Hierarchical Bayesian Analysis Research Articles

Trends in gross body coordination and cardiorespiratory fitness-a hierarchical Bayesian Analysis of 35000 2nd Graders.

A negative decline of motor competence in children has been observed over the last decades. Though most studies derive their inferences from only two distant points in time and thus neglect to investigate the variability of the temporal trends. Between the year 2000 and 2011, 35018second graders performed the Körperkoordinationstest für Kinder (KTK), consisting of four items (WB, HH, JS, and MS) and a six minute run test (6MRT). A hierarchical Bayesian regression model with varying intercepts and temporal trends was fitted to the data. Age, sex, and BMI categories were included as input variables. The outcome variables were z-standardized to the initial cohort. In all four KTK items, we observed a yearly decline of -0.020 (95% UI -0.038 to -0.001) for WB, -0.054 (95% UI -0.071, -0.037) for HH, -0.028 (95% UI -0.045 to -0.012) for JS and -0.088 (95% UI -0.108 to -0.067) for MS. For the 6MRT, no trend was identified. Overweight and obese children showed a disadvantage in all tests scores. Negative time interactions were observed for overweight and obese children in HH and JS. A substantial between-city variation for all temporal trends was observed. The predictive validation for all models but MS was successful. A general negative decline was confirmed for coordinative abilities but not in cardiorespiratory fitness. For all outcome variables, a substantial between-city variation was observed, highlighting the importance of environmental factors in motor development. Overweight and obese children demonstrated an urgent need for action.

Spatio-temporal Distribution of Suicide Risk in Iran: A Bayesian Hierarchical Analysis of Repeated Cross-sectional Data.

ObjectivesWe aimed to estimate the space-time distribution of the risk of suicide mortality in Iran from 2006 to 2016.MethodsIn this repeated cross-sectional study, the age-standardized risk of suicide mortality from 2006 to 2016 was determined. To estimate the cumulative and temporal risk, the Besag, York, and Mollié and Bernardinelli models were used.ResultsThe relative risk of suicide mortality was greater than 1 in 43.0% of Iran’s provinces (posterior probability >0.8; range, 0.46 to 3.93). The spatio-temporal model indicated a high risk of suicide in 36.7% of Iran’s provinces. In addition, significant upward temporal trends in suicide risk were observed in the provinces of Tehran, Fars, Kermanshah, and Gilan. A significantly decreasing pattern of risk was observed for men (β, −0.013; 95% credible interval [CrI], −0.010 to −0.007), and a stable pattern of risk was observed for women (β, −0.001; 95% CrI, −0.010 to 0.007). A decreasing pattern of suicide risk was observed for those aged 15–29 years (β, −0.006; 95% CrI, −0.010 to −0.0001) and 30–49 years (β, −0.001; 95% CrI, −0.018 to −0.002). The risk was stable for those aged >50 years.ConclusionsThe highest risk of suicide mortality was observed in Iran’s northwestern provinces and among Kurdish women. Although a low risk of suicide mortality was observed in the provinces of Tehran, Fars, and Gilan, the risk in these provinces is increasing rapidly compared to other regions.

Mapping the Morbidity Risk Associated with Coal Mining in Queensland, Australia.

The populations in the vicinity of surface coal mining activities have a higher risk of morbidity due to diseases, such as cardiovascular, respiratory and hypertensive diseases, as well as cancer and diabetes mellitus. Despite the large and historical volume of coal production in Queensland, the main Australian coal mining state, there is little research on the association of coal mining exposures with morbidity in non-occupational populations in this region. This study explored the association of coal production (Gross Raw Output—GRO) with hospitalisations due to six disease groups in Queensland using a Bayesian spatial hierarchical analysis and considering the spatial distribution of the Local Government Areas (LGAs). There is a positive association of GRO with hospitalisations due to circulatory diseases (1.022, 99% CI: 1.002–1.043) and respiratory diseases (1.031, 95% CI: 1.001–1.062) for the whole of Queensland. A higher risk of circulatory, respiratory and chronic lower respiratory diseases is found in LGAs in northwest and central Queensland; and a higher risk of hypertensive diseases, diabetes mellitus and lung cancer is found in LGAs in north, west, and north and southeast Queensland, respectively. These findings can be used to support public health strategies to protect communities at risk. Further research is needed to identify the causal links between coal mining and morbidity in non-occupational populations in Queensland.

