This paper describes the origins of the logistic function, its adoption in bio-assay, and its wider acceptance in statistics. Its roots spread far back to the early 19th century; the survival of the term logistic and the wide application of the device have been determined decisively by the...

In a binary logit analysis with unequal sample frequencies of the twooutcomes the less frequent outcome always has lower estimatedprediction probabilities than the other one. This effect is unavoidable,and its extent varies inversely with the fit of the model, as given by anew measure that...

In binary discrete regression models like logit or probit the omis-sion of a relevant regressor (even if it is orthogonal) depresses the re-maining b coefficients towards zero. For the probit model, Wooldridge(2002) has shown that this bias does not carry over to the effect ofthe regressor on...

In a discrete model, the predicted probabilities of a particular eventcan be matched to the observed (0, I) outcomes and this will give riseto a measure of fit for that event. Previous results for the binomialmodel are applied to multinomial models. In these models the measureof fit will vary...

This paper describes the origins of the logistic function, its adoption in bio-assay, and its wider acceptance in statistics. Its roots spread far back to the early 19th century; the survival of the term logistic and the wide application of the device have been determined decisively by the...

In binary discrete regression models like logit or probit the omis- sion of a relevant regressor (even if it is orthogonal) depresses the re- maining <font face="Symbol">b</font> coefficients towards zero. For the probit model, Wooldridge (2002) has shown that this bias does not carry over to the effect of the regressor...

The Brabant Data Set, now freely accessible, contains information on a sample cohort of 3,000 individuals born around 1940 from surveys in 1952, 1983 and 1993, as well as on deaths between 1994 and 2009. In line with numerous epidemiological studies we find that among the early variables...

This technical note consists of three parts. The first describes the origins of the Brabant data set, the later surveys and the mortality data. The second section discusses the variation of mortality rates with age in the population and in the sample. The third section sets out the proportional...

In a discrete model, the predicted probabilities of a particular event can be matched to the observed (0, I) outcomes and this will give rise to a measure of fit for that event. Previous results for the binomial model are applied to multinomial models. In these models the measure of fit will...

The discrete outcome of a probability model is recorded as Y(i)=1 while otherwise Y(i)=0. y is the vector of observed outcomes, p the corresponding probabilities, p^ a consistent estimate of p, and residuals are defined as e = y - p^. Under quite general conditions, the asymptotic properties of...