Selecting 2m−pDesigns Using a Minimum Aberration Criterion When Some Two-Factor Interactions Are Important

Technometrics ◽  
2003 ◽  
Vol 45 (4) ◽  
pp. 352-360 ◽  
Author(s):  
Weiming Ke ◽  
Boxin Tang
Keyword(s):  
Minimum Aberration ◽  
Factor Interactions

scholarly journals Clear two-factor interactions and minimum aberration

2002 ◽  
Vol 30 (5) ◽  
pp. 1496-1511 ◽  
Author(s):  
Huaiqing Wu ◽  
C. F. J. Wu
Keyword(s):  
Minimum Aberration ◽  
Factor Interactions

Forms, Importance, and Ineffability of Factor Interactions to Define Personality Disorders: Comment on Lilienfeld et al. (2019)

2019 ◽  
Author(s):  
Stephen D Benning ◽  
Edward Smith
Keyword(s):  
Personality Disorders ◽  
False Positive Rate ◽  
Empirical Work ◽  
Design Studies ◽  
Linear Threshold ◽  
Positive Rate ◽  
Saturation Effects ◽  
Factor Interactions ◽  
Main Effects ◽  
Criterion Variables

The emergent interpersonal syndrome (EIS) approach conceptualizes personality disorders as the interaction among their constituent traits to predict important criterion variables. We detail the difficulties we have experienced finding such interactive predictors in our empirical work on psychopathy, even when using uncorrelated traits that maximize power. Rather than explaining a large absolute proportion of variance in interpersonal outcomes, EIS interactions might explain small amounts of variance relative to the main effects of each trait. Indeed, these interactions may necessitate samples of almost 1,000 observations for 80% power and a false positive rate of .05. EIS models must describe which specific traits’ interactions constitute a particular EIS, as effect sizes appear to diminish as higher-order trait interactions are analyzed. Considering whether EIS interactions are ordinal with non-crossing slopes, disordinal with crossing slopes, or entail non-linear threshold or saturation effects may help researchers design studies, sampling strategies, and analyses to model their expected effects efficiently.

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