Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 9 |
Descriptor
Sampling | 10 |
Statistical Analysis | 10 |
Computation | 7 |
Item Response Theory | 4 |
National Competency Tests | 4 |
Comparative Analysis | 3 |
Error of Measurement | 3 |
Grade 8 | 3 |
Probability | 3 |
Equated Scores | 2 |
Grade 4 | 2 |
More ▼ |
Source
ETS Research Report Series | 10 |
Author
Qian, Jiahe | 4 |
Oranje, Andreas | 2 |
von Davier, Alina A. | 2 |
Braun, Henry | 1 |
Dorans, Neil | 1 |
Dorans, Neil J. | 1 |
Haberman, Shelby J. | 1 |
Jiang, Yanming | 1 |
Lee, Yi-Hsuan | 1 |
Livingston, Samuel A. | 1 |
Manalo, Jonathan R. | 1 |
More ▼ |
Publication Type
Journal Articles | 10 |
Reports - Research | 10 |
Education Level
Elementary Education | 4 |
Grade 8 | 3 |
Junior High Schools | 3 |
Middle Schools | 3 |
Secondary Education | 3 |
Grade 4 | 2 |
Higher Education | 2 |
Intermediate Grades | 2 |
Postsecondary Education | 2 |
Audience
Location
United States | 1 |
Laws, Policies, & Programs
Assessments and Surveys
National Assessment of… | 4 |
What Works Clearinghouse Rating
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
Qian, Jiahe; Jiang, Yanming; von Davier, Alina A. – ETS Research Report Series, 2013
Several factors could cause variability in item response theory (IRT) linking and equating procedures, such as the variability across examinee samples and/or test items, seasonality, regional differences, native language diversity, gender, and other demographic variables. Hence, the following question arises: Is it possible to select optimal…
Descriptors: Item Response Theory, Test Items, Sampling, True Scores
Haberman, Shelby J.; Lee, Yi-Hsuan; Qian, Jiahe – ETS Research Report Series, 2009
Grouped jackknifing may be used to evaluate the stability of equating procedures with respect to sampling error and with respect to changes in anchor selection. Properties of grouped jackknifing are reviewed for simple-random and stratified sampling, and its use is described for comparisons of anchor sets. Application is made to examples of item…
Descriptors: Equated Scores, Accuracy, Sampling, Statistical Analysis
von Davier, Alina A.; Manalo, Jonathan R.; Rijmen, Frank – ETS Research Report Series, 2008
The standard errors of the 2 most widely used population-invariance measures of equating functions, root mean square difference (RMSD) and root expected mean square difference (REMSD), are not derived for common equating methods such as linear equating. Consequently, it is unknown how much noise is contained in these estimates. This paper…
Descriptors: Equated Scores, Error of Measurement, Statistical Analysis, Sampling
Yu, Lei; Moses, Tim; Puhan, Gautam; Dorans, Neil – ETS Research Report Series, 2008
All differential item functioning (DIF) methods require at least a moderate sample size for effective DIF detection. Samples that are less than 200 pose a challenge for DIF analysis. Smoothing can improve upon the estimation of the population distribution by preserving major features of an observed frequency distribution while eliminating the…
Descriptors: Test Bias, Item Response Theory, Sample Size, Evaluation Criteria
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
Livingston, Samuel A.; Dorans, Neil J. – ETS Research Report Series, 2004
This paper describes an approach to item analysis that is based on the estimation of a set of response curves for each item. The response curves show, at a glance, the difficulty and the discriminating power of the item and the popularity of each distractor, at any level of the criterion variable (e.g., total score). The curves are estimated by…
Descriptors: Item Analysis, Computation, Difficulty Level, Test Items
Qian, Jiahe – ETS Research Report Series, 2006
Weighting and variance estimation are two statistical issues involved in survey data analysis for large-scale assessment programs such as the Higher Education Information and Communication Technology (ICT) Literacy Assessment. Because survey data are always acquired by probability sampling, to draw unbiased or almost unbiased inferences for the…
Descriptors: Weighted Scores, Sampling, Statistical Analysis, Higher Education