A comprehensive suite of functions to perform and visualise 
    pairwise and network meta-analysis with aggregate binary or continuous
    missing participant outcome data. The package covers core Bayesian one-stage
    models implemented in a systematic review with multiple interventions, 
    including fixed-effect and random-effects network meta-analysis, 
    meta-regression, and evaluation of the consistency assumption via the 
    node-splitting approach and the unrelated mean effects model (original and
    revised model proposed by Spineli, (2021) <doi:10.1177/0272989X211068005>). 
    Missing participant outcome data are addressed in all models of the package 
    (see Spineli, (2019) <doi:10.1186/s12874-019-0731-y>, Spineli et al., (2019) 
    <doi:10.1002/sim.8207>, Spineli, (2019) <doi:10.1016/j.jclinepi.2018.09.002>, 
    and Spineli et al., (2021) <doi:10.1177/0962280220983544>). 
    The robustness to primary analysis results can also be investigated using a 
    novel intuitive index (see Spineli et al., (2021) <doi:10.1002/jrsm.1478> and 
    Spineli et al., (2021) <doi:10.1186/s12916-021-02195-y>). 
    Methods to evaluate the transitivity assumption using trial dissimilarities
    and hierarchical clustering are provided 
    (see Spineli, (2024) <doi:10.1186/s12874-024-02436-7>, and 
    Spineli et al., (2025) <doi:10.1002/sim.70068>). A novel index to 
    facilitate interpretation of local inconsistency is also available 
    (see Spineli, (2024) <doi:10.1186/s13643-024-02680-4> and 
    Spineli, (2025) <doi:10.1186/s13643-025-02984-z>).
    The package also offers a rich, user-friendly visualisation toolkit that aids 
    in appraising and interpreting the results thoroughly and preparing the 
    manuscript for journal submission. The visualisation tools comprise the 
    network plot, forest plots, panel of diagnostic plots, heatmaps on the extent 
    of missing participant outcome data in the network, league heatmaps on 
    estimation and prediction, rankograms, Bland-Altman plot, leverage plot, 
    deviance scatterplot, heatmap of robustness, barplot of Kullback-Leibler 
    divergence, heatmap of comparison dissimilarities and dendrogram of comparison 
    clustering. The package also allows the user to export the results to an Excel 
    file at the working directory.