tab (version 2.1.3)

tabmedians: Generate Summary Tables of Median Comparisons for Statistical Reports

Description

This function compares the median of a continuous variable across levels of a categorical variable and summarizes the results in a clean table for a statistical report.

Usage

tabmedians(x, y, latex = FALSE, xlevels = NULL, yname = "Y variable", decimals = 1, 
           p.decimals = c(2, 3), p.cuts = 0.01, p.lowerbound = 0.001, p.leading0 = TRUE, 
           p.avoid1 = FALSE, n = FALSE, parenth = "iqr", text.label = NULL, 
           parenth.sep = "-")

Arguments

x

Vector of values for the categorical variable.

y

Vector of values for the continuous variable.

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 continuous variable.

decimals

Number of decimal places for means and standard deviations or standard errors.

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 returned will include sample sizes in the column headings.

parenth

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 third quartiles; 'iqr' for

text.label

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)' instead.

parenth.sep

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 to ', ' the values in the

Value

• A character matrix with the requested table comparing median y across levels of x. 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

If x has two levels, a Mann-Whitney U (also known as Wilcoxon rank-sum) test is used to test whether the distribution of the continuous variable (y) differs in the two groups (x). If x has more than two levels, a Kruskal-Wallis test is used to test whether the distribution of y differs across at least two of the x groups. Both x and y can have missing values. The function drops observations with missing x or y.

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, 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 group and race
groups <- c("Control", "Treatment")
races <- c("White", "Black", "Mexican American", "Other")

# Compare median BMI in control group vs. treatment group
medtable1 <- tabmedians(x = d$group, y = d$bmi, xlevels = groups, yname = "BMI")

# Repeat, but suppress Min-Max from being shown in parentheses
medtable2 <- tabmedians(x = d$group, y = d$bmi, xlevels = groups, yname = "BMI", 
             parenth = "none")

# Compare median BMI by race and include sample size
medtable3 <- tabmedians(x = d$race, y = d$bmi, xlevels = races, yname = "BMI", n = TRUE)

# Create single table comparing median BMI and median age in control vs. treatment group
medtable4 <- rbind(tabmedians(x = d$group, y = d$bmi, xlevels = groups, yname = "BMI"),
                   tabmedians(x = d$group, y = d$age, xlevels = groups, yname = "Age"))
                   
# An easier way to make the above table is to call the tabmulti function
medtable5 <- tabmulti(dataset = d, xvarname = "group", yvarnames = c("bmi", "age"),
                      ymeasures = "median", xlevels = groups, ynames = c("BMI", "Age"))
                        
# medtable4 and medtable5 are equivalent
all(medtable4 == medtable5)

# Click on medtable1, medtable2, medtable3, medtable4, or medtable5 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.