Analysis of infant growth curves using multivariate adaptive splines.
In this paper, we study the effect of cocaine use by a pregnant woman on the growth of her infant after birth. Using a data set from a retrospective study, we found that cocaine use was a marginally significant contributor to the infant growth as measured by bodyweight. From a statistical point of view, the data represent a common, though complex, structure that has received little attention in the statistical literature. To analyze these data, we adopt and further enhance an approach developed recently called MASAL (multivariate adaptive splines for the analysis of longitudinal data). In addition to the fitting of growth curves, we demonstrate particularly how to explore and estimate the underlying covariance structures for the longitudinal data that were collected from a rather irregular schedule.
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Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, Connecticut 06520, USA. heping.zhang@yale.edu
D001699:Biometry; D001835:Body Weight; D002657:Child Development; D019970:Cocaine-Related Disorders / Q000150:complications; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008137:Longitudinal Studies; D008297:Male; D008431:Maternal-Fetal Exchange; D015233:Models, Statistical; D015999:Multivariate Analysis; D011247:Pregnancy; D011248:Pregnancy Complications