Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Building predictive models of soil particle-size distribution

Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.

Random diffusion and leverage effect in financial markets

We prove that Brownian market models with random diffusion coefficients provide an exact measure of the leverage effect [J-P. Bouchaud et al., Phys. Rev. Lett. 87, 228701 (2001)]. This empirical fact asserts that past returns are anticorrelated with future diffusion coefficient. Several models with random diffusion have been suggested but without a quantitative study of the leverage effect. Our analysis lets us to fully estimate all parameters involved and allows a deeper study of correlated random diffusion models that may have practical implications for many aspects of financial markets.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Exposure to bioaerosols, respiratory health and lung-specific proteins: a prospective study in garbage and wastewater workers.

Objectives To prospectively assess respiratory health in wastewater workers and garbage collectors over 5 years. Methods Exposure, respiratory symptoms and conditions, spirometry and lung-specific proteins were assessed yearly in a cohort of 304 controls, 247 wastewater workers and 52 garbage collectors. Results were analysed with random coefficient models and linear regression taking into account several potential confounders. Results Symptoms, spirometry and lung-specific proteins were not affected by occupational exposure. Conclusions In this population no effects of occupational exposure to bioaerosols were found, probably because of good working conditions.

The Persistence of Finnish Equity Fund Performance

Tutkimuksen tavoitteena on selvittää, esiintyykö suomeen sijoittavilla osakerahastoilla menestyksen pysyvyyttä. Tutkimusaineisto koostuu kaikista suomalaisista osakerahastoista, jotka toimivat ajanjaksolla 15.1.1998-13.1.2005. Aineisto on vapaa selviytymisvinoumasta. Suorituskyvyn mittareina käytetään CAPM-alfaa sekä kolmi- ja nelifaktori-alfaa. Empiirisessä osassa osakerahastojen menestyksen pysyvyyttä testataan Spearmanin järjestyskorrelaatiotestillä. Evidenssi menestyksen pysyvyydestä jäi vähäiseksi, vaikkakin sitä esiintyi satunnaisesti kaikilla menestysmittareilla joillakin ranking- ja sijoitusperiodin yhdistelmillä. CAPM-alfalla tarkasteltuna tilastollisesti merkitsevää menestyksen pysyvyyttä esiintyi selvästi useammin kuin muilla menestysmittareilla. Tulokset tukevat viimeaikaisia kansainvälisiä tutkimuksia, joiden mukaan menestyksen pysyvyys riippuu usein mittaustavasta. Menestysmittareina käytettyjen regressiomallien merkitsevyystestit osoittavat multifaktorimallien selittävän osakerahastojen tuottoja CAPM:a paremmin. Lisätyt muuttujat parantavat merkittävästi CAPM:n selitysvoimaa.

Evidence for chronic low-grade systemic inflammation in individuals with agoraphobia from a population-based prospective study.

BACKGROUND: Anxiety disorders have been linked to an increased risk of incident coronary heart disease in which inflammation plays a key pathogenic role. To date, no studies have looked at the association between proinflammatory markers and agoraphobia. METHODS: In a random Swiss population sample of 2890 persons (35-67 years, 53% women), we diagnosed a total of 124 individuals (4.3%) with agoraphobia using a validated semi-structured psychiatric interview. We also assessed socioeconomic status, traditional cardiovascular risk factors (i.e., body mass index, hypertension, blood glucose levels, total cholesterol/high-density lipoprotein-cholesterol ratio), and health behaviors (i.e., smoking, alcohol consumption, and physical activity), and other major psychiatric diseases (other anxiety disorders, major depressive disorder, drug dependence) which were treated as covariates in linear regression models. Circulating levels of inflammatory markers, statistically controlled for the baseline demographic and health-related measures, were determined at a mean follow-up of 5.5 ± 0.4 years (range 4.7 - 8.5). RESULTS: Individuals with agoraphobia had significantly higher follow-up levels of C-reactive protein (p = 0.007) and tumor-necrosis-factor-α (p = 0.042) as well as lower levels of the cardioprotective marker adiponectin (p = 0.032) than their non-agoraphobic counterparts. Follow-up levels of interleukin (IL)-1β and IL-6 did not significantly differ between the two groups. CONCLUSIONS: Our results suggest an increase in chronic low-grade inflammation in agoraphobia over time. Such a mechanism might link agoraphobia with an increased risk of atherosclerosis and coronary heart disease, and needs to be tested in longitudinal studies.

