R/summary.mm.R

Defines functions summary.mm

Documented in summary.mm

#' summary.mm
#'
#' "summary.mm" is used to display the results of the mediation analyzes done with "multimediate".
#'
#'
#' @param object element of the class "mm".
#' @param opt a character string indicating the details of the analysis "navg" for the average causal effects for t=0,1 and "avg"  for the average causal effects.
#' @param logit a character string indicating, when the outcome is binary, the scale of the average causal effects. "effects" for average causal effects, " OR" average causal effects on OR scale, "logOR" average causal effects on logOR scale and "all" for all scale.
#' @param ... additional arguments affecting the summary produced
#'
#' @return table summarizing the causal analysis
#' @export
#'

summary.mm = function(object,opt="navg",logit="all",...){
    nom.navg=c("ACME.joint.treat","PM(treat)","ACME.joint.control","PM(control)",paste(c("ACME.treat.","PM(treat).","ACME.control.","PM(control)."),rep(object$mediator,each=4),sep=""),"ADE.treat","ADE.control","Total Effect")
    nom.avg=c("ACME.joint","PM.joint",paste(c("ACME.","PM."),rep(object$mediator,each=2),sep=""),"ADE","Total Effect")


  if (length(object$mediator)>1){
    navg=data.frame("."        =nom.navg,
                    Estimation=round(c(object$d1,object$n1,object$d0,object$n0,triout.NM(object$d1.NM,object$n1.NM,object$d0.NM,object$n0.NM),object$z1,object$z0,object$tau.coef),4),
                    IC.inf    =round(c(object$d1.ci[1],object$n1.ci[1],object$d0.ci[1],object$n0.ci[1],triout.ci.NM(object$d1.ci.NM,object$n1.ci.NM,object$d0.ci.NM,object$n0.ci.NM)[,1],object$z1.ci[1],object$z0.ci[1],object$tau.ci[1]),4),
                    IC.sup    =round(c(object$d1.ci[2],object$n1.ci[2],object$d0.ci[2],object$n0.ci[2],triout.ci.NM(object$d1.ci.NM,object$n1.ci.NM,object$d0.ci.NM,object$n0.ci.NM)[,2],object$z1.ci[2],object$z0.ci[2],object$tau.ci[2]),4),
                    P.val     =round(c(object$d1.p,object$n1.p,object$d0.p,object$n0.p,triout.NM(object$d1.p.NM,object$n1.p.NM,object$d0.p.NM,object$n0.p.NM),object$z1.p,object$z0.p,object$tau.p),4)
    )
    avg=data.frame("."        =nom.avg,
                   Estimation=round(c(object$d.avg,object$n.avg,triout.avg.NM(object$d.avg.NM,object$n.avg.NM),object$z.avg,object$tau.coef),4),
                   IC.inf    =round(c(object$d.avg.ci[1],object$n.avg.ci[1],triout.ci.avg.NM(object$d.avg.ci.NM,object$n.avg.ci.NM)[,1],object$z.avg.ci[1],object$tau.ci[1]),4),
                   IC.sup    =round(c(object$d.avg.ci[2],object$n.avg.ci[2],triout.ci.avg.NM(object$d.avg.ci.NM,object$n.avg.ci.NM)[,2],object$z.avg.ci[2],object$tau.ci[2]),4),
                   P.val     =round(c(object$d.avg.p,object$n.avg.p,triout.avg.NM(object$d.avg.p.NM,object$n.avg.p.NM),object$z.avg.p,object$tau.p),4)
    )

    if (!is.null(object$model.y$family)){
      if (object$model.y$family$link=="logit"){

