NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 9 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Samuelsen, Karen – Measurement: Interdisciplinary Research and Perspectives, 2012
The notion that there is often no clear distinction between factorial and typological models (von Davier, Naemi, & Roberts, this issue) is sound. As von Davier et al. state, theory often indicates a preference between these models; however the statistical criteria by which these are delineated offer much less clarity. In many ways the procedure…
Descriptors: Models, Statistical Analysis, Classification, Factor Structure
Peer reviewed Peer reviewed
Direct linkDirect link
Rupp, Andre A. – Measurement: Interdisciplinary Research and Perspectives, 2012
In the focus article of this issue, von Davier, Naemi, and Roberts essentially coupled: (1) a short methodological review of structural similarities of latent variable models with discrete and continuous latent variables; and (2) 2 short empirical case studies that show how these models can be applied to real, rather than simulated, large-scale…
Descriptors: Models, Classification, Multivariate Analysis, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
McLachlan, Geoffrey J. – Psychological Methods, 2011
I discuss the recommendations and cautions in Steinley and Brusco's (2011) article on the use of finite models to cluster a data set. In their article, much use is made of comparison with the "K"-means procedure. As noted by researchers for over 30 years, the "K"-means procedure can be viewed as a special case of finite mixture modeling in which…
Descriptors: Computation, Multivariate Analysis, Matrices, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Steinley, Douglas; Brusco, Michael J. – Psychological Methods, 2011
McLachlan (2011) and Vermunt (2011) each provided thoughtful replies to our original article (Steinley & Brusco, 2011). This response serves to incorporate some of their comments while simultaneously clarifying our position. We argue that greater caution against overparamaterization must be taken when assuming that clusters are highly elliptical…
Descriptors: Multivariate Analysis, Research Methodology, Data, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Lubke, Gitta – Measurement: Interdisciplinary Research and Perspectives, 2012
Von Davier et al. (this issue) describe two analyses that aim at determining whether the constructs measured with a number of observed items are categorical or continuous in nature. The issue of types versus traits has a long history and is relevant in many areas of behavioral research, including personality research, as emphasized by von Davier…
Descriptors: Models, Classification, Multivariate Analysis, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Vermunt, Jeroen K. – Psychological Methods, 2011
Steinley and Brusco (2011) presented the results of a huge simulation study aimed at evaluating cluster recovery of mixture model clustering (MMC) both for the situation where the number of clusters is known and is unknown. They derived rather strong conclusions on the basis of this study, especially with regard to the good performance of…
Descriptors: Multivariate Analysis, Simulation, Research, Mathematics
Peer reviewed Peer reviewed
Direct linkDirect link
Van Landeghem, Georges; De Fraine, Bieke; Van Damme, Jan – Multivariate Behavioral Research, 2005
This short contribution is a comment on M. Moerbeek's exploration of consequences of ignoring a level of clustering in a multilevel model, which was published in the first issue of the 2004 volume of Multivariate Behavioral Research. After having recapitulated the framework and extended the results of Moerbeek's study, we formulate two critical…
Descriptors: Multivariate Analysis, Behavioral Science Research, Models, Research Methodology
Misanchuk, Earl R. – 1984
The technique of multivariate analysis is particularly suited to educational needs assessment research because it allows for the summarization of data across any number of learners or components of educational need to produce a single numerical index of need for each skill examined. In the needs assessment process, educational or training need is…
Descriptors: Comparative Analysis, Competence, Data Analysis, Educational Needs
Peer reviewed Peer reviewed
Sullivan, Howard J.; And Others – Educational Technology, Research and Development, 1993
Discusses a nationwide survey of university educational technology professionals and students that was conducted to determine their opinions about the future of the field. Areas addressed include educational technology and learning theory; instructional design models; technology and individualized instruction; technological advances; educational…
Descriptors: Educational Technology, Elementary Secondary Education, Employment Opportunities, Futures (of Society)