convert_inputs function

Convert inputs for baggr models

Converts data to a list of inputs suitable for Stan models, checks integrity of data and suggests the appropriate default model if needed. Typically all of this is done automatically by baggr , so this function is included only for debugging

or running (custom) models "by hand".

convert_inputs(
  data,
  model,
  quantiles,
  effect = NULL,
  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")
• effect: Only matters for binary data, use logOR, logRR, or RD. Otherwise ignore. See prepare_ma for details.
• 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

Returns

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

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.

Examples

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

Author(s)

Witold Wiecek