generate_MAPC_formula: Generate MAPC formula for INLA
In MAPCtools: Multivariate Age-Period-Cohort (MAPC) Modeling for Health Data

generate_MAPC_formula

R Documentation

Generate MAPC formula for INLA

Description

Based on APC-format, generate the proper formula to pass to INLA for fitting MAPC models.

Usage

generate_MAPC_formula(
  df,
  APC_format,
  response,
  stratify_var,
  age = "age",
  period = "period",
  cohort = "cohort",
  intercept = FALSE,
  apc_prior = "rw1",
  apc_hyper = NULL,
  random_term = TRUE,
  extra.fixed = NULL,
  extra.random = NULL,
  extra.models = NULL,
  extra.hyper = NULL
)

Arguments

`df`	Data frame for which MAPC models should be fit
`APC_format`	A string where lower-case letters indicate stratum-specific time effects and upper-case letters indicate shared time effects.
`response`	A string, name of the column in `df` that represents the response variable.
`stratify_var`	Stratification variable. At least one time effect should be stratum-specific, and at least one should be shared.
`age`	Name of age column
`period`	Name of period column
`cohort`	Name of cohort column
`intercept`	Boolean, indicating if an overall intercept should be included in the formula. Defaults to TRUE (optional).
`apc_prior`	Which prior model to use for the time effects. Defaults to "rw1" (optional).
`apc_hyper`	If the user wants non-default hyperpriors for the random time effects, this can be achieved by passing the entire prior specification as a string. If e.g. `hyper = list(theta = list(prior="pc.prec", param=c(0.5,0.01)))` is desired, pass the string "`list(theta = list(prior="pc.prec", param=c(0.5,0.01)))`" to this argument.
`random_term`	Indicator, indicating if a random term should be included in the model. Defaults to TRUE (optional).
`extra.fixed`	Name of additional fixed effects. Defaults to NULL (optional).
`extra.random`	Name of additional random effects. Defaults to NULL (optional).
`extra.models`	Models for additional random effects. Supported `INLA` models include `'iid'`, `'rw1'` and `'rw2'`. Defaults to NULL (optional).
`extra.hyper`	If the user wants non-default hyperpriors for the additional random effects, this can be achieved by passing the entire prior specification as a string. If e.g. `hyper = list(theta = list(prior="pc.prec", param=c(0.5,0.01)))` is desired, pass the string "`list(theta = list(prior="pc.prec", param=c(0.5,0.01)))`" to this argument.