A general class of small area estimation using calibrated hierarchical likelihood approach with applications to COVID-19 data.

The direct estimation techniques in small area estimation (SAE) models require sufficiently large sample sizes to provide accurate estimates. Hence, indirect model-based methodologies are developed to incorporate auxiliary information. The most commonly used SAE models, including the Fay-Herriot (FH) model and its extended models, are estimated using marginal likelihood estimation and the Bayesian methods, which rely heavily on the computationally intensive integration of likelihood function.

Using place-based characteristics to inform FDA tobacco sales inspections: results from a multilevel propensity score model.

Background: Conducting routine inspections for compliance with age-of-sale laws is essential to reducing underage access to tobacco. We seek to develop a multilevel propensity score model (PSM) to predict retail violation of sales to minors (RVSM).

Methods: The Food and Drug Administration compliance check of tobacco retailers with minor-involved inspections from 2015 to 2019 (n=683 741) was linked with multilevel data for demographics and policies.

Geographical distribution and social determinants of Tobacco 21 policy adoption and retail inspections in the United States, 2015-2019.

Introduction: Tobacco control laws that raise the minimum age of tobacco sales to 21 years (T21) play a pivotal role in youth tobacco prevention, yet empirical data are sorely needed to inform enforcement, compliance efforts, and future legislation.

Methods: Spatial analysis was conducted at the zip code level by geocoding the states and localities that adopted T21 ordinances from 2015 to 2019. A multi-level logistic regression model was conducted to examine disparities in neighborhood socioeconomic status (SES), FDA retail inspection, and state-level tobacco control policies associated with T21 adoption.

Invariant Characteristics of Carcinogenesis.

Carcinogenic modeling is aimed at mathematical descriptions of cancer development in aging. In this work, we assumed that a small fraction of individuals in the population is susceptible to cancer, while the rest of the population is resistant to cancer. For individuals susceptible to cancer we adopted methods of conditional survival analyses.