Literature DB >> 3383562

RECPAM: a computer program for recursive partition and amalgamation for censored survival data and other situations frequently occurring in biostatistics. I. Methods and program features.

A Ciampi1, S A Hogg, S McKinney, J Thiffault.   

Abstract

The methodology of recursive partition and amalgamation in biostatistics is presented and a FORTRAN program for its implementation, RECPAM, is described. RECPAM can be used to obtain classifications of patients according to several criteria commonly occurring in clinical biostatistics: an example is prognostic classification based on survival data. Classes are defined by simple statements, expressed in clinical terms, about predictor variables (e.g. prognostic factors). Special features of RECPAM are: the possibility of implementing a variety of classification criteria, the integration of recursive partition and amalgamation, and the availability of several strategies for constructing classification trees. A simple example to illustrate input and output features is given. The scope and flexibility of RECPAM will be illustrated in greater detail in a subsequent paper.

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Year:  1988        PMID: 3383562     DOI: 10.1016/0169-2607(88)90004-1

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


  14 in total

1.  Survival trees: an alternative non-parametric multivariate technique for life history analysis.

Authors:  A De Rose; A Pallara
Journal:  Eur J Popul       Date:  1997

2.  L₁ splitting rules in survival forests.

Authors:  Hoora Moradian; Denis Larocque; François Bellavance
Journal:  Lifetime Data Anal       Date:  2016-07-05       Impact factor: 1.588

3.  Controlled trial of high- versus low-dose aspirin treatment after percutaneous transluminal angioplasty in patients with peripheral vascular disease.

Authors:  C Ranke; A Creutzig; G Luska; H H Wagner; M Galanski; S Bode-Böger; J Frölich; H J Avenarius; H Hecker; K ALexander
Journal:  Clin Investig       Date:  1994-09

4.  Derivation and validation of a clinical decision rule to identify young children with skull fracture following isolated head trauma.

Authors:  Jocelyn Gravel; Serge Gouin; Dominic Chalut; Louis Crevier; Jean-Claude Décarie; Nicolas Elazhary; Benoît Mâsse
Journal:  CMAJ       Date:  2015-09-08       Impact factor: 8.262

Review 5.  RECPAM analysis of prognostic factors in patients with stage III breast cancer.

Authors:  C Erlichman; P Warde; T Gadalla; A Ciampi; T Baskerville
Journal:  Breast Cancer Res Treat       Date:  1990-10       Impact factor: 4.872

6.  Psychosocial distress in oncology: using the distress thermometer for assessing risk classes.

Authors:  Claudia Cormio; Francesca Caporale; Roberta Spatuzzi; Fulvia Lagattolla; Andrea Lisi; Giusi Graziano
Journal:  Support Care Cancer       Date:  2019-02-20       Impact factor: 3.603

7.  Non-albuminuric renal impairment is a strong predictor of mortality in individuals with type 2 diabetes: the Renal Insufficiency And Cardiovascular Events (RIACE) Italian multicentre study.

Authors:  Giuseppe Penno; Anna Solini; Emanuela Orsi; Enzo Bonora; Cecilia Fondelli; Roberto Trevisan; Monica Vedovato; Franco Cavalot; Olga Lamacchia; Marco Scardapane; Antonio Nicolucci; Giuseppe Pugliese
Journal:  Diabetologia       Date:  2018-07-21       Impact factor: 10.122

8.  Recursively Imputed Survival Trees.

Authors:  Ruoqing Zhu; Michael R Kosorok
Journal:  J Am Stat Assoc       Date:  2011-12-06       Impact factor: 5.033

9.  Artificial neural networks versus proportional hazards Cox models to predict 45-year all-cause mortality in the Italian Rural Areas of the Seven Countries Study.

Authors:  Paolo Emilio Puddu; Alessandro Menotti
Journal:  BMC Med Res Methodol       Date:  2012-07-23       Impact factor: 4.615

10.  Establishing long-term efficacy in chronic disease: use of recursive partitioning and propensity score adjustment to estimate outcome in MS.

Authors:  Douglas S Goodin; Jason Jones; David Li; Anthony Traboulsee; Anthony T Reder; Karola Beckmann; Andreas Konieczny; Volker Knappertz
Journal:  PLoS One       Date:  2011-11-30       Impact factor: 3.240

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