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xdm20.test

A data set used in example of recur.bart.


Description

A matrix containing a 20% random sample of the testing set for a real data example of recurrent events survival analysis. There are 100 patients in the cohort: 50 in the training set and 50 in the testing set. See the Reference below (and the References therein) for more detailed information; a brief synopsis follows.

xdm20.test contains both the training set and the testing set. There are 798 unique time points so there are 50*798=39900 rows of the training set followed by 50*798=39900 rows of the testing set. For patient's who died prior to the end of follow-up, their external factors are last value carried forward. Therefore, we can use xdm20.test to estimate the cumulative hazard for all patients for all time points.

The full data set, xdm.test, can be obtained online at https://www.mcw.edu/-/media/MCW/Departments/Biostatistics/Tech-Report-64-April-2017-data-file.tar?la=en. There are 488 patients in the full cohort: 235 in the training set and 253 in the testing set.

xdm.test contains both the training set and the testing set. There are 798 unique time points so there are 235*798=187530 rows of the training set followed by 253*798=201894 rows of the testing set. For patient's who died prior to the end of follow-up, their external factors are last value carried forward.

Usage

data(xdm20.test)

References

Sparapani, Rein, Tarima, Jackson, Meurer (2020). Non-parametric recurrent events analysis with BART and an application to the hospital admissions of patients with diabetes. Biostatistics doi:10.1093/biostatistics/kxy032

See Also

xdm20.train

Examples

data(xdm20.test)
head(xdm20.test[ , 1:10])

BART

Bayesian Additive Regression Trees

v2.9
GPL (>= 2)
Authors
Robert McCulloch [aut], Rodney Sparapani [aut, cre], Charles Spanbauer [aut], Robert Gramacy [aut], Matthew Pratola [aut], Martyn Plummer [ctb], Nicky Best [ctb], Kate Cowles [ctb], Karen Vines [ctb]
Initial release
2020-12-21

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