This paper reviews adjusted methods of estimation of attributable risk (AR), that is methods
that allow one to obtain estimates of AR while controlling for other factors. Estimability and …

Conditional logistic regression was developed to avoid “sparse-data” biases that can arise
in ordinary logistic regression analysis. Nonetheless, it is a large-sample method that can …

Students in statistics or data science usually learn early on that when the sample size n is
large relative to the number of variables p, fitting a logistic model by the method of maximum …

In an earlier paper the writer reported on the natural enemies found attacking the Iris borer,
Macronoctua onusta Grote, at Madison, Wisconsin, in 1928. The studies were continued in …

The Wiley-Interscience Paperback Series consists of selected books that have been made
more accessible to consumers in an effort to increase global appeal and general circulation …

Applications of item response theory, which depend upon its parameter invariance property,
require that parameter estimates be unbiased. A new method, weighted likelihood …

In recent years, increasing attention has been given to the statistical aspects of contingent
valuation (CV) survey design and data analysis. The main reason for the growing interest in …

A conditional logit model of the location decision of foreign firms investing in manufacturing
facilities in the United States is developed and estimated. Our results for 1981-1983 indicate …

It is found that multicollinearity among the independent variables in logistic regression
inflates the variances of the maximum likelihood estimator. A Ridge type estimator is …

In this paper we derive general formulae for first-order biases of maximum likelihood
estimates of the linear parameters, linear predictors, the dispersion parameter and fitted …