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Logistic regression

Known as: Regression, Binary logit model, Conditional logistic regression 
In statistics, logistic regression, or logit regression, or logit model is a regression model where the dependent variable (DV) is categorical. This… 
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Papers overview

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2012
2012
The application of spatial‐temporal stochastic rainfall models to semi‐arid or arid areas is expected to be particularly… 
Review
2009
Review
2009
The use of customer preference models to evaluate the economic impact of design changes and new product introductions has become… 
2005
2005
Elicker, James; Clawson, Carolyn; Hong, Soo-Young; Kim, Tae-Eun; Evangelou, Demetra; and Kontos, Susan J., "Child Care for… 
2005
2005
OBJETIVO: Identificar a los sujetos afectados por lesiones de caries severas, por medio del tamano de la lesion, y determinar los… 
2000
2000
Abstract The effects of habitat and vegetation characteristics on the reproductive success of Yellow-breasted Chats (Icteria… 
1999
1999
The contribution of this paper is to compare paradigms coming from the classes of parametric, and non-parametric techniques to… 
1998
1998
By Stephen A. Barlow, Ian A. Munn, David A. Cleaves, and David L. Evans T he potential impact of urbanization on the South’s… 
1997
1997
A slightly different version of this study is published in the International Journal of Crashworthiness, 1998, Volume 3, Number 2… 
Highly Cited
1995
Highly Cited
1995
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
1987
1987
On considere une forme dynamique du modele de regression logistique en temps discret, comme moyen d'analyse des donnees de…