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Profile monitoring is defined as the act of utilizing regression and quality control techniques to monitor the functional relationship between a response variable and one or more regressors. Most of the previous studies focused either on parametric modeling of profiles or assumed the response variable followed a normal distribution, but that is an unrealistic scenario in most cases. In this study, a Haar wavelet approach is applied for profile monitoring of Poisson data. We showed via simulation that, Haar wavelet can outperform parametric models when there is a sudden jump in the profile and concluded with a case study. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak of 2020 has required many governments to develop mathematical-statistical models of the outbreak for policy and planning purposes. This work provides a tutorial on building a compartmental model using Susceptibles, Exposed, Infected, Recovered and Deaths (SEIRD) status through time. A Bayesian Framework is utilized to perform both parameter estimation and predictions. This model uses interventions to quantify the impact of various government attempts to slow the spread of the virus. Predictions are also made to determine when the peak Active Infections will occur. [ABSTRACT FROM AUTHOR]

The increase of exposure to toxic materials and hazardous chemicals is a major concern due to the adverse effect on human health. Among the major concerns of toxicologists is to determine acceptable levels of exposure to hazardous substances. Current approaches often evaluate each endpoint and stressor individually. We propose a novel method to simultaneously determine the Benchmark Dose Tolerable Region (BMDTR) for multiple endpoint and multiple stressor studies by adopting a Bayesian approach. A main concern while assessing the combined toxicological effect of a chemical mixture is the anticipated type of the combined action (i.e. synergistic or antagonistic); thus it was essential to account for interaction effects to handle this situation, imposing more challenges due to the non-linearity of the tolerable region. The proposed method will be evaluated using two approaches, the first one using the estimated value of the posterior median and the second approach using all MCMC samples from the posterior distribution. Furthermore, we propose a new method to determine the endpoint probabilities for each endpoint, which reflects the importance of each endpoint in helping determining the boundaries of the benchmark dose tolerable region (BMDTR). [ABSTRACT FROM AUTHOR]

The problem of statistical calibration of a measuring instrument can be framed both in a statistical context as well as in an engineering context. In the first, the problem is dealt with by distinguishing between the ‘classical’ approach and the ‘inverse’ regression approach. Both of these models are static models and are used to estimate exact measurements from measurements that are affected by error. In the engineering context, the variables of interest are considered to be taken at the time at which you observe it. The Bayesian time series analysis method of Dynamic Linear Models can be used to monitor the evolution of the measures, thus introducing adynamicapproach to statistical calibration. The research presented employs a new approach to performing statistical calibration. A simulation study in the context of microwave radiometry is conducted that compares the dynamic model to traditional static frequentist and Bayesian approaches. The focus of the study is to understand how well thedynamic statistical calibrationmethod performs under various signal-to-noise ratios,r. [ABSTRACT FROM PUBLISHER]

Bayesian analysis often requires the researcher to employ Markov Chain Monte Carlo (MCMC) techniques to draw samples from a posterior distribution which in turn is used to make inferences. Currently, several approaches to determine convergence of the chain as well as sensitivities of the resulting inferences have been developed. This work develops a Hellinger distance approach to MCMC diagnostics. An approximation to the Hellinger distance between two distributionsfandgbased on sampling is introduced. This approximation is studied via simulation to determine the accuracy. A criterion for using this Hellinger distance for determining chain convergence is proposed as well as a criterion for sensitivity studies. These criteria are illustrated using a dataset concerning theAnguilla australis, an eel native to New Zealand. [ABSTRACT FROM PUBLISHER]

Strength, when considering gender and race, provides a basis for training, hiring, and retention for police officers. The purpose of this study is to identify muscular strength differences among racial groups from initial-recruit to in-service tests. Strength variables included bench press, bench press/lean mass and bench press/body mass. Scores were retrieved for the 1990 to 1995 recruit classes and were paired to the 2006 in-service fitness log. Sample included 309 officers: 30 females (13 black, 17 white) and 279 males (41 black, 238 white). Mean age of recruit was 24.6 ± 3.4 years and for in-service was 37.1 ± 3.7 years. Time between tests was 12.5 ± 2.0 years. Bench press strength significantly increased for all gender and racial groups. Black males were significantly stronger in bench press at initial-recruit and at in-service than white males. All racial and gender groups increased in bench press/lean mass, however, the increase in white females was not significant. No differences were found between black and white females in all strength variables at both testing periods. Black males were significantly stronger than white males in bench press/body mass only at the initial-recruit test. White males showed a significant increase in bench press/body mass over time, but they did not reach the strength level of the black males at in-service. Police departments, with a properly designed physical fitness program, can expect to see increases in strength of personnel over the first half of their careers; however, there are gender and racial differences. [ABSTRACT FROM AUTHOR]

