Using principal component scores reduces the effect of socially desirable responding

Abstract. Varimax rotated principal component scores (VRPCS) have previously been offered as a possible solution to the non-orthogonality of scores for the Big Five factors. However, few researchers have examined the reliability and validity of VRPCS. To address this gap, we use a lab study and a field study to investigate whether using VRPCS increase orthogonality, reliability, and criterion-related validity. Compared to the traditional unit-weighting scoring method, the use of VRPCS enhanced the reliability and discriminant validity of the Big Five factors, although there was little improvement in criterion-related validity. Results are discussed in terms of the benefit of using VRPCS instead of traditional unit-weighted sum scores.

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Using principal component scores for Big Five personality measures

PsycEXTRA Dataset ◽

10.1037/e518422013-866 ◽

2009 ◽

Author(s):

Jeffrey M. Cucina ◽

Nicholas L. Vasilopoulos

Keyword(s):

Big Five ◽

Principal Component ◽

Big Five Personality ◽

Personality Measures ◽

Component Scores

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PM10and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set

Chemistry Central Journal ◽

10.1186/1752-153x-8-14 ◽

2014 ◽

Vol 8 (1) ◽

Cited By ~ 8

Author(s):

Pierina Ielpo ◽

Vincenzo Paolillo ◽

Gianluigi de Gennaro ◽

Paolo Rosario Dambruoso

Keyword(s):

Principal Component Analysis ◽

Air Quality ◽

Principal Component ◽

Component Analysis ◽

Quality Monitoring ◽

Gaseous Pollutants ◽

Air Quality Monitoring ◽

Monitoring Networks ◽

Data Set ◽

Component Scores

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Effects of cumulative illness severity on hippocampal gray matter volume in major depression: a voxel-based morphometry study

Psychological Medicine ◽

10.1017/s0033291718000016 ◽

2018 ◽

Vol 48 (14) ◽

pp. 2391-2398 ◽

Cited By ~ 13

Author(s):

Dario Zaremba ◽

Verena Enneking ◽

Susanne Meinert ◽

Katharina Förster ◽

Christian Bürger ◽

...

Keyword(s):

Major Depression ◽

Gray Matter ◽

Gray Matter Volume ◽

Principal Component ◽

Hippocampal Volume ◽

Illness Severity ◽

Voxel Based Morphometry ◽

Matter Volume ◽

Duration Of Illness ◽

Component Scores

AbstractBackgroundPatients with major depression show reduced hippocampal volume compared to healthy controls. However, the contribution of patients’ cumulative illness severity to hippocampal volume has rarely been investigated. It was the aim of our study to find a composite score of cumulative illness severity that is associated with hippocampal volume in depression.MethodsWe estimated hippocampal gray matter volume using 3-tesla brain magnetic resonance imaging in 213 inpatients with acute major depression according to DSM-IV criteria (employing the SCID interview) and 213 healthy controls. Patients’ cumulative illness severity was ascertained by six clinical variables via structured clinical interviews. A principal component analysis was conducted to identify components reflecting cumulative illness severity. Regression analyses and a voxel-based morphometry approach were used to investigate the influence of patients’ individual component scores on hippocampal volume.ResultsPrincipal component analysis yielded two main components of cumulative illness severity: Hospitalization and Duration of Illness. While the component Hospitalization incorporated information from the intensity of inpatient treatment, the component Duration of Illness was based on the duration and frequency of illness episodes. We could demonstrate a significant inverse association of patients’ Hospitalization component scores with bilateral hippocampal gray matter volume. This relationship was not found for Duration of Illness component scores.ConclusionsVariables associated with patients’ history of psychiatric hospitalization seem to be accurate predictors of hippocampal volume in major depression and reliable estimators of patients’ cumulative illness severity. Future studies should pay attention to these measures when investigating hippocampal volume changes in major depression.

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