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pcnetmeta - Patient-Centered Network Meta-Analysis

Performs Bayesian arm-based network meta-analysis for datasets with binary, continuous, and count outcomes (Zhang et al., 2014 <doi:10.1177/1740774513498322>; Lin et al., 2017 <doi:10.18637/jss.v080.i05>).

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jagscpp

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altmeta - Alternative Meta-Analysis Methods

Provides alternative statistical methods for meta-analysis, including: - bivariate generalized linear mixed models for synthesizing odds ratios, relative risks, and risk differences (Chu et al., 2012 <doi:10.1177/0962280210393712>) - tests and measures for between-study heterogeneity (Lin et al., 2017 <doi:10.1111/biom.12543>; Wang et al., 2022 <doi:10.1002/sim.9261>; Yu et al., 2025 <doi:10.1186/s12874-025-02719-7>); - measures, tests, and visualization tools for publication bias, small-study effects, or related bias (Lin and Chu, 2018 <doi:10.1111/biom.12817>; Lin, 2019 <doi:10.1002/jrsm.1340>; Lin, 2020 <doi:10.1177/0962280220910172>; Shi et al., 2020 <doi:10.1002/jrsm.1415>); - meta-analysis of combining standardized mean differences and odds ratios (Jing et al., 2023 <doi:10.1080/10543406.2022.2105345>); - meta-analysis of diagnostic tests for synthesizing sensitivities, specificities, etc. (Reitsma et al., 2005 <doi:10.1016/j.jclinepi.2005.02.022>; Chu and Cole, 2006 <doi:10.1016/j.jclinepi.2006.06.011>); - meta-analysis methods for synthesizing proportions (Lin and Chu, 2020 <doi:10.1097/ede.0000000000001232>); - models for multivariate meta-analysis, measures of inconsistency degrees of freedom in Bayesian network meta-analysis, and predictive P-score (Lin and Chu, 2018 <doi:10.1002/jrsm.1293>; Lin, 2020 <doi:10.1080/10543406.2020.1852247>; Rosenberger et al., 2021 <doi:10.1186/s12874-021-01397-5>).

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jagscpp

1.56 score 1 stars 12 scripts 686 downloads

fragility - Assessing and Visualizing Fragility of Clinical Results

A collection of user-friendly functions for assessing fragility of clinical results with binary and survival outcomes. For binary outcomes, the package assesses and visualizes fragility of individual studies (Walsh et al., 2014 <doi:10.1016/j.jclinepi.2013.10.019>; Lin, 2021 <doi:10.1111/jep.13428>), conventional pairwise meta-analyses (Atal et al., 2019 <doi:10.1016/j.jclinepi.2019.03.012>), and network meta-analyses of multiple treatments with binary outcomes (Xing et al., 2020 <doi:10.1016/j.jclinepi.2020.07.003>). The functions for binary outcomes are designed to: 1) calculate the fragility index (i.e., the minimal event status modifications that can alter the significance or non-significance of the original result) and fragility quotient (i.e., fragility index divided by sample size) at a specific significance level; 2) give the cases of event status modifications for altering the result's significance or non-significance and visualize these cases; 3) visualize the trend of statistical significance as event status is modified; 4) efficiently derive fragility indexes and fragility quotients at multiple significance levels, and visualize the relationship between these fragility measures against the significance levels; and 5) calculate fragility indexes and fragility quotients of multiple datasets (e.g., a collection of clinical trials or meta-analyses) and produce plots of their overall distributions. For survival outcomes, the package implements the event status modification method based on the log-rank test described by Xing et al. (2026 <doi:10.1093/aje/kwaf229>). It calculates the fragility index and fragility quotient for two-group studies with right-censored data, modifying event status in one or both groups while preserving follow-up times and group assignments. Results include the sequence of modifications, corresponding p-values, and an S3 print method. The outputs from these functions may inform the robustness of clinical results in terms of statistical significance and aid the interpretation of fragility measures. The usage of this package is illustrated in Lin et al. (2023 <doi:10.1016/j.ajog.2022.08.053>) and detailed in Lin and Chu (2022 <doi:10.1371/journal.pone.0268754>).

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1.00 score 2 scripts 324 downloads