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adw96 merged 1 commit into from
Apr 21, 2025
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small formatting updates before resubmitting to cran #165

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2 changes: 1 addition & 1 deletion DESCRIPTION
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Expand Up @@ -29,7 +29,7 @@ Suggests:
tidyverse,
car
VignetteBuilder: knitr
RoxygenNote: 7.3.1
RoxygenNote: 7.3.2
Encoding: UTF-8
Config/testthat/edition: 3
LazyData: true
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16 changes: 8 additions & 8 deletions R/data.R
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#' (especially heart attacks and congestive heart failure) and cerebrovascular disease
#' (especially strokes) in the U.S. elderly. More information, including a coding key,
#' is available at
#' \url{http://www.emersonstatistics.com/datasets/mri.doc}.
#' \url{https://rct-design.com/TeachingMaterials/Datasets/mri.txt}.
#'
#'
#' @format A data frame with 735 rows and 30 variables:
Expand Down Expand Up @@ -116,7 +116,7 @@
#' to their death. If 0, the number of days in \code{obstime} is the number of
#' days between that participant's MRI and September 16, 1997.} }
#'
#' @source \url{http://www.emersonstatistics.com/datasets/mri.txt}
#' @source \url{https://rct-design.com/TeachingMaterials/Datasets/mri.txt}
"mri"

#' Salary dataset
Expand All @@ -125,7 +125,7 @@
#' monthly salary each year from 1976 through 1995, as well as sex, highest degree attained,
#' year of highest degree, field, year hired, rank, and administrative duties.
#' More information, including a coding key, is available at
#' \url{http://www.emersonstatistics.com/datasets/salary.doc}.
#' \url{https://rct-design.com/TeachingMaterials/Datasets/salary.txt}.
#'
#'
#' @format A data frame with 19792 rows and 11 variables:
Expand Down Expand Up @@ -155,15 +155,15 @@
#'
#' }
#'
#' @source \url{http://www.emersonstatistics.com/datasets/salary.txt}
#' @source \url{https://rct-design.com/TeachingMaterials/Datasets/salary.txt}
"salary"

#' PSA dataset
#'
#' Data from a study of 50 men having hormonally treated prostate cancer. Includes information on
#' PSA levels, tumor characteristics, remission status, age, and disease state.
#' More information, including a coding key, is available at
#' \url{http://www.emersonstatistics.com/datasets/PSA.doc}.
#' \url{https://rct-design.com/TeachingMaterials/Datasets/psa.txt}.
#'
#'
#' @format A data frame with 50 rows and 9 variables:
Expand All @@ -189,7 +189,7 @@
#'
#' }
#'
#' @source \url{http://www.emersonstatistics.com/datasets/psa.txt}
#' @source \url{https://rct-design.com/TeachingMaterials/Datasets/psa.txt}
"psa"

