A Pseudo‐Bayesian Shrinkage Approach to Regression with Missing Covariates

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93673/1/j.1541-0420.2011.01718.x.pd

Ignorable and Nonignorable Modeling in Regression with Incomplete Covariates.

Regression analysis is a statistical tool for studying the relationships between outcome and predictor variables. The analysis is often complicated by missing data. Complete-case analysis discards all the incomplete cases, and can result in serious loss of information and biased estimates. Ignorable likelihood methods use information in the incomplete cases by basing inferences on the likelihood function given the observed data, without modeling the missing-data mechanism. It is a valid method when the mechanism of missing data is missing at random, in the sense that missingness does not depend on the underlying missing values after conditioning on the observed data. When the missing-data mechanism depends on the missing values, nonignorable modeling methods are required to make valid inferences. However, a nonignorable model is difficult to specify correctly and needs restrictions to be identifiable. In Chapter 2, we propose a method called subsample ignorable likelihood (SSIL), which applies an ignorable likelihood method to a subsample of observations that are complete on a set of variables, but possibly incomplete on others. We describe the missing data mechanism under which SSIL gives valid estimates, but both complete-case analysis and IL methods give poor estimates. We provide a simulation study to illuminate the properties of the method, and apply the proposed method to a dataset from the National Health and Nutrition Examination Survey. In Chapter 3, we propose a pseudo-Bayesian approach for regression with missing covariates, which compromises between complete-case analysis and the regression analysis that drops the incomplete variables. We illustrate the favorable properties of the method by simulation. Chapter 4 studies the question of when it is necessary to model the missing data mechanism. We study two aspects of covariate missingness on the estimation of regression: (1) nonignorability, which concerns mainly how ignorable likelihood methods perform under varying levels of association between missingness and the missing covariates; (2) outcome dependency, which studies the relatedness of covariate missingness to the outcome on the estimation of regression. We apply methods from Chapter 3 and Chapter 4 to a liver cancer dataset.Ph.D.BiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89828/1/nhzhang_1.pd

Driving behavior-guided battery health monitoring for electric vehicles using machine learning

An accurate estimation of the state of health (SOH) of batteries is critical to ensuring the safe and reliable operation of electric vehicles (EVs). Feature-based machine learning methods have exhibited enormous potential for rapidly and precisely monitoring battery health status. However, simultaneously using various health indicators (HIs) may weaken estimation performance due to feature redundancy. Furthermore, ignoring real-world driving behaviors can lead to inaccurate estimation results as some features are rarely accessible in practical scenarios. To address these issues, we proposed a feature-based machine learning pipeline for reliable battery health monitoring, enabled by evaluating the acquisition probability of features under real-world driving conditions. We first summarized and analyzed various individual HIs with mechanism-related interpretations, which provide insightful guidance on how these features relate to battery degradation modes. Moreover, all features were carefully evaluated and screened based on estimation accuracy and correlation analysis on three public battery degradation datasets. Finally, the scenario-based feature fusion and acquisition probability-based practicality evaluation method construct a useful tool for feature extraction with consideration of driving behaviors. This work highlights the importance of balancing the performance and practicality of HIs during the development of feature-based battery health monitoring algorithms

Predictors of Condom Use among Peer Social Networks of Men Who Have Sex with Men in Ghana, West Africa

Ghanaian men who have sex with men (MSM) have high rates of HIV infection. A first step in designing culturally relevant prevention interventions for MSM in Ghana is to understand the influence that peer social networks have on their attitudes and behaviors. We aimed to examine whether, in a sample of Ghanaian MSM, mean scores on psychosocial variables theorized to influence HIV/STI risk differed between peer social networks and to examine whether these variables were associated with condom use. We conducted a formative, cross-sectional survey with 22 peer social networks of MSM (n = 137) in Ghana. We assessed basic psychological- needs satisfaction, HIV/STI knowledge, sense of community, HIV and gender non-conformity stigmas, gender equitable norms, sexual behavior and condom use. Data were analyzed using analysis of variance, generalized estimating equations, and Wilcoxon two sample tests. All models were adjusted for age and income, ethnicity, education, housing and community of residence. Mean scores for all psychosocial variables differed significantly by social network. Men who reported experiencing more autonomy support by their healthcare providers had higher odds of condom use for anal (AOR = 3.29, p \u3c 0.01), oral (AOR = 5.06, p \u3c 0.01) and vaginal (AOR = 1.8, p \u3c 0.05) sex. Those with a stronger sense of community also had higher odds of condom use for anal sex (AOR = 1.26, p \u3c 0.001). Compared to networks with low prevalence of consistent condom users, networks with higher prevalence of consistent condom users had higher STD and HIV knowledge, had norms that were more supportive of gender equity, and experienced more autonomy support in their healthcare encounters. Healthcare providers and peer social networks can have an important influence on safer-sex behaviors in Ghanaian MSM. More research with Ghanaian MSM is needed that considers knowledge, attitudes, and norms of their social networks in the development and implementation of culturally relevant HIV/STI prevention intervention strategies

