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Abdul Haq; Muhammad Usman; Manzoor Khan – Measurement: Interdisciplinary Research and Perspectives, 2024
Measurement errors may significantly distort the properties of an estimator. In this paper, estimators of the finite population variance using the information on first and second raw moments of the study variable are developed under stratified random sampling that incorporate the variance of a measurement error component. Additionally, combined…
Descriptors: Sampling, Error of Measurement, Evaluation Methods, Statistical Bias
Kelvin Terrell Pompey – ProQuest LLC, 2021
Many methods are used to measure interrater reliability for studies where each target receives ratings by a different set of judges. The purpose of this study is to explore the use of hierarchical modeling for estimating interrater reliability using the intraclass correlation coefficient. This study provides a description of how the ICC can be…
Descriptors: Interrater Reliability, Evaluation Methods, Test Reliability, Correlation
Goodman, Joshua T.; Dallas, Andrew D.; Fan, Fen – Applied Measurement in Education, 2020
Recent research has suggested that re-setting the standard for each administration of a small sample examination, in addition to the high cost, does not adequately maintain similar performance expectations year after year. Small-sample equating methods have shown promise with samples between 20 and 30. For groups that have fewer than 20 students,…
Descriptors: Equated Scores, Sample Size, Sampling, Weighted Scores
Testing Autocorrelation and Partial Autocorrelation: Asymptotic Methods versus Resampling Techniques
Ke, Zijun; Zhang, Zhiyong – Grantee Submission, 2018
Autocorrelation and partial autocorrelation, which provide a mathematical tool to understand repeating patterns in time series data, are often used to facilitate the identification of model orders of time series models (e.g., moving average and autoregressive models). Asymptotic methods for testing autocorrelation and partial autocorrelation such…
Descriptors: Correlation, Mathematical Formulas, Sampling, Monte Carlo Methods
Tarray, Tanveer A.; Singh, Housila P.; Yan, Zaizai – Sociological Methods & Research, 2017
This article addresses the problem of estimating the proportion Pi[subscript S] of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is…
Descriptors: Models, Efficiency, Sampling, Research Problems
Suero, Manuel; Privado, Jesús; Botella, Juan – Psicologica: International Journal of Methodology and Experimental Psychology, 2017
A simulation study is presented to evaluate and compare three methods to estimate the variance of the estimates of the parameters d and "C" of the signal detection theory (SDT). Several methods have been proposed to calculate the variance of their estimators, "d'" and "c." Those methods have been mostly assessed by…
Descriptors: Evaluation Methods, Theories, Simulation, Statistical Analysis
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
Itang'ata, Mukaria J. J. – ProQuest LLC, 2013
Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…
Descriptors: Comparative Analysis, Probability, Statistical Bias, Monte Carlo Methods
In'nami, Yo; Koizumi, Rie – International Journal of Testing, 2013
The importance of sample size, although widely discussed in the literature on structural equation modeling (SEM), has not been widely recognized among applied SEM researchers. To narrow this gap, we focus on second language testing and learning studies and examine the following: (a) Is the sample size sufficient in terms of precision and power of…
Descriptors: Structural Equation Models, Sample Size, Second Language Instruction, Monte Carlo Methods
Reardon, Sean F. – Society for Research on Educational Effectiveness, 2010
Instrumental variable estimators hold the promise of enabling researchers to estimate the effects of educational treatments that are not (or cannot be) randomly assigned but that may be affected by randomly assigned interventions. Examples of the use of instrumental variables in such cases are increasingly common in educational and social science…
Descriptors: Social Science Research, Least Squares Statistics, Computation, Correlation

Estes, Carole; Estes, Gary D. – 1980
Multiple matrix sampling is a sampling design in which both test items and examinees are randomly sampled from their respective populations. This study was designed to develop and assess a method for computing an estimate of a correlation coefficient when a multiple matrix sampling design is used. The examinee populations included 212 third-grade…
Descriptors: Correlation, Elementary Secondary Education, Evaluation Methods, Grade 3
McCaffrey, Daniel F.; Sass, Tim R.; Lockwood, J. R.; Mihaly, Kata – Education Finance and Policy, 2009
The utility of value-added estimates of teachers' effects on student test scores depends on whether they can distinguish between high- and low-productivity teachers and predict future teacher performance. This article studies the year-to-year variability in value-added measures for elementary and middle school mathematics teachers from five large…
Descriptors: Teacher Characteristics, Mathematics Achievement, Sampling, Middle School Teachers
Ritter, Lois A., Ed.; Sue, Valerie M., Ed. – New Directions for Evaluation, 2007
This chapter provides an overview of sampling methods that are appropriate for conducting online surveys. The authors review some of the basic concepts relevant to online survey sampling, present some probability and nonprobability techniques for selecting a sample, and briefly discuss sample size determination and nonresponse bias. Although some…
Descriptors: Sampling, Probability, Evaluation Methods, Computer Assisted Testing

Sandison, Alexander – Journal of Documentation, 1989
Argues that the difficulties of identifying and estimating the size of any pools of citable items are so great that comparisons of citation counts are rarely valid, and that the relationship between the value of a work and its citation can only be assessed by careful study of the citing paper. (four references) (CLB)
Descriptors: Citation Analysis, Citations (References), Evaluation Methods, Ratios (Mathematics)
Carifio, James; And Others – 1990
Possible bias due to sampling problems or low response rates has been a troubling "nuisance" variable in empirical research since seminal and classical studies were done on these problems at the beginning of this century. Recent research suggests that: (1) earlier views of the alleged bias problem were misleading; (2) under a variety of fairly…
Descriptors: Data Collection, Evaluation Methods, Research Problems, Response Rates (Questionnaires)
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