Poisson-Based Inference for Perturbation Models in Adaptive Spelling Training
ERIC Educational Resources Information Center
Baschera, Gian-Marco; Gross, Markus
2010-01-01
We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…
77 FR 13691 - Qualification of Drivers; Exemption Applications; Vision
Federal Register 2010, 2011, 2012, 2013, 2014
2012-03-07
..., ocular hypertension, retinal detachment, cataracts and corneal scaring. In most cases, their eye... Application of Multiple Regression Analysis of a Poisson Process,'' Journal of American Statistical...
Poisson Mixture Regression Models for Heart Disease Prediction.
Mufudza, Chipo; Erol, Hamza
2016-01-01
Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.
Poisson Mixture Regression Models for Heart Disease Prediction
Erol, Hamza
2016-01-01
Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611
Yelland, Lisa N; Salter, Amy B; Ryan, Philip
2011-10-15
Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, despite a lack of evidence to support its use in this setting. The purpose of this article is to evaluate the performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data, by using generalized estimating equations to account for clustering. A simulation study is conducted to compare log binomial regression and modified Poisson regression for analyzing clustered data from intervention and observational studies. Both methods generally perform well in terms of bias, type I error, and coverage. Unlike log binomial regression, modified Poisson regression is not prone to convergence problems. The methods are contrasted by using example data sets from 2 large studies. The results presented in this article support the use of modified Poisson regression as an alternative to log binomial regression for analyzing clustered prospective data when clustering is taken into account by using generalized estimating equations.
Modified Regression Correlation Coefficient for Poisson Regression Model
NASA Astrophysics Data System (ADS)
Kaengthong, Nattacha; Domthong, Uthumporn
2017-09-01
This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).
Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M
In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.
Modelling infant mortality rate in Central Java, Indonesia use generalized poisson regression method
NASA Astrophysics Data System (ADS)
Prahutama, Alan; Sudarno
2018-05-01
The infant mortality rate is the number of deaths under one year of age occurring among the live births in a given geographical area during a given year, per 1,000 live births occurring among the population of the given geographical area during the same year. This problem needs to be addressed because it is an important element of a country’s economic development. High infant mortality rate will disrupt the stability of a country as it relates to the sustainability of the population in the country. One of regression model that can be used to analyze the relationship between dependent variable Y in the form of discrete data and independent variable X is Poisson regression model. Recently The regression modeling used for data with dependent variable is discrete, among others, poisson regression, negative binomial regression and generalized poisson regression. In this research, generalized poisson regression modeling gives better AIC value than poisson regression. The most significant variable is the Number of health facilities (X1), while the variable that gives the most influence to infant mortality rate is the average breastfeeding (X9).
Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan
2011-11-01
To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P < 0.0001) based on testing by the Lagrangemultiplier. Therefore, the over-dispersion dispersed data using a modified Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.
NASA Astrophysics Data System (ADS)
Zhang, Ying; Bi, Peng; Hiller, Janet
2008-01-01
This is the first study to identify appropriate regression models for the association between climate variation and salmonellosis transmission. A comparison between different regression models was conducted using surveillance data in Adelaide, South Australia. By using notified salmonellosis cases and climatic variables from the Adelaide metropolitan area over the period 1990-2003, four regression methods were examined: standard Poisson regression, autoregressive adjusted Poisson regression, multiple linear regression, and a seasonal autoregressive integrated moving average (SARIMA) model. Notified salmonellosis cases in 2004 were used to test the forecasting ability of the four models. Parameter estimation, goodness-of-fit and forecasting ability of the four regression models were compared. Temperatures occurring 2 weeks prior to cases were positively associated with cases of salmonellosis. Rainfall was also inversely related to the number of cases. The comparison of the goodness-of-fit and forecasting ability suggest that the SARIMA model is better than the other three regression models. Temperature and rainfall may be used as climatic predictors of salmonellosis cases in regions with climatic characteristics similar to those of Adelaide. The SARIMA model could, thus, be adopted to quantify the relationship between climate variations and salmonellosis transmission.
A generalized right truncated bivariate Poisson regression model with applications to health data.
Islam, M Ataharul; Chowdhury, Rafiqul I
2017-01-01
A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.
A generalized right truncated bivariate Poisson regression model with applications to health data
Islam, M. Ataharul; Chowdhury, Rafiqul I.
2017-01-01
A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model. PMID:28586344
Background stratified Poisson regression analysis of cohort data.
Richardson, David B; Langholz, Bryan
2012-03-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.
Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg
2009-11-01
G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
Understanding poisson regression.
Hayat, Matthew J; Higgins, Melinda
2014-04-01
Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.
Analyzing hospitalization data: potential limitations of Poisson regression.
Weaver, Colin G; Ravani, Pietro; Oliver, Matthew J; Austin, Peter C; Quinn, Robert R
2015-08-01
Poisson regression is commonly used to analyze hospitalization data when outcomes are expressed as counts (e.g. number of days in hospital). However, data often violate the assumptions on which Poisson regression is based. More appropriate extensions of this model, while available, are rarely used. We compared hospitalization data between 206 patients treated with hemodialysis (HD) and 107 treated with peritoneal dialysis (PD) using Poisson regression and compared results from standard Poisson regression with those obtained using three other approaches for modeling count data: negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression and zero-inflated negative binomial (ZINB) regression. We examined the appropriateness of each model and compared the results obtained with each approach. During a mean 1.9 years of follow-up, 183 of 313 patients (58%) were never hospitalized (indicating an excess of 'zeros'). The data also displayed overdispersion (variance greater than mean), violating another assumption of the Poisson model. Using four criteria, we determined that the NB and ZINB models performed best. According to these two models, patients treated with HD experienced similar hospitalization rates as those receiving PD {NB rate ratio (RR): 1.04 [bootstrapped 95% confidence interval (CI): 0.49-2.20]; ZINB summary RR: 1.21 (bootstrapped 95% CI 0.60-2.46)}. Poisson and ZIP models fit the data poorly and had much larger point estimates than the NB and ZINB models [Poisson RR: 1.93 (bootstrapped 95% CI 0.88-4.23); ZIP summary RR: 1.84 (bootstrapped 95% CI 0.88-3.84)]. We found substantially different results when modeling hospitalization data, depending on the approach used. Our results argue strongly for a sound model selection process and improved reporting around statistical methods used for modeling count data. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.
Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio
2014-11-24
The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine stratification.
Hu, Wenbiao; Tong, Shilu; Mengersen, Kerrie; Connell, Des
2007-09-01
Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.
Non-Poisson Processes: Regression to Equilibrium Versus Equilibrium Correlation Functions
2004-07-07
ARTICLE IN PRESSPhysica A 347 (2005) 268–2880378-4371/$ - doi:10.1016/j Correspo E-mail adwww.elsevier.com/locate/physaNon- Poisson processes : regression...05.40.a; 89.75.k; 02.50.Ey Keywords: Stochastic processes; Non- Poisson processes ; Liouville and Liouville-like equations; Correlation function...which is not legitimate with renewal non- Poisson processes , is a correct property if the deviation from the exponential relaxation is obtained by time
Modeling health survey data with excessive zero and K responses.
Lin, Ting Hsiang; Tsai, Min-Hsiao
2013-04-30
Zero-inflated Poisson regression is a popular tool used to analyze data with excessive zeros. Although much work has already been performed to fit zero-inflated data, most models heavily depend on special features of the individual data. To be specific, this means that there is a sizable group of respondents who endorse the same answers making the data have peaks. In this paper, we propose a new model with the flexibility to model excessive counts other than zero, and the model is a mixture of multinomial logistic and Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts, including zeros, K (where K is a positive integer) and all other values. The Poisson regression component models the counts that are assumed to follow a Poisson distribution. Two examples are provided to illustrate our models when the data have counts containing many ones and sixes. As a result, the zero-inflated and K-inflated models exhibit a better fit than the zero-inflated Poisson and standard Poisson regressions. Copyright © 2012 John Wiley & Sons, Ltd.
Di Donato, Violante; Kontopantelis, Evangelos; Aletti, Giovanni; Casorelli, Assunta; Piacenti, Ilaria; Bogani, Giorgio; Lecce, Francesca; Benedetti Panici, Pierluigi
2017-06-01
Primary cytoreductive surgery (PDS) followed by platinum-based chemotherapy is the cornerstone of treatment and the absence of residual tumor after PDS is universally considered the most important prognostic factor. The aim of the present analysis was to evaluate trend and predictors of 30-day mortality in patients undergoing primary cytoreduction for ovarian cancer. Literature was searched for records reporting 30-day mortality after PDS. All cohorts were rated for quality. Simple and multiple Poisson regression models were used to quantify the association between 30-day mortality and the following: overall or severe complications, proportion of patients with stage IV disease, median age, year of publication, and weighted surgical complexity index. Using the multiple regression model, we calculated the risk of perioperative mortality at different levels for statistically significant covariates of interest. Simple regression identified median age and proportion of patients with stage IV disease as statistically significant predictors of 30-day mortality. When included in the multiple Poisson regression model, both remained statistically significant, with an incidence rate ratio of 1.087 for median age and 1.017 for stage IV disease. Disease stage was a strong predictor, with the risk estimated to increase from 2.8% (95% confidence interval 2.02-3.66) for stage III to 16.1% (95% confidence interval 6.18-25.93) for stage IV, for a cohort with a median age of 65 years. Metaregression demonstrated that increased age and advanced clinical stage were independently associated with an increased risk of mortality, and the combined effects of both factors greatly increased the risk.
Introduction to the use of regression models in epidemiology.
Bender, Ralf
2009-01-01
Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.
Christensen, A L; Lundbye-Christensen, S; Dethlefsen, C
2011-12-01
Several statistical methods of assessing seasonal variation are available. Brookhart and Rothman [3] proposed a second-order moment-based estimator based on the geometrical model derived by Edwards [1], and reported that this estimator is superior in estimating the peak-to-trough ratio of seasonal variation compared with Edwards' estimator with respect to bias and mean squared error. Alternatively, seasonal variation may be modelled using a Poisson regression model, which provides flexibility in modelling the pattern of seasonal variation and adjustments for covariates. Based on a Monte Carlo simulation study three estimators, one based on the geometrical model, and two based on log-linear Poisson regression models, were evaluated in regards to bias and standard deviation (SD). We evaluated the estimators on data simulated according to schemes varying in seasonal variation and presence of a secular trend. All methods and analyses in this paper are available in the R package Peak2Trough[13]. Applying a Poisson regression model resulted in lower absolute bias and SD for data simulated according to the corresponding model assumptions. Poisson regression models had lower bias and SD for data simulated to deviate from the corresponding model assumptions than the geometrical model. This simulation study encourages the use of Poisson regression models in estimating the peak-to-trough ratio of seasonal variation as opposed to the geometrical model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.
Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C
2014-03-01
To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Zero-inflated Conway-Maxwell Poisson Distribution to Analyze Discrete Data.
Sim, Shin Zhu; Gupta, Ramesh C; Ong, Seng Huat
2018-01-09
In this paper, we study the zero-inflated Conway-Maxwell Poisson (ZICMP) distribution and develop a regression model. Score and likelihood ratio tests are also implemented for testing the inflation/deflation parameter. Simulation studies are carried out to examine the performance of these tests. A data example is presented to illustrate the concepts. In this example, the proposed model is compared to the well-known zero-inflated Poisson (ZIP) and the zero- inflated generalized Poisson (ZIGP) regression models. It is shown that the fit by ZICMP is comparable or better than these models.
A test of inflated zeros for Poisson regression models.
He, Hua; Zhang, Hui; Ye, Peng; Tang, Wan
2017-01-01
Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Poisson and a zero-inflated Poisson model is commonly applied in practice. However, the type I error of the test often deviates seriously from the nominal level, rendering serious doubts on the validity of the test in such applications. In this paper, we develop a new approach for testing inflated zeros under the Poisson model. Unlike the Vuong test for inflated zeros, our method does not require a zero-inflated Poisson model to perform the test. Simulation studies show that when compared with the Vuong test our approach not only better at controlling type I error rate, but also yield more power.
Poisson Regression Analysis of Illness and Injury Surveillance Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Frome E.L., Watkins J.P., Ellis E.D.
2012-12-12
The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences duemore » to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to extra-Poisson variation. The R open source software environment for statistical computing and graphics is used for analysis. Additional details about R and the data that were used in this report are provided in an Appendix. Information on how to obtain R and utility functions that can be used to duplicate results in this report are provided.« less
Spirituality and Resilience Among Mexican American IPV Survivors.
de la Rosa, Iván A; Barnett-Queen, Timothy; Messick, Madeline; Gurrola, Maria
2016-12-01
Women with abusive partners use a variety of coping strategies. This study examined the correlation between spirituality, resilience, and intimate partner violence using a cross-sectional survey of 54 Mexican American women living along the U.S.-Mexico border. The meaning-making coping model provides the conceptual framework to explore how spirituality is used as a copying strategy. Multiple ordinary least squares (OLS) regression results indicate women who score higher on spirituality also report greater resilient characteristics. Poisson regression analyses revealed that an increase in level of spirituality is associated with lower number of types of abuse experienced. Clinical, programmatic, and research implications are discussed. © The Author(s) 2015.
Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.
Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai
2011-01-01
Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.
Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Manh, Cuong Do
2015-01-01
The Mekong Delta is highly vulnerable to climate change and a dengue endemic area in Vietnam. This study aims to examine the association between climate factors and dengue incidence and to identify the best climate prediction model for dengue incidence in Can Tho city, the Mekong Delta area in Vietnam. We used three different regression models comprising: standard multiple regression model (SMR), seasonal autoregressive integrated moving average model (SARIMA), and Poisson distributed lag model (PDLM) to examine the association between climate factors and dengue incidence over the period 2003-2010. We validated the models by forecasting dengue cases for the period of January-December, 2011 using the mean absolute percentage error (MAPE). Receiver operating characteristics curves were used to analyze the sensitivity of the forecast of a dengue outbreak. The results indicate that temperature and relative humidity are significantly associated with changes in dengue incidence consistently across the model methods used, but not cumulative rainfall. The Poisson distributed lag model (PDLM) performs the best prediction of dengue incidence for a 6, 9, and 12-month period and diagnosis of an outbreak however the SARIMA model performs a better prediction of dengue incidence for a 3-month period. The simple or standard multiple regression performed highly imprecise prediction of dengue incidence. We recommend a follow-up study to validate the model on a larger scale in the Mekong Delta region and to analyze the possibility of incorporating a climate-based dengue early warning method into the national dengue surveillance system. Copyright © 2014 Elsevier B.V. All rights reserved.
Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach.
Mohammadi, Tayeb; Kheiri, Soleiman; Sedehi, Morteza
2016-01-01
Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.
Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach
Mohammadi, Tayeb; Sedehi, Morteza
2016-01-01
Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables “number of blood donation” and “number of blood deferral”: as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models. PMID:27703493
A quantile count model of water depth constraints on Cape Sable seaside sparrows
Cade, B.S.; Dong, Q.
2008-01-01
1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.
Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data
Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.
2013-01-01
Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689
Fuzzy classifier based support vector regression framework for Poisson ratio determination
NASA Astrophysics Data System (ADS)
Asoodeh, Mojtaba; Bagheripour, Parisa
2013-09-01
Poisson ratio is considered as one of the most important rock mechanical properties of hydrocarbon reservoirs. Determination of this parameter through laboratory measurement is time, cost, and labor intensive. Furthermore, laboratory measurements do not provide continuous data along the reservoir intervals. Hence, a fast, accurate, and inexpensive way of determining Poisson ratio which produces continuous data over the whole reservoir interval is desirable. For this purpose, support vector regression (SVR) method based on statistical learning theory (SLT) was employed as a supervised learning algorithm to estimate Poisson ratio from conventional well log data. SVR is capable of accurately extracting the implicit knowledge contained in conventional well logs and converting the gained knowledge into Poisson ratio data. Structural risk minimization (SRM) principle which is embedded in the SVR structure in addition to empirical risk minimization (EMR) principle provides a robust model for finding quantitative formulation between conventional well log data and Poisson ratio. Although satisfying results were obtained from an individual SVR model, it had flaws of overestimation in low Poisson ratios and underestimation in high Poisson ratios. These errors were eliminated through implementation of fuzzy classifier based SVR (FCBSVR). The FCBSVR significantly improved accuracy of the final prediction. This strategy was successfully applied to data from carbonate reservoir rocks of an Iranian Oil Field. Results indicated that SVR predicted Poisson ratio values are in good agreement with measured values.
Characterizing the performance of the Conway-Maxwell Poisson generalized linear model.
Francis, Royce A; Geedipally, Srinivas Reddy; Guikema, Seth D; Dhavala, Soma Sekhar; Lord, Dominique; LaRocca, Sarah
2012-01-01
Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model based on the Conway-Maxwell Poisson (COM-Poisson) distribution was recently proposed, a model that has the potential to overcome the limitations of the traditional model. However, the statistical performance of this new model has not yet been fully characterized. This article assesses the performance of a maximum likelihood estimation method for fitting the COM-Poisson generalized linear model (GLM). The objectives of this article are to (1) characterize the parameter estimation accuracy of the MLE implementation of the COM-Poisson GLM, and (2) estimate the prediction accuracy of the COM-Poisson GLM using simulated data sets. The results of the study indicate that the COM-Poisson GLM is flexible enough to model under-, equi-, and overdispersed data sets with different sample mean values. The results also show that the COM-Poisson GLM yields accurate parameter estimates. The COM-Poisson GLM provides a promising and flexible approach for performing count data regression. © 2011 Society for Risk Analysis.
Wen, L; Bowen, C R; Hartman, G L
2017-10-01
Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short-distance movement of urediniospores from within the soybean canopy and up to 61 m from field-grown rust-infected soybean plants. Environmental variables were used to develop and compare models including the least absolute shrinkage and selection operator regression, zero-inflated Poisson/regular Poisson regression, random forest, and neural network to describe deposition of urediniospores collected in passive and active traps. All four models identified distance of trap from source, humidity, temperature, wind direction, and wind speed as the five most important variables influencing short-distance movement of urediniospores. The random forest model provided the best predictions, explaining 76.1 and 86.8% of the total variation in the passive- and active-trap datasets, respectively. The prediction accuracy based on the correlation coefficient (r) between predicted values and the true values were 0.83 (P < 0.0001) and 0.94 (P < 0.0001) for the passive and active trap datasets, respectively. Overall, multiple machine learning techniques identified the most important variables to make the most accurate predictions of movement of P. pachyrhizi urediniospores short-distance.
Predictors for the Number of Warning Information Sources During Tornadoes.
Cong, Zhen; Luo, Jianjun; Liang, Daan; Nejat, Ali
2017-04-01
People may receive tornado warnings from multiple information sources, but little is known about factors that affect the number of warning information sources (WISs). This study examined predictors for the number of WISs with a telephone survey on randomly sampled residents in Tuscaloosa, Alabama, and Joplin, Missouri, approximately 1 year after both cities were struck by violent tornadoes (EF4 and EF5) in 2011. The survey included 1006 finished interviews and the working sample included 903 respondents. Poisson regression and Zero-Inflated Poisson regression showed that older age and having an emergency plan predicted more WISs in both cities. Education, marital status, and gender affected the possibilities of receiving warnings and the number of WISs either in Joplin or in Tuscaloosa. The findings suggest that social disparity affects the access to warnings not only with respect to the likelihood of receiving any warnings but also with respect to the number of WISs. In addition, historical and social contexts are important for examining predictors for the number of WISs. We recommend that the number of WISs should be regarded as an important measure to evaluate access to warnings in addition to the likelihood of receiving warnings. (Disaster Med Public Health Preparedness. 2017;11:168-172).
Naya, Hugo; Urioste, Jorge I; Chang, Yu-Mei; Rodrigues-Motta, Mariana; Kremer, Roberto; Gianola, Daniel
2008-01-01
Dark spots in the fleece area are often associated with dark fibres in wool, which limits its competitiveness with other textile fibres. Field data from a sheep experiment in Uruguay revealed an excess number of zeros for dark spots. We compared the performance of four Poisson and zero-inflated Poisson (ZIP) models under four simulation scenarios. All models performed reasonably well under the same scenario for which the data were simulated. The deviance information criterion favoured a Poisson model with residual, while the ZIP model with a residual gave estimates closer to their true values under all simulation scenarios. Both Poisson and ZIP models with an error term at the regression level performed better than their counterparts without such an error. Field data from Corriedale sheep were analysed with Poisson and ZIP models with residuals. Parameter estimates were similar for both models. Although the posterior distribution of the sire variance was skewed due to a small number of rams in the dataset, the median of this variance suggested a scope for genetic selection. The main environmental factor was the age of the sheep at shearing. In summary, age related processes seem to drive the number of dark spots in this breed of sheep. PMID:18558072
Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China
Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao
2018-01-01
Background This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Methods Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Results Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). Conclusions The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention. PMID:29561835
Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
Liu, Kangkang; Zhu, Yanshan; Xia, Yao; Zhang, Yingtao; Huang, Xiaodong; Huang, Jiawei; Nie, Enqiong; Jing, Qinlong; Wang, Guoling; Yang, Zhicong; Hu, Wenbiao; Lu, Jiahai
2018-03-01
This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention.
Estimating the Depth of the Navy Recruiting Market
2016-09-01
recommend that NRC make use of the Poisson regression model in order to determine high-yield ZIP codes for market depth. 14. SUBJECT...recommend that NRC make use of the Poisson regression model in order to determine high-yield ZIP codes for market depth. vi THIS PAGE INTENTIONALLY LEFT...DEPTH OF THE NAVY RECRUITING MARKET by Emilie M. Monaghan September 2016 Thesis Advisor: Lyn R. Whitaker Second Reader: Jonathan K. Alt
DOE Office of Scientific and Technical Information (OSTI.GOV)
Croft, S.; Favalli, Andrea; Weaver, Brian Phillip
2015-10-06
In this paper we develop and investigate several criteria for assessing how well a proposed spectral form fits observed spectra. We consider the classical improved figure of merit (FOM) along with several modifications, as well as criteria motivated by Poisson regression from the statistical literature. We also develop a new FOM that is based on the statistical idea of the bootstrap. A spectral simulator has been developed to assess the performance of these different criteria under multiple data configurations.
Applying the compound Poisson process model to the reporting of injury-related mortality rates.
Kegler, Scott R
2007-02-16
Injury-related mortality rate estimates are often analyzed under the assumption that case counts follow a Poisson distribution. Certain types of injury incidents occasionally involve multiple fatalities, however, resulting in dependencies between cases that are not reflected in the simple Poisson model and which can affect even basic statistical analyses. This paper explores the compound Poisson process model as an alternative, emphasizing adjustments to some commonly used interval estimators for population-based rates and rate ratios. The adjusted estimators involve relatively simple closed-form computations, which in the absence of multiple-case incidents reduce to familiar estimators based on the simpler Poisson model. Summary data from the National Violent Death Reporting System are referenced in several examples demonstrating application of the proposed methodology.
A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution.
Inouye, David; Yang, Eunho; Allen, Genevera; Ravikumar, Pradeep
2017-01-01
The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world high-dimensional count-valued data found in word counts, genomics, and crime statistics, for example, exhibit rich dependencies, and motivate the need for multivariate distributions that can appropriately model this data. We review multivariate distributions derived from the univariate Poisson, categorizing these models into three main classes: 1) where the marginal distributions are Poisson, 2) where the joint distribution is a mixture of independent multivariate Poisson distributions, and 3) where the node-conditional distributions are derived from the Poisson. We discuss the development of multiple instances of these classes and compare the models in terms of interpretability and theory. Then, we empirically compare multiple models from each class on three real-world datasets that have varying data characteristics from different domains, namely traffic accident data, biological next generation sequencing data, and text data. These empirical experiments develop intuition about the comparative advantages and disadvantages of each class of multivariate distribution that was derived from the Poisson. Finally, we suggest new research directions as explored in the subsequent discussion section.
A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.
Ferrari, Alberto; Comelli, Mario
2016-12-01
In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.
Kerry, Ruth; Goovaerts, Pierre; Smit, Izak P.J.; Ingram, Ben R.
