presmoothedTP

Multi-state models are essential tools in longitudinal data analysis. One primary goal of these models is the estimation of transition probabilities, a critical metric for predicting clinical prognosis across various stages of diseases or medical conditions. Traditionally, inference in multi-state models relies on the Aalen-Johansen (AJ) estimator which is consistent under the Markov assumption. However, in many practical applications, the Markovian nature of the process is often not guaranteed, limiting the applicability of the AJ estimator in more complex scenarios. This package extends the landmark Aalen-Johansen estimator Putter, H, Spitoni, C (2018) incorporating presmoothing techniques described by Soutinho, Meira-Machado and Oliveira (2020) doi:10.1080/03610918.2020.1762895, offering a robust alternative for estimating transition probabilities in non-Markovian multi-state models with multiple states and potential reversible transitions.

Last 30 days

This package has been downloaded 179 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 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 551 times in the last 365 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The day with the most downloads was Jan 27, 2025 with 42 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.