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Yongyun Shin; Stephen W. Raudenbush – Grantee Submission, 2023
We consider two-level models where a continuous response R and continuous covariates C are assumed missing at random. Inferences based on maximum likelihood or Bayes are routinely made by estimating their joint normal distribution from observed data R[subscript obs] and C[subscript obs]. However, if the model for R given C includes random…
Descriptors: Maximum Likelihood Statistics, Hierarchical Linear Modeling, Error of Measurement, Statistical Distributions
Vicki Steinle; Kaye Stacey; Beth Price – Mathematics Education Research Group of Australasia, 2024
This paper provides evidence that a short, fully online, well-constructed diagnostic test based on research literature can give teachers information about their students' thinking and strategies that is sufficiently accurate to use for formative assessment purposes. The example is a test for students beginning to learn to solve equations. The main…
Descriptors: Foreign Countries, Secondary School Mathematics, Secondary School Students, Secondary School Teachers
Brown, Reagan D.; Oswald, Frederick L.; Converse, Patrick D. – Practical Assessment, Research & Evaluation, 2017
Operational validities are important to personnel selection research because they estimate how well a predictor in practical use correlates with a criterion construct, if the criterion measure were purged of measurement error variance. Because range restriction on a predictor or predictor composite creates incidental range restriction on the…
Descriptors: Computation, Validity, Personnel Selection, Predictor Variables
Trafimow, David – Educational and Psychological Measurement, 2018
Because error variance alternatively can be considered to be the sum of systematic variance associated with unknown variables and randomness, a tripartite assumption is proposed that total variance in the dependent variable can be partitioned into three variance components. These are variance in the dependent variable that is explained by the…
Descriptors: Statistical Analysis, Correlation, Experiments, Effect Size
Schoeneberger, Jason A. – Journal of Experimental Education, 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Descriptors: Sample Size, Models, Computation, Predictor Variables
Goldhaber, Dan; Long, Mark C.; Person, Ann E.; Rooklyn, Jordan – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2017
We investigate factors influencing student sign-ups for Washington State's College Bound Scholarship (CBS) program. We find a substantial share of eligible middle school students fail to sign the CBS, forgoing college financial aid. Student characteristics associated with signing the scholarship parallel characteristics of low-income students who…
Descriptors: Predictor Variables, Middle School Students, College Preparation, Mixed Methods Research
Powell, Sarah R.; Fuchs, Lynn S. – Learning Disabilities Research & Practice, 2014
According to national mathematics standards, algebra instruction should begin at kindergarten and continue through elementary school. Most often, teachers address algebra in the elementary grades with problems related to solving equations or understanding functions. With 789 second-grade students, we administered: (1) measures of calculations and…
Descriptors: Algebra, Mathematics Instruction, Grade 2, Elementary School Students
Haberman, Shelby J. – ETS Research Report Series, 2013
A general program for item-response analysis is described that uses the stabilized Newton-Raphson algorithm. This program is written to be compliant with Fortran 2003 standards and is sufficiently general to handle independent variables, multidimensional ability parameters, and matrix sampling. The ability variables may be either polytomous or…
Descriptors: Predictor Variables, Mathematics, Item Response Theory, Probability
Beauducel, Andre – Applied Psychological Measurement, 2013
The problem of factor score indeterminacy implies that the factor and the error scores cannot be completely disentangled in the factor model. It is therefore proposed to compute Harman's factor score predictor that contains an additive combination of factor and error variance. This additive combination is discussed in the framework of classical…
Descriptors: Factor Analysis, Predictor Variables, Reliability, Error of Measurement
Hornback, Joseph E. – ProQuest LLC, 2013
This dissertation addresses two research questions: 1. Do states misrepresent their progress on their own state assessments? 2. If states do distort their progress, are their predictors to suggest why this distortion occurs? The first research question requires that distortion be defined. For the purposes of this dissertation I calculated the…
Descriptors: Standardized Tests, State Standards, Computation, Equations (Mathematics)
Jongerling, Joran; Hamaker, Ellen L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article shows that the mean and covariance structure of the predetermined autoregressive latent trajectory (ALT) model are very flexible. As a result, the shape of the modeled growth curve can be quite different from what one might expect at first glance. This is illustrated with several numerical examples that show that, for example, a…
Descriptors: Statistics, Structural Equation Models, Scores, Predictor Variables
Kelava, Augustin; Werner, Christina S.; Schermelleh-Engel, Karin; Moosbrugger, Helfried; Zapf, Dieter; Ma, Yue; Cham, Heining; Aiken, Leona S.; West, Stephen G. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Interaction and quadratic effects in latent variable models have to date only rarely been tested in practice. Traditional product indicator approaches need to create product indicators (e.g., x[superscript 2] [subscript 1], x[subscript 1]x[subscript 4]) to serve as indicators of each nonlinear latent construct. These approaches require the use of…
Descriptors: Simulation, Computation, Evaluation, Predictor Variables
Choi, Kilchan; Seltzer, Michael – Journal of Educational and Behavioral Statistics, 2010
In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a period of substantive interest relate to differences in subsequent change. In this article, the authors present a fully Bayesian approach to estimating three-level Hierarchical Models in which latent…
Descriptors: Simulation, Computation, Models, Bayesian Statistics
Jance, Marsha; Thomopoulos, Nick – American Journal of Business Education, 2009
The extreme interval values and statistics (expected value, median, mode, standard deviation, and coefficient of variation) for the smallest (min) and largest (max) values of exponentially distributed variables with parameter ? = 1 are examined for different observation (sample) sizes. An extreme interval value g[subscript a] is defined as a…
Descriptors: Intervals, Statistics, Predictor Variables, Sample Size
Schluchter, Mark D. – Multivariate Behavioral Research, 2008
In behavioral research, interest is often in examining the degree to which the effect of an independent variable X on an outcome Y is mediated by an intermediary or mediator variable M. This article illustrates how generalized estimating equations (GEE) modeling can be used to estimate the indirect or mediated effect, defined as the amount by…
Descriptors: Intervals, Predictor Variables, Equations (Mathematics), Computation
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