simulations/summarize_estimator.R

   1
   2 summarize.estimator <- function(df, suffix='naive', coefname='x'){
   3
   4     part <- df[,c('N',
   5                   'm',
   6                   'Bxy',
   7                   paste0('B',coefname,'y.est.',suffix),
   8                   paste0('B',coefname,'y.ci.lower.',suffix),
   9                   paste0('B',coefname,'y.ci.upper.',suffix),
  10                   'y_explained_variance',
  11                   'Bzx',
  12                   'Bzy',
  13                   'accuracy_imbalance_difference'
  14                   ),
  15                with=FALSE]
  16
  17     true.in.ci <- as.integer((part$Bxy >= part[[paste0('B',coefname,'y.ci.lower.',suffix)]]) & (part$Bxy <= part[[paste0('B',coefname,'y.ci.upper.',suffix)]]))
  18     zero.in.ci <- as.integer(0 >= part[[paste0('B',coefname,'y.ci.lower.',suffix)]]) & (0 <= part[[paste0('B',coefname,'y.ci.upper.',suffix)]])
  19     bias <- part$Bxy - part[[paste0('B',coefname,'y.est.',suffix)]]
  20     sign.correct <- as.integer(sign(part$Bxy) == sign(part[[paste0('B',coefname,'y.est.',suffix)]]))
  21
  22     part <- part[,':='(true.in.ci = true.in.ci,
  23                        zero.in.ci = zero.in.ci,
  24                        bias=bias,
  25                        sign.correct =sign.correct)]
  26
  27     part.plot <- part[, .(p.true.in.ci = mean(true.in.ci),
  28                           mean.bias = mean(bias),
  29                           mean.est = mean(.SD[[paste0('B',coefname,'y.est.',suffix)]]),
  30                           var.est = var(.SD[[paste0('B',coefname,'y.est.',suffix)]]),
  31                           est.upper.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.95,na.rm=T),
  32                           est.lower.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.05,na.rm=T),
  33                           N.sims = .N,
  34                           p.sign.correct = mean(as.integer(sign.correct & (! zero.in.ci))),
  35                           variable=coefname,
  36                           method=suffix
  37                           ),
  38                       by=c("N","m",'y_explained_variance','Bzx', 'Bzy', 'accuracy_imbalance_difference')
  39                       ]
  40
  41     return(part.plot)
  42 }