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Stephen Porter – Asia Pacific Education Review, 2024
Instrumental variables is a popular approach for causal inference in education when randomization of treatment is not feasible. Using a first-year college program as a running example, this article reviews the five assumptions that must be met to successfully use instrumental variables to estimate a causal effect with observational data: SUTVA,…
Descriptors: Causal Models, Educational Research, College Freshmen, Observation
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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
Lo, Yun-Jia – ProQuest LLC, 2012
In educational research, a randomized controlled trial is the best design to eliminate potential selection bias in a sample to support valid causal inferences, but it is not always possible in educational research because of financial, ethical, and logistical constrains. One alternative solution is use of the propensity score (PS) methods.…
Descriptors: Educational Research, Probability, Scores, Research Methodology
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McCoach, D. Betsy – Gifted Child Quarterly, 2010
In education, most naturally occurring data are clustered within contexts. Students are clustered within classrooms, classrooms are clustered within schools, and schools are clustered within districts. When people are clustered within naturally occurring organizational units such as schools, classrooms, or districts, the responses of people from…
Descriptors: Regression (Statistics), Causal Models, Academically Gifted, Educational Research
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Sheehan, Janet K.; Han, Tianqi – Mid-Western Educational Researcher, 1996
Contrasts aptitude by treatment interaction (ATI) and hierarchical linear modeling (HLM) methods for making cross-level inferences between individual-level and group-level factors in school effectiveness research. Recommends HLM when intraclass correlations are high. ATI is suitable when intraclass correlations are low, but partitioning the…
Descriptors: Aptitude Treatment Interaction, Causal Models, Context Effect, Educational Research
Quinn, Petrina; Hemmings, Brian – 1999
Drawing on data collected from students attending Australian rural- and urban-based universities, structural modeling was used to test the validity of a model of student persistence and satisfaction in agricultural courses. The model placed personal and environmental factors as predictors of student persistence and satisfaction and was comprised…
Descriptors: Academic Persistence, Agribusiness, Agricultural Education, Agricultural Production
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McPherson, Gary E.; And Others – Journal of Research in Music Education, 1997
Surveys 101 wind instrumentalists to reveal major differences in the pattern of influences leading to the re-creative skill of performing a repertoire of rehearsed music for a formal examination compared to the creative ability of improvising. Uses a path analysis to determine links between the data and theoretical model. (MJP)
Descriptors: Behavioral Objectives, Causal Models, Context Effect, Correlation
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers