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Noma, Hisashi; Hamura, Yasuyuki; Gosho, Masahiko; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…
Descriptors: Network Analysis, Meta Analysis, Regression (Statistics), Error of Measurement
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Martin, Michael O.; Mullis, Ina V. S. – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments of student achievement such as International Association for the Evaluation of Educational Achievement's Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study and Organization for Economic Cooperation and Development's Program for International…
Descriptors: Achievement Tests, International Assessment, Mathematics Tests, Science Achievement
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Astivia, Oscar L. Olvera; Zumbo, Bruno D. – Practical Assessment, Research & Evaluation, 2019
Within psychology and the social sciences, Ordinary Least Squares (OLS) regression is one of the most popular techniques for data analysis. In order to ensure the inferences from the use of this method are appropriate, several assumptions must be satisfied, including the one of constant error variance (i.e. homoskedasticity). Most of the training…
Descriptors: Multiple Regression Analysis, Least Squares Statistics, Statistical Analysis, Error of Measurement
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White, Simon R.; Bonnett, Laura J. – Teaching Statistics: An International Journal for Teachers, 2019
The statistical concept of sampling is often given little direct attention, typically reduced to the mantra "take a random sample". This low resource and adaptable activity demonstrates sampling and explores issues that arise due to biased sampling.
Descriptors: Statistical Bias, Sampling, Statistical Analysis, Learning Activities
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Fellers, Pamela S.; Kuiper, Shonda – Journal of Statistics Education, 2020
Increasingly students, particularly those in the social sciences, work with survey data collected through a more complex sampling method than a simple random sample. Failing to understand how to properly approach survey data can lead to inaccurate results. In this article, we describe a series of online data visualization applications and…
Descriptors: Statistics, Introductory Courses, Teaching Methods, Concept Formation
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Arzumanyan, George; Halcoussis, Dennis; Phillips, G. Michael – American Journal of Business Education, 2015
This paper presents the Agresti & Coull "Adjusted Wald" method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small…
Descriptors: Business Administration Education, Error of Measurement, Error Patterns, Intervals
Haberman, Shelby J.; Dorans, Neil J. – Educational Testing Service, 2011
For testing programs that administer multiple forms within a year and across years, score equating is used to ensure that scores can be used interchangeably. In an ideal world, samples sizes are large and representative of populations that hardly change over time, and very reliable alternate test forms are built with nearly identical psychometric…
Descriptors: Scores, Reliability, Equated Scores, Test Construction
Liu, Qin – Association for Institutional Research, 2012
This discussion constructs a survey data quality strategy for institutional researchers in higher education in light of total survey error theory. It starts with describing the characteristics of institutional research and identifying the gaps in literature regarding survey data quality issues in institutional research and then introduces the…
Descriptors: Institutional Research, Higher Education, Quality Control, Researchers
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
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Broughman, Stephen P.; Swaim, Nancy L.; Hryczaniuk, Cassie A. – National Center for Education Statistics, 2011
In 1988, the National Center for Education Statistics (NCES) introduced a proposal to develop a private school data collection that would improve on the sporadic collection of private school data dating back to 1890 and improve on commercially available private school sampling frames. Since 1989, the U.S. Bureau of the Census has conducted the…
Descriptors: Private Schools, Statistical Significance, Sampling, Statistics
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Hutchison, Dougal – Oxford Review of Education, 2008
There is a degree of instability in any measurement, so that if it is repeated, it is possible that a different result may be obtained. Such instability, generally described as "measurement error", may affect the conclusions drawn from an investigation, and methods exist for allowing it. It is less widely known that different disciplines, and…
Descriptors: Measurement Techniques, Data Analysis, Error of Measurement, Test Reliability
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Bonnett, Douglas G. – Psychological Methods, 2008
Most psychology journals now require authors to report a sample value of effect size along with hypothesis testing results. The sample effect size value can be misleading because it contains sampling error. Authors often incorrectly interpret the sample effect size as if it were the population effect size. A simple solution to this problem is to…
Descriptors: Intervals, Hypothesis Testing, Effect Size, Sampling
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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
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Schumacker, Randall E.; Smith, Everett V., Jr. – Educational and Psychological Measurement, 2007
Measurement error is a common theme in classical measurement models used in testing and assessment. In classical measurement models, the definition of measurement error and the subsequent reliability coefficients differ on the basis of the test administration design. Internal consistency reliability specifies error due primarily to poor item…
Descriptors: Measurement Techniques, Error of Measurement, Item Sampling, Item Response Theory
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Birenbaum, Menucha – Studies in Educational Evaluation, 2007
High quality assessment practice is expected to yield valid and useful score-based interpretations about what the examinees know and are able to do with respect to a defined target domain. Given this assertion, the article presents a framework based on the "unified view of validity," advanced by Cronbach and Messick over two decades ago, to assist…
Descriptors: Quality Control, Student Evaluation, Validity, Evaluation Methods
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