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Fitting Covariance Models for Theory Generation

Joerg Evermann, Mary Tate
2011 Journal of the AIS  
Research Article Covariance-based structural equation modeling (CB-SEM) is an increasingly popular technique for analyzing quantitative data in Information Systems research.  ...  This paper shows that as part of the pursuit of model fit, researchers using CB-SEM can provide deeper insights into a phenomenon, allowing us to build theories based on quantitative data.  ...  researchers to build on a body of data for new theory generation.  ... 
doi:10.17705/1jais.00276 fatcat:rioq4oxydjht5alaodci2uxequ

Significance tests and goodness of fit in the analysis of covariance structures

P. M. Bentler, Douglas G. Bonett
1980 Psychological bulletin  
Large-sample theory provides a chi-square goodness-of-fit test for comparing a model against a general alternative model based on correlated variables.  ...  Normed and nonnormed fit indices are developed and illustrated. Covariance structure analysis represents a set of techniques for theory testing with correlational data.  ...  Large-sample theory provides a chi-square goodness-of-fit test for comparing a model against a general alternative model based on correlated variables.  ... 
doi:10.1037/0033-2909.88.3.588 fatcat:qrbqvcqa5ncdnhp7c5uxauci2i

Statistical estimation of extreme ocean environments: The requirement for modelling directionality and other covariate effects

Philip Jonathan, Kevin Ewans, George Forristall
2008 Ocean Engineering  
If effects of other covariates (e.g. time or space) are suspected, we similarly recommend use of extreme value models which adequately capture sources of covariate variability for all design analysis.  ...  , and that omni-directional criteria developed from a directional model are different from those generated when directionality is not accounted for.  ...  Median return values for different return periods, from theory (solid black), directional model fitting (dashed black) and constant model fitting for different thresholds (grey), for Case Study 1.  ... 
doi:10.1016/j.oceaneng.2008.04.002 fatcat:ggnvlgaa5reqtgjcxzxxogfee4

Generalized Additive Models: An Introduction with R (2nd Edition)

Virgilio Gomez-Rubio
2018 Journal of Statistical Software  
Generalized additive models (GAMs) are one of the main modeling tools for data analysis.  ...  As described in Wood's book, GAMs cover a wide range of statistical models used in practice, such as the general linear model, generalized linear models and mixed-effects models.  ...  Hence, the theory required for model fitting and the tools for model assessment and comparison are updated to cover this more general case.  ... 
doi:10.18637/jss.v086.b01 fatcat:aqgp4d3heva7vemejokol2hem4

Estimating Measurement Error on Highly Speeded Tests

Susan E. Whitely
1979 Applied Psychological Measurement  
Under strong true score models, such as the Birnbaum (1968) twoparameter logistic model, measurement error for internal structure is estimated within a wellspecified model, using efficient estimation methods  ...  The appropriateness of the model is tested for five traits, and error estimates are compared to the classical formula estimates.  ...  Acknowledgments This study was partially supported by grant number 34 72-xO-0038.from the University of Kansas General Research Fund. Susan E. Whitely, Principal Investigator.  ... 
doi:10.1177/014662167900300201 fatcat:yp6ah2p3j5a7tis4lpykazfy2e

How to Compare Psychometric Factor and Network Models

Kees-Jan Kan, Hannelies de Jonge, Han L J van der Maas, Stephen Z Levine, Sacha Epskamp
2020 Journal of Intelligence  
We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value  ...  Of substantive theoretical interest, the results support a network interpretation of general intelligence.  ...  We thank our reviewers for their valuable comments and so for the improvement of our manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jintelligence8040035 pmid:33023229 pmcid:PMC7709577 fatcat:y7gqgjrhbfezpggjg6w5z6moum

Covariance-Based Structural Equation Modeling in the Journal of Advertising: Review and Recommendations

Joseph F. Hair, Barry J. Babin, Nina Krey
2017 Journal of Advertising  
In this paper, we review applications of covariance-based structural equation modeling (SEM) in the Journal of Advertising (JA) starting with the first issue in 1972.  ...  , multiple group analysis, reporting, and guidelines for interpretation of results.  ...  Statistical identification For recursive (one-way causality) models. In general avoid two item and single item measures.  ... 
doi:10.1080/00913367.2017.1329496 fatcat:wbfsldnzxjacppcheztyzhlfsm

