OptimalCutoff 约登指数计算

OptimalCutoff Youden index calculation

计算二分变量 (a vs b) 的 ROC 曲线后。我想计算最佳截止值来区分这个变量。约登指数是优化区分灵敏度和特异性的值。

显然,包 "OptimalCutpoints" 应该可以做到。但是,我得到了这个奇怪的错误。下面插入代码:

library(pROC)
library(OptimalCutpoints)
df <- structure(list(value = c(1945.523629, 2095.549323, 2066.585153, 
                         2445.878083, 2112.252632, 2115.92955, 2000.285032, 2224.611905, 
                         1616.534694, 1668.017699, 1475.980978, 1940.849817, 1716.666667, 
                         2153.284314, 2063.353635, 2163.070313, 1856.319149, 1499.986928, 
                         2240.440449, 1869.083916, 1807.196078, 2025.603604, 1638.22973, 
                         1781.602941, 2014.013809, 1906.027356, 2033.148718, 1923.403162, 
                         1687.107744, 2632.280305, 1774.073084, 2196.162393, 2164.108659, 
                         2055.031216, 2229.501425, 1273.872576, 2224.126126, 2006.858974, 
                         1956.601942, 1808.214521, 1535.387136, 1382.15, 1596.69693, 1779.477273, 
                         1577.174699, 1908.321526, 1833.124454, 1679.492978, 1777.31114, 
                         1988.249023, 1736.75, 1985.68521, 1821.025974, 1745.325862, 1805.640777, 
                         2326.821229, 1858.558824, 2025.622727, 2197.781321, 1475.685446, 
                         2000.906423, 1714.749573, 1436.529412, 1981.15572, 1939.612779, 
                         2007.679335, 2029.189536, 1644.298246, 1824.697342, 2281.990385, 
                         2131.331776, 1143.722714, 1784.578076, 2143.131579, 982.4908457, 
                         2217.021592, 1799.512346, 526.7047753, 1613.25, 951.9103079, 
                         1006.241888, 1146.276835, 1651.474138, 1568.484778, 1938.867704, 
                         792.5410822, 1602.037383, 1244.281863, 957.5739437, 819.6116071, 
                         879.2128326, 1189.638632, 775.5525292, 1148.193333, 1130.812183, 
                         902.34, 994.3302961), type = c("a", "a", "a", "a", "a", "a", 
                                                        "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", 
                                                        "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", 
                                                        "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", 
                                                        "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", 
                                                        "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", 
                                                        "a", "a", "a", "a", "a", "a", "b", "b", "b", "b", "b", "b", "b", 
                                                        "b", "b", "b", "b", "b", "b", "b", "b", "b", "b", "b", "b", "b"
                         )), .Names = c("value", "type"), row.names = c(NA, -97L), class = "data.frame")

rocobj <- plot.roc(df$type, df$value, percent = TRUE, main="ROC", col="#1c61b6", add=FALSE)

optimal.cutpoint.Youden <- optimal.cutpoints(X = "value", status = "type", tag.healthy = 0, methods = "Youden", 
                                             data = df, pop.prev = NULL,
                                             control = control.cutpoints(), ci.fit = FALSE, conf.level = 0.95, trace = FALSE)
summary(optimal.cutpoint.Youden)
plot(optimal.cutpoint.Youden)

错误:您的数据集中没有健康的受试者。请查看数据和 变量。患病率必须是大于 0 且小于 1 的值。

我可能遗漏了一些非常明显的东西。尝试根据包的帮助文件修改代码,还是无法解决错误。

非常感谢你,我为我的 R 道歉 "skills"

PS:我理解定义 "optimal cutoff" 的局限性,因为它取决于您的敏感性与特异性等的重要性。我只是想知道我们会得到什么价值使用这种技术。

问题在于您如何定义 tag.healthy 参数。它应该是 'a''b',因为它们在您的数据中。您已将其定义为 0

希望对您有所帮助。