MuSyC_prior: Create a Prior for the MuSyC Synergy Model

In maomlab/BayesPharma: Tools for Bayesian Analysis of Non-Linear Pharmacology Models

Create a Prior for the MuSyC Synergy Model

Description

Creating a data.frame of priors of the dose response parameters required for the MuSyC model.

If you would like to set a parameter as a constant, enter a numeric value for the function argument. If you would like to set your own distribution, for example, in the function arguments type ⁠ec50 = brms::prior(prior = normal(<mu>, <sigma>), nlpar = 'ec50')⁠. For other distribution options, reference brms::prior and Prior Choice Recommendations

Usage

MuSyC_prior(
  logE0 = brms::prior(prior = normal(-0.6931, 3), nlpar = "logE0", ub = 0),
  logE1 = brms::prior(prior = normal(-1.386, 3), nlpar = "logE1", ub = 0),
  logC1 = brms::prior(prior = normal(0, 3), nlpar = "logC1"),
  h1 = brms::prior(prior = normal(4, 3), nlpar = "h1", lb = 0.1),
  logE2 = brms::prior(prior = normal(-1.386, 3), nlpar = "logE2", ub = 0),
  logC2 = brms::prior(prior = normal(0, 3), nlpar = "logC2"),
  h2 = brms::prior(prior = normal(4, 3), nlpar = "h2", lb = 0.1),
  logE3 = brms::prior(prior = normal(-1.386, 3), nlpar = "logE3", ub = 0),
  logalpha = brms::prior(prior = normal(0, 0.5), nlpar = "logalpha"),
  ...
)

Arguments

logE0	brms::brmsprior() or numeric. Prior for the log response with no treatment. (Default: normal(log(0.5), 3) lower bounded by 0).
logE1	brms::brmsprior() or numeric. Prior for the full log response for treatment 1 and the treatment 2 is zero. (Default: normal(log(0.25), 3) lower bounded by 0).
logC1	brms::brmsprior() or numeric. Prior for the log AC50 of treatment 1 and the dose of treatment 2 is zero. (Default: normal(log(1), 3)).
h1	brms::brmsprior() or numeric. Prior for the slope of treatment 1 at its AC50 and treatment 2 is zero in exponential form. To converted the slope to exponential form, use MuSyC_si_to_hi()). In particular, let mu = MuSyC_si_to_hi(si = 1, Ci = 1, E0 = 0, Ei = 0), then (Default: normal(mu, 3) lower bounded by .1).
logE2	brms::brmsprior() or numeric. Prior for the full log response for treatment 2 and the treatment 1 is zero. (Default: normal(log(0.25), 3) lower bounded by 0).
logC2	brms::brmsprior() or numeric. Prior for the log AC50 of treatment 2. (Default: to normal(log(1), 3)).
h2	brms::brmsprior() or numeric. Prior the slope of treatment 2 at its AC50 and treatment 1 is zero in exponential form. To converted the slope to exponential form, use MuSyC_si_to_hi()). In particular, let mu = MuSyC_si_to_hi(si = 1, Ci = 1, E0 = 0, Ei = 0), then (Default: normal(mu, 3) lower bounded by .1).
logE3	brms::brmsprior() or numeric. Prior for the combined full response for treatment 1 and treatment 2. (Default: normal(log(0.25), 3) lower bounded by 0).
logalpha	brms::brmsprior() or numeric. Prior for the log synergistic potency. Where values greater than 1 are synergistic, values less than 1 are antagonistic. (Default: normal(log(0), 0.5).
...	additional brms::brmsprior() objects to add to the prior.

Value

brms::brmsprior() data.frame

maomlab/BayesPharma documentation built on Aug. 24, 2024, 8:45 a.m.