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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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Patton, Jeffrey M.; Cheng, Ying; Hong, Maxwell; Diao, Qi – Journal of Educational and Behavioral Statistics, 2019
In psychological and survey research, the prevalence and serious consequences of careless responses from unmotivated participants are well known. In this study, we propose to iteratively detect careless responders and cleanse the data by removing their responses. The careless responders are detected using person-fit statistics. In two simulation…
Descriptors: Test Items, Response Style (Tests), Identification, Computation
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Hallberg, Kelly; Williams, Ryan; Swanlund, Andrew – Journal of Research on Educational Effectiveness, 2020
More aggregate data on school performance is available than ever before, opening up new possibilities for applied researchers interested in assessing the effectiveness of school-level interventions quickly and at a relatively low cost by implementing comparative interrupted times series (CITS) designs. We examine the extent to which effect…
Descriptors: Data Use, Research Methodology, Program Effectiveness, Design
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Lee, Daniel Y.; Harring, Jeffrey R.; Stapleton, Laura M. – Journal of Experimental Education, 2019
Respondent attrition is a common problem in national longitudinal panel surveys. To make full use of the data, weights are provided to account for attrition. Weight adjustments are based on sampling design information and data from the base year; information from subsequent waves is typically not utilized. Alternative methods to address bias from…
Descriptors: Longitudinal Studies, Research Methodology, Research Problems, Data Analysis
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Peugh, James L.; Heck, Ronald H. – Journal of Early Adolescence, 2017
Researchers in the field of early adolescence interested in quantifying the environmental influences on a response variable of interest over time would use cluster sampling (i.e., obtaining repeated measures from students nested within classrooms and/or schools) to obtain the needed sample size. The resulting longitudinal data would be nested at…
Descriptors: Longitudinal Studies, Early Adolescents, Hierarchical Linear Modeling, Sampling
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Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S. – Psychometrika, 2012
We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Reliability
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Lu, Zhenqiu Laura; Zhang, Zhiyong; Lubke, Gitta – Multivariate Behavioral Research, 2011
"Growth mixture models" (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class…
Descriptors: Bayesian Statistics, Statistical Inference, Computation, Models
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Peugh, James L. – Journal of School Psychology, 2010
Collecting data from students within classrooms or schools, and collecting data from students on multiple occasions over time, are two common sampling methods used in educational research that often require multilevel modeling (MLM) data analysis techniques to avoid Type-1 errors. The purpose of this article is to clarify the seven major steps…
Descriptors: Educational Research, Research Methodology, Data Analysis, Academic Achievement
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Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2013
The 2012 edition of the "Digest of Education Statistics" is the 48th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: School Statistics, Definitions, Tables (Data), Longitudinal Studies
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Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2012
The 2011 edition of the "Digest of Education Statistics" is the 47th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: Educational Research, Data Collection, Data Analysis, Error Patterns
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Tourangeau, Karen; Nord, Christine; Lê, Thanh; Wallner-Allen, Kathleen; Vaden-Kiernan, Nancy; Blaker, Lisa; Najarian, Michelle – National Center for Education Statistics, 2018
This manual provides guidance and documentation for users of the longitudinal kindergarten-fourth grade (K-4) public-use data file of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011), which includes the first release of the public version of the third-grade data. This manual mainly provides information specific…
Descriptors: Longitudinal Studies, Children, Surveys, Kindergarten
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Luyten, Hans; Tymms, Peter; Jones, Paul – School Effectiveness and School Improvement, 2009
The research findings presented in this paper illustrate how the "value added" of schooling can be assessed empirically using cross-sectional data. Application of the regression-discontinuity approach within a multilevel framework produces both an estimate of the absolute effect of 1 year schooling and an estimate of the variation across…
Descriptors: Academic Achievement, Longitudinal Studies, Sampling, Achievement Gains
Rothman, Sheldon – Australian Council for Educational Research, 2009
This technical paper examines the issue of attrition bias in two cohorts of the Longitudinal Surveys of Australian Youth (LSAY), based on an analysis using data from 1995 to 2002. Data up to 2002 provided eight years of information on members of the Y95 cohort and five years of information on members of the Y98 cohort. This study suggests that…
Descriptors: Outcomes of Education, Foreign Countries, Secondary School Students, Adults
Herman, Joan L.; Yamashiro, Kyo; Lefkowitz, Sloane; Trusela, Lee Ann – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2008
This study examined the relationship between data use and achievement at 13 urban Title I schools. Using multiple methods, including test scores, district surveys, school transformation plans, and four case study site visits, the researchers found wide variation in the use of data to inform instruction and planning. In some cases, schools were …
Descriptors: Academic Achievement, Program Effectiveness, Scores, Data Analysis
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Lubke, Gitta H.; Muthen, Bengt – Psychological Methods, 2005
Sources of population heterogeneity may or may not be observed. If the sources of heterogeneity are observed (e.g., gender), the sample can be split into groups and the data analyzed with methods for multiple groups. If the sources of population heterogeneity are unobserved, the data can be analyzed with latent class models. Factor mixture models…
Descriptors: Youth, Evaluation Methods, Factor Analysis, Data Analysis
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