Selected article for: "adjusted aor and logistic regression"
Author: Ying Wen; Lan Wei; Yuan Li; Xiujuan Tang; Shuo Feng; Kathy Leung; Xiaoliang Wu; Xiong-Fei Pan; Cong Chen; Junjie Xia; Xuan Zou; Tiejian Feng; Shujiang Mei
Title: Epidemiological and clinical characteristics of COVID-19 in Shenzhen, the largest migrant city of China
  • Document date: 2020_3_23
    • ID: ddq2q1pg_45
    Snippet: The copyright holder for this preprint . https://doi.org/10.1101/2020.03.22.20035246 doi: medRxiv preprint .47) *AOR, adjusted OR; the model is constructed using the stepwise logistic regression (entry probability 0.05; removal probability 0.10) with variables including age, fever, cough with phlegm, sore throat, headache, breath problem, diarrhea, days from illness onset to the first medical visit, days from the first medical visit to admission,.....
    Document: The copyright holder for this preprint . https://doi.org/10.1101/2020.03.22.20035246 doi: medRxiv preprint .47) *AOR, adjusted OR; the model is constructed using the stepwise logistic regression (entry probability 0.05; removal probability 0.10) with variables including age, fever, cough with phlegm, sore throat, headache, breath problem, diarrhea, days from illness onset to the first medical visit, days from the first medical visit to admission, identification mode, and cluster.

    Search related documents:
    Co phrase search for related documents
    • admission medical visit and medical visit onset: 1, 2, 3, 4, 5
    • entry probability and logistic regression: 1
    • illness day and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
    • illness day and medical visit: 1
    • illness day and medical visit onset: 1
    • illness day medical visit onset and medical visit: 1
    • illness day medical visit onset and medical visit onset: 1
    • logistic regression and medical visit: 1, 2
    • logistic regression and phlegm cough: 1
    • logistic regression and removal probability: 1
    • logistic regression and stepwise logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25