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Showing 1 to 15 of 191 results
Eid, Michael; Koch, Tobias – Measurement: Interdisciplinary Research and Perspectives, 2014
Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…
Descriptors: Factor Analysis, Measurement, Theories, Executive Function
Wiebe, Sandra A.; McFall, G. Peggy – Measurement: Interdisciplinary Research and Perspectives, 2014
Since Miyake and his colleagues (2000) published their seminal paper on the use of confirmatory factor analysis (CFA) to parse executive function (EF), CFA methods have become ubiquitous in EF research. In their interesting and thoughtful Focus article, "Executive Function: Formative Versus Reflective Measurement," Willoughby and…
Descriptors: Executive Function, Cognitive Measurement, Factor Analysis, Individual Development
Graf, Edith Aurora – Measurement: Interdisciplinary Research and Perspectives, 2014
In "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games," Almond, Kim, Velasquez, and Shute have prepared a thought-provoking piece contrasting the roles of task model variables in a traditional assessment of mathematics word problems to their roles in "Newton's Playground," a game designed…
Descriptors: Task Analysis, Models, Educational Games, Word Problems (Mathematics)
Markus, Keith A. – Measurement: Interdisciplinary Research and Perspectives, 2014
Keith Marcus congratulates Almond et al. on an interesting article bringing together two topics that are important to the field of testing. He states that some aspects of the exposition came across as not yet fully developed, as if the manuscript had been hurried to press. In this commentary, he attempts to expand aspects of the article, which he…
Descriptors: Test Validity, Theory Practice Relationship, Observation, Educational Assessment
Timms, Mike – Measurement: Interdisciplinary Research and Perspectives, 2014
In his commentary on "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Almond et al., Mike Timms writes that his own research has involved the use of embedded assessments using simulations in interactive learning environments, and the Evidence Centered Design (ECD) approach has provided a solid…
Descriptors: Task Analysis, Models, Educational Assessment, Simulation
Walker, A. Adrienne; Engelhard, George, Jr. – Measurement: Interdisciplinary Research and Perspectives, 2014
"Game-Based Assessments: A Promising Way to Create Idiographic Perspectives" (Adrienne Walker and George Englehard) comments on: "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Russell G. Almond, Yoon Jeon Kim, Gertrudes Velasquez, and Valerie J. Shute. Here, Walker and Englehard write…
Descriptors: Educational Games, Task Analysis, Models, Educational Assessment
Bond, Lloyd – Measurement: Interdisciplinary Research and Perspectives, 2014
Lloyd Bond comments here on the Focus article in this issue of "Measurement: Interdisciplinary Research and Perspectives". The Focus article is entitled: "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" (Russell G. Almond, Yoon Jeon Kim, Gertrudes Velasquez, and Valerie J. Shute). Bond…
Descriptors: Educational Assessment, Task Analysis, Models, Design
Bauer, Malcolm – Measurement: Interdisciplinary Research and Perspectives, 2014
Malcolm Bauer, from Education Testing Services, provides his comments on the Focus article in this issue of "Measurement" entitled : "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" (Russell G. Almond, Yoon Jeon Kim, Gertrudes Velasquez, Valerie J. Shute). Bauer begins his remarks by noting…
Descriptors: Task Analysis, Models, Design Requirements, Educational Games
Peterson, Eric; Welsh, Marilyn C. – Measurement: Interdisciplinary Research and Perspectives, 2014
Research into executive functioning (EF) has indeed grown exponentially across the past few decades, but as the Willoughby et al. critique makes clear, there remain fundamental questions to be resolved. The crux of their argument is built upon an examination of the confirmatory factor analysis (CFA) approach to understanding executive processes.…
Descriptors: Executive Function, Measurement, Factor Analysis, Reliability
Wang, Jue; Engelhard, George, Jr.; Lu, Zhenqiu – Measurement: Interdisciplinary Research and Perspectives, 2014
The authors of the focus article in this issue have emphasized the continuing confusion among some researchers regarding various indicators used in structural equation models (SEMs). Their major claim is that causal indicators are not inherently unstable, and even if they are unstable they are at least not more unstable than other types of…
Descriptors: Structural Equation Models, Measurement, Statistical Analysis, Causal Models
Howell, Roy D. – Measurement: Interdisciplinary Research and Perspectives, 2014
Building on the work of Bollen (2007) and Bollen & Bauldry (2011), Bainter and Bollen (this issue) clarifies several points of confusion in the literature regarding causal indicator models. This author would certainly agree that the effect indicator (reflective) measurement model is inappropriate for some indicators (such as the social…
Descriptors: Statistical Analysis, Measurement, Causal Models, Data Interpretation
West, Stephen G.; Grimm, Kevin J. – Measurement: Interdisciplinary Research and Perspectives, 2014
These authors agree with Bainter and Bollen that causal effects represents a useful measurement structure in some applications. The structure of the science of the measurement problem should determine the model; the measurement model should not determine the science. They also applaud Bainter and Bollen's important reminder that the full…
Descriptors: Causal Models, Measurement, Test Theory, Statistical Analysis
Markus, Keith A. – Measurement: Interdisciplinary Research and Perspectives, 2014
In a series of articles and comments, Kenneth Bollen and his collaborators have incrementally refined an account of structural equation models that (a) model a latent variable as the effect of several observed variables and (b) carry an interpretation of the observed variables as, in some sense, measures of the latent variable that they cause.…
Descriptors: Measurement, Structural Equation Models, Statistical Analysis, Causal Models
McCoach, D. Betsy; Kenny, David A. – Measurement: Interdisciplinary Research and Perspectives, 2014
In this commentary, Betsy McCoach and David Kenny state they are in general agreement with Bainter and Bollen (this issue) that causal indicators are not inherently unstable. Herein, they outline several similarities and differences between latent variables with reflective and causal indicators. In their examination of the two models, they find…
Descriptors: Causal Models, Statistical Analysis, Measurement
Widaman, Keith F. – Measurement: Interdisciplinary Research and Perspectives, 2014
Latent variable structural equation modeling has become the analytic method of choice in many domains of research in psychology and allied social sciences. One important aspect of a latent variable model concerns the relations hypothesized to hold between latent variables and their indicators. The most common specification of structural equation…
Descriptors: Structural Equation Models, Predictor Variables, Educational Research, Causal Models

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