression analysis. Results are reported as hazard ratios (HRs) with 95% confidence intervals (95% CIs). To prevent immortal time bias in the short-term rifampicin antibiotic groups and to focus on the targeted treatment phase for PJI, the minimal survival time required for inclusion in the survival analysis was defined as at least 15 days after debridement. SPSS Statistics for Windows was used (IBM SPSS Statistics for Windows, Version 25.0., Armonk, NY).

All statistical analyses were performed using SPSS (IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 27.0. IBM Corp. Armonk, NY, USA).
The two-step clustering method was performed to identify underlying clusters of complaints using SPSS (IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 27.0. IBM Corp. Armonk, NY, USA). Clusters were identified using log-likelihood distance measure and Schwarz’s Bayesian clustering criterion.
Odds ratios (OR) for the complaints were calculated and Cramer's V test for statistical significance was performed. We used logistic regression analyses to examine the association of risk factors (“no” as reference) with patients’ symptoms resulting in odds ratios (OR) and 95% confidence interval (CI). Comparison of means was performed using Mann–Whitney U test, and analysis of multiple groups was performed using Kruskal–Wallis ANOVA with Dunn’s post hoc test after testing for parametric distribution with Shapiro–Wilk test. Influencing factors on somatization (PHQ-15) and cognitive dimensions were identified with linear regression calculation with the method enter. Correlations were analyzed by bivariate correlation and spearman’s rho. The level of significance was set at p < 0.05.