This paper presents new biostatistical methods for the analysis of microbiome data based on a fully parametric approach using all the data. The Dirichlet-multinomial distribution allows the analyst to calculate power and sample sizes for experimental design, perform tests of hypotheses (e.g., compare microbiomes across groups), and to estimate parameters describing microbiome properties. The use of a fully parametric model for these data has the benefit over alternative nonparametric approaches such as bootstrapping and permutation testing, in that this model is able to retain more information contained in the data. This paper details the statistical approaches for several tests of hypothesis and power/sample size calculations, and applies them for illustration to taxonomic abundance distribution and rank abundance distribution data using HMP Jumpstart data on 24 subjects for saliva, subgingival, and supragingival samples. Software for running these analyses is available. [ABSTRACT FROM AUTHOR]

Assessing the linear relationship between a set of continuous predictors and a continuous response is a well-studied problem in statistics and data mining. L2-based methods such as ordinary least squares and orthogonal regression can be used to determine this relationship. However, both of these methods become impaired when influential values are present. This problem becomes compounded when outliers confound standard diagnostics. This work proposes an L1-norm orthogonal regression method (L1OR) formulated as a nonconvex optimization problem. Solution strategies for finding globally optimal solutions are presented. Simulation studies are conducted to assess the resistance of the method to outliers and the consistency of the method. The method is also applied to real-world data arising from an environmental science application [ABSTRACT FROM AUTHOR]

Firefighters and police have different physical job requirements and selection processes. Firefighters have on-duty exercise time and police do not. This could affect body composition and strength. The purpose of this investigation was to compare body composition and bench press strength between firefighters and police officers in the Charlotte-Mecklenburg departments. Current 2006 fitness records were analyzed to compare firefighters and police (N = 2330). Variables included: gender, age, body mass, percent body-fat, fat mass, lean mass, bench press strength, bench press/lean mass, bench press/body mass, and percent that were obese. Significant (p ⩽ 0.05) differences were found between male firefighters and police in age (37.7 vs. 36.9 yrs), body mass (91.5 vs. 93.2 kg), percent body-fat (17.8% vs.18.5%), fat mass (16.9 vs. 18.0 kg), bench press strength (93.4 vs. 96.3 kg), bench press/body mass (1.03 vs.1.05) and percent that were obese (10% vs.17%), respectively. Significant differences between female firefighters and police were found in age (42.4 vs. 37.4 yrs), body mass (77.5 vs. 71.8 kg), lean mass (54.4 vs. 51.2 kg), bench press strength (52.3 vs. 43.9 kg), bench press/lean mass (0.99 vs. 0.86) and bench press/body mass (0.69 vs. 0.62), respectively. Male police were younger, weighed more, had higher percent body fat, higher percent of obesity, and had greater upper body strength than firefighters. Female police were younger, weighed less, had less lean mass and less upper body strength than their firefighter counterparts. Contributing factors might include pre-employment selection, recruit training, in-service physical fitness testing, and counseling provided by departments. [ABSTRACT FROM AUTHOR]

Impulsivity and the attentional orienting response to cocaine-associated cues ( cue reactivity ) promote relapse in cocaine-use disorder (CUD). A time-dependent escalation of cue reactivity ( incubation ) occurs during extended, forced abstinence from cocaine self-administration in rats. The investigational serotonin (5-HT) 5-HT 2A receptor (5-HT 2A R) antagonist/inverse agonist M100907 suppresses impulsive action , or the inability to withhold premature responses, and cocaine-seeking behaviors. The present preclinical study was designed to establish the potential for repurposing the Food and Drug Administration-approved selective 5-HT 2A R antagonist/inverse agonist pimavanserin as a therapeutic agent to forestall relapse vulnerability in CUD. In male Sprague-Dawley rats, pimavanserin suppressed impulsive action ( premature responses ) measured in the 1-choice serial reaction time (1-CSRT) task, similarly to M100907. We also used the 1-CSRT task to establish baseline levels of impulsive action before cocaine self-administration and evaluation of cue reactivity (lever presses reinforced by the discrete cue complex previously paired with cocaine delivery). We observed an incubation of cocaine cue reactivity between day 1 and day 30 of forced abstinence from cocaine self-administration. Baseline levels of impulsive action predicted incubated levels of cocaine cue reactivity in late abstinence. We also found that baseline impulsive action predicted the effectiveness of pimavanserin to suppress incubated cue reactivity in late abstinence from cocaine self-administration at doses that were ineffective in early abstinence. These data suggest that integration of clinical measures of impulsive action may inform refined, personalized pharmacotherapeutic intervention for the treatment of relapse vulnerability in CUD., (U.S. Government work not protected by U.S. copyright.)