casebase

Fit flexible and fully parametric hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. Our formulation allows for arbitrary functional forms of time and its interactions with other predictors for time-dependent hazards and hazard ratios. From the fitted hazard model, we provide functions to readily calculate and plot cumulative incidence and survival curves for a given covariate profile. This approach accommodates any log-linear hazard function of prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing incidence density via population time plots. Based on the case-base sampling approach of Hanley and Miettinen (2009) doi:10.2202/1557-4679.1125, Saarela and Arjas (2015) doi:10.1111/sjos.12125, and Saarela (2015) doi:10.1007/s10985-015-9352-x.

Last 30 days

This package has been downloaded 1,056 times in the last 30 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 41 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 15,557 times in the last 365 days. The academic equivalent of having a dedicated subreddit. There are fans, and maybe even a few trolls! The day with the most downloads was Apr 11, 2024 with 165 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.