fsmry.graph: Summarize y by x graphically

In xkzhou/BTKR: Biostatistics Tools Kit in R

Summarize y by x graphically

Description

Summarize y by x graphically

Usage

fsmry.graph(y, x, type = c("scatter", "bxp", "errbar", "bar", "bar2"),
  y.plab = "", x.plab = "", ynames = NULL, xnames = NULL,
  stat.txt = NULL, loc.stat = NULL, ylim = NULL, fname = NULL,
  y.fnlab = NULL, x.fnlab = NULL, subgrp = "", withline = T,
  geomean = F, silent = T, width = 3, height = 3, mar = NULL,
  mgp = NULL, cex.bar = NULL, cex = 1, ...)

Arguments

y	A continuous variable.
x	A continuous or categorical variable.
type	a text string for the type of graph, e.g., "scatter","bxp","errbar","bar",or "bar2"
y.plab	y-axis label
x.plab	x-axis label
ynames	names for different categories of y
xnames	names for different categories of x
stat.txt	statistics to show on the graph, typically, p-value and/or correlation coefficient
loc.stat	location of the stat.txt
ylim	specify the y-axis limit if needed
fname	a text string of file name if a win-meta file is to be generated
y.fnlab	a text string of y variable name to be included in a file name
x.fnlab	a text string of x variable name to be included in a file name
subgrp	a text string of analysis cohort name to be included in a file name
withline	a logic indicator of whether to include the Tukey line in the scatter plot, default true
geomean	a logic indicator of whether to plot geometric mean/sd when plotting the errbar plot, default false
silent	a logic indicator of whether to output the mp variable generated by barplot function, default true
width	width of the graph is a win-meta file is to be generated
height	height of the graph is a win-meta file is to be generated
mar	graphical parameter
mgp	graphical parameter
cex.bar	graphical parameter for specifying text size of text above each bar
cex	graphical parameter
...	additional graphical paramter

Value

Summary graph of y by x.

Examples

set.seed(16)
dat.work <- data.frame(ht = c(rnorm(10, mean=1.72, sd=0.1), rnorm(10, mean=1.65, sd=0.1)),
                       wt = c(rnorm(10, mean=70, sd=10), rnorm(10, mean=60, sd=10)),
                       sex = factor(rep(c("Female", "Male", "Female", "Male"), c(2,8,6,4))),
                       group = factor(rep(c("grp1", "grp2"), each=10)))
cor.test(dat.work$wt, x = dat.work$ht)
fsmry.graph(y = dat.work$wt, x = dat.work$ht, type ="scatter",
            y.plab = "Weight",
            x.plab = "Height",
            stat.txt = "r=-0.24, p=0.31")
fsmry.by.grp(y = dat.work$ht, grp = dat.work$sex)
fsmry.graph(y = dat.work$ht, x = dat.work$sex, type ="bxp",
            y.plab = "Weight",
            x.plab = "Sex",
            stat.txt = "p=0.68")
fsmry.graph(y = dat.work$ht, x = dat.work$sex, type ="errbar",
            y.plab = "Weight",
            x.plab = "Sex",
            stat.txt = "p=0.66")
fsmry.graph(y = dat.work$ht, x = dat.work$sex, type ="errbar",
            y.plab = "Weight",
            stat.txt = "p=0.68",
            geomean=T)
fsmry2.by.grp(y = dat.work$sex, grp=dat.work$group, cmp.method="fisher")
fsmry.graph(y = dat.work$sex, x = dat.work$group, type ="bar",
            stat.txt = "p=0.17")
fsmry.graph(y = dat.work$sex, x = dat.work$group, type ="bar",
            xnames=c("Group1", "Group2"),
            stat.txt = "p=0.17")
fsmry.graph(y = dat.work$sex, x = dat.work$group, type ="bar2",
            xnames=c("Group1", "Group2"),
            stat.txt = "p=0.17")

xkzhou/BTKR documentation built on Feb. 1, 2023, 1:14 a.m.