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boutliers package

Outlier detection and influence diagnostics for meta-analysis

A R package for implementing outlier detection and influence diagnostics for meta-analysis:

  • Studentized residuals by leave-one-out analysis
  • Likelihood ratio test using a mean-shifted model
  • The VRATIO statistic (relative change of the variance of the overall estimator) by leave-one-out analysis
  • The TAU2RATIO statistic (relative change of the heterogeneity variance) by leave-one-out analysis

Bootstrap distributions of the influence statistics are calculated by simple codes, and the thresholds to determine outliers are clearly provided.

Installation

# Or the the development version from GitHub:
# install.packages("devtools")
devtools::install_github("nomahi/boutliers")

Downloads: please see the release page

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Version

Install

install.packages('boutliers')

Monthly Downloads

229

Version

1.1-2

License

GPL-3

Maintainer

Hisashi Noma

Last Published

May 22nd, 2023

Functions in boutliers (1.1-2)

LRT_FE

Likelihood ratio test using a mean-shifted model by the fixed-effect model
LRT

Likelihood ratio test using a mean-shifted model
finasteride

A multicenter clinical trial data assessing the treatment effect of finasteride for benign prostatic hyperplasia
STR

Studentized residuals by leave-one-out analysis
boutliers-package

The 'boutliers' package.
STR_FE

Studentized residuals by leave-one-out analysis for the fixed-effect model
VRATIO

Variance ratio influential statistics
SMT

Rubinstein et al. (2019)'s chronic low back pain data
PPI

Crocker et al. (2018)'s patient and public involvement (PPI) intervention data