Nothing
.reg1anvBasic <-
function(lm.out, digits_d=NULL, show_R=FALSE) {
nm <- all.vars(lm.out$terms) # names of vars in the model
n.vars <- length(nm)
n.pred <- n.vars - 1L
n.obs <- nrow(lm.out$model)
d <- digits_d
x.cat <- 0
x.cont <- 0
balance <- TRUE
# ANOVA
smc <- anova(lm.out)
n.terms <- nrow(smc) - 1
nt1 <- n.terms + 1
# kable experimentation
# k <- kable(smc, digits=digits_d)
# k <- gsub("|", " ", k, fixed=TRUE)
# k[1] <- gsub("Pr(>F)", "p-value", k[1], fixed=TRUE)
# k[length(k)] <- gsub("NA", " ", k[length(k)], fixed=TRUE)
SSE <- smc[nt1,2]
tx <- character(length=0)
if (is.null(options()$knitr.in.progress)) {
}
tx[length(tx)+1] <- "-- Analysis of Variance"
tx[length(tx)+1] <- ""
if (show_R) {
tx[length(tx)+1] <- ""
.dash2(68)
tx[length(tx)+1] <- paste("> ","anova(model)", "\n",sep="")
tx[length(tx)+1] <-.dash2(68)
}
# width of column 1
max.c1 <- max(nchar("Model"), nchar(nm))
for (i in 1:nt1) {
c1 <- nchar(rownames(smc)[i])
if (c1 > max.c1) max.c1 <- c1
}
# width of data columns
max.ln <- integer(length=4)
for (i in 1:4) {
ln.nm <- nchar(colnames(smc)[i])
max.ln[i] <- ln.nm + 1
for (j in 1:nrow(smc)) {
xjc <- .fmt(smc[j,i], d=digits_d)
if (nchar(xjc) > max.ln[i]) max.ln[i] <- nchar(xjc)
}
max.ln[i] <- max.ln[i] + 1L
if (max.ln[i] < 9L) max.ln[i] <- 9L
}
# header
df.lbl <- .fmtc(" df", max.ln[1]+1)
SS.lbl <- .fmtc(" Sum Sq", max.ln[2]+1)
MS.lbl <- .fmtc("Mean Sq", max.ln[3]+1)
fv.lbl <- .fmtc("F-value", max.ln[4]+1)
tx[length(tx)+1] <- paste(eval(format("", width=max.c1-5)), df.lbl, SS.lbl,
MS.lbl, fv.lbl, " p-value", sep="")
# predictors (terms, including interactions)
if (n.pred > 1) {
#for (i in 1:(n.pred)) {
for (i in 1:n.terms) {
rlb <- .fmtc(rownames(smc)[i], max.c1)
df <- .fmti(smc[i,1], max.ln[1]-5)
SS <- .fmt(smc[i,2], digits_d, max.ln[2])
MS <- .fmt(smc[i,3], digits_d, max.ln[3])
fv <- .fmt(smc[i,4], digits_d, max.ln[4])
pv <- .fmt(smc[i,5], 3, 9)
tx[length(tx)+1] <- paste(rlb, df, SS, MS, fv, pv)
}
}
if (n.pred > 1) tx[length(tx)+1] <- ""
# Model term in ANOVA table
mdl <- NA
if (n.pred > 0) {
rlb <- .fmtc("Model", max.c1, j="left")
mod.df <- 0
for (i in 1:n.terms) mod.df <- mod.df + smc[i,1]
md <- .fmti(mod.df, max.ln[1]-5)
mod.ss <- 0
for (i in 1:n.terms) mod.ss <- mod.ss + smc[i,2]
ms <- .fmt(mod.ss, digits_d, max.ln[2])
mod.ms <- mod.ss/mod.df
mm <- .fmt(mod.ms, digits_d, max.ln[3])
mod.f <- mod.ms/smc[nt1, 3]
mf <- .fmt(mod.f, digits_d, max.ln[4])
mod.p <- pf(mod.f, mod.df, smc[nt1,1], lower.tail=FALSE)
mp <- .fmt(mod.p, 3, 9)
tx[length(tx)+1] <- paste(rlb, md, ms, mm, mf, mp)
# if (n.pred > 1) tx[length(tx)+1] <- ""
mdl <- c(mod.df, mod.ss, mod.ms, mod.f, mod.p)
names(mdl) <- c("df", "ss", "ms", "fvalue", "pvalue")
}
# Residuals
rlb <- .fmtc(rownames(smc)[nt1], max.c1, j="left")
df <- .fmti(smc[nt1,1], max.ln[1]-5)
SS <- .fmt(smc[nt1,2], digits_d, max.ln[2])
MS <- .fmt(smc[nt1,3], digits_d, max.ln[3])
MSW <- smc[nt1,3]
tx[length(tx)+1] <- paste(rlb, df, SS, MS)
rsd <- c(smc[nt1,1], smc[nt1,2], smc[nt1,3])
names(rsd) <- c("df", "ss", "ms")
# Total
tot <- NA
if (n.pred > 0) {
rlb <- .fmtc(nm[1], max.c1, j="left")
tot.df <- mod.df + smc[nt1,1]
td <- .fmti(tot.df, max.ln[1]-5)
tot.ss <- mod.ss + smc[nt1,2]
ts <- .fmt(tot.ss, digits_d, max.ln[2])
tot.ms <- tot.ss/tot.df
tm <- .fmt(tot.ms, digits_d, max.ln[3])
tx[length(tx)+1] <- paste(rlb, td, ts, tm)
tot <- c(tot.df, tot.ss, tot.ms)
names(tot) <- c("df", "ss", "ms")
}
return(list(out_anova=tx, mdl=mdl, rsd=rsd, tot=tot, MSW=MSW))
}
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