title: A multivariate Bayesian model for embryonic growth.
abstract: Most longitudinal growth curve models evaluate the evolution of each of the anthropometric measurements separately. When applied to a 'reference population', this exercise leads to univariate reference curves against which new individuals can be evaluated. However, growth should be evaluated in totality, that is, by evaluating all body characteristics jointly. Recently, Cole et al. suggested the Superimposition by Translation and Rotation (SITAR) model, which expresses individual growth curves by three subject-specific parameters indicating their deviation from a flexible overall growth curve. This model allows the characterization of normal growth in a flexible though compact manner. In this paper, we generalize the SITAR model in a Bayesian way to multiple dimensions. The multivariate SITAR model allows us to create multivariate reference regions, which is advantageous for prediction. The usefulness of the model is illustrated on longitudinal measurements of embryonic growth obtained in the first semester of pregnancy, collected in the ongoing Rotterdam Predict study. Further, we demonstrate how the model can be used to find determinants of embryonic growth.
authors.affiliation: Department of Biostatistics, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Obstetrics and Gynaecology, Erasmus University Medical Center, Rotterdam, the Netherlands.
authors.forename: Sten P
authors.initials: SP
authors.lastname: Willemsen
authors.forename: Paul H C
authors.initials: PH
authors.lastname: Eilers
authors.forename: Régine P M
authors.initials: RP
authors.lastname: Steegers-Theunissen
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Lesaffre
mesh_terms: D000328:Adult; D000428:Alcohol Drinking / Q000009:adverse effects; D000704:Analysis of Variance; D001499:Bayes Theorem; D015992:Body Mass Index; D047108:Embryonic Development; D005260:Female; D005544:Forecasting; D006801:Humans; D008137:Longitudinal Studies; D008423:Maternal Age; D008954:Models, Biological; D015999:Multivariate Analysis; D009426:Netherlands; D010298:Parity; D016742:Preconception Care; D011247:Pregnancy; D011256:Pregnancy Outcome; D011261:Pregnancy Trimester, First; D018566:Pregnancy, High-Risk; D012907:Smoking / Q000009:adverse effects; D016216:Ultrasonography, Prenatal
keywords: Bayesian modeling; growth curves; multivariate statistics