scholarly journals Psychopathy factor interactions and co-occurring psychopathology: Does measurement approach matter?

2015 ◽  
Vol 27 (2) ◽  
pp. 583-595 ◽  
Author(s):  
Elizabeth Hunt ◽  
Marina A. Bornovalova ◽  
Eva R. Kimonis ◽  
Scott O. Lilienfeld ◽  
Norman G. Poythress
Keyword(s):  
Factor Interactions ◽  
Measurement Approach

Assessing General Ecological Behavior

2000 ◽  
Vol 16 (1) ◽  
pp. 44-52 ◽  
Author(s):  
Florian G. Kaiser ◽  
Anders Biel
Keyword(s):  
Internal Consistency ◽  
Cross Cultural ◽  
Questionnaire Data ◽  
Situational Influences ◽  
Behavior Difficulties ◽  
Differential Behavior ◽  
Ecological Behavior ◽  
Political Actions ◽  
Measurement Approach

Summary: The General Ecological Behavior (GEB) scale was developed for cross-cultural applications ( Kaiser & Wilson, in press ). The present study compares ecological behavior in Sweden and Switzerland. Questionnaire data from 247 Swedish and 445 Swiss participants are presented. Reliability and internal consistency analyses revealed that the GEB scale was applicable to both the Swedish and Swiss samples. In general, Swiss behave more ecologically than Swedes. Nevertheless, several ecological behaviors turned out to be easier to conduct in Sweden than in Switzerland and vice versa. The GEB scale takes differential behavior difficulties into account that are most likely caused by situational influences. At the same time, the proposed behavior measurement approach guides the search for potentially useful political actions that make it easier for people to behave ecologically in some societies and, thus, can be adopted by others.

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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