HIGH-ORDER CONSTRUCTS FOR THE STRUCTURAL EQUATION MODEL
|
|
- Phoebe Gaines
- 6 years ago
- Views:
Transcription
1 HIGH-ORDER CONSTRUCTS FOR THE STRUCTURAL EQUATION MODEL Enrico Ciavolino (1) * Mariangela Nitti (2) (1) Dipartimento di Filosofia e Scienze Sociali, Università del Salento (2) Dipartimento di Scienze Pedagogiche, Psicologiche e Didattiche, Università del Salento Abstract: The aim of the paper is to present a structural equation model based on high order latent variables. The non parametric estimation method used is the partial least squares which enables the definition of complex structure in the data with few model assumptions. The paper contribution is the analysis of the latent dimensions with a third level of abstraction by considering two main approaches presented in literature: the repeated indicators and the two-step approach. Empirical evidences and simulations results are provided in order to show the methodology and check the reliability of the approaches at issue. Keywords: structural equation model, partial least squares, high-order construct, latent dimension of sense. 1. Introduction PLS enables researchers in many field of social sciences to investigate models at high level of abstraction. The dimensions of a higher-order construct could be conceptualized under an overall abstraction, and it is theoretically meaningful to use this abstraction for the representation of the dimensions, instead of merely interrelating them. In this paper, a third-order latent construct model estimated by PLS-SEM is presented. Two modelbuilding approaches (named repeated indicators and two-step approach) are compared through a simulation study for determining which method better represents the relationships among constructs levels. The work is articulated as follows: in section 2 PLS estimator and its extension to higherorder construct modeling are described; section 3 presents a case study in which Latent Dimensions of Sense (LDS) are modeled as a third-order latent variable;in section 4, the description of the montecarlo simulation is reported for the third-order model, in way to compare the two modelbuilding approaches and draw conclusion on their performances. 2. PLS-path modeling for higher-order constructs Due to its ability of estimating complex models, PLS Path Modeling can be used to investigate models with a high level of abstraction. As a matter of fact, many studies in social sciences involve the conceptualization of multi-dimensional constructs, that is, composed of different but strictly related conceptual dimensions. The basic PLS design was completed for the first time in 1966 by Herman Wold for the use in multivariate analysis, and subsequently extended for its application in the Structural Equation Modeling (SEM) in 1975 by Wold himself. An extensive review on PLS approach is given the Handbook of PLS (Esposito Vinzi, Chin, Henseler, Wang, 2010). The model-building procedure can be thought of as the analysis of two conceptually different models. A measurement (or outer) model specifies the relationship of the observed variables with their (hypothesized) underlying (latent) constructs; a structural (or inner) model then specifies the causal relationships among latent constructs, as posited by some theory. The two sub models' equations are the following: * Corresponding Author: enrico.ciavolino@unisalento.it ξ (m,1) =B (m,m) ξ (m,1) +τ (m,1)
2 x (p,1) =Λ (p,m) ξ (m,1) +δ (p,1) where the subscripts m and p are the number of, respectively, the latent (LV) and the manifest variables (MV) in the model, while the letters ξ, x, B, Λ, τ and δ indicates LV and MV vectors, the path coefficients linking the LV, the factor loading linking the MV to the LV, and the errors terms of the model. 2.1 The PLS algorithm The parameters estimation (Ciavolino et al., 2009) is based on a double approximation of the LVs ξ j (with j=1,...,m). The external estimation y j, obtained as the product of the block of MVs X j (considered as the matrix units for variables) and the outer weights w j (which represent the estimation of measurement coefficients, Λ). The internal estimation z j, obtained as the product of the external estimation of ξ j, y j, and the inner weights e j. According with the relationship among MVs and LVs hypothesized, outer weights are computed as: for Mode A (reflective relationship), and: w j = X j ' z j w j = (X j ' X j ) -1 X j ' z j for Mode B (formative relationship). The inner weights e j,i, in the centroid scheme, are defined as the sign of the correlation between the connected estimated y j and y i, with i j. The PLS algorithm starts by initializing outer weights to one for the first MV of each LV; then, the parameters estimation is performed, until the convergence, by iteratively computing: 1) external estimation, y j = X j z j ; 2) internal estimation, z j = Σ j i e j,i y i ; 3) outer weights estimation, with Mode A or B. The causal paths among LVs (the coefficients in the B matrix) are obtained through Ordinary Least Squares (OLS) method. 2.2 Modelling higher-order constructs Wold's original design of PLS path modeling does not consider higher-order LVs; each construct has to be necessarily related to a set of observed variables in order to be estimated. On this basis, Lohmöller (1989) proposed a procedure for the case of hierarchical constructs, the so-called Hierarchical Component Model or Repeated Indicators Approach, which is the most popular approach when estimating higher-order constructs through PLS. The procedure is very simple: a second-order factor is directly measured by observed variables for all the first-order factors. While this approach repeats the number of MVs used, the model can be estimated by the standard PLS algorithm (Reinartz et al., 2004). The manifests indicators are repeated in order represent the higher-order construct. A prerequisite for the repeated indicators approach is that all indicators of the first-order and the second-order factors should be reflective. This approach is the most favored by researchers when using PLS for modeling higher-order constructs. A disadvantage of this approach is a possibly biasing of the estimates by relating variables of the same type together through PLS estimation. Another way of building a higher-order model is the Two-Step Approach: the LV scores are initially estimated in a model without second-order constructs (Agarwal et al., 2000). The LV scores are subsequently used as indicators in a separate higher-order structural model analysis. It may offer advantages when estimating higher-order models with formative indicators (Diamantopoulos et al., 2001; Reinartz et al., 2004). The implementation is not one simultaneous PLS run. A clear disadvantage of such two-stage approach is that any construct which is investigated in stage two is not taken into account when estimating LV scores at stage one. The two approaches are illustrated in figure 1.
3 Figure 1. Model building: Repeated Indicators and Two-Step approaches In a recent study, Wilson et al. (2007) showed that the second-order constructs reliability does not depend on the approach adopted; anyway, the repeated indicators approach produce biased and less consistent estimates (in the case of small samples) with respect to the two-step approach. 3. Empirical evidence The study here presented concern the LDS underlying students' image of three different areas: Social Context (social behaviors, future perspectives, image on adults and young s, etc.), University (motivation, teachers and teaching, university functions, problems and development strategies, etc.), Psychology and Psychologist (field of interventions, functions, potential users, etc.). LDS is here conceived as a third-order latent construct affecting second-order dimensions (Social Context, University and Psychology), which in turn shape first-order latent variables underlying specific aspects of the second-order dimensions. A sample of 136 students of the first year of Psychology course at University of Salento were invited to fill in a 120 item multiple choice questionnaire, divided into 19 sections (first-order LVs). The questionnaire was designed to facilitate the expression of perceptions, opinion, judgment, about the three general area of experience, by referring to the repertoire of cultural meanings typical of the ISO method (Carli, Paniccia, 2002; Carli, Salvatore, 2001). In order to model the LDS, here called Image, the two approaches to higher-order constructs' modeling have been followed: 1) Repeated indicators approach: all of the MVs of the first level are repeated for the secondorder LVs (University, Social and Psychology) they belong to. The third-order LV Image is then linked with all the MVs used for measuring the second-order constructs. Here, the three levels are connected by means of path coefficients (β); 2) Two-step approach: the 19 first-order LVs are estimated and then used as MVs for measuring the second-order constructs which become MVs for determining the third-order LV Image. The link between the three levels is represented by weights (Λ). The two approaches, performed by a tailor-made algorithm developed with MATLAB 7.1, lead to the following results for weights and path coefficients linking the three levels: I Table 2. Parameter estimation with the two approaches 0,442 0,343-0,460 0,478-0,762-0,717 0,236-0,272 0,278 0,598 0,428 0,487-0,426 0,377 0,169 0,214 0,170 0,293 0,259 0,477 0,594 0,581-0,846 0,359-0,430 0,557 0,773 0,836 0,697 0,466 0,501 0,492-0,155-0,198 0,408 0,541 0,535 0,504 0,798 0,801 0,442 0,701 0,463 0,542 The parameters have been further investigated by using bootstrap procedure. The resulting means for the parameters of the two approaches are summarized in Table 3. The parameters are divided
4 according to the approach used, the construct level and its composition (e.g., Level II University contains the links between second-order LV University and its 9 first-order LVs). Table 3. Bootstrap results REPEATED INDICATORS: Beta I University Image Sample 0,53 0,44-0,36 0,44-0,12 0 0,25 0,01 0,17 0,70 0,49 0,44 mean Social Psychology 0,63 0,62 0,59-0,01 0,05-0,29 0,63 0,65 0,69 0,6 TWO-STEP: Weights I University Image Sample 0,36 0,34-0,27 0,29 0,08 0,1 0,12 0,16 0,13 0,67 0,25 0,37 mean Social Psychology 0,44 0,43 0,47 0,45-0,1-0,18 0,39 0,34 0,55 0,47 The differences in the strategy adopted for the higher-order LVs definition, as the type of link between levels (betas or weights) or the number of MVs per LV, are reflected in differences in the parameters' estimates. The main dissimilarities concern the second-order LV Social Context, in both the relations with first and third level. For instance, the link between Social Context with the 4 th LV of the first level is -0,01, for the repeated indicators approach, and 0,45 for the two step approach; furthermore, the relationship with the third-order LV Image is equal to, respectively, 0,49 and 0,25. In order to explore the conditions affecting the two approaches results and check their reliability, a Monte Carlo simulation has been defined. 4. Discussion This section describes the definition of a Monte Carlo experiment aimed at catching the differences between the two strategies of building a third-order LV model. Following the procedure used by Hulland et al., (2010) the data are generated, for each simulation design, as described below: 1. generation of the exogenous LVs with the specified sample size; 2. standardization of the generated LVs; 3. computation of the endogenous LVs as the weighted average (weights are the fixed path coefficient linking exogenous with endogenous LVs) of the exogenous standardized LVs (the model) plus an error component e drawn from a univariate normal distribution. Given a R 2 value, the error term standard deviation is chosen to satisfy the equation: R 2 = var (model)/[var(model) + var(e)] 4. standardization of the endogenous LVs; 5. computation of the observed variables from the standardized constructs, by fixing the value of the coefficients; 6. standardization of observed variables befor estimation. Factors varying across the simulation designs are sample size (n=50, 200, 500), number of replications (k=100, 500) and distribution probability of errors (symmetric and non-symmetric).
