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10 changes: 5 additions & 5 deletions DESCRIPTION
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@@ -1,7 +1,7 @@
Type: Package
Package: pairwiseComparisons
Title: Multiple Pairwise Comparison Tests
Version: 0.1.0.9000
Version: 0.1.0
Authors@R:
person(given = "Indrajeet",
family = "Patil",
Expand All @@ -10,10 +10,10 @@ Authors@R:
comment = c(ORCID = "0000-0003-1995-6531"))
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>
Description: Multiple pairwise comparison tests for one-way
analysis of variance designs for both between-subjects and
within-subjects designs. Currently, it supports only the most common
types of statistical analyses and tests: parametric (Welch's and
Student's t-test), nonparametric (Durbin-Conover test and
analysis of variance for both between-subjects and within-subjects
designs. Currently, it supports only the most common types of
statistical analyses and tests: parametric (Welch's and Student's
t-test), nonparametric (Durbin-Conover test and
Dwass-Steel-Crichtlow-Fligner test), robust (Yuen’s trimmed means test
).
License: GPL-3 | file LICENSE
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20 changes: 17 additions & 3 deletions R/pairwise_comparisons.R
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Expand Up @@ -32,9 +32,23 @@
#' @inheritParams stats::t.test
#' @inheritParams WRS2::rmmcp
#'
#' @return A tibble dataframe containing groups levels being compared with each
#' other and *p*-value corresponding to this comparison and a label for this
#' *p*-value, in case this needs to be displayed in `geom_ggsignif`.
#' @return A tibble dataframe containing two columns corresponding to group
#' levels being compared with each other (`group1` and `group2`) and `p.value`
#' column corresponding to this comparison. The dataframe will also contain a
#' `p.value.label` column containing a *label* for this *p*-value, in case
#' this needs to be displayed in `geom_ggsignif`. In addition to these common
#' columns across the different types of statistics, there will be additional
#' columns specific to the `type` of test being run.
#'
#' The `significance` column will display asterisks to indicate significance
#' of *p*-values in the American Psychological Association (APA) mandated
#' format:
#' \itemize{
#' \item `ns` : > 0.05
#' \item `*` : < 0.05
#' \item `**` : < 0.01
#' \item `***` : < 0.001
#' }
#'
#' @importFrom dplyr select rename mutate mutate_if everything full_join vars
#' @importFrom stats p.adjust pairwise.t.test na.omit aov TukeyHSD var sd
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36 changes: 15 additions & 21 deletions README.Rmd
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Expand Up @@ -37,12 +37,12 @@ Package | Status | Usage | GitHub | References
[`pairwiseComparisons`](https://indrajeetpatil.github.io/pairwiseComparisons/)
provides a tidy data friendly way to carry out pairwise comparison tests.

It currently supports *post hoc* multiple pairwise comparisons tests both
It currently supports *post hoc* multiple pairwise comparisons tests for both
between-subjects and within-subjects one-way analysis of variance designs. For
all such designs, parametric, non-parametric, and robust statistical tests are
available.
both of these designs, parametric, non-parametric, and robust statistical tests
are available.

# Installation
## Installation

To get the latest, stable `CRAN` release (`0.1.0`):

Expand All @@ -60,7 +60,7 @@ prefer-

```{r installation1, eval = FALSE}
# needed package to download from GitHub repo
utils::install.packages(pkgs = "remotes")
install.packages(pkgs = "remotes")
# downloading the package from GitHub
remotes::install_github(
Expand All @@ -80,23 +80,11 @@ remotes::install_github(
)
```

# Citation

If you want to cite this package in a scientific journal or in any other
context, run the following code in your `R` console:

```{r citation, eval = FALSE}
citation("pairwiseComparisons")
```

# Documentation and Examples

To see the documentation relevant for the **development** version of the package,
see the dedicated website for `pairwiseComparisons`, which is updated after every new
commit: <https://indrajeetpatil.github.io/pairwiseComparisons/>.

