Package: reappraised 0.1.1

Mark Bolland

reappraised: Statistical Tools for Assessing Publication Integrity of Groups of Trials

Takes user-provided baseline data from groups of randomised controlled data and assesses whether the observed distribution of baseline p-values, numbers of participants in each group, or categorical variables are consistent with the expected distribution, as an aid to the assessment of integrity concerns in published randomised controlled trials. References (citations in PubMed format in details of each function): Bolland MJ, Avenell A, Gamble GD, Grey A. (2016) <doi:10.1212/WNL.0000000000003387>. Bolland MJ, Gamble GD, Avenell A, Grey A, Lumley T. (2019) <doi:10.1016/j.jclinepi.2019.05.006>. Bolland MJ, Gamble GD, Avenell A, Grey A. (2019) <doi:10.1016/j.jclinepi.2019.03.001>. Bolland MJ, Gamble GD, Grey A, Avenell A. (2020) <doi:10.1111/anae.15165>. Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2021) <doi:10.1016/j.jclinepi.2020.11.012>. Bolland MJ, Gamble GD, Avenell A, Grey A. (2021) <doi:10.1016/j.jclinepi.2021.05.002>. Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2023) <doi:10.1016/j.jclinepi.2022.12.018>. Carlisle JB, Loadsman JA. (2017) <doi:10.1111/anae.13650>. Carlisle JB. (2017) <doi:10.1111/anae.13938>.

Authors:Mark Bolland [aut, cre, cph]

reappraised_0.1.1.tar.gz
reappraised_0.1.1.tar.gz(r-4.5-noble)reappraised_0.1.1.tar.gz(r-4.4-noble)
reappraised_0.1.1.tgz(r-4.4-emscripten)reappraised_0.1.1.tgz(r-4.3-emscripten)
reappraised.pdf |reappraised.html✨
reappraised/json (API)
NEWS

# Install 'reappraised' in R:

install.packages('reappraised', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

SI_cat - Example of 20 observations for categorical analysis
SI_cat_all - Example of 50 variables from different studies for categorical (cat_all_fn) analysis
SI_cohort - Example of 100 observations for cohort analysis
SI_pvals_cont - Example of 50 observations for p-value analysis

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

10 exports 0.00 score 122 dependencies 2 scripts 283 downloads

Last updated 12 months agofrom:85351fbc31. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Aug 31 2024
R-4.5-linux	OK	Aug 31 2024

Exports:anova_fn cat_all_fn cat_fn cohort_fn final_digit_fn load_clean match_fn pval_cat_fn pval_cont_fn sr_fn

Dependencies:abind askpass backports base64enc boot broom bslib ca cachem car carData cellranger cli colorspace corrplot cowplot cpp11 crayon data.table Deriv digest doBy dplyr epitools evaluate fansi farver fastmap flextable fontawesome fontBitstreamVera fontLiberation fontquiver fs gdtools generics ggplot2 ggpubr ggrepel ggsci ggsignif glue gnm gridExtra gtable here highr hms htmltools isoband jquerylib jsonlite knitr labeling lattice lifecycle lme4 lmtest magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa modelr munsell nlme nloptr nnet numDeriv officer openssl pbkrtest pillar pkgconfig polynom prettyunits progress purrr quantreg qvcalc R6 ragg rappdirs RColorBrewer Rcpp RcppEigen readxl relimp rematch rlang rmarkdown rprojroot rstatix sass scales SparseM stringi stringr survival sys systemfonts textshaping tibble tidyr tidyselect tinytex utf8 uuid vcd vcdExtra vctrs viridisLite withr xfun xml2 yaml zip zoo

reappraised

Rendered fromreappraised.Rmdusingknitr::rmarkdownon Aug 31 2024.

Last update: 2023-03-20
Started: 2023-03-20

Citation

Readme and manuals

Help Manual

Help page	Topics
Compares differences between baseline means using Carlisle's montecarlo anova method	anova_fn
Compares observed and expected distribution of all categorical (binomial) variables	cat_all_fn
Compares observed and expected distribution of a categorical (binomial) variable	cat_fn
Compares proportions of matching summary statistics in different cohorts	cohort_fn
Compares proportions of final digits from summary statistics	final_digit_fn
Load data then clean and format it	load_clean
Compares proportions of matching summary statistics within two-arm randomised trials	match_fn
Compares observed and expected distribution of p-values for categorical variables	pval_cat_fn
Compares observed and expected distribution of p-values for continuous variables	pval_cont_fn
Example of 20 observations for categorical analysis	SI_cat
Example of 50 variables from different studies for categorical (cat_all_fn) analysis	SI_cat_all
Example of 100 observations for cohort analysis	SI_cohort
Example of 50 observations for p-value analysis	SI_pvals_cont
Compares observed and expected distribution of difference in numbers of participants between groups in two-arm randomised trials	sr_fn