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Qian, Jiahe – ETS Research Report Series, 2020
The finite population correction (FPC) factor is often used to adjust variance estimators for survey data sampled from a finite population without replacement. As a replicated resampling approach, the jackknife approach is usually implemented without the FPC factor incorporated in its variance estimates. A paradigm is proposed to compare the…
Descriptors: Computation, Sampling, Data, Statistical Analysis
Rickles, Jordan H.; Seltzer, Michael – Journal of Educational and Behavioral Statistics, 2014
When nonrandom treatments occur across sites, within-site matching (WM) is often desirable. This approach, however, can significantly reduce treatment group sample size and exclude substantively important subgroups. To limit these drawbacks, we extend a matching approach developed by Stuart and Rubin to a multisite study. We demonstrate the…
Descriptors: Computation, Probability, Observation, Algebra
Hawera, Ngarewa; Taylor, Merilyn – Mathematics Education Research Group of Australasia, 2015
In Maori medium schools, research that investigates children's mathematical computation with number and connections they might make to mathematical ideas in other strands is limited. This paper seeks to share ideas elicited in a task-based observation and interview with one child about the number ideas she utilises to solve a problem requiring…
Descriptors: Foreign Countries, Mathematics Education, Computation, Probability
Wetzel, Eunike; Xu, Xueli; von Davier, Matthias – Educational and Psychological Measurement, 2015
In large-scale educational surveys, a latent regression model is used to compensate for the shortage of cognitive information. Conventionally, the covariates in the latent regression model are principal components extracted from background data. This operational method has several important disadvantages, such as the handling of missing data and…
Descriptors: Surveys, Regression (Statistics), Models, Research Methodology
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
Dingman, Shannon; Teuscher, Dawn; Newton, Jill A.; Kasmer, Lisa – Elementary School Journal, 2013
This article reports the findings from a comparative analysis that examined several mathematical content strands, reasoning processes, and emphasis on technology in prior K-8 state mathematics standards and the Common Core State Standards for Mathematics (CCSSM). Various methodological tools were utilized to compare and contrast CCSSM with prior…
Descriptors: Academic Standards, Mathematics Instruction, Mathematics Achievement, Course Content
Rickles, Jordan H. – Society for Research on Educational Effectiveness, 2011
This study seeks to demonstrate a method for treatment effect estimation in a multisite observational study where the treatment is highly selective and the assignment mechanism varies across sites. The method is demonstrated by addressing three primary research questions about the effect of 8th grade algebra: (1) For students who take algebra in…
Descriptors: Computation, Probability, Mathematics Achievement, Grade 9
Feldman, Betsy J.; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2012
In longitudinal education studies, assuming that dropout and missing data occur completely at random is often unrealistic. When the probability of dropout depends on covariates and observed responses (called "missing at random" [MAR]), or on values of responses that are missing (called "informative" or "not missing at random" [NMAR]),…
Descriptors: Dropouts, Academic Achievement, Longitudinal Studies, Computation
Rai, Dovan; Gong, Yue; Beck, Joseph E. – International Working Group on Educational Data Mining, 2009
Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better understand student learning there are two problems. First, a model's ability to predict student performance is at best weakly related to the accuracy of any one of its…
Descriptors: Data Analysis, Statistical Analysis, Probability, Models
Oranje, Andreas – ETS Research Report Series, 2006
Confidence intervals are an important tool to indicate uncertainty of estimates and to give an idea of probable values of an estimate if a different sample from the population was drawn or a different sample of measures was used. Standard symmetric confidence intervals for proportion estimates based on a normal approximation can yield bounds…
Descriptors: Computation, Statistical Analysis, National Competency Tests, Comparative Analysis
Novotna, Jarmila, Ed.; Moraova, Hana, Ed.; Kratka, Magdalena, Ed.; Stehlikova, Nad'a, Ed. – International Group for the Psychology of Mathematics Education, 2006
This document contains the second volume of the proceedings of the 30th Annual Conference of the International Group for the Psychology of Mathematics Education. Conference presentations are centered around the theme "Mathematics at the Centre." This volume features 60 research reports by presenters with last names beginning between Abr…
Descriptors: Program Effectiveness, Foreign Countries, Middle Schools, Textbooks