What do you do when Hosmer and Lemeshow test is significant?

What to do when Hosmer lemeshow test fails during Logistic…

  1. change the selection of numerical variables which you are doing. Try to use relevant variables and check there significance.
  2. Bucket your continuous variable in 3-4 bins(depends on business).
  3. Create dummy variables replacing the categorical variables.

Which option do you use to obtain the Hosmer Lemeshow goodness of fit statistic in Proc logistic?

In SAS, the Hosmer and Lemeshow goodness of fit test is generated with the lackfit option to the model statement in proc logistic (section 4.1. 1).

Should Hosmer-Lemeshow test be significant?

It is possible to have a significant p-value, but still have poor predictions of the proportion of successes. The Hosmer–Lemeshow test is useful to determine if the poor predictions (lack of fit) are significant, indicating that there are problems with the model.

How is Hosmer-Lemeshow test calculated?

The HL statistic is calculated in cell N16 via the formula =SUM(N4:N15). E.g. cell N4 contains the formula =(H4-L4)^2/L4+(I4-M4)^2/M4. The Hosmer-Lemeshow test results are shown in range Q12:Q16.

How do you improve the goodness of fit regression?

How to improve the accuracy of a Regression Model

  1. Handling Null/Missing Values.
  2. Data Visualization.
  3. Feature Selection and Scaling.
  4. 3A. Feature Engineering.
  5. 3B. Feature Transformation.
  6. Use of Ensemble and Boosting Algorithms.
  7. Hyperparameter Tuning.

What measure do we use to evaluate the goodness of fit of a logistic model?

The Hosmer-Lemeshow goodness-of-fit statistic is computed as the Pearson chi-square from the contingency table of observed frequencies and expected frequencies. Similar to a test of association of a two-way table, a good fit as measured by Hosmer and Lemeshow’s test will yield a large p-value.