sumtbl: Summary Statistics Table

In haozhu233/ifaR.handtools: A collection of reusable R functions used in clinical research

Description

This function will generate a common statistical summary table after you select a dataset, select targeting variables, select grouping variables, select whether you want number, mean, standard deviation and quantile.

Usage

sumtbl(dataset, variable, grp.by, n = F, mu = F, s = F, q = NULL,
  q.type = 8, mdn = F, mnm = F, sem = F, round.N = 3)

Arguments

dataset	Select the dataset you are working on
variable	Select the variables you want to analyze
grp.by	Select grouping variables
n	Whether the number of non-missing/null values will be displayed
mu	Whether the value of mean will be calculated
s	Whether the value of standard deviation will be calculated
q	A list of quantiles
q.type	Quantile type
round.N	Round digits

Examples

library(data.table)
library(ifaR.handtool)
dt<-data.table(grp=rep(c("Control", "Treatment"), each=50),
               time=rep(c("Base", "Follow", "Base", "Follow"), each=25),
               age=rnorm(100, mean=65, sd=10),bmi=rnorm(100, mean=28, sd=4),
               leanmass=rnorm(100, mean=65, sd=6))
dt$leanmass[95]<-NA

sumtbl(dt, c("age", "bmi"), c("grp"), n=F, mu=T, s=T, q=c(.25, .5, .75))
sumtbl(dt, c("age", "bmi", "leanmass"), c("grp", "time"), n=T, mu=T, s=T, q=c(.25, .5, .75))

haozhu233/ifaR.handtools documentation built on May 17, 2019, 2:30 p.m.