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what is the difference between survival analysis and logistic regression with a timing variable?
2 messages · zhongmiao wang, Stephen D. Weigand
On 3/27/07, zhongmiao wang <zhongmiao at gmail.com> wrote:
Hello: If the question is how likely an event will occur at a give time point, can we use logistic regression with time t as a predictor variable? For example, if the data is ID Gender Tenure Churn 1 M 17 0 2 M 3 1 3 M 6 0 4 F 10 1 5 F 9 0 6 F 20 1 We want to predict the likelihood that an insurance policy holder will churn at a given tenure, can we build the model as: logit (churn=1)=b0+b1*Gender+b2*tenure? or we have to use survival analysis for discrete time? Thank you. Best Regards Zhongmiao Wang Senior Analyst RMG Connect
I'd guess you've got censored data so survival analysis is more appropriate. If you've followed a customer for only four months and she hasn't churned (switched companies?) yet, you only know her time to churning is > 4 months, but not exactly how long it is. So you need survival (time to event) methods that account for this partial information. Hope this helps, Stephen Rochester, MN