Domains of importance to the quality of life of older people from two Swiss regions

BACKGROUND: quality of life (QoL) is a subjective perception whose components may vary in importance between individuals. Little is known about which domains of QoL older people deem most important. OBJECTIVE: this study investigated in community-dwelling older people the relationships between the importance given to domains defining their QoL and socioeconomic, demographic and health status. METHODS: data were compiled from older people enrolled in the Lc65+ cohort study and two additional, population-based, stratified random samples (n = 5,300). Principal components analysis (PCA) was used to determine the underlying domains among 28 items that participants defined as important to their QoL. The components extracted were used as dependent variables in multiple linear regression models to explore their associations with socioeconomic, demographic and health status. RESULTS: PCA identified seven domains that older persons considered important to their QoL. In order of importance (highest to lowest): feeling of safety, health and mobility, autonomy, close entourage, material resources, esteem and recognition, and social and cultural life. A total of six and five domains of importance were significantly associated with education and depressive symptoms, respectively. The importance of material resources was significantly associated with a good financial situation (β = 0.16, P = 0.011), as was close entourage with living with others (β = 0.20, P = 0.007) and as was health and mobility with age (β = -0.16, P = 0.014). CONCLUSION: the importance older people give to domains of their QoL appears strongly related to their actual resources and experienced losses. These findings may help clinicians, researchers and policy makers better adapt strategies to individuals' needs.

Long term trends in prevalence of neural tube defects in Europe: population based study.

STUDY QUESTION: What are the long term trends in the total (live births, fetal deaths, and terminations of pregnancy for fetal anomaly) and live birth prevalence of neural tube defects (NTD) in Europe, where many countries have issued recommendations for folic acid supplementation but a policy for mandatory folic acid fortification of food does not exist? METHODS: This was a population based, observational study using data on 11 353 cases of NTD not associated with chromosomal anomalies, including 4162 cases of anencephaly and 5776 cases of spina bifida from 28 EUROCAT (European Surveillance of Congenital Anomalies) registries covering approximately 12.5 million births in 19 countries between 1991 and 2011. The main outcome measures were total and live birth prevalence of NTD, as well as anencephaly and spina bifida, with time trends analysed using random effects Poisson regression models to account for heterogeneities across registries and splines to model non-linear time trends. SUMMARY ANSWER AND LIMITATIONS: Overall, the pooled total prevalence of NTD during the study period was 9.1 per 10 000 births. Prevalence of NTD fluctuated slightly but without an obvious downward trend, with the final estimate of the pooled total prevalence of NTD in 2011 similar to that in 1991. Estimates from Poisson models that took registry heterogeneities into account showed an annual increase of 4% (prevalence ratio 1.04, 95% confidence interval 1.01 to 1.07) in 1995-99 and a decrease of 3% per year in 1999-2003 (0.97, 0.95 to 0.99), with stable rates thereafter. The trend patterns for anencephaly and spina bifida were similar, but neither anomaly decreased substantially over time. The live birth prevalence of NTD generally decreased, especially for anencephaly. Registration problems or other data artefacts cannot be excluded as a partial explanation of the observed trends (or lack thereof) in the prevalence of NTD. WHAT THIS STUDY ADDS: In the absence of mandatory fortification, the prevalence of NTD has not decreased in Europe despite longstanding recommendations aimed at promoting peri-conceptional folic acid supplementation and existence of voluntary folic acid fortification. FUNDING, COMPETING INTERESTS, DATA SHARING: The study was funded by the European Public Health Commission, EUROCAT Joint Action 2011-2013. HD and ML received support from the European Commission DG Sanco during the conduct of this study. No additional data available.

Effects of cobalt-chromium everolimus eluting stents or bare metal stent on fatal and non-fatal cardiovascular events: patient level meta-analysis

Objectives: To examine the safety and effectiveness of cobalt-chromium everolimus eluting stents compared with bare metal stents. Design: Individual patient data meta-analysis of randomised controlled trials. Cox proportional regression models stratified by trial, containing random effects, were used to assess the impact of stent type on outcomes. Hazard ratios with 95% confidence interval for outcomes were reported. Data sources and study selection: Medline, Embase, the Cochrane Central Register of Controlled Trials. Randomised controlled trials that compared cobalt-chromium everolimus eluting stents with bare metal stents were selected. The principal investigators whose trials met the inclusion criteria provided data for individual patients. Primary outcomes: The primary outcome was cardiac mortality. Secondary endpoints were myocardial infarction, definite stent thrombosis, definite or probable stent thrombosis, target vessel revascularisation, and all cause death. Results: The search yielded five randomised controlled trials, comprising 4896 participants. Compared with patients receiving bare metal stents, participants receiving cobalt-chromium everolimus eluting stents had a significant reduction of cardiac mortality (hazard ratio 0.67, 95% confidence interval 0.49 to 0.91; P=0.01), myocardial infarction (0.71, 0.55 to 0.92; P=0.01), definite stent thrombosis (0.41, 0.22 to 0.76; P=0.005), definite or probable stent thrombosis (0.48, 0.31 to 0.73; P<0.001), and target vessel revascularisation (0.29, 0.20 to 0.41; P<0.001) at a median follow-up of 720 days. There was no significant difference in all cause death between groups (0.83, 0.65 to 1.06; P=0.14). Findings remained unchanged at multivariable regression after adjustment for the acuity of clinical syndrome (for instance, acute coronary syndrome v stable coronary artery disease), diabetes mellitus, female sex, use of glycoprotein IIb/IIIa inhibitors, and up to one year v longer duration treatment with dual antiplatelets. Conclusions: This meta-analysis offers evidence that compared with bare metal stents the use of cobalt-chromium everolimus eluting stents improves global cardiovascular outcomes including cardiac survival, myocardial infarction, and overall stent thrombosis.

