tab (version 2.1.3)

tabfreq: Generate Frequency Tables for Statistical Reports

Description

This function creates an I-by-J frequency table and summarizes the results in a clean table for a statistical report.

Usage

tabfreq(x, y, latex = FALSE, xlevels = NULL, yname = "Y variable", ylevels = NULL, 
        test = "chi", decimals = 1, p.decimals = c(2, 3), p.cuts = 0.01, 
        p.lowerbound = 0.001, p.leading0 = TRUE, p.avoid1 = FALSE, n = FALSE, 
        compress = FALSE)

Arguments

x

Vector of values indicating group membership for columns of IxJ table.

y

Vector of values indicating group membership for rows of IxJ table.

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.

yname

Optional label for the y (row) variable.

ylevels

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

test

Controls test for association between x and y. Use "chi" for Pearson's chi-squared test, which is valid only in large samples; "fisher" for Fisher's exact test, which is valid in small or large samples; "z" for z test without continuity correction; or "z.

decimals

Number of decimal places for percentages.

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 input.

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.

compress

If y has only two levels, setting compress to TRUE will produce a single row for n (percent) for the higher level. For example, if y is sex with 0 for female, 1 for male, setting compress = TRUE will return a table with n (percent) for males only. If FALS

Value

• A character matrix with the requested frequency table. 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

NA

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

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

Examples

# Load in sample dataset d and drop rows with missing values
data(d)
d <- d[complete.cases(d), ]

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

# Compare sex distribution by group, with group as column variable
freqtable1 <- tabfreq(x = d$group, y = d$sex, xlevels = groups, ylevels = sexes, 
                      yname = "Sex")

# Same comparison, but compress table to single row and include sample size
freqtable2 <- tabfreq(x = d$group, y = d$sex, xlevels = groups, yname = "Male", 
                      compress = TRUE, n = TRUE)

# Compare sex distribution by race, with race as column variable
freqtable3 <- tabfreq(x = d$race, y = d$sex, xlevels = races, yname = "Sex", 
                      ylevels = sexes)

# Use rbind to create single table comparing sex and race in control vs. treatment group
freqtable4 <- rbind(tabfreq(x = d$group, y = d$sex, xlevels = groups, 
                            ylevels = sexes, yname = "Sex"),
                    tabfreq(x = d$group, y = d$race, xlevels = groups, 
                            ylevels = races, yname = "Race"))
                            
# An easier way to make the above table is to call the tabmulti function
freqtable5 <- tabmulti(dataset = d, xvarname = "group", yvarnames = c("sex", "race"),
                       xlevels = groups, ynames = c("Sex", "Race"), 
                       ylevels = list(sexes, races))
                        
# freqtable4 and freqtable5 are equivalent
all(freqtable4 == freqtable5)

# Click on freqtable1, freqtable2, freqtable3, freqtable4, or freqtable5 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.