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Simple prior for a brms MMRM

Source: R/brm_prior_simple.R
brm_prior_simple.Rd

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.

Value

A classed data frame with the brms prior.

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.

See also

Other priors: brm_prior_archetype(), brm_prior_label(), brm_prior_template()

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)"
)
#>                 prior     class coef group resp  dpar nlpar lb ub  source
#>  student_t(3, 0, 2.5) Intercept                                   default
#>         normal(0, 10)         b                                   default
#>              lkj(2.5)   cortime                                   default
#>    student_t(2, 0, 4)         b                 sigma             default