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Moretti, Angelo; Whitworth, Adam – Sociological Methods & Research, 2023
Spatial microsimulation encompasses a range of alternative methodological approaches for the small area estimation (SAE) of target population parameters from sample survey data down to target small areas in contexts where such data are desired but not otherwise available. Although widely used, an enduring limitation of spatial microsimulation SAE…
Descriptors: Simulation, Geometric Concepts, Computation, Measurement
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Raykov, Tenko; Marcoulides, George A.; Pusic, Martin – Measurement: Interdisciplinary Research and Perspectives, 2021
An interval estimation procedure is discussed that can be used to evaluate the probability of a particular response for a binary or binary scored item at a pre-specified point along an underlying latent continuum. The item is assumed to: (a) be part of a unidimensional multi-component measuring instrument that may contain also polytomous items,…
Descriptors: Item Response Theory, Computation, Probability, Test Items
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Huang, Hening – Research Synthesis Methods, 2023
Many statistical methods (estimators) are available for estimating the consensus value (or average effect) and heterogeneity variance in interlaboratory studies or meta-analyses. These estimators are all valid because they are developed from or supported by certain statistical principles. However, no estimator can be perfect and must have error or…
Descriptors: Statistical Analysis, Computation, Measurement Techniques, Meta Analysis
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Arribas, E.; Escobar, I.; Ramirez-Vazquez, R. – International Journal of Mathematical Education in Science and Technology, 2021
In the article 'How Long Is My Toilet Roll--A Simple Exercise in Mathematical Modelling' several models of increasing complexity are introduced and solved to calculate indirectly the length of paper on a toilet-roll. All these results are presented without errors. The authors of this comment believe the error analysis of measurements made in a…
Descriptors: Mathematics Instruction, Teaching Methods, Mathematical Models, Computation
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Cross, Rod – Physics Teacher, 2021
A common procedure when conducting physics experiments is to repeat a measurement several times to calculate the mean and standard deviation. That might be the only instruction we give to students as a means to minimize random errors. However, that technique does not guarantee that the answer will be correct. It might give the same wrong answer…
Descriptors: Physics, Science Experiments, Computation, Error of Measurement
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Erik-Jan van Kesteren; Daniel L. Oberski – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Structural equation modeling (SEM) is being applied to ever more complex data types and questions, often requiring extensions such as regularization or novel fitting functions. To extend SEM, researchers currently need to completely reformulate SEM and its optimization algorithm -- a challenging and time-consuming task. In this paper, we introduce…
Descriptors: Structural Equation Models, Computation, Graphs, Algorithms
Eli Ben-Michael; Avi Feller; Erin Hartman – Grantee Submission, 2023
In the November 2016 U.S. presidential election, many state level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading explanation for this polling miss is that the precipitous decline in traditional polling response rates led to greater reliance on statistical methods to adjust for the…
Descriptors: Public Opinion, National Surveys, Elections, Political Campaigns
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van der Linden, Wim J.; Ren, Hao – Journal of Educational and Behavioral Statistics, 2020
The Bayesian way of accounting for the effects of error in the ability and item parameters in adaptive testing is through the joint posterior distribution of all parameters. An optimized Markov chain Monte Carlo algorithm for adaptive testing is presented, which samples this distribution in real time to score the examinee's ability and optimally…
Descriptors: Bayesian Statistics, Adaptive Testing, Error of Measurement, Markov Processes
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Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2019
Longitudinal data analysis has received widespread interest throughout educational, behavioral, and social science research, with latent growth curve modeling currently being one of the most popular methods of analysis. Despite the popularity of latent growth curve modeling, limited attention has been directed toward understanding the issues of…
Descriptors: Reliability, Longitudinal Studies, Growth Models, Structural Equation Models
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Leite, Walter L.; Aydin, Burak; Gurel, Sungur – Journal of Experimental Education, 2019
This Monte Carlo simulation study compares methods to estimate the effects of programs with multiple versions when assignment of individuals to program version is not random. These methods use generalized propensity scores, which are predicted probabilities of receiving a particular level of the treatment conditional on covariates, to remove…
Descriptors: Probability, Weighted Scores, Monte Carlo Methods, Statistical Bias
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Vegetabile, Brian G.; Stout-Oswald, Stephanie A.; Davis, Elysia Poggi; Baram, Tallie Z.; Stern, Hal S. – Journal of Educational and Behavioral Statistics, 2019
Predictability of behavior is an important characteristic in many fields including biology, medicine, marketing, and education. When a sequence of actions performed by an individual can be modeled as a stationary time-homogeneous Markov chain the predictability of the individual's behavior can be quantified by the entropy rate of the process. This…
Descriptors: Markov Processes, Prediction, Behavior, Computation
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Walters, Glenn D. – International Journal of Social Research Methodology, 2019
Identifying mediators in variable chains as part of a causal mediation analysis can shed light on issues of causation, assessment, and intervention. However, coefficients and effect sizes in a causal mediation analysis are nearly always small. This can lead those less familiar with the approach to reject the results of causal mediation analysis.…
Descriptors: Effect Size, Statistical Analysis, Sampling, Statistical Inference
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Torche, Florencia; Corvalan, Alejandro – Sociological Methods & Research, 2018
This article distinguishes three measures of intergenerational economic mobility that emerge when the population is divided into groups: overall individual mobility, within-group mobility, and between-group mobility. We clarify their properties and the relationship between them. We then evaluate Clark's use of surname between-group persistence as…
Descriptors: Social Mobility, Computation, Generational Differences, Persistence
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Wang, Jianjun; Ma, Xin – Athens Journal of Education, 2019
This rejoinder keeps the original focus on statistical computing pertaining to the correlation of student achievement between mathematics and science from the Trend in Mathematics and Science Study (TIMSS). Albeit the availability of student performance data in TIMSS and the emphasis of the inter-subject connection in the Next Generation Science…
Descriptors: Scores, Correlation, Achievement Tests, Elementary Secondary Education
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McCoach, D. Betsy; Rifenbark, Graham G.; Newton, Sarah D.; Li, Xiaoran; Kooken, Janice; Yomtov, Dani; Gambino, Anthony J.; Bellara, Aarti – Journal of Educational and Behavioral Statistics, 2018
This study compared five common multilevel software packages via Monte Carlo simulation: HLM 7, M"plus" 7.4, R (lme4 V1.1-12), Stata 14.1, and SAS 9.4 to determine how the programs differ in estimation accuracy and speed, as well as convergence, when modeling multiple randomly varying slopes of different magnitudes. Simulated data…
Descriptors: Hierarchical Linear Modeling, Computer Software, Comparative Analysis, Monte Carlo Methods
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