Fitting Additive Binomial Regression Models with the R Package blm

The R package blm provides functions for fitting a family of additive regression models to binary data. The included models are the binomial linear model, in which all covariates have additive effects, and the linear-expit (lexpit) model, which allows some covariates to have additive effects and other covariates to have logisitc effects. Additive binomial regression is a model of event probability, and the coefficients of linear terms estimate covariate-adjusted risk differences. Thus, in contrast to logistic regression, additive binomial regression puts focus on absolute risk and risk differences. In this paper, we give an overview of the methodology we have developed to fit the binomial linear and lexpit models to binary outcomes from cohort and population-based case-control studies. We illustrate the blm packages methods for additive model estimation, diagnostics, and inference with risk association analyses of a bladder cancer nested case-control study in the NIH-AARP Diet and Health Study

Policies and Protocols to Prevent the Spread and Costs of Clostridium Difficile Infection

Background: Clostridium Difficile Infection (CDI) is a highly contagious, potentially lethal, and often preventable hospital acquired infection that costs the U.S. healthcare system billions of dollars annually. Because of the serious consequences and expensive nature of CDI, it is predicted the Centers for Medicare and Medicaid Services will begin following CDI trends and basing reimbursement on how well a facility can protect against this infection. Objectives: The overall purpose of this quality improvement project was to develop, implement, and evaluate an evidenced-based protocol to guide the staff of the University of Cincinnati Medical Center (UCMC) to recognize and prevent the spread of CDI to all hospitalized patients. Methods: A multidisciplinary committee was formed to evaluate UCMC’s current CDI practices and determine which evidence-based interventions should be included in any policy changes. After a comprehensive review of the literature and staff interviews were performed, the CDI prevention interventions selected for this project included: standardized room cleaning, use of ultraviolet lighting, updated antimicrobial stewardship practices, disposable gown use, and staff education. Results: After a review of the isolation protocol there were practices found that were not conducive to preventing the spread of CDI, and the committee focused on three aims: instituting reusable gowns while changing the process for ordering isolation supplies, education through online PowerPoint instruction, and implementing changes on a pilot unit. These changes resulted in 19 fewer cases of CDI at UCMC in the first six months of the current fiscal year. Conclusions: A multicomponent, interprofessional, evidence-based, CDI prevention protocol may decrease the risk of hospital-acquired infections.No embarg

Aging and decision making: a comparison between neurologically healthy elderly and young individuals

We report the results of experiments on economic decisions with two populations, one of healthy elderly individuals (average age 82) and one of younger students (average age 20). We examine confidence, decisions under uncertainty, differences between willingness to pay and willingness to accept and the theory of mind (strategic thinking). Our findings indicate that the older adults’ decision behavior is similar to that of young adults, contrary to the notion that economic decision making is impaired with age. Moreover, some of the demonstrated decision behaviors suggest that the elderly individuals are less biased than the younger individuals

Comparing subjective and objective evaluations of player performance in Australian Rules football

Player evaluation plays a fundamental role in the decision-making processes of professional sporting organisations. In the Australian Football League, both subjective and objective evaluations of player match performance are commonplace. This study aimed to identify the extent to which performance indicators can explain subjective ratings of player performance. A secondary aim was to compare subjective and objective ratings of player performance. Inside Football Player Ratings (IFPR) and Australian Football League Player Ratings were collected as subjective and objective evaluations of player performance, respectively, for each player during all 1026 matches throughout the 2013-2017 Australian Football League seasons. Nine common player performance indicators, player role classification, player age and match outcomes were also collected. Standardised linear mixed model and recursive partitioning and regression tree models were undertaken across the whole dataset, as well as separately for each of the seven player roles. The mixed model analysis produced a model associating the performance indicators with IFPR at a root mean square error of 0.98. Random effects accounting for differences between seasons and players ranged by 0.09 and 1.73 IFPR each across the five seasons and 1052 players, respectively. The recursive partitioning and regression tree model explained IFPR exactly in 35.8% of instances, and to within 1.0 IFPR point in 81.0% of instances. When analysed separately by player role, exact explanation varied from 25.2% to 41.7%, and within 1.0 IFPR point from 70.3% to 88.6%. Overall, kicks and handballs were most associated with the IFPR. This study highlights that a select few features account for a majority of the variance when explaining subjective ratings of player performance, and that these vary by player role. Australian Football League organisations should utilise both subjective and objective assessments of performance to gain a better understanding of the differences associated with subjective performance assessment

Validation of the Australian Football League Player Ratings

This study investigated the validity of the official Australian Football League Player Ratings system. It also aimed to determine the extent to which the distribution of points across the 13 rating subcategories could explain Australian Football League match outcome. Ratings were obtained for each player from Australian Football League matches played during the 2013–2016 seasons, along with the corresponding match outcome (Win/Loss and score margin). The values for each of the 13 subcategories that comprise the ratings were also obtained for the 2016 season. Total team rating scores were derived as an objective team outcome for each match. Percentage agreement and Pearson correlational analyses revealed that winning teams displayed a higher total team rating in 94.2% of matches and an association of r = 0.96 (95% confidence interval = 0.95–0.96) between match score margin and total team rating differential, respectively. A Partial Decision Tree (PART) analysis resulted in seven rules capable of determining the extent to which relative contributions of rating subcategories explain Win/Loss at an accuracy of 79.3%. These models support the validity of the Australian Football League Player Ratings system and its use as a pertinent system for objective player analyses in the Australian Football League. </jats:p

Aging and decision making: A comparison between neurologically healthy elderly and young individuals

We report the results of experiments on economic decisions with two populations, one of healthy elderly individuals (average age 82) and one of younger students (average age 20). We examine confidence, decisions under uncertainty, differences between willingness to pay and willingness to accept and the theory of mind (strategic thinking). Our findings indicate that the older adults’ decision behavior is similar to that of young adults, contrary to the notion that economic decision making is impaired with age. Choices over lotteries do not reflect the age differences previously reported in the psychology and biology literature. Moreover, some of the demonstrated decision behaviors suggest that the elderly individuals are less biased than the younger individuals.(1)There is a greater prevalence of overconfident behavior in the younger population. (2) Our results show no significant support for a theory of an endowment effect in either population. (3) Both populations perform similarly on the beauty contest task, although there is a modest indication of a higher incidence of confused behavior by the older

Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League

This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players (n = 1052) from the 1034 matches played during the 2013–2017 seasons, along with data pertaining to the abovementioned player characteristics. Two separate linear mixed models revealed that all factors influenced player performance, with age and experience the strongest in each model, respectively. Post hoc Tukey tests indicated that performance was affected by age at each level up until the age of 21 (effect ranging from 0.98 to 3.70 rating points), and by experience at the levels 1–20 and 21–40 matches in comparison to all higher levels of experience (effect ranging from 1.01 to 3.77 rating points). Two segmented models indicated that a point of marginal gains exists within longitudinal performance progression between the age levels 22 and 23, and the experience levels 41–60 and 61–80 matches. Professional sporting organisations may apply the methods provided here to support decisions regarding player recruitment and development