5 References Agarwal, R., Karahanna, E., (2000). Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage. MIS Quarterly, 24 (4), Carli, R., Salvatore, S. (2001). L immagine della psicologia: Una ricerca sulla popolazione del Lazio [The image of psychology: Research on Latial population]. Roma: Kappa. Carli, R., Paniccia, R.M. (2002). L Analisi Emozionale del Testo: Uno strumento psicologico per leggere testi e discorsi [The Emotional analysis of the text: an instrument for reading texts and discourse]. Milano: FrancoAngeli. Ciavolino, E., Al-Nasser, A.D., (2009). Comparing Generalized Maximum Entropy and Partial Least Squares methods for Structural Equation Models, Journal of Nonparametric Statistics, 21 (8), Diamantopoulos, A., Winklhofer, H.M., (2001). Index construction with formative indicators: An alternative to scale development. Journal of Marketing Research, 38 (2), Esposito Vinzi, V., Chin, W.W., Henseler, J., Wang, H., (2010). Handbook of Partial Least Squares. Concepts, Methods and Applications. Springer Handbooks of Computational Statistics. New York. Hulland J., Ryan M.J., Rayner R.K., (2010). Modeling Customer Satisfaction: A Comparative Performance Evaluation of Covariance Structure Analysis versus Partial Least Squares, in Handbook of Partial Least Squares. Concepts, Methods and Applications. Springer Handbooks of Computational Statistics. New York. Lohmöller, J.B., (1989). Latent Variable Path Modeling with Partial Least Squares. Heidelberg: Physica-Verlag. Reinartz, W., Krafft, M., Hoyer, W.D., (2003). Measuring the Customer Relationship Management Construct and Linking it to Performance Outcomes. INSEAD Working Paper Series. 2003/02/MKT, Reinartz, W., Krafft, M., Hoyer, W.D., (2004). The Customer Relationship Management Process: Its Measurement and Impact on Performance. Journal of Marketing Research, 41(3), Wilson, B., Henseler, J. (2007). Modeling Reflective Higher-Order Constructs using Three Approaches with PLS Path Modeling: A Monte Carlo Comparison. In Thyne, M., Deans, K.R., Gnoth, J (eds.). Australian and New Zealand Marketing Academy Conference. Department of Marketing, School of Business, University of Otago. 3rd 5th December; Wold, H. (1966). Estimation of principal components and related models by iterative least squares. In Multivariate Analysis, P.R. Krishnajah, ed., Academic Press, NewYork, 1966, pp Wold, H., (1975). Path models with latent variables: The NIPALS approach, in Quantitative Sociology, H.M. Blalock, ed., Seminar Press, NewYork, 1975, pp
Can We Assess Formative Measurement using Item Weights? A Monte Carlo Simulation Analysis
Association for Information Systems AIS Electronic Library (AISeL) MWAIS 2013 Proceedings Midwest (MWAIS) 5-24-2013 Can We Assess Formative Measurement using Item Weights? A Monte Carlo Simulation Analysis
More informationComplex modeling in marketing using component based SEM
University of Wollongong Research Online Faculty of Commerce - Papers (Archive) Faculty of Business 2011 Complex modeling in marketing using component based SEM Shahriar Akter University of Wollongong,
More informationCombining Behavioral and Design Research Using Variance-based Structural Equation Modeling
Combining Behavioral and Design Research Using Variance-based Structural Equation Modeling Course to be held on 1-3 December 2016 at Texas Tech, Lubbock, TX, U.S.A. Instructor: Jörg Henseler, PhD Professor
More informationAn Empirical Study on Causal Relationships between Perceived Enjoyment and Perceived Ease of Use
An Empirical Study on Causal Relationships between Perceived Enjoyment and Perceived Ease of Use Heshan Sun Syracuse University hesun@syr.edu Ping Zhang Syracuse University pzhang@syr.edu ABSTRACT Causality
More informationAn Empirical Study of the Roles of Affective Variables in User Adoption of Search Engines
An Empirical Study of the Roles of Affective Variables in User Adoption of Search Engines ABSTRACT Heshan Sun Syracuse University hesun@syr.edu The current study is built upon prior research and is an
More informationA critical look at the use of SEM in international business research
sdss A critical look at the use of SEM in international business research Nicole F. Richter University of Southern Denmark Rudolf R. Sinkovics The University of Manchester Christian M. Ringle Hamburg University
More informationDoing Quantitative Research 26E02900, 6 ECTS Lecture 6: Structural Equations Modeling. Olli-Pekka Kauppila Daria Kautto
Doing Quantitative Research 26E02900, 6 ECTS Lecture 6: Structural Equations Modeling Olli-Pekka Kauppila Daria Kautto Session VI, September 20 2017 Learning objectives 1. Get familiar with the basic idea
More informationPanel: Using Structural Equation Modeling (SEM) Using Partial Least Squares (SmartPLS)
Panel: Using Structural Equation Modeling (SEM) Using Partial Least Squares (SmartPLS) Presenters: Dr. Faizan Ali, Assistant Professor Dr. Cihan Cobanoglu, McKibbon Endowed Chair Professor University of
More informationPLS structural Equation Modeling for Customer Satisfaction -Methodological and Application Issues-
PLS structural Equation Modeling for Customer Satisfaction -Methodological and Application Issues- Kai Kristensen, J. Eskildsen, H.J. Juhl, P. Østergaard Centre for Corporate Performance The Aarhus School
More informationSystem and User Characteristics in the Adoption and Use of e-learning Management Systems: A Cross-Age Study
System and User Characteristics in the Adoption and Use of e-learning Management Systems: A Cross-Age Study Oscar Lorenzo Dueñas-Rugnon, Santiago Iglesias-Pradas, and Ángel Hernández-García Grupo de Tecnologías
