scholarly journals Bayesian hierarchical age-period-cohort models with time-structured effects: An application to religious voting in the US, 1972–2008

2014 ◽  
Vol 33 ◽  
pp. 52-62 ◽  
Author(s):  
Daniel Stegmueller
Keyword(s):  
Bayesian Hierarchical ◽  
The Us ◽  
Religious Voting

Abstract 15772: Cardiovascular Hospitalizations and Procedures Plummet Nationwide During Covid-19 - an Analysis of US Medical Claims

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Monica R Shah ◽  
Tanya F Partridge ◽  
Xiaoqing Xue ◽  
Justin L Gregg
Keyword(s):  
Claims Data ◽  
Private Insurance ◽  
National Level ◽  
Regional Studies ◽  
Bayesian Hierarchical ◽  
Medical Claims ◽  
Equivalent Time ◽  
Time Period ◽  
The Us ◽  
National Trends

Introduction: Regional studies have reported a decline in cardiovascular (CV) hospitalizations and procedures with the onset of the coronavirus disease-2019 (COVID-19) pandemic. Factors may include patient reluctance to seek care and de-prioritization of approvals for CV admissions by hospitals. We wanted to assess these observations at a national level. Hypothesis: To examine national trends in CV hospitalizations for acute myocardial infarction (AMI), unstable angina (USA), and heart failure (HF), as well as left heart catheterizations (LHC), using US medical claims data. Methods: We interrogated IQVIA US Claims data, a verified source, from Jan 2019 to May 2020 (214 million patients; 76% private insurance claims, 19% Medicare claims, 5% Medicaid claims). Since confirmed COVID-19 cases in the US began rising in Mar 2020, this was used as reference point to identify cohorts for comparison. Trends in volumes of hospitalizations for key CV events (AMI, USA, and HF) and LHC were compared from Mar 1 to May 8, 2020 to the equivalent time period in 2019. We used a Bayesian hierarchical model to assess trends. Results: From Mar to May 2020, compared to 2019, there were significantly fewer hospitalizations for: key CV events (1,110,492 vs. 1,487,558; p=0.0016); AMI (277,615 vs. 412,235; p=0.0002); USA (1,007 vs. 1,688, p=0.1245); and, HF (831,870 vs. 1,073,635; p=0.0036). There were significantly fewer LHC (118,393 vs. 221,701; p=0.0002). As shown in the Figure, there was a significant decline in CV hospitalizations in 2020 compared to 2019. Conclusions: During the COVID-19 pandemic, CV hospitalizations have declined significantly in the US. We observed an ~25% drop in CV hospitalizations and an ~50% drop in LHC. To the best of our knowledge, this is the first national evaluation of trends in CV care during COVID-19 and validate concerns that acute CV care in the US has been delayed or deferred, potentially foreshadowing a surge of CV complications in the future.

scholarly journals State-level tracking of COVID-19 in the United States

2020 ◽  
Author(s):  
H. Juliette T. Unwin ◽  
Swapnil Mishra ◽  
Valerie C. Bradley ◽  
Axel Gandy ◽  
Thomas A. Mellan ◽  
...  
Keyword(s):  
State Level ◽  
The United States ◽  
Bayesian Hierarchical ◽  
Secondary Infections ◽  
The Us ◽  
Control And Prevention ◽  
Credible Intervals ◽  
Behaviour Changes ◽  
The Impact ◽  
Number Of Individuals

AbstractAs of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly modelled the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We used changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. On 1st June, we estimated that Rt was only below one in 23 states. We also estimated that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

scholarly journals State-level tracking of COVID-19 in the United States

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
H. Juliette T. Unwin ◽  
Swapnil Mishra ◽  
Valerie C. Bradley ◽  
Axel Gandy ◽  
Thomas A. Mellan ◽  
...  
Keyword(s):  
State Level ◽  
The United States ◽  
Bayesian Hierarchical ◽  
Secondary Infections ◽  
The Us ◽  
Control And Prevention ◽  
Credible Intervals ◽  
Behaviour Changes ◽  
The Impact ◽  
Number Of Individuals

AbstractAs of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that Rt was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%–4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

The Eleventh Circuit Holds that Agreements in which Pharmaceutical Companies Pay Generic Companies Not to Compete May be Valid

2004 ◽  
Vol 32 (1) ◽  
pp. 181-184
Author(s):  
Amy Garrigues
Keyword(s):  
Pharmaceutical Companies ◽  
Court Decisions ◽  
Patent Holder ◽  
Trial Court ◽  
Court Of Appeals ◽  
The Us ◽  
Antitrust Laws ◽  
Per Se ◽  
Appeals Court ◽  
Two Sides

On September 15, 2003, the US. Court of Appeals for the Eleventh Circuit held that agreements between pharmaceutical and generic companies not to compete are not per se unlawful if these agreements do not expand the existing exclusionary right of a patent. The Valley DrugCo.v.Geneva Pharmaceuticals decision emphasizes that the nature of a patent gives the patent holder exclusive rights, and if an agreement merely confirms that exclusivity, then it is not per se unlawful. With this holding, the appeals court reversed the decision of the trial court, which held that agreements under which competitors are paid to stay out of the market are per se violations of the antitrust laws. An examination of the Valley Drugtrial and appeals court decisions sheds light on the two sides of an emerging legal debate concerning the validity of pay-not-to-compete agreements, and more broadly, on the appropriate balance between the seemingly competing interests of patent and antitrust laws.

