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scipy-yli
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Implement likelihood ratio test for Cox regression

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RunasSudo 2023-02-25 15:07:42 +11:00
parent eb0d520d95
commit 642d0d4e4f
Signed by: RunasSudo
GPG Key ID: 7234E476BF21C61A
1 changed files with 12 additions and 10 deletions
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yli/regress.py
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@ -1,5 +1,5 @@
# scipy-yli: Helpful SciPy utilities and recipes # scipy-yli: Helpful SciPy utilities and recipes
# Copyright © 2022 Lee Yingtong Li (RunasSudo) # Copyright © 2022–2023 Lee Yingtong Li (RunasSudo)
# #
# This program is free software: you can redistribute it and/or modify # This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by # it under the terms of the GNU Affero General Public License as published by
@ -520,16 +520,18 @@ class RegressionResult:
else: else:
right_col.append(('F:', format(f_result.statistic, '.2f'))) right_col.append(('F:', format(f_result.statistic, '.2f')))
right_col.append(('p (F):', fmt_p(f_result.pvalue, PValueStyle.VALUE_ONLY))) right_col.append(('p (F):', fmt_p(f_result.pvalue, PValueStyle.VALUE_ONLY)))
elif self.ll_null: else:
# Otherwise report likelihood ratio test as overall test # Otherwise report likelihood ratio test as overall test
lrtest_result = self.lrtest_null()
right_col.append(('LL-Model:', format(self.ll_model, '.2f'))) right_col.append(('LL-Model:', format(self.ll_model, '.2f')))
right_col.append(('LL-Null:', format(self.ll_null, '.2f')))
if html: if self.ll_null:
right_col.append(('<i>p</i> (LR):', fmt_p(lrtest_result.pvalue, PValueStyle.VALUE_ONLY | PValueStyle.HTML))) lrtest_result = self.lrtest_null()
else:
right_col.append(('p (LR):', fmt_p(lrtest_result.pvalue, PValueStyle.VALUE_ONLY))) right_col.append(('LL-Null:', format(self.ll_null, '.2f')))
if html:
right_col.append(('<i>p</i> (LR):', fmt_p(lrtest_result.pvalue, PValueStyle.VALUE_ONLY | PValueStyle.HTML)))
else:
right_col.append(('p (LR):', fmt_p(lrtest_result.pvalue, PValueStyle.VALUE_ONLY)))
return left_col, right_col return left_col, right_col
@ -917,7 +919,7 @@ def regress(
elif hasattr(result, 'llnull'): elif hasattr(result, 'llnull'):
ll_null = result.llnull ll_null = result.llnull
elif model_class is sm.PHReg: elif model_class is sm.PHReg:
ll_null = None ll_null = model.loglike([0 for _ in result.params])
else: else:
# Construct null (intercept-only) model # Construct null (intercept-only) model
#result_null = model_class.from_formula(formula=dep + ' ~ 1', data=df).fit() #result_null = model_class.from_formula(formula=dep + ' ~ 1', data=df).fit()