How to deal with continuous and dichotomic outcomes in epidemiological research: Linear and logistic regression analyses

Nephron - Clinical Practice

Volumn 118, Issue 4, 2011, Pages

  Tripepi, Giovanni ^a   Jager, Kitty J ^b   Stel, Vianda S ^b   Dekker, Friedo W ^b,c   Zoccali, Carmine ^a  

^a CNR Consiglio Nazionale delle Ricerche   (Italy)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

^c LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

Confounding; Linear regression analyses; Logistic regression analysis; Multiple regression analysis

Indexed keywords

ARTICLE; CONFOUNDING VARIABLE; HUMAN; LINEAR REGRESSION ANALYSIS; LOGISTIC REGRESSION ANALYSIS; MEDICAL RESEARCH; METHODOLOGY; MICROALBUMINURIA; MULTIPLE LINEAR REGRESSION ANALYSIS; MULTIVARIATE LOGISTIC REGRESSION ANALYSIS; OUTCOME ASSESSMENT; PRACTICE GUIDELINE; PRIORITY JOURNAL; STATISTICAL ANALYSIS;

BLOOD GLUCOSE; DATA INTERPRETATION, STATISTICAL; EPIDEMIOLOGIC STUDIES; HUMANS; LINEAR MODELS; LOGISTIC MODELS; REGRESSION ANALYSIS; TIME FACTORS; TREATMENT OUTCOME;

EID: 79951853465     PISSN: None     EISSN: 16602110     Source Type: Journal    
DOI: 10.1159/000324049     Document Type: Article

References (8)

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