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Showing 1 to 15 of 18 results Save | Export
Mai, Yujiao; Zhang, Zhiyong; Wen, Zhonglin – Grantee Submission, 2018
Exploratory structural equation modeling (ESEM) is an approach for analysis of latent variables using exploratory factor analysis to evaluate the measurement model. This study compared ESEM with two dominant approaches for multiple regression with latent variables, structural equation modeling (SEM) and manifest regression analysis (MRA). Main…
Descriptors: Structural Equation Models, Multiple Regression Analysis, Comparative Analysis, Statistical Bias
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Sanders, Elizabeth A.; Dietrich, Elizabeth A. – AERA Online Paper Repository, 2017
The purpose of this paper is to provide guidance in choice of analytic bias reduction methods for educational studies in which the goal is to estimate a treatment effect in the presence of selection bias into treatment. In addition, issues of dimensionality, collinearity, omitted confounders, missing outcomes, and non-independence may be factors…
Descriptors: Statistical Bias, Quasiexperimental Design, Computation, Educational Research
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Watson, Silvana Maria R.; Lopes, João; Oliveira, Célia; Judge, Sharon – Journal for Multicultural Education, 2018
Purpose: The purpose of this descriptive study is to investigate why some elementary children have difficulties mastering addition and subtraction calculation tasks. Design/methodology/approach: The researchers have examined error types in addition and subtraction calculation made by 697 Portuguese students in elementary grades. Each student…
Descriptors: Error Patterns, Foreign Countries, Elementary School Students, Mathematics Instruction
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Tipton, Elizabeth; Pustejovsky, James E. – Journal of Educational and Behavioral Statistics, 2015
Meta-analyses often include studies that report multiple effect sizes based on a common pool of subjects or that report effect sizes from several samples that were treated with very similar research protocols. The inclusion of such studies introduces dependence among the effect size estimates. When the number of studies is large, robust variance…
Descriptors: Meta Analysis, Effect Size, Computation, Robustness (Statistics)
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Harring, Jeffrey R.; Weiss, Brandi A.; Li, Ming – Educational and Psychological Measurement, 2015
Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…
Descriptors: Structural Equation Models, Statistical Analysis, Monte Carlo Methods, Computation
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Nagengast, Benjamin; Brisson, Brigitte M.; Hulleman, Chris S.; Gaspard, Hanna; Häfner, Isabelle; Trautwein, Ulrich – Journal of Experimental Education, 2018
An emerging literature demonstrates that relevance interventions, which ask students to produce written reflections on how what they are learning relates to their lives, improve student learning outcomes. As part of a randomized evaluation of a relevance intervention (N = 1,978 students from 82 ninth-grade classes), we used Complier Average Causal…
Descriptors: Educational Research, Intervention, Relevance (Education), Reflection
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Beaujean, A. Alexander – Practical Assessment, Research & Evaluation, 2014
A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…
Descriptors: Regression (Statistics), Sample Size, Sampling, Monte Carlo Methods
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Ching, Boby Ho-Hong; Nunes, Terezinha – Journal of Educational Psychology, 2017
This longitudinal study examines the relative importance of counting ability, additive reasoning, and working memory in children's mathematical achievement (calculation and story problem solving). In Hong Kong, 115 Chinese children aged 6 years old participated in 2 waves of assessments (T1 = first grade and T2 = second grade). Multiple regression…
Descriptors: Longitudinal Studies, Mathematics Achievement, Short Term Memory, Intelligence Quotient
McLean, Tamika Ann – ProQuest LLC, 2017
The current study investigated college students' content knowledge and cognitive abilities as factors associated with their algebra performance, and examined how combinations of content knowledge and cognitive abilities related to their algebra performance. Specifically, the investigation examined the content knowledge factors of computational…
Descriptors: College Students, Knowledge Level, College Mathematics, Mathematics Skills
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Osborne, Jason W. – Practical Assessment, Research & Evaluation, 2013
Osborne and Waters (2002) focused on checking some of the assumptions of multiple linear regression. In a critique of that paper, Williams, Grajales, and Kurkiewicz correctly clarify that regression models estimated using ordinary least squares require the assumption of normally distributed errors, but not the assumption of normally distributed…
Descriptors: Multiple Regression Analysis, Least Squares Statistics, Computation, Statistical Analysis
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Attout, Lucie; Noël, Marie-Pascale; Majerus, Steve – Developmental Psychology, 2014
Despite numerous studies, the link between verbal working memory (WM) and calculation abilities remains poorly understood. The present longitudinal study focuses specifically on the role of serial order retention capacities, based on recent findings suggesting a link between ordinal processing in verbal WM and numerical processing tasks. Children…
Descriptors: Short Term Memory, Computation, Longitudinal Studies, Cognitive Processes
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Aloe, Ariel M.; Becker, Betsy Jane – Journal of Educational and Behavioral Statistics, 2012
A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…
Descriptors: Meta Analysis, Effect Size, Multiple Regression Analysis, Models
Isenberg, Eric; Hock, Heinrich – Mathematica Policy Research, Inc., 2012
In this report, the authors describe the value-added models used as part of teacher evaluation systems in the District of Columbia Public Schools (DCPS) and in eligible DC charter schools participating in Race to the Top. They estimated (1) teacher effectiveness in DCPS and eligible DC charter schools during the 2011-2012 school year; and (2)…
Descriptors: Value Added Models, Teacher Evaluation, Public Schools, Urban Schools
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Woodcock, Alison; Camfield, Laura; McGregor, J. Allister; Martin, Faith – Social Indicators Research, 2009
The aim of this study was to validate an individualised measure of quality of life (WeDQoL-Goals-Thailand). Three hundred and sixty-nine Thai people completed the WeDQoL by interview. Respondents rated (0-2) the perceived necessity for wellbeing of 51 goals (goal necessity), then rated (0-3) their satisfaction with the same goals (goal…
Descriptors: Marital Status, Place of Residence, Geographic Location, Quality of Life
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Shieh, Gwowen – Psychometrika, 2007
The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all…
Descriptors: Sample Size, Monte Carlo Methods, Multiple Regression Analysis, Statistical Analysis
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