        warning("The proportions mediated on the OR scale can be considered if the outcome is rare, otherwise the proportions mediated on effects scale and/or logOR scale have to be considered.")
        ORnavg=data.frame("."        =paste("OR",nom.navg),
                          Estimation=round(c(object$ORd1,object$ORn1,object$ORd0,object$ORn0,triout.NM(object$ORd1.NM,object$ORn1.NM,object$ORd0.NM,object$ORn0.NM),object$ORz1,object$ORz0,object$ORtau.coef),4),
                          IC.inf    =round(c(object$ORd1.ci[1],object$ORn1.ci[1],object$ORd0.ci[1],object$ORn0.ci[1],triout.ci.NM(object$ORd1.ci.NM,object$ORn1.ci.NM,object$ORd0.ci.NM,object$ORn0.ci.NM)[,1],object$ORz1.ci[1],object$ORz0.ci[1],object$ORtau.ci[1]),4),
                          IC.sup    =round(c(object$ORd1.ci[2],object$ORn1.ci[2],object$ORd0.ci[2],object$ORn0.ci[2],triout.ci.NM(object$ORd1.ci.NM,object$ORn1.ci.NM,object$ORd0.ci.NM,object$ORn0.ci.NM)[,2],object$ORz1.ci[2],object$ORz0.ci[2],object$ORtau.ci[2]),4),
                          P.val     =round(c(object$ORd1.p,object$ORn1.p,object$ORd0.p,object$ORn0.p,triout.NM(object$ORd1.p.NM,object$ORn1.p.NM,object$ORd0.p.NM,object$ORn0.p.NM),object$ORz1.p,object$ORz0.p,object$ORtau.p),4)
        )
        ORavg=data.frame("."        =paste("OR",nom.avg),
                         Estimation=round(c(object$ORd.avg      ,object$ORn.avg      ,triout.avg.NM(   object$ORd.avg.NM                   ,object$ORn.avg.NM)       ,object$ORz.avg      ,object$ORtau.coef) ,4),
                         IC.inf    =round(c(object$ORd.avg.ci[1],object$ORn.avg.ci[1],triout.ci.avg.NM(object$ORd.avg.ci.NM             ,object$ORn.avg.ci.NM)[,1],object$ORz.avg.ci[1],object$ORtau.ci[1]),4),
                         IC.sup    =round(c(object$ORd.avg.ci[2],object$ORn.avg.ci[2],triout.ci.avg.NM(object$ORd.avg.ci.NM             ,object$ORn.avg.ci.NM)[,2],object$ORz.avg.ci[2],object$ORtau.ci[2]),4),
                         P.val     =round(c(object$ORd.avg.p    ,object$ORn.avg.p    ,triout.avg.NM(   object$ORd.avg.p.NM                 ,object$ORn.avg.p.NM)     ,object$ORz.avg.p    ,object$ORtau.p)    ,4)
        )

