Sage-Bionetworks / challengescoring

This R package provides scoring mechanisms for computational challenges and implements the bayesBootLadderBoot approach for avoiding test data leakage.
Apache License 2.0
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Issue with challengescoring vignette #16

Open andrewelamb opened 4 years ago

andrewelamb commented 4 years ago

I'm getting this error trying to get the vignette to run:

library(survival)
goldStandard <- Surv(d.time, death) %>% as.character() %>% as.data.frame() %>% magrittr::set_colnames(c("gold"))
predictions <- age_new %>% as.data.frame() %>% magrittr::set_colnames(c("pred"))
prevPredictions <- age_previous %>% as.data.frame() %>% magrittr::set_colnames(c("pred"))

bootLadderBoot(predictions = predictions,
               predictionColname = "pred",
               prevPredictions = prevPredictions,
               goldStandard = goldStandard,
               goldStandardColname = "gold",
               scoreFun = c_statistic,
               verbose = T)

Error: `by` required, because the data sources have no common variables
16.
stop(fallback)
15.
signal_abort(cnd)
14.
.abort(text)
13.
glubort(fmt_args(args), ..., .envir = .envir)
12.
bad_args("by", "required, because the data sources have no common variables")
11.
common_by.NULL(by, x, y)
10.
common_by(by, x, y)
9.
full_join.tbl_df(tbl_df(x), y, by = by, copy = copy, ...)
8.
full_join(tbl_df(x), y, by = by, copy = copy, ...)
7.
as.data.frame(full_join(tbl_df(x), y, by = by, copy = copy, ...))
6.
full_join.data.frame(goldStandardDF, predictionsDF)
5.
dplyr::full_join(goldStandardDF, predictionsDF)
4.
eval(lhs, parent, parent)
3.
eval(lhs, parent, parent)
2.
dplyr::full_join(goldStandardDF, predictionsDF) %>% dplyr::full_join(prevPredictionsDF) %>% dplyr::select_(goldStandardColname, predictionColname, "prevpred") %>% purrr::set_names("gold", "pred", "prevpred") at bootstrap.R#71
1.
bootLadderBoot(predictions = predictions, predictionColname = "pred", prevPredictions = prevPredictions, goldStandard = goldStandard, goldStandardColname = "gold", scoreFun = c_statistic, verbose = T)