rr <- function(l) {
r1 <- (function(x) {temp=summary(x); f=temp$fstatistic;c(R=sqrt(temp$r.squared),"R\U00B2"=temp$r.squared, p = unname(pf(f[1],f[2],f[3],lower.tail=FALSE)),"adj R\U00B2"=temp$adj.r.squared,"pred R\U00B2"=lm_pred_r_squared(x))})(l)
#r2 <- anova(l)
#r2 <- r2[c(5,3,1,6)]
f <- summary(l)$fstatistic#[c(2,3,1)]
f <- c(summary(l)$sigma,f)
names(f) <- c("Res SE","F","df1","df2")
#p <- pf(f[1],f[2],f[3],lower.tail=FALSE)
#r2[1,] <- c(summary(ll[[1]])$fstatistic,p)
# rch <- c(r1[1,2],diff(r1[,2]))
#data.frame(t(r1),t(f), row.names="Model")
temp <- c(r1,f)
temp1=data.frame(A=NA,B=NA,C=NA,D=NA,E=NA,F=NA,G=NA)[numeric(0), ]
temp1=rbind(temp1,temp)
names(temp1) <- names(temp)
if(round(temp1$p,3)==0) temp1$p <- "<.001" ## neu
row.names(temp1) <- "Model"
temp1
}
round.df <- function(x, digits) {
# round all numeric variables
# x: data frame
# digits: number of digits to round
numeric_columns <- sapply(x, mode) == 'numeric'
x[numeric_columns] <- round(x[numeric_columns], digits)
x
}
qqplot.data <- function (vec) # argument: vector of numbers
{
# following four lines from base R's qqline()
y <- quantile(vec[!is.na(vec)], c(0.25, 0.75))
x <- qnorm(c(0.25, 0.75))
slope <- diff(y)/diff(x)
int <- y[1L] - slope * x[1L]
d <- data.frame(resids = vec)
ggplot(d, aes(sample = resids)) + stat_qq() + geom_abline(slope = slope, intercept = int)+theme_bw()
}
round_ps <- function (x,stellen=2)
{
substr(as.character(ifelse(x < 1e-04, " <.0001",
ifelse(x < 0.001, formatC(x, digits = 4, format = "f"),
ifelse(x < 0.01, formatC(x, digits = 3, format = "f"),
ifelse(round(x, 2) == 1, " >.99", formatC(x, digits = stellen, format = "f")))))),2, 7)
}
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