Nothing
getSummary.lm <- function(obj,
alpha=.05,
...
){
smry <- summary(obj)
coef <- smry$coef
dendf <- smry$df[2]
lower <- coef[,1] + coef[,2]*qt(p=alpha/2,df=dendf)
upper <- coef[,1] + coef[,2]*qt(p=1-alpha/2,df=dendf)
coef <- cbind(coef,lower,upper)
dn <- list(
rownames(coef),
c("est","se","stat","p","lwr","upr"),
names(obj$model)[1]
)
dim(coef) <- c(dim(coef)[1],dim(coef)[2],1)
dimnames(coef) <- dn
sigma <- smry$sigma
r.squared <- smry$r.squared
adj.r.squared <- smry$adj.r.squared
if(length(smry$fstatistic)){
F <- unname(smry$fstatistic[1])
numdf <- unname(smry$fstatistic[2])
p <- pf(F,numdf,dendf,lower.tail=FALSE)
}
else {
F <- 0
numdf <- 0
p <- 1
}
N <- sum(smry$df[1:2])
ll <- logLik(obj)
deviance <- deviance(obj)
AIC <- AIC(obj)
BIC <- AIC(obj,k=log(N))
sumstat <- c(
sigma = sigma,
r.squared = r.squared,
adj.r.squared = adj.r.squared,
F = F,
numdf = numdf,
dendf = dendf,
p = p,
logLik = ll,
deviance = deviance,
AIC = AIC,
BIC = BIC,
N = N
)
list(coef=coef,
sumstat=sumstat,
contrasts=obj$contrasts,
xlevels=obj$xlevels,
call=obj$call)
}
.SummaryStats$lm <- c("R-squared","N")
getSummary.glm <- function(obj,alpha=.05,...){
smry <- summary(obj)
N <- if(length(weights(obj)))
sum(weights(obj),na.rm=TRUE)
else sum(smry$df[1:2])
coef <- smry$coef
lower <- qnorm(p=alpha/2,mean=coef[,1],sd=coef[,2])
upper <- qnorm(p=1-alpha/2,mean=coef[,1],sd=coef[,2])
coef <- cbind(coef,lower,upper)
dn <- list(
rownames(coef),
c("est","se","stat","p","lwr","upr"),
names(obj$model)[1]
)
dim(coef) <- c(dim(coef)[1],dim(coef)[2],1)
dimnames(coef) <- dn
phi <- smry$dispersion
LR <- smry$null.deviance - smry$deviance
df <- smry$df.null - smry$df.residual
ll <- logLik(obj)
deviance <- deviance(obj)
if(df > 0){
p <- pchisq(LR,df,lower.tail=FALSE)
L0.pwr <- exp(-smry$null.deviance/N)
#LM.pwr <- exp(-smry$deviance/N)
Aldrich.Nelson <- LR/(LR+N)
McFadden <- 1- smry$deviance/smry$null.deviance
Cox.Snell <- 1 - exp(-LR/N)
Nagelkerke <- Cox.Snell/(1-L0.pwr)
}
else {
LR <- NA
df <- NA
p <- NA
Aldrich.Nelson <- NA
McFadden <- NA
Cox.Snell <- NA
Nagelkerke <- NA
}
AIC <- AIC(obj)
BIC <- AIC(obj,k=log(N))
sumstat <- c(
phi = phi,
LR = LR,
df = df,
p = p,
logLik = ll,
deviance = deviance,
Aldrich.Nelson = Aldrich.Nelson,
McFadden = McFadden,
Cox.Snell = Cox.Snell,
Nagelkerke = Nagelkerke,
AIC = AIC,
BIC = BIC,
N = N
)
list(coef=coef,
sumstat=sumstat,
contrasts=obj$contrasts,
xlevels=obj$xlevels,
call=obj$call)
}
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