6.0 Logistic_Univariate


#載入包
library(epiDisplay)

#單因素logistic


fit1<-glm(formula = MACE ~ Age 
         , family = binomial(), 
         data = Vdata2)


fit2<-glm(formula = MACE ~ Hypertention 
          , family = binomial(), 
          data = Vdata2)

fit3<-glm(formula = MACE ~ Hhcy 
          , family = binomial(), 
          data = Vdata2)

fit4<-glm(formula = MACE ~ HF 
          , family = binomial(), 
          data = Vdata2)

fit5<-glm(formula = MACE ~ Sent 
          , family = binomial(), 
          data = Vdata2)

fit6<-glm(formula = MACE ~ Killip 
          , family = binomial(), 
          data = Vdata2)

fit7<-glm(formula = MACE ~ VD3LM 
          , family = binomial(), 
          data = Vdata2)

fit8<-glm(formula = MACE ~ LDLC 
          , family = binomial(), 
          data = Vdata2)

fit9<-glm(formula = MACE ~ LVEF_F
          , family = binomial(), 
          data = Vdata2)


#查看單因素結(jié)果
logistic.display(fit1)
logistic.display(fit2)
logistic.display(fit3)
logistic.display(fit4)
logistic.display(fit5)
logistic.display(fit6)
logistic.display(fit7)
logistic.display(fit8)
logistic.display(fit9)
?著作權(quán)歸作者所有,轉(zhuǎn)載或內(nèi)容合作請(qǐng)聯(lián)系作者
【社區(qū)內(nèi)容提示】社區(qū)部分內(nèi)容疑似由AI輔助生成，瀏覽時(shí)請(qǐng)結(jié)合常識(shí)與多方信息審慎甄別。
平臺(tái)聲明：文章內(nèi)容（如有圖片或視頻亦包括在內(nèi)）由作者上傳并發(fā)布，文章內(nèi)容僅代表作者本人觀點(diǎn)，簡(jiǎn)書系信息發(fā)布平臺(tái)，僅提供信息存儲(chǔ)服務(wù)。

相關(guān)閱讀更多精彩內(nèi)容

友情鏈接更多精彩內(nèi)容