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Summary: We propose a hierarchical Gaussian locally linear mapping structured mixture model, named HGLLiM, to predict low dimensional responses based on high dimensional covariates when the associations between the responses and the covariates are non‐linear. For tractability, HGLLiM adopts inverse regression to handle the high dimension and locally linear mappings to capture potentially non‐linear relations. Data with similar associations are grouped together to form a cluster. A mixture is composed of several clusters following a hierarchical structure. This structure enables shared covariance matrices and latent factors across smaller clusters to limit the number of parameters to estimate. Moreover, HGLLiM adopts a robust estimation procedure for model stability. We use three real data sets to demonstrate different features of HGLLiM. With the face data set, HGLLiM shows ability to model non‐linear relationships through mixtures. With the orange juice data set, we show that the prediction performance of HGLLiM is robust to the presence of outliers. Moreover, we demonstrate that HGLLiM is capable of handling large‐scale complex data by using the data acquired from a magnetic resonance vascular fingerprinting study. These examples illustrate the wide applicability of HGLLiM to handle different aspects of a complex data structure in prediction. [ABSTRACT FROM AUTHOR]

The Penn Ovarian Aging Study tracked a population-based sample of 436 women aged 35-47 years to determine associations between reproductive hormone levels and menopausal symptoms. We develop a joint modelling method that uses the individual level longitudinal measurements of follicle stimulating hormone (FSH) to predict the risk of severe hot flashes in a manner that distinguishes long-term trends of the mean trajectory, cumulative changes captured by the derivative of mean trajectory and short-term residual variability. Our method allows the potential effects of longitudinal trajectories on the health risks to vary and accumulate over time. We further utilize the proposed methods to narrow the critical time windows of increased health risks. We find that high residual variation of FSH is a strong predictor of hot flash risk, and that the high cumulative changes of the FSH mean trajectories in the 52.5-55-year age range also provides evidence of increased risk over that of short-term FSH residual variation by itself. [ABSTRACT FROM AUTHOR]

Joint modeling methods have become popular tools to link important features extracted from longitudinal data to a primary event. While most modeling strategies have focused on the association between the longitudinal mean trajectories and risk of an event, we consider joint models that incorporate information from both long-term trends and short-term variability in a longitudinal submodel. We also consider both shared random effect and latent class (LC) approaches in the primary-outcome model to predict a binary outcome of interest. We develop simulation studies to compare and contrast these two modeling strategies; in particular, we study in detail the effects of the primary-outcome model misspecification. Among other findings, we note that when we analyze data from a shared random-effect using a LC model while the information from the longitudinal data is weak, the LC approach is more sensitive to such a model misspecification. Under this setting, the LC model has a superior performance in within-sample prediction that cannot be duplicated when predicting new samples. This is a unique feature of the LC approach that is new as far as we know to the existing literature. Finally, we use the proposed models to study how follicle stimulating hormone (FSH) trajectories are related to the risk of developing severe hot flashes for participating women in the Penn Ovarian Aging Study. [ABSTRACT FROM AUTHOR]

We introduce the effective balancing score for estimation of the mean response under a missing-at-random mechanism. Unlike conventional balancing scores, the proposed score is constructed via dimension reduction free of model specification. Three types of such scores are introduced, distinguished by whether they carry the covariate information about the missingness, the response, or both. The effective balancing score leads to consistent estimation with little or no loss in efficiency. Compared to existing estimators, it reduces the burden of model specification and is more robust. It is a near-automatic procedure which is most appealing when high-dimensional covariates are involved. We investigate its asymptotic and numerical properties, and illustrate its application with an HIV disease study. [ABSTRACT FROM PUBLISHER]

The article discusses changes to the periodical "Biometrics," published by the International Biometrics Society (IBS).

The article presents information on the changes to the journal "Biometrics" in 2007.

