Survival curve/time to event analysis without individual subject tracking

I am trying to perform a survival curve/time to event analysis to determine if two treatments cause animal offspring to meet developmental milestones at different ages. For example, I have a litter of offspring with 5 pups and I record their behavior daily with a score of 0,1, or 2 (0=not achieved, 1=partial, 2=completely achieved). The problem is that I cannot ID individual offspring every day. So I end up with a litter based dataset where I cannot ensure that each row is an individual. See below for an example data set: P3 P4 P5 P6 P7 P8 P9 P10 1 0 2 2 2 2 2 2 0 0 1 1 1 2 2 2 2 0 0 1 2 2 2 2 0 1 2 2 2 2 2 2 0 2 2 2 2 1 2 2 I want to calculate the survival curve to calculate the age to reach 2. But I cannot guarantee that each row in the dataset is the same individual. Does this cause any problems for Kaplan Meier anaylsis? I am using survfit from the survival package in RStudio. I am able to run the analysis fine, I am just not sure if it is valid. The eventual goal would be to statistically compare these curves based on treatment with the survdiff function (uses Gehan-Wilcoxin test). Any advice on whether this is a valid analysis or how to implement this would be appreciated. EDIT: Someone in the comments asked if it was possible for a subject to drop back from 2 to 1 or 1 to 0 as time goes on. Theoretically yes, but practically rarely. Some of the tasks that are being measured are behaviors and a 0 would then represent "not being observed on this day". I looked over my r…