classmethod PHReg.from_formula(formula, data, status=None, entry=None, strata=None, offset=None, subset=None, ties='breslow', missing='drop', *args, **kwargs)[source]

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


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 occured (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 : string

The method used to handle tied times, must be either ‘breslow’ or ‘efron’.

missing : string

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.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.


model : PHReg model instance

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