Models for Survival and Duration Analysis

Examples

import statsmodels.api as sm
import statsmodels.formula.api as smf
 
data = sm.datasets.get_rdataset("flchain", "survival").data
del data["chapter"]
data = data.dropna()
data["lam"] = data["lambda"]
data["female"] = (data["sex"] == "F").astype(int)
data["year"] = data["sample.yr"] - min(data["sample.yr"])
status = data["death"].values
 
mod = smf.phreg("futime ~ 0 + age + female + creatinine + "
                "np.sqrt(kappa) + np.sqrt(lam) + year + mgus",
                data, status=status, ties="efron")
rslt = mod.fit()
print(rslt.summary())

Detailed examples can be found here:

There are some notebook examples on the Wiki: Wiki notebooks for PHReg and Survival Analysis

References

References for Cox proportional hazards regression model:

T Therneau (1996). Extending the Cox model. Technical report.
http://www.mayo.edu/research/documents/biostat-58pdf/DOC-10027288
 
G Rodriguez (2005). Non-parametric estimation in survival models.
http://data.princeton.edu/pop509/NonParametricSurvival.pdf
 
B Gillespie (2006). Checking the assumptions in the Cox proportional
hazards model.
http://www.mwsug.org/proceedings/2006/stats/MWSUG-2006-SD08.pdf

Module Reference

The model class is:

PHReg(endog, exog[, status, entry, strata, ...]) Fit the Cox proportional hazards regression model for right censored data.

The result class is:

PHRegResults(model, params, cov_params[, ...]) Class to contain results of fitting a Cox proportional hazards survival model.

Links:

http://statsmodels.sourceforge.net/stable/duration.html

doc_statsmodels

2025-01-10 15:47:30

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