Syndemic factors associated with non-fatal overdose among young opioid users in New York City.

Introduction: Rates of illicit opioid use are particularly high among young adults, yet research on overdose experience and factors associated with overdose in this population remains limited. This study examines the experiences and correlates of non-fatal overdose among young adults using illicit opioids in New York City (NYC).

Methods: 539 participants were recruited via Respondent-Driven Sampling in 2014-2016.

Tracheostomy dislodgement: Are obese patients at increased risk?

Background: Obesity is a risk factor for tracheostomy-related complications. We aimed to investigate whether obesity was associated with a risk of unplanned tracheostomy dislodgement or decannulation (DD).

Methods: Retrospective review of patients undergoing tracheostomy at a single institution from 2013 to 2019 was performed.

Outcome of Hypotensive Trauma Patients by Time and Day of Arrival.

Background: Although most studies of trauma patients have not demonstrated a "weekend" or "night" effect on mortality, outcomes of hypotensive (systolic blood pressure <90 mm Hg) patients have not been studied. We sought to evaluate whether outcomes of hypotensive patients were associated with admission time and day.

Methods: We retrospectively analyzed patients from Pennsylvania Level 1 and Level 2 trauma centers with systolic blood pressure of <90 mm Hg over 5 y.

Examining the Relationship Between Biometric Indicators and Pharmacy Students' Academic Performance.

To use a fitness tracking device to track student wellness habits, specifically number of steps, activity, and sleep duration, in an attempt to identify relationships between these variables and academic performance outcomes such as examination scores and course grades. A fitness tracker was issued to second professional year Doctor of Pharmacy (PharmD) students to track their daily number of steps, activity levels, and minutes of sleep. Individual data from these devices were collected using a cloud-based data aggregation platform.

A SIMULATION-BASED FRAMEWORK FOR ASSESSING THE FEASIBILITY OF RESPONDENT-DRIVEN SAMPLING FOR ESTIMATING CHARACTERISTICS IN POPULATIONS OF LESBIAN, GAY AND BISEXUAL OLDER ADULTS.

Respondent-driven sampling (RDS) is a method for sampling from a target population by leveraging social connections. RDS is invaluable to the study of hard-to-reach populations. However, RDS is costly and can be infeasible.

Multi-institutional study of GRE scores as predictors of STEM PhD degree completion: GRE gets a low mark.

The process of selecting students likely to complete science, technology, engineering and mathematics (STEM) doctoral programs has not changed greatly over the last few decades and still relies heavily on Graduate Record Examination (GRE) scores in most U.S. universities.

Fixed choice design and augmented fixed choice design for network data with missing observations.

The statistical analysis of social networks is increasingly used to understand social processes and patterns. The association between social relationships and individual behaviors is of particular interest to sociologists, psychologists, and public health researchers. Several recent network studies make use of the fixed choice design (FCD), which induces missing edges in the network data.

High enhancer, downer, withdrawal helper: Multifunctional nonmedical benzodiazepine use among young adult opioid users in New York City.

Background: Benzodiazepines are a widely prescribed psychoactive drug; in the U.S., both medical and nonmedical use of benzodiazepines has increased markedly in the past 15 years.

Analysis of Networks with Missing Data with Application to the National Longitudinal Study of Adolescent Health.

It is common in the analysis of social network data to assume a census of the networked population of interest. Often the observations are subject to partial observation due to a known sampling or unknown missing data mechanism. However, most social network analysis ignores the problem of missing data by including only actors with complete observations.

Bayesian Peer Calibration with Application to Alcohol Use.

Peers are often able to provide important additional information to supplement self-reported behavioral measures. The study motivating this work collected data on alcohol in a social network formed by college students living in a freshman dormitory. By using two imperfect sources of information (self-reported and peer-reported alcohol consumption), rather than solely self-reports or peer-reports, we are able to gain insight into alcohol consumption on both the population and the individual level, as well as information on the discrepancy of individual peer-reports.

Network Model-Assisted Inference from Respondent-Driven Sampling Data.

Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process.

Estimating the size of populations at high risk for HIV using respondent-driven sampling data.

The study of hard-to-reach populations presents significant challenges. Typically, a sampling frame is not available, and population members are difficult to identify or recruit from broader sampling frames. This is especially true of populations at high risk for HIV/AIDS.

Diagnostics for Respondent-driven Sampling.

Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for HIV. Data are collected through peer-referral over social networks. RDS has proven practical for data collection in many difficult settings and is widely used.

Estimating hidden population size using Respondent-Driven Sampling data.

Respondent-Driven Sampling (RDS) is n approach to sampling design and inference in hard-to-reach human populations. It is often used in situations where the target population is rare and/or stigmatized in the larger population, so that it is prohibitively expensive to contact them through the available frames. Common examples include injecting drug users, men who have sex with men, and female sex workers.

Respondent-Driven Sampling: An Assessment of Current Methodology.

Respondent-Driven Sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure to expand the sample and reduce its dependence on the initial (convenience) sample.The current estimators of population averages make strong assumptions in order to treat the data as a probability sample.

MODELING SOCIAL NETWORKS FROM SAMPLED DATA.

Network models are widely used to represent relational information among interacting units and the structural implications of these relations. Recently, social network studies have focused a great deal of attention on random graph models of networks whose nodes represent individual social actors and whose edges represent a specified relationship between the actors. Most inference for social network models assumes that the presence or absence of all possible links is observed, that the information is completely reliable, and that there are no measurement (e.

A Framework for the Comparison of Maximum Pseudo Likelihood and Maximum Likelihood Estimation of Exponential Family Random Graph Models.

The statistical modeling of social network data is difficult due to the complex dependence structure of the tie variables. Statistical exponential families of distributions provide a flexible way to model such dependence. They enable the statistical characteristics of the network to be encapsulated within an exponential family random graph (ERG) model.

Developmental Contexts and Mental Disorders Among Asian Americans.

In this article, we use age of immigration as a proxy for the developmental context for understanding the association between immigration experiences and mental health. Generation defines the context under which immigrants arrive in the United States. We drew data from the National Latino and Asian American Study (N = 2,095), the first ever study conducted on the mental health of a national sample of Asian Americans.