Integrated Multiple Mediation Analysis: A Robustness–Specificity Trade-Off In Causal Structure,
2020
Institute of Statistics, National Chiao Tung University, Hsinchu, Taiwan.
Integrated Multiple Mediation Analysis: A Robustness–Specificity Trade-Off In Causal Structure, An-Shun Tai, Sheng-Hsuan Lin
Harvard University Biostatistics Working Paper Series
Recent methodological developments in causal mediation analysis have addressed several issues regarding multiple mediators. However, these developed methods differ in their definitions of causal parameters, assumptions for identification, and interpretations of causal effects, making it unclear which method ought to be selected when investigating a given causal effect. Thus, in this study, we construct an integrated framework, which unifies all existing methodologies, as a standard for mediation analysis with multiple mediators. To clarify the relationship between existing methods, we propose four strategies for effect decomposition: two-way, partially forward, partially backward, and complete decompositions. This study reveals how the direct and …
A Call For Consistency In The Official Naming Of The Disease Caused By Severe Acute Respiratory Syndrome Coronavirus 2 In Non-English Languages,
2020
RAND Corporation
A Call For Consistency In The Official Naming Of The Disease Caused By Severe Acute Respiratory Syndrome Coronavirus 2 In Non-English Languages, Lu Dong, Zhe Li, Isaac Fung
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
We investigated the adoption of World Health Organization (WHO) naming of COVID-19 into the respective languages among the Group of Twenty (G20) countries, and the variation of COVID-19 naming in the Chinese language across different health authorities. On May 7, 2020, we identified the websites of the national health authorities of the G20 countries to identify naming of COVID-19 in their respective languages, and the websites of the health authorities in mainland China, Hong Kong, Macau, Taiwan and Singapore and identify their Chinese name for COVID-19. Among the G20 nations, Argentina, China, Italy, Japan, Mexico, Saudi Arabia and Turkey do …
Brain Structure Changes Over Time In Normal And Mildly Impaired Aged Persons,
2020
University of Kentucky
Brain Structure Changes Over Time In Normal And Mildly Impaired Aged Persons, Charles D. Smith, Linda J. Van Eldik, Gregory A. Jicha, Frederick A. Schmitt, Peter T. Nelson, Erin L. Abner, Richard J. Kryscio, Richard R. Murphy, Anders H. Andersen
Neurology Faculty Publications
Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70-78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a …
Sensitivity Analysis For Incomplete Data And Causal Inference,
2020
Southern Methodist University
Sensitivity Analysis For Incomplete Data And Causal Inference, Heng Chen
Statistical Science Theses and Dissertations
In this dissertation, we explore sensitivity analyses under three different types of incomplete data problems, including missing outcomes, missing outcomes and missing predictors, potential outcomes in \emph{Rubin causal model (RCM)}. The first sensitivity analysis is conducted for the \emph{missing completely at random (MCAR)} assumption in frequentist inference; the second one is conducted for the \emph{missing at random (MAR)} assumption in likelihood inference; the third one is conducted for one novel assumption, the ``sixth assumption'' proposed for the robustness of instrumental variable estimand in causal inference.
Statistical Inference Of Adaptation At Multiple Genomic Scales Using Supervised Classification And A Hidden Markov Model,
2020
Duquesne University
Statistical Inference Of Adaptation At Multiple Genomic Scales Using Supervised Classification And A Hidden Markov Model, Lauren A. Sugden
Biology and Medicine Through Mathematics Conference
No abstract provided.
Modeling Species Distribution And Habitat Suitability Of American Ginseng (Panax Quinquefolius) In Virginia,
2020
James Madison University
Modeling Species Distribution And Habitat Suitability Of American Ginseng (Panax Quinquefolius) In Virginia, Jacob D. J. Peters
Masters Theses, 2020-current
American ginseng (Panax quinquefolius) is a well-known and sought-after medicinal plant native to North America that is facing increased threat of extinction due to overharvesting, herbivory, and habitat loss. Species distribution and habitat suitability models may be valuable to landowners interested in sustainable harvest or to institutions interested in the conservation and restoration of the species. With unequal sampling efforts across a region of interest, it is likely that some locations with appropriate habitat may be misrepresented in model predictions. This study refined a state-derived species distribution model for ginseng through increased sampling effort across the Cumberland Plateau …
Splitting Up A Complex Mess: The Effectiveness Of Statistical Analysis On Delimiting Species Complexes,
2020
James Madison University
Splitting Up A Complex Mess: The Effectiveness Of Statistical Analysis On Delimiting Species Complexes, Sara N. Schoen
Masters Theses, 2020-current
Recent studies have highlighted a need for more refined tools in species delimitation. This is especially true when considering diversity within species complexes, where members are morphologically similar and traditional tools have thus far failed to provide clearly defined boundaries between species. This project seeks to refine our traditional tools of species delimitation and apply new tools to the challenges created by species complexes. The focus organisms of this study are the anurans of the Limnonectes kuhlii complex. This species complex comprises more than 25 species of stream frogs from Southeast Asia. Traditionally, morphometrics (particularly linear measures) has been the …
Age At Migration And The Risk Of Psychotic Disorders: A Systematic Review And Meta-Analysis.,
2020
Western University
Age At Migration And The Risk Of Psychotic Disorders: A Systematic Review And Meta-Analysis., Kelly K. Anderson, Jordan Edwards
Epidemiology and Biostatistics Publications
OBJECTIVE: To conduct a systematic review and meta-analysis of the existing evidence on the association between age at migration and the risk of psychotic disorders.