More informationTHE INDIRECT EFFECT IN MULTIPLE MEDIATORS MODEL BY STRUCTURAL EQUATION MODELING ABSTRACT
European Journal of Business, Economics and Accountancy Vol. 4, No. 3, 016 ISSN 056-6018 THE INDIRECT EFFECT IN MULTIPLE MEDIATORS MODEL BY STRUCTURAL EQUATION MODELING Li-Ju Chen Department of Business
More informationResearch on Software Continuous Usage Based on Expectation-confirmation Theory
Research on Software Continuous Usage Based on Expectation-confirmation Theory Daqing Zheng 1, Jincheng Wang 1, Jia Wang 2 (1. School of Information Management & Engineering, Shanghai University of Finance
More informationStatistical Audit. Summary. Conceptual and. framework. MICHAELA SAISANA and ANDREA SALTELLI European Commission Joint Research Centre (Ispra, Italy)
Statistical Audit MICHAELA SAISANA and ANDREA SALTELLI European Commission Joint Research Centre (Ispra, Italy) Summary The JRC analysis suggests that the conceptualized multi-level structure of the 2012
More informationStructural Equation Modelling: Tips for Getting Started with Your Research
: Tips for Getting Started with Your Research Kathryn Meldrum School of Education, Deakin University kmeldrum@deakin.edu.au At a time when numerical expression of data is becoming more important in the
More informationExamining the efficacy of the Theory of Planned Behavior (TPB) to understand pre-service teachers intention to use technology*
Examining the efficacy of the Theory of Planned Behavior (TPB) to understand pre-service teachers intention to use technology* Timothy Teo & Chwee Beng Lee Nanyang Technology University Singapore This
More informationAppendix B Construct Reliability and Validity Analysis. Initial assessment of convergent and discriminate validity was conducted using factor
Appendix B Construct Reliability and Validity Analysis Reflective Construct Reliability and Validity Analysis Initial assessment of convergent and discriminate validity was conducted using factor analysis
More informationScore Tests of Normality in Bivariate Probit Models
Score Tests of Normality in Bivariate Probit Models Anthony Murphy Nuffield College, Oxford OX1 1NF, UK Abstract: A relatively simple and convenient score test of normality in the bivariate probit model
More informationCHAPTER VI RESEARCH METHODOLOGY
CHAPTER VI RESEARCH METHODOLOGY 6.1 Research Design Research is an organized, systematic, data based, critical, objective, scientific inquiry or investigation into a specific problem, undertaken with the
More informationVolitional Autonomy and Relatedness: Mediators explaining Non Tenure Track Faculty Job. Satisfaction
Autonomy and : Mediators explaining Non Tenure Track Faculty Job Satisfaction Non-tenure track (NTT) faculty are increasingly utilized in higher education and shoulder much of the teaching load within
More informationCitation for published version (APA): Ebbes, P. (2004). Latent instrumental variables: a new approach to solve for endogeneity s.n.
University of Groningen Latent instrumental variables Ebbes, P. IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document
More informationAnalysis Propensity Score with Structural Equation Model Partial Least Square
PROCEEDING OF 3 RD INTERNATIONAL CONFERENCE ON RESEARCH, IMPLEMENTATION AND EDUCATION OF MATHEMATICS AND SCIENCE YOGYAKARTA, 16 17 MAY 2016 Analysis Propensity Score with Structural Equation Model Partial
More informationThe Effect of the Fulfillment of Hedonic and Aesthetic Information Needs of a Travel Magazine on Tourist Decision Making
University of Massachusetts Amherst ScholarWorks@UMass Amherst Travel and Tourism Research Association: Advancing Tourism Research Globally 2011 ttra International Conference The Effect of the Fulfillment
More informationUnderstanding Social Norms, Enjoyment, and the Moderating Effect of Gender on E-Commerce Adoption
Association for Information Systems AIS Electronic Library (AISeL) SAIS 2010 Proceedings Southern (SAIS) 3-1-2010 Understanding Social Norms, Enjoyment, and the Moderating Effect of Gender on E-Commerce
More informationMISSING DATA AND PARAMETERS ESTIMATES IN MULTIDIMENSIONAL ITEM RESPONSE MODELS. Federico Andreis, Pier Alda Ferrari *
Electronic Journal of Applied Statistical Analysis EJASA (2012), Electron. J. App. Stat. Anal., Vol. 5, Issue 3, 431 437 e-issn 2070-5948, DOI 10.1285/i20705948v5n3p431 2012 Università del Salento http://siba-ese.unile.it/index.php/ejasa/index
More informationW e l e a d
http://www.ramayah.com 1 2 Developing a Robust Research Framework T. Ramayah School of Management Universiti Sains Malaysia ramayah@usm.my Variables in Research Moderator Independent Mediator Dependent
More informationModeling the Influential Factors of 8 th Grades Student s Mathematics Achievement in Malaysia by Using Structural Equation Modeling (SEM)
International Journal of Advances in Applied Sciences (IJAAS) Vol. 3, No. 4, December 2014, pp. 172~177 ISSN: 2252-8814 172 Modeling the Influential Factors of 8 th Grades Student s Mathematics Achievement
More information2 Critical thinking guidelines
What makes psychological research scientific? Precision How psychologists do research? Skepticism Reliance on empirical evidence Willingness to make risky predictions Openness Precision Begin with a Theory
More informationGezinskenmerken: De constructie van de Vragenlijst Gezinskenmerken (VGK) Klijn, W.J.L.
UvA-DARE (Digital Academic Repository) Gezinskenmerken: De constructie van de Vragenlijst Gezinskenmerken (VGK) Klijn, W.J.L. Link to publication Citation for published version (APA): Klijn, W. J. L. (2013).
