- Background
- Bachelor in Mathematics
- Master in Statistics
- PhD in Biostatistics
- Job
- Statistical consultant for Open Analytics NV
The research discussed in this presentation was conducted during my PhD at the KU Leuven.
Kirsten Van Hoorde - Ben Van Calster
July 2, 2015
The research discussed in this presentation was conducted during my PhD at the KU Leuven.
A good accurate specific pre-operative diagnosis is crucial for:
Note: can be used irrespective of the adopted algorithm or used risk prediction model.
multiCalibration <- function(outcome, k, p = NULL, LP, r = 1, estimates = FALSE, dfr = 2, parametric = TRUE, generic = TRUE, plotseparate = TRUE, plotoverall = TRUE, datapoints = TRUE, smoothing = TRUE, smoothpar = 1, eci = TRUE, intercept = FALSE, slope = FALSE, test = FALSE, legendOutcome = NULL, pathGraphs = "./"){...}
multiCalibrationGeneric <- function(outcome, k, p, r = 1, dfr = 2, generic = TRUE, plotseparate = TRUE, plotoverall = TRUE, datapoints = TRUE, smoothing = TRUE, smoothpar = 1, eci = TRUE, legendOutcome = NULL, pathGraphs = "./"){...}
multiCalibration(outcomeTest, k = 5, p = pTest, LP = lpTest, r = 1, estimates = FALSE, dfr = 2, parametric = TRUE, generic = TRUE, plotseparate = TRUE, plotoverall = TRUE, datapoints = FALSE, smoothing = TRUE, smoothpar = 1.5, eci = TRUE, intercept = TRUE, slope = TRUE, test = TRUE, legendOutcome = c("benign", "borderline", "stage I invasive", "stage II-IV invasive", "metastatic"), pathGraphs = "./graphs/test_")
Note: the calibration is expected to be 'not perfect' in the considered case study, since the data were split in a specific way which enforced differences in training and validation data.
## $ECI ## [1] 0.3432562 ## ## $calibrationIntercepts ## calInt.1 calIntLL.1 calIntUL.1 calInt.2 calIntLL.2 calIntUL.2 calInt.3 ## -0.60132379 -0.82962752 -0.37302006 -0.54280519 -0.77736772 -0.30824265 -0.49632892 ## calIntLL.3 calIntUL.3 calInt.4 calIntLL.4 calIntUL.4 ## -0.72634453 -0.26631331 -0.18817938 -0.46252389 0.08616514 ## ## $calibrationSlopes ## calSlopeLp.1 calSlopeLpLL.1 calSlopeLpUL.1 calSlopeLp.2 calSlopeLpLL.2 calSlopeLpUL.2 ## 1.0183461 0.7380275 1.2986646 0.9987075 0.7344830 1.2629320 ## calSlopeLp.3 calSlopeLpLL.3 calSlopeLpUL.3 calSlopeLp.4 calSlopeLpLL.4 calSlopeLpUL.4 ## 0.8816050 0.6476059 1.1156042 1.0048464 0.6924594 1.3172334 ## ## $Deviances ## devianceOriginal devianceIntercept devianceSlopes ## 2130.282 2082.359 2070.403 ## ## $PValues ## pOverall pInt pSlopes ## 4.922852e-10 9.795137e-10 1.767830e-02
http://repos.openanalytics.eu/html/multiCalibration.html