MC808 - 1 year ago 132

R Question

I am trying to create a table of a multivariable logistic regression model using

`stargazer`

I figured out how to replace the coefficients with the odds ratios, thanks to this link but doing the same with the CI creates problems. If I give

`stargazer`

`se = *a list of the standard errors or exp(standard errors)*`

Here's some sample code, first part from UCLA DAE:

`library(stargazer)`

mydata <- read.csv("http://www.ats.ucla.edu/stat/data/binary.csv")

mydata$rank <- factor(mydata$rank)

mylogit <- glm(admit ~ gre + gpa + rank, data = mydata, family = "binomial")

summary(mylogit)

# Table with coefficients

stargazer(mylogit, ci = T, single.row = T, type = "text")

# Table with Odds Ratios, but the CI is not right

OR.vector <- exp(mylogit$coef)

stargazer(mylogit, coef = list(OR.vector), ci = T, single.row = T, type = "text")

# Correct CIs

CI.vector <- exp(confint(mylogit))

cbind(OR = OR.vector, CI.vector)

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Answer Source

You can use the `ci.custom`

argument to feed `stargazer`

a list with custom confidence intervals (first column is the lower bound, second column is the upper bound). In your example, all you have to do is call:

```
stargazer(mylogit, coef = list(OR.vector), ci = T,
ci.custom = list(CI.vector), single.row = T, type = "text")
```

Alternatively, you can define your own function to exponentiate values and simply apply this function to your coefficients and/or confidence intervals (using arguments `apply.coef`

and `apply.ci`

):

```
exponentiate <- function(x) exp(x)
stargazer(mylogit, ci=T, apply.coef=exponentiate, apply.ci=exponentiate,
single.row = T, type="text")
```

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