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  "Title": "The Wally Calibration Plot for Risk Prediction Models",
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  "Author": "Paul F Blanche <paulfblanche@gmail.com>, Thomas A. Gerds\n<tag@biostat.ku.dk>",
  "Maintainer": "Paul F. Blanche <paulfblanche@gmail.com>",
  "Description": "A prediction model is calibrated if, roughly, for any\npercentage x we can expect that x subjects out of 100\nexperience the event among all subjects that have a predicted\nrisk of x%. A calibration plot provides a simple, yet useful,\nway of assessing the calibration assumption. The Wally plot\nconsists of a sequence of usual calibration plots. Among the\nplots contained within the sequence, one is the actual\ncalibration plot which has been obtained from the data and the\nothers are obtained from similar simulated data under the\ncalibration assumption. It provides the investigator with a\ndirect visual understanding of the shape and sampling\nvariability that are common under the calibration assumption.\nThe original calibration plot from the data is included\nrandomly among the simulated calibration plots, similarly to a\npolice lineup. If the original calibration plot is not easily\nidentified then the calibration assumption is not contradicted\nby the data. The method handles the common situations in which\nthe data contain censored observations and occurrences of\ncompeting events.",
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  "RoxygenNote": "6.1.1",
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  "Date/Publication": "2019-10-30 13:40:02 UTC",
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