tab (version 2.1.3)

tabmulti: Generate Multi-row Tables Comparing Means/Medians/Frequencies of Multiple Variables Across Levels of One Categorical Variable

Description

This function basically provides an alternative to making multiple calls to tabmeans, tabmedians, and tabfreq, then using rbind to combine the results into a single table.

Usage

tabmulti(dataset, xvarname, yvarnames, ymeasures = NULL, listwise.deletion = FALSE, 
         latex = FALSE, xlevels = NULL, ynames = yvarnames, ylevels = NULL, 
         freq.tests = "chi", decimals = 1, p.decimals = c(2, 3), p.cuts = 0.01, 
         p.lowerbound = 0.001, p.leading0 = TRUE, p.avoid1 = FALSE, n = FALSE, 
         se = FALSE, compress = FALSE, parenth = "iqr", text.label = NULL, 
         parenth.sep = "-")

Arguments

dataset

Data frame or matrix containing variables of interest.

xvarname

Character string with name of column variable. Should be one of colnames(dataset).

yvarnames

Character string or vector of character strings with names of row variables. Each element should be one of colnames(dataset).

ymeasures

Character string or vector of character strings indicating whether each row variable should be summarized by mean, median, or frequency. For example, if yvarnames has length three and you wish to display frequencies for the first variable, means for the s

listwise.deletion

If TRUE, observations with missing values for any row variable are excluded entirely; if FALSE, all available data is used for each comparison. If FALSE, recommend also setting n to TRUE so table shows effective sample size for each comparison.

latex

If TRUE, object returned will be formatted for printing in LaTeX using xtable [1]; if FALSE, it will be formatted for copy-and-pasting from RStudio into a word processor.

xlevels

Optional character vector to label the levels of x. If unspecified, the function uses the values that x takes on.

ynames

Optional labels for the row variables.

ylevels

Character vector or list of character vectors to label the levels of the categorical row variables.

freq.tests

Character string or vector of character strings indicating which statistical tests should be used to compare distributions of each categorical row variable across levels of the column variable. Elements can be "chi" for Pearson's chi-squared test, which i

decimals

Number of decimal places for various cell entries, such as means and percentages. Does not affect p-values.

p.decimals

Number of decimal places for p-values. If a vector is provided rather than a single value, number of decimal places will depend on what range the p-value lies in. See p.cuts.

p.cuts

Cut-point(s) to control number of decimal places used for p-values. For example, by default p.cuts is 0.1 and p.decimals is c(2, 3). This means that p-values in the range [0.1, 1] will be printed to two decimal places, while p-values in the range [0, 0.1)

p.lowerbound

Controls cut-point at which p-values are no longer printed as their value, but rather

p.leading0

If TRUE, p-values are printed with 0 before decimal place; if FALSE, the leading 0 is omitted.

p.avoid1

If TRUE, p-values rounded to 1 are not printed as 1, but as >0.99 (or similarly depending on values for p.decimals and p.cuts).

n

If TRUE, the table will have a column for sample size.

se

If TRUE, the table will present mean (standard error) rather than mean (standard deviation) for continuous row variables.

compress

If TRUE, categorical row variables with two levels will have a single row for n (percent) for the higher level. For example, if a row variable is sex, with 0 for females and 1 for males, setting compress = TRUE would result in the sex row showing n (perce

parenth

For median comparisons, controls what values (if any) are placed in parentheses after the medians in each cell. Possible choices are as follows: 'minmax' for minimum and maximum; 'range' for difference between minimum and maximum; 'q1q3' for first and thi

text.label

For median comparisons, optional text to put after the variable name. For example, if parenth is 'q1q3' and yname is 'BMI' the default label would be 'BMI, Median (Q1-Q3)'. You might prefer to set text.label to something like 'Med (Quartile 1-Quartile 3)'

parenth.sep

For median comparisons, optional character specifying the separator for the two numbers in parentheses when parenth is set to 'minmax' or 'q1q3'. The default is a dash, so values in the table are formatted as Median (Lower-Upper). If you set parenth.sep t

Value

• A character matrix comparing mean/medians/frequencies of row variables across levels of the column variable. If you click on the matrix name under "Data" in the RStudio Workspace tab, you will see a clean table that you can copy and paste into a statistical report or manuscript. If latex is set to TRUE, the character matrix will be formatted for inserting into an Sweave or Knitr report using the xtable package [1].

Details

Please see help files for tabmeans, tabmedians, and tabfreq for details on statistical tests.

References

1. Dahl DB (2013). xtable: Export tables to LaTeX or HTML. R package version 1.7-1, http://CRAN.R-project.org/package=xtable. Acknowledgment: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0940903.

See Also

tabfreq, tabmeans, tabmedians, tabglm, tabcox, tabgee, tabfreq.svy, tabmeans.svy, tabglm.svy,

Examples

# Load in sample dataset d
data(d)

# Create labels for group and race
groups <- c("Control", "Treatment")
sexes <- c("Female", "Male")
races <- c("White", "Black", "Mexican American", "Other")

# Compare age, sex, race, and BMI in control vs. treatment group, using all available
# data for each comparison
table1 <- tabmulti(dataset = d, xvarname = "group",
                   yvarnames = c("age", "sex", "race", "bmi"), xlevels = groups,
                   ynames = c("Age", "Sex", "Race", "BMI"), ylevels = list(sexes, races), 
                   n = TRUE)
                   
# Repeat, but use listwise deletion, i.e. drop observations that do not have complete
# data for all variables of interest, and suppress sample size column
table2 <- tabmulti(dataset = d, xvarname = "group",
                   yvarnames = c("age", "sex", "race", "bmi"), listwise.deletion = TRUE,
                   xlevels = groups, ynames = c("Age", "Sex", "Race", "BMI"), 
                   ylevels = list(sexes, races))
                   
# Repeat, but compare medians rather than means for BMI
table3 <- tabmulti(dataset = d, xvarname = "group", 
                   yvarnames = c("age", "sex", "race", "bmi"), 
                   ymeasures = c("mean", "freq", "freq", "median"), 
                   listwise.deletion = TRUE, xlevels = groups, 
                   ynames = c("Age", "Sex", "Race", "BMI"), ylevels = list(sexes, races))

# Click on table1, table2, or table3 in the Workspace tab of RStudio to see the tables 
# that could be copied and pasted into a report or manuscript. Alternatively, setting 
# the latex input to TRUE produces tables that can be inserted into LaTeX using the 
# xtable package.