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>);
 - measures, tests, and visualization tools for publication bias or small-study effects
   (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>).

Creates the optimal (D, U and I) designs for the accelerated life
    testing with right censoring or interval censoring. It uses generalized 
    linear model (GLM) approach to derive the asymptotic variance-covariance 
    matrix of regression coefficients. The failure time distribution is assumed 
    to follow Weibull distribution with a known shape parameter and log-linear 
    link functions are used to model the relationship between failure time 
    parameters and stress variables. The acceleration model may have multiple 
    stress factors, although most ALTs involve only two or less stress factors. 
    ALTopt package also provides several plotting functions including contour plot,
    Fraction of Use Space (FUS) plot and Variance Dispersion graphs of Use Space
    (VDUS) plot. For more details, see Seo and Pan (2015) <doi:10.32614/RJ-2015-029>.