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Lisa G Smithers, Ben W Mol, Chris Wilkinson, John W Lynch
BACKGROUND: Caesarean birth is one of the most frequently performed major obstetrical interventions. Although there is speculation that caesarean at term may have consequences for children's later health and development, longer-term studies are needed. AIM: We aimed to evaluate risks to poor school achievement among children born by caesarean section compared with spontaneous vaginal birth. MATERIALS AND METHODS: This population-based observational study involved linkage of routinely collected perinatal data with children's school assessments...
August 2016: Australian & New Zealand Journal of Obstetrics & Gynaecology
Michelle Shardell, Gregory E Hicks, Luigi Ferrucci
Motivated by aging research, we propose an estimator of the effect of a time-varying exposure on an outcome in longitudinal studies with dropout and truncation by death. We use an inverse-probability weighted (IPW) estimator to derive a doubly robust augmented inverse-probability weighted (AIPW) estimator. IPW estimation involves weights for the exposure mechanism, dropout, and mortality; AIPW estimation additionally involves estimating data-generating models via regression. We demonstrate that the estimators identify a causal contrast that is a function of principal strata effects under a set of assumptions...
January 2015: Biostatistics
Yuanjia Wang, Tanya P Garcia, Yanyuan Ma
This work presents methods for estimating genotype-specific distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estimators (NPMLEs) which do not make parametric assumptions on the genotype-specific density functions...
2012: Journal of the American Statistical Association
Lu Wang, Andrea Rotnitzky, Xihong Lin
We consider nonparametric regression of a scalar outcome on a covariate when the outcome is missing at random (MAR) given the covariate and other observed auxiliary variables. We propose a class of augmented inverse probability weighted (AIPW) kernel estimating equations for nonparametric regression under MAR. We show that AIPW kernel estimators are consistent when the probability that the outcome is observed, that is, the selection probability, is either known by design or estimated under a correctly specified model...
September 2010: Journal of the American Statistical Association
E J Williamson, A Forbes, R Wolfe
We consider the estimation of the causal effect of a binary exposure on a continuous outcome. Confounding and missing data are both likely to occur in practice when observational data are used to estimate this causal effect. In dealing with each of these problems, model misspecification is likely to introduce bias. We present augmented inverse probability weighted (AIPW) estimators that account for both confounding and missing data, with the latter occurring in a single variable only. These estimators have an element of robustness to misspecification of the models used...
December 30, 2012: Statistics in Medicine
Gailen D Marshall et al.
The American Academy of Allergy, Asthma & Immunology has tracked the US allergy/immunology physician workforce (AIPW) over the past 3 decades by funding 2 workforce surveys (1999, 2004). Results have demonstrated both accomplishments of and challenges for the US AIPW. Accomplishments include increases in diversity (25% women in 2004, 20% in 1999, 10% in 1989; 6% underrepresented minorities in 2004, 5% in 1999), 95% of AIPW has completed an allergy/immunology (A/I) training program, and 91% are American Board of Allergy and Immunology (a conjoint board of the American Board of Internal Medicine and the American Board of Pediatrics)-certified (90% in 1999)...
April 2007: Journal of Allergy and Clinical Immunology
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