arsenal v2.0.0

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An Arsenal of 'R' Functions for Large-Scale Statistical Summaries

An Arsenal of 'R' functions for large-scale statistical summaries, which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and which use formulas and versatile summary statistics for summary tables and models. The primary functions include tableby(), a Table-1-like summary of multiple variable types 'by' the levels of one or more categorical variables; paired(), a Table-1-like summary of multiple variable types paired across two time points; modelsum(), which performs simple model fits on one or more endpoints for many variables (univariate or adjusted for covariates); freqlist(), a powerful frequency table across many categorical variables; compare.data.frame(), the S3 method for comparing data.frames; and write2(), a function to output tables to a document.

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Overview

The goal of library(arsenal) is to make statistical reporting easy. It includes many functions which the useR will find useful to have in his/her "arsenal" of functions. There are, at this time, 6 main functions, documented below. Each of these functions is motivated by a local SAS macro or procedure of similar functionality.

Note that arsenal v2.0.0 may not be backwards compatible with previous versions. See the NEWS file for more details.

The tableby() Function

tableby() is a function to easily summarize a set of independent variables by one or more categorical variables. Optionally, an appropriate test is performed to test the distribution of the independent variables across the levels of the categorical variable. Options for this function are easily controlled using tableby.control().

The tableby() output is easily knitted in an Rmarkdown document or displayed in the command line using the summary() function. Other S3 methods are implemented for objects from tableby(), including print(), [, as.data.frame(), and merge().

The paired() Function

paired() is a function to easily summarize a set of independent variables across two time points. Optionally, an appropriate test is performed to test the distribution of the independent variables across the time points. Options for this function are easily controlled using paired.control().

The paired() output is easily knitted in an Rmarkdown document or displayed in the command line using the summary() function. It has the same S3 methods as tableby(), since it's a special case of the tableby() object.

The modelsum() Function

modelsum() is a function to fit and summarize models for each independent variable with one or more response variables, with options to adjust for covariates for each model. Options for this function are easily controlled using modelsum.control().

The modelsum output is easily knitted in an Rmarkdown document or displayed in the command line using the summary() function. Other S3 methods are implemented for objects from modelsum(), including print(), [, as.data.frame(), and merge().

The freqlist() Function

freqlist() is a function to approximate the output from SAS's PROC FREQ procedure when using the /list option of the TABLE statement. Options for this function are easily controlled using freq.control().

The freqlist() output is easily knitted in an Rmarkdown document or displayed in the command line using the summary() function. Other S3 methods are implemented for objects from freqlist(), including print(), [, as.data.frame(), and merge().

The compare.data.frame() Function

compare.data.frame() is the S3 method for comparing two data.frames and reporting any differences between them, much like SAS's PROC COMPARE procedure.

The compare.data.frame() output is easily knitted in an Rmarkdown document or displayed in the command line using the summary() function. Other S3 methods are implemented for objects of class "compare.data.frame", including print() and diffs().

The write2*() Family of Functions

write2word(), write2pdf(), and write2html() are functions to output a table into a document, much like SAS's ODS procedure. The S3 method behind them is write2(). There are methods implemented for tableby(), modelsum(), freqlist(), and compare(), and also methods for knitr::kable(), xtable::xtable(), and pander::pander_return(). Another option is to coerce an object using verbatim() to print out the results monospaced (as if they were in the terminal)--the default method does this automatically. To output multiple tables into a document, simply make a list of them and call the same function as before. A YAML header can be added using yaml(). Code chunks can be written using code.chunk().

For more information, see vignette("write2").

Other Notable Functions

  • keep.labels() keeps the 'label' attribute on an R object when subsetting.

  • formulize() is a shortcut to collapse variable names into a formula.

  • mdy.Date() and Date.mdy() convert numeric dates for month, day, and year to Date object, and vice versa.

  • is.Date: tests if an object is a date.

  • %nin% tests for "not in", the negation of %in%.

  • allNA() tests for all elements being NA, and includeNA() makes NAs explicit values.

Functions in arsenal

Name Description
arsenal_table arsenal tables with common structure
paired.internal Helper functions for paired
as.data.frame.freqlist as.data.frame.freqlist
formulize formulize
freq.control Control settings for freqlist function
reexports Objects exported from other packages
as.data.frame.modelsum as.data.frame.modelsum
compare.data.frame Compare two data.frames and report differences
summary.compare The summary method for a compare.data.frame object
NA.operations Some functions to handle NAs
comparison.control Control settings for `compare` function
as.data.frame.tableby as.data.frame.tableby
%nin% Not in
tableby.control Control settings for tableby function
freqlist freqlist
tableby.internal Helper functions for tableby
arsenal An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
freqlist.internal Helper functions for freqlist
modelsum.family Family functions for modelsum
mdy.Date Convert numeric dates to Date object, and vice versa
diffs Extract differences
comparison.tolerances Comparison tolerances
mockstudy Mock study data for examples
modelsum.internal Helper functions for modelsum
internal.functions Split a string into pieces intelligently
summary.tableby The summary method for a tableby object
write2 write2
tableby Summary Statistics of a Set of Independent Variables by a Categorical Variable
write2.internal Helper functions for write2
write2specific write2word, write2html, write2pdf
paired Summary Statistics of a Set of Independent Variables Paired Across Two Timepoints
padjust Adjust P-values for Multiple Comparisons
tableby.stats tableby Summary Statistics Functions
tableby.stats.internal Internal tableby functions
yaml Include a YAML header in write2
keep.labels Keep Labels
labels Labels
modelsum.control Control settings for modelsum function
modelsum Fit models over each of a set of independent variables with a response variable
summary.freqlist summary.freqlist
summary.modelsum Summarize a modelsum object.
paired.control Control settings for paired function
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Vignettes of arsenal

Name
compare.Rmd
freqlist.Rmd
labels.Rmd
modelsum.Rmd
paired.Rmd
tableby.Rmd
write2.Rmd
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Last month downloads

Details

Date 2019-01-15
URL https://github.com/eheinzen/arsenal, https://cran.r-project.org/package=arsenal
BugReports https://github.com/eheinzen/arsenal/issues
VignetteBuilder knitr
License GPL (>= 2)
RoxygenNote 6.1.1
LazyData true
Encoding UTF-8
NeedsCompilation no
Packaged 2019-01-16 02:39:41 UTC; m144326
Repository CRAN
Date/Publication 2019-01-16 05:30:02 UTC

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