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Chapter 9
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 General Linear Model Estimated Means
Figure 9-5
General Linear Model Estimated Means dialog box