Added lrt proportion to ROSALI aggregation
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@ -621,6 +621,7 @@ compile_simulation2_rosali <- function(scenario) {
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thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"])),na.rm=F)/7,0) ))
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thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"])),na.rm=F)/7,0) ))
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}
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}
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lrt.pass <- mean(s$lrt_passed)
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z <- data.frame(m.beta=mean(s$beta),
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z <- data.frame(m.beta=mean(s$beta),
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se.empirical.beta=sd(s$beta),
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se.empirical.beta=sd(s$beta),
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se.analytical.beta=mean(s$se_beta),
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se.analytical.beta=mean(s$se_beta),
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@ -636,7 +637,8 @@ compile_simulation2_rosali <- function(scenario) {
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moreflexible.detect=moreflexible.detect,
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moreflexible.detect=moreflexible.detect,
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any.detect=any.detect,
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any.detect=any.detect,
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thay.tpr=thay.tpr,
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thay.tpr=thay.tpr,
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thay.fpr=thay.fpr
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thay.fpr=thay.fpr,
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lrt.pass=lrt.pass
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)
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)
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d <- cbind(b,a,z)
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d <- cbind(b,a,z)
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d$prop.
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d$prop.
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