tabmeans.svy {tab}

Create Table Comparing Group Means (for Complex Survey Data)

Description

Creates a table comparing the mean of y across levels of x.

Usage

tabmeans.svy(
  formula,
  design,
  columns = c("xgroups", "p"),
  parenth = "sd",
  sep.char = ", ",
  xlevels = NULL,
  yname = NULL,
  text.label = NULL,
  decimals = 1,
  anova.svyglm.list = NULL,
  formatp.list = NULL,
  n.headings = FALSE,
  N.headings = FALSE,
  kable = TRUE
)

Arguments

formula

Formula, e.g. BMI ~ Sex.

design

Survey design object from svydesign.

columns

Character vector specifying what columns to include. Choices for each element are "n" for total sample size, "overall" for overall mean, "xgroups" for x group means, "diff" for difference in x group means (this one and the next two are only available for binary x), "diffci" for 95 x group means, "diff.ci" for difference in group means and 95 confidence interval, and "p" for p-value.

parenth

Character string specifying what statistic to display in parentheses after the means. Choices are "none", "sd", "se", "t.ci", "z.ci", "range", and "minmax".

sep.char

Character string with separator to place between lower and upper bound of confidence intervals. Typically "-" or ", ".

xlevels

Character vector with labels for the levels of x, used in column headings.

yname

Character string with a label for the y variable.

text.label

Character string with text to put after the y variable name, identifying what cell values and parentheses represent

decimals

Numeric value specifying number of decimal places for numbers other than p-values.

anova.svyglm.list

List of arguments to pass to anova.svyglm. Only used if x has three or more levels.

formatp.list

List of arguments to pass to formatp.

n.headings

Logical value for whether to display group sample sizes in parentheses in column headings.

N.headings

Logical value for whether to display weighted sample sizes in parentheses in column headings.

kable

Logical value for whether to return a kable.

Details

Basically tabmeans for complex survey data. Relies heavily on the survey package.

Value

kable or character matrix.

Examples

# Create survey design object
library("survey")
design <- svydesign(
  data = tabsvydata,
  ids = ~sdmvpsu,
  strata = ~sdmvstra,
  weights = ~wtmec2yr,
  nest = TRUE
)

# Compare mean BMI by sex
(meanstable <- tabmeans.svy(BMI ~ Sex, design = design))