Abstract
An approach to the logistic modeling of interobserver agreement is described that allows for the estimation of a commonly employed measure of agreement. The dependent variable is defined to be 1 if the two raters agree, and 0 otherwise. Covariates may be included in the regression equation in order to obtain adjusted or subgroup-specific estimates of percent agreement. As an empirical example, logistic models were fitted to data from a validation study of the agreement between interview information and physician records on the history of post-menopausal estrogen use, from a case-control study of breast cancer conducted on Oahu, Hawaii. Variables found to be related to agreement in previous univariate analyses were examined as Covarates in the logistic model. The directly calculated estimates of percent agreement agreed well with the modeled estimates derived from the regression coefficients. Thus, the logistic model may provide a useful alternative to existing methods for the description of interobserver agreement.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1237-1241 |
| Number of pages | 5 |
| Journal | Journal of Clinical Epidemiology |
| Volume | 45 |
| Issue number | 11 |
| DOIs | |
| State | Published - Jan 1 1992 |
| Externally published | Yes |
Fingerprint
Keywords
- Breast cancer
- Epidemiologic methods
- Mathematical modeling
- Percent agreement Reliability
ASJC Scopus subject areas
- Epidemiology
Cite this
The logistic modeling of interobserver agreement. / Coughlin, Steven Scott; Pickle, Linda W.; Goodman, Marc T.; Wilkens, Lynne R.
In: Journal of Clinical Epidemiology, Vol. 45, No. 11, 01.01.1992, p. 1237-1241.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The logistic modeling of interobserver agreement
AU - Coughlin, Steven Scott
AU - Pickle, Linda W.
AU - Goodman, Marc T.
AU - Wilkens, Lynne R.
PY - 1992/1/1
Y1 - 1992/1/1
N2 - An approach to the logistic modeling of interobserver agreement is described that allows for the estimation of a commonly employed measure of agreement. The dependent variable is defined to be 1 if the two raters agree, and 0 otherwise. Covariates may be included in the regression equation in order to obtain adjusted or subgroup-specific estimates of percent agreement. As an empirical example, logistic models were fitted to data from a validation study of the agreement between interview information and physician records on the history of post-menopausal estrogen use, from a case-control study of breast cancer conducted on Oahu, Hawaii. Variables found to be related to agreement in previous univariate analyses were examined as Covarates in the logistic model. The directly calculated estimates of percent agreement agreed well with the modeled estimates derived from the regression coefficients. Thus, the logistic model may provide a useful alternative to existing methods for the description of interobserver agreement.
AB - An approach to the logistic modeling of interobserver agreement is described that allows for the estimation of a commonly employed measure of agreement. The dependent variable is defined to be 1 if the two raters agree, and 0 otherwise. Covariates may be included in the regression equation in order to obtain adjusted or subgroup-specific estimates of percent agreement. As an empirical example, logistic models were fitted to data from a validation study of the agreement between interview information and physician records on the history of post-menopausal estrogen use, from a case-control study of breast cancer conducted on Oahu, Hawaii. Variables found to be related to agreement in previous univariate analyses were examined as Covarates in the logistic model. The directly calculated estimates of percent agreement agreed well with the modeled estimates derived from the regression coefficients. Thus, the logistic model may provide a useful alternative to existing methods for the description of interobserver agreement.
KW - Breast cancer
KW - Epidemiologic methods
KW - Mathematical modeling
KW - Percent agreement Reliability
UR - http://www.scopus.com/inward/record.url?scp=0026476134&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0026476134&partnerID=8YFLogxK
U2 - 10.1016/0895-4356(92)90164-I
DO - 10.1016/0895-4356(92)90164-I
M3 - Article
C2 - 1432004
AN - SCOPUS:0026476134
VL - 45
SP - 1237
EP - 1241
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
SN - 0895-4356
IS - 11
ER -