# tabmedians: Generate Summary Tables of Median Comparisons for Statistical... In tab: Functions for Creating Summary Tables 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

 ```1 2 3 4 5 6 7``` ```tabmedians(x, y, latex = FALSE, xlevels = NULL, yname = NULL, quantiles = NULL, quantile.vals = FALSE, parenth = "iqr", text.label = NULL, parenth.sep = "-", decimals = NULL, p.include = TRUE, p.decimals = c(2, 3), p.cuts = 0.01, p.lowerbound = 0.001, p.leading0 = TRUE, p.avoid1 = FALSE, overall.column = TRUE, n.column = FALSE, n.headings = TRUE, bold.colnames = TRUE, bold.varnames = FALSE, variable.colname = "Variable", print.html = FALSE, html.filename = "table1.html") ```

## Arguments

 `x` Vector of values for the categorical variable. `y` Vector of values for the continuous variable. `latex` If TRUE, object returned is formatted for printing in LaTeX using xtable [1]; if FALSE, formatted for copy-and-pasting from RStudio into a word processor. `xlevels` Optional character vector to label the levels of x, used in the column headings. If unspecified, the function uses the values that x takes on. `yname` Optional label for the continuous y variable. If unspecified, variable name of y is used. `quantiles` If specified, function compares medians of the y variable across quantiles of the x variable. For example, if x contains continuous BMI values and y contains continuous HDL cholesterol levels, setting quantiles to 3 would result in median HDL being compared across tertiles of BMI. `quantile.vals` If TRUE, labels for x show quantile number and corresponding range of the x variable. For example, Q1 [0.00, 0.25). If FALSE, labels for quantiles just show quantile number (e.g. Q1). Only used if xlevels is not specified. `parenth` Controls what values (if any) are placed in parentheses after the medians in each cell. Possible values are "none", "iqr" for difference between first and third quartiles, "range" for difference between minimum and maximum, "minmax" for minimum and maximum, "q1q3" for first and third quartiles, or "ci.90", "ci.95", or "ci.99" for confidence intervals for the medians (based on binomial probabilities if one or more groups have n less than 10, otherwise based on normal approximation to binomial). `text.label` Optional text to put after the y variable name, identifying what cell values and parentheses indicate in the table. If unspecified, function uses default labels based on parenth, e.g. Median (IQR) if parenth is "iqr". Set to "none" for no text labels. `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 table would instead be formatted as Median (Lower, Upper). `decimals` Number of decimal places for values in table. If unspecified, function uses 0 decimal places if the largest median (in magnitude) is in [1,000, Inf), 1 decimal place if [10, 1,000), 2 decimal places if [0.1, 10), 3 decimal places if [0.01, 0.1), 4 decimal places if [0.001, 0.01), 5 decimal places if [0.0001, 0.001), and 6 decimal places if [0, 0.0001). `p.include` If FALSE, statistical test is not performed and p-value is not returned. `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) will be printed to three decimal places. `p.lowerbound` Controls cut-point at which p-values are no longer printed as their value, but rather 0.99 (or similarly depending on values for p.decimals and p.cuts). `overall.column` If FALSE, column showing median of y in full sample is suppressed. `n.column` If TRUE, the table will have a column for (unweighted) sample size. `n.headings` If TRUE, the table will indicate the (unweighted) sample size overall and in each group in parentheses after the column headings. `bold.colnames` If TRUE, column headings are printed in bold font. Only applies if latex = TRUE. `bold.varnames` If TRUE, variable name in the first column of the table is printed in bold font. Only applies if latex = TRUE. `variable.colname` Character string with desired heading for first column of table, which shows the y variable name. `print.html` If TRUE, function prints a .html file to the current working directory. `html.filename` Character string indicating the name of the .html file that gets printed if print.html is set to TRUE.

## 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.

## Value

A character matrix with the requested table comparing median y across levels of x. If latex is set to TRUE, the character matrix will be formatted for inserting into a Markdown/Sweave/knitr report using the xtable package [1].

## Note

If you wish to paste your tables into Word, you can use either of these approaches:

1. Use the write.cb function in the Kmisc package [2]. If your table is stored in a character matrix named table1, use write.cb(table1) to copy the table to your clipboard. Paste the result into Word, then highlight the text and go to Insert - Table - Convert Text to Table... OK.

2. Set the print.html input to TRUE. This will result in a .html file writing to your current working directory. When you open this file, you will see a nice looking table that you can copy and paste into Word. You can control the name of this file with the html.filename input.

If you wish to use LaTeX, R Markdown, knitr, Sweave, etc., please see the package vignette for examples. In most cases, you have to set the latex input to TRUE and then use the xtable package [1].

If you have suggestions for additional options or features, or if you would like some help using any function in the package tab, please e-mail me at [email protected] Thanks!

## Author(s)

Dane R. Van Domelen

## References

1. Dahl DB (2013). xtable: Export tables to LaTeX or HTML. R package version 1.7-1, https://cran.r-project.org/package=xtable.

2. Kevin Ushey (2013). Kmisc: Kevin Miscellaneous. R package version 0.5.0. https://CRAN.R-project.org/package=Kmisc.

Acknowledgment: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0940903.

`tabfreq`, `tabmeans`, `tabmulti`, `tabglm`, `tabcox`, `tabgee`, `tabfreq.svy`, `tabmeans.svy`, `tabmedians.svy`, `tabmulti.svy`, `tabglm.svy`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35``` ```# 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) # Repeat, but show first and third quartile rather than IQR in parentheses medtable2 <- tabmedians(x = d\$Group, y = d\$BMI, parenth = "q1q3") # Compare median BMI by race, suppressing overall column and (n = ) part of headings medtable3 <- tabmedians(x = d\$Race, y = d\$BMI, overall.column = FALSE, n.headings = FALSE) # Compare median BMI by quartile of age medtable4 <- tabmedians(x = d\$Age, y = d\$BMI, quantiles = 4) # Create single table comparing median BMI and median age in control vs. treatment group medtable5 <- rbind(tabmedians(x = d\$Group, y = d\$BMI), tabmedians(x = d\$Group, y = d\$Age)) # A (usually) faster way to make the above table is to call the tabmulti function medtable6 <- tabmulti(dataset = d, xvarname = "Group", yvarnames = c("BMI", "Age"), ymeasures = "median") # medtable5 and medtable6 are equivalent all(medtable5 == medtable6) # To move medtable1 into Word, run write.cb(medtable1) to copy the table onto your # clipboard. Paste into Word, highlight the table and go to Insert - Table - Convert Text # to Table... OK. Alternatively, if you set print.html to TRUE, the function will write # a html file named html.filename to your current working directory. You can open this # file, copy the table, and paste it into Word. ```