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Thomas A. Schmitt

Bio: Thomas A. Schmitt is an academic researcher from Eastern Michigan University. The author has contributed to research in topics: Exploratory factor analysis & Item response theory. The author has an hindex of 15, co-authored 26 publications receiving 2034 citations. Previous affiliations of Thomas A. Schmitt include University of Wisconsin–Milwaukee.

Papers
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Journal ArticleDOI
TL;DR: The present article provides a current overview of these areas in an effort to provide researchers with up-to-date methods and considerations in both exploratory and confirmatory factor analysis.
Abstract: Researchers must make numerous choices when conducting factor analyses, each of which can have significant ramifications on the model results. They must decide on an appropriate sample size to achieve accurate parameter estimates and adequate power, a factor model and estimation method, a method for determining the number of factors and evaluating model fit, and a rotation criterion. Unfortunately, researchers continue to use outdated methods in each of these areas. The present article provides a current overview of these areas in an effort to provide researchers with up-to-date methods and considerations in both exploratory and confirmatory factor analysis. A demonstration was provided to illustrate current approaches. Choosing between confirmatory and exploratory methods is also discussed, as researchers often make incorrect assumptions about the application of each.

774 citations

Journal ArticleDOI
TL;DR: Greater fusion with others was associated with greater spousal fusion and dimensions of adult attachment insecurity, and suggestions for future research with the DSI-R are discussed.
Abstract: The Differentiation of Self Inventory (DSI) is a multidimensional measure of differentiation consisting of four subscales focusing on adults (ages 25+), and their significant relationships, including current relationships with family of origin. Although the DSI full scale and three of its subscales are theoretically and psychometrically sound, the Fusion with Others (FO) subscale is lacking. Therefore, responses of 225 adults were used to revise the FO subscale. Results yielded a 12-item, revised FO subscale with improved internal consistency reliability and construct validity. Greater fusion with others was associated with greater spousal fusion and dimensions of adult attachment insecurity. Implications for Bowen theory and suggestions for future research with the DSI-R are discussed.

324 citations

Journal ArticleDOI
TL;DR: The results suggest that depending on the rotation criterion selected and the complexity of the factor pattern matrix, the interpretation of the interfactor correlations and factor pattern loadings can vary substantially.
Abstract: Exploratory factor analysis (EFA) is a commonly used statistical technique for examining the relationships between variables (e.g., items) and the factors (e.g., latent traits) they depict. There are several decisions that must be made when using EFA, with one of the more important being choice of the rotation criterion. This selection can be arduous given the numerous rotation criteria available and the lack of research/literature that compares their function and utility. Historically, researchers have chosen rotation criteria based on whether or not factors are correlated and have failed to consider other important aspects of their data. This study reviews several rotation criteria, demonstrates how they may perform with different factor pattern structures, and highlights for researchers subtle but important differences between each rotation criterion. The choice of rotation criterion is critical to ensure researchers make informed decisions as to when different rotation criteria may or may not be appropriate. The results suggest that depending on the rotation criterion selected and the complexity of the factor pattern matrix, the interpretation of the interfactor correlations and factor pattern loadings can vary substantially. Implications and future directions are discussed.

279 citations

Journal ArticleDOI
TL;DR: In this paper, the authors compared estimation methods within a measurement invariance (MI) framework and determined if research conclusions using normal-theory maximum likelihood (ML) generalizes to the robust ML (MLR) and weighted least squares means and variance adjusted (WLSMV) estimators.
Abstract: A paucity of research has compared estimation methods within a measurement invariance (MI) framework and determined if research conclusions using normal-theory maximum likelihood (ML) generalizes to the robust ML (MLR) and weighted least squares means and variance adjusted (WLSMV) estimators. Using ordered categorical data, this simulation study aimed to address these queries by investigating 342 conditions. When testing for metric and scalar invariance, Δχ2 results revealed that Type I error rates varied across estimators (ML, MLR, and WLSMV) with symmetric and asymmetric data. The Δχ2 power varied substantially based on the estimator selected, type of noninvariant indicator, number of noninvariant indicators, and sample size. Although some the changes in approximate fit indexes (ΔAFI) are relatively sample size independent, researchers who use the ΔAFI with WLSMV should use caution, as these statistics do not perform well with misspecified models. As a supplemental analysis, our results evaluate and sug...

