Literature DB >> 3595103

ISMOD: an all-subsets regression program for generalized linear models. II. Program guide and examples.

J F Lawless, K Singhal.   

Abstract

This paper describes a system written to carry out regression analyses under certain generalized linear models that are widely used in biomedical research. These include continuous response models such as the Weibull, log logistic, log normal and Cox proportional hazards models used in survival analysis, and also discrete Poisson, binomial and multinomial response regression models. The system fits models, generates residuals and other diagnostic output, and also has an all-subsets regression feature. This paper describes the ISMOD system and presents examples of its application; Part I describes the models implemented and gives statistical background.

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Year:  1987        PMID: 3595103     DOI: 10.1016/0169-2607(87)90023-x

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  5 in total

1.  Variable selection with stepwise and best subset approaches.

Authors:  Zhongheng Zhang
Journal:  Ann Transl Med       Date:  2016-04

2.  Comparison of Atmospheric Fungal Spore Concentrations between Two Main Cities in the Caribbean Basin.

Authors:  Félix E Rivera-Mariani; Michel Almaguer; María Jesús Aira; Benjamín Bolaños-Rosero
Journal:  P R Health Sci J       Date:  2020-09       Impact factor: 0.705

3.  A comparison of all-subset Cox and accelerated failure time models with Cox step-wise regression for node-positive breast cancer.

Authors:  J A Chapman; M E Trudeau; K I Pritchard; C A Sawka; B G Mobbs; W M Hanna; H Kahn; D R McCready; L A Lickley
Journal:  Breast Cancer Res Treat       Date:  1992       Impact factor: 4.872

4.  Bayesian Framework to Augment Tumor Board Decision Making.

Authors:  Stefano Pasetto; Robert A Gatenby; Heiko Enderling
Journal:  JCO Clin Cancer Inform       Date:  2021-05

5.  Prognostic value of urokinase-type plasminogen activator (uPA) and plasminogen activator inhibitors PAI-1 and PAI-2 in breast carcinomas.

Authors:  C Bouchet; F Spyratos; P M Martin; K Hacène; A Gentile; J Oglobine
Journal:  Br J Cancer       Date:  1994-02       Impact factor: 7.640

  5 in total

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