Learn empirical bias distributions sequentially or in groups; for each sequential step or analysis group, bias distributions is learned by by simultaneously analyzing a large set of negative control outcomes by a Bayesian hierarchical model through MCMC.
A list of lists, each of which is a set of grid profile likelihoods regarding negative controls, indexed by analysis period ID for sequential analyses or group ID for group analyses.
Arguments passed to the
A (long) dataframe with four columns.
mean includes MCMC samples for the average bias,
scale for the sd/scale parameter,
bias for predictive samples of the bias, and
Id for the period ID or group ID.
# load example data data("ncLikelihoods") # fit bias distributions over analysis periods # NOT RUN # biasDistributions = sequentialFitBiasDistribution(ncLikelihoods, seed = 42)