baggr: convert_inputs – R documentation

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convert_inputs

Convert inputs for baggr models

Description

Converts data to Stan inputs, checks integrity of data and suggests default model if needed. Typically all of this is done automatically by baggr, this function is only for debugging or running models "by hand".

Usage

convert_inputs(
  data,
  model,
  quantiles,
  group = "group",
  outcome = "outcome",
  treatment = "treatment",
  covariates = c(),
  test_data = NULL,
  silent = FALSE
)

Arguments

`data`	'data.frame“ with desired modelling input
`model`	valid model name used by baggr; see baggr for allowed models if `model = NULL`, this function will try to find appropriate model automatically
`quantiles`	vector of quantiles to use (only applicable if `model = "quantiles"`)
`group`	name of the column with grouping variable
`outcome`	name of column with outcome variable (designated as string)
`treatment`	name of column with treatment variable
`covariates`	Character vector with column names in `data`. The corresponding columns are used as covariates (fixed effects) in the meta-regression model.
`test_data`	same format as `data` argument, gets left aside for testing purposes (see baggr)
`silent`	Whether to print messages when evaluated

Details

Typically this function is only called within baggr and you do not need to use it yourself. It can be useful to understand inputs or to run models which you modified yourself.

Value

R structure that's appropriate for use by baggr Stan models; group_label, model and n_groups are included as attributes and are necessary for baggr to work correctly

Author(s)

Witold Wiecek

Examples

# simple meta-analysis example,
# this is the formatted input for Stan models in baggr():
convert_inputs(schools, "rubin")

baggr

Bayesian Aggregate Treatment Effects

v0.4.0

GPL (>= 3)

Authors

Witold Wiecek [cre, aut], Rachael Meager [aut], Brice Green [ctb] (predict(), loo_compare, many visuals), Trustees of Columbia University [cph] (tools/make_cc.R)

Initial release