METHODS: Observational studies were eligible for inclusion if they presented data on the association between age at migration and the risk of psychotic disorders among first-generation migrant groups. We used two random effects meta-analyses to pool effect estimates for each stratum of age at migration relative to (i) a native-born reference category and (ii) the youngest age stratum (0 to 2 years).
RESULTS: Ten studies met inclusion criteria, and five were included in the meta-analysis. …
Novel Bayesian Methodology For The Analysis Of Single-Cell Rna Sequencing Data.,
2020
University of Louisville
Novel Bayesian Methodology For The Analysis Of Single-Cell Rna Sequencing Data., Michael Sekula
Electronic Theses and Dissertations
With single-cell RNA sequencing (scRNA-seq) technology, researchers are able to gain a better understanding of health and disease through the analysis of gene expression data at the cellular-level; however, scRNA-seq data tend to have high proportions of zero values, increased cell-to-cell variability, and overdispersion due to abnormally large expression counts, which create new statistical problems that need to be addressed. This dissertation includes three research projects that propose Bayesian methodology suitable for scRNA-seq analysis. In the first project, a hurdle model for identifying differentially expressed genes across cell types in scRNA-seq data is presented. This model incorporates a correlated random …
Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data,
2020
Washington University in St. Louis
Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim
McKelvey School of Engineering Graduate Student Theses & Dissertations
Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross- sectional nature of training and prediction processes. Finding temporal patterns in EHR is …
Physical Therapy Nontreatment Events With Primary Physical Therapist,
2020
University of Nevada, Las Vegas
Physical Therapy Nontreatment Events With Primary Physical Therapist, Stephen Johnson
UNLV Theses, Dissertations, Professional Papers, and Capstones
Background: Physical therapy improves prognosis reduces stay and is generally helpful in aiding recovery from a wide range of ailments. Nontreatment rates occur for multiple reasons and are also related to the personalities of physical therapists.
Methods: We used data from a research project involving physical therapy at an acute care facility in our community. Our study focused on the retrospectively determined primary physical therapist for each patient. We used the chi-squared tests to compare nontreatment rates between days of the week and disease type and the reasons for nontreatment events. Repeated-measure models were used to evaluate the effect of …
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation.,
2020
University of Louisville
Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya
Electronic Theses and Dissertations
Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …
Equivalency Testing For Two Formulations Of A Clinical Laboratory Control Material,
2020
University of Nebraska Medical Center
Equivalency Testing For Two Formulations Of A Clinical Laboratory Control Material, Jessica M. Hart
Capstone Experience: Master of Public Health
Clinical laboratory control materials are an integral part of legally-mandated and highly regulated quality control protocols in all clinical laboratories. These controls ensure accurate performance of the laboratory testing and instrumentation used to produce medical test results for millions of patients. It is of clinical and public health interest to ensure the diagnostic test results which affect so many people are regulated by the most accurate and precise controls.
Formulation changes in control materials have the potential to impact laboratory quality control. In this study, data from two formulations of a hematology control were compared to assess equivalency of the …
Introduction To Research Statistical Analysis: An Overview Of The Basics,
2020
HCA Healthcare
Introduction To Research Statistical Analysis: An Overview Of The Basics, Christian Vandever
HCA Healthcare Journal of Medicine
This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power. Variable types and definitions are included to clarify necessities for how the analysis will be interpreted. Categorical and quantitative variable types are defined, as well as response and predictor variables. Statistical tests described include t-tests, ANOVA and chi-square tests. Multiple regression is also explored for both logistic and linear regression. Finally, the most common statistics produced by these methods are explored.
