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Chapter 12
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.
Save
Figure 12-10
Cox Regression dialog box, Save tab
Save Variables. This group allows you to save model-related variables to the active dataset for
further use in diagnostics and reporting of results. Note that n one of these are available when
time-dependent predictors are included in the model.
Survival function. Saves the probability of survival (the value of the survival function) at the
observed time and predictor values for each case.
Lower bound of confidence interval for survival function. Saves the lower bound of the
confidence interval for the survival function at the observed time and predictor values for
each case.