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Oliver Lüdtke; Alexander Robitzsch – Journal of Experimental Education, 2025
There is a longstanding debate on whether the analysis of covariance (ANCOVA) or the change score approach is more appropriate when analyzing non-experimental longitudinal data. In this article, we use a structural modeling perspective to clarify that the ANCOVA approach is based on the assumption that all relevant covariates are measured (i.e.,…
Descriptors: Statistical Analysis, Longitudinal Studies, Error of Measurement, Hierarchical Linear Modeling
Little, Todd D.; Bontempo, Daniel; Rioux, Charlie; Tracy, Allison – International Journal of Research & Method in Education, 2022
Multilevel modelling (MLM) is the most frequently used approach for evaluating interventions with clustered data. MLM, however, has some limitations that are associated with numerous obstacles to model estimation and valid inferences. Longitudinal multiple-group (LMG) modelling is a longstanding approach for testing intervention effects using…
Descriptors: Longitudinal Studies, Hierarchical Linear Modeling, Alternative Assessment, Intervention
von Hippel, Paul T. – Sociological Methods & Research, 2020
When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…
Descriptors: Computation, Error of Measurement, Data Analysis, Children
Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2022
This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…
Descriptors: Comparative Analysis, Statistical Analysis, Sample Size, Measurement Techniques
Duprey, Michael A.; Pratt, Daniel J.; Wilson, David H.; Jewell, Donna M.; Brown, Derick S.; Caves, Lesa R.; Kinney, Satkartar K.; Mattox, Tiffany L.; Ritchie, Nichole Smith; Rogers, James E.; Spagnardi, Colleen M.; Wescott, Jamie D. – National Center for Education Statistics, 2020
The nine appendices in this publication accompany the full report, "High School Longitudinal Study of 2009 (HSLS:09) Postsecondary Education Transcript Study and Student Financial Aid Records Collection. Data File Documentation. NCES 2020-004" (ED607366). They include: (1) Glossary of Terms; (2) Student Financial Aid Records Instrument…
Descriptors: Longitudinal Studies, High School Students, Data Collection, Academic Records
Mayer, Axel; Steyer, Rolf; Mueller, Horst – Structural Equation Modeling: A Multidisciplinary Journal, 2012
We present a 3-step approach to defining latent growth components. In the first step, a measurement model with at least 2 indicators for each time point is formulated to identify measurement error variances and obtain latent variables that are purged from measurement error. In the second step, we use contrast matrices to define the latent growth…
Descriptors: Statistical Analysis, Measurement, Structural Equation Models, Error of Measurement
Chen, Fang; Chalhoub-Deville, Micheline – Language Testing, 2014
Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…
Descriptors: Regression (Statistics), Language Tests, Language Proficiency, Mathematics Achievement
Gemici, Sinan; Bednarz, Alice; Lim, Patrick – International Journal of Training Research, 2012
Quantitative research in vocational education and training (VET) is routinely affected by missing or incomplete information. However, the handling of missing data in published VET research is often sub-optimal, leading to a real risk of generating results that can range from being slightly biased to being plain wrong. Given that the growing…
Descriptors: Vocational Education, Educational Research, Data, Statistical Analysis
Ingels, Steven J.; Pratt, Daniel J.; Herget, Deborah R.; Dever, Jill A.; Fritch, Laura Burns; Ottem, Randolph; Rogers, James E.; Kitmitto, Sami; Leinwand, Steve – National Center for Education Statistics, 2013
This manual has been produced to familiarize data users with the design, and the procedures followed for data collection and processing, in the base year and first follow-up of the High School Longitudinal Study of 2009 (HSLS:09), with emphasis on the first follow-up. It also provides the necessary documentation for use of the public-use data…
Descriptors: High School Students, Longitudinal Studies, Annual Reports, Followup Studies
Ingels, Steven J.; Pratt, Daniel J.; Herget, Deborah R.; Dever, Jill A.; Fritch, Laura Burns; Ottem, Randolph; Rogers, James E.; Kitmitto, Sami; Leinwand, Steve – National Center for Education Statistics, 2013
The manual that accompanies these appendices was produced to familiarize data users with the design, and the procedures followed for data collection and processing, in the base year and first follow-up of the High School Longitudinal Study of 2009 (HSLS:09), with emphasis on the first follow-up. It also provides the necessary documentation for use…
Descriptors: High School Students, Longitudinal Studies, Annual Reports, Followup Studies
Wang, Jichuan – Structural Equation Modeling, 2004
In addition to assessing the rate of change in outcome measures, it may be useful to test the significance of outcome changes during specific time periods within an entire observation period under study. While discussing the delta method and bootstrapping, this study demonstrates how to use these 2 methods to estimate the standard errors of the…
Descriptors: Longitudinal Studies, Error of Measurement, Measures (Individuals), Comparative Analysis
Ingels, Steven J.; Scott, Leslie A.; Taylor, John R.; Owings, Jeffrey; Quinn, Peggy – 1998
This technical report documents the methodology of the National Education Longitudinal Study of 1988 (NELS:88) base year survey of eighth graders through the 1992 second followup survey of high school students and dropouts. Chapter 1 begins with an overview and history of the NELS:88 and its database, Chapter 2 contains a description of the data…
Descriptors: Data Collection, Databases, Error of Measurement, Followup Studies