نتایج جستجو برای: logistic regression modeling

تعداد نتایج: 704384  

2012
André de Palma Karim Kilani

The logsum formula, which provides the expected maximum utility for the multinomial logit model, is often used as a measure of welfare. We provide here a closed form formula of the welfare measure of an individual who has not access to his first-best choice, but has access to his rth-best choice, r = 2, ...n, where n is the number of alternatives. The derivation is based on a standard identity ...

2004
Alison K. Williams Paul Angermeier Carlyle Brewster Marcella Kelly Dean Stauffer Christopher Zobel Alison K Williams

Databases of species observations from surveys and ad hoc observations are frequently maintained by managers for a particular area. Obtaining information from this type of survey data about the habitat associations of species can be an efficient method of predicting habitat suitability across a landscape. Many multivariate statistical methods have been used to develop models of habitat associat...

1999
Robert A. Vierkant Terry M. Therneau Jon L. Kosanke James M. Naessens

A matched case-control design is a common approach used to assess diseaseexposure relationships, and is often a more efficient method than an unmatched design. However, for the valid analysis of such an approach, a modeling technique that incorporates the matched nature of the data is needed. This prohibits the use of a standard unconditional logistic regression analysis generally available in ...

Journal: :Applied and environmental microbiology 2001
L Zhao Y Chen D W Schaffner

Percentage is widely used to describe different results in food microbiology, e.g., probability of microbial growth, percent inactivated, and percent of positive samples. Four sets of percentage data, percent-growth-positive, germination extent, probability for one cell to grow, and maximum fraction of positive tubes, were obtained from our own experiments and the literature. These data were mo...

2009
George J. Knafl

A SAS macro called genreg is available from the author for conducting adaptive regression modeling. It is written primarily in the matrix language PROC IML and supports nonparametric linear, logistic, and Poisson regression modeling of expected values and/or of variances/dispersions in terms of fractional polynomials in one or more predictor variables. Fractional polynomial models are compared ...

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