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Hedges, Larry V.; Schauer, Jacob M. – Grantee Submission, 2019
Formal empirical assessments of replication have recently become more prominent in several areas of science, including psychology. These assessments have used different statistical approaches to determine if a finding has been replicated. The purpose of this article is to provide several alternative conceptual frameworks that lead to different…
Descriptors: Statistical Analysis, Replication (Evaluation), Meta Analysis, Hypothesis Testing
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Heine, Jörg-Henrik; Robitzsch, Alexander – Large-scale Assessments in Education, 2022
Research Question: This paper examines the overarching question of to what extent different analytic choices may influence the inference about country-specific cross-sectional and trend estimates in international large-scale assessments. We take data from the assessment of PISA mathematics proficiency from the four rounds from 2003 to 2012 as a…
Descriptors: Foreign Countries, International Assessment, Achievement Tests, Secondary School Students
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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
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Sim, Julius; Saunders, Benjamin; Waterfield, Jackie; Kingstone, Tom – International Journal of Social Research Methodology, 2018
There has been considerable recent interest in methods of determining sample size for qualitative research a priori, rather than through an adaptive approach such as saturation. Extending previous literature in this area, we identify four distinct approaches to determining sample size in this way: rules of thumb, conceptual models, numerical…
Descriptors: Sample Size, Qualitative Research, Research Methodology, Statistical Analysis
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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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Rivera, Jason D. – Journal of Public Affairs Education, 2019
Across all social science disciplines, but in particular public administration, there is a shared concern about the costs of using traditional random samples to generate data, and its impact on researchers' ability to engage in "quality" research. As a result of these costs, more academics, practitioners, and students are turning to…
Descriptors: Public Affairs Education, Public Administration, Social Science Research, Graduate Students
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Cominole, Melissa; Ritchie, Nichole Smith; Cooney, Jennifer – National Center for Education Statistics, 2021
This publication describes the methods and procedures used for the 2008/18 Baccalaureate and Beyond Longitudinal Study (B&B:08/18). The B&B graduates, who completed the requirements for a bachelor's degree during the 2007-08 academic year, were first surveyed as part of the 2008 National Postsecondary Student Aid Study (NPSAS:08), and then…
Descriptors: Bachelors Degrees, College Graduates, Longitudinal Studies, Data Collection
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Mohammed, M. A.; Ibrahim, A. I. N.; Siri, Z.; Noor, N. F. M. – Sociological Methods & Research, 2019
In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to…
Descriptors: Monte Carlo Methods, Calculus, Sampling, Simulation
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National Center for Education Statistics, 2020
This document provides tables underlying figures in "Education, Employment, and Earnings: Expectations of 2009 Ninth-Graders in 2016" and describes the survey methodology, sources of error in estimates, response rates and nonresponse bias, and statistical procedures for the Statistics in Brief report "Education, Employment, and…
Descriptors: Expectation, Educational Attainment, Employment, Income
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Kim, Yukyoum; Lee, J. Lucy – Measurement in Physical Education and Exercise Science, 2019
The purposes of this manuscript are to identify common statistical mistakes in sport management, and to provide scholars with suggestions on how to develop and improve the quality of quantitative research. We have reviewed articles published from 2001 to 2017 in the "Journal of Sport Management," "Sport Management Review,"…
Descriptors: Athletics, Research, Research Problems, Statistical Analysis
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Wang, Yan; Kim, Eun Sook; Nguyen, Diep Thi; Pham, Thanh Vinh; Chen, Yi-Hsin; Yi, Zhiyao – AERA Online Paper Repository, 2017
The analysis of variance (ANOVA) F test is a commonly used method to test the mean equality among two or more populations. A critical assumption of ANOVA is homogeneity of variance (HOV), that is, the compared groups have equal variances. Although it is encouraged to test HOV as part of the regular ANOVA procedure, the efficacy of the initial HOV…
Descriptors: Statistical Analysis, Error of Measurement, Robustness (Statistics), Sampling
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Finch, W. Holmes; Finch, Maria Hernández – Journal of Experimental Education, 2018
Single subject (SS) designs are popular in educational and psychological research. There exist several statistical techniques designed to analyze such data and to address the question of whether an intervention has the desired impact. Recently, researchers have suggested that generalized additive models (GAMs) might be useful for modeling…
Descriptors: Educational Research, Longitudinal Studies, Simulation, Models
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Cappaert, Kevin J.; Wen, Yao; Chang, Yu-Feng – Measurement: Interdisciplinary Research and Perspectives, 2018
Events such as curriculum changes or practice effects can lead to item parameter drift (IPD) in computer adaptive testing (CAT). The current investigation introduced a point- and weight-adjusted D[superscript 2] method for IPD detection for use in a CAT environment when items are suspected of drifting across test administrations. Type I error and…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Identification
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Jennifer Wine; Beth Hustedt; Jennifer Cooney; Erin Thomsen – National Center for Education Statistics, 2023
This report describes the design, methods, and results of the 2016/20 Baccalaureate and Beyond Longitudinal Study (B&B:16/20) conducted by the U.S. Department of Education's National Center for Education Statistics (NCES). It is the second follow-up with a cohort of bachelor's degree recipients originally identified during the 2015-16 National…
Descriptors: Longitudinal Studies, College Graduates, Bachelors Degrees, College Students
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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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