More informationSTRUCTURAL EQUATION MODELING AND REGRESSION: GUIDELINES FOR RESEARCH PRACTICE
Volume 4, Article 7 October 2000 STRUCTURAL EQUATION MODELING AND REGRESSION: GUIDELINES FOR RESEARCH PRACTICE David Gefen Management Department LeBow College of Business Drexel University gefend@drexel.edu
More informationCatherine A. Welch 1*, Séverine Sabia 1,2, Eric Brunner 1, Mika Kivimäki 1 and Martin J. Shipley 1
Welch et al. BMC Medical Research Methodology (2018) 18:89 https://doi.org/10.1186/s12874-018-0548-0 RESEARCH ARTICLE Open Access Does pattern mixture modelling reduce bias due to informative attrition
More informationRussian Journal of Agricultural and Socio-Economic Sciences, 3(15)
ON THE COMPARISON OF BAYESIAN INFORMATION CRITERION AND DRAPER S INFORMATION CRITERION IN SELECTION OF AN ASYMMETRIC PRICE RELATIONSHIP: BOOTSTRAP SIMULATION RESULTS Henry de-graft Acquah, Senior Lecturer
More informationExternal Variables and the Technology Acceptance Model
Association for Information Systems AIS Electronic Library (AISeL) AMCIS 1995 Proceedings Americas Conference on Information Systems (AMCIS) 8-25-1995 External Variables and the Technology Acceptance Model
More informationHierarchical Linear Models: Applications to cross-cultural comparisons of school culture
Hierarchical Linear Models: Applications to cross-cultural comparisons of school culture Magdalena M.C. Mok, Macquarie University & Teresa W.C. Ling, City Polytechnic of Hong Kong Paper presented at the
More informationThe Impact of Rewards on Knowledge Sharing
Association for Information Systems AIS Electronic Library (AISeL) CONF-IRM 2014 Proceedings International Conference on Information Resources Management (CONF-IRM) 2014 The Impact of Rewards on Knowledge
More informationReveal Relationships in Categorical Data
SPSS Categories 15.0 Specifications Reveal Relationships in Categorical Data Unleash the full potential of your data through perceptual mapping, optimal scaling, preference scaling, and dimension reduction
More informationGeorgetown University ECON-616, Fall Macroeconometrics. URL: Office Hours: by appointment
Georgetown University ECON-616, Fall 2016 Macroeconometrics Instructor: Ed Herbst E-mail: ed.herbst@gmail.com URL: http://edherbst.net/ Office Hours: by appointment Scheduled Class Time and Organization:
More informationMEA DISCUSSION PAPERS
Inference Problems under a Special Form of Heteroskedasticity Helmut Farbmacher, Heinrich Kögel 03-2015 MEA DISCUSSION PAPERS mea Amalienstr. 33_D-80799 Munich_Phone+49 89 38602-355_Fax +49 89 38602-390_www.mea.mpisoc.mpg.de
More informationWhat is Psychology? chapter 1
What is Psychology? chapter 1 Overview! The science of psychology! What psychologists do! Critical and scientific thinking! Correlational studies! The experiment! Evaluating findings What is psychology?
More informationTitle: The Theory of Planned Behavior (TPB) and Texting While Driving Behavior in College Students MS # Manuscript ID GCPI
Title: The Theory of Planned Behavior (TPB) and Texting While Driving Behavior in College Students MS # Manuscript ID GCPI-2015-02298 Appendix 1 Role of TPB in changing other behaviors TPB has been applied
More informationAn Introduction to Multiple Imputation for Missing Items in Complex Surveys
An Introduction to Multiple Imputation for Missing Items in Complex Surveys October 17, 2014 Joe Schafer Center for Statistical Research and Methodology (CSRM) United States Census Bureau Views expressed
More informationDIFFERENTIAL EFFECTS OF OMITTING FORMATIVE INDICATORS: A COMPARISON OF TECHNIQUES
DIFFERENTIAL EFFECTS OF OMITTING FORMATIVE INDICATORS: A COMPARISON OF TECHNIQUES Completed Research Paper Miguel I. Aguirre-Urreta DePaul University 1 E. Jackson Blvd. Chicago, IL 60604 USA maguirr6@depaul.edu
More informationCHAPTER 3 RESEARCH METHODOLOGY
CHAPTER 3 RESEARCH METHODOLOGY 3.1 Introduction 3.1 Methodology 3.1.1 Research Design 3.1. Research Framework Design 3.1.3 Research Instrument 3.1.4 Validity of Questionnaire 3.1.5 Statistical Measurement
More informationUSER INTERFACE DESIGN: A STUDY OF EXPECTATION- CONFIRMATION THEORY
USER INTERFACE DESIGN: A STUDY OF EXPECTATION- CONFIRMATION THEORY Aslina Baharum 1, 2, and Azizah Jaafar 2 1 Universiti Malaysia Sabah (UMS), Malaysia, aslina@ums.edu.my 2 Universiti Kebangsaan Malaysia,
More informationexisting statistical techniques. However, even with some statistical background, reading and
STRUCTURAL EQUATION MODELING (SEM): A STEP BY STEP APPROACH (PART 1) By: Zuraidah Zainol (PhD) Faculty of Management & Economics, Universiti Pendidikan Sultan Idris zuraidah@fpe.upsi.edu.my 2016 INTRODUCTION
More informationNPC-BASED GLOBAL INDICATORS FOR TEACHING UNIVERSITY ASSESSMENT. Carrozzo E. a Joint with Arboretti R. b
Dealing with Complexity in Society: From Plurality of Data to Synthetic Indicators NPC-BASED GLOBAL INDICATORS FOR TEACHING UNIVERSITY ASSESSMENT Carrozzo E. a Joint with Arboretti R. b a Department of
More informationinvestigate. educate. inform.
investigate. educate. inform. Research Design What drives your research design? The battle between Qualitative and Quantitative is over Think before you leap What SHOULD drive your research design. Advanced
More informationMODELING HIERARCHICAL STRUCTURES HIERARCHICAL LINEAR MODELING USING MPLUS
MODELING HIERARCHICAL STRUCTURES HIERARCHICAL LINEAR MODELING USING MPLUS M. Jelonek Institute of Sociology, Jagiellonian University Grodzka 52, 31-044 Kraków, Poland e-mail: magjelonek@wp.pl The aim of
More informationUse of Structural Equation Modeling in Social Science Research
Asian Social Science; Vol. 11, No. 4; 2015 ISSN 1911-2017 E-ISSN 1911-2025 Published by Canadian Center of Science and Education Use of Structural Equation Modeling in Social Science Research Wali Rahman
More informationRong Quan Low Universiti Sains Malaysia, Pulau Pinang, Malaysia
International Journal of Accounting & Business Management Vol. 1 (No.1), April, 2013 Page: 99-106 ISSN: 2289-4519 This work is licensed under a Creative Commons Attribution 4.0 International License. www.ftms.edu.my/journals/index.php/journals/ijabm
More informationCritical Thinking Assessment at MCC. How are we doing?
