R: Simple prior for a 'brms' MMRM

brm_prior_simple {brms.mmrm}

R Documentation

Simple prior for a `brms` MMRM

Description

Generate a simple prior for a brms MMRM.

Usage

brm_prior_simple(
  data,
  formula,
  intercept = "student_t(3, 0, 2.5)",
  coefficients = "student_t(3, 0, 2.5)",
  sigma = "student_t(3, 0, 2.5)",
  unstructured = "lkj(1)",
  autoregressive = "",
  moving_average = "",
  compound_symmetry = "",
  correlation = NULL
)

Arguments

`data`	A classed data frame from `brm_data()`, or an informative prior archetype from a function like `brm_archetype_successive_cells()`.
`formula`	An object of class `"brmsformula"` from `brm_formula()` or `brms::brmsformula()`. Should include the full mapping of the model, including fixed effects, residual correlation, and heterogeneity in the discrete-time-specific residual variance components.
`intercept`	Character of length 1, Stan code for the prior to set on the intercept parameter.
`coefficients`	Character of length 1, Stan code for the prior to set independently on each of the non-intercept model coefficients.
`sigma`	Character of length 1, Stan code for the prior to set independently on each of the log-scale standard deviation parameters. Should be a symmetric prior in most situations.
`unstructured`	Character of length 1, Stan code for an unstructured correlation prior. Supply the empty string `""` to set a flat prior (default). Applies to the `⁠"cortime⁠` parameter class in `brms` priors. Used for formulas created with `brm_formula(correlation = "unstructured")`. LKJ is recommended. See also `brms::unstr()`.
`autoregressive`	Character of length 1, Stan code for a prior on autoregressive correlation parameters. Supply the empty string `""` to set a flat prior (default). Applies to the `⁠"ar⁠` parameter class in `brms` priors. Used for formulas created with `brm_formula(correlation = "autoregressive")` and `brm_formula(correlation = "autoregressive_moving_average")`. See also `brms::ar()` and `brms::arma()`.
`moving_average`	Character of length 1, Stan code for a prior on moving average correlation parameters. Supply the empty string `""` to set a flat prior (default). Applies to the `⁠"ma⁠` parameter class in `brms` priors. Used for formulas created with `brm_formula(correlation = "moving_average")` and `brm_formula(correlation = "autoregressive_moving_average")`. See also `brms::ma()` and `brms::arma()`.
`compound_symmetry`	Character of length 1, Stan code for a prior on compound symmetry correlation parameters. Supply the empty string `""` to set a flat prior (default). Applies to the `⁠"cosy⁠` parameter class in `brms` priors. Used for formulas created with `brm_formula(correlation = "compound_symmetry")`. See also `brms::cosy()`.
`correlation`	Deprecated on 2024-04-22 (version 0.1.0.9004). Please use arguments like `"unstructured"`, and/or `"autoregressive"` to supply correlation-specific priors.

Details

In brm_prior_simple(), you can separately choose priors for the intercept, model coefficients, log-scale standard deviations, and pairwise correlations between time points within patients. However, each class of parameters is set as a whole. In other words, brm_prior_simple() cannot assign different priors to different fixed effect parameters.

Value

A classed data frame with the brms prior.

Examples

set.seed(0L)
data <- brm_simulate_outline()
data <- brm_simulate_continuous(data, names = c("age", "biomarker"))
formula <- brm_formula(
  data = data,
  baseline = FALSE,
  baseline_time = FALSE,
  check_rank = FALSE
)
brm_prior_simple(
  data = data,
  formula = formula,
  intercept = "student_t(3, 0, 2.5)",
  coefficients = "normal(0, 10)",
  sigma = "student_t(2, 0, 4)",
  unstructured = "lkj(2.5)"
)

[Package brms.mmrm version 1.1.0 Index]

Simple prior for a brms MMRM