tableone (version 0.5.0)

CreateTableOne: Create an object summarizing both categorical and continuous variables

Description

Create an object summarizing all baseline variables optionally stratifying by one or more startifying variables and performing statistical tests. The object gives a table that is easy to use in medical research papers. See also print.TableOne and summary.TableOne.

Usage

CreateTableOne(vars, strata, data, factorVars, test = TRUE,
  testApprox = chisq.test, argsApprox = list(correct = TRUE),
  testExact = fisher.test, argsExact = list(workspace = 2 * 10^5),
  testNormal = oneway.test, argsNormal = list(var.equal = TRUE),
  testNonNormal = kruskal.test, argsNonNormal = list(NULL))

Arguments

vars

Variables to be summarized given as a character vector. Factors are handled as categorical variables, whereas numeric variables are handled as continuous variables.

strata

Stratifying (grouping) variable name(s) given as a character vector. If omitted, the overall results are returned.

data

A data frame in which these variables exist. All variables (both vars and strata) must be in this data frame.

factorVars

Numerically coded variables that should be handled as categorical variables given as a character vector. If omitted, only factors are considered categorical variables. If all categorical variables in the dataset are already factors, this option is

test

If TRUE, as in the default and there are more than two groups, groupwise comparisons are performed.

testNormal

A function used to perform the normal assumption based tests. The default is oneway.test. This is equivalent of the t-test when there are only two groups.

argsNormal

A named list of arguments passed to the function specified in testNormal. The default is list(var.equal = TRUE), which makes it the ordinary ANOVA that assumes equal variance across groups.

testNonNormal

A function used to perform the nonparametric tests. The default is kruskal.test (Kruskal-Wallis Rank Sum Test). This is equivalent of the wilcox.test (Man-Whitney U test) when there are only two groups.

argsNonNormal

A named list of arguments passed to the function specified in testNonNormal. The default is list(NULL), which is just a placeholder.

testApprox

A function used to perform the large sample approximation based tests. The default is chisq.test. This is not recommended when some of the cell have small counts like fewer than 5.

argsApprox

A named list of arguments passed to the function specified in testApprox. The default is list(correct = TRUE), which turns on the continuity correction for chisq.test.

testExact

A function used to perform the exact tests. The default is fisher.test. If the cells have large numbers, it will fail because of memory limitation. In this situation, the large sample approximation based should suffice.

argsExact

A named list of arguments passed to the function specified in testExact. The default is list(workspace = 2*10^5), which specifies the memory space allocated for fisher.test.

Value

• An object of class TableOne, which really is a list of three objects.
• TableOne
  a categorical-continuous mixture data formatted and printed by the print.TableOne method
• ContTable
  an object of class ContTable, containing continuous variables only
• CatTable
  an object of class CatTable, containing categorical variables only
• The second and third objects can be then be examined with the print and summary method, for example, summary(object$CatTable) to examine the categorical variables in detail.

See Also

CreateTableOne, print.TableOne, summary.TableOne, CreateCatTable, print.CatTable, summary.CatTable, CreateContTable, print.ContTable, summary.ContTable

Examples

## Load
library(tableone)

## Load Mayo Clinic Primary Biliary Cirrhosis Data
library(survival)
data(pbc)
## Check variables
head(pbc)

## Make categorical variables factors
varsToFactor <- c("status","trt","ascites","hepato","spiders","edema","stage")
pbc[varsToFactor] <- lapply(pbc[varsToFactor], factor)

## Create a variable list
dput(names(pbc))
vars <- c("time","status","age","sex","ascites","hepato",
          "spiders","edema","bili","chol","albumin",
          "copper","alk.phos","ast","trig","platelet",
          "protime","stage")

## Create Table 1 stratified by trt
tableOne <- CreateTableOne(vars = vars, strata = c("trt"), data = pbc)

## Just typing the object name will invoke the print.TableOne method
tableOne

## Specifying nonnormal variables will show the variables appropriately,
## and show nonparametric test p-values. Specify variables in the exact
## argument to obtain the exact test p-values.
print(tableOne, nonnormal = c("bili","chol","copper","alk.phos","trig"),
      exact = c("status","stage"))

## Use the summary.TableOne method for detailed summary
summary(tableOne)

## See the categorical part only using $ operator
tableOne$CatTable
summary(tableOne$CatTable)

## See the continuous part only using $ operator
tableOne$ContTable
summary(tableOne$ContTable)

## If your work flow includes copying to Excel and Word when writing manuscripts,
## you may benefit from the quote argument. This will quote everything so that
## Excel does not mess up the cells.
print(tableOne, nonnormal = c("bili","chol","copper","alk.phos","trig"),
      exact = c("status","stage"), quote = TRUE)

## If you want to center-align values in Word, use noSpaces option.
print(tableOne, nonnormal = c("bili","chol","copper","alk.phos","trig"),
      exact = c("status","stage"), quote = TRUE, noSpaces = TRUE)