missp.logist.results: Summary results of the parametric NLME, when the true data...

In unkyunglee/HDChangePoint: Estimating disease onset from change points of markers measured with error

Description

Summary results of the parametric NLME, when the true data are generated by the arctangent model, but the parametric NLME assumes the incorrect logistic model.

Usage

missp.logist.results(
  nsim = 100,
  n = 80,
  res = results,
  time.length = 20,
  beta = 0.1,
  beta0 = 2,
  file = "nlme_logisic"
)

Arguments

nsim	number of simulation runs.
n	number of sample size.
res	a nsim-length of list for simulation results.
time.length	number of data points at which predictors are required for each individual longitudinal trajectory. This time point for graphs to be plotted.
beta	a (p-1)-length of true coefficient vector corresponding to subject specific covariates.
beta0	true intercept of the log-normal model for the inflection point.
file	a character string of file name for a creating plot in .eps file extention.

Value

A list of the summarized simulation results including

• res.tablea data frame of the absolute biases, estimated standard deviations, average of the estimated standard errors and 95% coverage probabilities for the fixed effects (beta0, beta).

• Rel.glob.logT.esta data frame of the relative average performance of inflection points for all subjects including the relative absolute biases, the relative empirical standard errors, the relative bootstrap standard deviations and 95% boostrap confidence intervals.

unkyunglee/HDChangePoint documentation built on Nov. 27, 2021, 2:57 p.m.