Multivariate survival data occur in many different disciplines. If the correlation in the data is of interest by itself, two main modeling tools exist, the frailty model (Duchateau and Janssen, 2008) and the copula model. The use of copula modeling has been restricted due to the lack of software on the one hand. On the other hand, copula models mainly deal theoretically with small clusters, all of equal size, i.e., containing the same number of subjects. The Sunclarco package can handle large unbalanced clusters, i.e., of varying size. This allows the use of copula models to data sets that could previously not be handled, e.g., multicentre cancer clinical trials. Furthermore, the Sunclarco package is flexible in terms of the baseline hazard (Weibull, piecewise exponential, unspecified (using partial likelihood) and in terms of the copula function (Clayton and Gumbel-Hougaard).
Ewoud De Troyer
Prenen L, Braekers R, Duchateau L (2017). Extending the Archimedean copula methodology to model multivariate survival data grouped in clusters of variable size. Journal of the Royal Statistical Society, 6, 1-24.
Duchateau L, Janssen P. (2008). The frailty model. Spinger Verlag.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.