durdata: Duration data

In durmod: Mixed Proportional Hazard Competing Risk Model

Description

The dataset simulates a labour market programme. People entering the dataset are without a job.

Usage

data(durdata)

Format

A data.frame

Details

They experience two hazards, i.e. probabilities per time period. They can either get a job and exit from the dataset, or they can enter a labour market programme, e.g. a subsidised job or similar, and remain in the dataset and possibly get a job later. In the terms of this package, there are two transitions, "job" and "program".

The two hazards are influenced by covariates observed by the researcher, called "x1" and "x2". In addition there are unobserved characteristics influencing the hazards. Being on a programme also influences the hazard to get a job. In the generated dataset, being on a programme is the indicator variable alpha. While on a programme, the only transition you can make is "job".

The dataset is organized as a series of rows for each individual. Each row is a time period with constant covariates.

The length of the time period is in the covariate duration.

The transition being made at the end of the period is coded in the covariate d. This is an integer which is 0 if no transition occurs (e.g. if a covariate changes), it is 1 for the first transition, 2 for the second transition. It can also be a factor, in which case the level marking no transition must be called "none". In the test dataset it is a factor with the levels "none", "job", and "program".

The covariate alpha is zero when unemployed, and 1 if on a programme. It is used for two purposes. It is used as an explanatory variable for transition to job, this yields a coefficient which can be interpreted as the effect of being on the programme. It is also used as a "state variable", as an index into a "risk set". I.e. when estimating, the mphcrm function must be told which risks/hazards are present. When on a programme the "toprogram" transition can not be made. This is implemented by specifying a list of risksets and using alpha+1 as an index into this set.

The dataset has already been fitted in the fit object.

Examples

data(durdata)
print(durdata)
print(fit)
summary(fit[[1]])

durmod documentation built on March 31, 2020, 5:23 p.m.