Estimating net transition probabilities from cross-sectional data with application to risk factors in chronic disease modeling

Statistics in Medicine

Volumn 31, Issue 6, 2012, Pages 533-543

  van de Kassteele, J ^a   Hoogenveen, R T ^a   Engelfriet, P M ^a   van Baal, P H M ^a,b   Boshuizen, H C ^a  

^a NATIONAL INSTITUTE FOR PUBLIC HEALTH AND THE ENVIRONMENT   (Netherlands)

^b ERASMUS UNIVERSITY ROTTERDAM   (Netherlands)

Author keywords

Linear programming; Multistate modeling; Smoothing; Transition probabilities

Indexed keywords

ACCURACY; ADOLESCENT; ADULT; AGED; ALGORITHM; ARTICLE; BODY MASS; BOOTSTRAPPING; CHILD; CHRONIC DISEASE; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; DATA ANALYSIS; DISEASE MODEL; HUMAN; INFANT; LINEAR SYSTEM; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL COMPUTING; PREDICTION; PRESCHOOL CHILD; PROBABILITY; RISK ASSESSMENT; RISK FACTOR; SCHOOL CHILD; SENSITIVITY AND SPECIFICITY; SIGNAL NOISE RATIO; STATISTICAL ANALYSIS; UNCERTAINTY; WEIGHT CHANGE;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; BODY MASS INDEX; CHILD; CHILD, PRESCHOOL; CHRONIC DISEASE; CROSS-SECTIONAL STUDIES; HUMANS; INFANT; MALE; MIDDLE AGED; MODELS, BIOLOGICAL; NETHERLANDS; OVERWEIGHT; PREVALENCE; RISK FACTORS; YOUNG ADULT;

EID: 84857032115     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4423     Document Type: Article

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