Categorical variables were expressed as counts and percentages. Depending on whether it is normally distributed, continuous variables are expressed as mean ± SD or median, 25–75th interquartile range (IQR). Differences in frequencies were compared using chi‐square test or Fisher's exact test. In the comparison of continuous numerical variables in independent groups, the Mann–Whitney U test was used in the case of two groups, whereas nonparametric tests with multiple independent samples corrected by Bonferroni were used three or more groups. Factors with significant (p < .05) unadjusted associations with disease severity and suspected important variables were included in subsequent multivariable logistic regression analysis (Forward method) to determine risk factors associated with disease severity, yielding adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Goodness of‐fit was tested using the Hosmer‐Lemeshow test [reference]. All statistical tests were two‐sided, and p < .05 was considered to be statistically significant. All analyses were performed using IBM SPSS Statistics version 18.0 for Windows (IBM Corp.).
Spss statistics version 18.0 for windows
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SPSS Statistics version 18.0 for Windows is a software package developed by IBM for statistical analysis. It provides a comprehensive set of tools for data management, exploration, modeling, and reporting. The core function of SPSS Statistics is to analyze and interpret data, enabling users to make informed decisions based on statistical insights.
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Lab products found in correlation
5 protocols using spss statistics version 18.0 for windows
1
Statistical Analysis of Disease Severity Factors
2
Bioimpedance Analysis for Patient Evaluation
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All statistical analyses were performed using IBM SPSS Statistics version 18.0 for Windows (IBM corp., Armonk, NY) and R statistical software v.3.1.2 for Windows (Foundation for Statistical Computing, Vienna, Austria). We used Student t tests to compare the mean values of age, BMI, calculated SFBIA, and ECF ratios between the patient and the control groups. The cutoff values were obtained using ROC curves for calculated ECF, 1 kHz, and 5 kHz SFBIA ratios. Sensitivity and specificity were calculated with cutoff values of the bioimpedance analysis. Statistical significance was determined at P values <.05.
3
Statistical Analysis of Treatment Outcomes
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IBM SPSS™ statistics version 18.0 for Windows was used for statistical analysis. The treatment effect was evaluated with intention-to-treat analysis, with missing data assumed by multiple imputation method. Baseline demographic characteristics were presented using descriptive statistics; mean and standard deviation (SD), median and interquartile range (IQR), or number and percentage as appropriate. Primary and secondary outcome comparisons between groups were evaluated with Mann-Whitney U test or analysis of covariance (ANCOVA), with treatment arm as a fixed effect in the model and the baseline value used as a covariate, according to data distribution characteristics. P-value of less than 0.05 is determined statistically significant.
4
Impression Accuracy Across Dental Impression Techniques
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The statistical analysis was performed using IBM SPSS Statistics version 18.0 for Windows (IBM corp., Armonk, New York, NY, USA), and the significance level was set to 0.05. To analyze the statistically significance differences in the duration of impression taking and the accuracy between the control, MB, and CB groups, one-way analysis of variance (ANOVA) was performed. If there was a difference in the mean analyzed by one-way ANOVA, a post hoc test was performed with the Duncan test to confirm the difference between the groups. Intra-rater reliability analysis was performed using intraclass correlation coefficients (ICC). ICC range from 0.0 to 1.0 (0.00–0.49, poor; 0.50–0.74, moderate; 0.75–0.90 good; and ≥0.90, excellent agreement [39 (link)]).
5
Validating Thai COVID-19 Medication Adherence
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Categorical variables were reported as number and frequencies. Continuous variables were reported using the mean and standard deviations for normally distributed data and the median and interquartile ranges (IQR) were used for non-normal distribution. The criterion validity of the Thai CQR-19 was evaluated using pill counts. Agreement between the Thai CQR-19 at follow-up visit and the pill count was described using Cohen’s kappa and percentage of agreement. However, when a “kappa paradox” was present (a discrepancy between Cohen’s kappa and percentage of agreement), agreement was assessed using Gwet’s AC1.36–39 (link) To assess construct validity, Spearman correlation coefficients (rs) were calculated for the relationships between the Thai CQR-19 scores, DAS28 scores and Thai HAQ scores. Internal consistency was tested using Cronbach’s alpha, and test-retest reliability was tested using ICC with two-way random model, single measures, and consistency. The completion time and number of unanswered questions were recorded as a proxy for feasibility and described as median with IQR and percentage, respectively. A P value of less than 0.05 was considered to be statistically significant. All analyses were performed using IBM SPSS statistics Version 18.0 for Windows.
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