#' FEV dataset
Expand All @@ -198,7 +198,7 @@
#' lung function (measured by FEV). Each row corresponds to a single clinic visit and contains
#' information on age, height, sex, FEV, and smoking status.
#' More information, including a coding key, is available at
#' \url{http://www.emersonstatistics.com/datasets/fev.doc}.
#' \url{https://rct-design.com/TeachingMaterials/Datasets/fev.txt}.
#'
#'
#' @format A data frame with 654 rows and 7 variables:
Expand All @@ -219,5 +219,5 @@
#' \item{smoke}{smoking habits ("yes" or "no")}
#' }
#'
#' @source \url{http://www.emersonstatistics.com/datasets/fev.txt}
#' @source \url{https://rct-design.com/TeachingMaterials/Datasets/fev.txt}
"fev"
42 changes: 21 additions & 21 deletions R/descrip.R
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#' corresponding to variables and strata and columns corresponding to the
#' descriptive statistics. Descriptive statistics include
#' \itemize{
#' \item{N:} { the number of observations.}
#' \item{Msng:} { the number of observations with missing values.}
#' \item{Mean:} { the mean of the nonmissing observations (this is potentially
#' a restricted mean for right-censored time-to-event data).}
#' \item{Std Dev:} { the standard deviation of the nonmissing observations
#' \item N: the number of observations.
#' \item Msng: the number of observations with missing values.
#' \item Mean: the mean of the nonmissing observations (this is potentially
#' a restricted mean for right-censored time-to-event data).
#' \item Std Dev: the standard deviation of the nonmissing observations
#' (this is potentially a restricted standard deviation for
#' right-censored time to event data).}
#' \item{Geom Mn:} { the geometric mean of the nonmissing observations
#' right-censored time to event data).
#' \item Geom Mn: the geometric mean of the nonmissing observations
#' (this is potentially a restricted geometric mean for
#' right-censored time to event data). Nonpositive values in
#' the variable will generate \code{NA}, unless \code{replaceZeroes}
#' was specified.}
#' \item{Min:} { the minimum value of the nonmissing observations (this is
#' potentially restricted for right-censored time-to-event data).}
#' \item{Quantiles:} { columns corresponding to the quantiles specified by \code{probs}
#' was specified.
#' \item Min: the minimum value of the nonmissing observations (this is
#' potentially restricted for right-censored time-to-event data).
#' \item Quantiles: columns corresponding to the quantiles specified by \code{probs}
#' (these are potentially restricted for right-censored
#' time-to-event data).}
#' \item{Max:} { the maximum value of the nonmissing observations (this is
#' potentially restricted for right-censored time-to-event data).}
#' \item{Proportions:} { columns corresponding to the proportions as specified by
#' time-to-event data).
#' \item Max: the maximum value of the nonmissing observations (this is
#' potentially restricted for right-censored time-to-event data).
#' \item Proportions: columns corresponding to the proportions as specified by
#' \code{above}, \code{below}, \code{labove}, \code{rbelow},
#' \code{lbetween}, \code{rbetween}, \code{interval},
#' \code{linterval}, \code{rinterval}, and \code{lrinterval}.}
#' \item{restriction:} { the threshold for restricted means, standard deviations,
#' and geometric means.}
#' \item{firstEvent:} { the time of the first event for censored time-to-event variables.}
#' \item{lastEvent:} { the time of the last event for censored time-to-event variables.}
#' \item{isDate:} { an indicator that the variable is a \code{Date} object.}
#' \code{linterval}, \code{rinterval}, and \code{lrinterval}.
#' \item restriction: the threshold for restricted means, standard deviations,
#' and geometric means.
#' \item firstEvent: the time of the first event for censored time-to-event variables.
#' \item lastEvent: the time of the last event for censored time-to-event variables.
#' \item isDate: an indicator that the variable is a \code{Date} object.
#' }
#'
#' @examples
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8 changes: 4 additions & 4 deletions README.Rmd
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Expand Up @@ -46,17 +46,17 @@ You can install the development version of `rigr` from GitHub using the code bel

If this produces an error, please run `install.packages("remotes")` first then try the above line again.

`rigr` is maintained by the [StatDivLab](http://statisticaldiversitylab.com/), but relies on community support to log issues and implement new features. Is there a method you would like to have implemented? Please submit a pull request or start a [discussion](https://github.com/statdivlab/rigr/discussions/)!
`rigr` is maintained by the [StatDivLab](https://statdivlab.github.io/), but relies on community support to log issues and implement new features. Is there a method you would like to have implemented? Please submit a pull request or start a [discussion](https://github.com/statdivlab/rigr/discussions/)!

## Documentation

Examples of how to use the main functions in `rigr` are provided in three vignettes. One details the `regress` function and its utilities, one details the `descrip` function for descriptive statistics, and the third details functions used for one- and two-sample inference, including `ttest`, `wilcoxon`, and `proptest`.

