Create a function to draw from the meta model posterior predictive distribution

Individual level rows are predicted as in the marginal model using epidist_gen_posterior_predict(). For summary rows the predicted quantity is the reported summary itself, that is a simulated reported mean, standard deviation, or, for quantile rows, cumulative probability at the reported value. A row that stands for several summaries reported by one study predicts the first of them, drawn from its marginal. Predictions for summary rows are therefore not on the delay scale and should not be compared directly with individual level predictions. They come from the normal approximations described in as_epidist_meta_model(), so a predicted cumulative probability for a quantile row can fall outside [0, 1] when the study sample size is small.

Usage

epidist_gen_meta_predict(family)

Arguments

family

A description of the response distribution and link function to be used in the model. Every family function has a link argument allowing users to specify the link function to be applied on the response variable. If not specified, default links are used. For details of all supported families see brms::brmsfamily(). Commonly used, such as brms::lognormal(), are also reexported as part of epidist.

Value

A function that takes a prep argument from brms and returns a matrix of posterior predictions.

See also

brms::posterior_predict() for details on how this is used within brms.

Other gen: epidist_gen_log_lik(), epidist_gen_meta_log_lik(), epidist_gen_posterior_epred(), epidist_gen_posterior_predict()