273 citations

Journal ArticleDOI
TL;DR: Exploratory Factor Analysis (EFA) has been used in the social sciences to depict the relationships between variables/items and latent traits as mentioned in this paper, and it has been applied in many applications.
Abstract: Exploratory factor analysis (EFA) has long been used in the social sciences to depict the relationships between variables/items and latent traits. Researchers face many choices when using EFA, incl...

210 citations


Cited by
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01 Jan 2006
TL;DR: For example, Standardi pružaju okvir koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima.
Abstract: Pedagosko i psiholosko testiranje i procjenjivanje spadaju među najvažnije doprinose znanosti o ponasanju nasem drustvu i pružaju temeljna i znacajna poboljsanja u odnosu na ranije postupke. Iako se ne može ustvrditi da su svi testovi dovoljno usavrseni niti da su sva testiranja razborita i korisna, postoji velika kolicina informacija koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima. Pravilna upotreba testova može dovesti do boljih odluka o pojedincima i programima nego sto bi to bio slucaj bez njihovog koristenja, a također i ukazati na put za siri i pravedniji pristup obrazovanju i zaposljavanju. Međutim, losa upotreba testova može dovesti do zamjetne stete nanesene ispitanicima i drugim sudionicima u procesu donosenja odluka na temelju testovnih podataka. Cilj Standarda je promoviranje kvalitetne i eticne upotrebe testova te uspostavljanje osnovice za ocjenu kvalitete postupaka testiranja. Svrha objavljivanja Standarda je uspostavljanje kriterija za evaluaciju testova, provedbe testiranja i posljedica upotrebe testova. Iako bi evaluacija prikladnosti testa ili njegove primjene trebala ovisiti prvenstveno o strucnim misljenjima, Standardi pružaju okvir koji osigurava obuhvacanje svih relevantnih pitanja. Bilo bi poželjno da svi autori, sponzori, nakladnici i korisnici profesionalnih testova usvoje Standarde te da poticu druge da ih također prihvate.

3,905 citations

Journal ArticleDOI
TL;DR: ESEM, an overarching integration of the best aspects of CFA/SEM and traditional EFA, provides confirmatory tests of a priori factor structures, relations between latent factors and multigroup/multioccasion tests of full (mean structure) measurement invariance.
Abstract: Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), path analysis, and structural equation modeling (SEM) have long histories in clinical research. Although CFA has largely superseded EFA, CFAs of multidimensional constructs typically fail to meet standards of good measurement: goodness of fit, measurement invariance, lack of differential item functioning, and well-differentiated factors in support of discriminant validity. Part of the problem is undue reliance on overly restrictive CFAs in which each item loads on only one factor. Exploratory SEM (ESEM), an overarching integration of the best aspects of CFA/SEM and traditional EFA, provides confirmatory tests of a priori factor structures, relations between latent factors and multigroup/multioccasion tests of full (mean structure) measurement invariance. It incorporates all combinations of CFA factors, ESEM factors, covariates, grouping/multiple-indicator multiple-cause (MIMIC) variables, latent growth, and complex structures that typically have required CFA/SEM. ESEM has broad applicability to clinical studies that are not appropriately addressed either by traditional EFA or CFA/SEM.

1,052 citations

ReportDOI
01 Jan 1967

890 citations

Journal ArticleDOI
TL;DR: The present article provides a current overview of these areas in an effort to provide researchers with up-to-date methods and considerations in both exploratory and confirmatory factor analysis.
Abstract: Researchers must make numerous choices when conducting factor analyses, each of which can have significant ramifications on the model results. They must decide on an appropriate sample size to achieve accurate parameter estimates and adequate power, a factor model and estimation method, a method for determining the number of factors and evaluating model fit, and a rotation criterion. Unfortunately, researchers continue to use outdated methods in each of these areas. The present article provides a current overview of these areas in an effort to provide researchers with up-to-date methods and considerations in both exploratory and confirmatory factor analysis. A demonstration was provided to illustrate current approaches. Choosing between confirmatory and exploratory methods is also discussed, as researchers often make incorrect assumptions about the application of each.

774 citations