There is now general agreement that the etiology of proximal and distal colon cancers may differ, thus prompting renewed interest in understanding anatomical site-specific molecular mechanisms of tumor development. Using a 2×2×2 factorial design with male Sprague–Dawley rats (corn oil, fish oil; pectin, cellulose; plus or minus azoxymethane injection) we found a greater than 2-fold difference (P < 0.001) in tumor incidence proximally versus distally (prox/dist ratio: corn oil, 2.25; fish oil, 2.61). The purpose of the present study was to determine if the higher degree of proximal versus distal tumors in our model system could be accounted for by differences between these two sites in initial DNA damage, response to that damage or an effect of diet at one site but not the other. DNA damage was assessed by quantitative immunohistochemistry of O6-methylguanine adducts; repair by measurement of O6-methylguanine-DNA alkyltransferase and removal was determined by measurement of targeted apoptosis. Although overall initial DNA damage was similar at both sites, in the distal colon there was a greater expression of repair protein (P < 0.001) and a greater degree of targeted apoptosis (P < 0.0001). There was also a reduction in DNA damage in the distal colon of rats consuming fish oil. Together, these results suggest that the lower tumor incidence in the distal colon may be a result of the capacity to deal with initial DNA damage by the distal colon, as compared with the proximal colon. Therefore, the determination of site-specific mechanisms in tumor development is important because distinct strategies may be required to protect against cancer at different sites. [ABSTRACT FROM PUBLISHER]

We have recently demonstrated that overexpression of PKC βII renders transgenic mice more susceptible to carcinogen-induced colonic hyperproliferation and aberrant crypt foci formation. In order to further investigate the ability of PKC βII to modulate colonocyte cytokinetics, we determined the localization of PKC βII with respect to cell proliferation and apoptosis along the entire colonic crypt axis following carcinogen and diet manipulation. Rats were provided diets containing either corn oil [containing n-6 polyunsaturated fatty acids (PUFA)] or fish oil (containing n-3 PUFA), cellulose (non-fermentable fiber) or pectin (fermentable fiber) and injected with azoxymethane (AOM) or saline. After 16 weeks, an intermediate time point when no macroscopic tumors are detected, colonic sections were utilized for immunohistochemical image analysis and immunoblotting. Cell proliferation was measured by incorporation of bromodeoxyuridine into DNA and apoptosis by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end-labeling. In the distal colon, PKC βII staining was localized to the upper portion of the crypt. In comparison, proximal crypts had more (P < 0.05) staining in the lower tertile. AOM enhanced (P < 0.05) PKC βII expression in all regions of the distal colonic crypt (upper, middle and lower tertiles). There was also an interaction (P < 0.05) between dietary fat and fiber on PKC βII expression (corn/pectin > fish/cellulose, fish/pectin > corn/cellulose) in all regions of the distal colonic crypt. With respect to colonic cell kinetics, proliferation paralleled the increase in PKC βII expression in carcinogen-treated animals. In contrast, apoptosis at the lumenal surface was inversely proportional to PKC βII expression in the upper tertile. These results suggest that an elevation in PKC βII expression along the crypt axis in the distal colon is linked to enhancement of cell proliferation and suppression of apoptosis, predictive intermediate biomarkers of tumor development. Therefore, select dietary factors may confer protection against colon carcinogenesis in part by blocking carcinogen-induced PKC βII expression. [ABSTRACT FROM PUBLISHER]

We consider the asymptotic behaviour of various parametric multiple imputation procedures which include but are not restricted to the ‘proper’ imputation procedures proposed by Rubin (1978). The asymptotic variance structure of the resulting estimators is provided. This result is used to compare the relative efficiencies of different imputation procedures. It also provides a basis to understand the behaviour of two Monte Carlo iterative estimators, stochastic EM (Celeux & Diebolt, 1985; Wei & Tanner, 1990) and simulated EM (Ruud, 1991). We further develop properties of these estimators when they stop at iteration K with imputation size m. An application to a measurement error problem is used to illustrate the results. [ABSTRACT FROM AUTHOR]

Little is known about the effects of measurement error in intra-individual covariates on inference for the nonlinear mixed effects model. We investigate this issue for a controlled variable measurement error model, and find that a major consequence may be substantial bias in estimates of parameters characterising intra-individual variation. Estimation of population parameters may also be affected. The dramatic effect of measurement error on estimation of intra-individual variance parameters has implications not only in the repeated measurement context, but also in individual nonlinear regression models. [ABSTRACT FROM AUTHOR]