## Humans

Maintainer: [Amy Willis](http://statisticaldiversitylab.com/)
Maintainer: [Amy Willis](https://statdivlab.github.io/)

Authors: [Scott S Emerson](http://www.emersonstatistics.com/), [Brian D Williamson](https://bdwilliamson.github.io/), [Charles Wolock](https://cwolock.github.io/), [Taylor Okonek](https://taylorokonek.github.io/), [Yiqun T Chen](https://yiqunchen.github.io/), [Jim Hughes](https://www.biostat.washington.edu/people/james-hughes), [Amy Willis](http://statisticaldiversitylab.com/), [Andrew J Spieker](https://www.vumc.org/biostatistics/person/andrew-spieker) and Travis Y Hee Wai.
Authors: [Scott S Emerson](http://www.emersonstatistics.com/), [Brian D Williamson](https://bdwilliamson.github.io/), [Charles Wolock](https://cwolock.github.io/), [Taylor Okonek](https://taylorokonek.github.io/), [Yiqun T Chen](https://yiqunchen.github.io/), [Jim Hughes](https://www.biostat.washington.edu/people/james-hughes), [Amy Willis](https://statdivlab.github.io/), [Andrew J Spieker](https://www.vumc.org/biostatistics/person/andrew-spieker) and Travis Y Hee Wai.

## Issues

Expand All @@ -66,4 +66,4 @@ Do you have a **question**? Please first check out the vignettes, then please po

## Code of Conduct

Please note that the rigr project is released with a [Contributor Code of Conduct](<https://statdivlab.github.io/rigr/CODE_OF_CONDUCT.html).> By contributing to this project, you agree to abide by its terms.
Please note that the rigr project is released with a [Contributor Code of Conduct](https://statdivlab.github.io/rigr/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
77 changes: 58 additions & 19 deletions README.md
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<!-- README.md is generated from README.Rmd. Please edit that file -->

<!-- README.md is generated from README.Rmd. Please edit that file -->
<!-- badges: start -->

[![CRAN status](https://www.r-pkg.org/badges/version/rigr)](https://CRAN.R-project.org/package=rigr) [![R-CMD-check](https://github.com/statdivlab/rigr/workflows/R-CMD-check/badge.svg)](https://github.com/statdivlab/rigr/actions) [![codecov](https://codecov.io/gh/statdivlab/rigr/branch/main/graph/badge.svg)](https://app.codecov.io/gh/statdivlab/rigr)
[![CRAN
status](https://www.r-pkg.org/badges/version/rigr)](https://CRAN.R-project.org/package=rigr)
[![R-CMD-check](https://github.com/statdivlab/rigr/workflows/R-CMD-check/badge.svg)](https://github.com/statdivlab/rigr/actions)
[![codecov](https://codecov.io/gh/statdivlab/rigr/branch/main/graph/badge.svg)](https://app.codecov.io/gh/statdivlab/rigr)

<!-- badges: end -->

# `rigr`: Regression, Inference, and General Data Analysis Tools for R

## Introduction

`rigr` is an `R` package to streamline data analysis in `R`. Learning both `R` and introductory statistics at the same time can be challenging, and so we created `rigr` to facilitate common data analysis tasks and enable learners to focus on statistical concepts.

`rigr`, formerly known as [`uwIntroStats`](https://CRAN.R-project.org/package=uwIntroStats), provides easy-to-use interfaces for descriptive statistics, one- and two-sample inference, and regression analyses. `rigr` output includes key information while omitting unnecessary details that can be confusing to beginners. Heteroskedasticity-robust (“sandwich”) standard errors are returned by default, and multiple partial F-tests and tests for contrasts are easy to specify. A single regression function (`regress()`) can fit both linear models, generalized linear models, and proportional hazards models, allowing students to more easily make connections between different classes of models.
`rigr` is an `R` package to streamline data analysis in `R`. Learning
both `R` and introductory statistics at the same time can be
challenging, and so we created `rigr` to facilitate common data analysis
tasks and enable learners to focus on statistical concepts.

`rigr`, formerly known as
[`uwIntroStats`](https://CRAN.R-project.org/package=uwIntroStats),
provides easy-to-use interfaces for descriptive statistics, one- and
two-sample inference, and regression analyses. `rigr` output includes
key information while omitting unnecessary details that can be confusing
to beginners. Heteroskedasticity-robust (“sandwich”) standard errors are
returned by default, and multiple partial F-tests and tests for
contrasts are easy to specify. A single regression function
(`regress()`) can fit both linear models, generalized linear models, and
proportional hazards models, allowing students to more easily make
connections between different classes of models.

