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  "Description": "Provides robust and efficient methods for estimating\ncausal effects in a target population using a multi-source\ndataset, including those of Dahabreh et al. (2019)\n<doi:10.1111/biom.13716>, Robertson et al. (2021)\n<doi:10.48550/arXiv.2104.05905>, and Wang et al. (2024)\n<doi:10.48550/arXiv.2402.02684>. The multi-source data can be a\ncollection of trials, observational studies, or a combination\nof both, which have the same data structure (outcome,\ntreatment, and covariates). The target population can be based\non an internal dataset or an external dataset where only\ncovariate information is available. The causal estimands\navailable are average treatment effects and subgroup treatment\neffects. See Wang et al. (2025) <doi:10.1017/rsm.2025.5> for a\ndetailed guide on using the package.",
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