others.md

More details on the arguments.

The glmeObject( ) and survObject( ) must be in the following format:

  glmeObject <- list(fm, family, par, ran.par, sigma, disp, 
  lower, upper, str_val,  CenObject)

  survObject <- list(fm, event,  par, disp, 
  lower, upper, distribution, str_val)

  CenObject <- list(fm, family="binomial", par, ran.par, 
  disp, lower, upper, str_val, Cregime=1, truncated=T, delim_val)  

Arguments

fm	A two-sided linear formula object with the response on the left of a ~ operator and the terms, separated by + operators, on the right.
family	A GLM family.
par	A character string, naming the parameters. Such as, "alpha", "beta", ...
ran.par	A character string, naming the random effects. Such as, "b1","b2",...
sigma	A character string, naming the standard deviation for normal distribution. Such as, "sigma".
disp	A character vector, specifying the dispersion parameters.
lower / upper	lower/upper bounds of the dispersion parameters specified by disp.
str_val	A numeric vector of starting values for the fixed parameters in the model.
CenObject	A list, indicating the logistic GLME model used to model the censoring mechanism. CenObject=NULL means that the response variable is not censored.

event	event indicator
distribution	If distribution=NULL, a Cox PH model is fitted. If distribution=weibull, a Weibull model is fitted.
delim_val	the lower limit of quantification
Cregime	If Cregime=1 (by default), we assume that the censored data are from one regime (point mass). If Cregime=2, we assume that the censored data are from two regimes, one from normal distribution and one from point mass.
truncated	logical: if truncated=T (by default), we assume the observed response variable follows a truncated normal distribution; otherwise, we assume it follows a normal distribution.

See the example in example.md for details.