Drug Legalization, Elite Support, and Government Effectiveness in Latin America

In Latin America, the legalization of drugs—where it occurred—has been driven mainly by elites, although much attention has been placed on public opinion. Considering that efforts toward legalization have been top-down, analysis should concentrate on opinions of the governing elites. To undertake such an analysis, we draw on data from surveys conducted in 18 Latin American parliaments (2012–2018), and we examine elite perspectives on the legalization of all drugs. Results from a Bayesian hierarchical logistic analysis show that in countries where the government is less effective, and where public health problems persist, legislators are less likely to support legalization. We argue that this is due to a lack of trust by MPs in legalization as a solution to trafficking. Wherever those concerned with drug trafficking see the current government as problematic, they will be less likely to support so challenging and complex a policy as drug legalization.

Ecophysiological modeling of yield and yield components in winter wheat using hierarchical Bayesian analysis

AbstractYield components are widely recognized as drivers of wheat (Triticum aestivum L.) yield across environments and genotypes. In this study, we used a hierarchical Bayesian approach to model wheat grain yield in Oklahoma on an eco‐physiological basis using yield component traits thousand kernel weight (TKW) and nonyield biomass (NYB). The Bayesian approach allowed us to quantify uncertainties around the parameter values rather than obtaining a single value estimate for a parameter. The main objectives of this study were to (a) explain wheat yield as a function of component traits TKW and NYB, and thereby examine the implications for source‐sink balance; and (b) assess their association with weather conditions during key stages of wheat development. A secondary objective was to introduce Bayesian estimation for eco‐physiological modeling. Fifteen wheat genotypes planted in three locations in Oklahoma (Altus, Chickasha, and Lahoma) were evaluated across three harvest years (2017 to 2019), whereby the combination of location and year defined an environment. Results indicate that the environment explained a greater proportion of the variability in yield than genotypes or than genotype × environment (G × E) interaction; however, evidence for G × E was substantial. Yield was expected to increase with increasing TKW and NYB, which would suggest a source limitation to achieve potential yield. Yet, the contribution of early reproductive stage weather variables to the relationship between yield and NYB pointed in the direction of sink strength being compromised. In summary, our approach provides evidence for source‐sink co‐limitation in grain yield of this sample of hard red winter wheat genotypes.

Computational basis of decision-making impairment in multiple sclerosis

Background: Multiple sclerosis (MS) is commonly associated with decision-making, neurocognitive impairments, and mood and motivational symptoms. However, their relationship may be obscured by traditional scoring methods. Objectives: To study the computational basis underlying decision-making impairments in MS and their interaction with neurocognitive and neuropsychiatric measures. Methods: Twenty-nine MS patients and 26 matched control subjects completed a computer version of the Iowa Gambling Task (IGT). Participants underwent neurocognitive evaluation using an expanded version of the Brief Repeatable Battery. Hierarchical Bayesian Analysis was used to estimate three established computational models to compare parameters between groups. Results: Patients showed increased learning rate and reduced loss-aversion during decision-making relative to control subjects. These alterations were associated with: (1) reduced net gains in the IGT; (2) processing speed, executive functioning and memory impairments; and (3) higher levels of depression and current apathy. Conclusion: Decision-making deficits in MS patients could be described by the interplay between latent computational processes, neurocognitive impairments, and mood/motivational symptoms.

