Now showing items 1-4 of 4
Controlling the rate of Type I error over a large set of statistical tests
When many tests of significance are examined in a research investigation with procedures that limit the probability of making at least one Type I error—the so‐called familywise techniques of control—the likelihood of ...
The Pairwise Multiple Comparison Multiplicity Problem: An Alternative Approach to Familywise and Comparisonwise Type I Error Control
(American Psychological Association, 1999-03)
When simultaneously undertaking many tests of significance researchers are faced with the problem of how best to control the probability of committing a Type I error. The familywise approach deals directly with multiplicity ...
Multiplicity control in structural equation modeling
(Taylor & Francis, 2007)
Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this ...
Evaluating the importance of individual parameters in structural equation modeling: The need for Type I error control
The use of structural equation modeling in personality research has been increasing steadily over the past few decades. In evaluating the adequacy of a particular model researchers are often interested in evaluating not ...