2015-01-01
Kruger National Park (KNP), South Africa, provides protected habitats for the unique animals of the African savannah. For the past 40 years, annual aerial surveys of herbivores have been conducted to aid management decisions based on (1) the spatial distribution of species throughout the park and (2) total species populations in a year. The surveys are extremely time consuming and costly. For many years, the whole park was surveyed, but in 1998 a transect survey approach was adopted. This is cheaper and less time consuming but leaves gaps in the data spatially. Also the distance method currently employed by the park only gives estimates of total species populations but not their spatial distribution. We compare the ability of multiple indicator kriging and area-to-point Poisson kriging to accurately map species distribution in the park. A leave-one-out cross-validation approach indicates that multiple indicator kriging makes poor estimates of the number of animals, particularly the few large counts, as the indicator variograms for such high thresholds are pure nugget. Poisson kriging was applied to the prediction of two types of abundance data: spatial density and proportion of a given species. Both Poisson approaches had standardized mean absolute errors (St. MAEs) of animal counts at least an order of magnitude lower than multiple indicator kriging. The spatial density, Poisson approach (1), gave the lowest St. MAEs for the most abundant species and the proportion, Poisson approach (2), did for the least abundant species. Incorporating environmental data into Poisson approach (2) further reduced St. MAEs. PMID:25729318
Kerry, Ruth; Goovaerts, Pierre; Smit, Izak P J; Ingram, Ben R
Kruger National Park (KNP), South Africa, provides protected habitats for the unique animals of the African savannah. For the past 40 years, annual aerial surveys of herbivores have been conducted to aid management decisions based on (1) the spatial distribution of species throughout the park and (2) total species populations in a year. The surveys are extremely time consuming and costly. For many years, the whole park was surveyed, but in 1998 a transect survey approach was adopted. This is cheaper and less time consuming but leaves gaps in the data spatially. Also the distance method currently employed by the park only gives estimates of total species populations but not their spatial distribution. We compare the ability of multiple indicator kriging and area-to-point Poisson kriging to accurately map species distribution in the park. A leave-one-out cross-validation approach indicates that multiple indicator kriging makes poor estimates of the number of animals, particularly the few large counts, as the indicator variograms for such high thresholds are pure nugget. Poisson kriging was applied to the prediction of two types of abundance data: spatial density and proportion of a given species. Both Poisson approaches had standardized mean absolute errors (St. MAEs) of animal counts at least an order of magnitude lower than multiple indicator kriging. The spatial density, Poisson approach (1), gave the lowest St. MAEs for the most abundant species and the proportion, Poisson approach (2), did for the least abundant species. Incorporating environmental data into Poisson approach (2) further reduced St. MAEs.
Poisson process stimulation of an excitable membrane cable model.
Goldfinger, M D
1986-01-01
The convergence of multiple inputs within a single-neuronal substrate is a common design feature of both peripheral and central nervous systems. Typically, the result of such convergence impinges upon an intracellularly contiguous axon, where it is encoded into a train of action potentials. The simplest representation of the result of convergence of multiple inputs is a Poisson process; a general representation of axonal excitability is the Hodgkin-Huxley/cable theory formalism. The present work addressed multiple input convergence upon an axon by applying Poisson process stimulation to the Hodgkin-Huxley axonal cable. The results showed that both absolute and relative refractory periods yielded in the axonal output a random but non-Poisson process. While smaller amplitude stimuli elicited a type of short-interval conditioning, larger amplitude stimuli elicited impulse trains approaching Poisson criteria except for the effects of refractoriness. These results were obtained for stimulus trains consisting of pulses of constant amplitude and constant or variable durations. By contrast, with or without stimulus pulse shape variability, the post-impulse conditional probability for impulse initiation in the steady-state was a Poisson-like process. For stimulus variability consisting of randomly smaller amplitudes or randomly longer durations, mean impulse frequency was attenuated or potentiated, respectively. Limitations and implications of these computations are discussed. PMID:3730505
Park, Taeyoung; Krafty, Robert T; Sánchez, Alvaro I
2012-07-27
A Poisson regression model with an offset assumes a constant baseline rate after accounting for measured covariates, which may lead to biased estimates of coefficients in an inhomogeneous Poisson process. To correctly estimate the effect of time-dependent covariates, we propose a Poisson change-point regression model with an offset that allows a time-varying baseline rate. When the nonconstant pattern of a log baseline rate is modeled with a nonparametric step function, the resulting semi-parametric model involves a model component of varying dimension and thus requires a sophisticated varying-dimensional inference to obtain correct estimates of model parameters of fixed dimension. To fit the proposed varying-dimensional model, we devise a state-of-the-art MCMC-type algorithm based on partial collapse. The proposed model and methods are used to investigate an association between daily homicide rates in Cali, Colombia and policies that restrict the hours during which the legal sale of alcoholic beverages is permitted. While simultaneously identifying the latent changes in the baseline homicide rate which correspond to the incidence of sociopolitical events, we explore the effect of policies governing the sale of alcohol on homicide rates and seek a policy that balances the economic and cultural dependencies on alcohol sales to the health of the public.
Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P
2014-06-26
To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.
A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution
Inouye, David; Yang, Eunho; Allen, Genevera; Ravikumar, Pradeep
2017-01-01
The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world high-dimensional count-valued data found in word counts, genomics, and crime statistics, for example, exhibit rich dependencies, and motivate the need for multivariate distributions that can appropriately model this data. We review multivariate distributions derived from the univariate Poisson, categorizing these models into three main classes: 1) where the marginal distributions are Poisson, 2) where the joint distribution is a mixture of independent multivariate Poisson distributions, and 3) where the node-conditional distributions are derived from the Poisson. We discuss the development of multiple instances of these classes and compare the models in terms of interpretability and theory. Then, we empirically compare multiple models from each class on three real-world datasets that have varying data characteristics from different domains, namely traffic accident data, biological next generation sequencing data, and text data. These empirical experiments develop intuition about the comparative advantages and disadvantages of each class of multivariate distribution that was derived from the Poisson. Finally, we suggest new research directions as explored in the subsequent discussion section. PMID:28983398
Ruder, Avima M; Hein, Misty J; Hopf, Nancy B; Waters, Martha A
2014-03-01
The objective of this analysis was to evaluate mortality among a cohort of 24,865 capacitor-manufacturing workers exposed to polychlorinated biphenyls (PCBs) at plants in Indiana, Massachusetts, and New York and followed for mortality through 2008. Cumulative PCB exposure was estimated using plant-specific job-exposure matrices. External comparisons to US and state-specific populations used standardized mortality ratios, adjusted for gender, race, age and calendar year. Among long-term workers employed 3 months or longer, within-cohort comparisons used standardized rate ratios and multivariable Poisson regression modeling. Through 2008, more than one million person-years at risk and 8749 deaths were accrued. Among long-term employees, all-cause and all-cancer mortality were not elevated; of the a priori outcomes assessed only melanoma mortality was elevated. Mortality was elevated for some outcomes of a priori interest among subgroups of long-term workers: all cancer, intestinal cancer and amyotrophic lateral sclerosis (women); melanoma (men); melanoma and brain and nervous system cancer (Indiana plant); and melanoma and multiple myeloma (New York plant). Standardized rates of stomach and uterine cancer and multiple myeloma mortality increased with estimated cumulative PCB exposure. Poisson regression modeling showed significant associations with estimated cumulative PCB exposure for prostate and stomach cancer mortality. For other outcomes of a priori interest--rectal, liver, ovarian, breast, and thyroid cancer, non-Hodgkin lymphoma, Alzheimer disease, and Parkinson disease--neither elevated mortality nor positive associations with PCB exposure were observed. Associations between estimated cumulative PCB exposure and stomach, uterine, and prostate cancer and myeloma mortality confirmed our previous positive findings. Published by Elsevier GmbH.
Ruder, Avima M.; Hein, Misty J.; Hopf, Nancy B.; Waters, Martha A.
2015-01-01
The objective of this analysis was to evaluate mortality among a cohort of 24,865 capacitor-manufacturing workers exposed to polychlorinated biphenyls (PCBs) at plants in Indiana, Massachusetts, and New York and followed for mortality through 2008. Cumulative PCB exposure was estimated using plant-specific job-exposure matrices. External comparisons to US and state-specific populations used standardized mortality ratios, adjusted for gender, race, age and calendar year. Among long-term workers employed 3 months or longer, within-cohort comparisons used standardized rate ratios and multivariable Poisson regression modeling. Through 2008, more than one million person-years at risk and 8749 deaths were accrued. Among long-term employees, all-cause and all-cancer mortality were not elevated; of the a priori outcomes assessed only melanoma mortality was elevated. Mortality was elevated for some outcomes of a priori interest among subgroups of long-term workers: all cancer, intestinal cancer and amyotrophic lateral sclerosis (women); melanoma (men); melanoma and brain and nervous system cancer (Indiana plant); and melanoma and multiple myeloma (New York plant). Standardized rates of stomach and uterine cancer and multiple myeloma mortality increased with estimated cumulative PCB exposure. Poisson regression modeling showed significant associations with estimated cumulative PCB exposure for prostate and stomach cancer mortality. For other outcomes of a priori interest – rectal, liver, ovarian, breast, and thyroid cancer, non-Hodgkin lymphoma, Alzheimer disease, and Parkinson disease – neither elevated mortality nor positive associations with PCB exposure were observed. Associations between estimated cumulative PCB exposure and stomach, uterine, and prostate cancer and myeloma mortality confirmed our previous positive findings. PMID:23707056
Simulation on Poisson and negative binomial models of count road accident modeling
NASA Astrophysics Data System (ADS)
Sapuan, M. S.; Razali, A. M.; Zamzuri, Z. H.; Ibrahim, K.
2016-11-01
Accident count data have often been shown to have overdispersion. On the other hand, the data might contain zero count (excess zeros). The simulation study was conducted to create a scenarios which an accident happen in T-junction with the assumption the dependent variables of generated data follows certain distribution namely Poisson and negative binomial distribution with different sample size of n=30 to n=500. The study objective was accomplished by fitting Poisson regression, negative binomial regression and Hurdle negative binomial model to the simulated data. The model validation was compared and the simulation result shows for each different sample size, not all model fit the data nicely even though the data generated from its own distribution especially when the sample size is larger. Furthermore, the larger sample size indicates that more zeros accident count in the dataset.
NASA Astrophysics Data System (ADS)
Octavianty, Toharudin, Toni; Jaya, I. G. N. Mindra
2017-03-01
Tuberculosis (TB) is a disease caused by a bacterium, called Mycobacterium tuberculosis, which typically attacks the lungs but can also affect the kidney, spine, and brain (Centers for Disease Control and Prevention). Indonesia had the largest number of TB cases after India (Global Tuberculosis Report 2015 by WHO). The distribution of Mycobacterium tuberculosis genotypes in Indonesia showed the high genetic diversity and tended to vary by geographic regions. For instance, in Bandung city, the prevalence rate of TB morbidity is quite high. A number of TB patients belong to the counted data. To determine the factors that significantly influence the number of tuberculosis patients in each location of the observations can be used statistical analysis tool that is Geographically Weighted Poisson Regression Semiparametric (GWPRS). GWPRS is an extension of the Poisson regression and GWPR that is influenced by geographical factors, and there is also variables that influence globally and locally. Using the TB Data in Bandung city (in 2015), the results show that the global and local variables that influence the number of tuberculosis patients in every sub-district.
Casimir meets Poisson: improved quark/gluon discrimination with counting observables
Frye, Christopher; Larkoski, Andrew J.; Thaler, Jesse; ...
2017-09-19
Charged track multiplicity is among the most powerful observables for discriminating quark- from gluon-initiated jets. Despite its utility, it is not infrared and collinear (IRC) safe, so perturbative calculations are limited to studying the energy evolution of multiplicity moments. While IRC-safe observables, like jet mass, are perturbatively calculable, their distributions often exhibit Casimir scaling, such that their quark/gluon discrimination power is limited by the ratio of quark to gluon color factors. In this paper, we introduce new IRC-safe counting observables whose discrimination performance exceeds that of jet mass and approaches that of track multiplicity. The key observation is that trackmore » multiplicity is approximately Poisson distributed, with more suppressed tails than the Sudakov peak structure from jet mass. By using an iterated version of the soft drop jet grooming algorithm, we can define a “soft drop multiplicity” which is Poisson distributed at leading-logarithmic accuracy. In addition, we calculate the next-to-leading-logarithmic corrections to this Poisson structure. If we allow the soft drop groomer to proceed to the end of the jet branching history, we can define a collinear-unsafe (but still infrared-safe) counting observable. Exploiting the universality of the collinear limit, we define generalized fragmentation functions to study the perturbative energy evolution of collinear-unsafe multiplicity.« less
Casimir meets Poisson: improved quark/gluon discrimination with counting observables
DOE Office of Scientific and Technical Information (OSTI.GOV)
Frye, Christopher; Larkoski, Andrew J.; Thaler, Jesse
Charged track multiplicity is among the most powerful observables for discriminating quark- from gluon-initiated jets. Despite its utility, it is not infrared and collinear (IRC) safe, so perturbative calculations are limited to studying the energy evolution of multiplicity moments. While IRC-safe observables, like jet mass, are perturbatively calculable, their distributions often exhibit Casimir scaling, such that their quark/gluon discrimination power is limited by the ratio of quark to gluon color factors. In this paper, we introduce new IRC-safe counting observables whose discrimination performance exceeds that of jet mass and approaches that of track multiplicity. The key observation is that trackmore » multiplicity is approximately Poisson distributed, with more suppressed tails than the Sudakov peak structure from jet mass. By using an iterated version of the soft drop jet grooming algorithm, we can define a “soft drop multiplicity” which is Poisson distributed at leading-logarithmic accuracy. In addition, we calculate the next-to-leading-logarithmic corrections to this Poisson structure. If we allow the soft drop groomer to proceed to the end of the jet branching history, we can define a collinear-unsafe (but still infrared-safe) counting observable. Exploiting the universality of the collinear limit, we define generalized fragmentation functions to study the perturbative energy evolution of collinear-unsafe multiplicity.« less
Sharma, Smita S; Mamtani, Manju R; Sharma, Mamta S; Kulkarni, Hemant
2006-06-16
With dwindling rates of postoperative mortality in perforated peptic ulcer that is attributable to H2-receptor blocker usage, there is a need to shift the focus towards the prevention of postoperative morbidity. Further, the simultaneous contribution of several putative clinical predictors to this postoperative morbidity is not fully appreciated. Our objective was to assess the predictors of the risk, rate and number of postoperative complications in surgically treated patients of perforated peptic ulcer. In a prospective cohort study of 96 subjects presenting as perforated peptic ulcer and treated using Graham's omentoplatsy patch or gastrojejunostomy (with total truncal vagotomy), we assessed the association of clinical predictors with three domains of postoperative complications: the risk of developing a complication, the rate of developing the first complication and the risk of developing higher number of complications. We used multiple regression methods - logistic regression, Cox proportional hazards regression and Poisson regression, respectively - to examine the association of the predictors with these three domains. We observed that the risk of developing a postoperative complication was significantly influenced by the presence of a concomitant medical illness [odds ratio (OR) = 8.9, p = 0.001], abdominal distension (3.8, 0.048) and a need of blood transfusion (OR = 8.2, p = 0.027). Using Poisson regression, it was observed that the risk for a higher number of complications was influenced by the same three factors [relative risk (RR) = 2.6, p = 0.015; RR = 4.6, p < 0.001; and RR = 2.4, p = 0.002; respectively]. However, the rate of development of complications was influenced by a history suggestive of shock [relative hazards (RH) = 3.4, p = 0.002] and A- blood group (RH = 4.7, p = 0.04). Abdominal distension, presence of a concomitant medical illness and a history suggestive of shock at the time of admission warrant a closer and alacritous postoperative management in patients of perforated peptic ulcer.
Epidemiology of occupational injury among cleaners in the healthcare sector.
Alamgir, Hasanat; Yu, Shicheng
2008-09-01
The cleaning profession has been associated with multiple ergonomic and chemical hazards which elevate the risk for occupational injury. This study investigated the epidemiology of occupational injury among cleaners in healthcare work settings in the Canadian province of British Columbia. Incidents of occupational injury among cleaners, resulting in lost time from work or medical care, over a period of 1 year in two healthcare regions were extracted from a standardized operational database and with person-years obtained from payroll data. Detailed analysis was conducted using Poisson regression modeling. A total of 145 injuries were identified among cleaners, with an annual incidence rate of 32.1 per 100 person-years. After adjustment for age, gender, subsector, facility, experience and employment status, Poisson regression models demonstrated that a significantly higher relative risk (RR) of all injury, musculoskeletal injury and cuts was associated with cleaning work in acute care facilities, compared with long-term care facilities. Female cleaners were at a higher RR of all injuries and contusions than male cleaners. A lower risk of all injury and allergy and irritation incidents among part-time or casual workers was found. Cleaners with >10 years of experience were at significantly lower risk for all injury, contusion and allergy and irritation incidents. Cleaners were found to be at an elevated risk of all injury categories compared with healthcare workers in general.
Quantization of Poisson Manifolds from the Integrability of the Modular Function
NASA Astrophysics Data System (ADS)
Bonechi, F.; Ciccoli, N.; Qiu, J.; Tarlini, M.
2014-10-01
We discuss a framework for quantizing a Poisson manifold via the quantization of its symplectic groupoid, combining the tools of geometric quantization with the results of Renault's theory of groupoid C*-algebras. This setting allows very singular polarizations. In particular, we consider the case when the modular function is multiplicatively integrable, i.e., when the space of leaves of the polarization inherits a groupoid structure. If suitable regularity conditions are satisfied, then one can define the quantum algebra as the convolution algebra of the subgroupoid of leaves satisfying the Bohr-Sommerfeld conditions. We apply this procedure to the case of a family of Poisson structures on , seen as Poisson homogeneous spaces of the standard Poisson-Lie group SU( n + 1). We show that a bihamiltonian system on defines a multiplicative integrable model on the symplectic groupoid; we compute the Bohr-Sommerfeld groupoid and show that it satisfies the needed properties for applying Renault theory. We recover and extend Sheu's description of quantum homogeneous spaces as groupoid C*-algebras.
ERIC Educational Resources Information Center
Liou, Pey-Yan
2009-01-01
The current study examines three regression models: OLS (ordinary least square) linear regression, Poisson regression, and negative binomial regression for analyzing count data. Simulation results show that the OLS regression model performed better than the others, since it did not produce more false statistically significant relationships than…
Doyle, John R.
2018-01-01
The paper analyses two datasets of elite soccer players (top 1000 professionals and UEFA Under-19 Youth League). In both, we find a Relative Age Effect (RAE) for frequency, but not for value. That is, while there are more players born at the start of the competition year, their transfer values are no higher, nor are they given more game time. We use Poisson regression to derive a transparent index of the discrimination present in RAE. Also, because Poisson is valid for small frequency counts, it supports analysis at the disaggregated levels of country and club. From this, we conclude there are no paragon clubs or countries immune to RAE; that is clubs and countries do not differ systematically in the RAE they experience; also, that Poisson regression is a powerful and flexible method of analysing RAE data. PMID:29420576
Sentürk, Damla; Dalrymple, Lorien S; Nguyen, Danh V
2014-11-30
We propose functional linear models for zero-inflated count data with a focus on the functional hurdle and functional zero-inflated Poisson (ZIP) models. Although the hurdle model assumes the counts come from a mixture of a degenerate distribution at zero and a zero-truncated Poisson distribution, the ZIP model considers a mixture of a degenerate distribution at zero and a standard Poisson distribution. We extend the generalized functional linear model framework with a functional predictor and multiple cross-sectional predictors to model counts generated by a mixture distribution. We propose an estimation procedure for functional hurdle and ZIP models, called penalized reconstruction, geared towards error-prone and sparsely observed longitudinal functional predictors. The approach relies on dimension reduction and pooling of information across subjects involving basis expansions and penalized maximum likelihood techniques. The developed functional hurdle model is applied to modeling hospitalizations within the first 2 years from initiation of dialysis, with a high percentage of zeros, in the Comprehensive Dialysis Study participants. Hospitalization counts are modeled as a function of sparse longitudinal measurements of serum albumin concentrations, patient demographics, and comorbidities. Simulation studies are used to study finite sample properties of the proposed method and include comparisons with an adaptation of standard principal components regression. Copyright © 2014 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Wayan Mangku, I.
2017-10-01
In this paper we survey some results on estimation of the intensity function of a cyclic Poisson process in the presence of additive and multiplicative linear trend. We do not assume any parametric form for the cyclic component of the intensity function, except that it is periodic. Moreover, we consider the case when there is only a single realization of the Poisson process is observed in a bounded interval. The considered estimators are weakly and strongly consistent when the size of the observation interval indefinitely expands. Asymptotic approximations to the bias and variance of those estimators are presented.
Lipscomb, Hester J; Schoenfisch, Ashley; Cameron, Wilfrid
2013-07-01
We evaluated work-related injuries involving a hand or fingers and associated costs among a cohort of 24,830 carpenters between 1989 and 2008. Injury rates and rate ratios were calculated by using Poisson regression to explore higher risk on the basis of age, sex, time in the union, predominant work, and calendar time. Negative binomial regression was used to model dollars paid per claim after adjustment for inflation and discounting. Hand injuries accounted for 21.1% of reported injuries and 9.5% of paid lost time injuries. Older carpenters had proportionately more amputations, fractures, and multiple injuries, but their rates of these more severe injuries were not higher. Costs exceeded $21 million, a cost burden of $0.11 per hour worked. Older carpenters' higher proportion of serious injuries in the absence of higher rates likely reflects age-related reporting differences.
Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.
Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed
2013-01-01
In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.
A Negative Binomial Regression Model for Accuracy Tests
ERIC Educational Resources Information Center
Hung, Lai-Fa
2012-01-01
Rasch used a Poisson model to analyze errors and speed in reading tests. An important property of the Poisson distribution is that the mean and variance are equal. However, in social science research, it is very common for the variance to be greater than the mean (i.e., the data are overdispersed). This study embeds the Rasch model within an…
Parameter estimation in Cox models with missing failure indicators and the OPPERA study.
Brownstein, Naomi C; Cai, Jianwen; Slade, Gary D; Bair, Eric
2015-12-30
In a prospective cohort study, examining all participants for incidence of the condition of interest may be prohibitively expensive. For example, the "gold standard" for diagnosing temporomandibular disorder (TMD) is a physical examination by a trained clinician. In large studies, examining all participants in this manner is infeasible. Instead, it is common to use questionnaires to screen for incidence of TMD and perform the "gold standard" examination only on participants who screen positively. Unfortunately, some participants may leave the study before receiving the "gold standard" examination. Within the framework of survival analysis, this results in missing failure indicators. Motivated by the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study, a large cohort study of TMD, we propose a method for parameter estimation in survival models with missing failure indicators. We estimate the probability of being an incident case for those lacking a "gold standard" examination using logistic regression. These estimated probabilities are used to generate multiple imputations of case status for each missing examination that are combined with observed data in appropriate regression models. The variance introduced by the procedure is estimated using multiple imputation. The method can be used to estimate both regression coefficients in Cox proportional hazard models as well as incidence rates using Poisson regression. We simulate data with missing failure indicators and show that our method performs as well as or better than competing methods. Finally, we apply the proposed method to data from the OPPERA study. Copyright © 2015 John Wiley & Sons, Ltd.
do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro
2015-01-01
Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593
Le Bihan, Nicolas; Margerin, Ludovic
2009-07-01
In this paper, we present a nonparametric method to estimate the heterogeneity of a random medium from the angular distribution of intensity of waves transmitted through a slab of random material. Our approach is based on the modeling of forward multiple scattering using compound Poisson processes on compact Lie groups. The estimation technique is validated through numerical simulations based on radiative transfer theory.
Khazraee, S Hadi; Johnson, Valen; Lord, Dominique
2018-08-01
The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients). Copyright © 2018. Published by Elsevier Ltd.
Combined analysis of magnetic and gravity anomalies using normalized source strength (NSS)
NASA Astrophysics Data System (ADS)
Li, L.; Wu, Y.
2017-12-01
Gravity field and magnetic field belong to potential fields which lead inherent multi-solution. Combined analysis of magnetic and gravity anomalies based on Poisson's relation is used to determinate homology gravity and magnetic anomalies and decrease the ambiguity. The traditional combined analysis uses the linear regression of the reduction to pole (RTP) magnetic anomaly to the first order vertical derivative of the gravity anomaly, and provides the quantitative or semi-quantitative interpretation by calculating the correlation coefficient, slope and intercept. In the calculation process, due to the effect of remanent magnetization, the RTP anomaly still contains the effect of oblique magnetization. In this case the homology gravity and magnetic anomalies display irrelevant results in the linear regression calculation. The normalized source strength (NSS) can be transformed from the magnetic tensor matrix, which is insensitive to the remanence. Here we present a new combined analysis using NSS. Based on the Poisson's relation, the gravity tensor matrix can be transformed into the pseudomagnetic tensor matrix of the direction of geomagnetic field magnetization under the homologous condition. The NSS of pseudomagnetic tensor matrix and original magnetic tensor matrix are calculated and linear regression analysis is carried out. The calculated correlation coefficient, slope and intercept indicate the homology level, Poisson's ratio and the distribution of remanent respectively. We test the approach using synthetic model under complex magnetization, the results show that it can still distinguish the same source under the condition of strong remanence, and establish the Poisson's ratio. Finally, this approach is applied in China. The results demonstrated that our approach is feasible.
Marginalized zero-inflated negative binomial regression with application to dental caries
Preisser, John S.; Das, Kalyan; Long, D. Leann; Divaris, Kimon
2015-01-01
The zero-inflated negative binomial regression model (ZINB) is often employed in diverse fields such as dentistry, health care utilization, highway safety, and medicine to examine relationships between exposures of interest and overdispersed count outcomes exhibiting many zeros. The regression coefficients of ZINB have latent class interpretations for a susceptible subpopulation at risk for the disease/condition under study with counts generated from a negative binomial distribution and for a non-susceptible subpopulation that provides only zero counts. The ZINB parameters, however, are not well-suited for estimating overall exposure effects, specifically, in quantifying the effect of an explanatory variable in the overall mixture population. In this paper, a marginalized zero-inflated negative binomial regression (MZINB) model for independent responses is proposed to model the population marginal mean count directly, providing straightforward inference for overall exposure effects based on maximum likelihood estimation. Through simulation studies, the finite sample performance of MZINB is compared to marginalized zero-inflated Poisson, Poisson, and negative binomial regression. The MZINB model is applied in the evaluation of a school-based fluoride mouthrinse program on dental caries in 677 children. PMID:26568034
Spatial variation of natural radiation and childhood leukaemia incidence in Great Britain.
