Models for Pooled Time-Series Cross-Section Data

Several models are available for the analysis of pooled time-series cross-section (TSCS) data, defined as “repeated observations on fixed units” (Beck and Katz 1995). In this paper, we run the following models: (1) a completely pooled model, (2) fixed effects models, and (3) multi-level/hierarchical linear models. To illustrate these models, we use a Generalized Least Squares (GLS) estimator with cross-section weights and panel-corrected standard errors (with EViews 8) on the cross-national homicide trends data of forty countries from 1950 to 2005, which we source from published research (Messner et al. 2011). We describe and discuss the similarities and differences between the models, and what information each can contribute to help answer substantive research questions. We conclude with a discussion of how the models we present may help to mitigate validity threats inherent in pooled time-series cross-section data analysis

Cumulative incidence and diagnosis of SARS-CoV-2 infection in New York

Purpose New York State (NYS) is an epicenter of the SARS-CoV-2 pandemic in the United States. Reliable estimates of cumulative incidence in the population are critical to tracking the extent of transmission and informing policies. Methods We conducted a statewide seroprevalence study in a 15,101 patron convenience sample at 99 grocery stores in 26 counties throughout NYS. SARS-CoV-2 cumulative incidence was estimated from antibody reactivity by first poststratification weighting and then adjusting by antibody test characteristics. The percent diagnosed was estimated by dividing the number of diagnoses by the number of estimated infection-experienced adults. Results Based on 1887 of 15,101 (12.5%) reactive results, estimated cumulative incidence through March 29 was 14.0% (95% confidence interval [CI]: 13.3%–14.7%), corresponding to 2,139,300 (95% CI: 2,035,800–2,242,800) infection-experienced adults. Cumulative incidence was highest in New York City 22.7% (95% CI: 21.5%–24.0%) and higher among Hispanic/Latino (29.2%), non-Hispanic black/African American (20.2%), and non-Hispanic Asian (12.4%) than non-Hispanic white adults (8.1%, P \u3c .0001). An estimated 8.9% (95% CI: 8.4%–9.3%) of infections in NYS were diagnosed, with diagnosis highest among adults aged 55 years or older (11.3%, 95% CI: 10.4%–12.2%). Conclusions From the largest U.S. serosurvey to date, we estimated \u3e2 million adult New York residents were infected through late March, with substantial disparities, although cumulative incidence remained less than herd immunity thresholds. Monitoring, testing, and contact tracing remain essential public health strategies

The third wave of democratization: Consolidation of nominal democracy

The topic of the dissertation is the third wave of democratization: Authoritarian regimes on earth around 1975 mostly gave way to democratic regimes by 2000. How did it happen? Why did democracies massively emerge even in the poorest countries where democracy was least expected? Why did global democracy increase in number but decline in quality? I inquire what factors promoted the third wave in what manners. To answer the question, I employ a mixed-methods approach, taking a sequential design of quantitative-to-qualitative methods. Event history analysis is conducted to test the factors of democratic transitions. Alternative theories are proposed based on the results and further tested through comparative historical analysis of South Korea and Nigeria. Employing elite conflict framework, those proposed theories focus on ruling elite’s roles in promoting democratic transition. Importantly, democratic transition in the third wave rarely meant realizing true democracy, but usually meant ruler’s adopting multi-party election to claim democracy. The latter is defined as nominal democratization. My main argument is that elite-driven democratizations are responsible for the rapid but nominal democratizations of many less-developed countries in the third wave. As less-developed countries were faced with political legitimacy crises due to poor economic performance, ruling elite chose democratic transition as a means of appeasing the people, but did so nominally so that they would not lose much. Also, ruling elite of less-developed countries chose democratic transition to appeal to international financial donors and attract more capital for industrialization than nearby competitors. Two important factors emerged from the case studies of South Korea and Nigeria. First, the legacies of democratic institutions kept promoting nominal democratization. The legacies were born as the United States and the British Empire installed the initial governments of post-independence Korea and Nigeria and filled them with those who were docile to great powers but failed their nationals. The legacies were further entrenched, as those unrepresentative elites consolidated their power. Second, because of different structures of the ruling elites in both countries, they employed different strategies for competing with one another and pacifying the people, but eventually converged to nominal democratization and stabilized their collective interest

HIV screening in the dental setting in New York State.

While primary care providers in New York State (NYS) are mandated to offer all patients a HIV test, still many NYS residents miss the HIV screening opportunity. To fill the gap, and as the CDC recommends, this study aimed to examine the feasibility of implementing HIV screening in dental setting, identify patient characteristics associated with acceptance of HIV rapid testing, and discuss best practices of HIV screening in dental setting. New York State Department of Health (NYSDOH) collaborated with the Northeast/Caribbean AIDS Education and Training Center (NECA AETC) and three dental schools in New York State to offer free HIV screening tests as a component of routine dental care between February 2016 and March 2018. Ten clinics in upstate New York and Long Island participated in the study. HIV screening was performed using the OraQuick™ In-Home HIV Test. 14,887 dental patients were offered HIV screening tests; 9,057 (60.8%) were screened; and one patient (0.011%) was confirmed HIV positive and linked to medical care. Of all dental patients, 33% had never been screened for HIV; and 56% had not had a primary care visit or had not been offered an HIV screening test by primary care providers in the previous 12 months. Multi-level generalized linear modeling analysis indicated that test acceptance was significantly associated with patient's age, race/ethnicity, gender, country of origin, primary payer (or insurance), past primary care visits, past HIV testing experiences, and the poverty level of patient's community. HIV screening is well accepted by dental patients and can be effectively integrated into routine dental care. HIV screening in the dental setting can be a good option for first-time testers, those who have not seen a primary care provider in the last 12 months, and those who have not been offered HIV screening at their last primary care visit