Selected article for: "chi square test and correlation analysis"
Author: Jing Qi; Jing Xu; Bozhi Li; Jinsha Huang; Yuan Yang; Zhentao Zhang; Dongai Yao; Qunhui Liu; Min Jia; Daokai Gong; Xiaohong Ni; Qimei Zhang; Furong Shang; Nian Xiong; Chunli Zhu; Tao Wang; Xi Zhang
Title: The Evaluation of Sleep Disturbances for Chinese Frontline Medical Workers under the Outbreak of COVID-19
  • Document date: 2020_3_8
    • ID: dtoheyo4_14
    Snippet: Categorical variables were described as frequencies and percentages, and continuous variables were described as the mean ± SDs. Statistical analyses were performed using SPSS 23.0 for Windows (IBM, Somers, NY). The demographic characteristics were compared by non-parametric test for continuous variables and by Pearson's chi-square test for categorical variables between two groups. The scores of PSQI, AIS, anxiety, and depression VAS were compare.....
    Document: Categorical variables were described as frequencies and percentages, and continuous variables were described as the mean ± SDs. Statistical analyses were performed using SPSS 23.0 for Windows (IBM, Somers, NY). The demographic characteristics were compared by non-parametric test for continuous variables and by Pearson's chi-square test for categorical variables between two groups. The scores of PSQI, AIS, anxiety, and depression VAS were compared by ANOVA. The variables with significant differences between two groups in demographic characteristics were described as covariates and joined in the process of ANOVA. In the subgroup analysis of fMW, the scores of PSQI, AIS, anxiety, and depression VAS were compared by ANOVA between male and female fMW. Partial correlation analysis was conducted to . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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