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Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
Ravand, Hamdollah; Baghaei, Purya – Practical Assessment, Research & Evaluation, 2016
Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…
Descriptors: Least Squares Statistics, Structural Equation Models, Nonparametric Statistics, Sample Size
Savi Çakar, Firdevs; Tagay, Özlem – Educational Sciences: Theory and Practice, 2017
This research is a descriptive study based on the testing of a structural model developed by considering the effects of perceived social support and subjective well-being on adolescents' risky behaviors, and the possible mediating role of self-esteem. Participants consisted of 676 high school students attending formal education institutions,…
Descriptors: Self Esteem, Social Support Groups, Risk, Health Behavior
Cho, Jaehee; Lee, H. Erin; Quinlan, Margaret – Journal of American College Health, 2017
Objective: Based on the technology acceptance model (TAM), we explored the nationally-bounded roles of four predictors (subjective norms, entertainment, recordability, and networkability) in determining the TAM variables of perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI) to use diet/fitness apps on…
Descriptors: Cross Cultural Studies, Telecommunications, Handheld Devices, College Students
Peer reviewedRindskopf, David – Psychometrika, 1984
Using LISREL, the only types of constraints allowed are fixing parameters at a constant value and constraining parameters to be equal. In this paper, two new concepts ("phantom" and "imaginary" latent variables) are introduced which allow fairly general equality and inequality constraints on factor loadings and structural model…
Descriptors: Computer Software, Factor Analysis, Mathematical Models, Path Analysis

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