diff --git a/DESCRIPTION b/DESCRIPTION
index c68e359..6be9cc6 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
Package: statcheck
Title: Extract Statistics from Articles and Recompute P-Values
Version: 1.4.0
-Date: 2021-03-17
+Date: 2022-12-09
Authors@R: c(
person("Michele B.", "Nuijten", email = "m.b.nuijten@uvt.nl",
role = c("aut", "cre")),
diff --git a/README.Rmd b/README.Rmd
index 591e002..ef5d7db 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -13,11 +13,19 @@ knitr::opts_chunk$set(
)
```
+```{r echo=FALSE, results="hide", message=FALSE}
+library("badger")
+```
+
# statcheck
-[![CRAN status](https://www.r-pkg.org/badges/version/statcheck)](https://cran.r-project.org/package=statcheck)
-[![CRAN_Downloads_Total](http://cranlogs.r-pkg.org/badges/grand-total/statcheck?color=brightgreen)](https://cran.r-project.org/package=statcheck)
+```{r, echo = FALSE, results='asis'}
+cat(
+ badge_cran_release("statcheck", "green"),
+ badge_cran_download("statcheck", "grand-total", "green")
+)
+```
## What is statcheck?
diff --git a/README.md b/README.md
index 180056f..e33495d 100644
--- a/README.md
+++ b/README.md
@@ -1,15 +1,13 @@
-
# statcheck
-[![CRAN
-status](https://www.r-pkg.org/badges/version/statcheck)](https://cran.r-project.org/package=statcheck)
-[![CRAN\_Downloads\_Total](http://cranlogs.r-pkg.org/badges/grand-total/statcheck?color=brightgreen)](https://cran.r-project.org/package=statcheck)
+[![](https://www.r-pkg.org/badges/version/statcheck?color=green)](https://cran.r-project.org/package=statcheck)
+[![](http://cranlogs.r-pkg.org/badges/grand-total/statcheck?color=green)](https://cran.r-project.org/package=statcheck)
## What is statcheck?
@@ -32,9 +30,9 @@ inconsistencies.
3. **Research**: `statcheck` can be used to automatically extract
statistical test results from articles that can then be analyzed.
You can for instance investigate whether you can predict statistical
- inconsistencies (see e.g., [Nuijten et
- al., 2017](https://www.collabra.org/article/10.1525/collabra.102/)),
- or use it to analyze p-value distributions (see e.g., [Hartgerink et
+ inconsistencies (see e.g., [Nuijten et al.,
+ 2017](https://www.collabra.org/article/10.1525/collabra.102/)), or
+ use it to analyze p-value distributions (see e.g., [Hartgerink et
al., 2016](https://peerj.com/articles/1935/)).
## How does statcheck work?
@@ -44,9 +42,11 @@ The algorithm behind `statcheck` consists of four basic steps:
1. **Convert** pdf and html articles to plain text files.
2. **Search** the text for instances of NHST results. Specifically,
`statcheck` can recognize *t*-tests, *F*-tests, correlations,
- *z*-tests, \(\chi^2\) -tests, and Q-tests (from meta-analyses) if
- they are reported completely (test statistic, degrees of freedom,
- and *p*-value) and in APA style.
+ *z*-tests,
+ ![\chi^2](https://latex.codecogs.com/png.image?%5Cdpi%7B110%7D&space;%5Cbg_white&space;%5Cchi%5E2 "\chi^2")
+ -tests, and Q-tests (from meta-analyses) if they are reported
+ completely (test statistic, degrees of freedom, and *p*-value) and
+ in APA style.
3. **Recompute** the *p*-value using the reported test statistic and
degrees of freedom.
4. **Compare** the reported and recomputed *p*-value. If the reported