# Survival analysis using Linear Probability Models and Panel data

This question might have been answered somewhere else but I could not find it.

Hi all. My research is about investigating whether a certain policy increases the speed of construction of housing units or has no effect. Since market factors play role in duration, I need to structure it in panel format and I am in desperate need for panel data tools (Fixed effects, clustering etc.)

I was thinking to use Probability Linear Models (PLM) for estimation that its results are much easier to explain as well as the ability to use panel data settings. Also there are new methods to produce better estimates which you can find here.

However, I could not find a source that explains how I can estimate a survival model using PLM or Least Square methods. All I could find was Additive Hazard models, which are a bit problematic because of time-variant covariates and the difficulty in reporting results as well as statistical inference.

I want to know do you have any suggestions or do you any sources that could help me with this settings?

In short, how can I estimate a survival model in panel format using linear regression.

Thank you all for your time!

• It's not clear that a linear probability model will help you. The reference you cite uses that only as a first step in a linear discriminant model (LDM) approach to efficient imputation on a large scale--which involves logistic regression as a final step, anyway. For evaluating the LDM approach, it says: "Standard logit should be the gold standard. LDM can't do any better than conventional logit..." Please edit your question to say more about the specific problems you face, as there are many tools available for refining time-to-event analysis both in continuous and in discrete time scales.
– EdM
Dec 7, 2021 at 14:47
• Thank you @EdM for your comment. I modified the question as you advised.My main issue is finding a way to estimate survival model using Linear regression. LDM is just helping with producing estimates for further analysis. Dec 8, 2021 at 13:26
• I mean, once you estimated your discrete time model you can use the Allison procedure to get the instant hazards, and then based on those calculate the cumulative hazards. (That gets you point estimates, I don't know about standard errors though for those survival curves.) Dec 8, 2021 at 13:36