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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/D3.R
\name{D3}
\alias{D3}
\title{Compare two nested models using D3-statistic}
\usage{
D3(fit1, fit0 = NULL, dfcom = NULL, df.com = NULL)
}
\arguments{
\item{fit1}{An object of class \code{mira}, produced by \code{with()}.}
\item{fit0}{An object of class \code{mira}, produced by \code{with()}. The
model in \code{fit0} is a nested within \code{fit1}. The default null
model \code{fit0 = NULL} compares \code{fit1} to the intercept-only model.}
\item{dfcom}{A single number denoting the
complete-data degrees of freedom of model \code{fit1}. If not specified,
it is set equal to \code{df.residual} of model \code{fit1}. If that cannot
be done, the procedure assumes (perhaps incorrectly) a large sample.}
\item{df.com}{Deprecated}
}
\value{
An object of class \code{mice.anova}
}
\description{
The D3-statistic is a likelihood-ratio test statistic.
}
\details{
The \code{D3()} function implement the LR-method by
Meng and Rubin (1992). The implementation of the method relies
on the \code{broom} package, the standard \code{update} mechanism
for statistical models in \code{R} and the \code{offset} function.
The function calculates \code{m} repetitions of the full
(or null) models, calculates the mean of the estimates of the
(fixed) parameter coefficients \eqn{\beta}. For each imputed
imputed dataset, it calculates the likelihood for the model with
the parameters constrained to \eqn{\beta}.
The \code{mitml::testModels()} function offers similar functionality
for a subset of statistical models. Results of \code{mice::D3()} and
\code{mitml::testModels()} differ in multilevel models because the
\code{testModels()} also constrains the variance components parameters.
For more details on
}
\examples{
# Compare two linear models:
imp <- mice(nhanes2, seed = 51009, print = FALSE)
mi1 <- with(data = imp, expr = lm(bmi ~ age + hyp + chl))
mi0 <- with(data = imp, expr = lm(bmi ~ age + hyp))
D3(mi1, mi0)
\dontrun{
# Compare two logistic regression models
imp <- mice(boys, maxit = 2, print = FALSE)
fit1 <- with(imp, glm(gen > levels(gen)[1] ~ hgt + hc + reg, family = binomial))
fit0 <- with(imp, glm(gen > levels(gen)[1] ~ hgt + hc, family = binomial))
D3(fit1, fit0)
}
}
\references{
Meng, X. L., and D. B. Rubin. 1992.
Performing Likelihood Ratio Tests with Multiply-Imputed Data Sets.
\emph{Biometrika}, 79 (1): 103–11.
\url{https://stefvanbuuren.name/fimd/sec-multiparameter.html#sec:likelihoodratio}
\url{http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#setting-residual-variances-to-a-fixed-value-zero-or-other}
}
\seealso{
\code{\link{fix.coef}}
}
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