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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
Li, Tiandong – ProQuest LLC, 2012
In large-scale assessments, such as the National Assessment of Educational Progress (NAEP), plausible values based on Multiple Imputations (MI) have been used to estimate population characteristics for latent constructs under complex sample designs. Mislevy (1991) derived a closed-form analytic solution for a fixed-effect model in creating…
Descriptors: National Competency Tests, Statistical Analysis, Educational Assessment, Test Theory
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
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
Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2013
The 2012 edition of the "Digest of Education Statistics" is the 48th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: School Statistics, Definitions, Tables (Data), Longitudinal Studies
Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2012
The 2011 edition of the "Digest of Education Statistics" is the 47th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: Educational Research, Data Collection, Data Analysis, Error Patterns
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
Kalsbeek, William D.; And Others – 1975
The National Assessment of Educational Progress; Second Science Assessment No-Show Study assessed the magnitude and causation of nonresponse biases. A No-Show is defined as an individual who was selected as a sample respondent but failed to be present for regular assessment of the 17-year-old group. The procedure whereby a sample of eligible…
Descriptors: Educational Assessment, High Schools, Mathematical Models, Performance Factors
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
Beaton, Albert E. – 1987
In 1982, the Educational Testing Service (ETS) proposed to implement a new, complex design for the National Assessment of Educational Progress (NAEP). The major features of this design are described in "A New Design for a New Era" (Messick, Beaton, and Lord, 1983). The purpose of this document is to describe the actual implementation of…
Descriptors: Academic Achievement, Data Analysis, Data Collection, Data Interpretation
Probing a Model of Educational Productivity in High School Science with National Assessment Samples.

Walberg, Herbert J.; And Others – Journal of Educational Psychology, 1982
A psychological theory of educational productivity is tested, and the usefulness of the National Assessment of Educational Progress data for secondary analyses for policy purposes is explored. Class as a social psychological factor and the didactic quality of instruction appear to be the only unequivocal and potentially manipulable causes of…
Descriptors: Academic Achievement, High Schools, Models, Productivity
Chromy, James R. – 2003
This study addressed statistical techniques that might ameliorate some of the sampling problems currently facing states with small populations participating in State National Assessment of Educational Progress (NAEP) assessments. The study explored how the application of finite population correction factors to the between-school component of…
Descriptors: Elementary Secondary Education, National Surveys, Sample Size, Sampling
Folsom, Ralph E.; Williams, Rick L. – 1982
The National Assessment of Educational Progress (NAEP), like most large national surveys, employs a complex stratified multistage unequal probability sample. The design provides a rigorous justification for extending survey results to the entire U.S. target population. Developments in the analysis of data from complex surveys which provide a…
Descriptors: Cluster Analysis, Educational Assessment, Hypothesis Testing, Mathematics Achievement

Johnson, Eugene G. – Journal of Educational Statistics, 1989
The effects of certain characteristics (e.g., sample design) of National Assessment of Educational Progress (NAEP) data on statistical analysis techniques are considered. Ignoring special features of NAEP data and proceeding with a standard analysis can produce inferences that underestimate the true variability and overestimate the true degrees of…
Descriptors: Data Collection, Educational Assessment, Elementary Secondary Education, Estimation (Mathematics)
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