# interval censored survival analysis with time dependent covariates

I'm working on a long-term, large tree data set from Africa. I have data on the same set of individuals from year 2006, 2008, 2011 and 2015. The data consist of tree status (alive/dead) at each time period and covariates such as elephant damage (type and proportion) and fire damage (type and proportion), rainfall, species, crown height etc. I would like to use the data from 2006-2011 to predict mortality in 2015, based on the values of covariates for 2011-2015.

Since the data includes censored individuals, I felt I should apply a survival analysis technique such as a Cox PH regression. However, the data seems to be interval censored, since exact time of death is not observed. I just know that death occurred before 2006, between 2006 and 2008 or 2008 and 2011. I also have time-dependent covariates such as proportion elephant damage for each census interval.

Is there an R package for conducting interval-based CoxPH with time dependent covariates? Is there some other analysis framework that would be better suited to this dataset and my question, such as a mixed-effects logistic regression with time-dependent covariates?

I am new to survival analysis. Any guidance would be greatly appreciated!

• Are all of the events (deaths) in your data in the last period (2015)? Dec 1 '16 at 18:49
• Hi, no all of the deaths are not in the last period (2015). They are spread across all the census years (2006, 2008, 2011 and 2015). Dec 4 '16 at 14:07
• The vingette of the R library timedep is a good starting point. May 10 '18 at 21:36