Assessing the impact of measurement error in modeling change in the absence of auxiliary data
Publication
, Journal Article
Yanez, ND; Aljasser, I; Andre, M; Hu, C; Juraska, M; Lumley, T
Published in: Communications in Statistics - Theory and Methods
March 19, 2017
Measurement error is well known to cause bias in estimated regression coefficients and a loss of power for detecting associations. Methods commonly used to correct for bias often require auxiliary data. We develop a solution for investigating associations between the change in an imprecisely measured outcome and precisely measured predictors, adjusting for the baseline value of the outcome when auxiliary data are not available. We require the specification of ranges for the reliability or the measurement error variance. The solution allows one to investigate the associations for change and to assess the impact of the measurement error.
Duke Scholars
Published In
Communications in Statistics - Theory and Methods
DOI
EISSN
1532-415X
ISSN
0361-0926
Publication Date
March 19, 2017
Volume
46
Issue
6
Start / End Page
2667 / 2680
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 0199 Other Mathematical Sciences
- 0104 Statistics
Citation
APA
Chicago
ICMJE
MLA
NLM
Yanez, N. D., Aljasser, I., Andre, M., Hu, C., Juraska, M., & Lumley, T. (2017). Assessing the impact of measurement error in modeling change in the absence of auxiliary data. Communications in Statistics - Theory and Methods, 46(6), 2667–2680. https://doi.org/10.1080/03610926.2015.1040508
Yanez, N. D., I. Aljasser, M. Andre, C. Hu, M. Juraska, and T. Lumley. “Assessing the impact of measurement error in modeling change in the absence of auxiliary data.” Communications in Statistics - Theory and Methods 46, no. 6 (March 19, 2017): 2667–80. https://doi.org/10.1080/03610926.2015.1040508.
Yanez ND, Aljasser I, Andre M, Hu C, Juraska M, Lumley T. Assessing the impact of measurement error in modeling change in the absence of auxiliary data. Communications in Statistics - Theory and Methods. 2017 Mar 19;46(6):2667–80.
Yanez, N. D., et al. “Assessing the impact of measurement error in modeling change in the absence of auxiliary data.” Communications in Statistics - Theory and Methods, vol. 46, no. 6, Mar. 2017, pp. 2667–80. Scopus, doi:10.1080/03610926.2015.1040508.
Yanez ND, Aljasser I, Andre M, Hu C, Juraska M, Lumley T. Assessing the impact of measurement error in modeling change in the absence of auxiliary data. Communications in Statistics - Theory and Methods. 2017 Mar 19;46(6):2667–2680.
Published In
Communications in Statistics - Theory and Methods
DOI
EISSN
1532-415X
ISSN
0361-0926
Publication Date
March 19, 2017
Volume
46
Issue
6
Start / End Page
2667 / 2680
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 0199 Other Mathematical Sciences
- 0104 Statistics