Richardson, S; Monfort, C; Green, M; Draper, G; Muirhead, C
This paper describes an analysis of the geographical variation of childhood leukaemia incidence in Great Britain over a 15 year period in relation to natural radiation (gamma and radon). Data at the level of the 459 district level local authorities in England, Wales and regional districts in Scotland are analysed in two complementary ways: first, by Poisson regressions with the inclusion of environmental covariates and a smooth spatial structure; secondly, by a hierarchical Bayesian model in which extra-Poisson variability is modelled explicitly in terms of spatial and non-spatial components. From this analysis, we deduce a strong indication that a main part of the variability is accounted for by a local neighbourhood 'clustering' structure. This structure is furthermore relatively stable over the 15 year period for the lymphocytic leukaemias which make up the majority of observed cases. We found no evidence of a positive association of childhood leukaemia incidence with outdoor or indoor gamma radiation levels. There is no consistent evidence of any association with radon levels. Indeed, in the Poisson regressions, a significant positive association was only observed for one 5-year period, a result which is not compatible with a stable environmental effect. Moreover, this positive association became clearly non-significant when over-dispersion relative to the Poisson distribution was taken into account.
Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I
2018-01-01
Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.
Prediction of forest fires occurrences with area-level Poisson mixed models.
Boubeta, Miguel; Lombardía, María José; Marey-Pérez, Manuel Francisco; Morales, Domingo
2015-05-01
The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia. Copyright © 2015 Elsevier Ltd. All rights reserved.
A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.
Ye, Xin; Wang, Ke; Zou, Yajie; Lord, Dominique
2018-01-01
This paper develops a semi-nonparametric Poisson regression model to analyze motor vehicle crash frequency data collected from rural multilane highway segments in California, US. Motor vehicle crash frequency on rural highway is a topic of interest in the area of transportation safety due to higher driving speeds and the resultant severity level. Unlike the traditional Negative Binomial (NB) model, the semi-nonparametric Poisson regression model can accommodate an unobserved heterogeneity following a highly flexible semi-nonparametric (SNP) distribution. Simulation experiments are conducted to demonstrate that the SNP distribution can well mimic a large family of distributions, including normal distributions, log-gamma distributions, bimodal and trimodal distributions. Empirical estimation results show that such flexibility offered by the SNP distribution can greatly improve model precision and the overall goodness-of-fit. The semi-nonparametric distribution can provide a better understanding of crash data structure through its ability to capture potential multimodality in the distribution of unobserved heterogeneity. When estimated coefficients in empirical models are compared, SNP and NB models are found to have a substantially different coefficient for the dummy variable indicating the lane width. The SNP model with better statistical performance suggests that the NB model overestimates the effect of lane width on crash frequency reduction by 83.1%.
Effect of motivational interviewing on rates of early childhood caries: a randomized trial.
Harrison, Rosamund; Benton, Tonya; Everson-Stewart, Siobhan; Weinstein, Phil
2007-01-01
The purposes of this randomized controlled trial were to: (1) test motivational interviewing (MI) to prevent early childhood caries; and (2) use Poisson regression for data analysis. A total of 240 South Asian children 6 to 18 months old were enrolled and randomly assigned to either the MI or control condition. Children had a dental exam, and their mothers completed pretested instruments at baseline and 1 and 2 years postintervention. Other covariates that might explain outcomes over and above treatment differences were modeled using Poisson regression. Hazard ratios were produced. Analyses included all participants whenever possible. Poisson regression supported a protective effect of MI (hazard ratio [HR]=0.54 (95%CI=035-0.84)-that is, the M/ group had about a 46% lower rate of dmfs at 2 years than did control children. Similar treatment effect estimates were obtained from models that included, as alternative outcomes, ds, dms, and dmfs, including "white spot lesions." Exploratory analyses revealed that rates of dmfs were higher in children whose mothers had: (1) prechewed their food; (2) been raised in a rural environment; and (3) a higher family income (P<.05). A motivational interviewing-style intervention shows promise to promote preventive behaviors in mothers of young children at high risk for caries.
NASA Astrophysics Data System (ADS)
Gavish, Nir
2018-04-01
We study the existence and stability of stationary solutions of Poisson-Nernst-Planck equations with steric effects (PNP-steric equations) with two counter-charged species. We show that within a range of parameters, steric effects give rise to multiple solutions of the corresponding stationary equation that are smooth. The PNP-steric equation, however, is found to be ill-posed at the parameter regime where multiple solutions arise. Following these findings, we introduce a novel PNP-Cahn-Hilliard model, show that it is well-posed and that it admits multiple stationary solutions that are smooth and stable. The various branches of stationary solutions and their stability are mapped utilizing bifurcation analysis and numerical continuation methods.
Prescription-induced jump distributions in multiplicative Poisson processes.
Suweis, Samir; Porporato, Amilcare; Rinaldo, Andrea; Maritan, Amos
2011-06-01
Generalized Langevin equations (GLE) with multiplicative white Poisson noise pose the usual prescription dilemma leading to different evolution equations (master equations) for the probability distribution. Contrary to the case of multiplicative Gaussian white noise, the Stratonovich prescription does not correspond to the well-known midpoint (or any other intermediate) prescription. By introducing an inertial term in the GLE, we show that the Itô and Stratonovich prescriptions naturally arise depending on two time scales, one induced by the inertial term and the other determined by the jump event. We also show that, when the multiplicative noise is linear in the random variable, one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We apply these results to a recently proposed stochastic model describing the dynamics of primary soil salinization, in which the salt mass balance within the soil root zone requires the analysis of different prescriptions arising from the resulting stochastic differential equation forced by multiplicative white Poisson noise, the features of which are tailored to the characters of the daily precipitation. A method is finally suggested to infer the most appropriate prescription from the data.
Prescription-induced jump distributions in multiplicative Poisson processes
NASA Astrophysics Data System (ADS)
Suweis, Samir; Porporato, Amilcare; Rinaldo, Andrea; Maritan, Amos
2011-06-01
Generalized Langevin equations (GLE) with multiplicative white Poisson noise pose the usual prescription dilemma leading to different evolution equations (master equations) for the probability distribution. Contrary to the case of multiplicative Gaussian white noise, the Stratonovich prescription does not correspond to the well-known midpoint (or any other intermediate) prescription. By introducing an inertial term in the GLE, we show that the Itô and Stratonovich prescriptions naturally arise depending on two time scales, one induced by the inertial term and the other determined by the jump event. We also show that, when the multiplicative noise is linear in the random variable, one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We apply these results to a recently proposed stochastic model describing the dynamics of primary soil salinization, in which the salt mass balance within the soil root zone requires the analysis of different prescriptions arising from the resulting stochastic differential equation forced by multiplicative white Poisson noise, the features of which are tailored to the characters of the daily precipitation. A method is finally suggested to infer the most appropriate prescription from the data.
Modeling the number of car theft using Poisson regression
NASA Astrophysics Data System (ADS)
Zulkifli, Malina; Ling, Agnes Beh Yen; Kasim, Maznah Mat; Ismail, Noriszura
2016-10-01
Regression analysis is the most popular statistical methods used to express the relationship between the variables of response with the covariates. The aim of this paper is to evaluate the factors that influence the number of car theft using Poisson regression model. This paper will focus on the number of car thefts that occurred in districts in Peninsular Malaysia. There are two groups of factor that have been considered, namely district descriptive factors and socio and demographic factors. The result of the study showed that Bumiputera composition, Chinese composition, Other ethnic composition, foreign migration, number of residence with the age between 25 to 64, number of employed person and number of unemployed person are the most influence factors that affect the car theft cases. These information are very useful for the law enforcement department, insurance company and car owners in order to reduce and limiting the car theft cases in Peninsular Malaysia.
Regression: The Apple Does Not Fall Far From the Tree.
Vetter, Thomas R; Schober, Patrick
2018-05-15
Researchers and clinicians are frequently interested in either: (1) assessing whether there is a relationship or association between 2 or more variables and quantifying this association; or (2) determining whether 1 or more variables can predict another variable. The strength of such an association is mainly described by the correlation. However, regression analysis and regression models can be used not only to identify whether there is a significant relationship or association between variables but also to generate estimations of such a predictive relationship between variables. This basic statistical tutorial discusses the fundamental concepts and techniques related to the most common types of regression analysis and modeling, including simple linear regression, multiple regression, logistic regression, ordinal regression, and Poisson regression, as well as the common yet often underrecognized phenomenon of regression toward the mean. The various types of regression analysis are powerful statistical techniques, which when appropriately applied, can allow for the valid interpretation of complex, multifactorial data. Regression analysis and models can assess whether there is a relationship or association between 2 or more observed variables and estimate the strength of this association, as well as determine whether 1 or more variables can predict another variable. Regression is thus being applied more commonly in anesthesia, perioperative, critical care, and pain research. However, it is crucial to note that regression can identify plausible risk factors; it does not prove causation (a definitive cause and effect relationship). The results of a regression analysis instead identify independent (predictor) variable(s) associated with the dependent (outcome) variable. As with other statistical methods, applying regression requires that certain assumptions be met, which can be tested with specific diagnostics.
Extensions of Rasch's Multiplicative Poisson Model.
ERIC Educational Resources Information Center
Jansen, Margo G. H.; van Duijn, Marijtje A. J.
1992-01-01
A model developed by G. Rasch that assumes scores on some attainment tests can be realizations of a Poisson process is explained and expanded by assuming a prior distribution, with fixed but unknown parameters, for the subject parameters. How additional between-subject and within-subject factors can be incorporated is discussed. (SLD)
do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado Junior, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro
2015-01-01
To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95% was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α<5%. From 226 women included, 200 (88.5%) were 20 to 44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.
2013-01-01
Background Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. Methods The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. Results The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother’s education, father’s education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Conclusions Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh. PMID:23297699
An INAR(1) Negative Multinomial Regression Model for Longitudinal Count Data.
ERIC Educational Resources Information Center
Bockenholt, Ulf
1999-01-01
Discusses a regression model for the analysis of longitudinal count data in a panel study by adapting an integer-valued first-order autoregressive (INAR(1)) Poisson process to represent time-dependent correlation between counts. Derives a new negative multinomial distribution by combining INAR(1) representation with a random effects approach.…
Pick Your Poisson: A Tutorial on Analyzing Counts of Student Victimization Data
ERIC Educational Resources Information Center
Huang, Francis L.; Cornell, Dewey G.
2012-01-01
School violence research is often concerned with infrequently occurring events such as counts of the number of bullying incidents or fights a student may experience. Analyzing count data using ordinary least squares regression may produce improbable predicted values, and as a result of regression assumption violations, result in higher Type I…
Easy Demonstration of the Poisson Spot
ERIC Educational Resources Information Center
Gluck, Paul
2010-01-01
Many physics teachers have a set of slides of single, double and multiple slits to show their students the phenomena of interference and diffraction. Thomas Young's historic experiments with double slits were indeed a milestone in proving the wave nature of light. But another experiment, namely the Poisson spot, was also important historically and…
Zhang, Ling Yu; Liu, Zhao Gang
2017-12-01
Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.
NASA Astrophysics Data System (ADS)
Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.
2018-04-01
Sea level rise has already caused more frequent and severe coastal flooding and this trend will likely continue. Flood prediction is an essential part of a coastal city's capacity to adapt to and mitigate this growing problem. Complex coastal urban hydrological systems however, do not always lend themselves easily to physically-based flood prediction approaches. This paper presents a method for using a data-driven approach to estimate flood severity in an urban coastal setting using crowd-sourced data, a non-traditional but growing data source, along with environmental observation data. Two data-driven models, Poisson regression and Random Forest regression, are trained to predict the number of flood reports per storm event as a proxy for flood severity, given extensive environmental data (i.e., rainfall, tide, groundwater table level, and wind conditions) as input. The method is demonstrated using data from Norfolk, Virginia USA from September 2010 to October 2016. Quality-controlled, crowd-sourced street flooding reports ranging from 1 to 159 per storm event for 45 storm events are used to train and evaluate the models. Random Forest performed better than Poisson regression at predicting the number of flood reports and had a lower false negative rate. From the Random Forest model, total cumulative rainfall was by far the most dominant input variable in predicting flood severity, followed by low tide and lower low tide. These methods serve as a first step toward using data-driven methods for spatially and temporally detailed coastal urban flood prediction.
NASA Astrophysics Data System (ADS)
Long, Kai; Yuan, Philip F.; Xu, Shanqing; Xie, Yi Min
2018-04-01
Most studies on composites assume that the constituent phases have different values of stiffness. Little attention has been paid to the effect of constituent phases having distinct Poisson's ratios. This research focuses on a concurrent optimization method for simultaneously designing composite structures and materials with distinct Poisson's ratios. The proposed method aims to minimize the mean compliance of the macrostructure with a given mass of base materials. In contrast to the traditional interpolation of the stiffness matrix through numerical results, an interpolation scheme of the Young's modulus and Poisson's ratio using different parameters is adopted. The numerical results demonstrate that the Poisson effect plays a key role in reducing the mean compliance of the final design. An important contribution of the present study is that the proposed concurrent optimization method can automatically distribute base materials with distinct Poisson's ratios between the macrostructural and microstructural levels under a single constraint of the total mass.
Xing, Jian; Burkom, Howard; Tokars, Jerome
2011-12-01
Automated surveillance systems require statistical methods to recognize increases in visit counts that might indicate an outbreak. In prior work we presented methods to enhance the sensitivity of C2, a commonly used time series method. In this study, we compared the enhanced C2 method with five regression models. We used emergency department chief complaint data from US CDC BioSense surveillance system, aggregated by city (total of 206 hospitals, 16 cities) during 5/2008-4/2009. Data for six syndromes (asthma, gastrointestinal, nausea and vomiting, rash, respiratory, and influenza-like illness) was used and was stratified by mean count (1-19, 20-49, ≥50 per day) into 14 syndrome-count categories. We compared the sensitivity for detecting single-day artificially-added increases in syndrome counts. Four modifications of the C2 time series method, and five regression models (two linear and three Poisson), were tested. A constant alert rate of 1% was used for all methods. Among the regression models tested, we found that a Poisson model controlling for the logarithm of total visits (i.e., visits both meeting and not meeting a syndrome definition), day of week, and 14-day time period was best. Among 14 syndrome-count categories, time series and regression methods produced approximately the same sensitivity (<5% difference) in 6; in six categories, the regression method had higher sensitivity (range 6-14% improvement), and in two categories the time series method had higher sensitivity. When automated data are aggregated to the city level, a Poisson regression model that controls for total visits produces the best overall sensitivity for detecting artificially added visit counts. This improvement was achieved without increasing the alert rate, which was held constant at 1% for all methods. These findings will improve our ability to detect outbreaks in automated surveillance system data. Published by Elsevier Inc.
Salazar, Edwin; Buitrago, Carolina; Molina, Federico; Alzate, Catalina Arango
2015-05-01
Determine the trend in mortality from external causes in pregnant and postpartum women and its relationship to socioeconomic factors. Descriptive study, based on the official registries of deaths reported by the National Statistics Agency, 1998-2010. The trend was analyzed using Poisson regressions. Bivariate correlations and multiple linear regression models were constructed to explore the relationship between mortality and socioeconomic factors: human development index, Gini index, gross domestic product, unsatisfied basic needs, unemployment rate, poverty, extreme poverty, quality of life index, illiteracy rate, and percentage of affiliation to the Social Security System. A total of 2 223 female deaths from external causes were recorded, of which 1 429 occurred during pregnancy and 794 in the postpartum period. The gross mortality rate dropped from 30.7 per 100 000 live births plus fetal deaths in 1998 to 16.7 in 2010. A downward curve with no significant inflection points was shown in the risk of dying from this cause. The multiple linear regression model showed a correlation between mortality and extreme poverty and the illiteracy rate, suggesting that these indicators could explain 89.4% of the change in mortality from external causes in pregnant and postpartum women each year in Colombia. Mortality from external causes in pregnant and postpartum women showed a significant downward trend that may be explained by important socioeconomic changes in the country, including a decrease in extreme poverty and in the illiteracy rate.
Bacterial diversity in saliva and oral health-related conditions: the Hisayama Study
NASA Astrophysics Data System (ADS)
Takeshita, Toru; Kageyama, Shinya; Furuta, Michiko; Tsuboi, Hidenori; Takeuchi, Kenji; Shibata, Yukie; Shimazaki, Yoshihiro; Akifusa, Sumio; Ninomiya, Toshiharu; Kiyohara, Yutaka; Yamashita, Yoshihisa
2016-02-01
This population-based study determined the salivary microbiota composition of 2,343 adult residents of Hisayama town, Japan, using 16S rRNA gene next-generation high-throughput sequencing. Of 550 identified species-level operational taxonomic units (OTUs), 72 were common, in ≥75% of all individuals, as well as in ≥75% of the individuals in the lowest quintile of phylogenetic diversity (PD). These “core” OTUs constituted 90.9 ± 6.1% of each microbiome. The relative abundance profiles of 22 of the core OTUs with mean relative abundances ≥1% were stratified into community type I and community type II by partitioning around medoids clustering. Multiple regression analysis revealed that a lower PD was associated with better conditions for oral health, including a lower plaque index, absence of decayed teeth, less gingival bleeding, shallower periodontal pockets and not smoking, and was also associated with tooth loss. By contrast, multiple Poisson regression analysis demonstrated that community type II, as characterized by a higher ratio of the nine dominant core OTUs, including Neisseria flavescens, was implicated in younger age, lower body mass index, fewer teeth with caries experience, and not smoking. Our large-scale data analyses reveal variation in the salivary microbiome among Japanese adults and oral health-related conditions associated with the salivary microbiome.
Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.
Ritz, Christian; Van der Vliet, Leana
2009-09-01
The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.
Marginalized zero-inflated Poisson models with missing covariates.
Benecha, Habtamu K; Preisser, John S; Divaris, Kimon; Herring, Amy H; Das, Kalyan
2018-05-11
Unlike zero-inflated Poisson regression, marginalized zero-inflated Poisson (MZIP) models for counts with excess zeros provide estimates with direct interpretations for the overall effects of covariates on the marginal mean. In the presence of missing covariates, MZIP and many other count data models are ordinarily fitted using complete case analysis methods due to lack of appropriate statistical methods and software. This article presents an estimation method for MZIP models with missing covariates. The method, which is applicable to other missing data problems, is illustrated and compared with complete case analysis by using simulations and dental data on the caries preventive effects of a school-based fluoride mouthrinse program. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Cheng, Yiling J; Gregg, Edward W; Rolka, Deborah B; Thompson, Theodore J
2016-12-15
Monitoring national mortality among persons with a disease is important to guide and evaluate progress in disease control and prevention. However, a method to estimate nationally representative annual mortality among persons with and without diabetes in the United States does not currently exist. The aim of this study is to demonstrate use of weighted discrete Poisson regression on national survey mortality follow-up data to estimate annual mortality rates among adults with diabetes. To estimate mortality among US adults with diabetes, we applied a weighted discrete time-to-event Poisson regression approach with post-stratification adjustment to national survey data. Adult participants aged 18 or older with and without diabetes in the National Health Interview Survey 1997-2004 were followed up through 2006 for mortality status. We estimated mortality among all US adults, and by self-reported diabetes status at baseline. The time-varying covariates used were age and calendar year. Mortality among all US adults was validated using direct estimates from the National Vital Statistics System (NVSS). Using our approach, annual all-cause mortality among all US adults ranged from 8.8 deaths per 1,000 person-years (95% confidence interval [CI]: 8.0, 9.6) in year 2000 to 7.9 (95% CI: 7.6, 8.3) in year 2006. By comparison, the NVSS estimates ranged from 8.6 to 7.9 (correlation = 0.94). All-cause mortality among persons with diabetes decreased from 35.7 (95% CI: 28.4, 42.9) in 2000 to 31.8 (95% CI: 28.5, 35.1) in 2006. After adjusting for age, sex, and race/ethnicity, persons with diabetes had 2.1 (95% CI: 2.01, 2.26) times the risk of death of those without diabetes. Period-specific national mortality can be estimated for people with and without a chronic condition using national surveys with mortality follow-up and a discrete time-to-event Poisson regression approach with post-stratification adjustment.
The Code of the Street and Violent Versus Property Crime Victimization.
McNeeley, Susan; Wilcox, Pamela
2015-01-01
Previous research has shown that individuals who adopt values in line with the code of the street are more likely to experience violent victimization (e.g., Stewart, Schreck, & Simons, 2006). This study extends this literature by examining the relationship between the street code and multiple types of violent and property victimization. This research investigates the relationship between street code-related values and 4 types of victimization (assault, breaking and entering, theft, and vandalism) using Poisson-based multilevel regression models. Belief in the street code was associated with higher risk of experiencing assault, breaking and entering, and vandalism, whereas theft victimization was not related to the street code. The results suggest that the code of the street influences victimization broadly--beyond violence--by increasing behavior that provokes retaliation from others in various forms.
Doubly stochastic Poisson process models for precipitation at fine time-scales
NASA Astrophysics Data System (ADS)
Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao
2012-09-01
This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.
Bramness, Jørgen G; Walby, Fredrik A; Morken, Gunnar; Røislien, Jo
2015-08-01
Seasonal variation in the number of suicides has long been acknowledged. It has been suggested that this seasonality has declined in recent years, but studies have generally used statistical methods incapable of confirming this. We examined all suicides occurring in Norway during 1969-2007 (more than 20,000 suicides in total) to establish whether seasonality decreased over time. Fitting of additive Fourier Poisson time-series regression models allowed for formal testing of a possible linear decrease in seasonality, or a reduction at a specific point in time, while adjusting for a possible smooth nonlinear long-term change without having to categorize time into discrete yearly units. The models were compared using Akaike's Information Criterion and analysis of variance. A model with a seasonal pattern was significantly superior to a model without one. There was a reduction in seasonality during the period. Both the model assuming a linear decrease in seasonality and the model assuming a change at a specific point in time were both superior to a model assuming constant seasonality, thus confirming by formal statistical testing that the magnitude of the seasonality in suicides has diminished. The additive Fourier Poisson time-series regression model would also be useful for studying other temporal phenomena with seasonal components. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Setty, Karen E; Kayser, Georgia L; Bowling, Michael; Enault, Jerome; Loret, Jean-Francois; Serra, Claudia Puigdomenech; Alonso, Jordi Martin; Mateu, Arnau Pla; Bartram, Jamie
2017-05-01
Water Safety Plans (WSPs), recommended by the World Health Organization since 2004, seek to proactively identify potential risks to drinking water supplies and implement preventive barriers that improve safety. To evaluate the outcomes of WSP application in large drinking water systems in France and Spain, we undertook analysis of water quality and compliance indicators between 2003 and 2015, in conjunction with an observational retrospective cohort study of acute gastroenteritis incidence, before and after WSPs were implemented at five locations. Measured water quality indicators included bacteria (E. coli, fecal streptococci, total coliform, heterotrophic plate count), disinfectants (residual free and total chlorine), disinfection by-products (trihalomethanes, bromate), aluminum, pH, turbidity, and total organic carbon, comprising about 240K manual samples and 1.2M automated sensor readings. We used multiple, Poisson, or Tobit regression models to evaluate water quality before and after the WSP intervention. The compliance assessment analyzed exceedances of regulated, recommended, or operational water quality thresholds using chi-squared or Fisher's exact tests. Poisson regression was used to examine acute gastroenteritis incidence rates in WSP-affected drinking water service areas relative to a comparison area. Implementation of a WSP generally resulted in unchanged or improved water quality, while compliance improved at most locations. Evidence for reduced acute gastroenteritis incidence following WSP implementation was found at only one of the three locations examined. Outcomes of WSPs should be expected to vary across large water utilities in developed nations, as the intervention itself is adapted to the needs of each location. The approach may translate to diverse water quality, compliance, and health outcomes. Copyright © 2017 Elsevier GmbH. All rights reserved.
Age at First Concussion Influences the Number of Subsequent Concussions.
