bife
包装)
使用基本的logit模型(
glm
由于某些原因,logit和fixed effect logit的预测数不同。
例子:
library(bife)
library(tidyverse)
library(caret)
dataset <- psid
logit <- glm(LFP ~ AGE + I(AGE^2) + log(INCH) + KID1 + KID2 + KID3, data = dataset, family = "binomial")
mod <- bife(LFP ~AGE + I(AGE^2) + log(INCH) + KID1 + KID2 + KID3| ID, dataset)
summary(mod)
summary(logit)
predict(logit)
predict(mod)
Y <- factor(dataset$LFP)
PRE <- factor(round(predict(logit, type = "response")))
PRE_FIX <- factor(round(predict(mod, type = "response")))
confusionMatrix(Y, PRE)
# Not working
confusionMatrix(Y, PRE_FIX)
