# intEff: Functions for Estimating Interaction Effects in Logit and... In DAMisc: Dave Armstrong's Miscellaneous Functions

## Description

Norton and Ai (2003) and Norton, Wang and Ai (2004) discuss methods for calculating the appropriate marginal effects for interactions in binary logit/probit models. These functions are direct translations of the Norton, Wang and Ai (2004) Stata code.

## Usage

 `1` ``` intEff(obj, vars, data) ```

## Arguments

 `obj` A binary logit or probit model estimated with `glm`. `vars` A vector of the two variables involved in the interaction. `data` A data frame used in the call to `obj`.

## Value

A data frame with the following variable:

 `int_eff` The correctly calucalted marginal effect. `linear` The incorrectly calculated marginal effect following the linear model analogy. `phat` Predicted Pr(Y=1|X). `se_int_eff` Standard error of `int_eff`. `zstat` The interaction effect divided by its standard error

## Author(s)

Dave Armstrong (UW-Milwaukee, Department of Political Science)

## References

Norton, Edward C., Hua Wang and Chunrong Ai. 2004. Computing Interaction Effects and Standard Errors in Logit and Probit Models. The Stata Journal 4(2): 154-167.

Ai, Chunrong and Edward C. Norton. 2003. Interaction Terms in Logit and Probit Models. Economics Letters 80(1): 123-129.

Norton, Edward C., Hua Wang and Chunrong Ai. 2004. inteff: Computing Interaction Effects and Standard Errors in Logit and Probit Models, Stata Code.

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```data(france) mod <- glm(voteleft ~ age*lrself + retnat + male, data=france, family=binomial) out <- intEff(obj=mod, vars=c("age", "lrself"), data=france) plot(out\$phat, out\$int_eff, xlab="Predicted Pr(Y=1|X)", ylab = "Interaction Effect") ag <- aggregate(out\$linear, list(out\$phat), mean) lines(ag[,1], ag[,2], lty=2, col="red", lwd=2) legend("topright", c("Correct Marginal Effect", "Linear Marginal Effect"), pch=c(1, NA), lty=c(NA, 2), col=c("black", "red"), lwd=c(NA, 2), inset=.01) ```

### Example output

```Loading required package: car

Attaching package: 'carData'

The following objects are masked from 'package:car':

Guyer, UN, Vocab

lattice theme set by effectsTheme()
See ?effectsTheme for details.
```

DAMisc documentation built on May 30, 2017, 8:12 a.m.