Schmidt, Julianne D; Rizzone, Katherine; Hoffman, Nicole L; Weber, Michelle L; Jones, Courtney; Bazarian, Jeff; Broglio, Steven P; McCrea, Michael; McAllister, Thomas W
2018-04-01
Individuals who sustain their first concussion during childhood may be at greater risk of sustaining multiple concussions throughout their lifetime because of a longer window of vulnerability. This article aims to estimate the association between age at first concussion and number of subsequent concussions. A total of 23,582 collegiate athletes from 26 universities and military cadets from three military academies completed a concussion history questionnaire (65% males, age 19.9 ± 1.4 years). Participants self-reported concussions and age at time of each injury. Participants with a history of concussion (n = 3,647, 15.5%) were categorized as having sustained their first concussion during childhood (less than ten years old) or adolescence (≥10 and ≤18 years old). Poisson regression was used to model age group (childhood, adolescence) predicting the number of subsequent concussions (0, 1, 2+). A second Poisson regression was developed to determine whether age at first concussion predicted the number of subsequent concussions. Participants self-reporting their first concussion during childhood had an increased risk of subsequent concussions (rate ratio = 2.19, 95% confidence interval: 1.82, 2.64) compared with participants self-reporting their first concussion during adolescence. For every one-year increase in age at first concussion, we observed a 16% reduction in the risk of subsequent concussion (rate ratio = 0.84, 95% confidence interval: 0.82, 0.86). Individuals self-reporting a concussion at a young age sustained a higher number of concussions before age 18. Concussion prevention, recognition, and reporting strategies are of particular need at the youth level. Copyright © 2018 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Pohle, Ina; Niebisch, Michael; Müller, Hannes; Schümberg, Sabine; Zha, Tingting; Maurer, Thomas; Hinz, Christoph
2018-07-01
To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long precipitation time series with high temporal resolution are required. Due to limited availability of observed data such time series are typically obtained from stochastic models. However, most existing rainfall models are limited in their ability to conserve rainfall event statistics which are relevant for hydrological processes. Poisson rectangular pulse models are widely applied to generate long time series of alternating precipitation events durations and mean intensities as well as interstorm period durations. Multiplicative microcanonical random cascade (MRC) models are used to disaggregate precipitation time series from coarse to fine temporal resolution. To overcome the inconsistencies between the temporal structure of the Poisson rectangular pulse model and the MRC model, we developed a new coupling approach by introducing two modifications to the MRC model. These modifications comprise (a) a modified cascade model ("constrained cascade") which preserves the event durations generated by the Poisson rectangular model by constraining the first and last interval of a precipitation event to contain precipitation and (b) continuous sigmoid functions of the multiplicative weights to consider the scale-dependency in the disaggregation of precipitation events of different durations. The constrained cascade model was evaluated in its ability to disaggregate observed precipitation events in comparison to existing MRC models. For that, we used a 20-year record of hourly precipitation at six stations across Germany. The constrained cascade model showed a pronounced better agreement with the observed data in terms of both the temporal pattern of the precipitation time series (e.g. the dry and wet spell durations and autocorrelations) and event characteristics (e.g. intra-event intermittency and intensity fluctuation within events). The constrained cascade model also slightly outperformed the other MRC models with respect to the intensity-frequency relationship. To assess the performance of the coupled Poisson rectangular pulse and constrained cascade model, precipitation events were stochastically generated by the Poisson rectangular pulse model and then disaggregated by the constrained cascade model. We found that the coupled model performs satisfactorily in terms of the temporal pattern of the precipitation time series, event characteristics and the intensity-frequency relationship.
Determinants of preterm birth rates in Canada from 1981 through 1983 and from 1992 through 1994.
Joseph, K S; Kramer, M S; Marcoux, S; Ohlsson, A; Wen, S W; Allen, A; Platt, R
1998-11-12
The rates of preterm birth have increased in many countries, including Canada, over the past 20 years. However, the factors underlying the increase are poorly understood. We used data from the Statistics Canada live-birth and stillbirth data bases to determine the effects of changes in the frequency of multiple births, registration of births occurring very early in gestation, patterns of obstetrical intervention, and use of ultrasonographic dating of gestational age on the rates of preterm birth in Canada from 1981 through 1983 and from 1992 through 1994. All births in 9 of the 12 provinces and territories of Canada were included. Logistic-regression analysis and Poisson regression analysis were used to estimate changes between the two three-year periods, after adjustment for the above-mentioned determinants of the likelihood of preterm births. Preterm births increased from 6.3 percent of live births in 1981 through 1983 to 6.8 percent in 1992 through 1994, a relative increase of 9 percent (95 percent confidence interval, 7 to 10 percent). Among singleton births, preterm births increased by 5 percent (95 percent confidence interval, 3 to 6 percent). Multiple births increased from 1.9 percent to 2.1 percent of all live births; the rates of preterm birth among live births resulting from multiple gestations increased by 25 percent (95 percent confidence interval, 21 to 28 percent). Adjustment for the determinants of the likelihood of preterm birth reduced the increase in the rate of preterm birth to 3 percent among all live births and 1 percent among singleton births. The recent increase in preterm births in Canada is largely attributable to changes in the frequency of multiple births, obstetrical intervention, and the use of ultrasound-based estimates of gestational age.
An intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces.
Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying
2013-09-01
Poisson disk sampling has excellent spatial and spectral properties, and plays an important role in a variety of visual computing. Although many promising algorithms have been proposed for multidimensional sampling in euclidean space, very few studies have been reported with regard to the problem of generating Poisson disks on surfaces due to the complicated nature of the surface. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. In sharp contrast to the conventional parallel approaches, our method neither partitions the given surface into small patches nor uses any spatial data structure to maintain the voids in the sampling domain. Instead, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. Our algorithm guarantees that the generated Poisson disks are uniformly and randomly distributed without bias. It is worth noting that our method is intrinsic and independent of the embedding space. This intrinsic feature allows us to generate Poisson disk patterns on arbitrary surfaces in IR(n). To our knowledge, this is the first intrinsic, parallel, and accurate algorithm for surface Poisson disk sampling. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.
NASA Astrophysics Data System (ADS)
Eliazar, Iddo
2017-05-01
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their 'public relations' for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford's law, and 1/f noise.
Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.
Renner, Ian W; Warton, David I
2013-03-01
Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature. Copyright © 2013, The International Biometric Society.
NASA Astrophysics Data System (ADS)
Pohle, Ina; Niebisch, Michael; Zha, Tingting; Schümberg, Sabine; Müller, Hannes; Maurer, Thomas; Hinz, Christoph
2017-04-01
Rainfall variability within a storm is of major importance for fast hydrological processes, e.g. surface runoff, erosion and solute dissipation from surface soils. To investigate and simulate the impacts of within-storm variabilities on these processes, long time series of rainfall with high resolution are required. Yet, observed precipitation records of hourly or higher resolution are in most cases available only for a small number of stations and only for a few years. To obtain long time series of alternating rainfall events and interstorm periods while conserving the statistics of observed rainfall events, the Poisson model can be used. Multiplicative microcanonical random cascades have been widely applied to disaggregate rainfall time series from coarse to fine temporal resolution. We present a new coupling approach of the Poisson rectangular pulse model and the multiplicative microcanonical random cascade model that preserves the characteristics of rainfall events as well as inter-storm periods. In the first step, a Poisson rectangular pulse model is applied to generate discrete rainfall events (duration and mean intensity) and inter-storm periods (duration). The rainfall events are subsequently disaggregated to high-resolution time series (user-specified, e.g. 10 min resolution) by a multiplicative microcanonical random cascade model. One of the challenges of coupling these models is to parameterize the cascade model for the event durations generated by the Poisson model. In fact, the cascade model is best suited to downscale rainfall data with constant time step such as daily precipitation data. Without starting from a fixed time step duration (e.g. daily), the disaggregation of events requires some modifications of the multiplicative microcanonical random cascade model proposed by Olsson (1998): Firstly, the parameterization of the cascade model for events of different durations requires continuous functions for the probabilities of the multiplicative weights, which we implemented through sigmoid functions. Secondly, the branching of the first and last box is constrained to preserve the rainfall event durations generated by the Poisson rectangular pulse model. The event-based continuous time step rainfall generator has been developed and tested using 10 min and hourly rainfall data of four stations in North-Eastern Germany. The model performs well in comparison to observed rainfall in terms of event durations and mean event intensities as well as wet spell and dry spell durations. It is currently being tested using data from other stations across Germany and in different climate zones. Furthermore, the rainfall event generator is being applied in modelling approaches aimed at understanding the impact of rainfall variability on hydrological processes. Reference Olsson, J.: Evaluation of a scaling cascade model for temporal rainfall disaggregation, Hydrology and Earth System Sciences, 2, 19.30
Ramis, Rebeca; Vidal, Enrique; García-Pérez, Javier; Lope, Virginia; Aragonés, Nuria; Pérez-Gómez, Beatriz; Pollán, Marina; López-Abente, Gonzalo
2009-01-01
Background Non-Hodgkin's lymphomas (NHLs) have been linked to proximity to industrial areas, but evidence regarding the health risk posed by residence near pollutant industries is very limited. The European Pollutant Emission Register (EPER) is a public register that furnishes valuable information on industries that release pollutants to air and water, along with their geographical location. This study sought to explore the relationship between NHL mortality in small areas in Spain and environmental exposure to pollutant emissions from EPER-registered industries, using three Poisson-regression-based mathematical models. Methods Observed cases were drawn from mortality registries in Spain for the period 1994–2003. Industries were grouped into the following sectors: energy; metal; mineral; organic chemicals; waste; paper; food; and use of solvents. Populations having an industry within a radius of 1, 1.5, or 2 kilometres from the municipal centroid were deemed to be exposed. Municipalities outside those radii were considered as reference populations. The relative risks (RRs) associated with proximity to pollutant industries were estimated using the following methods: Poisson Regression; mixed Poisson model with random provincial effect; and spatial autoregressive modelling (BYM model). Results Only proximity of paper industries to population centres (>2 km) could be associated with a greater risk of NHL mortality (mixed model: RR:1.24, 95% CI:1.09–1.42; BYM model: RR:1.21, 95% CI:1.01–1.45; Poisson model: RR:1.16, 95% CI:1.06–1.27). Spatial models yielded higher estimates. Conclusion The reported association between exposure to air pollution from the paper, pulp and board industry and NHL mortality is independent of the model used. Inclusion of spatial random effects terms in the risk estimate improves the study of associations between environmental exposures and mortality. The EPER could be of great utility when studying the effects of industrial pollution on the health of the population. PMID:19159450
An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.
Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying
2013-03-08
Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.
Martina, R; Kay, R; van Maanen, R; Ridder, A
2015-01-01
Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.
Mallick, Himel; Tiwari, Hemant K.
2016-01-01
Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice. PMID:27066062
Mallick, Himel; Tiwari, Hemant K
2016-01-01
Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice.
Chan, King-Pan; Chan, Kwok-Hung; Wong, Wilfred Hing-Sang; Peiris, J. S. Malik; Wong, Chit-Ming
2011-01-01
Background Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus. Methods and Findings We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization. Conclusion The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong. PMID:21412433
Lin, Yi Hung; Tu, Yu Kang; Lu, Chun Tai; Chung, Wen Chen; Huang, Chiung Fang; Huang, Mao Suan; Lu, Hsein Kun
2014-01-01
Repigmentation variably occurs with different treatment methods in patients with gingival pigmentation. A systemic review was conducted of various treatment modalities for eliminating melanin pigmentation of the gingiva, comprising bur abrasion, scalpel surgery, cryosurgery, electrosurgery, gingival grafts, and laser techniques, to compare the recurrence rates (Rrs) of these treatment procedures. Electronic databases, including PubMed, Web of Science, Google, and Medline were comprehensively searched, and manual searches were conducted for studies published from January 1951 to June 2013. After applying inclusion and exclusion criteria, the final list of articles was reviewed in depth to achieve the objectives of this review. A Poisson regression was used to analyze the outcome of depigmentation using the various treatment methods. The systematic review was based on case reports mainly. In total, 61 eligible publications met the defined criteria. The various therapeutic procedures showed variable clinical results with a wide range of Rrs. A random-effects Poisson regression showed that cryosurgery (Rr = 0.32%), electrosurgery (Rr = 0.74%), and laser depigmentation (Rr = 1.16%) yielded superior result, whereas bur abrasion yielded the highest Rr (8.89%). Within the limit of the sampling level, the present evidence-based results show that cryosurgery exhibits the optimal predictability for depigmentation of the gingiva among all procedures examined, followed by electrosurgery and laser techniques. It is possible to treat melanin pigmentation of the gingiva with various methods and prevent repigmentation. Among those treatment modalities, cryosurgery, electrosurgery, and laser surgery appear to be the best choices for treating gingival pigmentation. © 2014 Wiley Periodicals, Inc.
Landsbergis, Paul A; Janevic, Teresa; Rothenberg, Laura; Adamu, Mohammed T; Johnson, Sylvia; Mirer, Franklin E
2013-07-01
We examined the association between long work hours, assembly line work and stress-related diseases utilizing objective health and employment data from an employer's administrative databases. A North American automobile manufacturing company provided data for claims for sickness, accident and disability insurance (work absence of at least 4 days) for cardiovascular disease (CVD), hypertension and psychological disorders, employee demographics, and facility hours worked per year for 1996-2001. Age-adjusted claim rates and age-adjusted rate ratios were calculated using Poisson regression, except for comparisons between production and skilled trades workers owing to lack of age denominator data by job category. Associations between overtime hours and claim rates by facility were examined by Poisson regression and multi-level Poisson regression. Claims for hypertension, coronary heart disease, CVD, and psychological disorders were associated with facility overtime hours. We estimate that a facility with 10 more overtime hours per week than another facility would have 4.36 more claims for psychological disorders, 2.33 more claims for CVD, and 3.29 more claims for hypertension per 1,000 employees per year. Assembly plants had the highest rates of claims for most conditions. Production workers tended to have higher rates of claims than skilled trades workers. Data from an auto manufacturer's administrative databases suggest that autoworkers working long hours, and assembly-line workers relative to skilled trades workers or workers in non-assembly facilities, have a higher risk of hypertension, CVD, and psychological disorders. Occupational disease surveillance and disease prevention programs need to fully utilize such administrative data. Copyright © 2013 Wiley Periodicals, Inc.
Silva, Fabyano Fonseca; Tunin, Karen P.; Rosa, Guilherme J.M.; da Silva, Marcos V.B.; Azevedo, Ana Luisa Souza; da Silva Verneque, Rui; Machado, Marco Antonio; Packer, Irineu Umberto
2011-01-01
Now a days, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr × Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable. PMID:22215960
Brian S. Cade; Barry R. Noon; Rick D. Scherer; John J. Keane
2017-01-01
Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical...
Farías-Antúnez, Simone; Lima, Natália Peixoto; Bierhals, Isabel Oliveira; Gomes, Ana Paula; Vieira, Luna Strieder; Tomasi, Elaine
2018-06-11
to estimate the prevalence of disability related to basic and instrumental activities of daily living and its association with socioeconomic, demographic, behavioral and health characteristics in the elderly. population-based cross-sectional study in Pelotas, Brazil, in 2014; Katz and Lawton scales were used to assess the outcomes using Poisson regression. the study included 1.451 elderly individuals; the prevalence of disability for basic and instrumental activities was 36.1% and 34.0%, respectively, and 18.1% in both; higher prevalence of functional disability were observed individuals ≥80 years (PR=3.01; 95%CI 2.17;4.18), not working (PR=2.02; 95%CI 1.13;3.60) and those with multiple morbidities (PR=3.28; 95%CI 1.38;7.79); and lower in individuals with ≥12 years of schooling (PR=0.40; 95%CI 0.24;0.66), and that were physically active (PR=0.42; 95%CI 0.21;0.82). functional disability was associated to individuals older than 80, with less schooling years and affected by multiple morbidities.
A note on an attempt at more efficient Poisson series evaluation. [for lunar libration
NASA Technical Reports Server (NTRS)
Shelus, P. J.; Jefferys, W. H., III
1975-01-01
A substantial reduction has been achieved in the time necessary to compute lunar libration series. The method involves eliminating many of the trigonometric function calls by a suitable transformation and applying a short SNOBOL processor to the FORTRAN coding of the transformed series, which obviates many of the multiplication operations during the course of series evaluation. It is possible to accomplish similar results quite easily with other Poisson series.
Incidence of multiple myeloma in Olmsted County, Minnesota: Trend over 6 decades.
Kyle, Robert A; Therneau, Terry M; Rajkumar, S Vincent; Larson, Dirk R; Plevak, Matthew F; Melton, L Joseph
2004-12-01
Previous studies have indicated that the incidence and mortality rates for multiple myeloma have increased in the United States. The authors reported on the incidence of multiple myeloma in Olmsted County, Minnesota, between 1991 and 2001 and on trends in multiple myeloma incidence over the last 56 years. Using the files of the Mayo Clinic and the Olmsted Medical Center (Rochester, MN), the authors identified all residents of Olmsted County who had multiple myeloma, suspected myeloma, or a related disorder. Reports of all laboratory determinations, in addition to autopsy findings and death certificates, were obtained. The criteria for the diagnosis of multiple myeloma have not changed during the last 6 decades. All but 1 of the 47 residents with multiple myeloma first diagnosed between 1991 and 2001 were recognized antemortem. Fifty-five percent had a previous monoclonal gammopathy of undetermined significance, smoldering multiple myeloma, or solitary plasmacytoma before multiple myeloma was diagnosed. From 1991 to 2001, the overall annual incidence rate, age-adjusted to the 2000 U.S. population, was 4.3 per 100,000 (95% confidence interval, 3.0-5.5 per 100,000). Poisson regression analysis showed no statistically significant trend in Olmsted County incidence rates over 56 years. In similar fashion, the authors adjusted multiple myeloma incidence rates from nine other studies worldwide for which adequate data were available and documented similar findings in each case, except for one study that included patients with smoldering multiple myeloma. The overall incidence of multiple myeloma in Olmsted County, Minnesota, has not changed in almost 6 decades. The apparent increase in incidence elsewhere is unexplained but probably is attributable to improvements in diagnostic techniques, particularly in older patients. (c) 2004 American Cancer Society
Lord, Dominique; Washington, Simon P; Ivan, John N
2005-01-01
There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states-perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of "excess" zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to "excess" zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed-and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros.
Multiple Myeloma and Glyphosate Use: A Re-Analysis of US Agricultural Health Study (AHS) Data
Sorahan, Tom
2015-01-01
A previous publication of 57,311 pesticide applicators enrolled in the US Agricultural Health Study (AHS) produced disparate findings in relation to multiple myeloma risks in the period 1993–2001 and ever-use of glyphosate (32 cases of multiple myeloma in the full dataset of 54,315 applicators without adjustment for other variables: rate ratio (RR) 1.1, 95% confidence interval (CI) 0.5 to 2.4; 22 cases of multiple myeloma in restricted dataset of 40,719 applicators with adjustment for other variables: RR 2.6, 95% CI 0.7 to 9.4). It seemed important to determine which result should be preferred. RRs for exposed and non-exposed subjects were calculated using Poisson regression; subjects with missing data were not excluded from the main analyses. Using the full dataset adjusted for age and gender the analysis produced a RR of 1.12 (95% CI 0.50 to 2.49) for ever-use of glyphosate. Additional adjustment for lifestyle factors and use of ten other pesticides had little effect (RR 1.24, 95% CI 0.52 to 2.94). There were no statistically significant trends for multiple myeloma risks in relation to reported cumulative days (or intensity weighted days) of glyphosate use. The doubling of risk reported previously arose from the use of an unrepresentative restricted dataset and analyses of the full dataset provides no convincing evidence in the AHS for a link between multiple myeloma risk and glyphosate use. PMID:25635915
Multiple myeloma and glyphosate use: a re-analysis of US Agricultural Health Study (AHS) data.
Sorahan, Tom
2015-01-28
A previous publication of 57,311 pesticide applicators enrolled in the US Agricultural Health Study (AHS) produced disparate findings in relation to multiple myeloma risks in the period 1993-2001 and ever-use of glyphosate (32 cases of multiple myeloma in the full dataset of 54,315 applicators without adjustment for other variables: rate ratio (RR) 1.1, 95% confidence interval (CI) 0.5 to 2.4; 22 cases of multiple myeloma in restricted dataset of 40,719 applicators with adjustment for other variables: RR 2.6, 95% CI 0.7 to 9.4). It seemed important to determine which result should be preferred. RRs for exposed and non-exposed subjects were calculated using Poisson regression; subjects with missing data were not excluded from the main analyses. Using the full dataset adjusted for age and gender the analysis produced a RR of 1.12 (95% CI 0.50 to 2.49) for ever-use of glyphosate. Additional adjustment for lifestyle factors and use of ten other pesticides had little effect (RR 1.24, 95% CI 0.52 to 2.94). There were no statistically significant trends for multiple myeloma risks in relation to reported cumulative days (or intensity weighted days) of glyphosate use. The doubling of risk reported previously arose from the use of an unrepresentative restricted dataset and analyses of the full dataset provides no convincing evidence in the AHS for a link between multiple myeloma risk and glyphosate use.
An examination of sources of sensitivity of consumer surplus estimates in travel cost models.
Blaine, Thomas W; Lichtkoppler, Frank R; Bader, Timothy J; Hartman, Travis J; Lucente, Joseph E
2015-03-15
We examine sensitivity of estimates of recreation demand using the Travel Cost Method (TCM) to four factors. Three of the four have been routinely and widely discussed in the TCM literature: a) Poisson verses negative binomial regression; b) application of Englin correction to account for endogenous stratification; c) truncation of the data set to eliminate outliers. A fourth issue we address has not been widely modeled: the potential effect on recreation demand of the interaction between income and travel cost. We provide a straightforward comparison of all four factors, analyzing the impact of each on regression parameters and consumer surplus estimates. Truncation has a modest effect on estimates obtained from the Poisson models but a radical effect on the estimates obtained by way of the negative binomial. Inclusion of an income-travel cost interaction term generally produces a more conservative but not a statistically significantly different estimate of consumer surplus in both Poisson and negative binomial models. It also generates broader confidence intervals. Application of truncation, the Englin correction and the income-travel cost interaction produced the most conservative estimates of consumer surplus and eliminated the statistical difference between the Poisson and the negative binomial. Use of the income-travel cost interaction term reveals that for visitors who face relatively low travel costs, the relationship between income and travel demand is negative, while it is positive for those who face high travel costs. This provides an explanation of the ambiguities on the findings regarding the role of income widely observed in the TCM literature. Our results suggest that policies that reduce access to publicly owned resources inordinately impact local low income recreationists and are contrary to environmental justice. Copyright © 2014 Elsevier Ltd. All rights reserved.
Nakahara, S.; Nakamura, Y.; Ichikawa, M.; Wakai, S.
2004-01-01
Objectives: To examine vehicle related mortality trends of children in Japan; and to investigate how environmental modifications such as the installation of public parks and pavements are associated with these trends. Design: Poisson regression was used for trend analysis, and multiple regression modelling was used to investigate the associations between trends in environmental modifications and trends in motor vehicle related child mortality rates. Setting: Mortality data of Japan from 1970 to 1994, defined as E-code 810–23 from 1970 to 1978 and E810–25 from 1979 to 1994, were obtained from vital statistics. Multiple regression modelling was confined to the 1970–1985 data. Data concerning public parks and other facilities were obtained from the Ministry of Land, Infrastructure, and Transport. Subjects: Children aged 0–14 years old were examined in this study and divided into two groups: 0–4 and 5–14 years. Main results: An increased number of public parks was associated with decreased vehicle related mortality rates among children aged 0–4 years, but not among children aged 5–14. In contrast, there was no association between trends in pavements and mortality rates. Conclusions: An increased number of public parks might reduce vehicle related preschooler deaths, in particular those involving pedestrians. Safe play areas in residential areas might reduce the risk of vehicle related child death by lessening the journey both to and from such areas as well as reducing the number of children playing on the street. However, such measures might not be effective in reducing the vehicle related mortalities of school age children who have an expanded range of activities and walk longer distances. PMID:15547055
Osche, G R
2000-08-20
Single- and multiple-pulse detection statistics are presented for aperture-averaged direct detection optical receivers operating against partially developed speckle fields. A partially developed speckle field arises when the probability density function of the received intensity does not follow negative exponential statistics. The case of interest here is the target surface that exhibits diffuse as well as specular components in the scattered radiation. An approximate expression is derived for the integrated intensity at the aperture, which leads to single- and multiple-pulse discrete probability density functions for the case of a Poisson signal in Poisson noise with an additive coherent component. In the absence of noise, the single-pulse discrete density function is shown to reduce to a generalized negative binomial distribution. The radar concept of integration loss is discussed in the context of direct detection optical systems where it is shown that, given an appropriate set of system parameters, multiple-pulse processing can be more efficient than single-pulse processing over a finite range of the integration parameter n.
Nascimento, Alex Rodrigues do; Andrade, Fabíola Bof de; César, Cibele Comini
2016-11-03
This study sought to describe the agreement between self-perception and clinical evaluation of dental treatment needs in adults and analyze associated factors. The sample comprised adult individuals who took part in SBBrazil 2010 and SBMinas Gerais 2012. The study's outcome was agreement between self-perception and clinical evaluation of dental treatment needs. We used multiple Poisson regression in order to determine the factors associated with the outcome. Agreement between self-perception and clinical evaluation was 78.8% in Brazil and 73.8% in Minas Gerais. Clinical and self-reported oral health conditions that affect function and quality of life were associated with a higher agreement, while a recent visit to the dentist was associated with a lower agreement. Identifying associated factors may enable the development of questionnaires that favor correct self-perception regarding treatment needs.
Geographical distribution of a seropositive myasthenia gravis population.
