Nothing
.OneGroup <-
function(Y, Ynm, mu=NULL, n=NULL, m=NULL, s=NULL, brief, bw1,
from.data, conf_level, alternative, digits_d, mmd, msmd,
Edesired, paired, graph, xlab, line_chart, show_title, quiet,
pdf_file, width, height, ...) {
# get lab_x_cex lab_y_cex
lab_cex <- getOption("lab_cex")
lab_x_cex <- getOption("lab_x_cex")
lab_x_cex <- ifelse(is.null(lab_x_cex), lab_cex, lab_x_cex)
adj <- .RSadj(lab_cex=lab_x_cex); lab_x_cex <- adj$lab_cex
# get variable labels if exist plus axes labels
gl <- .getlabels(xlab=NULL, ylab=xlab, main=NULL, lab_x_cex=lab_x_cex,
graph.win=FALSE) # # graphics window not yet set-up
x.name <- gl$yn; x.lbl <- gl$yl; x.lab <- gl$yb
main.lab <- gl$mb
sub.lab <- gl$sb
# get variable label if exists (redundant with above
gl <- .getlabels(graph.win=FALSE) # graphics window not yet set-up
y.lbl <- gl$yl
if ( (!is.null(y.lbl)) && !quiet) {
cat("Response Variable: ", Ynm, ", ", as.character(y.lbl), sep="", "\n")
cat("\n")
}
if (!brief && !quiet) cat("\n------ Describe ------\n\n")
if (from.data) {
n <- sum(!is.na(Y))
n.miss <- sum(is.na(Y))
Y <- na.omit(Y)
m <- mean(Y)
s <- sd(Y)
v <- var(Y)
}
else {
v <- s^2
}
clpct <- paste(toString(round((conf_level)*100, 2)), "%", sep="")
dig.smr.d <- ifelse (from.data, digits_d, digits_d - 1)
if (!quiet) {
if (Ynm != "Y") cat(Ynm, ": ", sep="")
if (from.data) cat(" n.miss = ", n.miss, ", ", sep="")
cat("n = ", n, ", mean = ", .fmt(m, dig.smr.d),
", sd = ", .fmt(s, dig.smr.d), sep="", "\n")
if
(brief) cat("\n")
else {
if (from.data) {
cat("\n\n------ Normality Assumption ------\n\n")
# Normality
if (n > 30) {
cat("Sample mean assumed normal because n > 30, so no test needed.",
sep="", "\n")
}
else {
cat("Null hypothesis is a normal distribution", sep="")
if (Ynm != "Y") cat(" of ", Ynm, ".", sep="") else cat(".")
cat("\n")
if (n > 2 && n < 5000) {
nrm1 <- shapiro.test(Y)
W.1 <- round(nrm1$statistic,min(4,digits_d+1))
p.val1 <- round(nrm1$p.value,min(4,digits_d))
cat(nrm1$method, ": W = ", W.1, ", p-value = ", p.val1,
sep="", "\n")
}
else
cat("Sample size out of range for Shapiro-Wilk normality test.",
"\n")
}
}
}
if (!brief) cat("\n\n------ Infer ------\n\n")
} # end !quiet
# t-test
if (alternative == "two_sided")
alt <- "two.sided"
else
alt <- alternative
if (!is.null(mu)) m.dist <- m - mu
df <- n - 1
sterr <- s * sqrt(1/n)
if (alternative == "two_sided")
tcut <- qt((1-conf_level)/2, df=df, lower.tail=FALSE)
else if (alternative == "less")
tcut <- qt(1-conf_level, df=df, lower.tail=FALSE)
else if (alternative == "greater")
tcut <- qt(1-conf_level, df=df, lower.tail=TRUE)
if (from.data) {
if (!is.null(mu)) mu.null <- mu else mu.null <- 0
ttest <- t.test(Y, conf.level=conf_level, alternative=alt, mu=mu.null)
df <- ttest$parameter
lb <- ttest$conf[1]
ub <- ttest$conf[2]
E <- (ub-lb)/2
if (!is.null(mu)) {
tvalue <- ttest$statistic
pvalue <- ttest$p.value
}
} # end from.data
else {
E <- tcut * sterr
lb <- m - E
ub <- m + E
if (!is.null(mu)) {
tvalue <- m.dist/sterr
if (alternative == "two_sided")
pvalue <- 2 * pt(abs(tvalue), df=df, lower.tail=FALSE)
else if (alternative == "less")
pvalue <- pt(abs(tvalue), df=df, lower.tail=FALSE)
else if (alternative == "greater")
pvalue <- pt(abs(tvalue), df=df, lower.tail=TRUE)
}
}
# difference from mu and standardized mean difference
if (!is.null(mu)) {
mdiff <- m - mu
smd <- abs(mdiff/s)
}
if (!quiet) {
cat("t-cutoff for 95% range of variation: tcut = ", .fmt(tcut,3), "\n")
cat("Standard Error of Mean: SE = ", .fmt(sterr), "\n\n")