Effects of cobalt-chromium everolimus eluting stents or bare metal stent on fatal and non-fatal cardiovascular events: patient level meta-analysis

Objectives: To examine the safety and effectiveness of cobalt-chromium everolimus eluting stents compared with bare metal stents. Design: Individual patient data meta-analysis of randomised controlled trials. Cox proportional regression models stratified by trial, containing random effects, were used to assess the impact of stent type on outcomes. Hazard ratios with 95% confidence interval for outcomes were reported. Data sources and study selection: Medline, Embase, the Cochrane Central Register of Controlled Trials. Randomised controlled trials that compared cobalt-chromium everolimus eluting stents with bare metal stents were selected. The principal investigators whose trials met the inclusion criteria provided data for individual patients. Primary outcomes: The primary outcome was cardiac mortality. Secondary endpoints were myocardial infarction, definite stent thrombosis, definite or probable stent thrombosis, target vessel revascularisation, and all cause death. Results: The search yielded five randomised controlled trials, comprising 4896 participants. Compared with patients receiving bare metal stents, participants receiving cobalt-chromium everolimus eluting stents had a significant reduction of cardiac mortality (hazard ratio 0.67, 95% confidence interval 0.49 to 0.91; P=0.01), myocardial infarction (0.71, 0.55 to 0.92; P=0.01), definite stent thrombosis (0.41, 0.22 to 0.76; P=0.005), definite or probable stent thrombosis (0.48, 0.31 to 0.73; P<0.001), and target vessel revascularisation (0.29, 0.20 to 0.41; P<0.001) at a median follow-up of 720 days. There was no significant difference in all cause death between groups (0.83, 0.65 to 1.06; P=0.14). Findings remained unchanged at multivariable regression after adjustment for the acuity of clinical syndrome (for instance, acute coronary syndrome v stable coronary artery disease), diabetes mellitus, female sex, use of glycoprotein IIb/IIIa inhibitors, and up to one year v longer duration treatment with dual antiplatelets. Conclusions: This meta-analysis offers evidence that compared with bare metal stents the use of cobalt-chromium everolimus eluting stents improves global cardiovascular outcomes including cardiac survival, myocardial infarction, and overall stent thrombosis.

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

Multivariate study and regression analysis of gluten-free granola

This study developed a gluten-free granola and evaluated it during storage with the application of multivariate and regression analysis of the sensory and instrumental parameters. The physicochemical, sensory, and nutritional characteristics of a product containing quinoa, amaranth and linseed were evaluated. The crude protein and lipid contents ranged from 97.49 and 122.72 g kg-1 of food, respectively. The polyunsaturated/saturated, and n-6:n-3 fatty acid ratios ranged from 2.82 and 2.59:1, respectively. Granola had the best alpha-linolenic acid content, nutritional indices in the lipid fraction, and mineral content. There were good hygienic and sanitary conditions during storage; probably due to the low water activity of the formulation, which contributed to inhibit microbial growth. The sensory attributes ranged from 'like very much' to 'like slightly', and the regression models were highly fitted and correlated during the storage period. A reduction in the sensory attribute levels and in the product physical stabilisation was verified by principal component analysis. The use of the affective test acceptance and instrumental analysis combined with statistical methods allowed us to obtain promising results about the characteristics of gluten-free granola.

The chronic kidney disease outcomes and practice patterns study Brazil (CKDopps-Brazil): Design, data and methodology

Introduction: The chronic kidney disease outcomes and practice patterns study (CKDopps) is an international observational, prospective, cohort study involving patients with chronic kidney disease (CKD) stages 3-5 [estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2, with a major focus upon care during the advanced CKD period (eGFR < 30 ml/min/1.73 m2)]. During a 1-year enrollment period, each one of the 22 selected clinics will enroll up to 60 advanced CKD patients (eGFR < 30 ml/min/1.73 m2 and not dialysis-dependent) and 20 earlier stage CKD patients (eGFR between 30-59 ml/min/1.73 m2). Exclusion criteria: age < 18 years old, patients on chronic dialysis or prior kidney transplant. The study timeline include up to one year for enrollment of patients at each clinic starting in the end of 2013, followed by up to 2-3 years of patient follow-up with collection of detailed longitudinal patient-level data, annual clinic practice-level surveys, and patient surveys. Analyses will apply regression models to evaluate the contribution of patient-level and clinic practice-level factors to study outcomes, and utilize instrumental variable-type techniques when appropriate. Conclusion: Launching in 2013, CKDopps Brazil will study advanced CKD care in a random selection of nephrology clinics across Brazil to gain understanding of variation in care across the country, and as part of a multinational study to identify optimal treatment practices to slow kidney disease progression and improve outcomes during the transition period to end-stage kidney disease.