Friends,
I have different companies with different characteristics and each company has the same positions I selected the data of several members of each position of each company and noted behavioral variables, ranging from 0 to 10, to facilitate calling x1, x2, x3, these variables were collected more than once for each person (ID) p> The goal is to predict the probability of occurrence of a fact, and each person also observed this fact occurred or not. (0 or 1)
I am sending an R code that simulates the situation and at the time of predicting the probability of occurrence of the fact I tried not to inform the ID because the objective is to be able to predict for any individual and not for a specific,
But at the end of the code it displays the following error at the end
"Error in eval (predvars, date, env): object ID not found"
(The code in R is only to facilitate the help of the masters in the understanding of the error, not being strictly faithful to the situation studied)
I thank you for your help
library(plyr)
library(dplyr)
library(lme4)
n = 300
xx<-c("r1", "r2", "r3", "r4", "r5")
xxx<-c("e1", "e2", "e3")
p=0.3
Empresa = factor(sample(xxx, n, replace=TRUE), levels=xxx, ordered=FALSE)
Cargo = factor(sample(xx, n, replace=TRUE), levels=xx, ordered=FALSE)
df1 <- data_frame(
ID = as.integer(runif(n, min = 1, max = n/7)),
xx1 = runif(n, min = 0, max = 10),
xx2 = runif(n, min = 0, max = 10),
xx3 = runif(n, min = 0, max = 10),
Empresa = Empresa,
Cargo = Cargo,
Fato = as.factor(rbinom(n, size = 1, prob = p))
)
df1 = df1[order(df1$ID, decreasing=FALSE),]
library(lme4)
mm2 <- glmer(Fato ~ xx1 + xx2 + xx3 + Cargo + (1 | ID) + (1 | Empresa /
Cargo), data = df1,
family = "binomial",control = glmerControl(calc.derivs = FALSE))
n11 <- data.frame(Empresa=factor("e1", levels =
levels(df1$Empresa),ordered=FALSE),
Cargo=factor("r1", levels = levels(df1$Cargo),ordered=FALSE),
xx1=8.58, xx2=8.75, xx3=7.92)
predict(mm2, n11, type="response",re.form= ~(1 | Empresa / Cargo))
##