if (!is.null(mu)) {
if (alt != "two.sided")
cat("\nAlternative hypothesis: Population mean difference is", alt,
"than", mu.null, "\n")
cat("Hypothesized Value H0: mu =", mu, "\n")
txt <- "Hypothesis Test of Mean: t-value = "
cat(txt, .fmt(tvalue,3), ", df = ", df, ", p-value = ", .fmt(pvalue,3),
sep="", "\n\n")
}
cat("Margin of Error for ", clpct, " Confidence Level: ", .fmt(E),
sep="", "\n")
txt <- " Confidence Interval for Mean: "
cat(clpct, txt, .fmt(lb), " to ", .fmt(ub), sep="", "\n")
# difference from mu and standardized mean difference
if (!is.null(mu)) {
if (!brief) cat("\n\n------ Effect Size ------\n\n") else cat("\n")
cat("Distance of sample mean from hypothesized: " , .fmt(mdiff), "\n",
"Standardized Distance, Cohen's d: ", .fmt(smd),
sep="", "\n")
}
# needed sample size from Edesired
if (!is.null(Edesired)) {
zcut <- qnorm((1-conf_level)/2)
ns <- ((zcut*s)/Edesired)^2
n.needed <- ceiling(1.132*ns + 7.368)
cat("\n\n------ Needed Sample Size ------\n\n")
if (Edesired > E) {
cat("Note: Desired margin of error,", .fmt(Edesired),
"is worse than what was obtained,", .fmt(E), "\n\n")
}
cat("Desired Margin of Error: ", .fmt(Edesired), "\n")
cat("\n")
cat("For the following sample size there is a 0.9 probability of obtaining\n")
cat("the desired margin of error for the resulting 95% confidence interval.\n")
cat("-------\n")
cat("Needed sample size: ", n.needed, "\n")
cat("\n")
cat("Additional data values needed: ", n.needed-n, "\n")
}
} # end !quiet
# graphs
if (graph) {
# keep track of the number of plots in this routine, see if manage graphics
plt.i <- 0
plt.title <- character(length=0)
manage.gr <- .graphman()
if (is.null(pdf_file)) {
if (manage.gr) {
n.win <- 0
if (!is.null(mu)) n.win <- n.win + 1
if (paired) n.win <- n.win + 1
if (line_chart) n.win <- n.win + 1
if (n.win > 0) {
.graphwin(n.win, width, height)
i.win <- 2 # start first graphics window on 3
orig.params <- par(no.readonly=TRUE)
on.exit(par(orig.params))
}
}
}
if (line_chart) {
if (!is.null(pdf_file))
pdf(file=paste("LineChart_",Ynm,".pdf",sep=""), width=width, height=height)
if (manage.gr) {
i.win <- i.win + 1
dev.set(which=i.win)
}
plt.i <- plt.i + 1
plt.title[plt.i] <- paste("Sequentially Plotted Data for", Ynm)
.lc.main(Y, type=NULL,
col.line=getOption("pt_color"), col.area=NULL, col.box="black",
col_color=getOption("pt_color"),
col_fill=getOption("bar_fill_cont"), shape_pts=21,
col.bg=getOption("panel_fill"), lab_cex=getOption("lab_cex"),
axis_cex=0.75, col.axis="gray30", rotate_x=0, rotate_y=0, offset=.5,
xy_ticks=TRUE, line_width=1.1,
xlab=NULL, ylab=NULL, main=plt.title[plt.i], sub=NULL, cex=NULL,
time_start=NULL, time_by=NULL, time_reverse=FALSE,
center_line="default", quiet=TRUE)
if (!is.null(pdf_file)) {
dev.off()
.showfile(paste("LineChart_", Ynm, ".pdf", sep=""),
paste("line chart of", Ynm))
}
}
if (!is.null(mu)) {
if (manage.gr) {
i.win <- i.win + 1
dev.set(which=i.win)
}
plt.i <- plt.i + 1
plt.title[plt.i] <- "One-Group Plot"
if (paired) x.lab <- "Difference"
if (!is.null(pdf_file)) {
if (!grepl(".pdf", pdf_file))
pdf_file <- paste(pdf_file, ".pdf", sep="")
.opendev(pdf_file, width, height)
}
.OneGraph(Y, bw1, Ynm, digits_d, brief,
n, m, mu, mdiff, s, smd, mmd, msmd,
clpct, tvalue, pvalue, ub, lb, x.lab, alt, show_title, quiet)
if (!is.null(pdf_file)) {
dev.off()
.showfile(pdf_file, paste("density plot of", Ynm))
}
}
return(list(i=plt.i, ttl=plt.title))
} # end if graph
} # End One Group
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