Contents
Which measure of fit is used in logistic regression?
deviance
With a p-value based on asympotics, a commonly used goodness of fit statistic for logistic regression is the deviance statistic which is twice the difference between the maximized log-likelihood with no constraints and the maximized log-likelihood, assuming the logistic regression model holds.
How is Hosmer Lemeshow test calculated?
Figure 1 – Hosmer-Lemeshow Test 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.
When to use Hosmer-Lemeshow test in logistic regression?
The Hosmer-Lemeshow test does not depend on the format of the data. When the data have few trials per row, the Hosmer-Lemeshow test is a more trustworthy indicator of how well the model fits the data. For more information, go to How data formats affect goodness-of-fit in binary logistic regression.
When to use Hosmer Lemeshow goodness of fit test?
The Hosmer–Lemeshow test can determine if the differences between observed and expected proportions are significant, indicating model lack of fit. The Pearson chi-squared goodness of fit test provides a method to test if the observed and expected proportions differ significantly.
When to use Hosmer Lemeshow or deviance test?
The p-value for the deviance test usually decreases as the number of trials per row decreases. The Hosmer-Lemeshow test does not depend on the format of the data. When the data have few trials per row, the Hosmer-Lemeshow test is a more trustworthy indicator of how well the model fits the data.
What is the ROC curve in logistic regression?
The resulting curve is called a ROC curve. page 171 Figure 5.3 Plot of leverage (h) versus the estimated logistic probability (pi-hat) for a hypothetical univariable logistic regression model. NOTE: We cannot recreate this figure because we do have the hypothetical data that were used.