rmsb: stackMI – R documentation

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stackMI

Bayesian Model Fitting and Stacking for Multiple Imputation

Description

Runs an rmsb package Bayesian fitting function such as blrm separately for each completed dataset given a multiple imputation result such as one produced by Hmisc::aregImpute. Stacks the posterior draws and diagnostics across all imputations, and computes parameter summaries on the stacked posterior draws.

Usage

stackMI(
  formula,
  fitter,
  xtrans,
  data,
  n.impute = xtrans$n.impute,
  dtrans,
  derived,
  subset,
  refresh = 0,
  progress = if (refresh > 0) "stan-progress.txt" else "",
  ...
)

Arguments

`formula`	a model formula
`fitter`	a Bayesian fitter
`xtrans`	an object created by `transcan`, `aregImpute`, or `mice`
`data`	data frame
`n.impute`	number of imputations to run, default is the number saved in `xtrans`
`dtrans`	see `Hmisc::fit.mult.impute`
`derived`	see `Hmisc::fit.mult.impute`
`subset`	an integer or logical vector specifying the subset of observations to fit
`refresh`	see rstan::sampling. The default is 0, indicating that no progress notes are output. If `refresh > 0` and `progress` is not `''`, progress output will be appended to file `progress`. The default file name is `'stan-progress.txt'`.
`progress`	see `refresh`. Defaults to `''` if `refresh = 0`. Note: If running interactively but not under RStudio, `rstan` will open a browser window for monitoring progress.
`...`	arguments passed to `fitter`

Value

an rmsb fit object with expanded posterior draws and diagnostics

Author(s)

Frank Harrell

rmsb

Bayesian Regression Modeling Strategies

v0.0.2

GPL (>= 3)

Authors

Frank Harrell [aut, cre] (<https://orcid.org/0000-0002-8271-5493>), Ben Goodrich [ctb] (contributed Stan code), Ben Bolker [ctb] (wrote original code that is folded into the pdensityContour function), Doug Bates [ctb] (write original code for highest posterior density interval that is folded into the HPDint function)

Initial release

2021-02-27