crmPack (version 1.0.6)

ModelTox-class: No intialization function Class for DLE models using pseudo data prior. This is a class of DLE (dose-limiting events) models/ toxicity model which contains all DLE models for which their prior are specified in form of pseudo data (as if there is some data before the trial starts). It inherits all slots from ModelPseudo

Description

The dose function has a first argument prob, a scalar a probability of the occurrence of a DLE which is targeted. Additional arguments are models parameters. It computes, using the model parameter(s)/ model parameter(s) samples, the resulting dose. Note that the model parameters are called exactly as in the model. The model estimates generated can be single values of the maximum likelihodd estimates (prior or posterior modal estimates) or samples of the model estimates generated. If samples of the model estimates are generated, the model parameters (samples) must be included in the samples vector. The vectors of all samples for these model paramters will be supplied to the function such that the function will be able to process vectors of model parameters.

Slots

dose

a function computing the dose level reaching a specific target probabilty of the occurrence of a DLE, based on the model parameters. The model paramters (samples)are obtained based on the prior specified in form of pseudo data and together with (if any) the observed DLE responses and their corresponding dose levels (see details above)

prob

a function computing the probability of the occurrence of a DLEat a specidfied dose level, based on the model parameters. The model paramters (samples) are obtained the prior specified in form of pseudo data and together with (if any) the observed DLE responses and their corresponding dose levels (see dtails above)

data

refers to the data input specification in Data class which are used to obtain model paramters estimates or samples (see details above)

Details

The prob function has a first argument dose, a scalar dose level which is targeted. Additional arguments are model paramters. It computes using model paramter(s) (samples), the resulting probabilities of a DLE occuring at the target dose level. If samples of model parameters are generated, the function must vectorize over the model parameters.

Note that dose and prob are the inverse functions of each other.

The data must obey the covention that the data input is called exactly in the Data class. This refers to any observed DLE responses (y in Data class), the dose (levels) (x in Data class) at which these responses are observed, all dose levels considered in the study (doseGrid in Data) class and other specifications in Data class that can be used to generate prior or posterior modal estimates or samples estimates for model parmater(s). If no responses is observed, at least doseGrid in Data has to be specified in data slot for which prior modal estimates or samples can be obtained for model parameters based on the specified pseudo data.

See Also

LogisticIndepBeta, Effloglog, EffFlexi