Exploratory Factor Analysis in Psychological Research : Current Status and Suggestions for Methodological Improvements

2018 ◽  
Vol 29 (1) ◽  
pp. 177-193
Author(s):  
Wonjin Seo ◽  
Sumin Lee ◽  
Mirihae Kim ◽  
Jejoong Kim
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Psychological Research ◽  
Current Status

scholarly journals Robustness of factor solutions in exploratory factor analysis

2021 ◽  
Author(s):  
David Goretzko ◽  
Markus Bühner
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Big Five ◽  
Sampling Error ◽  
Information Criterion ◽  
Psychological Research ◽  
Stable Factor ◽  
Research Areas ◽  
The Stability ◽  
The One

AbstractReplicability has become a highly discussed topic in psychological research. The debates focus mainly on significance testing and confirmatory analyses, whereas exploratory analyses such as exploratory factor analysis are more or less ignored, although hardly any analysis has a comparable impact on entire research areas. Determining the correct number of factors for this analysis is probably the most crucial, yet ambiguous decision—especially since factor structures have often been not replicable. Hence, an approach based on bootstrapping the factor retention process is proposed to evaluate the robustness of factor retention criteria against sampling error and to predict whether a particular factor solution may be replicable. We used three samples of the “Big Five Structure Inventory” and four samples of the “10 Item Big Five Inventory” to illustrate the relationship between stable factor solutions across bootstrap samples and their replicability. In addition, we compared four factor retention criteria and an information criterion in terms of their stability on the one hand and their replicability on the other. Based on this study, we want to encourage researchers to make use of bootstrapping to assess the stability of the factor retention criteria they use and to compare these criteria with regard to this stability as a proxy for possible replicability.

Abductive Research Methods in Psychological Science

2021 ◽  
Author(s):  
Brian Haig
Keyword(s):  
Factor Analysis ◽  
Research Methods ◽  
Exploratory Factor Analysis ◽  
Psychological Research ◽  
The Third ◽  
Psychological Science ◽  
Common Causes ◽  
Explanatory Coherence

This chapter discusses a number of different abductive research methods of relevance to psychological research. The first of these, exploratory factor analysis, has been widely employed to generate rudimentary explanatory theories about common causes, although it is not generally recognized as an abductive method. The second method, analogical modelling, can be viewed as an abductive strategy for developing explanatory theories once they have been generated. The third abductive method, known generally as inference to the best explanation, gets formulated in different ways. These methods of inference to the best explanation can be used to evaluate the worth of competing explanatory theories. Theories of explanatory coherence are important in this regard.

An exploratory factor analysis of the Nerdy Personality Attributes Scale in a sample of self-identified nerds/geeks.

2019 ◽  
Author(s):  
callum finister ◽  
Thomas Victor Pollet ◽  
Nicholas Neave
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Factor Structure ◽  
Subjective Wellbeing ◽  
Psychological Research ◽  
Personality Types ◽  
Openness To Experience ◽  
The Past ◽  
Behavioural Characteristics ◽  
Starting Point

In the past, the terms ‘geek’ and ‘nerd’ had negative social connotations, but so-called ‘Geek’ subculture is becoming increasingly mainstream, and its social and economic influence is expanding. There has been very little psychological research into this subculture and its associated personality types, but some authors have reported links with narcissism, extraversion, openness to experience, depression and subjective wellbeing. In a sample of 425 self-identified geeks/nerds registered with the Facebook community Geek Asylum and the Facebook page of the Manchester 2019 Comic-Con, we explored the factor structure of the Nerdy Personality Attributes Scale. Using exploratory factor analysis, we find that the scale items load onto three factors - ‘Social awkwardness’, ‘Interest in learning and science’ and ‘Interest in books’, with all correlating weakly to moderately with self-reported nerdiness. This scale may form a useful starting point to further assess the personality and behavioural characteristics of nerdiness.

scholarly journals Evaluating the use of exploratory factor analysis in psychological research.

1999 ◽  
Vol 4 (3) ◽  
pp. 272-299 ◽  
Author(s):  
Leandre R. Fabrigar ◽  
Duane T. Wegener ◽  
Robert C. MacCallum ◽  
Erin J. Strahan
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Psychological Research

Measuring Impact of Stress in Sandwich Generation Caring for Demented Parents

GeroPsych ◽  
2014 ◽  
Vol 27 (4) ◽  
pp. 171-179 ◽  
Author(s):  
Laurence M. Solberg ◽  
Lauren B. Solberg ◽  
Emily N. Peterson
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Social Worker ◽  
Resource Availability ◽  
Well Being ◽  
Sandwich Generation ◽  
Item Questionnaire ◽  
Significant Difference ◽  
Adult Caregivers ◽  
The Impact

Stress in caregivers may affect the healthcare recipients receive. We examined the impact of stress experienced by 45 adult caregivers of their elderly demented parents. The participants completed a 32-item questionnaire about the impact of experienced stress. The questionnaire also asked about interventions that might help to reduce the impact of stress. After exploratory factor analysis, we reduced the 32-item questionnaire to 13 items. Results indicated that caregivers experienced stress, anxiety, and sadness. Also, emotional, but not financial or professional, well-being was significantly impacted. There was no significant difference between the impact of caregiver stress on members from the sandwich generation and those from the nonsandwich generation. Meeting with a social worker for resource availability was identified most frequently as a potentially helpful intervention for coping with the impact of stress.

The Hierarchical Model of Exercise Dependence

2015 ◽  
Vol 36 (4) ◽  
pp. 247-257 ◽  
Author(s):  
Gayatri Kotbagi ◽  
Laurence Kern ◽  
Lucia Romo ◽  
Ramesh Pathare
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Physical Exercise ◽  
Exploratory Factor Analysis ◽  
Convergent Validity ◽  
Large Population ◽  
Assessment Tools ◽  
Negative Consequences ◽  
Confirmatory Factor ◽  
Preliminary Version

Abstract. Physical exercise when done excessively may have negative consequences on physical and psychological wellbeing. There exist many scales to measure this phenomenon. The purpose of this article is to create a scale measuring the problematic practice of physical exercise (PPPE Scale) by combining two assessment tools already existing in the field of exercise dependency but anchored in different approaches (EDS-R and EDQ). This research consists of three studies carried out on three independent sample populations. The first study (N = 341) tested the construct validity (exploratory factor analysis); the second study (N = 195) tested the structural validity (confirmatory factor analysis) and the third study (N = 104) tested the convergent validity (correlations) of the preliminary version of the PPPE scale. Exploratory factor analysis identified six distinct dimensions associated with exercise dependency. Furthermore, confirmatory factor analysis validated a second order model consisting of 25 items with six dimensions and four sub-dimensions. The convergent validity of this scale with other constructs (GLTEQ, EAT26, and The Big Five Inventory [BFI]) is satisfactory. The preliminary version of the PPPE must be administered to a large population to refine its psychometric properties and develop scoring norms.

Subclinical Sadism and the Dark Triad

2019 ◽  
Vol 40 (3) ◽  
pp. 127-133 ◽  
Author(s):  
Laura K. Johnson ◽  
Rachel A. Plouffe ◽  
Donald H. Saklofske
Keyword(s):  
Factor Analysis ◽  
University Students ◽  
Personality Traits ◽  
Exploratory Factor Analysis ◽  
Convergent Validity ◽  
Dark Triad ◽  
Antisocial Personality ◽  
Factor Solution ◽  
Online Study ◽  
Antisocial Personality Traits

Abstract. The Dark Triad is a constellation of three antisocial personality traits: Machiavellianism, narcissism, and psychopathy. Recently, researchers have introduced a “Dark Tetrad” that includes subclinical sadism, although others suggest considerable overlap between psychopathy and sadism. To clarify the position of sadism within the Dark Triad, an online study was conducted with 615 university students. Exploratory factor analysis revealed that a six-factor solution fit the data best, representing Machiavellianism, psychopathy, physical sadism, verbal sadism, narcissism, and vicarious sadism. Furthermore, convergent validity was supported through sadism’s correlations with the HEXACO personality traits. The results support sadism’s inclusion within the Dark Tetrad as a unique construct but with some conceptual overlap with psychopathy.

Equivalent Factorial Structure of the Brief Symptom Inventory (BSI) in Clinical and Nonclinical Jordanian Populations

2010 ◽  
Vol 26 (2) ◽  
pp. 116-121 ◽  
Author(s):  
Fawzi S. Daoud ◽  
Amjed A. Abojedi
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Clinical Sample ◽  
Brief Symptom Inventory ◽  
Factorial Structure ◽  
Symptom Inventory ◽  
Confirmatory Factor ◽  
Item Checklist ◽  
General Psychological Distress

This study investigates the equivalent factorial structure of the Brief Symptom Inventory (BSI) in clinical and nonclinical Jordanian populations, using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The 53-item checklist was administered to 647 nonclinical participants and 315 clinical participants. Eight factors emerged from the exploratory factor analysis (EFA) for the nonclinical sample, and six factors emerged for the clinical sample. When tested by parallel analysis (PA) and confirmatory factor analysis (CFA), the results reflected a unidimensional factorial structure in both samples. Furthermore, multigroup CFA showed invariance between clinical and nonclinical unidimensional models, which lends further support to the evidence of the unidimensionality of the BSI. The study suggests that the BSI is a potentially useful measure of general psychological distress in clinical and nonclinical population. Ideas for further research are recommended.

A Comparison of Simple Structure Rotation Criteria in Temporal Exploratory Factor Analysis for Event-Related Potential Data

Methodology ◽  
2019 ◽  
Vol 15 (Supplement 1) ◽  
pp. 43-60 ◽  
Author(s):  
Florian Scharf ◽  
Steffen Nestler
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Simple Structure ◽  
Ground Truth ◽  
Event Related Potential ◽  
Suitable Alternative ◽  
Factor Rotation ◽  
Rotation Methods ◽  
Simple Structure Rotation ◽  
Temporal Overlap

Abstract. It is challenging to apply exploratory factor analysis (EFA) to event-related potential (ERP) data because such data are characterized by substantial temporal overlap (i.e., large cross-loadings) between the factors, and, because researchers are typically interested in the results of subsequent analyses (e.g., experimental condition effects on the level of the factor scores). In this context, relatively small deviations in the estimated factor solution from the unknown ground truth may result in substantially biased estimates of condition effects (rotation bias). Thus, in order to apply EFA to ERP data researchers need rotation methods that are able to both recover perfect simple structure where it exists and to tolerate substantial cross-loadings between the factors where appropriate. We had two aims in the present paper. First, to extend previous research, we wanted to better understand the behavior of the rotation bias for typical ERP data. To this end, we compared the performance of a variety of factor rotation methods under conditions of varying amounts of temporal overlap between the factors. Second, we wanted to investigate whether the recently proposed component loss rotation is better able to decrease the bias than traditional simple structure rotation. The results showed that no single rotation method was generally superior across all conditions. Component loss rotation showed the best all-round performance across the investigated conditions. We conclude that Component loss rotation is a suitable alternative to simple structure rotation. We discuss this result in the light of recently proposed sparse factor analysis approaches.

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