Hi All, In one of my projects, I will not be getting patient level data for survival analysis (the usual time to an event, treatment and baseline covariates) but summarized data. I have to suggest a proper way to summarize patient level data for survival analysis. I am trying to figure the best possible summary data that will be amenable to modeling. One type of summary data I have in mind is attached It is made-up data. The actual data will have more time points and covariates. All covariates, including age, are going to be categorical. This data set has time points which you can take to be 6-month intervals (1 corresponds to 0-6 months, 2 corresponds to 6-12 months and 3 corresponds to > 12 months), number of events during each interval, number of  patients at risk at the beginning of each interval and two categorical variables. One of the categorical variables has three levels and the other (let's say treatment), two levels. Clearly, number of  patients at risk at the beginning of each interval (except the fist) excludes patients who had an event or were censored in the previous interval. This table has one record for each level of each categorical variable and time period. I have two questions. Is this the best way to organize the data? If so, what model would be suitable. The log-linear model is not because it does take into account the conditional nature of the data. That is, number at risk at the beginning of each interval clearly is determined by events and censoring in the previous interval. I would like to know what you would suggest. ... View more