Create a Formula for the MuSyC Synergy Model

Setup a MuSyC synergy model formula to predict the E0, E1, C1, h1, E2, C2, h2, log10alpha, and E3alpha parameters.

Usage

MuSyC_formula(
  treatment_1_variable = "logd1",
  treatment_1_units = "Log[Molar]",
  treatment_2_variable = "logd2",
  treatment_2_units = "Log[Molar]",
  response_variable = "response",
  response_units = NULL,
  predictors = 1,
  ...
)

Arguments

treatment_1_variable

character variable representing the treatment.

treatment_1_units

character the units of the treatment. The default is log base 10 of the molar concentration

treatment_2_variable

character variable representing the treatment.

treatment_2_units

character the units of the treatment. The default is log base 10 of the molar concentration

response_variable

character variable representing the response to treatment

response_units

character the units of the response

predictors

formula specify predictors of non-linear parameters. i.e. what perturbations/experimental differences should be modeled separately?

...

additional arguments passed to brms::brmsformula()

Value

brms::brmsformula()

Examples

if (FALSE) { # \dontrun{
  # Data has a string column drug_id with drug identifiers
  # Fit a separate model for each drug
  BayesPharma::MuSyC_formula(predictors = 0 + drug_id)

  # Data has a string column plate_id with plate identifiers
  # Estimate the change in response for each plate relative to a global
  # baseline.
  BayesPharma::MuSyC_formula(predictors = plate_id)

  # data has columns drug_id and plate_id
  # fit a multilevel model where the drug effect depends on the plate
  BayesPharma::MuSyC_formula(predictors = 0 + (drug_id|plate_id))
} # }