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reappraised (version 0.1.1)

Statistical Tools for Assessing Publication Integrity of Groups of Trials

Description

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) . Bolland MJ, Gamble GD, Avenell A, Grey A, Lumley T. (2019) . Bolland MJ, Gamble GD, Avenell A, Grey A. (2019) . Bolland MJ, Gamble GD, Grey A, Avenell A. (2020) . Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2021) . Bolland MJ, Gamble GD, Avenell A, Grey A. (2021) . Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2023) . Carlisle JB, Loadsman JA. (2017) . Carlisle JB. (2017) .

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Version

Install

install.packages('reappraised')

Monthly Downloads

270

Version

0.1.1

License

MIT + file LICENSE

Maintainer

Mark Bolland

Last Published

October 6th, 2023

Functions in reappraised (0.1.1)

pval_cat_fn

Compares observed and expected distribution of p-values for categorical variables
SI_cohort

Example of 100 observations for cohort analysis
cat_fn

Compares observed and expected distribution of a categorical (binomial) variable
anova_fn

Compares differences between baseline means using Carlisle's montecarlo anova method
cohort_fn

Compares proportions of matching summary statistics in different cohorts
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_pvals_cont

Example of 50 observations for p-value analysis
sr_fn

Compares observed and expected distribution of difference in numbers of participants between groups in two-arm randomised trials
pval_cont_fn

Compares observed and expected distribution of p-values for continuous variables
cat_all_fn

Compares observed and expected distribution of all categorical (binomial) variables
match_fn

Compares proportions of matching summary statistics within two-arm randomised trials
final_digit_fn

Compares proportions of final digits from summary statistics
load_clean

Load data then clean and format it