COVARIANCE STRUCTURE ANALYSIS: Statistical Practice, Theory, and Directions

Peter M. Bentler, Paul Dudgeon
1996 Annual Review of Psychology  
Valid conclusions about the adequacy of a model as an acceptable representation of data, which are based on goodness-of-fit test statistics and standard errors of parameter estimates, rely on the model  ...  Although covariance structure analysis is used increasingly to analyze nonexperimental data, important statistical requirements for its proper use are frequently ignored.  ...  degrees of freedom (df) for the fitted model.  ... 
doi:10.1146/annurev.psych.47.1.563 pmid:15012488 fatcat:mme5pn3b6ffm3h5kacjwwjvfmu

The genetic analysis of age-dependent traits: modeling the character process

S D Pletcher, C J Geyer
1999 Genetics  
In this theory, the analogs of variance components for single traits are covariance functions for function-valued traits.  ...  In the approach presented here, we employ a variety of parametric models for covariance functions that have a number of desirable properties: the functions (1) are positive definite, (2) can be estimated  ...  (C) Lack of fit of an estimated genetic covariance surface for a model consisting of four orthogonal polynomials (the same form used to generate the data).  ... 
pmid:10610347 pmcid:PMC1460778 fatcat:r5vhm7mqejbdtm457vsod3mzwa

The Genetic Analysis of Age-Dependent Traits: Modeling the Character Process

Scott D Pletcher, Charles J Geyer
1999 Genetics  
In this theory, the analogs of variance components for single traits are covariance functions for function-valued traits.  ...  In the approach presented here, we employ a variety of parametric models for covariance functions that have a number of desirable properties: the functions (1) are positive definite, (2) can be estimated  ...  (C) Lack of fit of an estimated genetic covariance surface for a model consisting of four orthogonal polynomials (the same form used to generate the data).  ... 
doi:10.1093/genetics/153.2.825 fatcat:nxt3xet7f5czxniwmi5sbr7bsm

Structural equation modelling: Adjudging model fit

Paul Barrett
2007 Personality and Individual Differences  
For journal editors, reviewers, and readers of research articles, structural equation model (SEM) fit has recently become a confusing and contentious area of evaluative methodology.  ...  On the other hand, suitably scaled indices of approximate fit do not possess this sensitivity to sample size, but neither are they "tests" of model fit.  ...  Either generate a new class of model which is based upon a new theory, or simply report the evaluative process undertaken and suggest that a new theory might be required for the area. 4.  ... 
doi:10.1016/j.paid.2006.09.018 fatcat:b5q6337zyffczkejbt7v5cx2lq

Structural Equation Modeling [chapter]

Catherine M. Stein, Nathan J. Morris, Nora L. Nock
2011 Msphere  
n (2001) announced a 'second generation' of structural equation modeling.  ...  In 1980, Peter Bentler (1980 ) stated that structural equation modeling held 'the greatest promise for furthering psychological science.'  ...  In addition, the general model specifies variances and covariances for ξ, ζ, ε, and δ, denoted Φ, Ψ, Θ ε , and Θ δ , respectively.  ... 
doi:10.1007/978-1-61779-555-8_27 pmid:22307716 fatcat:azjtzcnkgnaabkdtfqfhkvegaq

Structural Equation Modeling [chapter]

D. Kaplan
2001 International Encyclopedia of the Social & Behavioral Sciences  
n (2001) announced a 'second generation' of structural equation modeling.  ...  In 1980, Peter Bentler (1980 ) stated that structural equation modeling held 'the greatest promise for furthering psychological science.'  ...  In addition, the general model specifies variances and covariances for ξ, ζ, ε, and δ, denoted Φ, Ψ, Θ ε , and Θ δ , respectively.  ... 
doi:10.1016/b0-08-043076-7/00776-2 fatcat:4ciosgesizaihbw4qommvxq6la

Shame for disrespecting evidence: the personal consequences of insufficient respect for structural equation model testing

Leslie A Hayduk
2014 BMC Medical Research Methodology  
All covariance-based fit indices risk failing to expose model problems because the extent of model misspecification does not reliably correspond to the magnitude of covariance ill fitseriously causally  ...  ; and b) that the amount of covariance ill fit cannot be trusted to report the seriousness of model misspecifications.  ...  because it is possible for even seriously causally misspecified models to provide perfect covariance fit.  ... 
doi:10.1186/1471-2288-14-124 pmid:25430437 pmcid:PMC4297459 fatcat:hb76ld3xffdvdhxu2esujp6jmu

Page 292 of Educational and Psychological Measurement Vol. 71, Issue 2 [page]

2011 Educational and Psychological Measurement  
for generating equivalent models for PLS and covariance-based SEM.  ...  Finally, the fit for this model is good (x?  ... 
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