From the help desk: Bootstrapped standard errors

Bootstrapping is a nonparametric approach for evaluating the distribution of a statistic based on random resampling. This article illustrates the bootstrap as an alternative method for estimating the standard errors when the theoretical calculation is complicated or not available in the current software. Copyright 2003 by Stata Corporation.st0034, bootstrap, cluster, nl, instrumental variables

Models and Methods for Genome-Wide Association Studies.

Genome-wide association (GWA) studies provide an extensive assessment of common genetic variants across the human genome for disease association. However, due to variation in allele frequencies and disease prevalence across populations, combining samples from different geographic or ethnic groups may lead to spurious evidence for association or diminish the true association signals. In part one of this dissertation, I propose a novel approach to correct for population stratification that makes use of the large amount of genetic information available in a GWA study. Based on allele-sharing identity-by-state (IBS) measures, I develop similarity scores that can describe genetic similarity between individuals, and match cases and controls accordingly. Association tests can then be performed conditional on the matched case-control groups. I apply our approach to the Pritzker bipolar GWA study. In part two, I extend our matching approach to families of arbitrary structure. I first apply similarity score-based matching to selected members from each family and then assign other family members to the same matched group. I modify a corrected chi-square test [Bourgain et al., 2003] following the Mantel-Haenszel procedure to account for correlations both between the family samples and between the matched cases and controls. The rapid advance in next-generation sequencing technologies allows a near-complete survey of genomic regions of interest and even whole genomes, enabling more extensive genetic association studies of rare variants. As we plan such re-sequencing studies of a complex disease, it is useful to consider the range of plausible genetic models, e.g., risk allele frequency (RAF) and genotype relative risk (GRR) of rare or less common causal variants, based on results of previous genetic linkage and association studies for the trait. In part three, I compute the power to detect linkage and/or association as a function of genetic model, and summarize the range of models likely to yield results that are consistent with existing GWA and/or linkage studies.Ph.D.BiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/77921/1/wguan_1.pd

Research on the health status and influencing factors of the older adult floating population in Shanghai

IntroductionOver the past decade, against the dual background of population aging and mobility, the older adult/adults floating population has become a new type of mobile group in China, continually congregating in large cities, posing significant challenges to the socio-economic development, eldercare services, and public management of these metropolises. Shanghai, as a mega-city and the economic center of the China, is typically representative of the national population.MethodsBased on the dynamic monitoring data of Shanghai’s floating population in 2018, this research uses mathematical statistics and binary Logistic regression models.ObjectiveThis research analyzes the demographic characteristics and health status of the older adult/adults floating population in Shanghai in the new era and reveals its primary influencing factors.Results and discussion(1) A prominent contradiction in the scale and structure of the older adult/adults floating population, with widowed and low-educated mobile older adult/adults requiring attention. (2) There is a lack of health knowledge, and the proportion of local reimbursement is low. Over 90% of migrant older adult/adults self-assessed their health (with a very few unable to care for themselves), far higher than the proportion of older adult/adults who are not sick (injured) or uncomfortable (actually healthy), which exceeds 70%. The health status of migrant older adult/adults deteriorates with age, and those who have never attended school and live alone have the worst health status. (3) Older adult/adults people with advanced age and low educational levels are at risk of health issues, while a better living environment can reduce the risk of illness in the older adult/adults floating population. Low family income, poor housing affordability, and the medical burden brought about by illness can easily lead to older adult/adults floating populations falling into the trap of older adult/adults poverty, and older adult/adults people from central regions and those who migrate along have difficulty adapting to city life, leading to poor self-assessed health. Meanwhile, community/enterprise health education helps to enhance the health protection awareness of the older adult/adults floating population. Finally, based on the governance concept of “mobility publicness,” several public management and service optimization strategies for social support for the older adult/adults floating population in Shanghai are proposed

AaKOS: Aspect-adaptive Knowledge-based Opinion Summarization

The rapid growth of information on the Internet has led to an overwhelming amount of opinions and comments on various activities, products, and services. This makes it difficult and time-consuming for users to process all the available information when making decisions. Text summarization, a Natural Language Processing (NLP) task, has been widely explored to help users quickly retrieve relevant information by generating short and salient content from long or multiple documents. Recent advances in pre-trained language models, such as ChatGPT, have demonstrated the potential of Large Language Models (LLMs) in text generation. However, LLMs require massive amounts of data and resources and are challenging to implement as offline applications. Furthermore, existing text summarization approaches often lack the ``adaptive" nature required to capture diverse aspects in opinion summarization, which is particularly detrimental to users with specific requirements or preferences. In this paper, we propose an Aspect-adaptive Knowledge-based Opinion Summarization model for product reviews, which effectively captures the adaptive nature required for opinion summarization. The model generates aspect-oriented summaries given a set of reviews for a particular product, efficiently providing users with useful information on specific aspects they are interested in, ensuring the generated summaries are more personalized and informative. Extensive experiments have been conducted using real-world datasets to evaluate the proposed model. The results demonstrate that our model outperforms state-of-the-art approaches and is adaptive and efficient in generating summaries that focus on particular aspects, enabling users to make well-informed decisions and catering to their diverse interests and preferences.Comment: 21 pages, 4 figures, 7 table