Critical Thinking Assessment at MCC How are we doing? Prepared by Maura McCool, M.S. Office of Research, Evaluation and Assessment Metropolitan Community Colleges Fall 2003 1 General Education Assessment
More informationBayesian and Frequentist Approaches
Bayesian and Frequentist Approaches G. Jogesh Babu Penn State University http://sites.stat.psu.edu/ babu http://astrostatistics.psu.edu All models are wrong But some are useful George E. P. Box (son-in-law
More informationQuantitative Research. By Dr. Achmad Nizar Hidayanto Information Management Lab Faculty of Computer Science Universitas Indonesia
Quantitative Research By Dr. Achmad Nizar Hidayanto Information Management Lab Faculty of Computer Science Universitas Indonesia Depok, 2 Agustus 2017 Quantitative Research: Definition (Source: Wikipedia)
More informationSTATISTICS AND RESEARCH DESIGN
Statistics 1 STATISTICS AND RESEARCH DESIGN These are subjects that are frequently confused. Both subjects often evoke student anxiety and avoidance. To further complicate matters, both areas appear have
More informationStrategies to Measure Direct and Indirect Effects in Multi-mediator Models. Paloma Bernal Turnes
China-USA Business Review, October 2015, Vol. 14, No. 10, 504-514 doi: 10.17265/1537-1514/2015.10.003 D DAVID PUBLISHING Strategies to Measure Direct and Indirect Effects in Multi-mediator Models Paloma
More informationASSESSING THE UNIDIMENSIONALITY, RELIABILITY, VALIDITY AND FITNESS OF INFLUENTIAL FACTORS OF 8 TH GRADES STUDENT S MATHEMATICS ACHIEVEMENT IN MALAYSIA
1 International Journal of Advance Research, IJOAR.org Volume 1, Issue 2, MAY 2013, Online: ASSESSING THE UNIDIMENSIONALITY, RELIABILITY, VALIDITY AND FITNESS OF INFLUENTIAL FACTORS OF 8 TH GRADES STUDENT
More informationPACDEFF 2017 Melbourne - Australia
PACDEFF 2017 Melbourne - Australia Risk Perception and Cultural Intelligence in Human Factors: The Interaction of Emotional Intelligence and Organisational Culture in High Risk Industries Across Borders
More informationStudy Evaluating the Alterations Caused in an Exploratory Factor Analysis when Multivariate Normal Data is Dichotomized
Journal of Modern Applied Statistical Methods Volume 16 Issue 2 Article 33 December 2017 Study Evaluating the Alterations Caused in an Exploratory Factor Analysis when Multivariate Normal Data is Dichotomized
More informationIdentification of Tissue Independent Cancer Driver Genes
Identification of Tissue Independent Cancer Driver Genes Alexandros Manolakos, Idoia Ochoa, Kartik Venkat Supervisor: Olivier Gevaert Abstract Identification of genomic patterns in tumors is an important
More informationInternational Conference on Humanities and Social Science (HSS 2016)
International Conference on Humanities and Social Science (HSS 2016) The Chinese Version of WOrk-reLated Flow Inventory (WOLF): An Examination of Reliability and Validity Yi-yu CHEN1, a, Xiao-tong YU2,
More informationCOMPARING PLS TO REGRESSION AND LISREL: A RESPONSE TO MARCOULIDES, CHIN, AND SAUNDERS 1
ISSUES AND OPINIONS COMPARING PLS TO REGRESSION AND LISREL: A RESPONSE TO MARCOULIDES, CHIN, AND SAUNDERS 1 Dale L. Goodhue Terry College of Business, MIS Department, University of Georgia, Athens, GA
More informationAssessing Measurement Invariance in the Attitude to Marriage Scale across East Asian Societies. Xiaowen Zhu. Xi an Jiaotong University.
Running head: ASSESS MEASUREMENT INVARIANCE Assessing Measurement Invariance in the Attitude to Marriage Scale across East Asian Societies Xiaowen Zhu Xi an Jiaotong University Yanjie Bian Xi an Jiaotong
More informationZainab M. AlQenaei. Dissertation Defense University of Colorado at Boulder Leeds School of Business Operations and Information Management Division
An Investigation of the Relationship between Consumer Mental Health Recovery Indicators and Clinicians Reports Using Multivariate Analyses of the Singular Value Decomposition of a Textual Corpus Zainab
More informationPackianathan Chelladurai Troy University, Troy, Alabama, USA.
