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Varas, Inés M.; González, Jorge; Quintana, Fernando A. – Journal of Educational and Behavioral Statistics, 2020
Equating is a family of statistical models and methods used to adjust scores on different test forms so that they can be comparable and used interchangeably. Equated scores are obtained estimating the equating transformation function, which maps the scores on the scale of one test form into their equivalents on the scale of other one. All the…
Descriptors: Bayesian Statistics, Nonparametric Statistics, Equated Scores, Statistical Analysis
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Doval, Eduardo; Delicado, Pedro – Journal of Educational and Behavioral Statistics, 2020
We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. ARPs…
Descriptors: Response Style (Tests), Data Analysis, Identification, Classification
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Wang, Yu; Chiu, Chia-Yi; Köhn, Hans Friedrich – Journal of Educational and Behavioral Statistics, 2023
The multiple-choice (MC) item format has been widely used in educational assessments across diverse content domains. MC items purportedly allow for collecting richer diagnostic information. The effectiveness and economy of administering MC items may have further contributed to their popularity not just in educational assessment. The MC item format…
Descriptors: Multiple Choice Tests, Nonparametric Statistics, Test Format, Educational Assessment
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Keller, Bryan – Journal of Educational and Behavioral Statistics, 2020
Widespread availability of rich educational databases facilitates the use of conditioning strategies to estimate causal effects with nonexperimental data. With dozens, hundreds, or more potential predictors, variable selection can be useful for practical reasons related to communicating results and for statistical reasons related to improving the…
Descriptors: Nonparametric Statistics, Computation, Testing, Causal Models
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Liu, Yang; Wang, Xiaojing – Journal of Educational and Behavioral Statistics, 2020
Parametric methods, such as autoregressive models or latent growth modeling, are usually inflexible to model the dependence and nonlinear effects among the changes of latent traits whenever the time gap is irregular and the recorded time points are individually varying. Often in practice, the growth trend of latent traits is subject to certain…
Descriptors: Bayesian Statistics, Nonparametric Statistics, Regression (Statistics), Item Response Theory
Thoemmes, Felix; Liao, Wang; Jin, Ze – Journal of Educational and Behavioral Statistics, 2017
This article describes the analysis of regression-discontinuity designs (RDDs) using the R packages rdd, rdrobust, and rddtools. We discuss similarities and differences between these packages and provide directions on how to use them effectively. We use real data from the Carolina Abecedarian Project to show how an analysis of an RDD can be…
Descriptors: Regression (Statistics), Research Design, Robustness (Statistics), Computer Software
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Mealli, Fabrizia; Pacini, Barbara; Stanghellini, Elena – Journal of Educational and Behavioral Statistics, 2016
Unless strong assumptions are made, nonparametric identification of principal causal effects can only be partial and bounds (or sets) for the causal effects are established. In the presence of a secondary outcome, recent results exist to sharpen the bounds that exploit conditional independence assumptions. More general results, though not embedded…
Descriptors: Graphs, Nonparametric Statistics, Causal Models, Statistical Analysis
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Berger, Moritz; Tutz, Gerhard – Journal of Educational and Behavioral Statistics, 2016
Detection of differential item functioning (DIF) by use of the logistic modeling approach has a long tradition. One big advantage of the approach is that it can be used to investigate nonuniform (NUDIF) as well as uniform DIF (UDIF). The classical approach allows one to detect DIF by distinguishing between multiple groups. We propose an…
Descriptors: Test Bias, Regression (Statistics), Nonparametric Statistics, Statistical Analysis
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Bartolucci, Francesco; Pennoni, Fulvia; Vittadini, Giorgio – Journal of Educational and Behavioral Statistics, 2016
We extend to the longitudinal setting a latent class approach that was recently introduced by Lanza, Coffman, and Xu to estimate the causal effect of a treatment. The proposed approach enables an evaluation of multiple treatment effects on subpopulations of individuals from a dynamic perspective, as it relies on a latent Markov (LM) model that is…
Descriptors: Causal Models, Markov Processes, Longitudinal Studies, Probability