stpm (version 1.3.2)

simdata_gamma_frailty: This script simulates data using familial frailty model. We use the following variation: gamma(mu, ssq), where mu is the mean and ssq is sigma square. See: https://www.rocscience.com/help/swedge/webhelp/swedge/Gamma_Distribution.htm

Description

This script simulates data using familial frailty model. We use the following variation: gamma(mu, ssq), where mu is the mean and ssq is sigma square. See: https://www.rocscience.com/help/swedge/webhelp/swedge/Gamma_Distribution.htm

Usage

simdata_gamma_frailty(N = 10, f = list(at = "-0.05", f1t = "80", Qt = "2e-8", ft = "80", bt = "5", mu0t = "1e-3"), step = 1, tstart = 30, tend = 105, ystart = 80, sd0 = 1, nobs = NULL, gamma_mu = 1, gamma_ssq = 0.5)

Arguments

N

Number of individuals.

f

a list of formulas that define age (time) - dependency. Default: list(at="a", f1t="f1", Qt="Q*exp(theta*t)", ft="f", bt="b", mu0t="mu0*exp(theta*t)")

step

An interval between two observations, a random uniformally-distributed value is then added to this step.

tstart

Starting time (age). Can be a number (30 by default) or a vector of two numbers: c(a, b) - in this case, starting value of time is simulated via uniform(a,b) distribution.

tend

A number, defines final time (105 by default).

ystart

A starting value of covariates.

sd0

A standard deviation for modelling the next covariate value, sd0 = 1 by default.

nobs

A number of observations (lines) for individual observations.

gamma_mu

A parameter which is a mean value, default = 1

gamma_ssq

A sigma squared, default = 0.5.

Value

A table with simulated data.

References

Yashin, A. et al (2007), Health decline, aging and mortality: how are they related? Biogerontology, 8(3), 291-302..

Examples

library(stpm)
dat <- simdata_time_dep(N=100)
head(dat)