logistic.display.local = function (logistic.model, alpha = 0.05, decimal = 5) {
model <- logistic.model
if (class(model)[1] != "glm" | class(model)[2] != "lm" |
model$family$family != "binomial") {
stop("model not from logistic regression")
}
s0 = Anova(model)
s1 <- summary(model)
orci <- as.data.frame(s1$coefficients)
colnames(orci) <- c("OddsRatio", paste("Lower", 100 - 100 * alpha,
"CI", sep = ""), paste("Upper", 100 - 100 * alpha, "CI",
sep = ""), "P-value")
orci[, 3] <- exp(orci[, 1] + qnorm(1 - alpha/2) * orci[, 2])
orci[, 2] <- exp(orci[, 1] - qnorm(1 - alpha/2) * orci[, 2])
orci[, 1] <- exp(orci[, 1])
a <- orci[rownames(orci) != "(Intercept)", ]
a$LogLikelihood = as.numeric(logLik(model))
a$N = length(model$y)
a$AIC = s1$aic
a$deviance = s1$deviance
a$Chisq.LogRatio = s0$"LR Chisq"
a$Chisq.df = s0$Df
a$Chisq.Pvalue = s0$"Pr(>Chisq)"
a = round(a, decimal)
a$Level = rownames(a)
return(a)
}
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