statsmodels.formula.api.phreg

statsmodels.formula.api.phreg(formula, data, status=None, entry=None, strata=None, offset=None, subset=None, ties='breslow', missing='drop', *args, **kwargs)

Create a proportional hazards regression model from a formula and dataframe.

Parameters:

  • formula (str or generic Formula object) – The formula specifying the model

  • data (array_like) – The data for the model. See Notes.

  • status (array_like) – The censoring status values; status=1 indicates that an event occurred (e.g. failure or death), status=0 indicates that the observation was right censored. If None, defaults to status=1 for all cases.

  • entry (array_like) – The entry times, if left truncation occurs

  • strata (array_like) – Stratum labels. If None, all observations are taken to be in a single stratum.

  • offset (array_like) – Array of offset values

  • subset (array_like) – An array-like object of booleans, integers, or index values that indicate the subset of df to use in the model. Assumes df is a pandas.DataFrame

  • ties (str) – The method used to handle tied times, must be either ‘breslow’ or ‘efron’.

  • missing (str) – The method used to handle missing data

  • args (extra arguments) – These are passed to the model

  • kwargs (extra keyword arguments) – These are passed to the model with one exception. The eval_env keyword is passed to patsy. It can be either a patsy:patsy.EvalEnvironment object or an integer indicating the depth of the namespace to use. For example, the default eval_env=0 uses the calling namespace. If you wish to use a “clean” environment set eval_env=-1.

Returns:

model

Return type:

PHReg model instance