# Summary of types of statistical analyses

Following table contains a brief summary of the currently supported pairwise
comparison tests-

## Between-subjects design

Type | Equal variance? | Test | *p*-value adjustment?
Expand All @@ -119,6 +107,13 @@ Bayes Factor | <font color="red">No</font> | <font color="red">No</font>

# Examples

Here we will see specific examples of how to use this function for different
types of

- designs (between or within subjects)
- statistics (parametric, non-parametric, robust)
- *p*-value adjustment methods

## Between-subjects design

```{r}
Expand Down Expand Up @@ -208,7 +203,6 @@ pairwise_comparisons(
)
```


# Code coverage

As the code stands right now, here is the code coverage for all primary
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36 changes: 15 additions & 21 deletions README.md
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Expand Up @@ -19,12 +19,12 @@
provides a tidy data friendly way to carry out pairwise comparison
tests.

It currently supports *post hoc* multiple pairwise comparisons tests
It currently supports *post hoc* multiple pairwise comparisons tests for
both between-subjects and within-subjects one-way analysis of variance
designs. For all such designs, parametric, non-parametric, and robust
statistical tests are available.
designs. For both of these designs, parametric, non-parametric, and
robust statistical tests are available.

# Installation
## Installation

To get the latest, stable `CRAN` release (`0.1.0`):

Expand All @@ -42,7 +42,7 @@ If you are in hurry and want to reduce the time of installation, prefer-

``` r
# needed package to download from GitHub repo
utils::install.packages(pkgs = "remotes")
install.packages(pkgs = "remotes")

# downloading the package from GitHub
remotes::install_github(
Expand All @@ -62,24 +62,11 @@ remotes::install_github(
)
```

# Citation

If you want to cite this package in a scientific journal or in any other
context, run the following code in your `R` console:

``` r
citation("pairwiseComparisons")
```

# Documentation and Examples

To see the documentation relevant for the **development** version of the
package, see the dedicated website for `pairwiseComparisons`, which is
updated after every new commit:
<https://indrajeetpatil.github.io/pairwiseComparisons/>.

# Summary of types of statistical analyses

Following table contains a brief summary of the currently supported
pairwise comparison tests-

## Between-subjects design

| Type | Equal variance? | Test | *p*-value adjustment? |
Expand All @@ -102,6 +89,13 @@ updated after every new commit:

# Examples

Here we will see specific examples of how to use this function for
different types of

- designs (between or within subjects)
- statistics (parametric, non-parametric, robust)
- *p*-value adjustment methods

## Between-subjects design

``` r
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4 changes: 2 additions & 2 deletions codemeta.json
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Expand Up @@ -5,13 +5,13 @@
],
"@type": "SoftwareSourceCode",
"identifier": "pairwiseComparisons",
"description": "Multiple pairwise comparison tests for one-way\n analysis of variance designs for both between-subjects and\n within-subjects designs. Currently, it supports only the most common\n types of statistical analyses and tests: parametric (Welch's and\n Student's t-test), nonparametric (Durbin-Conover test and\n Dwass-Steel-Crichtlow-Fligner test), robust (Yuen’s trimmed means test\n ).",
"description": "Multiple pairwise comparison tests for one-way\n analysis of variance for both between-subjects and within-subjects\n designs. Currently, it supports only the most common types of\n statistical analyses and tests: parametric (Welch's and Student's\n t-test), nonparametric (Durbin-Conover test and\n Dwass-Steel-Crichtlow-Fligner test), robust (Yuen’s trimmed means test\n ).",
"name": "pairwiseComparisons: Multiple Pairwise Comparison Tests",
"codeRepository": "https://github.com/IndrajeetPatil/pairwiseComparisons",
"relatedLink": "https://indrajeetpatil.github.io/pairwiseComparisons/",
"issueTracker": "\n https://github.com/IndrajeetPatil/pairwiseComparisons/issues",
"license": "https://spdx.org/licenses/GPL-3.0",
"version": "0.1.0.9000",
"version": "0.1.0",
"programmingLanguage": {
"@type": "ComputerLanguage",
"name": "R",
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18 changes: 18 additions & 0 deletions cran-comments.md
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## Test environments
* local OS X install, R 3.6.1
* ubuntu 14.04 (on travis-ci), R 3.6.1
* win-builder (devel and release)

## R CMD check results

0 errors | 0 warnings | 1 note

- Initial submission.
- There is currently no publication associated with this package and therefore
no `doi` to report in `DESCRIPTION` file.
- I get one `NOTE` about invalid URLs but these URLs will be active once the
package is available on `CRAN`.
- Although in the past I have been encouraged to not have the `LICENSE` file
at the top level directory, I prefer to do this because most people explore
this package on `GitHub` and, in such cases, the LICENSE file is easily
accessible.
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