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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
Oranje, Andreas; Kolstad, Andrew – Journal of Educational and Behavioral Statistics, 2019
The design and psychometric methodology of the National Assessment of Educational Progress (NAEP) is constantly evolving to meet the changing interests and demands stemming from a rapidly shifting educational landscape. NAEP has been built on strong research foundations that include conducting extensive evaluations and comparisons before new…
Descriptors: National Competency Tests, Psychometrics, Statistical Analysis, Computation
Reardon, Sean F.; Shear, Benjamin R.; Castellano, Katherine E.; Ho, Andrew D. – Journal of Educational and Behavioral Statistics, 2017
Test score distributions of schools or demographic groups are often summarized by frequencies of students scoring in a small number of ordered proficiency categories. We show that heteroskedastic ordered probit (HETOP) models can be used to estimate means and standard deviations of multiple groups' test score distributions from such data. Because…
Descriptors: Scores, Statistical Analysis, Models, Computation
Jan, Show-Li; Shieh, Gwowen – Journal of Educational and Behavioral Statistics, 2014
The analysis of variance (ANOVA) is one of the most frequently used statistical analyses in practical applications. Accordingly, the single and multiple comparison procedures are frequently applied to assess the differences among mean effects. However, the underlying assumption of homogeneous variances may not always be tenable. This study…
Descriptors: Sample Size, Statistical Analysis, Computation, Probability
Ost, Ben; Gangopadhyaya, Anuj; Schiman, Jeffrey C. – Education Economics, 2017
Studies using tests scores as the dependent variable often report point estimates in student standard deviation units. We note that a standard deviation is not a standard unit of measurement since the distribution of test scores can vary across contexts. As such, researchers should be cautious when interpreting differences in the numerical size of…
Descriptors: Scores, Statistical Analysis, Measurement, Computation
Bohrnstedt, G.; Kitmitto, S.; Ogut, B.; Sherman, D.; Chan, D. – National Center for Education Statistics, 2015
The School Composition and the Black-White Achievement Gap study was undertaken by the National Center for Education Statistics to present both descriptive and associative information on the relationships among the percentage of students in a school who were Black (referred to as "Black student density" or "density"), the…
Descriptors: School Demography, Racial Composition, Achievement Gap, African American Students
Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan – Educational Testing Service, 2011
Estimation of parameters of random effects models from samples collected via complex multistage designs is considered. One way to reduce estimation bias due to unequal probabilities of selection is to incorporate sampling weights. Many researchers have been proposed various weighting methods (Korn, & Graubard, 2003; Pfeffermann, Skinner,…
Descriptors: Computation, Statistical Bias, Sampling, Statistical Analysis
Hsieh, Chueh-an; Xu, Xueli; von Davier, Matthias – Educational Testing Service, 2010
This paper presents an application of a jackknifing approach to variance estimation of ability inferences for groups of students, using a multidimensional discrete model for item response data. The data utilized to demonstrate the approach come from the National Assessment of Educational Progress (NAEP). In contrast to the operational approach…
Descriptors: National Competency Tests, Reading Tests, Grade 4, Computation
Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan – Journal of Educational and Behavioral Statistics, 2011
In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…
Descriptors: Sampling, Computation, Statistical Bias, Statistical Analysis
Braun, Henry; Zhang, Jinming; Vezzu, Sailesh – ETS Research Report Series, 2008
At present, although the percentages of students with disabilities (SDs) and/or students who are English language learners (ELL) excluded from a NAEP administration are reported, no statistical adjustment is made for these excluded students in the calculation of NAEP results. However, the exclusion rates for both SD and ELL students vary…
Descriptors: Research Methodology, Computation, Disabilities, English Language Learners
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
Oranje, Andreas – ETS Research Report Series, 2006
A multitude of methods has been proposed to estimate the sampling variance of ratio estimates in complex samples (Wolter, 1985). Hansen and Tepping (1985) studied some of those variance estimators and found that a high coefficient of variation (CV) of the denominator of a ratio estimate is indicative of a biased estimate of the standard error of a…
Descriptors: Statistical Analysis, Computation, Sampling, Statistical Bias

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