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Yang, Ji Seung; Cai, Li – Journal of Educational and Behavioral Statistics, 2014
The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM). Results indicate that the MH-RM algorithm can produce estimates and standard…
Descriptors: Computation, Hierarchical Linear Modeling, Mathematics, Context Effect
Yang, Ji Seung; Cai, Li – Grantee Submission, 2014
The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM algorithm can…
Descriptors: Computation, Hierarchical Linear Modeling, Mathematics, Context Effect
Phillips, Gary W. – Applied Measurement in Education, 2015
This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…
Descriptors: State Programs, Sampling, Research Design, Error of Measurement
Haberman, Shelby J. – Educational Testing Service, 2010
Sampling errors limit the accuracy with which forms can be linked. Limitations on accuracy are especially important in testing programs in which a very large number of forms are employed. Standard inequalities in mathematical statistics may be used to establish lower bounds on the achievable inking accuracy. To illustrate results, a variety of…
Descriptors: Testing Programs, Equated Scores, Sampling, Accuracy
Doorey, Nancy A. – Council of Chief State School Officers, 2011
The work reported in this paper reflects a collaborative effort of many individuals representing multiple organizations. It began during a session at the October 2008 meeting of TILSA when a representative of a member state asked the group if any of their programs had experienced unexpected fluctuations in the annual state assessment scores, and…
Descriptors: Testing, Sampling, Expertise, Testing Programs
Olsen, Robert B.; Unlu, Fatih; Price, Cristofer; Jaciw, Andrew P. – National Center for Education Evaluation and Regional Assistance, 2011
This report examines the differences in impact estimates and standard errors that arise when these are derived using state achievement tests only (as pre-tests and post-tests), study-administered tests only, or some combination of state- and study-administered tests. State tests may yield different evaluation results relative to a test that is…
Descriptors: Achievement Tests, Standardized Tests, State Standards, Reading Achievement
Wu, Margaret – Educational Measurement: Issues and Practice, 2010
In large-scale assessments, such as state-wide testing programs, national sample-based assessments, and international comparative studies, there are many steps involved in the measurement and reporting of student achievement. There are always sources of inaccuracies in each of the steps. It is of interest to identify the source and magnitude of…
Descriptors: Testing Programs, Educational Assessment, Measures (Individuals), Program Effectiveness
Kolen, Michael J. – 1984
Large sample standard errors for the Tucker method of linear equating under the common item nonrandom groups design are derived under normality assumptions as well as under less restrictive assumptions. Standard errors of Tucker equating are estimated using the bootstrap method described by Efron. The results from different methods are compared…
Descriptors: Certification, Comparative Analysis, Equated Scores, Error of Measurement
Williams, Rick L.; And Others – 1981
The National Assessment of Educational Progress in-school sampling design is a three-stage stratified design. Stratification variables include region, size of community and socioeconomic status. The three levels of sample selection are Primary Sampling Units (PSUs), schools and students. In general, two and sometimes three PSUs are selected from…
Descriptors: Educational Assessment, Elementary Secondary Education, Error of Measurement, National Competency Tests
Searls, Donald T., Ed. – 1983
The purpose of this paper is to provide an overview of the analysis of data collected by the National Assessment of Educational Progress (NAEP). In simplest terms, the analysis can be characterized as establishing baseline estimates of the percentages of young Americans possessing certain skills, knowledge, understandings, and attitudes and…
Descriptors: Data Analysis, Data Collection, Databases, Educational Assessment
Folsom, Ralph E., Jr. – 1977
Beginning with the planning stages of the National Assessment of Educational Progress (NAEP), careful attention has been given to the design of efficient probability sampling methods for the selection of class-age respondents and the assignment of test packages. With these methods, it is possible for NAEP researchers to make relatively precise…
Descriptors: Educational Assessment, Elementary Secondary Education, Error of Measurement, National Competency Tests

Gao, Xiaohong; And Others – Applied Measurement in Education, 1994
This study provides empirical evidence about the sampling variability and generalizability (reliability) of a statewide performance assessment for grade six. Results for 600 students at individual and school levels indicate that task-sampling variability was the major source of measurement error. Rater-sampling variability was negligible. (SLD)
Descriptors: Achievement Tests, Educational Assessment, Elementary School Students, Error of Measurement
Spencer, Bruce D. – 1986
The National Assessment of Educational Progress (NAEP) currently tests seventeen-year-old students enrolled in public and private secondary schools, but it does not test "out-of-school" seventeen-year-olds who have either graduated or dropped out. Estimating that one of five seventeen-year-olds is out of school, the interpretability of…
Descriptors: Adolescents, Cohort Analysis, Dropouts, Educational Assessment
Cook, Linda L.; Petersen, Nancy S. – 1986
This paper examines how various equating methods are affected by: (1) sampling error; (2) sample characteristics; and (3) characteristics of anchor test items. It reviews empirical studies that investigated the invariance of equating transformations, and it discusses empirical and simulation studies that focus on how the properties of anchor tests…
Descriptors: Educational Research, Equated Scores, Error of Measurement, Evaluation Methods