Models with random effects, such as generalised linear mixed models (GLMMs), are often used for analysing clustered data. Parameter inference with these models is difficult because of the presence of cluster-specific random effects, which must be integrated out when evaluating the likelihood function. Here, we propose a sequential variational Bayes algorithm, called Recursive Variational Gaussian Approximation for Latent variable models (R-VGAL), for estimating parameters in GLMMs. The R-VGAL algorithm operates on the data sequentially, requires only a single pass through the data, and can provide parameter updates as new data are collected without the need of re-processing the previous data. At each update, the R-VGAL algorithm requires the gradient and Hessian of a “partial” log-likelihood function evaluated at the new observation, which are generally not available in closed form for GLMMs. To circumvent this issue, we propose using an importance-sampling-based approach for estim
Forest fire size, frequency and severity are increasing worldwide, with corresponding reductions in long-unburnt habitat and greater modification of forest structure over wider areas. Understanding the implications for animals is imperative in optimizing management for species persistence and overall biodiversity. We investigated how avian responses to historical high-severity fire differ in forests at short (five years) and mid-range (16 years) time since fire, including whether increased time since fire mitigates any negative responses to high-severity fire. Sites were established in fire-prone dry forests of the Greater Blue Mountains World Heritage Area, Australia. A Bayesian latent variable analysis of bird data obtained from acoustic recordings was used to estimate the occurrence of 74 species in relation to time since fire (short, mid-range), the spatial extent of historical high-severity fire (limited, extensive), and their interaction. Time since fire influenced the number of
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As part of the “CY 2021 Medicare Hospital Outpatient Prospective Payment System and Ambulatory Surgical Center Payment System Final Rule” (the “Final Rule”) published on December 2, 2020, the Centers for Medicare and Medicaid Services (“CMS”) finalized policies designed to overhaul the methodology used to calculate the Overall Hospital Quality Star Rating effective 2021.
By way of background, the Overall Hospital Quality Star Rating was developed as a tool for consumers to use to make informed decisions about where they receive care. CMS designed the methodology for determining Star Ratings with the goal of including as many hospitals and as many measuring criteria as possible.