Heldal, Anne Taraldsen; Eide, Geir Egil; Gilhus, Nils Erik; Romi, Fredrik
2012-06-01
To assess age- and sex-specific myasthenia gravis (MG) occurrence and incidence in the different geographical regions in Norway and thereby to identify factors that may contribute to the development of MG. Multiple Poisson regression analysis was used to assess variation in incidence dependent on year, gender and onset age in five geographically defined health regions. The study population comprised 419 individuals with first time seropositive tests from 1995 to 2007. Annual MG incidence ranged from < 1 to 14 per million, with an average of 7.04 per million for all five health regions combined. This is the first nation-wide epidemiological study of seropositive MG that elucidates the geographical differences within a country. The incidence of seropositive MG did not vary significantly between the regions. Mid-Norway tended to have a higher incidence, and North tended to have a lower incidence. Copyright © 2011 Wiley Periodicals, Inc.
Dong, Chunjiao; Clarke, David B; Richards, Stephen H; Huang, Baoshan
2014-01-01
The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle types is rarely addressed. This paper develops and presents a multivariate regression model of crash frequencies by collision vehicle type using crash data for urban signalized intersections in Tennessee. In addition, the performance of univariate Poisson-lognormal (UVPLN), multivariate Poisson (MVP), and multivariate Poisson-lognormal (MVPLN) regression models in establishing the relationship between crashes, traffic factors, and geometric design of roadway intersections is investigated. Bayesian methods are used to estimate the unknown parameters of these models. The evaluation results suggest that the MVPLN model possesses most of the desirable statistical properties in developing the relationships. Compared to the UVPLN and MVP models, the MVPLN model better identifies significant factors and predicts crash frequencies. The findings suggest that traffic volume, truck percentage, lighting condition, and intersection angle significantly affect intersection safety. Important differences in car, car-truck, and truck crash frequencies with respect to various risk factors were found to exist between models. The paper provides some new or more comprehensive observations that have not been covered in previous studies. Copyright © 2013 Elsevier Ltd. All rights reserved.
Geographical variation in the incidence of childhood leukaemia in Manitoba.
Torabi, Mahmoud; Singh, Harminder; Galloway, Katie; Israels, Sara J
2015-11-01
Identification of geographical areas and ecological factors associated with higher incidence of childhood leukaemias can direct further study for preventable factors and location of health services to manage such individuals. The aim of this study was to describe the geographical variation and the socio-demographic factors associated with childhood leukaemia in Manitoba. Information on childhood leukaemia incidence between 1992 and 2008 was obtained from the Canadian Cancer Registry and the socio-demographic characteristics for the area of residence from the 2006 Canadian Census. Bayesian spatial Poisson mixed models were used to describe the geographical variation of childhood leukaemia and to determine the association between childhood leukaemia and socio-demographic factors. The south-eastern part of the province had a higher incidence of childhood leukaemia than other parts of the province. In the age and sex-adjusted Poisson regression models, areas with higher proportions of visible minorities and immigrant residents had higher childhood leukaemia incidence rate ratios. In the saturated Poisson regression model, the childhood leukaemia rates were higher in areas with higher proportions of immigrant residents. Unemployment rates were not a significant factor in leukaemia incidence. In Manitoba, areas with higher proportions of immigrants experience higher incidence rates of childhood leukaemia. We have identified geographical areas with higher incidence, which require further study and attention. © 2015 The Authors. Journal of Paediatrics and Child Health © 2015 Paediatrics and Child Health Division (Royal Australasian College of Physicians).
Evaluating the double Poisson generalized linear model.
Zou, Yaotian; Geedipally, Srinivas Reddy; Lord, Dominique
2013-10-01
The objectives of this study are to: (1) examine the applicability of the double Poisson (DP) generalized linear model (GLM) for analyzing motor vehicle crash data characterized by over- and under-dispersion and (2) compare the performance of the DP GLM with the Conway-Maxwell-Poisson (COM-Poisson) GLM in terms of goodness-of-fit and theoretical soundness. The DP distribution has seldom been investigated and applied since its first introduction two decades ago. The hurdle for applying the DP is related to its normalizing constant (or multiplicative constant) which is not available in closed form. This study proposed a new method to approximate the normalizing constant of the DP with high accuracy and reliability. The DP GLM and COM-Poisson GLM were developed using two observed over-dispersed datasets and one observed under-dispersed dataset. The modeling results indicate that the DP GLM with its normalizing constant approximated by the new method can handle crash data characterized by over- and under-dispersion. Its performance is comparable to the COM-Poisson GLM in terms of goodness-of-fit (GOF), although COM-Poisson GLM provides a slightly better fit. For the over-dispersed data, the DP GLM performs similar to the NB GLM. Considering the fact that the DP GLM can be easily estimated with inexpensive computation and that it is simpler to interpret coefficients, it offers a flexible and efficient alternative for researchers to model count data. Copyright © 2013 Elsevier Ltd. All rights reserved.
Schrödinger-Poisson-Vlasov-Poisson correspondence
NASA Astrophysics Data System (ADS)
Mocz, Philip; Lancaster, Lachlan; Fialkov, Anastasia; Becerra, Fernando; Chavanis, Pierre-Henri
2018-04-01
The Schrödinger-Poisson equations describe the behavior of a superfluid Bose-Einstein condensate under self-gravity with a 3D wave function. As ℏ/m →0 , m being the boson mass, the equations have been postulated to approximate the collisionless Vlasov-Poisson equations also known as the collisionless Boltzmann-Poisson equations. The latter describe collisionless matter with a 6D classical distribution function. We investigate the nature of this correspondence with a suite of numerical test problems in 1D, 2D, and 3D along with analytic treatments when possible. We demonstrate that, while the density field of the superfluid always shows order unity oscillations as ℏ/m →0 due to interference and the uncertainty principle, the potential field converges to the classical answer as (ℏ/m )2. Thus, any dynamics coupled to the superfluid potential is expected to recover the classical collisionless limit as ℏ/m →0 . The quantum superfluid is able to capture rich phenomena such as multiple phase-sheets, shell-crossings, and warm distributions. Additionally, the quantum pressure tensor acts as a regularizer of caustics and singularities in classical solutions. This suggests the exciting prospect of using the Schrödinger-Poisson equations as a low-memory method for approximating the high-dimensional evolution of the Vlasov-Poisson equations. As a particular example we consider dark matter composed of ultralight axions, which in the classical limit (ℏ/m →0 ) is expected to manifest itself as collisionless cold dark matter.
Khan, Asaduzzaman; Western, Mark
The purpose of this study was to explore factors that facilitate or hinder effective use of computers in Australian general medical practice. This study is based on data extracted from a national telephone survey of 480 general practitioners (GPs) across Australia. Clinical functions performed by GPs using computers were examined using a zero-inflated Poisson (ZIP) regression modelling. About 17% of GPs were not using computer for any clinical function, while 18% reported using computers for all clinical functions. The ZIP model showed that computer anxiety was negatively associated with effective computer use, while practitioners' belief about usefulness of computers was positively associated with effective computer use. Being a female GP or working in partnership or group practice increased the odds of effectively using computers for clinical functions. To fully capitalise on the benefits of computer technology, GPs need to be convinced that this technology is useful and can make a difference.
Rosenblum, Michael; van der Laan, Mark J.
2010-01-01
Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636
Bidirectional relationship between renal function and periodontal disease in older Japanese women.
Yoshihara, Akihiro; Iwasaki, Masanori; Miyazaki, Hideo; Nakamura, Kazutoshi
2016-09-01
The purpose of this study was to evaluate the reciprocal effects of chronic kidney disease (CKD) and periodontal disease. A total of 332 postmenopausal never smoking women were enrolled, and their serum high-sensitivity C-reactive protein, serum osteocalcin and serum cystatin C levels were measured. Poor renal function was defined as serum cystatin C > 0.91 mg/l. Periodontal disease markers, including clinical attachment level and the periodontal inflamed surface area (PISA), were also evaluated. Logistic regression analysis was conducted to evaluate the relationships between renal function and periodontal disease markers, serum osteocalcin level and hsCRP level. The prevalence-rate ratios (PRRs) on multiple Poisson regression analyses were determined to evaluate the relationships between periodontal disease markers and serum osteocalcin, serum cystatin C and serum hsCRP levels. On logistic regression analysis, PISA was significantly associated with serum cystatin C level. The odds ratio for serum cystatin C level was 2.44 (p = 0.011). The PRR between serum cystatin C level and periodontal disease markers such as number of sites with clinical attachment level ≥6 mm was significantly positive (3.12, p < 0.001). Similar tendencies were shown for serum osteocalcin level. This study suggests that CKD and periodontal disease can have reciprocal effects. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of thismore » object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.« less
Evolutionary inference via the Poisson Indel Process.
Bouchard-Côté, Alexandre; Jordan, Michael I
2013-01-22
We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.
Evolutionary inference via the Poisson Indel Process
Bouchard-Côté, Alexandre; Jordan, Michael I.
2013-01-01
We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296
Detecting isotopic ratio outliers
NASA Astrophysics Data System (ADS)
Bayne, C. K.; Smith, D. H.
An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers.
Baulig, Christine; Krummenauer, Frank; Geis, Berit; Tulka, Sabrina; Knippschild, Stephanie
2018-05-22
To assess the reporting quality of randomised controlled trial (RCT) abstracts on age-related macular degeneration (AMD) healthcare, to evaluate the adherence to the Consolidated Standards of Reporting Trials (CONSORT) statement's recommendations on minimum abstract information and to identify journal characteristics associated with abstract reporting quality. Cross-sectional evaluation of RCT abstracts on AMD healthcare. A PubMed search was implemented to identify RCT abstracts on AMD healthcare published in the English language between January 2004 and December 2013. Data extraction was performed by two parallel readers independently by means of a documentation format in accordance with the 16 items of the CONSORT checklist for abstracts. The total number of criteria fulfilled by an abstract was derived as primary endpoint of the investigation; incidence rate ratios (IRRs) with unadjusted 95% CI were estimated by means of multiple Poisson regression to identify journal and article characteristics (publication year, multicentre design, structured abstract recommendations, effective sample size, effective abstract word counts and journal impact factor) possibly associated with the total number of fulfilled items. 136 of 673 identified abstracts (published in 36 different journals) fulfilled all eligibility criteria. The median number of fulfilled items was 7 (95% CI 7 to 8). No abstract reported all 16 recommended items; the maximum total number was 14, the minimum 3 of 16 items. Multivariate analysis only demonstrated the abstracts' word counts as being significantly associated with a better reporting of abstracts (Poisson regression-based IRR 1.002, 95% CI 1.001 to 1.003). Reporting quality of RCT abstracts on AMD investigations showed a considerable potential for improvement to meet the CONSORT abstract reporting recommendations. Furthermore, word counts of abstracts were identified as significantly associated with the overall abstract reporting quality. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Borchers, D L; Langrock, R
2015-12-01
We develop maximum likelihood methods for line transect surveys in which animals go undetected at distance zero, either because they are stochastically unavailable while within view or because they are missed when they are available. These incorporate a Markov-modulated Poisson process model for animal availability, allowing more clustered availability events than is possible with Poisson availability models. They include a mark-recapture component arising from the independent-observer survey, leading to more accurate estimation of detection probability given availability. We develop models for situations in which (a) multiple detections of the same individual are possible and (b) some or all of the availability process parameters are estimated from the line transect survey itself, rather than from independent data. We investigate estimator performance by simulation, and compare the multiple-detection estimators with estimators that use only initial detections of individuals, and with a single-observer estimator. Simultaneous estimation of detection function parameters and availability model parameters is shown to be feasible from the line transect survey alone with multiple detections and double-observer data but not with single-observer data. Recording multiple detections of individuals improves estimator precision substantially when estimating the availability model parameters from survey data, and we recommend that these data be gathered. We apply the methods to estimate detection probability from a double-observer survey of North Atlantic minke whales, and find that double-observer data greatly improve estimator precision here too. © 2015 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
NASA Astrophysics Data System (ADS)
Xie, Dexuan; Jiang, Yi
2018-05-01
This paper reports a nonuniform ionic size nonlocal Poisson-Fermi double-layer model (nuNPF) and a uniform ionic size nonlocal Poisson-Fermi double-layer model (uNPF) for an electrolyte mixture of multiple ionic species, variable voltages on electrodes, and variable induced charges on boundary segments. The finite element solvers of nuNPF and uNPF are developed and applied to typical double-layer tests defined on a rectangular box, a hollow sphere, and a hollow rectangle with a charged post. Numerical results show that nuNPF can significantly improve the quality of the ionic concentrations and electric fields generated from uNPF, implying that the effect of nonuniform ion sizes is a key consideration in modeling the double-layer structure.
Generation of Plausible Hurricane Tracks for Preparedness Exercises
2017-04-25
wind extents are simulated by Poisson regression and temporal filtering . The un-optimized MATLAB code runs in less than a minute and is integrated into...of real hurricanes. After wind radii have been simulated for the entire track, median filtering , attenuation over land, and smoothing clean up the wind
Inhalant Use among Indiana School Children, 1991-2004
ERIC Educational Resources Information Center
Ding, Kele; Torabi, Mohammad R.; Perera, Bilesha; Jun, Mi Kyung; Jones-McKyer, E. Lisako
2007-01-01
Objective: To examine the prevalence and trend of inhalant use among Indiana public school students. Methods: The Alcohol, Tobacco, and Other Drug Use among Indiana Children and Adolescents surveys conducted annually between 1991 and 2004 were reanalyzed using 2-way moving average, Poisson regression, and ANOVA tests. Results: The prevalence had…
Multiscale analysis of neural spike trains.
Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin
2014-01-30
This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. Copyright © 2013 John Wiley & Sons, Ltd.
Seasonally adjusted birth frequencies follow the Poisson distribution.
Barra, Mathias; Lindstrøm, Jonas C; Adams, Samantha S; Augestad, Liv A
2015-12-15
Variations in birth frequencies have an impact on activity planning in maternity wards. Previous studies of this phenomenon have commonly included elective births. A Danish study of spontaneous births found that birth frequencies were well modelled by a Poisson process. Somewhat unexpectedly, there were also weekly variations in the frequency of spontaneous births. Another study claimed that birth frequencies follow the Benford distribution. Our objective was to test these results. We analysed 50,017 spontaneous births at Akershus University Hospital in the period 1999-2014. To investigate the Poisson distribution of these births, we plotted their variance over a sliding average. We specified various Poisson regression models, with the number of births on a given day as the outcome variable. The explanatory variables included various combinations of years, months, days of the week and the digit sum of the date. The relationship between the variance and the average fits well with an underlying Poisson process. A Benford distribution was disproved by a goodness-of-fit test (p < 0.01). The fundamental model with year and month as explanatory variables is significantly improved (p < 0.001) by adding day of the week as an explanatory variable. Altogether 7.5% more children are born on Tuesdays than on Sundays. The digit sum of the date is non-significant as an explanatory variable (p = 0.23), nor does it increase the explained variance. INERPRETATION: Spontaneous births are well modelled by a time-dependent Poisson process when monthly and day-of-the-week variation is included. The frequency is highest in summer towards June and July, Friday and Tuesday stand out as particularly busy days, and the activity level is at its lowest during weekends.
Choo-Wosoba, Hyoyoung; Levy, Steven M; Datta, Somnath
2016-06-01
Community water fluoridation is an important public health measure to prevent dental caries, but it continues to be somewhat controversial. The Iowa Fluoride Study (IFS) is a longitudinal study on a cohort of Iowa children that began in 1991. The main purposes of this study (http://www.dentistry.uiowa.edu/preventive-fluoride-study) were to quantify fluoride exposures from both dietary and nondietary sources and to associate longitudinal fluoride exposures with dental fluorosis (spots on teeth) and dental caries (cavities). We analyze a subset of the IFS data by a marginal regression model with a zero-inflated version of the Conway-Maxwell-Poisson distribution for count data exhibiting excessive zeros and a wide range of dispersion patterns. In general, we introduce two estimation methods for fitting a ZICMP marginal regression model. Finite sample behaviors of the estimators and the resulting confidence intervals are studied using extensive simulation studies. We apply our methodologies to the dental caries data. Our novel modeling incorporating zero inflation, clustering, and overdispersion sheds some new light on the effect of community water fluoridation and other factors. We also include a second application of our methodology to a genomic (next-generation sequencing) dataset that exhibits underdispersion. © 2015, The International Biometric Society.
Impact of previous ART and of ART initiation on outcome of HIV-associated tuberculosis.
Girardi, Enrico; Palmieri, Fabrizio; Angeletti, Claudio; Vanacore, Paola; Matteelli, Alberto; Gori, Andrea; Carbonara, Sergio; Ippolito, Giuseppe
2012-01-01
Combination antiretroviral therapy (cART) has progressively decreased mortality of HIV-associated tuberculosis .To date, however, limited data on tuberculosis treatment outcomes among coinfected patients who are not ART-naive at the time of tuberculosis diagnosis are available. A multicenter, observational study enrolled 246 HIV-infected patients diagnosed with tuberculosis, in 96 Italian infectious diseases hospital units, who started tuberculosis treatment. A polytomous logistic regression model was used to identify baseline factors associated with the outcome. A Poisson regression model was used to explain the effect of ART during tuberculosis treatment on mortality, as a time-varying covariate, adjusting for baseline characteristics. Outcomes of tuberculosis treatment were as follows: 130 (52.8%) were successfully treated, 36 (14.6%) patients died in a median time of 2 months (range: 0-16), and 80 (32.6%) had an unsuccessful outcome. Being foreign born or injecting drug users was associated with unsuccessful outcomes. In multivariable Poisson regression, cART during tuberculosis treatment decreased the risk of death, while this risk increased for those who were not ART-naive at tuberculosis diagnosis. ART during tuberculosis treatment is associated with a substantial reduction of death rate among HIV-infected patients. However, patients who are not ART-naive when they develop tuberculosis remain at elevated risk of death.
NASA Astrophysics Data System (ADS)
Amaliana, Luthfatul; Sa'adah, Umu; Wayan Surya Wardhani, Ni
2017-12-01
Tetanus Neonatorum is an infectious disease that can be prevented by immunization. The number of Tetanus Neonatorum cases in East Java Province is the highest in Indonesia until 2015. Tetanus Neonatorum data contain over dispersion and big enough proportion of zero-inflation. Negative Binomial (NB) regression is an alternative method when over dispersion happens in Poisson regression. However, the data containing over dispersion and zero-inflation are more appropriately analyzed by using Zero-Inflated Negative Binomial (ZINB) regression. The purpose of this study are: (1) to model Tetanus Neonatorum cases in East Java Province with 71.05 percent proportion of zero-inflation by using NB and ZINB regression, (2) to obtain the best model. The result of this study indicates that ZINB is better than NB regression with smaller AIC.
Paramedic-Initiated Home Care Referrals and Use of Home Care and Emergency Medical Services.
Verma, Amol A; Klich, John; Thurston, Adam; Scantlebury, Jordan; Kiss, Alex; Seddon, Gayle; Sinha, Samir K
2018-01-01
We examined the association between paramedic-initiated home care referrals and utilization of home care, 9-1-1, and Emergency Department (ED) services. This was a retrospective cohort study of individuals who received a paramedic-initiated home care referral after a 9-1-1 call between January 1, 2011 and December 31, 2012 in Toronto, Ontario, Canada. Home care, 9-1-1, and ED utilization were compared in the 6 months before and after home care referral. Nonparametric longitudinal regression was performed to assess changes in hours of home care service use and zero-inflated Poisson regression was performed to assess changes in the number of 9-1-1 calls and ambulance transports to ED. During the 24-month study period, 2,382 individuals received a paramedic-initiated home care referral. After excluding individuals who died, were hospitalized, or were admitted to a nursing home, the final study cohort was 1,851. The proportion of the study population receiving home care services increased from 18.2% to 42.5% after referral, representing 450 additional people receiving services. In longitudinal regression analysis, there was an increase of 17.4 hours in total services per person in the six months after referral (95% CI: 1.7-33.1, p = 0.03). The mean number of 9-1-1 calls per person was 1.44 (SD 9.58) before home care referral and 1.20 (SD 7.04) after home care referral in the overall study cohort. This represented a 10% reduction in 9-1-1 calls (95% CI: 7-13%, p < 0.001) in Poisson regression analysis. The mean number of ambulance transports to ED per person was 0.91 (SD 8.90) before home care referral and 0.79 (SD 6.27) after home care referral, representing a 7% reduction (95% CI: 3-11%, p < 0.001) in Poisson regression analysis. When only the participants with complete paramedic and home care records were included in the analysis, the reductions in 9-1-1 calls and ambulance transports to ED were attenuated but remained statistically significant. Paramedic-initiated home care referrals in Toronto were associated with improved access to and use of home care services and may have been associated with reduced 9-1-1 calls and ambulance transports to ED.
Accident prediction model for public highway-rail grade crossings.
Lu, Pan; Tolliver, Denver
2016-05-01
Considerable research has focused on roadway accident frequency analysis, but relatively little research has examined safety evaluation at highway-rail grade crossings. Highway-rail grade crossings are critical spatial locations of utmost importance for transportation safety because traffic crashes at highway-rail grade crossings are often catastrophic with serious consequences. The Poisson regression model has been employed to analyze vehicle accident frequency as a good starting point for many years. The most commonly applied variations of Poisson including negative binomial, and zero-inflated Poisson. These models are used to deal with common crash data issues such as over-dispersion (sample variance is larger than the sample mean) and preponderance of zeros (low sample mean and small sample size). On rare occasions traffic crash data have been shown to be under-dispersed (sample variance is smaller than the sample mean) and traditional distributions such as Poisson or negative binomial cannot handle under-dispersion well. The objective of this study is to investigate and compare various alternate highway-rail grade crossing accident frequency models that can handle the under-dispersion issue. The contributions of the paper are two-fold: (1) application of probability models to deal with under-dispersion issues and (2) obtain insights regarding to vehicle crashes at public highway-rail grade crossings. Copyright © 2016 Elsevier Ltd. All rights reserved.
Statistical modeling of dental unit water bacterial test kit performance.
Cohen, Mark E; Harte, Jennifer A; Stone, Mark E; O'Connor, Karen H; Coen, Michael L; Cullum, Malford E
2007-01-01
While it is important to monitor dental water quality, it is unclear whether in-office test kits provide bacterial counts comparable to the gold standard method (R2A). Studies were conducted on specimens with known bacterial concentrations, and from dental units, to evaluate test kit accuracy across a range of bacterial types and loads. Colony forming units (CFU) were counted for samples from each source, using R2A and two types of test kits, and conformity to Poisson distribution expectations was evaluated. Poisson regression was used to test for effects of source and device, and to estimate rate ratios for kits relative to R2A. For all devices, distributions were Poisson for low CFU/mL when only beige-pigmented bacteria were considered. For higher counts, R2A remained Poisson, but kits exhibited over-dispersion. Both kits undercounted relative to R2A, but the degree of undercounting was reasonably stable. Kits did not grow pink-pigmented bacteria from dental-unit water identified as Methylobacterium rhodesianum. Only one of the test kits provided results with adequate reliability at higher bacterial concentrations. Undercount bias could be estimated for this device and used to adjust test kit results. Insensitivity to methylobacteria spp. is problematic.
Generic Schemes for Single-Molecule Kinetics. 2: Information Content of the Poisson Indicator.
Avila, Thomas R; Piephoff, D Evan; Cao, Jianshu
2017-08-24
Recently, we described a pathway analysis technique (paper 1) for analyzing generic schemes for single-molecule kinetics based upon the first-passage time distribution. Here, we employ this method to derive expressions for the Poisson indicator, a normalized measure of stochastic variation (essentially equivalent to the Fano factor and Mandel's Q parameter), for various renewal (i.e., memoryless) enzymatic reactions. We examine its dependence on substrate concentration, without assuming all steps follow Poissonian kinetics. Based upon fitting to the functional forms of the first two waiting time moments, we show that, to second order, the non-Poissonian kinetics are generally underdetermined but can be specified in certain scenarios. For an enzymatic reaction with an arbitrary intermediate topology, we identify a generic minimum of the Poisson indicator as a function of substrate concentration, which can be used to tune substrate concentration to the stochastic fluctuations and to estimate the largest number of underlying consecutive links in a turnover cycle. We identify a local maximum of the Poisson indicator (with respect to substrate concentration) for a renewal process as a signature of competitive binding, either between a substrate and an inhibitor or between multiple substrates. Our analysis explores the rich connections between Poisson indicator measurements and microscopic kinetic mechanisms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gonis, Antonios; Zhang, Xiaoguang
2012-01-01
This is a comment on the paper by Aftab Alam, Brian G. Wilson, and D. D. Johnson [1], proposing the solution of the near-field corrections (NFC s) problem for the Poisson equation for extended, e.g., space filling, charge densities. We point out that the problem considered by the authors can be simply avoided by means of performing certain integrals in a particular order, while their method does not address the genuine problem of NFC s that arises when the solution of the Poisson equation is attempted within multiple scattering theory. We also point out a flaw in their line ofmore » reasoning leading to the expression for the potential inside the bounding sphere of a cell that makes it inapplicable to certain geometries.« less
NASA Astrophysics Data System (ADS)
Gonis, A.; Zhang, X.-G.
