Title: Bayesian Meta-Analysis Using Basic Uncertain Pooling
Description: Contains functions that allow Bayesian meta-analysis (1) with binomial data, counts(y) and total counts (n) or, (2) with user-supplied point estimates and associated variances.   Case (1) provides an analysis based on the logit transformation of the sample proportion. This methodology is also appropriate for combining data from sample surveys and related sources. The functions can  calculate the corresponding similarity matrix. More details can be found in Cahoy and Sedransk (2023), Cahoy and Sedransk (2022)  <doi:10.1007/s42519-018-0027-2>, Evans and Sedransk (2001) <doi:10.1093/biomet/88.3.643>, and Malec and Sedransk (1992) <doi:10.1093/biomet/79.3.593>.

Title: Meta-CART: A Flexible Approach to Identify Moderators in
Author: Xinru Li [aut, cre], Elise Dusseldorp [aut, cph], Kaihua Liu [ctb] (supported with the plot function), Jacqueline Meulman [ctb]
Description: Fits meta-CART by integrating classification and regression trees (CART) into meta-analysis. Meta-CART is a flexible approach to identify interaction effects between moderators in meta-analysis. The methods are described in Dusseldorp et al. (2014) <doi:10.1037/hea0000018> and Li et al. (2017) <doi:10.1111/bmsp.12088>.
Depends: R (>= 3.0.2), rpart, stats, methods, rpart.plot,

Author: Xinru Li [aut, cre], Elise Dusseldorp [aut, cph], Kaihua Liu [ctb] (supported with the plot function), Juan Claramunt [ctb], Jacqueline Meulman [ctb]
Description: Meta-CART integrates classification and regression trees (CART) into meta-analysis. Meta-CART is a flexible approach to identify interaction effects between moderators in meta-analysis. The method is described in Dusseldorp et al. (2014) <doi:10.1037/hea0000018> and Li et al. (2017) <doi:10.1111/bmsp.12088>.
Depends: R (>= 3.0.2), stats, ggplot2, gridExtra, methods, rpart

Packaged: 2019-05-09 08:47:17 UTC; jclaramunt

Packaged: 2019-12-06 09:17:11 UTC; jclaramunt

Packaged: 2020-07-10 11:01:19 UTC; jclaramunt