Description: A common task faced by researchers is the creation of APA style
(i.e., American Psychological Association style) tables from statistical
output. In R a large number of function calls are often needed to obtain all of
the desired information for a single APA style table. As well, the process of
manually creating APA style tables in a word processor is prone to transcription
errors. This package creates Word files (.doc files) containing APA style tables
for several types of analyses. Using this package minimizes transcription errors
and reduces the number commands needed by the user.
Imports: rockchalk, stats, utils, methods, MBESS, car, broom, dplyr,
Suggests: testthat, knitr, rmarkdown, psych

Imports: stats, utils, methods, MBESS, car, broom, dplyr

Imports: stats, utils, methods, car, broom, dplyr, boot, tibble
Suggests: testthat, knitr, rmarkdown, psych, ez, tidyverse, MBESS

Suggests: testthat, knitr, rmarkdown, psych, ez, tidyr, forcats, MBESS

Imports: stats, utils, methods, car, broom, dplyr, boot, tibble, MBESS

Title: Create R Markdown Text for Results in the Style of the American
Description: Create APA style text from analyses for use within R Markdown documents. Descriptive statistics, confidence intervals, and cell sizes are reported.

person(family = "The Apache Software Foundation",
Description: R interface for 'Apache Sedona' based on 'sparklyr'
SystemRequirements: 'Apache Spark' 2.4.x or 3.x

Description: Functions for age-period-cohort analysis. The data can be organised in matrices indexed by age-cohort, age-period or cohort-period. The data can include dose and response or just doses.  The statistical model is a generalized linear model (GLM) allowing for 3,2,1 or 0 of the age-period-cohort factors. The canonical parametrisation of Kuang, Nielsen and Nielsen (2008) is used. Thus, the analysis does not rely on ad hoc identification.

Description: Functions for age-period-cohort analysis. The data can be organised in matrices indexed by age-cohort, age-period or cohort-period. The data can include dose and response or just doses. The statistical model is a generalized linear model (GLM) allowing for 3,2,1 or 0 of the age-period-cohort factors. The canonical parametrisation of Kuang, Nielsen and Nielsen (2008) <DOI:10.1093/biomet/asn026> is used. Thus, the analysis does not rely on ad hoc identification.