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Waller, Niels G. – Journal of Educational and Behavioral Statistics, 2023
Although many textbooks on multivariate statistics discuss the common factor analysis model, few of these books mention the problem of factor score indeterminacy (FSI). Thus, many students and contemporary researchers are unaware of an important fact. Namely, for any common factor model with known (or estimated) model parameters, infinite sets of…
Descriptors: Statistics Education, Multivariate Analysis, Factor Analysis, Factor Structure
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Iqbal, Farhan; Iqbal, Farah; Humayun, Ghazal Khawaja – Psychology in the Schools, 2023
Despite several theoretical, structural, and statistical issues reported against Five Facets Mindfulness Questionnaire (FFMQ), most studies in the educational sector of Pakistan use it without analyzing its factor structure. Since culture might change the structure, this first systematic study filled the gap and explored the factor structure of…
Descriptors: Questionnaires, Metacognition, Personality Measures, Foreign Countries
McNeish, Daniel; Bauer, Daniel J. – Grantee Submission, 2020
Deciding which random effects to retain is a central decision in mixed effect models. Recent recommendations advise a maximal structure whereby all theoretically relevant random effects are retained. Nonetheless, including many random effects often leads to nonpositive definiteness. A typical remedy is to simplify the random effect structure by…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Factor Analysis, Matrices
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Guasch, Marc; Haro, Juan; Boada, Roger – Psicologica: International Journal of Methodology and Experimental Psychology, 2017
With the increasing refinement of language processing models and the new discoveries about which variables can modulate these processes, stimuli selection for experiments with a factorial design is becoming a tough task. Selecting sets of words that differ in one variable, while matching these same words into dozens of other confounding variables…
Descriptors: Factor Analysis, Language Processing, Design, Cluster Grouping
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Schulz, Andreas – Mathematical Thinking and Learning: An International Journal, 2018
Theoretical analysis of whole number-based calculation strategies and digit-based algorithms for multi-digit multiplication and division reveals that strategy use includes two kinds of reasoning: reasoning about the relations between numbers and reasoning about the relations between operations. In contrast, algorithms aim to reduce the necessary…
Descriptors: Computation, Mathematics Instruction, Multiplication, Arithmetic
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Stewart, Christie; Root, Melissa M.; Koriakin, Taylor; Choi, Dowon; Luria, Sarah R.; Bray, Melissa A.; Sassu, Kari; Maykel, Cheryl; O'Rourke, Patricia; Courville, Troy – Journal of Psychoeducational Assessment, 2017
This study investigated developmental gender differences in mathematics achievement, using the child and adolescent portion (ages 6-19 years) of the Kaufman Test of Educational Achievement-Third Edition (KTEA-3). Participants were divided into two age categories: 6 to 11 and 12 to 19. Error categories within the Math Concepts & Applications…
Descriptors: Gender Differences, Error Patterns, Mathematics Tests, Achievement Tests
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Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman – Psychological Methods, 2013
In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…
Descriptors: Structural Equation Models, Multivariate Analysis, Computation, Factor Analysis
Grochowalski, Joseph H. – ProQuest LLC, 2015
Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…
Descriptors: Computation, Psychometrics, Profiles, Scores
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Wetzel, Eunike; Xu, Xueli; von Davier, Matthias – Educational and Psychological Measurement, 2015
In large-scale educational surveys, a latent regression model is used to compensate for the shortage of cognitive information. Conventionally, the covariates in the latent regression model are principal components extracted from background data. This operational method has several important disadvantages, such as the handling of missing data and…
Descriptors: Surveys, Regression (Statistics), Models, Research Methodology
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Jia, Fan; Moore, E. Whitney G.; Kinai, Richard; Crowe, Kelly S.; Schoemann, Alexander M.; Little, Todd D. – International Journal of Behavioral Development, 2014
Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This article explores this question by using…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
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Song, Hairong; Ferrer, Emilio – Multivariate Behavioral Research, 2012
Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…
Descriptors: Bayesian Statistics, Computation, Factor Analysis, Models
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Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2012
These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution…
Descriptors: Test Results, Statistical Analysis, Multivariate Analysis, Evaluation Methods
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Bennett, Kevin J.; Probst, Janice C.; Vyavaharkar, Medha; Glover, Saundra H. – Journal of Rural Health, 2012
Purpose: We estimated the 30-day readmission rate of Medicare beneficiaries with diabetes, across levels of rurality. Methods: We merged the 2005 Medicare Chronic Conditions 5% sample data with the 2007 Area Resource File. The study population was delimited to those with diabetes and at least 1 hospitalization in the year. Unadjusted readmission…
Descriptors: Hospitals, Diabetes, Patients, Rural Areas
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Reckase, Mark D.; Xu, Jing-Ru – Educational and Psychological Measurement, 2015
How to compute and report subscores for a test that was originally designed for reporting scores on a unidimensional scale has been a topic of interest in recent years. In the research reported here, we describe an application of multidimensional item response theory to identify a subscore structure in a test designed for reporting results using a…
Descriptors: English, Language Skills, English Language Learners, Scores
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Blozis, Shelley A. – Psychological Methods, 2004
This article considers a structured latent curve model for multiple repeated measures. In a structured latent curve model, a smooth nonlinear function characterizes the mean response. A first-order Taylor polynomial taken with regard to the mean function defines elements of a restricted factor matrix that may include parameters that enter…
Descriptors: Factor Analysis, Computation, Item Response Theory, Multivariate Analysis