riskRegression

Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.

Last 30 days

This package has been downloaded 8,865 times in the last 30 days. That's a lot of interest! Someone might even write a blog post about it. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 234 times.

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Last 365 days

This package has been downloaded 99,626 times in the last 365 days. This work is reaching a lot of screens. A significant achievement indeed! The day with the most downloads was Oct 24, 2024 with 459 downloads.

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