Key steps in the structure-based optimization of the hepatitis C virus NS3/4A protease inhibitor SCH503034

Crystal structures of protease/inhibitor complexes guided optimization of the buried nonpolar surface area thereby maximizing hydrophobic binding. The resulting potent tripeptide inhibitor is in clinical trials

“But the moment they find out that you are MSM…”: a qualitative investigation of HIV prevention experiences among men who have sex with men (MSM) in Ghana’s health care system

Abstract: The prevalence of HIV in Ghana is 1.3%, compared to 17% among men who have sex with men (MSM). There is limited empirical data on the current health care climate and its impact on HIV prevention services for Ghanaian MSM. The purposes of this study were to investigate (1) MSM’s experiences using HIV prevention resources, (2) what factors, including health care climate factors, influenced MSM’s use of prevention resources and (3) MSM self-identified strategies for improving HIV/sexually transmitted infection (STI) prevention among MSM in Ghanaian communities. Methods: We conducted 22 focus groups (n = 137) with peer social networks of MSM drawn from three geographic communities in Ghana (Accra, Kumasi, Manya Krobo). The data were examined using qualitative content analysis. Interviews with individual health care providers were also conducted to supplement the analysis of focus group findings to provide more nuanced illuminations of the experiences reported by MSM..

Childhood Cardiovascular Risk Factors and Adult Cardiovascular Events

BACKGROUND Childhood cardiovascular risk factors predict subclinical adult cardiovascular disease, but links to clinical events are unclear. METHODS In a prospective cohort study involving participants in the International Childhood Cardiovascular Cohort (i3C) Consortium, we evaluated whether childhood risk factors (at the ages of 3 to 19 years) were associated with cardiovascular events in adulthood after a mean follow-up of 35 years. Body-mass index, systolic blood pressure, total cholesterol level, triglyceride level, and youth smoking were analyzed with the use of i3C-derived age- and sex-specific z scores and with a combined-risk z score that was calculated as the unweighted mean of the five risk z scores. An algebraically comparable adult combined-risk z score (before any cardiovascular event) was analyzed jointly with the childhood risk factors. Study outcomes were fatal cardiovascular events and fatal or nonfatal cardiovascular events, and analyses were performed after multiple imputation with the use of proportional-hazards regression. RESULTS In the analysis of 319 fatal cardiovascular events that occurred among 38,589 participants (49.7% male and 15.0% Black; mean [±SD] age at childhood visits, 11.8±3.1 years), the hazard ratios for a fatal cardiovascular event in adulthood ranged from 1.30 (95% confidence interval [CI], 1.14 to 1.47) per unit increase in the z score for total cholesterol level to 1.61 (95% CI, 1.21 to 2.13) for youth smoking (yes vs. no). The hazard ratio for a fatal cardiovascular event with respect to the combined-risk z score was 2.71 (95% CI, 2.23 to 3.29) per unit increase. The hazard ratios and their 95% confidence intervals in the analyses of fatal cardiovascular events were similar to those in the analyses of 779 fatal or nonfatal cardiovascular events that occurred among 20,656 participants who could be evaluated for this outcome. In the analysis of 115 fatal cardiovascular events that occurred in a subgroup of 13,401 participants (31.0±5.6 years of age at the adult measurement) who had data on adult risk factors, the adjusted hazard ratio with respect to the childhood combined-risk z score was 3.54 (95% CI, 2.57 to 4.87) per unit increase, and the mutually adjusted hazard ratio with respect to the change in the combined-risk z score from childhood to adulthood was 2.88 (95% CI, 2.06 to 4.05) per unit increase. The results were similar in the analysis of 524 fatal or nonfatal cardiovascular events. CONCLUSIONS In this prospective cohort study, childhood risk factors and the change in the combined-risk z score between childhood and adulthood were associated with cardiovascular events in midlife.publishedVersionPeer reviewe