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A simulation study on SPSS ridge regression and ordinary least squares regression procedures for multicollinearity data

Zhang, John; Ibrahim, Mahmud - In: Journal of Applied Statistics 32 (2005) 6, pp. 571-588

This study compares the SPSS ordinary least squares (OLS) regression and ridge regression procedures in dealing with multicollinearity data. The LS regression method is one of the most frequently applied statistical procedures in application. It is well documented that the LS method is extremely...

Persistent link: https://www.econbiz.de/10005492136

A permutation test approach to the choice of size k for the nearest neighbors classifier

Lai, Yinglei; Wu, Baolin; Zhao, Hongyu - In: Journal of Applied Statistics 38 (2011) 10, pp. 2289-2302

usefulness of our approach is demonstrated through the evaluation of prediction accuracies using Z-score as a criterion to select … selected by our approach yields high prediction accuracies when informative features are used for classification, whereas the …

Persistent link: https://www.econbiz.de/10009279030

Logistic and neural network models for predicting a hospital admission

Adams, Joseph Brian; Wert, Yijin - In: Journal of Applied Statistics 32 (2005) 8, pp. 861-869

Feedforward neural networks are often used in a similar manner as logistic regression models; that is, to estimate the probability of the occurrence of an event. In this paper, a probabilistic model is developed for the purpose of estimating the probability that a patient who has been admitted...

Persistent link: https://www.econbiz.de/10005141257

Strategies for inference robustness in focused modelling

Spiegelhalter, D. J.; Marshall, E. C. - In: Journal of Applied Statistics 33 (2006) 2, pp. 217-232

across all candidate models. It is, therefore, applicable to analyses whose goal is prediction, or where a set of common …

Persistent link: https://www.econbiz.de/10005492067

Measures of fit in principal component and canonical variate analyses

Gardner-Lubbe, Sugnet; Roux, Niël Le; Gowers, John - In: Journal of Applied Statistics 35 (2008) 9, pp. 947-965

Treating principal component analysis (PCA) and canonical variate analysis (CVA) as methods for approximating tables, we develop measures, collectively termed predictivity, that assess the quality of fit independently for each variable and for all dimensionalities. We illustrate their use with...

Persistent link: https://www.econbiz.de/10005495257

Test and prediction in factorial models with independent variance estimates

Mark, Sigyn; Holm, Sture - In: Journal of Applied Statistics 35 (2008) 7, pp. 773-782

requiring that the tests have a multiple level of significance. Also, a prediction problem in an application with several … done in the methods commonly used to choose predictor variables. Here, we discuss both the test and prediction methods in …. By an example use demonstrated that the principle proposed leads to the use of fewer prediction variables than does the …

Persistent link: https://www.econbiz.de/10005495269

Bayesian non-parametric models for regional prevalence estimation

Branscum, Adam; Hanson, Timothy; Gardner, Ian - In: Journal of Applied Statistics 35 (2008) 5, pp. 567-582

We developed a flexible non-parametric Bayesian model for regional disease-prevalence estimation based on cross-sectional data that are obtained from several subpopulations or clusters such as villages, cities, or herds. The subpopulation prevalences are modeled with a mixture distribution that...

Persistent link: https://www.econbiz.de/10005639842