Update AEO analysis; re-arrange order of methods in plots

Author: nicebread

4-EstimationPlot.R

@@ -38,7 +38,7 @@ theme_metashowdown <- theme(
 
 # reduced set for revision
 	summ2 <- summ %>% filter(method %in% c("reMA", "TF", "PETPEESE.lm", "pcurve", "puniform", "3PSM", "WAAP-WLS")) %>% 
-	  mutate(method = factor(method, levels=c("reMA", "TF", "PETPEESE.lm", "pcurve", "puniform", "3PSM", "WAAP-WLS"), labels=c("RE", "TF", "PET-PEESE", "p-curve", "p-uniform", "3PSM", "WAAP-WLS")))
+	  mutate(method = factor(method, levels=c("reMA", "TF", "WAAP-WLS", "pcurve", "puniform", "PETPEESE.lm", "3PSM"), labels=c("RE", "TF", "WAAP-WLS", "p-curve", "p-uniform", "PET-PEESE", "3PSM")))
 
 
 

5-hypTestPlot.R

@@ -25,7 +25,7 @@ H1 <- 0.5
 # reduced set for revision
 hyp.sel <-  summ %>%
  filter(method %in% c("reMA", "TF", "PETPEESE.lm", "pcurve.evidence", "puniform", "3PSM", "WAAP-WLS")) %>%
- mutate(method = factor(method, levels=c("reMA", "TF", "PETPEESE.lm", "pcurve.evidence", "puniform", "3PSM", "WAAP-WLS"), labels=c("RE", "TF", "PET-PEESE", "p-curve", "p-uniform", "3PSM", "WAAP-WLS"))) %>%
+ mutate(method = factor(method, levels=c("reMA", "TF", "WAAP-WLS", "pcurve.evidence", "puniform", "PETPEESE.lm", "3PSM"), labels=c("RE", "TF", "WAAP-WLS", "p-curve", "p-uniform", "PET-PEESE", "3PSM"))) %>%
 	ungroup()
 
 

8-pcurve recover AEO.R

@@ -1,10 +1,10 @@
 library(dplyr)
 library(ggplot2)
-load("../dataFiles/res.wide.RData")
+load("dataFiles/res.wide.RData")
 
 # res.wide$qrp.label <- factor(res.wide$qrpEnv, levels=c("none", "med", "high"), labels=paste0("QRP = ", c("none", "med", "high")), ordered=TRUE)
 # res.wide$delta.label <- factor(res.wide$delta, levels=c(0, 0.2, 0.5, 0.8), labels=paste0("delta = ", c(0, 0.2, 0.5, 0.8)), ordered=TRUE)
-# res.wide$selProp.label <- factor(res.wide$selProp, levels=unique(res.wide$selProp), labels=paste0("PB = ", unique(res.wide$selProp)))
+# res.wide$censor <- factor(res.wide$selProp, levels=unique(res.wide$selProp), labels=paste0("PB = ", unique(res.wide$selProp)))
 
 # ---------------------------------------------------------------------
 #  Compute summary measures across replications
@@ -14,7 +14,7 @@ posify <- function(x) {x[x<0] <- 0; return(x)}
 # use the data set without any reductions (i.e., also keep p-curves with <=3 sign. studies)
 PC <- res.wide %>% filter(method=="pcurve", !is.na(kSig_estimate) & kSig_estimate >= 1)
 
-summ.PC <- PC %>% group_by(condition, k, k.label, delta, delta.label, qrpEnv, qrp.label, selProp, selProp.label, tau, tau.label) %>% 
+summ.PC <- PC %>% group_by(condition, k, k.label, delta, delta.label, qrpEnv, qrp.label, censor, censor.label, tau, tau.label) %>% 
 	dplyr::summarise(
 		meanEst.AEO		= mean(b0_estimate, na.rm=TRUE),
 		meanEst.pos.AEO	= mean(posify(b0_estimate), na.rm=TRUE),
@@ -34,7 +34,7 @@ summ.PC <- PC %>% group_by(condition, k, k.label, delta, delta.label, qrpEnv, qr
 
 # average kSig in tau=0 conditions:
 
-summ.PC %>% filter(tau==0, delta <= 0.2, qrpEnv=="none", selProp==0) %>% select(1:8, nSig)
+summ.PC %>% filter(tau==0, delta == 0, qrpEnv=="none") %>% select(1:8, nSig)
 
 # ---------------------------------------------------------------------
 # Plot
@@ -46,7 +46,7 @@ summ.PC %>%
 	geom_hline(yintercept=0) + 
 	coord_flip(ylim=c(-0.4, 0.25)) +
 	xlab("k") + ylab("Mean error (relative to average true effect size of studies submitted to p-curve)") +
-	facet_grid(tau.label~selProp.label~qrp.label) + 
+	facet_grid(tau.label~censor~qrp.label) + 
 	theme_bw() + ggtitle("Effect size estimates (keep all), all p-curves (i.e., >= 4 study rule not applied)")
 
 ggsave("Plots/ME_AEO_raw.jpg", dpi=120)	
@@ -58,7 +58,7 @@ summ.PC %>%
 	geom_hline(yintercept=0) + 
 	coord_flip(ylim=c(-0.4, 0.25)) +
 	xlab("k") + ylab("Mean error (relative to average true effect size of studies submitted to p-curve)") +
-	facet_grid(tau.label~selProp.label~qrp.label) + 
+	facet_grid(tau.label~censor~qrp.label) + 
 	theme_bw() + ggtitle("Posified effect size estimates, all p-curves (i.e., >= 4 study rule not applied)")
 
 ggsave("Plots/ME_AEO_pos.jpg", dpi=120)	
@@ -74,7 +74,7 @@ summ.PC %>%
 	geom_hline(yintercept=0) + 
 	coord_flip(ylim=c(0, 0.8)) +
 	xlab("k") + ylab("RMSE (relative to average true effect size of studies submitted to p-curve)") +
-	facet_grid(tau.label~selProp.label~qrp.label) + 
+	facet_grid(tau.label~censor~qrp.label) + 
 	theme_bw() + ggtitle("Effect size estimates (keep all), all p-curves (i.e., >= 4 study rule not applied)")
 
 ggsave("Plots/RMSE_AEO.jpg", dpi=120)	
@@ -85,7 +85,7 @@ summ.PC %>%
 	geom_hline(yintercept=0) + 
 	coord_flip(ylim=c(0, 0.8)) +
 	xlab("k") + ylab("RMSE (relative to average true effect size of studies submitted to p-curve)") +
-	facet_grid(tau.label~selProp.label~qrp.label) + 
+	facet_grid(tau.label~censor~qrp.label) + 
 	theme_bw() + ggtitle("Posified effect size estimates, all p-curves (i.e., >= 4 study rule not applied)")
 
 ggsave("Plots/RMSE_AEO_pos.jpg", dpi=120)