A bayesian approach to modeling associations between pulsatile hormones

Biometrics

Volumn 65, Issue 2, 2009, Pages 650-659

  Carlson, Nichole E ^a   Johnson, Timothy D ^b   Brown, Morton B ^b  

^a UNIVERSITY OF COLORADO   (United States)

^b UNIVERSITY OF MICHIGAN SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Bayesian analysis; Birth death process; Deconvolution; Joint models; MCMC; Mixture models

Indexed keywords

BAYESIAN NETWORKS; ENDOCRINOLOGY; MARKOV PROCESSES; PARAMETER ESTIMATION; SIGNAL TO NOISE RATIO;

BAYESIAN ANALYSIS; BAYESIAN APPROACHES; BIOLOGICAL PROCESS; BIRTH-DEATH PROCESS; DECONVOLUTIONS; ENDOCRINE SYSTEMS; JOINT MODELS; MCMC; MIXTURE MODELING; PULSATILES;

HORMONES;

FOLLITROPIN; LUTEINIZING HORMONE;

BAYESIAN ANALYSIS; BIRTH RATE; CONCENTRATION (COMPOSITION); DECONVOLUTION; ENDOCRINE SYSTEM; HORMONE; MARKOV CHAIN; MODELING; MONTE CARLO ANALYSIS; MORTALITY; PARAMETERIZATION; POPULATION ESTIMATION; SECRETION; SIGNAL-TO-NOISE RATIO;

ARTICLE; BAYES THEOREM; CONTROLLED STUDY; MONTE CARLO METHOD; PROBABILITY; PULSATILE HORMONE RELEASE; SIGNAL NOISE RATIO; SIMULATION; UNIVARIATE ANALYSIS;

EID: 66949167429     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2008.01117.x     Document Type: Article

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