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Suk, Youmi; Kim, Jee-Seon; Kang, Hyunseung – Journal of Educational and Behavioral Statistics, 2021
There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…
Descriptors: Artificial Intelligence, Statistical Analysis, Statistical Inference, Classification
Sun, Shuyan; Pan, Wei – International Journal of Research & Method in Education, 2014
As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Longitudinal Studies, Educational Research
Michaelides, Michalis P.; Haertel, Edward H. – Applied Measurement in Education, 2014
The standard error of equating quantifies the variability in the estimation of an equating function. Because common items for deriving equated scores are treated as fixed, the only source of variability typically considered arises from the estimation of common-item parameters from responses of samples of examinees. Use of alternative, equally…
Descriptors: Equated Scores, Test Items, Sampling, Statistical Inference
Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H. – Educational and Psychological Measurement, 2015
When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically…
Descriptors: Competence, Tests, Evaluation Methods, Adults
Makar, Katie – Australian Mathematics Teacher, 2013
Statistics is one of the most widely used topics for everyday life in the school mathematics curriculum. Unfortunately, the statistics taught in schools focuses on calculations and procedures before students have a chance to see it as a useful and powerful tool. Researchers have found that a dominant view of statistics is as an assortment of tools…
Descriptors: Statistical Inference, Statistics, Prediction, Computation
Konold, Cliff; Madden, Sandra; Pollatsek, Alexander; Pfannkuch, Maxine; Wild, Chris; Ziedins, Ilze; Finzer, William; Horton, Nicholas J.; Kazak, Sibel – Mathematical Thinking and Learning: An International Journal, 2011
A core component of informal statistical inference is the recognition that judgments based on sample data are inherently uncertain. This implies that instruction aimed at developing informal inference needs to foster basic probabilistic reasoning. In this article, we analyze and critique the now-common practice of introducing students to both…
Descriptors: Probability, Statistical Inference, Mathematics Instruction, Mathematics Curriculum
Suleman, Qaiser; Hussain, Ishtiaq – Journal of Education and Practice, 2016
The purpose of the research paper was to investigate the effect of eclectic learning approach on the academic achievement and retention of students in English at elementary level. A sample of forty students of 8th grade randomly selected from Government Boys High School Khurram District Karak was used. It was an experimental study and that's why…
Descriptors: Elementary School Students, Academic Achievement, School Holding Power, Pretests Posttests
Zhang, Zhiyong; Lai, Keke; Lu, Zhenqiu; Tong, Xin – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Despite the widespread popularity of growth curve analysis, few studies have investigated robust growth curve models. In this article, the "t" distribution is applied to model heavy-tailed data and contaminated normal data with outliers for growth curve analysis. The derived robust growth curve models are estimated through Bayesian…
Descriptors: Structural Equation Models, Bayesian Statistics, Statistical Inference, Statistical Distributions
Oranje, Andreas; Freund, David; Lin, Mei-jang; Tang, Yuxin – ETS Research Report Series, 2007
In this paper, a data perturbation method for minimizing the possibility of disclosure of participants' identities on a survey is described in the context of the National Assessment of Educational Progress (NAEP). The method distinguishes itself from most approaches because of the presence of cognitive tasks. Hence, a data edit should have minimal…
Descriptors: Student Surveys, Risk, National Competency Tests, Data Analysis