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
orgeneric
Formula
object
The formula specifying the model
- dataarray_like
The data for the model. See Notes.
- statusarray_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.
- entryarray_like
The entry times, if left truncation occurs
- strataarray_like
Stratum labels. If None, all observations are taken to be in a single stratum.
- offsetarray_like
Array of offset values
- subsetarray_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 apatsy:patsy.EvalEnvironment
object or an integer indicating the depth of the namespace to use. For example, the defaulteval_env=0
uses the calling namespace. If you wish to use a “clean” environment seteval_env=-1
.
- formula
- Returns:¶
- model
PHReg
model
instance
- model