R/summary.est.matched.data.frame.R

In nonrandom: Stratification and matching by the propensity score

summary.est.matched.data.frame <- function(object,
                                           ...)
{
  if( object$family == "binomial" ){
    meas <- "odds ratios"
    col.n <- c("or","SE[log[or]]","[95%-CI[or]]")
  }else{
    meas <- "effects"
    col.n <- c("effect","SE[effect]","[95%-CI[effect]]")
  }
  
  if ( !is.list(object$lr.estimation) ){
    lr.eff.c <- lr.se.c <- NULL
    lr.eff.m <- lr.se.m <- NULL
    lr.ci.c <- lr.ci.m <- NULL
    
  }else{
    if( object$family == "binomial" ){
      lr.eff.c <- round(object$lr.estimation$effect,3)
      lr.se.c  <- round(object$lr.estimation$se,4)
      lr.eff.m <- round(object$lr.estimation$effect.marg,3)
      lr.se.m  <- round(object$lr.estimation$se.marg,4)

      lr.ci.c <- round(c(exp(log(lr.eff.c) - qnorm(0.975)*lr.se.c),
                         exp(log(lr.eff.c) + qnorm(0.975)*lr.se.c)),3)

      lr.ci.m <- round(c(exp(log(lr.eff.m) - qnorm(0.975)*lr.se.m),
                         exp(log(lr.eff.m) + qnorm(0.975)*lr.se.m)),3)
    }else{
      lr.eff.c <- round(object$lr.estimation$effect,3)
      lr.se.c  <- round(object$lr.estimation$se,4)
      
      lr.ci.c <- round(c(lr.eff.c - qnorm(0.975)*lr.se.c,
                         lr.eff.c + qnorm(0.975)*lr.se.c),3)
    }
  }
    
  if ( !is.list(object$ps.estimation$adj) ){    
    ps.adj.eff <-
      ps.adj.se <-
        ps.adj.ci <- NULL
  }else{
    ps.adj.eff <- round(object$ps.estimation$adj$effect,3)
    ps.adj.se  <- round(object$ps.estimation$adj$se,4)
   
    if( object$family == "binomial" ){
      ps.adj.ci <- round(c(exp(log(ps.adj.eff) - qnorm(0.975)*ps.adj.se),
                           exp(log(ps.adj.eff) + qnorm(0.975)*ps.adj.se)),3)
    }else{
      ps.adj.ci <- round(c(ps.adj.eff - qnorm(0.975)*ps.adj.se,
                           ps.adj.eff + qnorm(0.975)*ps.adj.se),3)     
    }
  }
  
  if ( object$family=="binomial" ){

    crude <- round(object$ps.estimation$crude$effect,3)
    crude.se <- round(object$ps.estimation$crude$se,4)
    crude.ci <- round(c(exp(log(crude)-qnorm(0.975)*crude.se),
                        exp(log(crude)+qnorm(0.975)*crude.se)),3)

    diff <- round(object$ps.estimation$unadj$effect,3)
    diff.se <- round(object$ps.estimation$unadj$se,4)  
    
    diff.ci <- round(c(exp(log(diff)-qnorm(0.975)*diff.se),
                       exp(log(diff)+qnorm(0.975)*diff.se)),3)

    
  }else{
    crude <- round(object$ps.estimation$crude$effect,3)
    crude.se <- round(object$ps.estimation$crude$se,4)
    crude.ci <- round(c(crude-qnorm(0.975)*crude.se,
                        crude+qnorm(0.975)*crude.se),3)
    
    diff <- round(object$ps.estimation$unadj$effect,3)
    diff.se <- round(object$ps.estimation$unadj$se,4) 
    diff.ci <- round(c(diff-qnorm(0.975)*diff.se,
                       diff+qnorm(0.975)*diff.se),3)

  }

  if ( object$family=="binomial" ){    
    eff <- c(" -----",
             paste("",crude,sep=""),
             "",
             paste("",diff,sep=""),
             paste("",ps.adj.eff,sep=""),
             "",
             paste("",lr.eff.c,sep=""),
             paste("",lr.eff.m,sep=""),
             "")    
    se <- c(" -----------",
            paste("",crude.se,"", sep=""),
            "",
            paste("",diff.se,"", sep=""),
            paste("",ps.adj.se,"", sep=""),
            "",
            paste("",lr.se.c,"", sep=""),
            paste("",lr.se.m,"", sep=""),
            "")
    ci <- c(" ------------",
            paste("[",crude.ci[1],",",crude.ci[2], "]",sep=""),
            "",
            paste("[",diff.ci[1],",",diff.ci[2],"]",sep=""),
            paste("[",ps.adj.ci[1],",",ps.adj.ci[2],"]",sep=""),
            "",
            paste("[",lr.ci.c[1],",",lr.ci.c[2],"]",sep=""),
            paste("[",lr.ci.m[1],",",lr.ci.m[2],"]",sep=""),
            "")
    df <-
      data.frame(cbind(eff, se, ci),
                 row.names=c("",
                   "Crude",
                   "Matching", "  Unadjusted", "  Adjusted",
                   "Regression", "  Conditional", "  Marginal", " "))
    colnames(df) <- col.n
  }else{
    eff <- c(" ------",
             paste("",crude,sep=""),
             "",
             paste("",diff,sep=""),
             paste("",ps.adj.eff,sep=""),
             paste("",lr.eff.c,sep=""),
             "")  
    se <- c(" ----------",
            paste("",crude.se,"", sep=""),
            "",
            paste("",diff.se,"", sep=""),
            paste("",ps.adj.se,"", sep=""),
            paste("",lr.se.c,"", sep=""),
            "")
    ci <- c(" ----------------",
            paste("[",crude.ci[1],",",crude.ci[2], "]",sep=""),
            "",
            paste("[",diff.ci[1],",",diff.ci[2],"]",sep=""),
            paste("[",ps.adj.ci[1],",",ps.adj.ci[2],"]",sep=""),
            paste("[",lr.ci.c[1],",",lr.ci.c[2],"]",sep=""),
            "")    
    df <- data.frame(cbind(eff, se, ci),
                     row.names=c("",
                       "Crude",
                       "Matching", "  Unadjusted", "  Adjusted",
                       "Regression", " "))
    colnames(df) <- col.n 
  }

  

  sum.eff <- list(treat   = object$name.treat,
                  outcome = object$name.resp,
                  measure = meas,
                  eff.tab = df)

  class(sum.eff) <- "summary.est.matched.data.frame"
  
  sum.eff
  
}