New Statistical Issues for Censored Survival Data: High-Dimensionality and Censored Covariate.

Censored survival data arise commonly in many areas including epidemiology, engineering and sociology. In this dissertation, we explore several emerging statistical issues for censored survival data. In Chapter 2, we consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz. We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression, using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses. In Chapter 3, we consider generalized linear regression analysis with a left-censored covariate due to the limit of detection. The complete case analysis yields valid estimates for regression coefficients, but loses efficiency. Substitution methods are biased; the maximum likelihood method relies on parametric models for the unobservable tail probability, thus may suffer from model misspecification. To obtain robust and more efficient results, we propose a semiparametric likelihood-based approach for the regression parameters using an accelerated failure time model for the left-censored covariate. A two-stage estimation procedure is considered. The proposed method outperforms the existing methods in simulation studies. Technical conditions for asymptotic properties are provided. In Chapter 4, we consider longitudinal data analysis with a terminal event. The existing methods include the joint modeling approach and the marginal estimating equation approach, and both assume that the relationship between the response variable and a set of covariates is the same no matter whether the terminal event occurs or not. This assumption, however, is not reasonable for many longitudinal studies. Therefore we directly model event time as a covariate, which provides intuitive interpretation. When the terminal event times are right-censored, a semiparametric likelihood-based approach similar to Chapter 3 is proposed for the parameter estimations. The proposed method outperforms the complete case analysis in simulation studies and its asymptotic properties are provided.PhDBiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108930/1/kongsc_1.pd

Possible atomic structures for the sub-bandgap absorption of chalcogen hyperdoped silicon

Single-crystal silicon wafers were hyperdoped respectively by sulfur, selenium, and tellurium element using ion implantation and nanosecond laser melting. The hyperdoping of such chalcogen elements endowed the treated silicon with a strong and wide sub-bandgap light absorptance. When these hyperdoped silicons were thermally annealed even at low temperatures (such as 200~400 oC), however, this extra sub-bandgap absorptance began to attenuate. In order to explain this attenuation of absorptance, alternatively, we consider it corresponding to a chemical decomposition reaction from optically absorbing structure to non-absorbing structure, and obtain a very good fitting to the attenuated absorptances by using Arrhenius equation. Further, we extract the reaction activation energies from the fittings and they are 0.343(+/- 0.031) eV for S-, 0.426(+/-0.042) eV for Se-, and 0.317(+/-0.033) eV for Te-hyperdoped silicon, respectively. We discuss these activation energies in term of the bond energies of chalcogen-Si metastable bonds, and finally suggest that several high-energy interstitial sites instead of the substitutional site, are very possibly the atomic structures that are responsible for the sub-bandgap absorptance of chalcogen hyperdoped silicon.Comment: 18 pages, 3 figures, 1 tabl

Changes in Iron Measures over Menopause and Associations with Insulin Resistance

Abstract Objectives: No longitudinal studies have examined how iron measures change over menopause. Our objectives were to examine iron measures in individual women at premenopause and at postmenopause and, secondarily, to determine if any changes contributed to insulin resistance. Methods: In a subset of participants (n=70) in a longitudinal study of menopause, we measured ferritin, transferrin, and soluble transferrin receptor (sTfR) once in the premenopause and once in the postmenopause. We also examined associations between menopausal status and change in iron markers after adjustment for age at menopause, race/ethnicity, and waist circumference. In linear regression models, we examined associations between premenopause iron measures and changes in iron markers over menopause with homeostasis model assessment of insulin resistance (HOMA-IR) changes over menopause, before and after adjustment for age at menopause, race/ethnicity, changes in waist circumference, C-reactive protein (CRP), and sex hormone-binding globulin (SHBG) levels. Results: Women had lower ferritin (p<0.01), higher sTfR:ferritin levels (p<0.01), lower HOMA-IR (p=0.022), and lower glucose (p=0.05) in premenopause compared to postmenopause. After adjustment, lower premenopausal iron levels (sTfR:ferritin levels ?=11.0, 95% confidence interval [CI] 0.017-22.0) and larger increases in iron over menopause (changes in sTfR:ferritin ?=13.6, 95% CI 0.93-26.3) were associated with larger increases in HOMA-IR. Conclusions: From premenopause to postmenopause, women on average have increases in measures of iron stores. Women who had the greatest changes in iron over menopause (lower measures of premenopausal iron and greater increases in iron measures over the menopause) had the strongest associations between changes in iron and changes in insulin resistance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98464/1/jwh%2E2012%2E3549.pd

Reproductive History and Chronic Hepatic Steatosis in the Michigan Study of Women's Health Across the Nation

Background: Reproductive history, particularly maternal age at most recent birth, may reflect lower risk for chronic disease and mortality due to socioeconomic factors, lifestyle behaviors, or genetics. Reproductive history has not been examined with respect to hepatic steatosis, the most common liver disease in the United States. Our objective was to examine the association between reproductive history and hepatic steatosis. Methods: We examined the association between reproductive history characteristics?specifically age at most recent birth?and the odds of moderate to severe hepatic steatosis using a population-based retrospective cohort study of women who underwent hepatic ultrasound at the Michigan site of the Study of Women's Health Across the Nation (n=331). Results: Women who gave birth at ≥35 years of age comprised 19% of the study population and were similar to other women regarding sociodemographic history and health behaviors. In multivariable analyses adjusting for age, race/ethnicity, chronic disease, and medications associated with hepatic steatosis, age at birth ≥35 years was associated with significantly decreased odds of hepatic steatosis (adjusted odds ratio [OR] 0.41, 95% confidence interval [CI] 0.20?0.87), which was attenuated after adjustment for waist circumference (OR 0.51, 95% CI 0.24?1.10). Other reproductive factors including gravidity, parity, miscarriages and abortions, recall of gestational weight gain, breastfeeding, age at first birth, and age at final menstrual period were not associated with hepatic steatosis. Conclusions: Women who were older at their most recent birth had a reduced odds of hepatic steatosis, possibly associated with their lower waist circumference.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140129/1/jwh.2014.4839.pd

Preparation of SnS2 colloidal quantum dots and their application in organic/inorganic hybrid solar cells

Dispersive SnS2 colloidal quantum dots have been synthesized via hot-injection method. Hybrid photovoltaic devices based on blends of a conjugated polymer poly[2-methoxy-5-(3",7"dimethyloctyloxy)-1,4-phenylenevinylene] (MDMO-PPV) as electron donor and crystalline SnS2 quantum dots as electron acceptor have been studied. Photoluminescence measurement has been performed to study the surfactant effect on the excitons splitting process. The photocurrent of solar cells with the hybrid depends greatly on the ligands exchange as well as the device heat treatment. AFM characterization has demonstrated morphology changes happening upon surfactant replacement and annealing, which can explain the performance variation of hybrid solar cells