All statistical analyses were performed with Statistical Package for the Social Science for Windows version 16.0 (SPSS, Chicago, IL, USA) and MedCalc version 17.9.2 (Mariakerke, Belgium). Categorical variables and continuous variables were reported as the percentages and the mean ± standard deviation (SD), respectively. Chi-Square test, one-way ANOVA, and Spearman rank correlation were employed. The receiver operating characteristic (ROC) curves were created and the areas under the curves (AUCs) were calculated to illustrate and compare the accuracy of the indices. The sensitivities, specificities, positive predictive values (PPVs), negative predictive values (NPVs), and Youden’s indices were also calculated. A p value of < 0.05 was considered statistically significant.
Statistical package for the social science for windows version 16
Manufactured by IBM
Sourced in United States
SPSS for Windows version 16.0 is a statistical software package used for data analysis, data management, and data documentation. It provides a comprehensive set of tools for descriptive statistics, bivariate analysis, and multivariate analysis.
Automatically generated - may contain errors
Lab products found in correlation
4 protocols using statistical package for the social science for windows version 16
1
Statistical Analysis of Medical Indices
2
Statistical Analysis in Medical Research
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All statistical analyses were performed with Statistical Package for the Social Science for Windows version 16.0 (SPSS, Chicago, IL, USA) and MedCalc version 19.1.3 (Mariakerke, Belgium). Categorical variables and continuous variables were reported as the percentages and the mean ± standard deviation (SD), respectively. Chi-Square test, one-way ANOVA, univariate logistic regression, and Spearman rank correlation were employed. The receiver operating characteristic (ROC) curves were created and the areas under the curves (AUCs) were calculated to illustrate and compare the accuracy of the indices. The sensitivities, specificities, positive predictive values (PPVs), negative predictive values (NPVs), and Youden’s indices were also calculated. A p value of < 0.05 was considered statistically significant.
3
Statistical Analysis of Clinical Indices
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All statistical analyses were performed with Statistical Package for the Social Science for Windows version 16.0 (SPSS, Chicago, IL) and MedCalc version 14.8.1.0 (Mariakerke, Belgium). Categorical variables and continuous variables were reported as the percentages and the mean ± standard deviation (SD), respectively. Chi-square test and univariate logistic regression were employed. The receiver operating characteristic curves were created and the areas under the curves (area under the receiver operating characteristic curves [AUCs]) were calculated to illustrate and compare the accuracy of the indices. The sensitivities, specificities, positive predictive values (PPVs), negative predictive values, and Youden indices were also calculated. A P value of <0.05 was considered statistically significant.
4
Diagnostic Accuracy of Epworth Sleepiness Scale for Obstructive Sleep Apnea
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All statistical analyses were performed with Statistical Package for the Social Science for Windows version 16.0 (SPSS, Chicago, IL, USA) and MedCalc version 19.1 (Mariakerke, Belgium). Categorical variables and continuous variables were reported as the percentages and the mean ± standard deviation (SD), respectively. Chi-Square test, unpaired Student’s t-test, one-way ANOVA, univariate logistic regression, and Spearman rank correlation were employed. Two groups were compared by unpaired Student’s t-test or Chi-Square test, and analyses of multiple groups were carried out using one-way ANOVA or Chi-Square test, depending on the characteristics of variables. Each ESS item’s increased odds ratio (OR) for the corresponding AHI was calculated using univariate logistic regression. The receiver operating characteristic (ROC) curves were created and the areas under the ROC curves (AUCs) were calculated to illustrate and compare the accuracies of the indices. The sensitivities, specificities, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive values (PPVs), negative predictive values (NPVs), and Youden’s indices were also calculated. A p value of < 0.05 was considered statistically significant.
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