DIMENSIONS OF ORGANIZATIONAL CAPACITY OF SPORT GOVERNING BODIES OF GHANA: DEVELOPMENT OF A SCALE Christopher Essilfie I.B.S Consulting Alliance, Accra, Ghana E-mail: chrisessilfie@yahoo.com Packianathan
More informationStatistical analysis DIANA SAPLACAN 2017 * SLIDES ADAPTED BASED ON LECTURE NOTES BY ALMA LEORA CULEN
Statistical analysis DIANA SAPLACAN 2017 * SLIDES ADAPTED BASED ON LECTURE NOTES BY ALMA LEORA CULEN Vs. 2 Background 3 There are different types of research methods to study behaviour: Descriptive: observations,
More informationSaville Consulting Wave Professional Styles Handbook
Saville Consulting Wave Professional Styles Handbook PART 4: TECHNICAL Chapter 19: Reliability This manual has been generated electronically. Saville Consulting do not guarantee that it has not been changed
More informationENDOGENEITY: AN OVERLOOKED THREAT TO VALIDITY OF CROSS-SECTIONAL RESEARCH. John Antonakis
ENDOGENEITY: AN OVERLOOKED THREAT TO VALIDITY OF CROSS-SECTIONAL RESEARCH John Antonakis Professor of Organizational Behavior Faculty of Business and Economics University of Lausanne Research seminar 28
More informationWE-INTENTION TO USE INSTANT MESSAGING FOR COLLABORATIVE WORK: THE MODERATING EFFECT OF EXPERIENCE
WE-INTENTION TO USE INSTANT MESSAGING FOR COLLABORATIVE WORK: THE MODERATING EFFECT OF EXPERIENCE Aaron X.L. Shen Department of Information Systems, University of Science and Technology of China City University
More informationAre Impulsive buying and brand switching satisfactory and emotional?
Are Impulsive buying and brand switching satisfactory and emotional? Abstract This study draws attention to a common concern about buying impulsiveness, by investigating this phenomenon in relation to
More informationManifestation Of Differences In Item-Level Characteristics In Scale-Level Measurement Invariance Tests Of Multi-Group Confirmatory Factor Analyses
Journal of Modern Applied Statistical Methods Copyright 2005 JMASM, Inc. May, 2005, Vol. 4, No.1, 275-282 1538 9472/05/$95.00 Manifestation Of Differences In Item-Level Characteristics In Scale-Level Measurement
More informationUnit 1 Exploring and Understanding Data
Unit 1 Exploring and Understanding Data Area Principle Bar Chart Boxplot Conditional Distribution Dotplot Empirical Rule Five Number Summary Frequency Distribution Frequency Polygon Histogram Interquartile
More informationIssues in Information Systems
ANALYZING THE ROLE OF SOME PERSONAL DETERMINANTS IN WEB 2.0 APPLICATIONS USAGE Adel M. Aladwani, Kuwait University, adel.aladwani@ku.edu.kw ABSTRACT This study examines the personal determinants of Web
More informationBayesian Logistic Regression Modelling via Markov Chain Monte Carlo Algorithm
Journal of Social and Development Sciences Vol. 4, No. 4, pp. 93-97, Apr 203 (ISSN 222-52) Bayesian Logistic Regression Modelling via Markov Chain Monte Carlo Algorithm Henry De-Graft Acquah University
More informationKelvin Chan Feb 10, 2015
Underestimation of Variance of Predicted Mean Health Utilities Derived from Multi- Attribute Utility Instruments: The Use of Multiple Imputation as a Potential Solution. Kelvin Chan Feb 10, 2015 Outline
More informationOrdinal Data Modeling
Valen E. Johnson James H. Albert Ordinal Data Modeling With 73 illustrations I ". Springer Contents Preface v 1 Review of Classical and Bayesian Inference 1 1.1 Learning about a binomial proportion 1 1.1.1
More informationSelection of Linking Items
Selection of Linking Items Subset of items that maximally reflect the scale information function Denote the scale information as Linear programming solver (in R, lp_solve 5.5) min(y) Subject to θ, θs,
More informationSurvey Sampling Weights and Item Response Parameter Estimation
Survey Sampling Weights and Item Response Parameter Estimation Spring 2014 Survey Methodology Simmons School of Education and Human Development Center on Research & Evaluation Paul Yovanoff, Ph.D. Department
More informationPrinciples of Sociology
Principles of Sociology DEPARTMENT OF ECONOMICS ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS [Academic year 2017/18, FALL SEMESTER] Lecturer: Dimitris Lallas Principles of Sociology 4th Session Sociological
More informationSelf-Oriented and Socially Prescribed Perfectionism in the Eating Disorder Inventory Perfectionism Subscale
Self-Oriented and Socially Prescribed Perfectionism in the Eating Disorder Inventory Perfectionism Subscale Simon B. Sherry, 1 Paul L. Hewitt, 1 * Avi Besser, 2 Brandy J. McGee, 1 and Gordon L. Flett 3
More informationOutlier Analysis. Lijun Zhang
Outlier Analysis Lijun Zhang zlj@nju.edu.cn http://cs.nju.edu.cn/zlj Outline Introduction Extreme Value Analysis Probabilistic Models Clustering for Outlier Detection Distance-Based Outlier Detection Density-Based
More informationCHAPTER 3 METHOD AND PROCEDURE
CHAPTER 3 METHOD AND PROCEDURE Previous chapter namely Review of the Literature was concerned with the review of the research studies conducted in the field of teacher education, with special reference
More informationTHE USE OF CRONBACH ALPHA RELIABILITY ESTIMATE IN RESEARCH AMONG STUDENTS IN PUBLIC UNIVERSITIES IN GHANA.