        logORnavg=data.frame("."        =paste("logOR",nom.navg),
                             Estimation=round(c(object$logORd1,               object$logORn1,      object$logORd0,      object$logORn0,      triout.NM(   object$logORd1.NM,   object$logORn1.NM,   object$logORd0.NM,   object$logORn0.NM),       object$logORz1,      object$logORz0,      object$logORtau.coef), 4),
                             IC.inf    =round(c(object$logORd1.ci[1],         object$logORn1.ci[1],object$logORd0.ci[1],object$logORn0.ci[1],triout.ci.NM(object$logORd1.ci.NM,object$logORn1.ci.NM,object$logORd0.ci.NM,object$logORn0.ci.NM)[,1],object$logORz1.ci[1],object$logORz0.ci[1],object$logORtau.ci[1]),4),
                             IC.sup    =round(c(object$logORd1.ci[2],         object$logORn1.ci[2],object$logORd0.ci[2],object$logORn0.ci[2],triout.ci.NM(object$logORd1.ci.NM,object$logORn1.ci.NM,object$logORd0.ci.NM,object$logORn0.ci.NM)[,2],object$logORz1.ci[2],object$logORz0.ci[2],object$logORtau.ci[2]),4),
                             P.val     =round(c(object$logORd1.p,             object$logORn1.p,    object$logORd0.p,    object$logORn0.p,    triout.NM(   object$logORd1.p.NM, object$logORn1.p.NM, object$logORd0.p.NM, object$logORn0.p.NM),     object$logORz1.p,    object$logORz0.p,    object$logORtau.p),    4)
        )
        logORavg=data.frame("."        =paste("logOR",nom.avg),
                            Estimation=round(c(object$logORd.avg,object$logORn.avg,triout.avg.NM(object$logORd.avg.NM,object$logORn.avg.NM),object$logORz.avg,object$logORtau.coef),4),
                            IC.inf    =round(c(object$logORd.avg.ci[1],object$logORn.avg.ci[1],triout.ci.avg.NM(object$logORd.avg.ci.NM,object$logORn.avg.ci.NM)[,1],object$logORz.avg.ci[1],object$logORtau.ci[1]),4),
                            IC.sup    =round(c(object$logORd.avg.ci[2],object$logORn.avg.ci[2],triout.ci.avg.NM(object$logORd.avg.ci.NM,object$logORn.avg.ci.NM)[,2],object$logORz.avg.ci[2],object$logORtau.ci[2]),4),
                            P.val     =round(c(object$logORd.avg.p,object$logORn.avg.p,triout.avg.NM(object$logORd.avg.p.NM,object$logORn.avg.p.NM),object$logORz.avg.p,object$logORtau.p),4)
        )
      }}
    pmtest= c(object$d1,object$d0,object$d1.NM,object$d0.NM,object$z1,object$z0,object$tau.coef)
    if(sum(pmtest>0)!=length(pmtest)){
      warning("Proportion mediated warning : This quantity makes sense only when the sign the causal mediated effects (i.e., the numerator) are the same as the sign of the average total effect (i.e., the denominator) and when the total effect is bigger than the mediated effect. Confidence intervals may be meaningless when the mediated and/or direct effects have a different sign.")
    }
  }
  else {
    navg=data.frame("."        =c("ACME.treat","PM(treat)","ACME.control","PM(control)","ADE.treat","ADE.control","Total Effect"),
                    Estimation=round(c(object$d1,object$n1,object$d0,object$n0,object$z1,object$z0,object$tau.coef),4),
                    IC.inf    =round(c(object$d1.ci[1],object$n1.ci[1],object$d0.ci[1],object$n0.ci[1],object$z1.ci[1],object$z0.ci[1],object$tau.ci[1]),4),
                    IC.sup    =round(c(object$d1.ci[2],object$n1.ci[2],object$d0.ci[2],object$n0.ci[2],object$z1.ci[2],object$z0.ci[2],object$tau.ci[2]),4),
                    P.val     =round(c(object$d1.p,object$n1.p,object$d0.p,object$n0.p,object$z1.p,object$z0.p,object$tau.p),4)
    )

    avg=data.frame("."        =c("ACME","PM","ADE","Total Effect"),
                   Estimation=round(c(object$d.avg,object$n.avg,object$z.avg,object$tau.coef),4),
                   IC.inf    =round(c(object$d.avg.ci[1],object$n.avg.ci[1],object$z.avg.ci[1],object$tau.ci[1]),4),
                   IC.sup    =round(c(object$d.avg.ci[2],object$n.avg.ci[2],object$z.avg.ci[2],object$tau.ci[2]),4),
                   P.val     =round(c(object$d.avg.p,object$n.avg.p,object$z.avg.p,object$tau.p),4)
    )
    if (!is.null(object$model.y$family)){
      if (object$model.y$family$link=="logit"){
        warning("The proportion mediated on the OR scale can be considered if the outcome is rare, otherwise the proportion mediated on effect scale and/or logOR scale have to be considered.")

        ORnavg=data.frame("."        =c("OR.ACME.treat","OR.PM(treat)","OR.ACME.control","OR.PM(control)","OR.ADE.treat","OR.ADE.control","OR.Total Effect"),
                          Estimation=round(c(object$ORd1,object$ORn1,object$ORd0,object$ORn0,object$ORz1,object$ORz0,object$ORtau.coef),4),
                          IC.inf    =round(c(object$ORd1.ci[1],object$ORn1.ci[1],object$ORd0.ci[1],object$ORn0.ci[1],object$ORz1.ci[1],object$ORz0.ci[1],object$ORtau.ci[1]),4),
                          IC.sup    =round(c(object$ORd1.ci[2],object$ORn1.ci[2],object$ORd0.ci[2],object$ORn0.ci[2],object$ORz1.ci[2],object$ORz0.ci[2],object$ORtau.ci[2]),4),
                          P.val     =round(c(object$ORd1.p,object$ORn1.p,object$ORd0.p,object$ORn0.p,object$ORz1.p,object$ORz0.p,object$ORtau.p),4)
        )