High landscape-level gene flow in the red-backed salamander (Plethodon cinereus)

Anthropogenic changes are expected to shape the genetic structure of many herpetofaunal populations. Indeed, genetic analyses are often applied in disturbed habitats because they can determine the loss of genetic diversity in isolated populations, identify barriers to dispersal and gene flow, and inform ways in which populations should be managed. As a result, there is a lack of baseline genetic data of organisms in relatively intact landscapes. Plethodontid salamanders are ideal for understanding fine-scale and landscape level genetic structure in continuous landscapes given their high abundance and their sensitivity to ecosystem changes. Given this, our study aimed to assess the landscape-level population structure in red-backed salamanders (Plethodon cinereus) within intact habitat. We investigated genetic variation in 479 individuals from three sites across roughly 26 km of intact hardwood forest. We tested for genetic structure among and within three sites using several metrics, including hierarchical Bayesian analysis, FST analysis, AMOVA, and isolation by genetic distance. The results revealed a single population throughout the study area and genetic structure within sites was not evident. Importantly, the sites in this study are part of a long-term project on the effects of standard silvicultural practices in the American Midwest, making it ideal for future re-evaluation of this red-backed salamander population. We now have baseline information to determine if any future disturbances or fragmentation may alter the genetic structure of this population, as well as how this population may change over time if the study area remains undisturbed.

Using Bayesian hierarchical analysis to combine evidence across outcomes and trials

AbstractBackgroundThe FDA’s statistical review for the recent aducanumab advisory committee included a Bayesian hierarchical analysis (BHA) combining CDR‐SB evidence across the ENGAGE and EMERGE studies resulting in a 62% probability of the treatment being efficacious. BHA can combine evidence across outcomes, trials within a drug development program, and trials for a specific mechanism of action, and provides an elegant solution to interpreting the totality of evidence. BHA is a comparable approach to composite scores and global statistical tests, but key differences exist.MethodUsing summary results from the aducanumab ENGAGE and EMERGE studies, solanezumab Expedition 1, 2, and 3 and the BAN2401 PRIME study, we combined evidence from ADAS‐Cog, ADCS‐ADL, and CDR‐SB using a BHA with hierarchies at the study, program, and three program level to assess the amyloid hypothesis, using the pre‐specified primary analysis populations. We compared these results to GSTs.ResultsThe aducanumab program combined across EMERGE and ENGAGE with all 3 outcomes has a 0.92 probability (>99.9% with GST), the solanezumab program combined across Expedition 1, Expedition 2 and Expedition 3 has a 0.92 probability (>99.9% with GST), and the BAN2401 program has a 0.95 probability (99.2% with GST) of treatment efficacy. We present BHA and GST results for individual studies compared to the original results. We also compare the study‐level BHA results to the global statistical test (GST) approach. We combine evidence across all 3 programs to get an overall probability of efficacy for the amyloid hypothesis with these 3 programs using BHA and GST.ConclusionBHA and GST both assess the totality of evidence within a study or development program, providing a natural correction for multiplicity, but results differ. BHA penalizes for divergence of outcomes or studies, and GST does not. This may be appropriate in some settings, but not in others. It allows an assessment of convergence of evidence, weakening of evidence, or elimination of evidence when a negative study “cancels out” a positive study. On a larger scale, it sheds light on how much evidence might exist for theories like the amyloid hypothesis when combining evidence across programs.

BOD as a Measure of Fluvial Organic Matter Lability—The Decoupling of O2 Consumption From CO2 Production

