我有这个数据框:
mac<-c( 0.125150, 0.045800, -0.955299, -0.232007, 0.120880, -0.041525, 0.290473, -0.648752, 0.113264, -0.403685)
narc<-c(-0.634753, 0.000492, -0.178591, -0.202462, -0.592054, -0.583173, -0.632375, -0.176673, -0.680557, -0.062127)
darc<-c(-0.434753, 0.000592, -0.278591, -0.402462, -0.692054, -0.783173, -0.732375, -0.576673, -0.880557, -0.162127)
ideo<-c(1,2,3,2,3,2,3,1,2,1)
ex<-data.frame(mac,darc,narc,ideo)
我为此运行了通用估计方程(GEE)回归:
library(geepack)
spss<-coef(summary(geeglm(as.integer(ideo) ~ mac+narc+darc,data = ex, id = ideo,
corstr = "independence"))) %>%
mutate(lowerWald = Estimate-1.96*Std.err, # Lower Wald CI
upperWald=Estimate+1.96*Std.err, # Upper Wald CI
df=1,
ExpBeta = exp(Estimate)) %>% # Transformed estimate
mutate(lWald=exp(lowerWald), # Upper transformed
uWald=exp(upperWald)) # Lower transformed
spss
#subsets for ever ideo
ex1<-ex[ex$ideo%in% as.factor(1),] #right men
ex2<-ex[ex$ideo%in% as.factor(2),] #center men
ex3<-ex[ex$ideo%in% as.factor(3),] #far men