Literature DB >> 1269260

A computer program suitable for fitting linear models when the dependent variable is dichotomous, polichotomous or censored survival and non-linear models when the dependent variable is quantitative.

A Morabito, E Marubini.   

Abstract

Given a set of measurements of s explanatory variables corresponding to each experimental unit, a computer program, whose methodological background can be found in [2] has been written in FORTRAN IV language in order to perform regression analyses when the dependent variable is: (i) dichotomous; (ii) polichotomous; (iii) censored survival. In the two former the Cox's [6] linear logistic models are used while in the third one it has been resorted to the models suggested by Feigl and Zelen [8]. The statistical estimation procedure is maximum likelihood and among the different algorithms developed to reach this goal, the one published by Van der Voort and Dorpema [3], has been utilized. Furthermore, when the dependent variable is quantitative, the program is suitable to fit any function non-linear in the parameters; the pertinent function and its first and second derivatives must be provided by the user. In the present version, implemented on a Univac 1106 machine, the program fits directly the Gompertz function.

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Year:  1976        PMID: 1269260     DOI: 10.1016/0010-468x(76)90056-8

Source DB:  PubMed          Journal:  Comput Programs Biomed        ISSN: 0010-468X


  2 in total

1.  Frequency of contact with community-based psychiatric services and the lunar cycle: a 10-year case-register study.

Authors:  F Amaddeo; G Bisoffi; R Micciolo; M Piccinelli; M Tansella
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  1997-08       Impact factor: 4.328

Review 2.  An analysis of predictor variables for adjuvant treatment of breast cancer.

Authors:  S Kister; J Aroesty; W Rogers; C Huber; K Willis; P Morrison; G Shangold; T Lincoln
Journal:  Cancer Chemother Pharmacol       Date:  1979       Impact factor: 3.333

  2 in total

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