AbstractBiochemical oxygen demand (BOD) has been taken as a measure of the lability of the fluvial organic matter (both dissolved and particulate organic matter—DOM and POM), but such a link is based on a number of assumptions. First, the oxidation state of the organic carbon is zero and the molar stoichiometry of the reaction between organic C and O2 is 1. Second, the consumption of O2, as measured by BOD, is a first‐order reaction with respect to DOM or POM. Third, that POM and DOM are correlated. Applying a Bayesian hierarchical analysis to an extensive river monitoring records for 236 sites across Great Britain from 1974 to 2019, it is possible to test the nature of the link between BOD and fluvial organic matter. The study shows that: (a) The inclusion of both DOC and SS concentrations improved the modeling. (b) When a first‐order reaction was assumed there was no significant linear relationship with BOD and DOC and suspended solids (SS) in at least 98% of cases. (c) 53% of sites showed a zero‐order reaction; when there was a significant order of reaction, the median was 0.28 and was never larger than 0.93, that is, a first‐order reaction rate was never observed. The lack of significant relationship means that the supply of organic matter exceeds the capacity to turn over that organic matter; and that given the range of oxidation states of fluvial organic carbon, it is possible to completely decouple O2 consumption from fluvial organic matter concentration in rivers.

\u03bc-opioid receptor availability is associated with sex drive in human males

The endogenous mu-opioid receptor (MOR) system modulates a multitude of social and reward-related functions, and exogenous opiates also influence sex drive in humans and animals. Sex drive shows substantial variation across humans, and it is possible that individual differences in MOR availability underlie interindividual of variation in human sex drive. We measured healthy male subjects’ (n = 52) brain’s MOR availability with positron emission tomography (PET) using an agonist radioligand, [11C]carfentanil, that has high affinity for MORs. Sex drive was measured using self-reports of engaging in sexual behaviour (sex with partner and masturbating). Bayesian hierarchical regression analysis revealed that sex drive was positively associated with MOR availability in cortical and subcortical areas, notably in caudate nucleus, hippocampus, and cingulate cortices. These results were replicated in full-volume GLM analysis. These widespread effects are in line with high spatial autocorrelation in MOR expression in human brain. Complementary voxel-based morphometry analysis (n = 108) of anatomical MR images provided limited evidence for positive association between sex drive and cortical density in the midcingulate cortex. We conclude that endogenous MOR tone is associated with individual differences in sex drive in human males.

Perceptions of Hospice and Transfusion Access Among Patients with Advanced Blood Cancers: Results from a Best-Worst Scaling Survey

