All the p-values with tidypvals
The p-value is the most widely-known statistic. P-values are reported in a large majority of scientific publications that measure and report data. R.A. Fisher is widely credited with inventing the p-value. If he was cited every time a p-value was reported his paper would have, at the very least, 3 million citations* - making it the most highly cited paper of all time.
tidypvals package organizes a large subset of these published p-values. They have been collected and synthesized from thousands of studies across multiple fields. The resulting data sets can be easily merged, combined, and analyzed.
This package will (hopefully) end up on Bioconductor soon, but for now you can install it with the devtools package
install.packages('devtools') library(devtools) devtools::install_github('jtleek/tidypvals')
The currently available p-value data sets in this package are:
jager2014- This data set comes from the paper: An estimate of the science-wise false discovery rate and application to the top medical literature that first proposed p-value scraping from the medical literature for re-analysis.
brodeur2016- This data set comes from the paper Star Wars: The empirics strike back which collected p-values from the economics literature.
head2015- This data set comes from the paper The Extent and Consequences of P-Hacking in Science and is an extension of the
jager2014idea to a much larger collection of biological papers.
chavalarias2016- This data set comes from the paper Evolution of Reporting P Values in the Biomedical Literature, 1990-2015 and is an extension of the
jager2014idea to a much larger collection of medical papers.
allp- merges the
brodeur2016while removing duplicates. To see how it is created view the
Each data set is "tidy" data frame and has the following columns:
pvalue- The reported p-value
year- The year of the publication where the p-value appeared
journal- The journal where the publication appeared
field- The field of the paper, using the categorization in Head et al. 2015.
abstract- Whether the p-value was in the abstract of the paper
operator- Whether the p-value was reported as "lessthan", "greaterthan", or "equals".
doi- When available the digital object identifier.
pmid- The pubmed ID for the paper when available
Load the library and then access each data set by name.
Data sets can be easily merged, but be careful to avoid duplicated p-values across different data sets. You can see how each data set was obtained and tidied by viewing the corresponding vignette.