Relation of Statistically Significant, Abnormal, and Typical WAIS-R VIQ-PIQ Discrepancies to Full Scale IQs

2000 ◽  
Vol 16 (2) ◽  
pp. 107-114 ◽  
Author(s):  
Louis M. Hsu ◽  
Judy Hayman ◽  
Judith Koch ◽  
Debbie Mandell
Keyword(s):  
Graphical Method ◽  
The United States ◽  
Full Scale ◽  
True Score ◽  
Absolute Value ◽  
Normative Population ◽  
The Us ◽  
The Mean ◽  
And Performance ◽  
Quadratic Models

Summary: In the United States' normative population for the WAIS-R, differences (Ds) between persons' verbal and performance IQs (VIQs and PIQs) tend to increase with an increase in full scale IQs (FSIQs). This suggests that norm-referenced interpretations of Ds should take FSIQs into account. Two new graphs are presented to facilitate this type of interpretation. One of these graphs estimates the mean of absolute values of D (called typical D) at each FSIQ level of the US normative population. The other graph estimates the absolute value of D that is exceeded only 5% of the time (called abnormal D) at each FSIQ level of this population. A graph for the identification of conventional “statistically significant Ds” (also called “reliable Ds”) is also presented. A reliable D is defined in the context of classical true score theory as an absolute D that is unlikely (p < .05) to be exceeded by a person whose true VIQ and PIQ are equal. As conventionally defined reliable Ds do not depend on the FSIQ. The graphs of typical and abnormal Ds are based on quadratic models of the relation of sizes of Ds to FSIQs. These models are generalizations of models described in Hsu (1996) . The new graphical method of identifying Abnormal Ds is compared to the conventional Payne-Jones method of identifying these Ds. Implications of the three juxtaposed graphs for the interpretation of VIQ-PIQ differences are discussed.

Factorial Structure of the Therapist Adherence Measure-Revised (TAM-R) Within Multisystemic Therapy

2020 ◽  
Vol 36 (2) ◽  
pp. 427-431
Author(s):  
Aurelie M. C. Lange ◽  
Marc J. M. H. Delsing ◽  
Ron H. J. Scholte ◽  
Rachel E. A. van der Rijken
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Multisystemic Therapy ◽  
Model Fit ◽  
Validity And Reliability ◽  
Adherence Measure ◽  
Therapist Adherence ◽  
Confirmatory Factor ◽  
The Us

Abstract. The Therapist Adherence Measure (TAM-R) is a central assessment within the quality-assurance system of Multisystemic Therapy (MST). Studies into the validity and reliability of the TAM in the US have found varying numbers of latent factors. The current study aimed to reexamine its factor structure using two independent samples of families participating in MST in the Netherlands. The factor structure was explored using an Exploratory Factor Analysis (EFA) in Sample 1 ( N = 580). This resulted in a two-factor solution. The factors were labeled “therapist adherence” and “client–therapist alliance.” Four cross-loading items were dropped. Reliability of the resulting factors was good. This two-factor model showed good model fit in a subsequent Confirmatory Factor Analysis (CFA) in Sample 2 ( N = 723). The current finding of an alliance component corroborates previous studies and fits with the focus of the MST treatment model on creating engagement.

Measurement Invariance of a Universal Behavioral Screener Across Samples From the USA and Germany

2018 ◽  
Vol 34 (2) ◽  
pp. 87-100 ◽  
Author(s):  
Gino Casale ◽  
Robert J. Volpe ◽  
Brian Daniels ◽  
Thomas Hennemann ◽  
Amy M. Briesch ◽  
...  
Keyword(s):  
Measurement Invariance ◽  
Student Behavior ◽  
Cross Cultural ◽  
Cross Cultural Comparison ◽  
School Based ◽  
Cultural Research ◽  
Universal Screener ◽  
Confirmatory Factor ◽  
The Us ◽  
The Usa

Abstract. The current study examines the item and scalar equivalence of an abbreviated school-based universal screener that was cross-culturally translated and adapted from English into German. The instrument was designed to assess student behavior problems that impact classroom learning. Participants were 1,346 K-6 grade students from the US (n = 390, Mage = 9.23, 38.5% female) and Germany (n = 956, Mage = 8.04, 40.1% female). Measurement invariance was tested by multigroup confirmatory factor analysis (CFA) across students from the US and Germany. Results support full scalar invariance between students from the US and Germany (df = 266, χ2 = 790.141, Δχ2 = 6.9, p < .001, CFI = 0.976, ΔCFI = 0.000, RMSEA = 0.052, ΔRMSEA = −0.003) indicating that the factor structure, the factor loadings, and the item thresholds are comparable across samples. This finding implies that a full cross-cultural comparison including latent factor means and structural coefficients between the US and the German version of the abbreviated screener is possible. Therefore, the tool can be used in German schools as well as for cross-cultural research purposes between the US and Germany.

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