An estimating equations approach to fitting latent exposure models with longitudinal health outcomes

The analysis of data arising from environmental health studies which collect a large number of measures of exposure can benefit from using latent variable models to summarize exposure information. However, difficulties with estimation of model parameters may arise since existing fitting procedures for linear latent variable models require correctly specified residual variance structures for unbiased estimation of regression parameters quantifying the association between (latent) exposure and health outcomes. We propose an estimating equations approach for latent exposure models with longitudinal health outcomes which is robust to misspecification of the outcome variance. We show that compared to maximum likelihood, the loss of efficiency of the proposed method is relatively small when the model is correctly specified. The proposed equations formalize the ad-hoc regression on factor scores procedure, and generalize regression calibration. We propose two weighting schemes for the equations, and compare their efficiency. We apply this method to a study of the effects of in-utero lead exposure on child development.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS226 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

On the "Poisson Trick" and its Extensions for Fitting Multinomial Regression Models

This article is concerned with the fitting of multinomial regression models using the so-called "Poisson Trick". The work is motivated by Chen & Kuo (2001) and Malchow-M{\o}ller & Svarer (2003) which have been criticized for being computationally inefficient and sometimes producing nonsense results. We first discuss the case of independent data and offer a parsimonious fitting strategy when all covariates are categorical. We then propose a new approach for modelling correlated responses based on an extension of the Gamma-Poisson model, where the likelihood can be expressed in closed-form. The parameters are estimated via an Expectation/Conditional Maximization (ECM) algorithm, which can be implemented using functions for fitting generalized linear models readily available in standard statistical software packages. Compared to existing methods, our approach avoids the need to approximate the intractable integrals and thus the inference is exact with respect to the approximating Gamma-Poisson model. The proposed method is illustrated via a reanalysis of the yogurt data discussed by Chen & Kuo (2001)

Characteristics and Enablers of Transparency in Product Development Organizations

Risks in product development lead to schedule and cost overruns and poor product quality. While many risk management frameworks have been published and research on specific practices has been conducted, little is understood of key characteristics of successful risk management in product development and how they manifest in real development projects. This research consists of two phases. The first phase is a survey on 171 best practices in risk management. Analysis of over 200 responses from industry practitioners identified transparency as a key characteristic of successful risk management in product development. Due to the limited exploration of the concept of transparency in the literature, the second phase of this work consisted of a qualitative investigation of transparency through interviews with 15 industry practitioners. Analysis of the interview results suggests a hierarchical structure which decomposes transparency into several characteristics and identifies enablers for each of these characteristics. We propose that transparency can be a valuable lever for product developers and managers. Future work is needed to validate the generalizability of the observations provided

The relationship between human semen parameters and environmental exposure to polychlorinated biphenyls and p,p′p,p'-DDE

Scientific and public concern exists about potential reproductive health effects of persistent chlorinated organic chemicals, such as polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethane (DDT), and dichlorodiphenyldichloroethylene (DDE, the most stable daughter compound of DDT). To explore the hypothesis that environmental exposures to PCBs and DDE are associated with altered semen parameters, we conducted a cross-sectional study of 212 male partners of subfertile couples who presented to the Massachusetts General Hospital Andrology Laboratory. Semen parameters were analyzed as both a continuous measure and dichotomized based on World Health Organization reference values for sperm concentration (< 20 million/mL), motility (< 50% motile), and Kruger strict criteria for morphology (< 4% normal). The comparison group for the dichotomized analysis was men with all three semen parameters above the reference values. In serum, 57 PCB congeners and $p,p'$-DDE were measured by congener-specific analysis using gas chromatography with electron capture detection. There were dose-response relationships among PCB-138 and sperm motility (odds ratio per tertile, adjusted for age, abstinence, and smoking, and $p$-value for trend were, respectively, 1.00, 1.68, 2.35, and $p$-value = 0.03) and morphology (1.00, 1.36, 2.53, $p$-value = 0.04). There was limited evidence of an inverse relationship between sum of PCBs, as well as those PCBs classified as cytochrome P450 enzyme inducers, with sperm motility and sperm morphology, as well as limited evidence of an inverse association between $p,p'$-DDE and sperm motility. The lack of a consistent relationship among semen parameters and other individual PCB congeners and groupings of congeners may indicate a difference in spermatotoxicity between congeners