A Bayesian growth mixture model to examine maternal hypertension and birth outcomes

Statistics in Medicine

Volumn 30, Issue 22, 2011, Pages 2721-2735

  Neelon, Brian ^a   Swamy, Geeta K ^b   Burgette, Lane F ^c   Miranda, Marie Lynn ^a  

^a DUKE UNIVERSITY   (United States)

^b DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c Duke University   (United States)

Author keywords

Bayesian analysis; Birth outcomes; Correlated probit model; Growth mixture model; Latent trajectory model; Maternal hypertension

Indexed keywords

ADULT; ANALYSIS OF COVARIANCE; ARTICLE; BAYES THEOREM; BAYESIAN GROWTH MIXTURE MODEL; BLOOD PRESSURE MEASUREMENT; CONTROLLED STUDY; CORRELATION ANALYSIS; FEMALE; HUMAN; LONGITUDINAL STUDY; LOW BIRTH WEIGHT; MAJOR CLINICAL STUDY; MATERNAL HYPERTENSION; MATHEMATICAL ANALYSIS; MEAN ARTERIAL PRESSURE; PREGNANCY OUTCOME; PREMATURE LABOR; REGRESSION ANALYSIS; STATISTICAL MODEL;

ADOLESCENT; ADULT; ALGORITHMS; BAYES THEOREM; COHORT STUDIES; FEMALE; HUMANS; HYPERTENSION; INFANT, LOW BIRTH WEIGHT; INFANT, NEWBORN; INFANT, PREMATURE; LONGITUDINAL STUDIES; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; PREGNANCY; PREGNANCY COMPLICATIONS, CARDIOVASCULAR; PREGNANCY OUTCOME; YOUNG ADULT;

EID: 80052860563     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4291     Document Type: Article

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