metamedian - Meta-Analysis of Medians

Implements several methods to meta-analyze studies that report the sample median of the outcome. When the primary studies are one-group studies, the methods of McGrath et al. (2019) <doi:10.1002/sim.8013> and Ozturk and Balakrishnan (2020) <doi:10.1002/sim.8738> can be applied to estimate the pooled median. In the two-group context, the methods of McGrath et al. (2020a) <doi:10.1002/bimj.201900036> can be applied to estimate the pooled difference of medians across groups. Additionally, a number of methods (e.g., McGrath et al. (2020b) <doi:10.1177/0962280219889080>, Cai et al. (2021) <doi:10.1177/09622802211047348>, and McGrath et al. (2023) <doi:10.1177/09622802221139233>) are implemented to estimate study-specific (difference of) means and their standard errors in order to estimate the pooled (difference of) means. See McGrath et al. (2024) <doi:10.1002/jrsm.1686> for a detailed guide on using the package.

Last updated 5 months ago

4.51 score 8 stars 16 scripts 362 downloads

estmeansd - Estimating the Sample Mean and Standard Deviation from Commonly Reported Quantiles in Meta-Analysis

Implements the methods of McGrath et al. (2020) <doi:10.1177/0962280219889080> and Cai et al. (2021) <doi:10.1177/09622802211047348> for estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. These methods can be applied to studies that report the sample median, sample size, and one or both of (i) the sample minimum and maximum values and (ii) the first and third quartiles. The corresponding standard error estimators described by McGrath et al. (2023) <doi:10.1177/09622802221139233> are also included.

Last updated 1 years ago

4.29 score 2 stars 1 dependents 58 scripts 1.1k downloads

learner - Latent Space-Based Transfer Learning

Implements transfer learning methods for low-rank matrix estimation. These methods leverage similarity in the latent row and column spaces between the source and target populations to improve estimation in the target population. The methods include the LatEnt spAce-based tRaNsfer lEaRning (LEARNER) method and the direct projection LEARNER (D-LEARNER) method described by McGrath et al. (2024) <doi:10.48550/arXiv.2412.20605>.

Last updated 1 months ago

3.18 score 1 stars 3 scripts 251 downloads