Background: Patients with hematologic malignancies have low rates of hospice use, and when they do enroll, they often do so in the last three days of life. While lack of access to transfusions in hospice has been posited to be a key barrier to hospice use for this population, data are lacking regarding the perception of patients with blood cancers about the importance of transfusion access compared to traditional hospice services. We sought to characterize the utility of transfusions and hospice services from the perspective of patients with advanced blood cancers, who would potentially be eligible for hospice care.Methods: In October 2020, we began a web-based survey of patients with hematologic malignancies recruited from the clinics of two large cancer centers. Eligible patients were at least 18 years of age, had at least two outpatient visits to the cancer center, and had a physician-estimated prognosis of six months or less based on their hematologic oncologist answering “no” to a modified “surprise” question (Hudson KE, JPM 2018): “would you be surprised if this patient died within the next six months?” A physician-estimated prognosis of ≤ 6 months was used for study inclusion as this is an eligibility criterion for hospice. The survey was developed through literature review, a series of patient/caregiver focus groups (n=27) and cognitive debriefing with blood cancer patients (n=5). The survey included a best-worst scaling (BWS) section to assess patients' perceptions of the utility of various services routinely provided in hospice (visiting nurse, case manager, home health aide, chaplain, social worker, respite care) as well as non-routine services (transfusion access, transportation, peer support, telemedicine through videoconferencing). We asked patients to imagine a program developed to support quality of life for patients with blood cancers just like them. We then presented them with 10 questions with different combinations of the services in groups of 4 and participants were asked to select the service they considered “most important” and “least important” in deciding whether to sign up for the program. The BWS questions were constructed using a near balanced incomplete block design (Louviere JJ, Patient 2010). We conducted a hierarchical Bayesian analysis to ascertain a standardized utility score assigned to each service, a measure of the average propensity to choose a service as most important more often than least important. Analyses were conducted using Sawtooth (Sawtooth Software, Inc).Results: As of July 2021, 102 patients had completed the survey (response rate: 64.6%). The median age of respondents was 71 years (IQR 63, 77). The majority of respondents were male, white, and married/living with partner (Table). The most common diagnosis was acute leukemia (38.2%). Patients considered access to blood transfusions to have the highest importance (Figure) with a standardized utility score of 21.1, 95% confidence interval [CI] [19.6-22.6], followed by telemedicine (19.4, 95% CI [17.8-20.9]), transportation to/from medical appointments (13.4, 95% CI 11.7-15.1), and visiting nurses (10.8, 95% [9.5-12.2]. The three least important services perceived by respondents were access to respite care (4.7, 95% CI [3.9-5.6]), social workers (4.5, 95% CI [3.5-5.5]), and chaplains (2.3, 95% CI [1.3-3.3]).Conclusions: In this cohort of blood cancer patients who would potentially be eligible for hospice care, access to blood transfusions had the greatest level of importance relative to services routinely provided in hospice settings. The high value placed on transfusion access suggests that this factor plays a crucial role in hospice decision making. Accordingly, lack of transfusion access in many hospices likely reduces the propensity of patients with blood cancers to choose hospice. Innovative hospice delivery models that include access to palliative transfusions may have strong potential to increase hospice use and optimize end-of-life care for this patient population. [Display omitted] DisclosuresHuntington: Genentech: Consultancy; SeaGen: Consultancy; Thyme Inc: Consultancy; Servier: Consultancy; Novartis: Consultancy; Bayer: Honoraria; AstraZeneca: Consultancy, Honoraria; AbbVie: Consultancy; DTRM Biopharm: Research Funding; TG Therapeutics: Research Funding; Flatiron Health Inc.: Consultancy; Pharmacyclics: Consultancy, Honoraria; Celgene: Consultancy, Research Funding.

Expert and novice sensitivity to environmental regularities in predicting NFL games

AbstractWe study whether experts and novices differ in the way they make predictions about National Football League games. In particular, we measure to what extent their predictions are consistent with five environmental regularities that could support decision making based on heuristics. These regularities involve the home team winning more often, the team with the better win-loss record winning more often, the team favored by the majority of media experts winning more often, and two others related to surprise wins and losses in the teams’ previous game. Using signal detection theory and hierarchical Bayesian analysis, we show that expert predictions for the 2017 National Football League (NFL) season generally follow these regularities in a near optimal way, but novice predictions do not. These results support the idea that using heuristics adapted to the decision environment can support accurate predictions and be an indicator of expertise.

Development of decision making based on internal and external information: A hierarchical Bayesian approach

AbstractIn decision making, people may rely on their own information as well as on information from external sources, such as family members, peers, or experts. The current study investigated how these types of information are used by comparing four decision strategies: 1) an internal strategy that relies solely on own information; 2) an external strategy that relies solely on the information from an external source; 3) a sequential strategy that relies on information from an external source only after own information is deemed inadequate; 4) an integrative strategy that relies on an integration of both types of information. Of specific interest were individual and developmental differences in strategy use. Strategy use was examined via Bayesian hierarchical mixture model analysis. A visual decision task was administered to children and young adolescents (N=305, ages 9–14). Individual differences but no age-related changes were observed in either decision accuracy or strategy use. The internal strategy was dominant across ages, followed by the integrative and sequential strategy, respectively, while the external strategy was extremely rare. This suggests a reluctance to rely entirely on information provided by external sources. We conclude that there are individual differences but not developmental changes in strategy use pertaining to perceptual decision-making in 9- through 14-year-olds. Generalizability of these findings is discussed with regard to different forms of social influence and varying perceptions of the external source. This study provides stepping stones in better understanding and modeling decision making processes in the presence of both internal and external information.