        ORavg=data.frame("."        =c("OR.ACME","OR.PM","OR.ADE","OR.Total Effect"),
                         Estimation=round(c(object$ORd.avg,object$ORn.avg,object$ORz.avg,object$ORtau.coef),4),
                         IC.inf    =round(c(object$ORd.avg.ci[1],object$ORn.avg.ci[1],object$ORz.avg.ci[1],object$ORtau.ci[1]),4),
                         IC.sup    =round(c(object$ORd.avg.ci[2],object$ORn.avg.ci[2],object$ORz.avg.ci[2],object$ORtau.ci[2]),4),
                         P.val     =round(c(object$ORd.avg.p,object$ORn.avg.p,object$ORz.avg.p,object$ORtau.p),4)
        )

        logORnavg=data.frame("."        =c("logOR.ACME.treat","logOR.PM(treat)","logOR.ACME.control","logOR.PM(control)","logOR.ADE.treat","logOR.ADE.control","logOR.Total Effect"),
                             Estimation=round(c(object$logORd1,object$logORn1,object$logORd0,object$logORn0,object$logORz1,object$logORz0,object$logORtau.coef),4),
                             IC.inf    =round(c(object$logORd1.ci[1],object$logORn1.ci[1],object$logORd0.ci[1],object$logORn0.ci[1],object$logORz1.ci[1],object$logORz0.ci[1],object$logORtau.ci[1]),4),
                             IC.sup    =round(c(object$logORd1.ci[2],object$logORn1.ci[2],object$logORd0.ci[2],object$logORn0.ci[2],object$logORz1.ci[2],object$logORz0.ci[2],object$logORtau.ci[2]),4),
                             P.val     =round(c(object$logORd1.p,object$logORn1.p,object$logORd0.p,object$logORn0.p,object$logORz1.p,object$logORz0.p,object$logORtau.p),4)
        )
        logORavg=data.frame("."        =c("logOR.ACME","logOR.PM","logOR.ADE","logOR.Total Effect"),
                            Estimation=round(c(object$logORd.avg,object$logORn.avg,object$logORz.avg,object$logORtau.coef),4),
                            IC.inf    =round(c(object$logORd.avg.ci[1],object$logORn.avg.ci[1],object$logORz.avg.ci[1],object$logORtau.ci[1]),4),
                            IC.sup    =round(c(object$logORd.avg.ci[2],object$logORn.avg.ci[2],object$logORz.avg.ci[2],object$logORtau.ci[2]),4),
                            P.val     =round(c(object$logORd.avg.p,object$logORn.avg.p,object$logORz.avg.p,object$logORtau.p),4)
        )
      }}
    pmtest= c(object$d1,object$d0,object$z1,object$z0,object$tau.coef)
    if(sum(pmtest>0)!=length(pmtest)){
      warning("Proportion mediated warning : This quantity makes sense only when the sign the causal mediated effects (i.e., the numerator) are the same as the sign of the average total effect (i.e., the denominator) and when the total effect is bigger than the mediated effect. Confidence intervals may be meaningless when the mediated and/or direct effects have a different sign.")
    }
  }
  if (opt=="avg"){
    if (is.null(object$model.y$family) || object$model.y$family$link=="probit")
    {res=avg}
    else{
      if (object$model.y$family$link=="logit" & logit=="all"){
        res=cbind(avg,ORavg,logORavg)
      }
      else if (object$model.y$family$link=="logit" & logit=="OR"){
        res=ORavg
      }
      else if (object$model.y$family$link=="logit" & logit=="logOR"){
        res=logORavg
      }
      else{
        res=avg
      }
    }

  }
  else{

    if (is.null(object$model.y$family) || object$model.y$family$link=="probit")
    {res=navg}
    else {
      if (object$model.y$family$link=="logit" & logit=="all"){
        res=cbind(navg,ORnavg,logORnavg)
      }
      else if (object$model.y$family$link=="logit" & logit=="OR"){
        res=ORnavg
      }
      else if (object$model.y$family$link=="logit" & logit=="logOR"){
        res=logORnavg
      }
      else{
        res=navg
      }
    }

  }
  return(res)
}
AllanJe/multimediate documentation built on July 25, 2024, 12:14 p.m.