In Weights, enter a numeric column of weights to perform weighted regression. The weights must be greater than or equal to zero. The weights column must have the same number of rows as the response column. For more information about determining the appropriate weight, go to Weighted regression.
Enter the level of confidence for the confidence intervals for the coefficients and the fitted values. If you use the logit link function, this confidence level is also the confidence level for the confidence intervals for the odds ratios.
Usually, a confidence level of 95% works well. A 95% confidence level indicates that, if you took 100 random samples from the population, the confidence intervals for approximately 95 of the samples would contain the parameter that the interval estimates. For a given set of data, a lower confidence level produces a narrower interval, and a higher confidence level produces a wider interval.
To display the confidence intervals for the coefficients and the fitted values, you must go to the Results sub-dialog box, and from Display of results, select Expanded tables.
Enter the number of groups for the Hosmer-Lemeshow test. If you leave this value blank, Minitab attempts to make 10 groups of equal size. Ten groups works well for most data sets.
The Hosmer-Lemeshow test is a goodness-of-fit test, which assesses the model fit by comparing the observed and expected frequencies. The test divides the data into groups by their estimated probabilities from lowest to highest, then performs a chi-square test to determine whether the observed and expected frequencies are significantly different. If the number of unique factor/covariate patterns is small or large, you may want to change the number of groups. For example, you can use fewer groups to increase the expected values within the groups. Alternatively, you can use more groups to see greater detail in the comparison of the observed and expected values. Hosmer and Lemeshow suggest using a minimum of 6 groups^{1}.