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Rehabilitation Dataset Directory: Dataset Profile


Dataset: National Longitudinal Transition Study 2 (NLTS-2)

Basic Information
Dataset full name: National Longitudinal Transition Study 2
Dataset acronym NLTS-2
Summary The National Longitudinal Transition Study-2 (NLTS-2) was an annual longitudinal study funded by the U.S. Department of Education and documents the experiences of a national sample of students receiving special education who were 13 to 16 years of age in 2000 as they moved from secondary school into adult roles. The study collected information regarding a wide range of topics, including high school coursework, extracurricular activities, academic performance, postsecondary education and training, employment, independent living, and community participation. Note: a new study, the NLTS2012, is in progress:
http://ies.ed.gov/ncee/nlts/ .
Key Terms
Study Design Longitudinal
Data Type(s) Survey
Sponsoring Agency/Entity Department of Education (DOE)
Health conditions/Disability measures
Health condition(s) Allergy, SCI, TBI, Mental/emotional problems, Respiratory issues
Disability Measures ADLs, IADLs, Functional limitations, Participation limitations, Learning disorder, ADD/ADHD, Developmental disabilities, Cognitive, Memory, Communication, Vision, Hearing
Measures/outcomes of interest
Topics Coursework, Extracurricular activities, Academic performance, Postsecondary education and training, Employment, Independent living, Community participation
Sample
Sample Population Special education students: 13-16 years of age in 2000
Sample Size/Notes 11,270 special education students
Unit of Observation Individual
Geographic Coverage United States
Geographic specificity National
Data Collection
Data Collection Mode Survey, interview, Assessments and administrative records
Years Collected 2000-2010
Data Collection Frequency Biannually over 10 year period (5 waves of data collection). For details see:
http://www.nlts2.org/faq.html#timeline
Strengths and limitations
Strengths Longitudinal data follows students for 10 years, using a wide array of data sources (parents, teachers students, school records) and data collection strategies. Large, nationally representative sample. Minimal bias found in comparison with other data sources. Data collection instruments designed to allow comparisons to general population of youth based on other national databases.
Limitations Potential bias due to attrition over waves. Sample limited to only youth who received special education, not representative of all youth with disabilities.
Data details
Primary Website http://www.nlts2.org/
Data Access http://www.nlts2.org/data_tables/datatable_training.html
Data Access Requirements Data Use agreement, No Cost
Summary Tables/reports http://www.nlts2.org/data_tables/index.html
Dataset components (where applicable) Parent Survey.

Teacher Survey.

School Characteristics Survey.

Cross-Instrument Data.

Parent/Youth Survey.

Direct Assessment.

Alternate Assessment.

Teacher Questionnaire.

Student's School Program Questionnaire.

Transcript Data.

For complete list and wave identification see:
http://www.nlts2.org/data_dictionary/data_documentation_dictionary.html#wave1_data_files_content


Selected papers
Technical Data documentation and dictionaries:
http://www.nlts2.org/data_dictionary/data_documentation_dictionary.html
Other Papers NLTS-2 Reports:
http://www.nlts2.org/reports/index.html



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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

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Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

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