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Statistics analysis software version 9

Manufactured by SAS Institute
Sourced in United States

SAS Statistics Analysis Software version 9.4 is a data analysis tool that provides a range of statistical capabilities for data exploration, modeling, and reporting. It offers a comprehensive set of functions and procedures for statistical analysis, including regression, ANOVA, time series analysis, and multivariate techniques. The software is designed to handle large and complex data sets, supporting a variety of data formats and sources.

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2 protocols using statistics analysis software version 9

1

Factors Affecting Pregnant Women's Anxiety During COVID-19

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We calculated the exact numbers and proportions for all variables in Wuhan and Chongqing, as well as the total for the two cities. Cronbach's alpha was used to assess the reliability of the anxiety scale. To compare the distribution of background, attitude, anxiety and obstetric decisions between the two cities, the Chi‐square test, Kruskal–Wallis test and Student's t test were used in accordance with the type of data.
All factors related to pregnant women's background and their attitude towards COVID‐19 were selected as independent variables. We used stepwise logistic regression models to estimate the effect of these factors on the anxiety status.
The Statistics Analysis Software version 9.4 (SAS Institute Inc., Cary, NC, USA) was used and a significance level set at P < 0.05 was applied. Figures presented were plotted with PRISM version 8.0 for windows (GraphPad Software Inc., San Diego, CA, USA).
The corresponding authors had full access to all of the data in the study and had the final responsibility to submit the article for publication.
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2

Evaluating Test Performance Metrics

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Numerical variables are provided as the mean (standard deviation [SD]) and median (range, interquartile range [IQR]), and categorical data are described by absolute numbers and frequencies. Numerical variables were analysed by the unpaired t-test or Mann–Whitney test for two groups or by one-way ANOVA with post hoc pairwise comparisons by LSD’s test for more than two groups. Categorical variables were compared by χ2 or Fisher’s exact test. To evaluate test performance, sensitivity and specificity were calculated with 95% confidence intervals. The positive likelihood ratio (P-LR) was calculated as sensitivity/(1 − specificity), and the negative likelihood ratio (N-LR) was calculated as (1 − sensitivity)/specificity with 95% confidence intervals. The percentage agreement between the test results and Cohen’s kappa coefficient (K) was also calculated. For correlation analysis, a scatterplot was constructed, and Spearman’s rank correlation coefficient (rs) was calculated12 (link). Statistics Analysis Software version 9.4 (SAS INSTITUTE INC, Cary, NC, USA) was used at a significance level of 0.05 in Figs. 4 and 5.
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