# R/ict.hausman.test.R In SensitiveQuestions/list: Statistical Methods for the Item Count Technique and List Experiment

#### Documented in ict.hausman.test

```#' Hausman Specification Test for Two List Experiment Regression Fit Objects
#'
#' @param ml Maximum likelihood model fit, for example from ictreg(method = "nls")
#' @param nls NLS model fit, for example from ictreg(method = "nls")
#' @param abs Flag to override error when Hausman statistic is negative, which may indicate misspecification. Set to \code{FALSE} to override.
#' @param psd Flag to override error when variance-covariance difference is non-positive semidefinite, suggesting misspecification.  Set to \code{TRUE} to override.
#'
#' @return List containing Hausman statistic, p-value, and the degrees of freedom of the test.
ict.hausman.test <- function(ml, nls, abs = FALSE, psd = FALSE){
if(length(coef(ml)) != length(coef(nls))){
stop("Please provide two ictreg fit objects that used the same number of covariates.")
}
psd.check <- min(eigen(vcov(nls) - vcov(ml))\$values) < 0
stat <-
as.numeric((coef(ml) - coef(nls)) %*%
ginv((vcov(nls) - vcov(ml))) %*%
(coef(ml) - coef(nls)))
# we found that the following check for positive semi-definiteness led to
# significant overrejection of the null
if (psd.check & psd) stop("The variance-covariance difference is non-positive semidefinite, suggesting misspecification.  Set psd = FALSE to compute anyway.")
if (stat < 0 & !abs) stop("Hausman test statistic is negative, suggesting possible misspecification.  Set abs = TRUE to compute anyway.")
df <- length(coef(ml))
p <- pchisq(q = abs(stat), df = df, lower.tail = FALSE)
return(structure(list(stat = stat, df = df, p = p), class = "ict.hausman.test"))
}

print.ict.hausman.test <- function(x, ...){

cat("\nTest for List Experiment Model Misspecification\n\n")

cat("Hausman statistic = ", x\$stat, ", df = ", x\$df, ", p-value = ", x\$p, ".", sep = "")

cat("\n")

}
```
SensitiveQuestions/list documentation built on Nov. 7, 2018, 12:28 p.m.