## Installation

You can install the stable release of `rigr` from CRAN as follows:

install.packages("rigr")

You can install the development version of `rigr` from GitHub using the code below. The installment is through the `R` package `remotes`.
You can install the development version of `rigr` from GitHub using the
code below. The installment is through the `R` package `remotes`.

#> Using GitHub PAT from the git credential store.
#> Skipping install of 'rigr' from a github remote, the SHA1 (8b901ee9) has not changed since last install.
#> Use `force = TRUE` to force installation

# run the following code to make sure that the remote package it installed
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
# install the package
remotes::install_github("statdivlab/rigr")
If this produces an error, please run `install.packages("remotes")`
first then try the above line again.

`rigr` is maintained by the [StatDivLab](http://statisticaldiversitylab.com/), but relies on community support to log issues and implement new features. Is there a method you would like to have implemented? Please submit a pull request or start a [discussion](https://github.com/statdivlab/rigr/discussions/)!
`rigr` is maintained by the [StatDivLab](https://statdivlab.github.io/),
but relies on community support to log issues and implement new
features. Is there a method you would like to have implemented? Please
submit a pull request or start a
[discussion](https://github.com/statdivlab/rigr/discussions/)!

## Documentation

Examples of how to use the main functions in `rigr` are provided in three vignettes, available [here](https://statdivlab.github.io/rigr/). One details the `regress` function and its utilities, one details the `descrip` function for descriptive statistics, and the third details functions used for one- and two-sample inference, including `ttest`, `wilcoxon`, and `proptest`.
Examples of how to use the main functions in `rigr` are provided in
three vignettes. One details the `regress` function and its utilities,
one details the `descrip` function for descriptive statistics, and the
third details functions used for one- and two-sample inference,
including `ttest`, `wilcoxon`, and `proptest`.

## Humans

Maintainer: [Amy Willis](http://statisticaldiversitylab.com/)
Maintainer: [Amy Willis](https://statdivlab.github.io/)

Authors: [Scott S Emerson](http://www.emersonstatistics.com/), [Brian D Williamson](https://bdwilliamson.github.io/), [Charles Wolock](https://cwolock.github.io/), [Taylor Okonek](https://taylorokonek.github.io/), [Yiqun T Chen](https://yiqunchen.github.io/), [Jim Hughes](https://www.biostat.washington.edu/people/james-hughes), [Amy Willis](http://statisticaldiversitylab.com/), [Andrew J Spieker](https://www.vumc.org/biostatistics/person/andrew-spieker) and Travis Y Hee Wai.
Authors: [Scott S Emerson](http://www.emersonstatistics.com/), [Brian D
Williamson](https://bdwilliamson.github.io/), [Charles
Wolock](https://cwolock.github.io/), [Taylor
Okonek](https://taylorokonek.github.io/), [Yiqun T
Chen](https://yiqunchen.github.io/), [Jim
Hughes](https://www.biostat.washington.edu/people/james-hughes), [Amy
Willis](https://statdivlab.github.io/), [Andrew J
Spieker](https://www.vumc.org/biostatistics/person/andrew-spieker) and
Travis Y Hee Wai.

## Issues

If you encounter any **bugs**, please [file an issue](https://github.com/statdivlab/rigr/issues/). Better yet, [submit a pull request](https://github.com/statdivlab/rigr/pulls/)!
If you encounter any **bugs**, please [file an
issue](https://github.com/statdivlab/rigr/issues/). Better yet, [submit
a pull request](https://github.com/statdivlab/rigr/pulls/)!

Do you have a **question**? Please first check out the vignettes, then please post on the [Discussions](https://github.com/statdivlab/rigr/discussions/).
Do you have a **question**? Please first check out the vignettes, then
please post on the
[Discussions](https://github.com/statdivlab/rigr/discussions/).

## Code of Conduct

Please note that the rigr project is released with a [Contributor Code of Conduct](<https://statdivlab.github.io/rigr/CODE_OF_CONDUCT.html).> By contributing to this project, you agree to abide by its terms.
Please note that the rigr project is released with a [Contributor Code
of Conduct](https://statdivlab.github.io/rigr/CODE_OF_CONDUCT.html). By
contributing to this project, you agree to abide by its terms.
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