summary.MMLongit <-
function(object, ...) {
oo <- object
m.i <- seq(length(oo$beta))
a.i <- seq(length(oo$alpha))+length(oo$beta)
mean.oo <- with(oo, data.frame(estimate = beta, mod.se = sqrt(diag(mod.cov)[m.i])))
mean.oo$X2 <- with(mean.oo, (estimate/mod.se)^2)
mean.oo$pX2 <- with(mean.oo, pchisq(X2, df=1,lower.tail=FALSE))
names(mean.oo) = c('Estimate','Model SE', 'Chi Square','Pr(>Chi)')
assoc.oo <- with(oo, data.frame(estimate = alpha, mod.se = sqrt(diag(mod.cov)[a.i])))
assoc.oo$X2 <- with(assoc.oo, (estimate/mod.se)^2)
assoc.oo$pX2 <- with(assoc.oo, pchisq(X2, df=1,lower.tail=FALSE))
names(assoc.oo) = c('Estimate','Model SE','Chi Square','Pr(>Chi)')
if(object$control[7]) {
mean.oo <- with(oo, data.frame(estimate = beta, rob.se = sqrt(diag(rob.cov)[m.i])))
mean.oo$X2 <- with(mean.oo, (estimate/rob.se)^2)
mean.oo$pX2 <- with(mean.oo, pchisq(X2, df=1,lower.tail=FALSE))
names(mean.oo) = c('Estimate','Robust SE', 'Chi Square','Pr(>Chi)')
assoc.oo <- with(oo, data.frame(estimate = alpha, rob.se = sqrt(diag(rob.cov)[a.i])))
assoc.oo$X2 <- with(assoc.oo, (estimate/rob.se)^2)
assoc.oo$pX2 <- with(assoc.oo, pchisq(X2, df=1,lower.tail=FALSE))
names(assoc.oo) = c('Estimate','Robust SE','Chi Square','Pr(>Chi)')
warning('When performing a weighted likelihood analysis (by specifying the samp.probi argument), robust standard errors are reported. Model based standard errors will not be correct and should not be used.')
}
out = list(class = class(object), call = deparse(object$call), control=object$control,
info=object$info_stats, mean.table = mean.oo, assoc.table=assoc.oo)
class(out) = 'summary.MMLongit'
out
}
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