Bayesian Refinement of the Permeability-Limited Physiologically Based Pharmacokinetic Model for Perfluorooctanoic Acid in Male Rats.

Physiologically based pharmacokinetic (PBPK) modeling is a powerful technique to inform risk assessment of xenobiotic substances such as perfluorooctanoic acid (PFOA). In our previous study, a permeability-limited PBPK model was developed to simulate the toxicokinetics and tissue distribution of PFOA in male rats. However, due to limited information on some key model parameters (e.g., protein binding and active transport rates), the uncertainty of the permeability-limited PBPK model was quite high. To address this issue, a hierarchical Bayesian analysis with Markov chain Monte Carlo (MCMC) was applied to reduce the uncertainty of parameters and improve the performance of the PBPK model. With the optimized posterior parameters, the PBPK model was evaluated by comparing its prediction with experimental data from three different studies. The results show that the uncertainties of the posterior model parameters were reduced substantially. In addition, most of the PBPK model predictions were improved: with the posterior parameters, most of the predicted plasma toxicokinetics (e.g., half-life) and tissue distribution fell well within a factor of 2.0 of the experimental data. Finally, the Bayesian framework could provide insights into the molecular mechanisms driving PFOA toxicokinetics: PFOA-protein binding, membrane permeability, and active transport.

Emerging data on the treatment of multiple sclerosis

Background and objectives. In the past few years, a myriad of new studies were aimed to find better ways to manage MS. As a result, a bunch of new molecules were found to have good efficacy, therefore FDA and EMA approved a series of treatments in the last few years, the last one receiving green light from EMA on March 30th, 2021 (Ofatumumab – Kesimpta®). The aim of this study was to evaluate and classify three of the newest drugs approved by the FDA and EMA. Material and methods. All the studies were chosen on the basis of pre-determined inclusion criteria and in accordance with PRISMA guidelines. We searched Pubmed and Cochrane Library for all studies published up until the end of 2020. For the data analysis we used MetaInsight®, a statistical web-based tool for meta-analyses and NMAs performing both Frequentist and Bayesian hierarchical model analyses, each one being seen as a sensitivity check for the other. Outcomes. The best therapeutic agent in reported efficacy amongst the three analyzed was Ofatumumab, ranked first in hierarchy, Ozanimod and Cladribine following in the second and third place, respectively. Conclusions. According to ABN’s 2015 guidelines, Cladribine was ranked between the most effective medicines for the treatment of MS; given the results from this study, other two may be considered as high efficacy alongside Natalizumab, Alemtuzumab and Ocrelizumab.

Hearing gravity from the cosmos: GWTC-2 probes general relativity at cosmological scales

Gravitational-wave (GW) catalogs are rapidly increasing in number, allowing for statistical analyses of the population of compact binaries. Nonetheless, GW inference of cosmology has typically relied on additional electromagnetic counterparts or galaxy catalogs. I present a new probe of cosmological modifications of general relativity with GW data only. I focus on deviations of the GW luminosity distance constrained with the astrophysical population of binary black holes (BBHs). The three key observables are 1) the number of events as a function of luminosity distance, 2) the stochastic GW background of unresolved binaries and 3) the location of any feature in the source mass distribution, such as the pair instability supernova (PISN) gap. Modifications of the GW luminosity distance are a priori degenerate with the unknown evolution of the merger rate and source masses. However, a large damping of the GW amplitude predicts a reduction of the events and lowering of the edges of the PISN gap with redshift that is against standard astrophysical expectations. Applying a hierarchical Bayesian analysis to the current LIGO–Virgo catalog (GWTC-2), the strongest constraints to date are placed on deviations from the GW luminosity distance, finding cM=−3.2−2.0+3.4 at 68% C.L., which is ∼10 times better than multi-messenger GW170817 bounds. These modifications also affect the determination of the BBH masses, which is crucial to accommodate the high-mass binary GW190521 away from the PISN gap. In this analysis it is found that the maximum mass of 99% of the population shifts to lower masses with increased uncertainty, m99%=46.2−9.1+11.4M⊙ at 68% C.L. Testing gravity at large scales with the population of BBHs will become increasingly relevant with future catalogs, providing an independent and self-contained test of the standard cosmological model.