2012-09-01
This is a Comment on the paper by Alam, Wilson, and Johnson [Phys. Rev. BPRBMDO1098-012110.1103/PhysRevB.84.205106 84, 205106 (2011)], proposing the solution of the near-field corrections (NFCs) problem for the Poisson equation for extended, e.g., space-filling charge densities. We point out that the problem considered by the authors can be simply avoided by means of performing certain integrals in a particular order, whereas, their method does not address the genuine problem of NFCs that arises when the solution of the Poisson equation is attempted within multiple-scattering theory. We also point out a flaw in their line of reasoning, leading to the expression for the potential inside the bounding sphere of a cell that makes it inapplicable for certain geometries.
The Effectiveness of an Electronic Security Management System in a Privately Owned Apartment Complex
ERIC Educational Resources Information Center
Greenberg, David F.; Roush, Jeffrey B.
2009-01-01
Poisson and negative binomial regression methods are used to analyze the monthly time series data to determine the effects of introducing an integrated security management system including closed-circuit television (CCTV), door alarm monitoring, proximity card access, and emergency call boxes to a large privately-owned complex of apartment…
A spatial scan statistic for compound Poisson data.
Rosychuk, Rhonda J; Chang, Hsing-Ming
2013-12-20
The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits. Copyright © 2013 John Wiley & Sons, Ltd.
Hospitalizations for primary care-sensitive conditions in Pelotas, Brazil: 1998 to 2012.
Costa, Juvenal Soares Dias da; Teixeira, Ana Maria Ferreira Borges; Moraes, Mauricio; Strauch, Eliane Schneider; Silveira, Denise Silva da; Carret, Maria Laura Vidal; Fantinel, Everton
2017-01-01
To verify the hospitalization trend for primary care sensitive-conditions in Pelotas, Rio Grande do Sul, Brazil from 1998 to 2012. An ecological study compared hospitalizations rates of the city of Pelotas with the rest of state of Rio Grande do Sul. Analysis was conducted using direct standardization of rates, coefficients were stratified by sex and the Poisson regression was used. Hospitalizations for sensitive conditions decreased in Pelotas and Rio Grande do Sul. In Pelotas, a 63.8% decrease was detected in the period observed, and there was a 43.1% decrease in the state of Rio Grande do Sul. Poisson regression coefficients showed a decrease of 7% in Pelotas and of 4% in the rest of Rio Grande do Sul each year. During the study period, several changes were introduced in the Brazilian Unified Health System ("Sistema Único de Saúde") that may have influenced the results, including changes in administration, health funding, and a complete reworking of primary care through the creation of the Family Health Strategy program ("Estratégia Saúde da Família").
Cezar-Vaz, Marta Regina; Bonow, Clarice Alves; da Silva, Mara Regina Santos; de Farias, Francisca Lucélia Ribeiro; de Almeida, Marlise Capa Verde
2016-01-01
This study’s objective was to analyze the use of illegal drugs by dockworkers and provide risk communication regarding the use of illegal drugs and test for infectious contagious diseases among dockworkers. This cross-sectional study including an intervention addressed to 232 dockworkers, who were individually interviewed, as well as communication of risk with testing for infectious contagious diseases for 93 dockworkers from a city in the interior of Rio Grande do Sul, Brazil. Poisson regression analysis was used. Twenty-nine workers reported the use of illegal drugs. Poisson regression indicated that being a wharfage worker, smoker, having a high income, and heavier workload increases the prevalence of the use of illegal drugs. During risk communication, two workers were diagnosed with hepatitis B (2.2%), three (3.2%) with hepatitis C, two (2.2%) with syphilis. None of the workers, though, had HIV. This study provides evidence that can motivate further research on the topic and also lead to treatment of individuals to improve work safety, productivity, and the health of workers. PMID:26771625
NASA Astrophysics Data System (ADS)
Winahju, W. S.; Mukarromah, A.; Putri, S.
2015-03-01
Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.
Singer, Donald A.; Menzie, W.D.; Cheng, Qiuming; Bonham-Carter, G. F.
2005-01-01
Estimating numbers of undiscovered mineral deposits is a fundamental part of assessing mineral resources. Some statistical tools can act as guides to low variance, unbiased estimates of the number of deposits. The primary guide is that the estimates must be consistent with the grade and tonnage models. Another statistical guide is the deposit density (i.e., the number of deposits per unit area of permissive rock in well-explored control areas). Preliminary estimates and confidence limits of the number of undiscovered deposits in a tract of given area may be calculated using linear regression and refined using frequency distributions with appropriate parameters. A Poisson distribution leads to estimates having lower relative variances than the regression estimates and implies a random distribution of deposits. Coefficients of variation are used to compare uncertainties of negative binomial, Poisson, or MARK3 empirical distributions that have the same expected number of deposits as the deposit density. Statistical guides presented here allow simple yet robust estimation of the number of undiscovered deposits in permissive terranes.
Cezar-Vaz, Marta Regina; Bonow, Clarice Alves; da Silva, Mara Regina Santos; de Farias, Francisca Lucélia Ribeiro; de Almeida, Marlise Capa Verde
2016-01-12
This study's objective was to analyze the use of illegal drugs by dockworkers and provide risk communication regarding the use of illegal drugs and test for infectious contagious diseases among dockworkers. This cross-sectional study including an intervention addressed to 232 dockworkers, who were individually interviewed, as well as communication of risk with testing for infectious contagious diseases for 93 dockworkers from a city in the interior of Rio Grande do Sul, Brazil. Poisson regression analysis was used. Twenty-nine workers reported the use of illegal drugs. Poisson regression indicated that being a wharfage worker, smoker, having a high income, and heavier workload increases the prevalence of the use of illegal drugs. During risk communication, two workers were diagnosed with hepatitis B (2.2%), three (3.2%) with hepatitis C, two (2.2%) with syphilis. None of the workers, though, had HIV. This study provides evidence that can motivate further research on the topic and also lead to treatment of individuals to improve work safety, productivity, and the health of workers.
Gene regulation and noise reduction by coupling of stochastic processes
NASA Astrophysics Data System (ADS)
Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Gene regulation and noise reduction by coupling of stochastic processes
Hornos, José Eduardo M.; Reinitz, John
2015-01-01
Here we characterize the low noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the the two gene states depends on protein number. This fact has a very important implication: there exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction. PMID:25768447
Gene regulation and noise reduction by coupling of stochastic processes.
Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso
2016-01-01
ABSTRACT Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process. IMPORTANCE We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation. PMID:27940547
Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso; Koseki, Shigenobu
2017-02-15
Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process. We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation. Copyright © 2017 Koyama et al.
Effect of Air Pollution on Exacerbations of Bronchiectasis in Badalona, Spain, 2008-2016.
Garcia-Olivé, Ignasi; Stojanovic, Zoran; Radua, Joaquim; Rodriguez-Pons, Laura; Martinez-Rivera, Carlos; Ruiz Manzano, Juan
2018-05-17
Air pollution has been widely associated with respiratory diseases. Nevertheless, the association between air pollution and exacerbations of bronchiectasis has been less studied. To analyze the effect of air pollution on exacerbations of bronchiectasis. This was a retrospective observational study conducted in Badalona. The number of daily hospital admissions and emergency room visits related to exacerbation of bronchiectasis (ICD-9 code 494.1) between 2008 and 2016 was obtained. We used simple Poisson regressions to test the effects of daily mean temperature, SO2, NO2, CO, and PM10 levels on bronchiectasis-related emergencies and hospitalizations on the same day and 1-4 days after. All p values were corrected for multiple comparisons. SO2 was significantly associated with an increase in the number of hospitalizations (lags 0, 1, 2, and 3). None of these associations remained significant after correcting for multiple comparisons. The number of emergency room visits was associated with higher levels of SO2 (lags 0-4). After correcting for multiple comparisons, the association between emergency room visits and SO2 levels was statistically significant for lag 0 (p = 0.043), lag 1 (p = 0.018), and lag 3 (p = 0.050). The number of emergency room visits for exacerbation of bronchiectasis is associated with higher levels of SO2. © 2018 S. Karger AG, Basel.
Pinheiro, Samya de Lara Lins de Araujo; Saldiva, Paulo Hilário Nascimento; Schwartz, Joel; Zanobetti, Antonella
2014-12-01
OBJECTIVE To analyze the effect of air pollution and temperature on mortality due to cardiovascular and respiratory diseases. METHODS We evaluated the isolated and synergistic effects of temperature and particulate matter with aerodynamic diameter < 10 µm (PM10) on the mortality of individuals > 40 years old due to cardiovascular disease and that of individuals > 60 years old due to respiratory diseases in Sao Paulo, SP, Southeastern Brazil, between 1998 and 2008. Three methodologies were used to evaluate the isolated association: time-series analysis using Poisson regression model, bidirectional case-crossover analysis matched by period, and case-crossover analysis matched by the confounding factor, i.e., average temperature or pollutant concentration. The graphical representation of the response surface, generated by the interaction term between these factors added to the Poisson regression model, was interpreted to evaluate the synergistic effect of the risk factors. RESULTS No differences were observed between the results of the case-crossover and time-series analyses. The percentage change in the relative risk of cardiovascular and respiratory mortality was 0.85% (0.45;1.25) and 1.60% (0.74;2.46), respectively, due to an increase of 10 μg/m3 in the PM10 concentration. The pattern of correlation of the temperature with cardiovascular mortality was U-shaped and that with respiratory mortality was J-shaped, indicating an increased relative risk at high temperatures. The values for the interaction term indicated a higher relative risk for cardiovascular and respiratory mortalities at low temperatures and high temperatures, respectively, when the pollution levels reached approximately 60 μg/m3. CONCLUSIONS The positive association standardized in the Poisson regression model for pollutant concentration is not confounded by temperature, and the effect of temperature is not confounded by the pollutant levels in the time-series analysis. The simultaneous exposure to different levels of environmental factors can create synergistic effects that are as disturbing as those caused by extreme concentrations.
Gildea, Kevin M; Hileman, Christy R; Rogers, Paul; Salazar, Guillermo J; Paskoff, Lawrence N
2018-04-01
Research indicates that first-generation antihistamine usage may impair pilot performance by increasing the likelihood of vestibular illusions, spatial disorientation, and/or cognitive impairment. Second- and third-generation antihistamines generally have fewer impairing side effects and are approved for pilot use. We hypothesized that toxicological findings positive for second- and third-generation antihistamines are less likely to be associated with pilots involved in fatal mishaps than first-generation antihistamines. The evaluated population consisted of 1475 U.S. civil pilots fatally injured between September 30, 2008, and October 1, 2014. Mishap factors evaluated included year, weather conditions, airman rating, recent airman flight time, quarter of year, and time of day. Due to the low prevalence of positive antihistamine findings, a count-based model was selected, which can account for rare outcomes. The means and variances were close for both regression models supporting the assumption that the data follow a Poisson distribution; first-generation antihistamine mishap airmen (N = 582, M = 0.17, S2 = 0.17) with second- and third-generation antihistamine mishap airmen (N = 116, M = 0.20, S2 = 0.18). The data indicate fewer airmen with second- and third-generation antihistamines than first-generation antihistamines in their system are fatally injured while flying in IMC conditions. Whether the lower incidence is a factor of greater usage of first-generation antihistamines versus second- and third-generation antihistamines by the pilot population or fewer deleterious side effects with second- and third-generation antihistamines is unclear. These results engender cautious optimism, but additional research is necessary to determine why these differences exist.Gildea KM, Hileman CR, Rogers P, Salazar GJ, Paskoff LN. The use of a Poisson regression to evaluate antihistamines and fatal aircraft mishaps in instrument meteorological conditions. Aerosp Med Hum Perform. 2018; 89(4):389-395.
Villeneuve, Paul J; Goldberg, Mark S; Krewski, Daniel; Burnett, Richard T; Chen, Yue
2002-11-01
We used Poisson regression methods to examine the relation between temporal changes in the levels of fine particulate air pollution (PM(2.5)) and the risk of mortality among participants of the Harvard Six Cities longitudinal study. Our analyses were based on 1430 deaths that occurred between 1974 and 1991 in a cohort that accumulated 105,714 person-years of follow-up. For each city, indices of PM(2.5) were derived using daily samples. Individual level data were collected on several risk factors including: smoking, education, body mass index (BMI), and occupational exposure to dusts. Time-dependent indices of PM(2.5) were created across 13 calendar periods (< 1979, 1979, 1980, em leader, 1989, >/= 1990) to explore whether recent or chronic exposures were more important predictors of mortality. The relative risk (RR) of mortality calculated using Poisson regression based on average city-specific exposures that remained constant during follow-up was 1.31 [95% confidence interval (CI) = 1.12-1.52] per 18.6 microg/m(3) of PM(2.5). This result was similar to the risk calculated using the Cox model (RR = 1.26, 95% CI = 1.08-1.46). The RR of mortality was attenuated when the Poisson regression model included a time-dependent estimate of exposure (RR = 1.19, 95% CI = 1.04-1.36). There was little variation in RR across time-dependent indices of PM(2.5). The attenuated risk of mortality that was observed with a time-dependent index of PM(2.5) is due to the combined influence of city-specific variations in mortality rates and decreasing levels of air pollution that occurred during follow-up. The RR of mortality associated with PM(2.5) did not depend on when exposure occurred in relation to death, possibly because of little variation between the time-dependent city-specific exposure indices.
Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method
Zhang, Tingting; Kou, S. C.
2010-01-01
Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure. PMID:21258615
Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method.
Zhang, Tingting; Kou, S C
2010-01-01
Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.
Log-normal frailty models fitted as Poisson generalized linear mixed models.
Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver
2016-12-01
The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Sousa, Clóvis Arlindo de; César, Chester Luiz Galvão; Barros, Marilisa Berti de Azevedo; Carandina, Luana; Goldbaum, Moisés; Marchioni, Dirce Maria Lobo; Fisberg, Regina Mara
2013-02-01
The purpose of this study was to ascertain the prevalence of self-reported leisure-time physical activity and related factors in the city of São Paulo, Brazil, 2008-2009. A population- based cross-sectional study interviewed 2,691 individuals of both sexes, 12 years or older. A two-stage cluster (census tract, household) random sample provided data using home interviews in 2008 and 2009. Leisure-time physical activity was measured with IPAQ, long version. Complex sample-adjusted descriptive statistics provided prevalence estimates, chi-square tests screened associations, and prevalence ratios (PR) expressed effects. Multiple Poisson regression was used to ascertain adjusted effects, and design effects were calculated. Of the interviewees, 16.4% (95%CI: 14.3-18.7) reported leisure-time physical activity. The findings indicate the importance of encouraging leisure-time physical activity, which was associated with male sex, higher income, younger age (12 to 29 years), not smoking, and not reporting frequent fatigue.
Choi, Sunha H
2012-04-01
This study tested a healthy immigrant effect (HIE) and postimmigration health status changes among late life immigrants. Using three waves of the Second Longitudinal Study of Aging (1994-2000) and the linked mortality file through 2006, this study compared (a) chronic health conditions, (b) longitudinal trajectories of self-rated health, (c) longitudinal trajectories of functional impairments, and (d) mortality between three groups (age 70+): (i) late life immigrants with less than 15 years in the United States (n = 133), (ii) longer term immigrants (n = 672), and (iii) U.S.-born individuals (n = 8,642). Logistic and Poisson regression, hierarchical generalized linear modeling, and survival analyses were conducted. Late life immigrants were less likely to suffer from cancer, had lower numbers of chronic conditions at baseline, and displayed lower hazards of mortality during the 12-year follow-up. However, their self-rated health and functional status were worse than those of their counterparts over time. A HIE was only partially supported among older adults.
Potential impacts of climate variability on respiratory morbidity in children, infants, and adults.
Souza, Amaury de; Fernandes, Widinei Alves; Pavão, Hamilton Germano; Lastoria, Giancarlo; Albrez, Edilce do Amaral
2012-01-01
To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R² = 68.4%), infants (R² = 71.8%), and adults (R² = 81.8%). Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study.
Theory of multicolor lattice gas - A cellular automaton Poisson solver
NASA Technical Reports Server (NTRS)
Chen, H.; Matthaeus, W. H.; Klein, L. W.
1990-01-01
The present class of models for cellular automata involving a quiescent hydrodynamic lattice gas with multiple-valued passive labels termed 'colors', the lattice collisions change individual particle colors while preserving net color. The rigorous proofs of the multicolor lattice gases' essential features are rendered more tractable by an equivalent subparticle representation in which the color is represented by underlying two-state 'spins'. Schemes for the introduction of Dirichlet and Neumann boundary conditions are described, and two illustrative numerical test cases are used to verify the theory. The lattice gas model is equivalent to a Poisson equation solution.
Vlasov Simulation of Mixing in Antihydrogen Formation
NASA Astrophysics Data System (ADS)
So, Chukman; Fajans, Joel; Friedland, Lazar; Wurtele, Jonathan; Alpha Collaboration
2011-10-01
In the ALPHA apparatus, low temperature antiprotons (p) and positrons (e+) are prepared adjacent to each other in a nested Penning trap. To create trappable antihydrogen (H), the two species must be mixed such that some resultant H atoms have sub-Kelvin kinetic energy. A new simulation has been developed to study and optimize the autoresonant mixing, in ALPHA. The p dynamics are governed by their own self- field, the e+ plasma field, and the external fields. The e+ 's are handled quasi-statically with a Poisson-Boltzmann solver. p 's are handled by multiple time dependent 1D Vlasov-Poisson solvers, each representing a radial slice of the plasma. The 1D simulatiuons couple through the 2D Poisson equation. We neglect radial transport due to the strong solenoidal field. The advantages and disadvantages of different descretization schemes, comparisons of simulation with experiment, and techniques for optimizing mixing, will be presented.
Occurrence of Conotruncal Heart Birth Defects in Texas: A Comparison of Urban/Rural Classifications
ERIC Educational Resources Information Center
Langlois, Peter H.; Jandle, Leigh; Scheuerle, Angela; Horel, Scott A.; Carozza, Susan E.
2010-01-01
Purpose: (1) Determine if there is an association between 3 conotruncal heart birth defects and urban/rural residence of mother. (2) Compare results using different methods of measuring urban/rural status. Methods: Data were taken from the Texas Birth Defects Registry, 1999-2003. Poisson regression was used to compare crude and adjusted birth…
Stagnation in Mortality Decline among Elders in the Netherlands
ERIC Educational Resources Information Center
Janssen, Fanny; Nusselder, Wilma J.; Looman, Caspar W. N.; Mackenbach, Johan P.; Kunst, Anton E.
2003-01-01
Purpose: This study assesses whether the stagnation of old-age (80+) mortality decline observed in The Netherlands in the 1980s continued in the 1990s and determines which factors contributed to this stagnation. Emphasis is on the role of smoking. Design and Methods: Poisson regression analysis with linear splines was applied to total and…
Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements
Wang, Liming; Huang, Jiaji; Yuan, Xin; ...
2015-09-17
The measurement matrix employed in compressive sensing typically cannot be known precisely a priori and must be estimated via calibration. One may take multiple compressive measurements, from which the measurement matrix and underlying signals may be estimated jointly. This is of interest as well when the measurement matrix may change as a function of the details of what is measured. This problem has been considered recently for Gaussian measurement noise, and here we develop this idea with application to Poisson systems. A collaborative maximum likelihood algorithm and alternating proximal gradient algorithm are proposed, and associated theoretical performance guarantees are establishedmore » based on newly derived concentration-of-measure results. A Bayesian model is then introduced, to improve flexibility and generality. Connections between the maximum likelihood methods and the Bayesian model are developed, and example results are presented for a real compressive X-ray imaging system.« less
Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan
2017-01-01
Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926
Oliveira, André; Cabral, António J R; Mendes, Jorge M; Martins, Maria R O; Cabral, Pedro
2015-11-04
Stroke risk has been shown to display varying patterns of geographic distribution amongst countries but also between regions of the same country. Traditionally a disease of older persons, a global 25% increase in incidence instead was noticed between 1990 and 2010 in persons aged 20-≤64 years, particularly in low- and medium-income countries. Understanding spatial disparities in the association between socioeconomic factors and stroke is critical to target public health initiatives aiming to mitigate or prevent this disease, including in younger persons. We aimed to identify socioeconomic determinants of geographic disparities of stroke risk in people <65 years old, in municipalities of mainland Portugal, and the spatiotemporal variation of the association between these determinants and stroke risk during two study periods (1992-1996 and 2002-2006). Poisson and negative binomial global regression models were used to explore determinants of disease risk. Geographically weighted regression (GWR) represents a distinctive approach, allowing estimation of local regression coefficients. Models for both study periods were identified. Significant variables included education attainment, work hours per week and unemployment. Local Poisson GWR models achieved the best fit and evidenced spatially varying regression coefficients. Spatiotemporal inequalities were observed in significant variables, with dissimilarities between men and women. This study contributes to a better understanding of the relationship between stroke and socioeconomic factors in the population <65 years of age, one age group seldom analysed separately. It can thus help to improve the targeting of public health initiatives, even more in a context of economic crisis.
Coincidence and covariance data acquisition in photoelectron and -ion spectroscopy. I. Formal theory
NASA Astrophysics Data System (ADS)
Mikosch, Jochen; Patchkovskii, Serguei
2013-10-01
We derive a formal theory of noisy Poisson processes with multiple outcomes. We obtain simple, compact expressions for the probability distribution function of arbitrarily complex composite events and its moments. We illustrate the utility of the theory by analyzing properties of coincidence and covariance photoelectron-photoion detection involving single-ionization events. The results and techniques introduced in this work are directly applicable to more general coincidence and covariance experiments, including multiple ionization and multiple-ion fragmentation pathways.
Evaluation of Shiryaev-Roberts procedure for on-line environmental radiation monitoring.
Watson, Mara M; Seliman, Ayman F; Bliznyuk, Valery N; DeVol, Timothy A
2018-04-30
Water can become contaminated as a result of a leak from a nuclear facility, such as a waste facility, or from clandestine nuclear activity. Low-level on-line radiation monitoring is needed to detect these events in real time. A Bayesian control chart method, Shiryaev-Roberts (SR) procedure, was compared with classical methods, 3-σ and cumulative sum (CUSUM), for quantifying an accumulating signal from an extractive scintillating resin flow-cell detection system. Solutions containing 0.10-5.0 Bq/L of 99 Tc, as T99cO 4 - were pumped through a flow cell packed with extractive scintillating resin used in conjunction with a Beta-RAM Model 5 HPLC detector. While T99cO 4 - accumulated on the resin, time series data were collected. Control chart methods were applied to the data using statistical algorithms developed in MATLAB. SR charts were constructed using Poisson (Poisson SR) and Gaussian (Gaussian SR) probability distributions of count data to estimate the likelihood ratio. Poisson and Gaussian SR charts required less volume of radioactive solution at a fixed concentration to exceed the control limit in most cases than 3-σ and CUSUM control charts, particularly solutions with lower activity. SR is thus the ideal control chart for low-level on-line radiation monitoring. Once the control limit was exceeded, activity concentrations were estimated from the SR control chart using the control chart slope on a semi-logarithmic plot. A linear regression fit was applied to averaged slope data for five activity concentration groupings for Poisson and Gaussian SR control charts. A correlation coefficient (R 2 ) of 0.77 for Poisson SR and 0.90 for Gaussian SR suggest this method will adequately estimate activity concentration for an unknown solution. Copyright © 2018 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Azziz-Baumgartner, Eduardo; McKeown, Loreta; Melvin, Patrice; Dang, Quynh; Reed, Joan
2011-01-01
To describe the epidemiology of intimate partner violence (IPV) homicide in Massachusetts, an IPV mortality data set developed by the Massachusetts Department of Public Health was analyzed. The rates of death were estimated by dividing the number of decedents over the aged-matched population and Poisson regression was used to estimate the…
Growth Curve Models for Zero-Inflated Count Data: An Application to Smoking Behavior
ERIC Educational Resources Information Center
Liu, Hui; Powers, Daniel A.
2007-01-01
This article applies growth curve models to longitudinal count data characterized by an excess of zero counts. We discuss a zero-inflated Poisson regression model for longitudinal data in which the impact of covariates on the initial counts and the rate of change in counts over time is the focus of inference. Basic growth curve models using a…
Bulka, Catherine; Nastoupil, Loretta J; Koff, Jean L; Bernal-Mizrachi, Leon; Ward, Kevin C; Williams, Jessica N; Bayakly, A Rana; Switchenko, Jeffrey M; Waller, Lance A; Flowers, Christopher R
2016-10-01
Examining the spatial patterns of diffuse large B-cell lymphoma (DLBCL) incidence and residential proximity to toxic release locations may provide insight regarding environmental and sociodemographic risk factors. We linked and geocoded cancer incidence data for the period 1999-2008 from the Georgia Comprehensive Cancer Registry with population data from the US Census and the Environmental Protection Agency's Toxics Release Inventory. We conducted cluster analyses and constructed Poisson regression models to assess DLBCL incidence as a function of mean distance to the toxic release sites. In total, 3851 incident DLBCL cases occurred among adults residing in Georgia between 1999 and 2008. Significant focal clustering was observed around 57% of ethylene oxide sites, 5% of benzene sites, 9% of tetrachloroethylene sites, 7% of styrene sites, 10% of formaldehyde sites, 5% of trichloroethylene sites, and 10% of all release sites. Mean distance to sites was significantly associated with DLBCL risk for all chemicals. Proximity to Toxics Release Inventory sites can be linked to increased DLBCL risk as assessed through focal clustering and Poisson regression, and confirmatory studies using geospatial mapping can aid in further specifying risk factors for DLBCL.
