Nothing
#==============================================================================
# Generalized Linear Modeling for multiply imputed dataset
#==============================================================================
glm.mi <- function (formula, mi.object, family = gaussian, ... )
{
call <- match.call( )
m <- m(mi.object)
result <- vector( "list", m )
names( result ) <- as.character(paste( "Chain", seq( m ), sep = "" ))
mi.data <- mi.completed(mi.object)
for ( i in 1:m ) {
result[[i]] <- glm( formula, family = family,
data = mi.data[[i]], ... )
}
coef <- vector( "list", m )
se <- vector( "list", m )
for( j in 1:m ) {
coef[[j]]<- lapply( result, summary )[[ j ]]$coef[ ,1]
se[[j]] <- lapply( result, summary )[[ j ]]$coef[ ,2]
}
pooled <- mi.pooled(coef, se)
mi.pooled.object <- new("mi.pooled",
call = call,
mi.pooled = pooled,
mi.fit = result)
return( mi.pooled.object )
}
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