Imaging modalities for the detection of posterior pelvic floor disorders in women with obstructed defaecation syndrome.

Imaging modalities for the detection of posterior pelvic floor disorders in women with obstructed defaecation syndrome.

Surgical Management of Focal Chondral Defects of the Talus: A Bayesian Network Meta-analysis

Background: No consensus has been reached regarding the optimal surgical treatment for focal chondral defects of the talus. Purpose: A Bayesian network meta-analysis was conducted to compare the clinical scores and complications of mosaicplasty, osteochondral auto- and allograft transplant, microfracture, matrix-assisted autologous chondrocyte transplant, and autologous matrix-induced chondrogenesis (AMIC) for chondral defects of the talus at midterm follow-up. Study Design: Bayesian network meta-analysis; Level of evidence, 4. Methods: This Bayesian network meta-analysis followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions. PubMed, Embase, Google Scholar, and Scopus databases were accessed in February 2021. All clinical trials comparing 2 or more surgical interventions for the management of chondral defects of the talus were accessed. The outcomes of interest were visual analog scale (VAS) score, American Orthopaedic Foot and Ankle Society (AOFAS) score, rate of failure, and rate of revision surgery. The network meta-analysis were performed through the routine for Bayesian hierarchical random-effects model analysis. The log odds ratio (LOR) effect measure was used for dichotomous variables, and the standardized mean difference (SMD) was used for continuous variables. Results: Data from 13 articles (521 procedures) were retrieved. The median length of the follow-up was 47.8 months (range, 31.7-66.8 months). Analysis of variance revealed no difference between the treatment groups at baseline in terms of age, sex, body mass index, AOFAS score, VAS score, and mean number of defects. AMIC demonstrated the greatest AOFAS score (SMD, 11.27) and lowest VAS score (SMD, –2.26) as well as the lowest rates of failure (LOR, 0.94) and revision (LOR, 0.94). The test for overall inconsistency was not significant. Conclusion: At approximately 4 years of follow-up, the AMIC procedure for management of focal chondral defects of the talus produced the best outcome.

BbsBayes: An R Package for Hierarchical Bayesian Analysis of North American Breeding Bird Survey Data

The North American Breeding Bird Survey (BBS) is the primary ecological monitoring program used to assess the population, status, and trends of North American birds. As such, accessible analysis of BBS data is crucial to wildlife conservation/management and ecological science in North America. The R package <em>bbsBayes</em> was developed as a wrapper for the analysis of BBS data using hierarchical Bayesian models, including the models currently used by the Canadian Wildlife Service and the United States Geological Survey. The goal of <em>bbsBayes</em> is to provide an accessible package for anyone in the conservation community to estimate population trajectories (time-series) and trends (rates of change) for any of the 400+ bird species monitored by the BBS, and to allow more advance users to easily access the data and model-templates necessary to customize an analysis for their research.

Bayesian Hierarchical Factor Analysis for Efficient Estimation Across Race/Ethnicity

Patient reported outcomes are gaining more attention in patient-centered health outcomes research and quality of life studies as important indicators of clinical outcomes, especially for patients with chronic diseases. Factor analysis is ideal for measuring patient reported outcomes. If there is heterogeneity in the patient population and when sample size is small, differential item functioning and convergence issues are challenges for applying factor models. Bayesian hierarchical factor analysis can assess health disparity by assessing for di˙erential item functioning, while avoiding convergence problems. We conducted a simulation study and used an empirical example with American Indian minorities to show thatffitting a Bayesian hierarchical factor model is an optimal solution regardless of heterogeneity of population and sample size.