R/cma.mix.R

In macc: Mediation Analysis of Causality under Confounding

cma.mix <-
function(dat,model.type=c("single","multilevel"),method=c("HL","TS","HL-TS"),delta=NULL,sens.plot=FALSE,
                  interval=c(-0.90,0.90),tol=10e-4,max.itr=50,conf.level=0.95,optimizer=c("bobyqa","Nelder_Mead","optimx"),
                  mix.pkg=c("lme4","nlme"),random.indep=TRUE,random.var.equal=TRUE,u.int=FALSE,Sigma.update=FALSE,
                  var.constraint=FALSE,random.var.update=TRUE,logLik.type=c("logLik","HL"),
                  legend.pos="topright",xlab=expression(delta),ylab=expression(hat(AB)),
                  cex.lab=1,cex.axis=1,lgd.cex=1,lgd.pt.cex=1,plot.delta0=TRUE,...)
{
  if(model.type[1]=="single")
  {
    if(is.null(delta))
    {
      delta<-0
    }
    re<-cma.uni.delta(dat,delta=delta,conf.level=conf.level)
    if(sens.plot)
    {
      re.sens<-cma.uni.sens(dat,conf.level=conf.level)
      cma.uni.plot(re.sens,re,delta=NULL,legend.pos=legend.pos,xlab=xlab,ylab=ylab,
                   cex.lab=cex.lab,cex.axis=cex.axis,lgd.cex=lgd.cex,lgd.pt.cex=1,plot.delta0=plot.delta0,...)
    }
  }else
    if(model.type[1]=="multilevel")
    {
      if(is.null(delta))
      {
        if(method[1]=="TS")
        {
          system.time(re1<-optimize(cma.uni.mix.dhl,interval=interval,dat=dat,tol=tol,max.itr=0,optimizer=optimizer,
                                    mix.pkg=mix.pkg,random.indep=random.indep,random.var.equal=random.var.equal,
                                    u.int=u.int,Sigma.update=Sigma.update,logLik.type=logLik.type,maximum=TRUE))
          re<-cma.uni.mix(dat,delta=re1$maximum,conf.level=conf.level,optimizer=optimizer,mix.pkg=mix.pkg,
                          random.indep=random.indep,random.var.equal=random.var.equal,u.int=u.int)
        }else
        {
          system.time(re1<-optimize(cma.uni.mix.dhl,interval=interval,dat=dat,tol=tol,max.itr=max.itr,optimizer=optimizer,
                                    mix.pkg=mix.pkg,random.indep=random.indep,random.var.equal=random.var.equal,
                                    u.int=u.int,Sigma.update=Sigma.update,var.constraint=var.constraint,
                                    random.var.update=random.var.update,logLik.type=logLik.type,maximum=TRUE))
          if(method[1]=="HL-TS")
          {
            re<-cma.uni.mix(dat,delta=re1$maximum,conf.level=conf.level,optimizer=optimizer,mix.pkg=mix.pkg,
                            random.indep=random.indep,random.var.equal=random.var.equal,u.int=u.int)
          }
          if(method[1]=="HL")
          {
            re<-cma.uni.mix.hl(dat,delta=re1$maximum,tol=tol,max.itr=max.itr,alpha=1-conf.level,random.indep=random.indep,
                               optimizer=optimizer,mix.pkg=mix.pkg,random.var.equal=random.var.equal,u.int=u.int,
                               Sigma.update=Sigma.update,var.constraint=var.constraint,random.var.update=random.var.update)
          }
        }
      }else
      {
        if(method[1]=="TS")
        {
          re<-cma.uni.mix(dat,delta=delta,conf.level=conf.level,optimizer=optimizer,mix.pkg=mix.pkg,
                          random.indep=random.indep,random.var.equal=random.var.equal,u.int=u.int)
        }
        if(method[1]=="HL")
        {
          re<-cma.uni.mix.hl(dat,delta=delta,tol=tol,max.itr=max.itr,alpha=1-conf.level,random.indep=random.indep,
                             optimizer=optimizer,mix.pkg=mix.pkg,random.var.equal=random.var.equal,u.int=u.int,
                             Sigma.update=Sigma.update,var.constraint=var.constraint,random.var.update=random.var.update)
        }
      }
    }
  return(re)
  if(as.numeric(re$Var.comp[1])<1e-5)
  {
    warning("The variance of A's random effect is less than 1e-5.")
  }
  return(re)
  if(as.numeric(re$Var.comp[2])<1e-5)
  {
    warning("The variance of C's random effect is less than 1e-5.")
  }
  return(re)
  if(as.numeric(re$Var.comp[3])<1e-5)
  {
    warning("The variance of B's random effect is less than 1e-5.")
  }
}