The Association Between Persistent Fetal Occiput Posterior Position and Perinatal Outcomes: An Example of Propensity Score and Covariate Distance Matching
Author(s) -
Yunzhong Cheng,
Alan Hubbard,
Aaron B. Caughey,
Ira B. Tager
Publication year - 2010
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwp437
Subject(s) - propensity score matching , medicine , odds ratio , covariate , logistic regression , confidence interval , mahalanobis distance , matching (statistics) , statistics , odds , surgery , mathematics , pathology
In a retrospective cohort study of 18,880 full-term, cephalic singletons born in San Francisco, California, during 1976-2001, the authors used multivariable logistic regression (MVLR) and propensity score analysis (PSA) to examine the association between persistent fetal occiput posterior (OP) position and perinatal outcomes. The principles and applications of these techniques are compared and discussed. Pregnancies with OP positions at delivery were compared with those with occiput anterior positions. Perinatal outcomes were examined as adjusted odds ratios determined by MVLR and PSA and as risk differences determined by propensity score matched bootstrapping based on covariate distance. Persistent OP position was associated with operative delivery and maternal morbidity. The odds ratio estimates based on PSA were somewhat larger than those obtained with standard MVLR, and the confidence intervals were narrower. When statistical inference was evaluated with the permutation test, the results were more consistent with the PSA. These analyses demonstrate that PSA is likely to provide more precise estimates of exposure associations and more reliable statistical inferences than MVLR. The authors show that PSA can be extended with Mahalanobis distance matching to obtain estimates of risk difference between exposed and unexposed subjects that avoid violations of the experimental treatment assignment (positivity) assumption that is required for valid causal inference.
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