statsmodels.duration.hazard_regression.PHRegResults
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class statsmodels.duration.hazard_regression.PHRegResults(model, params, cov_params, covariance_type='naive')
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Class to contain results of fitting a Cox proportional hazards survival model.
PHregResults inherits from statsmodels.LikelihoodModelResults
Parameters: See statsmodels.LikelihoodModelResults :
Returns: **Attributes** :
model : class instance
PHreg model instance that called fit.
normalized_cov_params : array
The sampling covariance matrix of the estimates
params : array
The coefficients of the fitted model. Each coefficient is the log hazard ratio corresponding to a 1 unit difference in a single covariate while holding the other covariates fixed.
bse : array
The standard errors of the fitted parameters.
See also
statsmodels.LikelihoodModelResults
Methods
baseline_cumulative_hazard
()A list (corresponding to the strata) containing the baseline cumulative hazard function evaluated at the event points. baseline_cumulative_hazard_function
()A list (corresponding to the strata) containing function objects that calculate the cumulative hazard function. bse
()Returns the standard errors of the parameter estimates. conf_int
([alpha, cols, method])Returns the confidence interval of the fitted parameters. cov_params
([r_matrix, column, scale, cov_p, ...])Returns the variance/covariance matrix. f_test
(r_matrix[, cov_p, scale, invcov])Compute the F-test for a joint linear hypothesis. get_distribution
()Returns a scipy distribution object corresponding to the distribution of uncensored endog (duration) values for each case. initialize
(model, params, **kwd)llf
()load
(fname)load a pickle, (class method) martingale_residuals
()The martingale residuals. normalized_cov_params
()predict
([endog, exog, strata, offset, pred_type])Returns predicted values from the fitted proportional hazards regression model. pvalues
()remove_data
()remove data arrays, all nobs arrays from result and model save
(fname[, remove_data])save a pickle of this instance schoenfeld_residuals
()A matrix containing the Schoenfeld residuals. score_residuals
()A matrix containing the score residuals. standard_errors
()Returns the standard errors of the parameter estimates. summary
([yname, xname, title, alpha])Summarize the proportional hazards regression results. t_test
(r_matrix[, cov_p, scale, use_t])Compute a t-test for a each linear hypothesis of the form Rb = q tvalues
()Return the t-statistic for a given parameter estimate. wald_test
(r_matrix[, cov_p, scale, invcov, ...])Compute a Wald-test for a joint linear hypothesis. weighted_covariate_averages
()The average covariate values within the at-risk set at each event time point, weighted by hazard. Attributes
use_t
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