Accurate Confidence Intervals For Risk Difference In Meta-Analysis With Rare Events,
2020
Zhejiang Gongshang University
Accurate Confidence Intervals For Risk Difference In Meta-Analysis With Rare Events, Tao Jiang, Baixin Cao, Guogen Shan
Environmental & Global Health Faculty Research
Background: Meta-analysis provides a useful statistical tool to effectively estimate treatment effect from multiple studies. When the outcome is binary and it is rare (e.g., safety data in clinical trials), the traditionally used methods may have unsatisfactory performance. Methods: We propose using importance sampling to compute confidence intervals for risk difference in meta-analysis with rare events. The proposed intervals are not exact, but they often have the coverage probabilities close to the nominal level. We compare the proposed accurate intervals with the existing intervals from the fixed- or random-effects models and the interval by Tian et al. (2009). Results: We …
Effect Of Zinc On Microcystis Aeruginosa And Its Toxin Production,
2020
Seton Hall University
Effect Of Zinc On Microcystis Aeruginosa And Its Toxin Production, Jose L. Perez
Seton Hall University Dissertations and Theses (ETDs)
Cyanobacteria harmful algal blooms (CHABs) are globally increasing biomasses of detrimental cyanobacteria due to anthropogenic water phosphorous and nitrogen loading and climate change. CHABs often produce secondary metabolites, cyanotoxins, that cause harmful effects to organisms, most water systems, and socioeconomic infrastructures. Additionally, the presence of heavy metal pollutant runoff in CHAB affected environments may result in CHAB population changes – aggravating toxigenicity. Zinc metal resistance and stress response were studied in microcystin (MC) cyanotoxin-producing Microcystis aeruginosa UTEX LB 2385 (M. aeruginosa UTEX LB 2385) and non-MC producing Microcystis aeruginosa UTEX LB 2386 (M. aeruginosa UTEX LB 2386) cyanobacteria. Molecular analysis …
Doubling Time Of The Covid-19 Epidemic By Province, China,
2020
Georgia Southern University, Jiann-Ping Hsu College of Public Health
Doubling Time Of The Covid-19 Epidemic By Province, China, Kamalich Muniz-Rodriguez, Gerardo Chowell, Chi-Hin Cheung, Dongyu Jia, Po-Ying Lai, Yiseul Lee, Manyun Liu, Sylvia Ofori, Kimberlyn M. Roosa, Lone Simonsen, Cecile Viboud, Isaac Fung
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
In China, the doubling time of the coronavirus disease epidemic by province increased during January 20–February 9, 2020. Doubling time estimates ranged from 1.4 (95% CI 1.2–2.0) days for Hunan Province to 3.1 (95% CI 2.1–4.8) days for Xinjiang Province. The estimate for Hubei Province was 2.5 (95% CI 2.4–2.6) days.
Auspicious Symbols Of Rank And Status,
2020
Centers for Disease Control and Prevention
Auspicious Symbols Of Rank And Status, Byron Breedlove, Isaac Fung
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
Work published in Emerging Infectious Diseases.
Dot: Gene-Set Analysis By Combining Decorrelated Association Statistics,
2020
University of Kentucky
Dot: Gene-Set Analysis By Combining Decorrelated Association Statistics, Olga A. Vsevolozhskaya, Min Shi, Fengjiao Hu, Dmitri V. Zaykin
Biostatistics Faculty Publications
Historically, the majority of statistical association methods have been designed assuming availability of SNP-level information. However, modern genetic and sequencing data present new challenges to access and sharing of genotype-phenotype datasets, including cost of management, difficulties in consolidation of records across research groups, etc. These issues make methods based on SNP-level summary statistics particularly appealing. The most common form of combining statistics is a sum of SNP-level squared scores, possibly weighted, as in burden tests for rare variants. The overall significance of the resulting statistic is evaluated using its distribution under the null hypothesis. Here, we demonstrate that this basic …
Limited Early Warnings And Public Attention To Coronavirus Disease 2019 In China, January–February, 2020: A Longitudinal Cohort Of Randomly Sampled Weibo Users,
2020
The University of Hong Kong
Limited Early Warnings And Public Attention To Coronavirus Disease 2019 In China, January–February, 2020: A Longitudinal Cohort Of Randomly Sampled Weibo Users, Yuner Zhu, King-Wa Fu, Karen A. Grépin, Hai Liang, Isaac Fung
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
Objective:
Awareness and attentiveness have implications for the acceptance and adoption of disease prevention and control measures. Social media posts provide a record of the public’s attention to an outbreak. To measure the attention of Chinese netizens to coronavirus disease 2019 (COVID-19), a pre-established nationally representative cohort of Weibo users was searched for COVID-19-related key words in their posts.
Methods:
COVID-19-related posts (N = 1101) were retrieved from a longitudinal cohort of 52 268 randomly sampled Weibo accounts (December 31, 2019–February 12, 2020).
Results:
Attention to COVID-19 was limited prior to China openly acknowledging human-to-human transmission on …
