I'm dabbling in survival analysis, applied to cars. I created a survival graph based on kaplan-meyer. However, guidance on how to apply that to inference seems a bit thin (or i'm dense ;-) ) so I ask you to validate my current calculation of how many cars will still be on the road next year, given my data, collected about cars for the last few years. The kaplan-meyer graph describes the survival of a car related to it's age.
My calculation is : I have a population of cars on the road now. so for their current age, they have survived with probability 1. Now, their chance to reach next year, using the survival graph based on age, is (i think) : value[next year]/value[this year]. then I sum up this ratio for all cars currently still on the road, and that gives me the amount of cars to be on the road next year.
Please let me know if this is a valid way to estimate the amount of cars still on the road next year, given their age. Or what method you apply in cases like mine.
Thanks & Regards Ronald
I first just looked up the numbers in the graph for [age+1] and summed them over all cars, but (fortunately) that gave me far too low estimates, which got me thinking. I'm doing the calculation as a review of a report that included historical numbers. that gave me some indication, so i'm thinking i'm on the right track, but I felt the same way the previous time. So "feeling sure about it" might not be a good estimator of validity ;-)