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Jamelia Harris – Field Methods, 2024
Not knowing the population size is a common problem in data-limited contexts. Drawing on work in Sierra Leone, this short take outlines a four-step solution to this problem: (1) estimate the population size using expert interviews; (2) verify estimates using interviews with participants sampled; (3) triangulate using secondary data; and (4)…
Descriptors: Foreign Countries, Sample Size, Surveys, Computation
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Shelby J. Haberman; Sabine Meinck; Ann-Kristin Koop – Large-scale Assessments in Education, 2024
This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal…
Descriptors: Elementary Secondary Education, Foreign Countries, Achievement Tests, Mathematics Achievement
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Martínez, Sergio; Rueda, Maria; Arcos, Antonio; Martínez, Helena – Sociological Methods & Research, 2020
This article discusses the estimation of a population proportion, using the auxiliary information available, which is incorporated into the estimation procedure by a probit model fit. Three probit regression estimators are considered, using model-based and model-assisted approaches. The theoretical properties of the proposed estimators are derived…
Descriptors: Computation, Regression (Statistics), Statistical Analysis, Population Groups
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Mang, Julia; Küchenhoff, Helmut; Meinck, Sabine; Prenzel, Manfred – Large-scale Assessments in Education, 2021
Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…
Descriptors: Sampling, Hierarchical Linear Modeling, Simulation, Scaling
Mikheeva, Ekaterina, Ed.; Meyer, Sebastian, Ed. – International Association for the Evaluation of Educational Achievement, 2020
IEA's International Computer and Information Literacy Study (ICILS) 2018 is designed to assess how well students are prepared for study, work, and life in a digital world. The study measures international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and…
Descriptors: International Assessment, Computer Literacy, Information Literacy, Computer Assisted Testing
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Wang, Jianjun; Ma, Xin – Athens Journal of Education, 2019
This rejoinder keeps the original focus on statistical computing pertaining to the correlation of student achievement between mathematics and science from the Trend in Mathematics and Science Study (TIMSS). Albeit the availability of student performance data in TIMSS and the emphasis of the inter-subject connection in the Next Generation Science…
Descriptors: Scores, Correlation, Achievement Tests, Elementary Secondary Education
Fraillon, Julian, Ed.; Ainley, John, Ed.; Schulz, Wolfram, Ed.; Friedman, Tim, Ed.; Duckworth, Daniel, Ed. – International Association for the Evaluation of Educational Achievement, 2020
IEA's International Computer and Information Literacy Study (ICILS) 2018 investigated how well students are prepared for study, work, and life in a digital world. ICILS 2018 measured international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and communicate at…
Descriptors: International Assessment, Computer Literacy, Information Literacy, Computer Assisted Testing
Gongjun Xu; Tony Sit; Lan Wang; Chiung-Yu Huang – Grantee Submission, 2017
Biased sampling occurs frequently in economics, epidemiology, and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to incorrect inference. We propose a unified estimation procedure and a computationally fast resampling method to make statistical inference for…
Descriptors: Sampling, Statistical Inference, Computation, Generalization
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Inzunsa Cazares, Santiago – North American Chapter of the International Group for the Psychology of Mathematics Education, 2016
This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…
Descriptors: Qualitative Research, College Students, Inferences, Logical Thinking
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Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric – Journal of Experimental Education, 2015
This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…
Descriptors: Effect Size, Measurement Techniques, Statistical Analysis, Research Design
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Goedeme, Tim – Social Indicators Research, 2013
If estimates are based on samples, they should be accompanied by appropriate standard errors and confidence intervals. This is true for scientific research in general, and is even more important if estimates are used to inform and evaluate policy measures such as those aimed at attaining the Europe 2020 poverty reduction target. In this article I…
Descriptors: Foreign Countries, Poverty, Social Isolation, Social Indicators
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Herzog, Stefan M.; Hertwig, Ralph – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Individuals can partly recreate the "wisdom of crowds" within their own minds by combining nonredundant estimates they themselves have generated. Herzog and Hertwig (2009) showed that this accuracy gain could be boosted by urging people to actively think differently when generating a 2nd estimate ("dialectical bootstrapping").…
Descriptors: Sampling, Statistical Inference, Experimental Psychology, Hypothesis Testing
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Özyurt, Hacer; Özyurt, Özcan – Eurasian Journal of Educational Research, 2015
Problem Statement: Learning-teaching activities bring along the need to determine whether they achieve their goals. Thus, multiple choice tests addressing the same set of questions to all are frequently used. However, this traditional assessment and evaluation form contrasts with modern education, where individual learning characteristics are…
Descriptors: Probability, Adaptive Testing, Computer Assisted Testing, Item Response Theory
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Micklewright, John; Schnepf, Sylke V.; Silva, Pedro N. – Economics of Education Review, 2012
Investigation of peer effects on achievement with sample survey data on schools may mean that only a random sample of the population of peers is observed for each individual. This generates measurement error in peer variables similar in form to the textbook case of errors-in-variables, resulting in the estimated peer group effects in an OLS…
Descriptors: Foreign Countries, Sampling, Error of Measurement, Peer Groups
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Dumenci, Levent; Yates, Phillip D. – Educational and Psychological Measurement, 2012
Estimation problems associated with the correlated-trait correlated-method (CTCM) parameterization of a multitrait-multimethod (MTMM) matrix are widely documented: the model often fails to converge; even when convergence is achieved, one or more of the parameter estimates are outside the admissible parameter space. In this study, the authors…
Descriptors: Correlation, Models, Multitrait Multimethod Techniques, Matrices
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