Survey table: formatted survey estimates

The surveytable package provides short and understandable commands that generate tabulated, formatted, and rounded survey estimates. One useful function, which operates on categorical and logical variables, tabulates estimated counts and percentages with their standard errors and confidence intervals. Other functions list the variables in a survey, estimate the total population, tabulate survey subsets and variable interactions, tabulate numeric variables, tabulate rates, create or modify survey variables, perform hypothesis tests, and save the output. All of the tabulation functions check the National Center for Health Statistics (NCHS) presentation standards to flag low-precision estimates. If the surveytable code is called from an R Markdown notebook or a Quarto document, it generates HTML tables, which can be incorporated directly into documents.

Installation

You can install surveytable like so:

install.packages(c("remotes", "git2r"))
remotes::install_github("CDCgov/surveytable", upgrade = "never")

Once surveytable is available on CRAN, you will be able to install it like this:

install.packages("surveytable")

Documentation

Find the documentation for surveytable here: https://cdcgov.github.io/surveytable/

Example

Here is a basic example, to get you started.

library(surveytable)
set_survey(namcs2019sv)
#> * To adjust how counts are rounded, see ?set_count_int
#>                        _                                                                    
#> Survey name            NAMCS 2019 PUF                                                       
#> Number of variables    33                                                                   
#> Number of observations 8250                                                                 
#> Info1                  Stratified 1 - level Cluster Sampling design (with replacement)      
#> Info2                  With (398) clusters.                                                 
#> Info3                  survey::svydesign(ids = ~CPSUM, strata = ~CSTRATM, weights = ~PATWT, 
#> Info4                      data = namcs2019sv_df)
tab("AGER")
Patient age recode {NAMCS 2019 PUF}
Level Number (000) SE (000) LL (000) UL (000) Percent SE LL UL
Under 15 years 117,917 14,097 93,229 149,142 11.4 1.3 8.9 14.2
15-24 years 64,856 7,018 52,387 80,292 6.3 0.6 5.1 7.5
25-44 years 170,271 13,966 144,925 200,049 16.4 1.1 14.3 18.8
45-64 years 309,506 23,290 266,994 358,787 29.9 1.4 27.2 32.6
65-74 years 206,866 14,366 180,481 237,109 20   1.2 17.6 22.5
75 years and over 167,069 15,179 139,746 199,735 16.1 1.3 13.7 18.8
(Checked presentation standards. Nothing to report.)

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