24 мар. 2023 г. · mi() supports only gaussian modelling. Given that se() is the error variance of the outome, this also requires a gaussian model.

17 сент. 2021 г. · I am building a model an additive model that incorporates standard errors (SE) and regression weight, which are the sample sizes.

The brms package provides an interface to fit Bayesian generalized (non-)linear multivariate multilevel models using Stan.

The brms package implements Bayesian multilevel models in R using the probabilis- tic programming language Stan. A wide range of distributions and link ...

Provide additional information on the response variable in brms models, such as censoring, truncation, or known measurement error.

16 окт. 2020 г. · se() is one of the brms helper functions designed to provide additional information about the criterion variable. Here it informs brm() that ...

8 окт. 2021 г. · How to produce brms equivalent of se.fit = TRUE of predict() on a glm() fit?

Set up a model formula for use in the brms package allowing to define (potentially non-linear) additive multilevel models for all parameters of the assumed ...

N is the number of SE peaks and the slope β is the log odds ratio of SE peaks (S = 1) overlapping with Sox9 compared to randomly located genomic regions (S = 0) ...

14 окт. 2018 г. · The purpose of this post is to present a rough draft of how I'd like to introduce fitting meta-analyses with Bürkner's great brms package.