Association between large strongyle genera in larval cultures--using rare-event poisson regression.
Cao, X; Vidyashankar, A N; Nielsen, M K
2013-09-01
Decades of intensive anthelmintic treatment has caused equine large strongyles to become quite rare, while the cyathostomins have developed resistance to several drug classes. The larval culture has been associated with low to moderate negative predictive values for detecting Strongylus vulgaris infection. It is unknown whether detection of other large strongyle species can be statistically associated with presence of S. vulgaris. This remains a statistical challenge because of the rare occurrence of large strongyle species. This study used a modified Poisson regression to analyse a dataset for associations between S. vulgaris infection and simultaneous occurrence of Strongylus edentatus and Triodontophorus spp. In 663 horses on 42 Danish farms, the individual prevalences of S. vulgaris, S. edentatus and Triodontophorus spp. were 12%, 3% and 12%, respectively. Both S. edentatus and Triodontophorus spp. were significantly associated with S. vulgaris infection with relative risks above 1. Further, S. edentatus was associated with use of selective therapy on the farms, as well as negatively associated with anthelmintic treatment carried out within 6 months prior to the study. The findings illustrate that occurrence of S. vulgaris in larval cultures can be interpreted as indicative of other large strongyles being likely to be present.
REJEKI, Dwi Sarwani Sri; NURHAYATI, Nunung; AJI, Budi; MURHANDARWATI, E. Elsa Herdiana; KUSNANTO, Hari
2018-01-01
Background: Climatic and weather factors become important determinants of vector-borne diseases transmission like malaria. This study aimed to prove relationships between weather factors with considering human migration and previous case findings and malaria cases in endemic areas in Purworejo during 2005–2014. Methods: This study employed ecological time series analysis by using monthly data. The independent variables were the maximum temperature, minimum temperature, maximum humidity, minimum humidity, precipitation, human migration, and previous malaria cases, while the dependent variable was positive malaria cases. Three models of count data regression analysis i.e. Poisson model, quasi-Poisson model, and negative binomial model were applied to measure the relationship. The least Akaike Information Criteria (AIC) value was also performed to find the best model. Negative binomial regression analysis was considered as the best model. Results: The model showed that humidity (lag 2), precipitation (lag 3), precipitation (lag 12), migration (lag1) and previous malaria cases (lag 12) had a significant relationship with malaria cases. Conclusion: Weather, migration and previous malaria cases factors need to be considered as prominent indicators for the increase of malaria case projection. PMID:29900134
Factors associated with poor balance ability in older adults of nine high-altitude communities.
Urrunaga-Pastor, Diego; Moncada-Mapelli, Enrique; Runzer-Colmenares, Fernando M; Bailon-Valdez, Zaira; Samper-Ternent, Rafael; Rodriguez-Mañas, Leocadio; Parodi, Jose F
Poor balance ability in older adults result in multiple complications. Poor balance ability has not been studied among older adults living at high altitudes. In this study, we analysed factors associated with poor balance ability by using the Functional Reach (FR) among older adults living in nine high-altitude communities. Analytical cross-sectional study, carried out in inhabitants aged 60 or over from nine high-altitude Andean communities of Peru during 2013-2016. FR was divided according to the cut-off point of 8 inches (20.32 cm) and two groups were generated: poor balance ability (FR less or equal than 20.32 cm) and good balance ability (greater than 20.32 cm). Additionally, we collected socio-demographic, medical, functional and cognitive assessment information. Poisson regression models were constructed to identify factors associated with poor balance ability. Prevalence ratio (PR) with 95% confidence intervals (95CI%) are presented. A total of 365 older adults were studied. The average age was 73.0 ± 6.9 years (range: 60-91 years), and 180 (49.3%) participants had poor balance ability. In the adjusted Poisson regression analysis, the factors associated with poor balance ability were: alcohol consumption (PR = 1.35; 95%CI: 1.05-1.73), exhaustion (PR = 2.22; 95%CI: 1.49-3.31), gait speed (PR = 0.67; 95%CI: 0.50-0.90), having had at least one fall in the last year (PR = 2.03; 95%CI: 1.19-3.46), having at least one comorbidity (PR = 1.60; 95%CI: 1.10-2.35) and having two or more comorbidities (PR = 1.61; 95%CI: 1.07-2.42) compared to none. Approximately a half of the older adults from these high-altitude communities had poor balance ability. Interventions need to be designed to target these balance issues and prevent adverse events from concurring to these individuals. Copyright © 2018 Elsevier B.V. All rights reserved.
Stanton, Michelle C; Bockarie, Moses J; Kelly-Hope, Louise A
2013-01-01
Vector control, including the use of bed nets, is recommended as a possible strategy for eliminating lymphatic filariasis (LF) in post-conflict countries such as the Democratic Republic of Congo (DRC). This study examined the geographical factors that influence bed net ownership in DRC in order to identify hard-to-reach communities that need to be better targeted. In particular, urban/rural differences and the influence of population density, proximity to cities and health facilities, plus access to major transport networks were investigated. Demographic and Health Survey geo-referenced cluster level data were used to map bed net coverage (proportion of households with at least one of any type of bed net or at least one insecticide-treated net (ITN)), and ITN density (ITNs per person) for 260 clusters. Bivariate and multiple logistic or Poisson regression analyses were used to determine significant relationships. Overall, bed net (30%) and ITN (9%) coverage were very low with significant differences found between urban and rural clusters. In rural clusters, ITN coverage/density was positively correlated with population density (r = 0.25, 0.27 respectively, p<0.01), and negatively with the distance to the two largest cities, Kinshasa or Lubumbashi (r = -0.28, -0.30 respectively, p<0.0001). Further, ownership was significantly negatively correlated with distance to primary national roads and railways (all three measures), distance to main rivers (any bed net only) and distance to the nearest health facility (ITNs only). Logistic and Poisson regression models fitted to the rural cluster data indicated that, after controlling for measured covariates, ownership levels in the Bas-Congo province close to Kinshasa were much larger than that of other provinces. This was most noticeable when considering ITN coverage (odds ratio: 5.3, 95% CI: 3.67-7.70). This analysis provides key insights into the barriers of bed net ownership, which will help inform both LF and malaria bed net distribution campaigns as part of an integrated vector management strategy.
Correlates of current transactional sex among a sample of female exotic dancers in Baltimore, MD.
Reuben, Jacqueline; Serio-Chapman, Chris; Welsh, Christopher; Matens, Richard; Sherman, Susan G
2011-04-01
Transactional sex work, broadly defined as the exchange of money, drugs, or goods for sexual services, occurs in a wide range of environments. There is a large body of research characterizing the risks and harms associated with street- and venue-based sex work, but there is a dearth of research characterizing the risk associated with the environment of exotic dance clubs. The current study aimed to: (1) characterize the nature of female exotic dancers' sex- and drug-related risk behaviors, (2) to examine the role of the club environment in these behaviors, and (3) to examine correlates of currently exchanging sex. From June 2008 to February 2009, we conducted a cross-sectional study among women who were aged 18 years or older and reported exotic dancing within the past 3 months (n = 98). The survey ascertained socio-demographic characteristics, personal health, medical history, sexual practices, drug use, and employment at clubs on the block. Bivariate and multivariate Poisson regression with robust variance was used to identify correlates of current sex exchange. Participants were a median of 24 years old, and were 58% white; 43% had not completed high school. Seventy-four percent reported ever having been arrested. Twenty-six percent reported having injected heroin and 29% reported having smoked crack in the past 3 months. Fifty-seven percent reported using drugs in the club in the past 3 months. Sixty-one percent had ever engaged in transactional sex, and 67% of those did so for the first time after beginning to dance. Forty-three percent reported selling any sex in the club in the past 3 months. In multiple Poisson regression, factors associated with current sex exchange included: race, ever having been arrested, and using drugs in the club. High levels of both drug use and transactional sex among this sample of exotic dancers were reported. These findings indicate that there are a number of drug- and sex-related harms faced by exotic dancers in strip clubs, implicating the environment in the promotion of HIV/STI risk-taking behaviors. Prevention and intervention programs targeting this population are needed to reduce the harms faced by exotic dancers in this environment.
Stanton, Michelle C.; Bockarie, Moses J.; Kelly-Hope, Louise A.
2013-01-01
Vector control, including the use of bed nets, is recommended as a possible strategy for eliminating lymphatic filariasis (LF) in post-conflict countries such as the Democratic Republic of Congo (DRC). This study examined the geographical factors that influence bed net ownership in DRC in order to identify hard-to-reach communities that need to be better targeted. In particular, urban/rural differences and the influence of population density, proximity to cities and health facilities, plus access to major transport networks were investigated. Demographic and Health Survey geo-referenced cluster level data were used to map bed net coverage (proportion of households with at least one of any type of bed net or at least one insecticide-treated net (ITN)), and ITN density (ITNs per person) for 260 clusters. Bivariate and multiple logistic or Poisson regression analyses were used to determine significant relationships. Overall, bed net (30%) and ITN (9%) coverage were very low with significant differences found between urban and rural clusters. In rural clusters, ITN coverage/density was positively correlated with population density (r = 0.25, 0.27 respectively, p<0.01), and negatively with the distance to the two largest cities, Kinshasa or Lubumbashi (r = −0.28, −0.30 respectively, p<0.0001). Further, ownership was significantly negatively correlated with distance to primary national roads and railways (all three measures), distance to main rivers (any bed net only) and distance to the nearest health facility (ITNs only). Logistic and Poisson regression models fitted to the rural cluster data indicated that, after controlling for measured covariates, ownership levels in the Bas-Congo province close to Kinshasa were much larger than that of other provinces. This was most noticeable when considering ITN coverage (odds ratio: 5.3, 95% CI: 3.67–7.70). This analysis provides key insights into the barriers of bed net ownership, which will help inform both LF and malaria bed net distribution campaigns as part of an integrated vector management strategy. PMID:23308281
Fedeli, Ugo; Zorzi, Manuel; Urso, Emanuele D L; Gennaro, Nicola; Dei Tos, Angelo P; Saugo, Mario
2015-11-15
Colorectal cancer (CRC) screening programs based on the fecal immunochemical test (FIT) were found to reduce overall CRC surgery rates, but to the authors' knowledge data by subsite are lacking. The objective of the current study was to assess the impact of FIT-based screening on proximal and distal CRC surgical resection rates. The Veneto region in Italy can be subdivided into 3 areas with staggered introduction of FIT-based screening programs: early (2002-2004), intermediate (2005-2007), and late (2008-2009) areas. Time series of proximal and distal CRC surgery were investigated in the 3 populations between 2001 and 2012 by Joinpoint regression analysis and segmented Poisson regression models. The impact of screening was similar in the study populations. Rates of distal CRC surgical resection were stable before screening, increased at the time of screening implementation (rate ratio [RR], 1.25; 95% confidence interval [95% CI], 1.14-1.37), and thereafter declined by 10% annually (RR, 0.90; 95% CI, 0.88-0.92). Rates of proximal CRC surgical resection increased by 4% annually before screening (RR, 1.04; 95% CI, 1.03-1.05) but, after a peak at the time of screening initiation, the trend was reversed. The percentage represented by proximal CRC surgery rose from 28% in 2001 to 41% in 2012. In this natural multiple-baseline experiment, consistent findings across each time series demonstrated that FIT-based screening programs have an impact both on proximal and distal CRC surgery rates. However, underlying preexisting epidemiological trends are leading to a rapidly increasing percentage of proximal CRC. © 2015 American Cancer Society.
Sheikh, Mashhood Ahmed; Abelsen, Birgit; Olsen, Jan Abel
2017-11-01
Previous methods for assessing mediation assume no multiplicative interactions. The inverse odds weighting (IOW) approach has been presented as a method that can be used even when interactions exist. The substantive aim of this study was to assess the indirect effect of education on health and well-being via four indicators of adult socioeconomic status (SES): income, management position, occupational hierarchy position and subjective social status. 8516 men and women from the Tromsø Study (Norway) were followed for 17 years. Education was measured at age 25-74 years, while SES and health and well-being were measured at age 42-91 years. Natural direct and indirect effects (NIE) were estimated using weighted Poisson regression models with IOW. Stata code is provided that makes it easy to assess mediation in any multiple imputed dataset with multiple mediators and interactions. Low education was associated with lower SES. Consequently, low SES was associated with being unhealthy and having a low level of well-being. The effect (NIE) of education on health and well-being is mediated by income, management position, occupational hierarchy position and subjective social status. This study contributes to the literature on mediation analysis, as well as the literature on the importance of education for health-related quality of life and subjective well-being. The influence of education on health and well-being had different pathways in this Norwegian sample. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Berlin, Conny; Blanch, Carles; Lewis, David J; Maladorno, Dionigi D; Michel, Christiane; Petrin, Michael; Sarp, Severine; Close, Philippe
2012-06-01
The detection of safety signals with medicines is an essential activity to protect public health. Despite widespread acceptance, it is unclear whether recently applied statistical algorithms provide enhanced performance characteristics when compared with traditional systems. Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application (Empirica™ Signal System [ESS]). ESS uses two algorithms for routine analyses: empirical Bayes Multi-item Gamma Poisson Shrinker and logistic regression (LR). A model was developed comprising 14 medicines, categorized as "new" or "established." A standard was prepared on the basis of safety findings selected from traditional sources. ESS results were compared with the standard to calculate the positive predictive value (PPV), specificity, and sensitivity. PPVs of the lower one-sided 5% and 0.05% confidence limits of the Bayes geometric mean (EB05) and of the LR odds ratio (LR0005) almost coincided for all the drug-event combinations studied. There was no obvious difference comparing the PPV of the leading Medical Dictionary for Regulatory Activities (MedDRA) terms to the PPV for all terms. The PPV of narrow MedDRA query searches was higher than that for broad searches. The widely used threshold value of EB05 = 2.0 or LR0005 = 2.0 together with more than three spontaneous reports of the drug-event combination produced balanced results for PPV, sensitivity, and specificity. Consequently, performance characteristics were best for leading terms with narrow MedDRA query searches irrespective of applying Multi-item Gamma Poisson Shrinker or LR at a threshold value of 2.0. This research formed the basis for the configuration of ESS for signal detection at Novartis. Copyright © 2011 John Wiley & Sons, Ltd.
Neighborhood education inequality and drinking behavior.
Lê, Félice; Ahern, Jennifer; Galea, Sandro
2010-11-01
The neighborhood distribution of education (education inequality) may influence substance use among neighborhood residents. Using data from the New York Social Environment Study (conducted in 2005; n=4000), we examined the associations of neighborhood education inequality (measured using Gini coefficients of education) with alcohol use prevalence and levels of alcohol consumption among alcohol users. Analyses were adjusted for neighborhood education level, income level and income inequality, as well as for individual demographic and socioeconomic characteristics and history of drinking prior to residence in the current neighborhood. Neighborhood social norms about drinking were examined as a possible mediator. In adjusted generalized estimating equation regression models, one-standard-deviation-higher education inequality was associated with 1.18 times higher odds of alcohol use (logistic regression odds ratio=1.18, 95% confidence interval 1.08-1.30) but 0.79 times lower average daily alcohol consumption among alcohol users (Poisson regression relative rate=0.79, 95% confidence interval 0.68-0.92). The results tended to differ in magnitude depending on respondents' individual educational levels. There was no evidence that these associations were mediated by social drinking norms, although norms did vary with education inequality. Our results provide further evidence of a relation between education inequality and drinking behavior while illustrating the importance of considering different drinking outcomes and heterogeneity between neighborhood subgroups. Future research could fruitfully consider other potential mechanisms, such as alcohol availability or the role of stress; research that considers multiple mechanisms and their combined effects may be most informative. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Abrahams, M-R; Anderson, J A; Giorgi, E E; Seoighe, C; Mlisana, K; Ping, L-H; Athreya, G S; Treurnicht, F K; Keele, B F; Wood, N; Salazar-Gonzalez, J F; Bhattacharya, T; Chu, H; Hoffman, I; Galvin, S; Mapanje, C; Kazembe, P; Thebus, R; Fiscus, S; Hide, W; Cohen, M S; Karim, S Abdool; Haynes, B F; Shaw, G M; Hahn, B H; Korber, B T; Swanstrom, R; Williamson, C
2009-04-01
Identifying the specific genetic characteristics of successfully transmitted variants may prove central to the development of effective vaccine and microbicide interventions. Although human immunodeficiency virus transmission is associated with a population bottleneck, the extent to which different factors influence the diversity of transmitted viruses is unclear. We estimate here the number of transmitted variants in 69 heterosexual men and women with primary subtype C infections. From 1,505 env sequences obtained using a single genome amplification approach we show that 78% of infections involved single variant transmission and 22% involved multiple variant transmissions (median of 3). We found evidence for mutations selected for cytotoxic-T-lymphocyte or antibody escape and a high prevalence of recombination in individuals infected with multiple variants representing another potential escape pathway in these individuals. In a combined analysis of 171 subtype B and C transmission events, we found that infection with more than one variant does not follow a Poisson distribution, indicating that transmission of individual virions cannot be seen as independent events, each occurring with low probability. While most transmissions resulted from a single infectious unit, multiple variant transmissions represent a significant fraction of transmission events, suggesting that there may be important mechanistic differences between these groups that are not yet understood.
Muñoz, M Pilar; Soldevila, Núria; Martínez, Anna; Carmona, Glòria; Batalla, Joan; Acosta, Lesly M; Domínguez, Angela
2011-07-12
The objective of this work was to study the behaviour of influenza with respect to morbidity and all-cause mortality in Catalonia, and their association with influenza vaccination coverage. The study was carried out over 13 influenza seasons, from epidemiological week 40 of 1994 to week 20 of 2007, and included confirmed cases of influenza and all-cause mortality. Two generalized linear models were fitted: influenza-associated morbidity was modelled by Poisson regression and all-cause mortality by negative binomial regression. The seasonal component was modelled with the periodic function formed by the sum of the sinus and cosines. Expected influenza mortality during periods of influenza virus circulation was estimated by Poisson regression and its confidence intervals using the Bootstrap approach. Vaccination coverage was associated with a reduction in influenza-associated morbidity (p<0.001), but not with a reduction in all-cause mortality (p=0.149). In the case of influenza-associated morbidity, an increase of 5% in vaccination coverage represented a reduction of 3% in the incidence rate of influenza. There was a positive association between influenza-associated morbidity and all-cause mortality. Excess mortality attributable to influenza epidemics was estimated as 34.4 (95% CI: 28.4-40.8) weekly deaths. In conclusion, all-cause mortality is a good indicator of influenza surveillance and vaccination coverage is associated with a reduction in influenza-associated morbidity but not with all-cause mortality. Copyright © 2011 Elsevier Ltd. All rights reserved.
Use of ACE-inhibitors and falls in patients with Parkinson's disease.
Laudisio, Alice; Lo Monaco, Maria Rita; Silveri, Maria Caterina; Bentivoglio, Anna Rita; Vetrano, Davide L; Pisciotta, Maria Stella; Brandi, Vincenzo; Bernabei, Roberto; Zuccalà, Giuseppe
2017-05-01
Falls represent a major concern in patients with Parkinson's disease (PD); however, currently acknowledged treatments for PD are not effective in reducing the risk of falling. The aim was to assess the association of use of ACE-inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) with falls among patients with PD. We analysed data of 194 elderly with PD attending a geriatric Day Hospital. Self-reported history of falls that occurred over the last year, as well as use of drugs, including ACEIs and angiotensin II receptor blockers (ARBs) were recorded. The association of the occurrence of any falls with use of ACEIs, and ARBs was assessed by logistic regression analysis. The association between the number of falls and use of ACEIs, and ARBs was assessed according to Poisson regression. In logistic regression, after adjusting for potential confounders, use of ACEIs was associated with a reduced probability of falling over the last year (OR=0.15, 95% CI=0.03-0.81; P=0.028). This association did not vary with blood pressure levels (P for the interaction term=0.528). Also, using Poisson regression, use of ACEIs predicted a reduced number of falls among participants who fell (PR=0.31; 95% CI=0.10-0.94; P=0.039). No association was found between use of ARBs and falls. Our results indicate that use of ACEIs might be independently associated with reduced probability, and a reduced number of falls among patients with PD. Dedicated studies are needed to define the single agents and dosages that might most effectively reduce the risk of falling in clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.
Association between educational level and access to safe abortion in a Brazilian population.
Dias, Tábata Z; Passini, Renato; Duarte, Graciana A; Sousa, Maria H; Faúndes, Aníbal
2015-03-01
To evaluate sociodemographic factors associated with induced abortion. As part of a cross-sectional, descriptive study, 15 800 civil servants from Campinas, Brazil, were invited to complete a self-administered questionnaire about absolutely unwanted pregnancies in January 2010. Bivariate analysis and multivariate Poisson regression analysis were used to explore the associations between induced abortion and sociodemographic characteristics. Overall, 1660 questionnaires were returned. Unwanted pregnancy was reported by 296 (17.8%) respondents, of whom 165 (55.7%) resorted to abortion. Multiple regression analysis showed that college education was the only variable associated with an increased chance of abortion. Among 157 participants who answered questions about the abortion procedure, 97 (61.8%) reported that it had been performed by a physician. Following abortion, 35 (22.9%) of 153 reported that medical care was required and 26 (16.6%) of 157 reported hospitalization, principally those with a lower level of education and those whose abortion had been performed by a nonphysician. Compared with women with a college education, those with a lower education level were less likely to terminate an absolutely unwanted pregnancy and to have an abortion performed by a physician, and they were more likely to have complications. These findings confirm the social inequalities associated with abortion in Brazil. Copyright © 2014 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.
ERIC Educational Resources Information Center
Maxwell, Jane Carlisle; Pullum, Thomas W.
2001-01-01
Applied the capture-recapture model, through a Poisson regression to a time series of data for admissions to treatment from 1987 to 1996 to estimate the number of heroin addicts in Texas who are "at-risk" for treatment. The entire data set produced estimates that were lower and more plausible than those produced by drawing samples,…
Predicting Hospital Admissions With Poisson Regression Analysis
2009-06-01
East and Four West. Four East is where bariatric , general, neurologic, otolaryngology (ENT), ophthalmologic, orthopedic, and plastic surgery ...where care is provided for cardiovascular, thoracic, and vascular surgery patients. Figure 1 shows a bar graph for each unit, giving the proportion of...provided at NMCSD, or a study could be conducted on the amount of time that patients generally wait for elective surgeries . There is also the
Lord, Dominique
2006-07-01
There has been considerable research conducted on the development of statistical models for predicting crashes on highway facilities. Despite numerous advancements made for improving the estimation tools of statistical models, the most common probabilistic structure used for modeling motor vehicle crashes remains the traditional Poisson and Poisson-gamma (or Negative Binomial) distribution; when crash data exhibit over-dispersion, the Poisson-gamma model is usually the model of choice most favored by transportation safety modelers. Crash data collected for safety studies often have the unusual attributes of being characterized by low sample mean values. Studies have shown that the goodness-of-fit of statistical models produced from such datasets can be significantly affected. This issue has been defined as the "low mean problem" (LMP). Despite recent developments on methods to circumvent the LMP and test the goodness-of-fit of models developed using such datasets, no work has so far examined how the LMP affects the fixed dispersion parameter of Poisson-gamma models used for modeling motor vehicle crashes. The dispersion parameter plays an important role in many types of safety studies and should, therefore, be reliably estimated. The primary objective of this research project was to verify whether the LMP affects the estimation of the dispersion parameter and, if it is, to determine the magnitude of the problem. The secondary objective consisted of determining the effects of an unreliably estimated dispersion parameter on common analyses performed in highway safety studies. To accomplish the objectives of the study, a series of Poisson-gamma distributions were simulated using different values describing the mean, the dispersion parameter, and the sample size. Three estimators commonly used by transportation safety modelers for estimating the dispersion parameter of Poisson-gamma models were evaluated: the method of moments, the weighted regression, and the maximum likelihood method. In an attempt to complement the outcome of the simulation study, Poisson-gamma models were fitted to crash data collected in Toronto, Ont. characterized by a low sample mean and small sample size. The study shows that a low sample mean combined with a small sample size can seriously affect the estimation of the dispersion parameter, no matter which estimator is used within the estimation process. The probability the dispersion parameter becomes unreliably estimated increases significantly as the sample mean and sample size decrease. Consequently, the results show that an unreliably estimated dispersion parameter can significantly undermine empirical Bayes (EB) estimates as well as the estimation of confidence intervals for the gamma mean and predicted response. The paper ends with recommendations about minimizing the likelihood of producing Poisson-gamma models with an unreliable dispersion parameter for modeling motor vehicle crashes.
