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Titolo:
Analyzing data with clumping at zero - An example demonstration
Autore:
Chang, BH; Pocock, S;
Indirizzi:
New England Res Inst, Watertown, MA 02172 USA New England Res Inst Watertown MA USA 02172 Inst, Watertown, MA 02172 USA Bedford VAMC, Ctr Hlth Qual Outcomes & Econ Res, Bedford, MA 01730 USA Bedford VAMC Bedford MA USA 01730 comes & Econ Res, Bedford, MA 01730 USA London Sch Hyg & Trop Med, Med Stat Unit, London WC1, England London Sch Hyg & Trop Med London England WC1 t Unit, London WC1, England
Titolo Testata:
JOURNAL OF CLINICAL EPIDEMIOLOGY
fascicolo: 10, volume: 53, anno: 2000,
pagine: 1036 - 1043
SICI:
0895-4356(200010)53:10<1036:ADWCAZ>2.0.ZU;2-3
Fonte:
ISI
Lingua:
ENG
Soggetto:
MODELS; VARIABLES;
Keywords:
zero values; proportional odds model; regression analysis;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Life Sciences
Citazioni:
13
Recensione:
Indirizzi per estratti:
Indirizzo: Chang, BH New England Res Inst, 9 Galen St, Watertown, MA 02172 USA New England Res Inst 9 Galen St Watertown MA USA 02172 02172 USA
Citazione:
B.H. Chang e S. Pocock, "Analyzing data with clumping at zero - An example demonstration", J CLIN EPID, 53(10), 2000, pp. 1036-1043

Abstract

This article demonstrates the use of two approaches to analyzing the relationship of multiple covariates to an outcome which has a high proportion ofzero values. One approach is to categorize the continuous outcome (including the zero category) and then fit a proportional odds model. Another approach is to use logistic regression to model the probability of a zero response and ordinary least squares linear regression to model the non-zero continuous responses. The use of these two approaches was demonstrated using outcomes data on hours of care received from the Springfield Elder Project. A crude linear model including both zero and non-zero values was also used for comparison. We conclude that the choice of approaches for analysis depends on the data. If the proportional odds assumption is valid, then it appears to be the method of choice; otherwise, the combination of logistic regression and a linear model is preferable. (C) 2000 Elsevier Science Inc. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 29/09/20 alle ore 20:05:35