A practical guide for analyzing large-scale assessment data using Mplus: A case demonstration using the Program for International Assessment of Adult Competencies Data

dc.contributor.authorYamashita, Takashi
dc.contributor.authorSmith, Thomas J.
dc.contributor.authorCummins, Phyllis A.
dc.date.accessioned2021-01-27T19:13:48Z
dc.date.available2021-01-27T19:13:48Z
dc.date.issued2020-12-16
dc.description.abstractIn order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Mplus. Concise overview and key unique aspects of large-scale assessment data from the 2012/2014 Program for International Assessment of Adult Competencies (PIAAC) are described. Using commonly-used statistical software including SAS and R, a simple macro program and syntax are developed to streamline the data preparation process. Then, two examples of structural equation models are demonstrated using Mplus. The suggested data preparation and analytic approaches can be immediately applicable to existing large-scale assessment data.en_US
dc.description.sponsorshipFunding. In this study, TY, TJS and PAC were partially supported by the Institute of Education Sciences, U.S. Department of Education, through Grant (R305A170183) to Miami University and University of Maryland, Baltimore County. The opinions expressed are those of the authors and do not represent views of the institute or the U.S. Department of Education.en_US
dc.description.urihttps://journals.sagepub.com/doi/10.3102/1076998620978554en_US
dc.format.extent30 pagesen_US
dc.genrejournal articles postprintsen_US
dc.identifierdoi:10.13016/m2aql2-u31i
dc.identifier.citation1. Yamashita T, Smith TJ, Cummins PA. A Practical Guide for Analyzing Large-Scale Assessment Data Using Mplus: A Case Demonstration Using the Program for International Assessment of Adult Competencies Data. Journal of Educational and Behavioral Statistics. December 2020. doi:10.3102/1076998620978554en_US
dc.identifier.urihttps://doi.org/10.3102/1076998620978554
dc.identifier.urihttp://hdl.handle.net/11603/20636
dc.language.isoen_USen_US
dc.publisherSAGEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Sociology and Anthropology Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsTakashi Yamashita, Thomas J. Smith and Phyllis A. Cummins, A Practical Guide for Analyzing Large-Scale Assessment Data Using Mplus: A Case Demonstration Using the Program for International Assessment of Adult Competencies Data, Journal of Educational and Behavioral Statistics pp. 1–18. Copyright © 2020 AERA. DOI: 10.3102/1076998620978554.
dc.titleA practical guide for analyzing large-scale assessment data using Mplus: A case demonstration using the Program for International Assessment of Adult Competencies Dataen_US
dc.typeTexten_US

Files

Original bundle

Now showing 1 - 5 of 5
Loading...
Thumbnail Image
Name:
PIAAC in Mplus REVISION02 ver02 NOV09 2020.pdf
Size:
505.69 KB
Format:
Adobe Portable Document Format
Description:
Loading...
Thumbnail Image
Name:
Appendix 1.pdf
Size:
159.52 KB
Format:
Adobe Portable Document Format
Description:
Loading...
Thumbnail Image
Name:
Appendix 2.pdf
Size:
105.97 KB
Format:
Adobe Portable Document Format
Description:
Loading...
Thumbnail Image
Name:
Appendix 3.pdf
Size:
116 KB
Format:
Adobe Portable Document Format
Description:
Loading...
Thumbnail Image
Name:
Appendix 4.pdf
Size:
112.67 KB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.56 KB
Format:
Item-specific license agreed upon to submission
Description: