A measurement-error model for binary and ordinal regression.
A measurement-error model for binary and ordinal regression.
复制标题
二元和序数回归的测量误差模型。
DOI:
10.1002/sim.4780080914
复制
发表时间:
1989
影响因子:
2
通讯作者:
Schafer,DW
中科院分区:
文献类型:
--
作者:
Tosteson,TD;Stefanski,LA;Schafer,DW
Exposure assessment poses special problems in air pollution epidemiology. This paper proposes a probit regression model for binary and ordinal outcomes that uses exposure validation information to develop estimates for the coefficient of the true exposure when only the inaccurate ‘surrogate’ measure of exposure is available for the individuals in the health study. This method is closely related to recently developed measurement‐error methods, and is based on the assumption that the outcome and the surrogate exposure are conditionally independent given the true exposure. A test statistic is proposed for checking this conditional independence assumption when more than one surrogate is available, and an interpretation of the coefficient estimate is provided in the event that the assumption is violated. The methods are applied to an example involving nitrogen dioxide exposure and wheeze in children.
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DOI:
10.1080/0002889768507522
发表时间:
1976-01-01
期刊:
AMERICAN INDUSTRIAL HYGIENE ASSOCIATION JOURNAL
影响因子:
--
作者:
PALMES, ED;GUNNISON, AF;TOMCZYK, C
通讯作者:
TOMCZYK, C
DOI:
10.1080/15298667991430028
发表时间:
1979
期刊:
American Industrial Hygiene Association journal
影响因子:
--
作者:
E. Palmes;C. Tomczyk
通讯作者:
C. Tomczyk
影响因子:
11.4
作者:
QUACKENBOSS, JJ;SPENGLER, JD;DUFFY, CP
通讯作者:
DUFFY, CP
DOI:
10.1164/arrd.1979.120.4.767
发表时间:
1979
期刊:
The American review of respiratory disease
影响因子:
--
作者:
B. Ferris;F. Speizer;J. Spengler;D. Dockery;Y. Bishop;M. Wolfson;C. Humble
通讯作者:
C. Humble
影响因子:
2.7
作者:
D. W. Schafer
通讯作者:
D. W. Schafer