simulations/summarize_estimator.R

   1
   2 summarize.estimator <- function(df, suffix='naive', coefname='x'){
   3
   4     reported_vars <- c(
   5                        'Bxy',
   6                        paste0('B',coefname,'y.est.',suffix),
   7                        paste0('B',coefname,'y.ci.lower.',suffix),
   8                        paste0('B',coefname,'y.ci.upper.',suffix)
   9                        )
  10
  11
  12     grouping_vars <- c('N','m','B0', 'Bxy', 'Bzy', 'Bzx', 'Px', 'y_explained_variance', 'prediction_accuracy','outcome_formula','proxy_formula','truth_formula','z_bias','y_bias')
  13
  14     grouping_vars <- grouping_vars[grouping_vars %in% names(df)]
  15
  16     part <- df[,
  17                c(reported_vars,
  18                  grouping_vars),
  19                with=FALSE]
  20
  21
  22     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)]]))
  23     zero.in.ci <- as.integer(0 >= part[[paste0('B',coefname,'y.ci.lower.',suffix)]]) & (0 <= part[[paste0('B',coefname,'y.ci.upper.',suffix)]])
  24     bias <- part[[paste0('B',coefname,'y')]] - part[[paste0('B',coefname,'y.est.',suffix)]]
  25     sign.correct <- as.integer(sign(part$Bxy) == sign(part[[paste0('B',coefname,'y.est.',suffix)]]))
  26
  27     part <- part[,':='(true.in.ci = true.in.ci,
  28                        zero.in.ci = zero.in.ci,
  29                        bias=bias,
  30                        sign.correct =sign.correct)]
  31
  32     part.plot <- part[, .(p.true.in.ci = mean(true.in.ci),
  33                           mean.bias = mean(bias),
  34                           mean.est = mean(.SD[[paste0('B',coefname,'y.est.',suffix)]],na.rm=T),
  35                           var.est = var(.SD[[paste0('B',coefname,'y.est.',suffix)]],na.rm=T),
  36                           est.upper.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.975,na.rm=T),
  37                           est.lower.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.025,na.rm=T),
  38                           mean.ci.upper = mean(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],na.rm=T),
  39                           mean.ci.lower = mean(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],na.rm=T),
  40                           ci.upper.975 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.975,na.rm=T),
  41                           ci.upper.025 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.025,na.rm=T),
  42                           ci.lower.975 = quantile(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],0.975,na.rm=T),
  43                           ci.lower.025 = quantile(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],0.025,na.rm=T),
  44                           N.ci.is.NA = sum(is.na(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]])),
  45                           N.sims = .N,
  46                           p.sign.correct = mean(as.integer(sign.correct & (! zero.in.ci))),
  47                           variable=coefname,
  48                           method=suffix
  49                           ),
  50                       by=grouping_vars,
  51                       ]
  52
  53     return(part.plot)
  54 }