Two decades of fumigation data from the Soybean Free Air Concentration Enrichment facility.

The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations.

The implementation of random survival forests in conflict management data: An examination of power sharing and third party mediation in post-conflict countries.

Time-to-event analysis is a common occurrence in political science. In recent years, there has been an increased usage of machine learning methods in quantitative political science research. This article advocates for the implementation of machine learning duration models to assist in a sound model selection process. We provide a brief tutorial introduction to the random survival forest (RSF) algorithm and contrast it to a popular predecessor, the Cox proportional hazards model, with emphasis on methodological utility for political science researchers. We implement both methods for simulated time-to-event data and the Power-Sharing Event Dataset (PSED) to assist researchers in evaluating the merits of machine learning duration models. We provide evidence of significantly higher survival probabilities for peace agreements with 3rd party mediated design and implementation. We also detect increased survival probabilities for peace agreements that incorporate territorial power-sharing and avoid multiple rebel party signatories. Further, the RSF, a previously under-used method for analyzing political science time-to event data, provides a novel approach for ranking of peace agreement criteria importance in predicting peace agreement duration. Our findings demonstrate a scenario exhibiting the interpretability and performance of RSF for political science time-to-event data. These findings justify the robust interpretability and competitive performance of the random survival forest algorithm in numerous circumstances, in addition to promoting a diverse, holistic model-selection process for time-to-event political science data.

Exploratory factor analysis of PROMIS-29 V1.0, PROMIS Global Health and the RAND SF-36 from chiropractic responders attending care in a practice-based research network.

BACKGROUND: The SF-36 questionnaire is perhaps the most widely used quality of life instrument in the world today, while the PROMIS instruments continue to gain popularity. Given their continued use in chiropractic research and practice, we examined their latent domain structure using exploratory factor analysis (EFA). METHODS: To uncover latent structures of a large series of measured variables from the PROMIS-29, PROMIS Global Health and RAND SF-36 domains, we defined a factor analysis model represented by the equation [Formula: see text], where [Formula: see text] is the matrix of random vectors corresponding to the domains with a mean of [Formula: see text] and the covariance matrix [Formula: see text] [Formula: see text] denotes the matrix of factor loadings, [Formula: see text] denotes the matrix of unobserved latent variables that influence the collection of domains and [Formula: see text] is the vector of latent error terms. The matrix of item responses X was the only observed quantity with restrictions such that variable scores were uncorrelated and of unit variance with the latent errors being independent with the variance vector [Formula: see text]. The inherited structure of X was expressed simply by [Formula: see text]. Orthogonal and oblique rotations were performed on the [Formula: see text] matrix with this equation to improve clarity of the latent structure. Model parameters [Formula: see text] were optimized using the method of minimum residuals. Each EFA model was constructed with Pearson and Polychoric correlation. RESULTS: For the PROMIS-29, domains were confirmed to be strongly correlated with Factor 1 (i.e., mental health) or Factor 2 (i.e., physical health). Satisfaction with participation in social roles was highly correlated with a 3rd factor (i.e., social health). For the PROMIS Global Health Scale, a 2-factor EFA confirmed the GPH and GMH domains. For the RAND SF-36, an apparent lack of definable structure was observed except for physical function which had a high correlational relationship with Factor 2. The remaining domains lacked correlation with any factors. CONCLUSION: Distinct separation in the latent factors between presumed physical, mental and social health domains were found with the PROMIS instruments but relatively indistinguishable domains in the RAND SF-36. We encourage continued efforts in this area of research to improving patient reported outcomes.

Smoothing splines of apex predator movement: Functional modeling strategies for exploring animal behavior and social interactions.

The collection of animal position data via GPS tracking devices has increased in quality and usage in recent years. Animal position and movement, although measured discretely, follows the same principles of kinematic motion, and as such, the process is inherently continuous and differentiable. I demonstrate the functionality and visual elegance of smoothing spline models. I discuss the challenges and benefits of implementing such an approach, and I provide an analysis of movement and social interaction of seven jaguars inhabiting the Taiamã Ecological Station, Pantanal, Brazil, a region with the highest known density of jaguars. In the analysis, I derive measures for pairwise distance, cooccurrence, and spatiotemporal association between jaguars, borrowing ideas from density estimation and information theory. These measures are feasible as a result of spline model estimation, and they provide a critical tool for a deeper investigation of cooccurrence duration, frequency, and localized spatio-temporal relationships between animals. In this work, I characterize a variety of interactive relationships between pairs of jaguars, and I particularly emphasize the relationships in movement of two male-female and two male-male jaguar pairs exhibiting highly associative relationships.

Towards a safety culture in chiropractic: The use of the safety, communication, Operational Reliability, and engagement (SCORE) questionnaire.

OBJECTIVE: To assess the attitudes, practices and other contributing factors to patient safety among chiropractors. METHODS: In addition to obtaining socio-demographic and practitioner/practice characteristics, we utilized the Safety, Communication, Operational Reliability, and Engagement (SCORE) questionnaire. To identify variables contributing to improved safety climate and lower burnout, we performed a random forest analysis. RESULTS: A convenience sample of 154 chiropractor responders (Female = 115; Male = 39) comprised our study population. The majority were between 26 and 35 years of age with an average practice experience of 11.1 years. The variables of importance predictive for a safety climate were participating in decision making, teamwork, local leadership and improvement readiness. For burnout, workload, growth opportunities, teamwork climate, safety climate and work-life balance were highly influential. CONCLUSION: We successfully utilized the SCORE instrument to measure safety climate in chiropractic. We identified those variables important to contributing to patient safety and mitigating burnout in the workplace.

The relationship between quality of life and sense of coherence in patients presenting for care in a chiropractic practice-based research network.

INTRODUCTION: Antonovsky's sense of coherence (SOC) has been shown to positively correlate with quality of life (QoL). We examined the relationship between socio-demographic data and clinical covariates along with various QoL domains to SOC in patients presenting for care within a chiropractic practice-based research network. METHODS: In addition to providing socio-demographic information and clinical covariates, patients attending care within a PBRN completed the PROMIS-29 and PROMIS global health to measure of QoL and SOC-29 to measure SOC at baseline. In addition to descriptive statistics, we utilized a random forest analysis to assess the predictively ability of covariates to SOC. RESULTS: Our dataset was comprised of a convenience sample of 1980 responders (average age = 40.72 years; 1494 females and 486 males). The mean T scores (T1/T2) for the various QoL domains physical functioning (50.97), anxiety (52.03), depression (47.47), fatigue (51.15), ability to participate in social roles and activities (54.44), sleep disturbance (59.85), pain interference (51.27), global physical health (GPH) (49.34) and global mental health (GMH) (50.69). Mean pain intensity rating was 4.23. The mean SOC-29 was 148.34. The most important covariates to changes in SOC were: GPH, depression, anxiety age, fatigue and sleep disturbance. Partial dependence plots revealed that increasing GPH, GMH and age of patient predict increasing SOC. A high SOC was predicted in the presence of low GPH given a high GMH scoring. CONCLUSIONS: The mental health QoL domains had a stronger predictability for SOC than physical health domains.