title: Tutorial in biostatistics: Analyzing associations between total plasma homocysteine and B vitamins using optimal categorization and segmented regression.
abstract: Data analysts consider standard regression models (e.g., generalized linear model) or nonparametric smoothing techniques (e.g., loess or splines) when examining the association between two variables. Before this step, a quantile-based summarization is typically used for exploring the exposure-response relationship. Unfortunately, these exploratory approaches may not be optimal or efficient for guiding the formal analysis in many biological and nutritional data settings. We suggest a recently developed method for selection of cutpoints as a tool of data summary and segmented regression as a modeling approach in the analysis of plasma total homocysteine and related vitamins. These methods are often complementary in discovering the underlying complex pattern of association.
authors.affiliation: Division of Biostatistics and Epidemiology, Department of Public Health, Weill Medical College of Cornell University, New York, NY 10021, USA. heb2013@med.cornell.edu
authors.forename: Heejung
authors.initials: H
authors.lastname: Bang
authors.forename: Madhu
authors.initials: M
authors.lastname: Mazumdar
authors.forename: J David
authors.initials: JD
authors.lastname: Spence
mesh_terms: D000465:Algorithms; D002170:Canada / Q000453:epidemiology; D003627:Data Interpretation, Statistical; D005492:Folic Acid / Q000097:blood; D006710:Homocysteine / Q000097:blood*; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D009749:Nutrition Surveys; D012044:Regression Analysis; D014805:Vitamin B 12 / Q000097:blood; D014803:Vitamin B Complex / Q000097:blood*
chemical_list: D006710:Homocysteine; D014803:Vitamin B Complex; D005492:Folic Acid; D014805:Vitamin B 12