Development of Markov random field models based on exponential family conditional distributions

Constructing statistical models through the specification of conditional distributions is being recognized as an appealing approach to a multivariate data analysis. A useful class of such models may be formulated by assuming that the conditional distributions are specified as exponential families. The class of exponential family conditional (EFC) models is expected to provide a general model framework that may be applied to a wide variety of situations that may contain complex dependence structures. The overall objective of this study is to develop and refine the general methodology for EFC models.;Among a number of EFC models that have been studied by far, the Gaussian conditionals family has attracted a major interest, both theoretically and practically, and has been applied to many problems. Unfortunately, many of the nice properties and results that are available for Gaussian conditionals models are not transferable to non-Gaussian EFC models, and we need to develop adequate procedures for modeling, estimation and inference for a generalized class of EFC models. Among a number of issues associated with such general EFC models, we are mainly concerned in this study with three problems: (1) developing a general procedure of MRF construction using multi-parameter exponential families, (2) application of the general procedure to a problem of spatial, categorical data analysis, and (3) investigating useful parameterizations of EFC models

Development of Markov random field models based on exponential family conditional distributions

Constructing statistical models through the specification of conditional distributions is being recognized as an appealing approach to a multivariate data analysis. A useful class of such models may be formulated by assuming that the conditional distributions are specified as exponential families. The class of exponential family conditional (EFC) models is expected to provide a general model framework that may be applied to a wide variety of situations that may contain complex dependence structures. The overall objective of this study is to develop and refine the general methodology for EFC models.;Among a number of EFC models that have been studied by far, the Gaussian conditionals family has attracted a major interest, both theoretically and practically, and has been applied to many problems. Unfortunately, many of the nice properties and results that are available for Gaussian conditionals models are not transferable to non-Gaussian EFC models, and we need to develop adequate procedures for modeling, estimation and inference for a generalized class of EFC models. Among a number of issues associated with such general EFC models, we are mainly concerned in this study with three problems: (1) developing a general procedure of MRF construction using multi-parameter exponential families, (2) application of the general procedure to a problem of spatial, categorical data analysis, and (3) investigating useful parameterizations of EFC models.</p

Effects of Omitting Non-confounding Predictors From General Relative-Risk Models for Binary Outcomes

Background: The effects, in terms of bias and precision, of omitting non-confounding predictive covariates from generalized linear models have been well studied, and it is known that such omission results in attenuation bias but increased precision with logistic regression. However, many epidemiologic risk analyses utilize alternative models that are not based on a linear predictor, and the effect of omitting non-confounding predictive covariates from such models has not been characterized. Methods: We employed simulation to study the effects on risk estimation of omitting non-confounding predictive covariates from an excess relative risk (ERR) model and a general additive-multiplicative relative-risk mixture model for binary outcome data in a case-control setting. We also compared the results to the effects with ordinary logistic regression. Results: For these commonly employed alternative relative-risk models, the bias was similar to that with logistic regression when the risk was small. More generally, the bias and standard error of the risk-parameter estimates demonstrated patterns that are similar to those with logistic regression, but with greater magnitude depending on the true value of the risk. The magnitude of bias and standard error had little relation to study size or underlying disease prevalence. Conclusions: Prior conclusions regarding omitted covariates in logistic regression models can be qualitatively applied to the ERR and the general additive-multiplicative relative-risk mixture model without substantial change. Quantitatively, however, these alternative models may have slightly greater omitted-covariate bias, depending on the magnitude of the true risk being estimated

Effect of Angiotensin Converting Enzyme Inhibitor and Benzodiazepine Intake on Bone Loss in Older Japanese

We investigated the effects of several frequently described medication regimens on annual percentage change in bone mineral density (BMD). A longitudinal cohort study (a retrospective analysis) was conducted. Subjects in the Adult Health Study (a prospective cohort study begun in 1958) have been followed through biennial medical examinations in Hiroshima, Japan. Participants were 2,111 subjects (67% women; aged 47-95 years) who were undergoing biennial health examinations from 1994 to 2000. The subjects were examined for the effect of certain drugs on bone mineral change during baseline and one follow-up (4 year later) measurements. Mean annual percentage change in BMD at the femoral neck was -0.38% for men, and -1.14% for women. After adjustment for sex, age, change of weight, alcohol consumption, and smoking status, annual percentage change in BMD decreased by 0.61 % among individuals taking angiotensin converting enzyme (ACE) inhibitors continuously in comparison with individuals who had not taken them (p=0.002): also decreased 0.40% among individuals taking benzodiazepines (BZDs) continuously (p=0.034). Our results suggest that careful consideration should be given to the use of ACE inhibitors and BZDs in a cohort of Japanese elderly

Temporal Changes in Sparing and Enhancing Dose Protraction Effects of Ionizing Irradiation for Aortic Damage in Wild-Type Mice

In medical and occupational settings, ionizing irradiation of the circulatory system occurs at various dose rates. We previously found sparing and enhancing dose protraction effects for aortic changes in wild-type mice at 6 months after starting irradiation with 5 Gy of photons. Here, we further analyzed changes at 12 months after stating irradiation. Irrespective of irradiation regimens, irradiation little affected left ventricular function, heart weight, and kidney weight. Irradiation caused structural disorganizations and intima-media thickening in the aorta, along with concurrent elevations of markers for proinflammation, macrophage, profibrosis, and fibrosis, and reductions in markers for vascular functionality and cell adhesion in the aortic endothelium. These changes were qualitatively similar but quantitatively less at 12 months than at 6 months. The magnitude of such changes at 12 months was not smaller in 25 fractions (Frs) but was smaller in 100 Frs and chronic exposure than acute exposure. The magnitude at 6 and 12 months was greater in 25 Frs, smaller in 100 Frs, and much smaller in chronic exposure than acute exposure. These findings suggest that dose protraction changes aortic damage, in a fashion that depends on post-irradiation time and is not a simple function of dose rate

Congenital Malformations and Perinatal Deaths among the Children of Atomic Bomb Survivors: A Reappraisal

From 1948 to 1954, the Atomic Bomb Casualty Commission conducted a study of pregnancy outcomes among births to atomic bomb survivors (Hiroshima and Nagasaki, Japan) who had received radiation doses ranging from 0 Gy to near-lethal levels. Past reports (1956, 1981, and 1990) on the cohort did not identify significant associations of radiation exposure with untoward pregnancy outcomes, such as major congenital malformations, stillbirths, or neonatal deaths, individually or in aggregate. We reexamined the risk of major congenital malformations and perinatal deaths in the children of atomic bomb survivors (n = 71,603) using fully reconstructed data to minimize the potential for bias, using refined estimates of the gonadal dose from Dosimetry System 2002 and refined analytical methods for characterizing dose-response relationships. The analyses showed that parental exposure to radiation was associated with increased risk of major congenital malformations and perinatal death, but the estimates were imprecise for direct radiation effects, and most were not statistically significant. Nonetheless, the uniformly positive estimates for untoward pregnancy outcomes among children of both maternal and paternal survivors are useful for risk assessment purposes, although extending them to populations other than the atomic bomb survivors comes with uncertainty as to generalizability