Analyzing Subjective Well-Being Data with Misclassification
Analyzing Subjective Well-Being Data with Misclassification
About this item
Full title
Author / Creator
Publisher
Alexandria: Taylor & Francis
Journal title
Language
English
Formats
Publication information
Publisher
Alexandria: Taylor & Francis
Subjects
More information
Scope and Contents
Contents
We use novel nonparametric techniques to test for the presence of nonclassical measurement error in reported life satisfaction (LS) and study the potential effects from ignoring it. Our dataset comes from Wave 3 of the UK Understanding Society that is surveyed from 35,000 British households. Our test finds evidence of measurement error in reported...
Alternative Titles
Full title
Analyzing Subjective Well-Being Data with Misclassification
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2803108049
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2803108049
Other Identifiers
ISSN
0735-0015
E-ISSN
1537-2707
DOI
10.1080/07350015.2020.1865169
