Selection of variables in exploratory factor analysis: An empirical comparison of a stepwise and traditional approach

Psychometrika ◽  
2004 ◽  
Vol 69 (4) ◽  
pp. 593-611 ◽  
Author(s):  
Kristine Y. Hogarty ◽  
Jeffrey D. Kromrey ◽  
John M. Ferron ◽  
Constance V. Hines
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Traditional Approach ◽  
Empirical Comparison ◽  
Selection Of Variables ◽  
Selection Of

scholarly journals Likert scale and change in range of response categories vs. the factors extraction in EFA model

2015 ◽  
Vol 1 (311) ◽  
Author(s):  
Piotr Tarka
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Rating Scale ◽  
Likert Scale ◽  
Optimal Number ◽  
Number Of Factors ◽  
Scale Experiment ◽  
Methodological Aspects ◽  
The Impact ◽  
Selection Of

Abstract: The objective article is the comparative analysis of Likert rating scale based on the following range of response categories, i.e. 5, 7, 9 and 11 in context of the appropriate process of factors extraction in exploratory factor analysis (EFA). The problem which is being addressed in article relates primarily to the methodological aspects, both in selection of the optimal number of response categories of the measured items (constituting the Likert scale) and identification of possible changes, differences or similarities associated (as a result of the impact of four types of scales) with extraction and determination the appropriate number of factors in EFA model.Keywords: Exploratory factor analysis, Likert scale, experiment research, marketing

scholarly journals Why people select the outpatient clinic of medical centers: a nationwide analysis in Taiwan

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9829
Author(s):  
Ming-Hwai Lin ◽  
Hsiao-Ting Chang ◽  
Tzeng-Ji Chen ◽  
Shinn-Jang Hwang
Keyword(s):  
Factor Analysis ◽  
Medical Care ◽  
Exploratory Factor Analysis ◽  
Outpatient Clinic ◽  
Medical Center ◽  
Outpatient Clinics ◽  
Medical Centers ◽  
Regular Family ◽  
High Tier ◽  
Selection Of

Introduction In contrast to other countries, Taiwan’s National Health Insurance (NHI) program allows patients to freely select the specialists and tiers of medical care facility without a referral. Some medical centers in Taiwan receive over 10,000 outpatients per day. In the NHI program, the co-payment was increased for high-tier facilities for outpatient visits in 2002, 2005, and 2017. However, the policies only mildly reduced the use of high-tier medical care facilities. The main purpose of this study was to evaluate the factors contributing to the patients’ selection of the outpatient clinic of medical centers without a referral. Methods An online anonymous survey was conducted by using the Google Forms platform utilizing a self-constructed questionnaire from September to October 2018. A nationwide sample in Taiwan was recruited using convenience sampling through social media. Based on a literature review and a focus group, 20 factors that may affect the choice of the outpatient institution were constructed. The associations between items that affect the patients selection of outpatient clinics were assessed using exploratory factor analysis. Principal axis factoring was performed to identify the major factors affecting the decision. Multiple logistic regression was performed to determine which factors satisfactorily explained “visiting the outpatient clinic of the medical center for an illness without a referral.” Results During the survey period, 5,060 people browsed the online survey, and 1,003 responded and completed the online questionnaire. Therefore, the response rate was 19.8%. A total of 987 valid responses was collected. Exploratory factor analysis revealed that three main factors, namely the “physician factor”, “image and reputation factor”, and “facility and medication factor”, affected the selection of outpatient clinics. A series of logistic regressions indicated that patients who reported that hospital facilities, high-quality drugs, and diverse specialties were very important were more likely to select the outpatient clinic of a medical center (OR = 2.218, 95% CI [1.514–3.249]). Patients who reported that physician factors were very important were less likely to select a medical center (OR = 0.717, 95% CI [0.523–0.984]). Patients who were previously satisfied with their experience of the primary clinics or had a regular family doctor were less likely to choose a medical center (OR = 0.509, 95% CI -0.435–0.595] and OR = 0.676, 95% CI [0.471–0.969]). Conclusion In Taiwan, patients with good primary medical experience and regular family physicians had significantly lower rates by selecting the outpatient clinic of a medical center. The results of this study support that the key to establishing graded medical care is to prioritize the strengthening of the primary medical system.

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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