59 lines
3.2 KiB
R
59 lines
3.2 KiB
R
library(ggdist)
|
|
|
|
summarize.estimator <- function(sims.df, suffix='naive', coefname='x'){
|
|
|
|
reported_vars <- c(
|
|
'Bxy',
|
|
paste0('B',coefname,'y.est.',suffix),
|
|
paste0('B',coefname,'y.ci.lower.',suffix),
|
|
paste0('B',coefname,'y.ci.upper.',suffix)
|
|
)
|
|
|
|
|
|
grouping_vars <- c('N','m','B0', 'Bxy', 'Bzy', 'Bzx', 'Px', 'Py','y_explained_variance', 'prediction_accuracy','outcome_formula','proxy_formula','truth_formula','z_bias','y_bias')
|
|
|
|
grouping_vars <- grouping_vars[grouping_vars %in% names(df)]
|
|
|
|
part <- sims.df[,
|
|
unique(c(reported_vars,
|
|
grouping_vars)),
|
|
with=FALSE]
|
|
|
|
|
|
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)]]))
|
|
zero.in.ci <- as.integer(0 >= part[[paste0('B',coefname,'y.ci.lower.',suffix)]]) & (0 <= part[[paste0('B',coefname,'y.ci.upper.',suffix)]])
|
|
bias <- part[[paste0('B',coefname,'y')]] - part[[paste0('B',coefname,'y.est.',suffix)]]
|
|
sign.correct <- as.integer(sign(part$Bxy) == sign(part[[paste0('B',coefname,'y.est.',suffix)]]))
|
|
|
|
part <- part[,':='(true.in.ci = true.in.ci,
|
|
zero.in.ci = zero.in.ci,
|
|
bias=bias,
|
|
sign.correct =sign.correct)]
|
|
|
|
|
|
part.plot <- part[, .(p.true.in.ci = mean(true.in.ci),
|
|
mean.bias = mean(bias),
|
|
mean.est = mean(.SD[[paste0('B',coefname,'y.est.',suffix)]],na.rm=T),
|
|
var.est = var(.SD[[paste0('B',coefname,'y.est.',suffix)]],na.rm=T),
|
|
est.upper.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.975,na.rm=T),
|
|
est.lower.95 = quantile(.SD[[paste0('B',coefname,'y.est.',suffix)]],0.025,na.rm=T),
|
|
mean.ci.upper = mean(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],na.rm=T),
|
|
mean.ci.lower = mean(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],na.rm=T),
|
|
median.ci.upper = median(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],na.rm=T),
|
|
median.ci.lower = median(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],na.rm=T),
|
|
ci.upper.975 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.975,na.rm=T),
|
|
ci.upper.025 = quantile(.SD[[paste0('B',coefname,'y.ci.upper.',suffix)]],0.025,na.rm=T),
|
|
ci.lower.975 = quantile(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],0.975,na.rm=T),
|
|
ci.lower.025 = quantile(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]],0.025,na.rm=T),
|
|
N.ci.is.NA = sum(is.na(.SD[[paste0('B',coefname,'y.ci.lower.',suffix)]])),
|
|
N.sims = .N,
|
|
p.sign.correct = mean(as.integer(sign.correct & (! zero.in.ci))),
|
|
variable=coefname,
|
|
method=suffix
|
|
),
|
|
by=grouping_vars,
|
|
]
|
|
|
|
return(part.plot)
|
|
}
|