Africa Journal of Teacher Education ISSN 1916-7822. A Journal of Spread Corporation Vol. 6 No. 1 2017 Pages 56-64 THE USE OF CRONBACH ALPHA RELIABILITY ESTIMATE IN RESEARCH AMONG STUDENTS IN PUBLIC UNIVERSITIES
More informationExploring the Influence of Particle Filter Parameters on Order Effects in Causal Learning
Exploring the Influence of Particle Filter Parameters on Order Effects in Causal Learning Joshua T. Abbott (joshua.abbott@berkeley.edu) Thomas L. Griffiths (tom griffiths@berkeley.edu) Department of Psychology,
More informationRegression CHAPTER SIXTEEN NOTE TO INSTRUCTORS OUTLINE OF RESOURCES
CHAPTER SIXTEEN Regression NOTE TO INSTRUCTORS This chapter includes a number of complex concepts that may seem intimidating to students. Encourage students to focus on the big picture through some of
More informationBasic concepts and principles of classical test theory
Basic concepts and principles of classical test theory Jan-Eric Gustafsson What is measurement? Assignment of numbers to aspects of individuals according to some rule. The aspect which is measured must
More informationSlacking and the Internet in the Classroom: A Preliminary Investigation
Association for Information Systems AIS Electronic Library (AISeL) SIGHCI 2006 Proceedings Special Interest Group on Human-Computer Interaction 2006 Slacking and the Internet in the Classroom: A Preliminary
More informationThis module illustrates SEM via a contrast with multiple regression. The module on Mediation describes a study of post-fire vegetation recovery in
This module illustrates SEM via a contrast with multiple regression. The module on Mediation describes a study of post-fire vegetation recovery in southern California woodlands. Here I borrow that study
More informationTHE INFLUENCE OF UNCONSCIOUS NEEDS ON COLLEGE PROGRAM CHOICE
University of Massachusetts Amherst ScholarWorks@UMass Amherst Tourism Travel and Research Association: Advancing Tourism Research Globally 2007 ttra International Conference THE INFLUENCE OF UNCONSCIOUS
More informationA COMPARISON OF IMPUTATION METHODS FOR MISSING DATA IN A MULTI-CENTER RANDOMIZED CLINICAL TRIAL: THE IMPACT STUDY
A COMPARISON OF IMPUTATION METHODS FOR MISSING DATA IN A MULTI-CENTER RANDOMIZED CLINICAL TRIAL: THE IMPACT STUDY Lingqi Tang 1, Thomas R. Belin 2, and Juwon Song 2 1 Center for Health Services Research,
More informationInternational Core Journal of Engineering Vol.3 No ISSN:
The Status of College Counselors' Subjective Well-being and Its Influence on the Occupational Commitment : An Empirical Research based on SPSS Statistical Analysis Wenping Peng Department of Social Sciences,
More informationImportance of factors contributing to work-related stress: comparison of four metrics
Importance of factors contributing to work-related stress: comparison of four metrics Mounia N. Hocine, Natalia Feropontova, Ndèye Niang, Karim Aït-Bouziad, Gilbert Saporta Conservatoire national des arts
More informationPrograms for facies modeling with DMPE
Programs for facies modeling with DMPE Yupeng Li and Clayton V. Deutsch The programs needed for direct multivariate probability estimation (DMPE) are introduced in detail. The first program (TPcalc) is
More informationDecision process on Health care provider A Patient outlook: Structural equation modeling approach
Decision process on Health care provider A Patient outlook: Structural equation modeling approach Ms. Sharanya Paranthaman, Lecturer, Sri Ramachra College of Management, Sri Ramachra University, Porur,
More informationFactors Influencing Undergraduate Students Motivation to Study Science
Factors Influencing Undergraduate Students Motivation to Study Science Ghali Hassan Faculty of Education, Queensland University of Technology, Australia Abstract The purpose of this exploratory study was
More informationOn Test Scores (Part 2) How to Properly Use Test Scores in Secondary Analyses. Structural Equation Modeling Lecture #12 April 29, 2015
On Test Scores (Part 2) How to Properly Use Test Scores in Secondary Analyses Structural Equation Modeling Lecture #12 April 29, 2015 PRE 906, SEM: On Test Scores #2--The Proper Use of Scores Today s Class:
More informationA Bayesian Nonparametric Model Fit statistic of Item Response Models
A Bayesian Nonparametric Model Fit statistic of Item Response Models Purpose As more and more states move to use the computer adaptive test for their assessments, item response theory (IRT) has been widely
More informationPA 552: Designing Applied Research. Bruce Perlman Planning and Designing Research
PA 552: Designing Applied Research Bruce Perlman Planning and Designing Research PA 552 DESIGNING RESEARCH Research Approach Basic Plan Adopted for Conducting the Research Overall Framework of the Project
More informationA STUDY ON IMPACT OF PSYCHOLOGICAL EMPOWERMENT ON EMPLOYEE RETENTION IN TECHNICAL INSTITUTES OF DURG AND BHILAI
Management A STUDY ON IMPACT OF PSYCHOLOGICAL EMPOWERMENT ON EMPLOYEE RETENTION IN TECHNICAL INSTITUTES OF DURG AND BHILAI Shivangi Jaiswal *1, Pankaj Joge 2 *1 Student, PG Department of Commerce, St Thomas
More informationExploring the Time Dimension in the Technology Acceptance Model with Latent Growth Curve Modeling
Association for Information Systems AIS Electronic Library (AISeL) AMCIS 2009 Proceedings Americas Conference on Information Systems (AMCIS) 2009 Exploring the Time Dimension in the Technology Acceptance
More informationAcceptance and Usage of Innovative Healthcare Service for the Elderly People: A System Dynamics Modeling Approach
2012 2 nd International Conference on Economics, Trade and Development IPEDR vol.36 (2012) (2012) IACSIT Press, Singapore Acceptance and Usage of Innovative Healthcare Service for the Elderly People: A
More informationAnalysis of the Reliability and Validity of an Edgenuity Algebra I Quiz
Analysis of the Reliability and Validity of an Edgenuity Algebra I Quiz This study presents the steps Edgenuity uses to evaluate the reliability and validity of its quizzes, topic tests, and cumulative
More information