IBM SPSS COMPLEX SAMPLES 19 manual Complex Samples Ordinal Regression Odds Ratios

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Chapter 11

Test Statistic. This group allows you to select the type of statistic used for testing hypotheses. You can choose between F, adjusted F, chi-square, and adjusted chi-square.

Sampling Degrees of Freedom. This group gives you control over the sampling design degrees of freedom used to compute p values for all test statistics. If based on the sampling design, the value is the difference between the number of primary sampling units and the number of strata in the first stage of sampling. Alternatively, you can set a custom degrees of freedom by specifying a positive integer.

Adjustment for Multiple Comparisons. When performing hypothesis tests with multiple contrasts, the overall significance level can be adjusted from the significance levels for the included contrasts. This group allows you to choose the adjustment method.

„Least significant difference. This method does not control the overall probability of rejecting the hypotheses that some linear contrasts are different from the null hypothesis values.

„Sequential Sidak. This is a sequentially step-down rejective Sidak procedure that is much less conservative in terms of rejecting individual hypotheses but maintains the same overall significance level.

„Sequential Bonferroni. This is a sequentially step-down rejective Bonferroni procedure that is much less conservative in terms of rejecting individual hypotheses but maintains the same overall significance level.

„Sidak. This method provides tighter bounds than the Bonferroni approach.

„Bonferroni. This method adjusts the observed significance level for the fact that multiple contrasts are being tested.

Complex Samples Ordinal Regression Odds Ratios

Figure 11-6

Ordinal Regression Odds Ratios dialog box

The Odds Ratios dialog box allows you to display the model-estimated cumulative odds ratios for specified factors and covariates. This feature is only available for models using the Logit link function. A single cumulative odds ratio is computed for all categories of the dependent variable except the last; the proportional odds model postulates that they are all equal.