Binary regression with stochastic covariates

Oral, E.
In binary regression the risk factor X has been treated in the literature as a non-stochastic variable. In most situations, however, X is stochastic. We present solutions applicable to such situations. We show that our solutions are more precise than those obtained by treating X as non-stochastic when, in fact, it is stochastic.


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When using data for estimating the parameters in a bivariate distribution, the tradition is to assume that data comes from a bivariate normal distribution. If the distribution is not bivariate normal, which often is the case, the maximum likelihood (ML) estimators are intractable and the least square (LS) estimators are inefficient. Here, we consider two independent sets of bivariate data which come from non-normal populations. We consider two distinctive distributions: the marginal and the conditional dist...
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Citation Formats
E. Oral, “Binary regression with stochastic covariates,” COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, pp. 1429–1447, 2006, Accessed: 00, 2020. [Online]. Available: