In isubirana/compareGroups: Descriptive Analysis by Groups

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE, comment="")
library(knitr)

compareGroups

package to create descriptive tables

• Overview
• News
• Package installation
• Costumizing the table
• Visual exploration
• Exporting the table
• Stratified tables
• Odds Ratios and Hazard Ratios
• Web-based User Interface
• Citation

Overview

compareGroups is an R package available on CRAN which performs descriptive tables displaying means, standard deviation, quantiles or frequencies of several variables. Also, p-value to test equality between groups is computed using the appropiate test.

With a very simple code, nice, compact and ready-to-publish descriptives table are displayed on R console. They can also be exported to different formats, such as Word, Excel, PDF or inserted in a R-Sweave or R-markdown document.

You will find an extensive manual describing all compareGropus capabilities with real examples in the vignette.

Also, compareGroups package has been published in Journal of Statistical Software [Subirana et al, 2014 http://www.jstatsoft.org/v57/i12/.].

News

Version 4.1

• Compute confidence intervals of means, medians, proporcions or incidences

• Proportions can be computed by rows as well as by columns, or by combinations of rows and columns (i.e. to sum up 100%).

• New argument "position" to place tables justified to the left, centered or to the right using Rmarkdown.

• When exporting tables to Excel, export2xls no longer uses xlsx package and uses write_xlsx function from writexl pacakge, instead.

• The web-based user interface , cGroupsWUI(), has been improved and updated.

Version 4.0

• New argument var.equal to consider unequal variances when performing ANOVA tests.

• Date variables are supported.

• New strataTable function: to create stratified tables without having to use cbind.

• package vignette improved.

• New descrTable function that builds a descriptive table in one step.

• New options added in export2md, to export tables in nicer format.

• New options added in compareGroups to control permutated chisquared test.

Package installation

Install the compareGroups package from CRAN and then load it by typing:

install.packages("compareGroups")

or from github to get the latest version

library(devtools)
devtools::install_github(repo = "isubirana/compareGroups")

Costumizing the table

In the following table, some variables from the REGICOR ("Registre Gironí del Cor") project (www.regicor.cat) data set available in the package are analysed. We illustrate the syntax of compareGroups functions to display tables containing descriptives or possible tests to compare groups.

Following, to describe all the variables of the data set just type:

library(compareGroups) # load compareGroups package
data(regicor) # load example data
descrTable(regicor)

Example

In the following table, variables are described by year of recruitment. Some variables such as tryglicerides (triglyc), physical activity (phyact), days to cardiovascular event (tocv) or days to death (todeath) have been treated as non-normal distributed, and medians and quantiles within square brackets instead of means and standard deviations within round brackets are displayed. Also, individuals older than 55 years old are selected. Appropiate tests to compare means, medians or proportions are performed. For those binary variables of type "yes/no", you may desire to show only the proportion of "yes" category without showing "yes" but only the variable name or label. For example, for "Cholesterol treatment" you may want to see simply "Cholesterol treatment" instead of "Cholesterol treatment: yes". This is possible by hide.no argument. Finally, patient id (id) has been removed using - from the formula environment.

Note the simplicity of the syntax. Also, note the use of formula to select the variables, and the use of subset to filter some individuals as usual in many other R funcions.

tab <- descrTable(year ~ . - id, regicor, hide.no="no", method=c(triglyc=2, tocv=2, todeath=2), 
                  subset=age>55)
tab

Also, number of decimals and much more options can be changed to costumize the table as desired (see the package manual)

Visual exploration

With compareGroups it is also possible to visualize the distribution of analysed variables. This can be done by the plot function applied on the table:

plot(tab["sex"]) # barplot
plot(tab["age"]) # histogram and normality plot

plot(tab["sex"],file="./man/figures/var1") # barplot
plot(tab["age"],file="./man/figures/var1") # histogram and normality plot

| | | |:-----------------------------------:|:------------------------------------:| | | |

Exporting the table

Once the table is created, it can be printed on the R console in a nice and compact format, or it can be exported to different formats, such as PDF, Excel, Word or LaTex code.

export2pdf(tab, file = "example.pdf")
export2xls(tab, file = "example.xlsx")
export2word(tab, file = "example.docx")
export2latex(tab, file = "example.tex")

This is how the table looks like in PDF:

Also, by using export2md function a descriptive table can be inserted in a Rmarkdown chunk to be compiled in HTML, PDF or Word report. Here there is an example of a Rmarkdown compiled to HTML.

export2md(tab, strip = TRUE, first = TRUE, 
          header.background = "blue", header.color = "white", 
          caption = "Description of variables by recruitment year",
          size=10)

Stratified tables

After creating a table you may want to repeat the descriptives within stratas. For example, you may want to compare the groups for men and for women. This is very easy using the strataTable function:

# stratify by sex
tabestr <- strataTable(tab, strata="sex")

# remove sex variable from the table
tabestr[-2]

or when is complied in HTML

export2md(tabestr, strip = TRUE, first = TRUE, 
          header.background = "blue", header.color = "white", size=8)

Odds Ratios and Hazard Ratios

Using compareGroups package you can compute Odds Ratios for transversal or case-control studies, or Hazard Ratios for cohort studies

• Example of case-control study: Odds Ratios

data(SNPs)
descrTable(casco ~ .-id, SNPs, show.ratio=TRUE, show.p.overall=FALSE)[1:4]

• Example of cohort study: Hazard Ratios

# create a Surv response:
library(survival)
regicor$tcv <- Surv(regicor$tocv, regicor$cv=="Yes")

# perform descriptive table placing the Surv object as the response (left side of ~):
tab <- descrTable(tcv ~ .-id-cv-tocv, regicor, 
           method=c(triglyc=2, tocv=2, todeath=2),
           hide.no="no", ref.no="no",
           show.ratio=TRUE, show.p.overall=FALSE)

# print table on R console
print(tab, header.label=c("p.ratio"="p-value"))           

# create a Surv response:
library(survival)
regicor$tcv <- Surv(regicor$tocv, regicor$cv=="Yes")

# perform descriptive table placing the Surv object as the response (left side of ~):
tab <- descrTable(tcv ~ .-id-cv-tocv, regicor, 
           method=c(triglyc=2, tocv=2, todeath=2),
           hide.no="no", ref.no="no",
           show.ratio=TRUE, show.p.overall=FALSE)

# print table on R console
print(tab, header.label=c("p.ratio"="p-value"))          

Web-based User Interface

For those not familiar to R syntax, a Web User Interface (WUI) has been implemented using Shiny tools, which can be used remotely just accessing the compareGroups project website

Try the WUI compareGroups here

Citation

citation("compareGroups")

References

Subirana, Isaac, Héctor Sanz, and Joan Vila. 2014. “Building Bivariate Tables: The compareGroups Package for R.” Journal of Statistical Software 57 (12): 1–16. https://www.jstatsoft.org/v57/i12/.

isubirana/compareGroups documentation built on Jan. 31, 2024, 9:19 p.m.