Goodness Of Fit Test Logistic Regression. The Pearson 2 goodness-of-fit test is a test of the observed against expected number of responses using cells defined by the covariate patterns. A test that is commonly used to assess model fit is the HosmerLemeshow test which is available in Stata and most other statistical software programs.
Hosmer-Lemeshow The Hosmer-Lemeshow goodness-of-fit test compares the observed and expected frequencies of events and non-events to assess how well the model fits the data. To use a different link function you should use Binary Fitted Line Plot or Fit Binary Logistic Regression in Minitab Statistical Software. The HosmerLemeshow test is a statistical test for goodness of fit for logistic regression models.
The tests large p -values indicate insufficient evidence for rejecting the null hypothesis that the model fits.
The test assesses whether or not the observed event rates match expected event rates in subgroups of the model population. A test that is commonly used to assess model fit is the HosmerLemeshow test which is available in Stata and most other statistical software programs. Jan 23 2019 The Hosmer-Lemeshow test is a statistical test for goodness of fit for the logistic regression model. The test that you are using is not a goodness-of-fit test but a likelihood ratio test for the comparison of the proposed model with the null model.
