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I have panel data on companies and I'm interested in how several DVs and covariates impact the time until a company gets funded. My data (pandas Dataframe) looks something like that:

               DV1 ... DV5 CV1...CV12 Funding CompanyFounded
Company Period
A       1      0       0    5    4    False   False
B       1      0       0    5    6    False   False
...
A       2      0       0    5    4    False   False
B       2      3       5    5    6    False   True
...
A       45     1       2    5    4    False   True
B       45     534     42   5    6    True    True

Now I'd like to perform a survival analysis. I know that I could calculate averages and calculate the time to first funding using CoxPHFitter. But I did not find any model to fit panel data. Is there a workaround? I'm looking for something comparable to STATA's stcox command.

Thanks in advace!

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lifelines has support for panel data using the CoxTimeVaryingFitter model: https://lifelines.readthedocs.io/en/latest/Time%20varying%20survival%20regression.html

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  • $\begingroup$ @ Cam.Davidson.Pilon could you maybe have a look at the following question? $\endgroup$
    – TiTo
    Commented Jun 11, 2020 at 11:21

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