Trend in frequency of extreme precipitation events over Ontario from ensembles of multiple GCMs
NASA Astrophysics Data System (ADS)
Deng, Ziwang; Qiu, Xin; Liu, Jinliang; Madras, Neal; Wang, Xiaogang; Zhu, Huaiping
2016-05-01
As one of the most important extreme weather event types, extreme precipitation events have significant impacts on human and natural environment. This study assesses the projected long term trends in frequency of occurrence of extreme precipitation events represented by heavy precipitation days, very heavy precipitation days, very wet days and extreme wet days over Ontario, based on results of 21 CMIP3 GCM runs. To achieve this goal, first, all model data are linearly interpolated onto 682 grid points (0.45° × 0.45°) in Ontario; Next, biases in model daily precipitation amount are corrected with a local intensity scaling method to make the total wet days and total wet day precipitation from each of the GCMs are consistent with that from the climate forecast system reanalysis data, and then the four indices are estimated for each of the 21 GCM runs for 1968-2000, 2046-2065 and 2081-2100. After that, with the assumption that the rate parameter of the Poisson process for the occurrence of extreme precipitation events may vary with time as climate changes, the Poisson regression model which expresses the log rate as a linear function of time is used to detect the trend in frequency of extreme events in the GCMs simulations; Finally, the trends and their uncertainty are estimated. The result shows that in the twenty-first century annual heavy precipitation days, very heavy precipitation days and very wet days and extreme wet days are likely to significantly increase over major parts of Ontario and particularly heavy precipitation days, very wet days are very likely to significantly increase in some sub-regions in eastern Ontario. However, trends of seasonal indices are not significant.
Performance and capacity analysis of Poisson photon-counting based Iter-PIC OCDMA systems.
Li, Lingbin; Zhou, Xiaolin; Zhang, Rong; Zhang, Dingchen; Hanzo, Lajos
2013-11-04
In this paper, an iterative parallel interference cancellation (Iter-PIC) technique is developed for optical code-division multiple-access (OCDMA) systems relying on shot-noise limited Poisson photon-counting reception. The novel semi-analytical tool of extrinsic information transfer (EXIT) charts is used for analysing both the bit error rate (BER) performance as well as the channel capacity of these systems and the results are verified by Monte Carlo simulations. The proposed Iter-PIC OCDMA system is capable of achieving two orders of magnitude BER improvements and a 0.1 nats of capacity improvement over the conventional chip-level OCDMA systems at a coding rate of 1/10.
Gilbert, Paul A; Perreira, Krista; Eng, Eugenia; Rhodes, Scott D
2014-09-01
We sought to quantify the association of social stressors with alcohol use among immigrant sexual and gender minority Latinos in North Carolina (n = 190). We modeled any drinking in past year using logistic regression and heavy episodic drinking in past 30 days using Poisson regression. Despite a large proportion of abstainers, there were indications of hazardous drinking. Among current drinkers, 63% reported at least one heavy drinking episode in past 30 days. Ethnic discrimination increased, and social support decreased, odds of any drinking in past year. Social support moderated the associations of English use and ethnic discrimination with heavy episodic drinking.
Ivers, Rebecca; Senserrick, Teresa; Boufous, Soufiane; Stevenson, Mark; Chen, Huei-Yang; Woodward, Mark; Norton, Robyn
2009-09-01
We explored the risky driving behaviors and risk perceptions of a cohort of young novice drivers and sought to determine their associations with crash risk. Provisional drivers aged 17 to 24 (n = 20 822) completed a detailed questionnaire that included measures of risk perception and behaviors; 2 years following recruitment, survey data were linked to licensing and police-reported crash data. Poisson regression models that adjusted for multiple confounders were created to explore crash risk. High scores on questionnaire items for risky driving were associated with a 50% increased crash risk (adjusted relative risk = 1.51; 95% confidence interval = 1.25, 1.81). High scores for risk perception (poorer perceptions of safety) were also associated with increased crash risk in univariate and multivariate models; however, significance was not sustained after adjustment for risky driving. The overrepresentation of youths in crashes involving casualties is a significant public health issue. Risky driving behavior is strongly linked to crash risk among young drivers and overrides the importance of risk perceptions. Systemwide intervention, including licensing reform, is warranted.
Silveira, Erika Aparecida; Ferreira, Carla Cristina da Conceição; Pagotto, Valéria; Santos, Annelisa Silva E Alves de Carvalho; Velasquez-Melendez, Gustavo
2017-05-06
The purpose of this study was to investigate whether sitting height-to-stature ratio (SHSR) is associated with total and central obesity in the elderly. This was a cross-sectional study with 133 noninstitutionalized elderly. High SHSR (≥ 1SD above the mean) was used as a marker of undernutrition (MU) in early life. Poisson's multiple regression was used to determine the association between variables. The prevalence of high SHSR was 21.0%, total obesity 43.6% and central obesity 50.4%. Elderly with high SHSR presented a statistically significant association with total obesity (PR 1.50; 95% CI 1.04-2.18) and central obesity (PR 1.42; 95% CI 1.03-1.95) after adjustment for sex, age, educational level and income in the multivariate analysis. The occurrence of total and central obesity in the elderly was associated with a MU in early life. This result indicates that nutritional deficiencies in childhood may increase the risk of obesity in the elderly, a nutritional paradox. © 2017 Wiley Periodicals, Inc.
Factors associated with hookah use initiation among adolescents.
Reveles, Caroline C; Segri, Neuber J; Botelho, Clovis
2013-01-01
to determine the prevalence and to analyze factors associated with hookah use initiation among adolescents. This was a cross-sectional study, in which questionnaires were collected from 495 students attending public and private schools of the urban area of the city of Várzea Grande, in the state of Mato Grosso, Brazil. Data were analyzed through descriptive, bivariate, and multiple Poisson regression analyses. A total of 19.7% students had tried a hookah. The use of hookah was associated with the final period of adolescence [PR=6.54 (2.79, 15.32)]; enrollment in private schools [PR=2.23 (1.73, 2.88)]; and presence of work activities [PR=1.80 (1.17, 2.78)]. The proportion of adolescents that had tried a hookah was high. The influence of age, work activities, and class period on smoking initiation using the hookah was observed. Preventive measures encompassing all forms of tobacco smoking should be targeted at adolescents in the school environment, aiming at tobacco use control. Copyright © 2013 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.
Borges, Carolina Marques; Cascaes, Andreia Morales; Fischer, Tatiana Konrad; Boing, Antonio Fernando; Peres, Marco Aurélio; Peres, Karen Glazer
2008-08-01
The aim of this study was to estimate the prevalence of dental and gingival pain and associated factors among Brazilian adolescents (15-19 years of age). Data from 16,126 adolescents who participated in the Brazilian Oral Health Survey SB-Brazil 2002-2003 were used. The outcome measured was dental and gingival pain in the last six months. Independent variables were per capita income, schooling, school enrollment, gender, skin color, age, area of residence, time since last dental appointment, type of dental service, DMFT index and its components, dental calculus, and Dental Aesthetic Index. Simple and multiple Poisson regression analyses were performed. Prevalence of dental and gingival pain was 35.6% (95%CI: 34.8-36.4). Increased prevalence of pain was associated with: female gender, low income, non-students, students enrolled in public schools, and grade-for-age lag. In addition, adolescents with high levels of dental caries and dental calculus also reported higher prevalence of dental pain. Dental and gingival pain can be considered a relevant public health problem, suggesting the need for preventive measures.
Women with HIV: gender violence and suicidal ideation
Ceccon, Roger Flores; Meneghel, Stela Nazareth; Hirakata, Vania Naomi
2014-01-01
OBJECTIVE To analyze the relationship between gender violence and suicidal ideation in women with HIV. METHODS A cross-sectional study with 161 users of specialized HIV/AIDS care services. The study investigated the presence of gender violence through the Brazilian version of the World Health Organization Violence against Women instrument, and suicidal ideation through the Suicidal Ideation Questionnaire. Statistical analyses were performed with the SPSS software, using the Chi-square test and Poisson multiple regression model. RESULTS Eighty-two women with HIV reported suicidal ideation (50.0%), 78 (95.0%) of who had suffered gender violence. Age at first sexual intercourse < 15 years old, high number of children, poverty, living with HIV for long, and presence of violence were statistically associated with suicidal ideation. Women who suffered gender violence showed 5.7 times more risk of manifesting suicidal ideation. CONCLUSIONS Women with HIV showed a high prevalence to gender violence and suicidal ideation. Understanding the relationship between these two grievances may contribute to the comprehensive care of these women and implementation of actions to prevent violence and suicide. PMID:25372166
Nunes, Ana Paula de Oliveira Barbosa; Luiz, Olinda do Carmo; Barros, Marilisa Berti Azevedo; Cesar, Chester Luis Galvão; Goldbaum, Moisés
2015-08-01
This study aimed to estimate the prevalence of physical activity in different domains and the association with schooling, using a serial cross-sectional population-based design comparing data from two editions of a health survey in the city of São Paulo, Brazil. Participation included 1,667 adults in 2003 and 2,086 in 2008. Probabilistic sampling was performed by two-stage clusters. The long version of International Physical Activity Questionnaire (IPAQ) allowed evaluating multiple domains of physical activity. Poisson regression was used. Men were more active in their leisure time and at work and women in the home. Schooling was associated directly with leisure-time activity (2003 and 2008) and inversely with work-related physical activity (2003) for men and for women in housework. The studies showed that Brazilians with less schooling are becoming less active, so that intervention strategies should consider different educational levels. Interventions in the urban space and transportation can increase the opportunities for physical activity and broaden access by the population.
Silva, Etna Kaliane Pereira da; Medeiros, Danielle Souto de; Martins, Poliana Cardoso; Sousa, Líllian de Almeida; Lima, Gislane Pereira; Rêgo, Maria Amanda Sousa; Silva, Tainan Oliveira da; Freire, Alessandra Silva; Silva, Fernanda Moitinho
2017-06-01
This study aimed to measure the prevalence of food insecurity in a rural area of Northeast Brazil and investigate this outcome according to residence in quilombola communities (descendants of African slaves) versus non-quilombola communities. This was a cross-sectional study in 21 rural communities, 9 of which quilombolas, in 2014, using the Brazilian Food Insecurity Scale (EBIA). Prevalence rates and prevalence ratios were estimated for food insecurity, and Poisson multiple regression analysis with robust variance was performed. Food insecurity was found in 52.1% of the families: 64.9% in quilombola communities and 42% in the others. Food insecurity was associated with belonging to a quilombola community (PR = 1.25), lower economic status (PR = 1.89; 2.98, and 3.22 for status C2, D, and E, respectively), beneficiaries of Bolsa Família program (PR = 1.52), and four or more household members (PR = 1.20). Food insecurity prevalence was high in the entire population, but it was even higher in quilombola communities, even though they belonged to the same coverage area. The results emphasize this population's vulnerability.
Silveira, Erika Aparecida; Martins, Bruna Bittar; de Abreu, Laísa Ribeiro Silva; Cardoso, Camila Kellen de Souza
2015-12-01
The scope of the study was to evaluate the prevalence of daily consumption of fruit, vegetables and greens by the elderly and its association with sociodemographic, lifestyle, morbidity and hospitalization variables. The study was part of the multiple-stage sampling cross-sectional research entitled the Goiânia Elderly Project (Projeto Idosos Goiânia). 416 elderly people were interviewed in their homes. Multivariate analysis was conducted using Poisson regression to analyze statistical associations. P values of <.05 were considered statistically significant. Daily consumption of fruit, vegetables and greens was 16.6%: fruit accounted for 44%, vegetables 39.7% and greens 32.5%. Factors statistically associated with daily consumption of fruits and vegetables were female sex, age between 70 and 79, higher education level, social class A/B and C, alcohol consumption, use of sweeteners, regular physical activity during leisure time, abdominal obesity and hospitalization. Public policies to promote health should develop strategies that encourage adequate intake of fruit, vegetables and greens among the elderly, since regular consumption of same can improve quality of life and prevent/control diseases.
Cavalcante, Nádia Carenina Nunes; Simões, Vanda Maria Ferreira; Ribeiro, Marizélia Rodrigues Costa; Lamy-Filho, Fernando; Barbieri, Marco Antonio; Bettiol, Heloisa; Silva, Antônio Augusto Moura da
2017-01-01
Several studies have identified social inequalities in low birth weight (LBW), preterm birth (PTB), and intrauterine growth restriction (IUGR), which, in recent years, have diminished or disappeared in certain locations. Estimate the LBW, PTB, and IUGR rates in São Luís, Maranhão, Brazil, in 2010, and check for associations between socioeconomic factors and these indicators. This study is based on a birth cohort performed in São Luís. It included 5,051 singleton hospital births in 2010. The chi-square test was used for proportion comparisons, while simple and multiple Poisson regression models with robust error variance were used to estimate relative risks. LBW, PTB and IUGR rates were 7.5, 12.2, and 10.3% respectively. LBW was higher in low-income families, while PTB and IUGR were not associated with socioeconomic factors. The absence or weak association of these indicators with social inequality point to improvements in health care and/or in social conditions in São Luís.
Association between prolonged breast-feeding and early childhood caries: a hierarchical approach.
Nunes, Ana Margarida Melo; Alves, Claudia Maria Coelho; Borba de Araújo, Fernando; Ortiz, Tânia Mara Lopes; Ribeiro, Marizélia Rodrigues Costa; Silva, Antônio Augusto Moura da; Ribeiro, Cecília Claudia Costa
2012-12-01
This study was conducted to investigate the association between prolonged breastfeeding and early childhood caries(ECC) with adjustment for important confounders, using hieraschical approach. This retrospective cohort study involved 260 low-income children (18-42 months). The number of decayed teeth was used as a measure of caries. Following a theoretical framework, the hierarchical model was built in a forward fashion, by adding the following levels in succession: level 1: age; level 2: social variables; level 3: health variables; level 4: behavioral variables; level 5: oral hygiene-related variables; level 6: oral hygiene quality measured by visible plaque; and level 7: contamination by mutans streptococci. Sequential forward multiple Poisson regression analysis was employed. Breast-feeding was not a risk factor for ECC after adjustment for some confounders (incidence density ratio, 1.15; 95% confidence interval, 0.84-1.59, P = 0.363). Prolonged breast-feeding was not a risk factor for ECC while age, high sucrose comption between main meals and the quality of oral higiene were associated with disease in children. © 2012 John Wiley & Sons A/S.
Angiogenic Signaling in Living Breast Tumor Models
2007-06-01
Poisson distributed random noise is added in an amount relative to the desired signal to noise ratio. We fit the data using a regressive fitting...AD_________________ Award Number: W81XWH-05-1-0396 TITLE: Angiogenic Signaling in Living Breast...CONTRACT NUMBER Angiogenic Signaling in Living Breast Tumor Models 5b. GRANT NUMBER W81XWH-05-1-0396 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d
ERIC Educational Resources Information Center
You, Jianing; Leung, Freedom
2012-01-01
This study used zero-inflated poisson regression analysis to examine the role of depressive symptoms, family invalidation, and behavioral impulsivity in the occurrence and repetition of non-suicidal self-injury among Chinese community adolescents over a 2-year period. Participants, 4782 high school students, were assessed twice during the…
Long-term sickness absence during pregnancy and the gender balance of workplaces.
Melsom, Anne M
2014-11-01
This study addresses how the gender composition of workplaces affects pregnant women's sickness absence. It also assesses whether an observed association may be explaine by differential selection to female- or male-dominated workplaces. The analyses are based on Norwegian registry data from 2003-2011. Using Poisson regressions with detailed control for occupational categories, I examine whether the number of absence days are associated with the proportion of females at the workplace. I address possible selection effects by Poisson regressions with fixed individual effects using only within-individual variation on women with two or more pregnancies during the time window. The analyses indicate a positive and significant relationship between the female proportion in workplaces and sickness absence rates during pregnancy. Analyses limited to within-individual variation also show positive and significant effects of similar strength, indicating that the observed relationship is not due to differential selection of absence-prone pregnant workers to female-dominated workplaces. The proportion of female individuals at workplaces is positively associated with sickness absence rates during pregnancy this association is not likely explained by occupational nor individual characteristics the results are consistent with absence culture theory and more lenient norms concerning sickness absence during pregnancy at female-dominated workplaces. © 2014 the Nordic Societies of Public Health.
Anonymous birth law saves babies--optimization, sustainability and public awareness.
Grylli, Chryssa; Brockington, Ian; Fiala, Christian; Huscsava, Mercedes; Waldhoer, Thomas; Klier, Claudia M
2016-04-01
The aims of this study are to assess the impact of Austria's anonymous birth law from the time relevant statistical records are available and to evaluate the use of hatches versus anonymous hospital delivery. This study is a complete census of police-reported neonaticides (1975-2012) as well as anonymous births including baby hatches in Austria during 2002-2012. The time trends of neonaticide rates, anonymous births and baby hatches were analysed by means of Poisson and logistic regression model. Predicted and observed rates were derived and compared using a Bayesian Poisson regression model. Predicted numbers of neonaticides for the period of the active awareness campaign, 2002-2004, were more than three times larger than the observed number (p = 0.0067). Of the 365 women who benefitted from this legislation, only 11.5% chose to put their babies in a baby hatch. Since the law was introduced, a significant decreasing tendency of numbers of anonymous births (p = 047) was observed, while there was significant increase of neonaticide rates (p = 0.0001). The implementation of the anonymous delivery law is associated with a decrease in the number of police-reported neonaticides. The subsequent significantly decreasing numbers of anonymous births with an accompanying increase of neonaticides represents additional evidence for the effectiveness of the measure.
Spatial distribution of psychotic disorders in an urban area of France: an ecological study.
Pignon, Baptiste; Schürhoff, Franck; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Saba, Ghassen; Leboyer, Marion; Kirkbride, James B; Szöke, Andrei
2016-05-18
Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux's model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02-1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation.
Le Strat, Yann
2017-01-01
The objective of this paper is to evaluate a panel of statistical algorithms for temporal outbreak detection. Based on a large dataset of simulated weekly surveillance time series, we performed a systematic assessment of 21 statistical algorithms, 19 implemented in the R package surveillance and two other methods. We estimated false positive rate (FPR), probability of detection (POD), probability of detection during the first week, sensitivity, specificity, negative and positive predictive values and F1-measure for each detection method. Then, to identify the factors associated with these performance measures, we ran multivariate Poisson regression models adjusted for the characteristics of the simulated time series (trend, seasonality, dispersion, outbreak sizes, etc.). The FPR ranged from 0.7% to 59.9% and the POD from 43.3% to 88.7%. Some methods had a very high specificity, up to 99.4%, but a low sensitivity. Methods with a high sensitivity (up to 79.5%) had a low specificity. All methods had a high negative predictive value, over 94%, while positive predictive values ranged from 6.5% to 68.4%. Multivariate Poisson regression models showed that performance measures were strongly influenced by the characteristics of time series. Past or current outbreak size and duration strongly influenced detection performances. PMID:28715489
Ergodicity-breaking bifurcations and tunneling in hyperbolic transport models
NASA Astrophysics Data System (ADS)
Giona, M.; Brasiello, A.; Crescitelli, S.
2015-11-01
One of the main differences between parabolic transport, associated with Langevin equations driven by Wiener processes, and hyperbolic models related to generalized Kac equations driven by Poisson processes, is the occurrence in the latter of multiple stable invariant densities (Frobenius multiplicity) in certain regions of the parameter space. This phenomenon is associated with the occurrence in linear hyperbolic balance equations of a typical bifurcation, referred to as the ergodicity-breaking bifurcation, the properties of which are thoroughly analyzed.
Zero-Inflated Poisson Modeling of Fall Risk Factors in Community-Dwelling Older Adults.
Jung, Dukyoo; Kang, Younhee; Kim, Mi Young; Ma, Rye-Won; Bhandari, Pratibha
2016-02-01
The aim of this study was to identify risk factors for falls among community-dwelling older adults. The study used a cross-sectional descriptive design. Self-report questionnaires were used to collect data from 658 community-dwelling older adults and were analyzed using logistic and zero-inflated Poisson (ZIP) regression. Perceived health status was a significant factor in the count model, and fall efficacy emerged as a significant predictor in the logistic models. The findings suggest that fall efficacy is important for predicting not only faller and nonfaller status but also fall counts in older adults who may or may not have experienced a previous fall. The fall predictors identified in this study--perceived health status and fall efficacy--indicate the need for fall-prevention programs tailored to address both the physical and psychological issues unique to older adults. © The Author(s) 2014.
Abrahams, M.-R.; Anderson, J. A.; Giorgi, E. E.; Seoighe, C.; Mlisana, K.; Ping, L.-H.; Athreya, G. S.; Treurnicht, F. K.; Keele, B. F.; Wood, N.; Salazar-Gonzalez, J. F.; Bhattacharya, T.; Chu, H.; Hoffman, I.; Galvin, S.; Mapanje, C.; Kazembe, P.; Thebus, R.; Fiscus, S.; Hide, W.; Cohen, M. S.; Karim, S. Abdool; Haynes, B. F.; Shaw, G. M.; Hahn, B. H.; Korber, B. T.; Swanstrom, R.; Williamson, C.
2009-01-01
Identifying the specific genetic characteristics of successfully transmitted variants may prove central to the development of effective vaccine and microbicide interventions. Although human immunodeficiency virus transmission is associated with a population bottleneck, the extent to which different factors influence the diversity of transmitted viruses is unclear. We estimate here the number of transmitted variants in 69 heterosexual men and women with primary subtype C infections. From 1,505 env sequences obtained using a single genome amplification approach we show that 78% of infections involved single variant transmission and 22% involved multiple variant transmissions (median of 3). We found evidence for mutations selected for cytotoxic-T-lymphocyte or antibody escape and a high prevalence of recombination in individuals infected with multiple variants representing another potential escape pathway in these individuals. In a combined analysis of 171 subtype B and C transmission events, we found that infection with more than one variant does not follow a Poisson distribution, indicating that transmission of individual virions cannot be seen as independent events, each occurring with low probability. While most transmissions resulted from a single infectious unit, multiple variant transmissions represent a significant fraction of transmission events, suggesting that there may be important mechanistic differences between these groups that are not yet understood. PMID:19193811
Yang, Tse-Chuan; Shoff, Carla; Matthews, Stephen A
2013-01-01
Based on ecological studies, second demographic transition (SDT) theorists concluded that some areas in the US were in vanguard of the SDT compared to others, implying spatial nonstationarity may be inherent in the SDT process. Linking the SDT to the infant mortality literature, we sought out to answer two related questions: Are the main components of the SDT, specifically marriage postponement, cohabitation, and divorce, associated with infant mortality? If yes, do these associations vary across the US? We applied global Poisson and geographically weighted Poisson regression (GWPR) models, a place-specific analytic approach, to county-level data in the contiguous US. After accounting for the racial/ethnic and socioeconomic compositions of counties and prenatal care utilization, we found (1) marriage postponement was negatively related to infant mortality in the southwestern states, but positively associated with infant mortality in parts of Indiana, Kentucky, and Tennessee, (2) cohabitation rates were positively related to infant mortality, and this relationship was stronger in California, coastal Virginia, and the Carolinas than other areas, and (3) a positive association between divorce rates and infant mortality in southwestern and northeastern areas of the US. These spatial patterns suggested that the associations between the SDT and infant mortality were stronger in the areas in vanguard of the SDT than in others. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the SDT and infant mortality.
A regularization corrected score method for nonlinear regression models with covariate error.
Zucker, David M; Gorfine, Malka; Li, Yi; Tadesse, Mahlet G; Spiegelman, Donna
2013-03-01
Many regression analyses involve explanatory variables that are measured with error, and failing to account for this error is well known to lead to biased point and interval estimates of the regression coefficients. We present here a new general method for adjusting for covariate error. Our method consists of an approximate version of the Stefanski-Nakamura corrected score approach, using the method of regularization to obtain an approximate solution of the relevant integral equation. We develop the theory in the setting of classical likelihood models; this setting covers, for example, linear regression, nonlinear regression, logistic regression, and Poisson regression. The method is extremely general in terms of the types of measurement error models covered, and is a functional method in the sense of not involving assumptions on the distribution of the true covariate. We discuss the theoretical properties of the method and present simulation results in the logistic regression setting (univariate and multivariate). For illustration, we apply the method to data from the Harvard Nurses' Health Study concerning the relationship between physical activity and breast cancer mortality in the period following a diagnosis of breast cancer. Copyright © 2013, The International Biometric Society.
[Factors associated with incidence of dengue in Costa Rica].
Mena, Nelson; Troyo, Adriana; Bonilla-Carrión, Roger; Calderón-Arguedas, Olger
2011-04-01
Determine the extent to which socioeconomic, demographic, geographic, and climate variables affected the incidence of dengue and dengue hemorrhagic fever (D/DH) in Costa Rica during the period 1999-2007. A correlational epidemiologic study was conducted that analyzed the cumulative incidence of D/DH from 1999 to 2007 and its association with different variables in the country's 81 cantons. Information was obtained from secondary sources, and the independent variables used for the analysis were selected on the basis of their representativeness in terms of sociodemographic, environmental, and health coverage factors that affect the epidemiology of D/DH. These variables were divided into four groups of indicators: demographic, socioeconomic, housing, and climate and geographical. The data were analyzed by means of simple and multiple Poisson regressions. The Costa Rican cantons with a higher incidence of D/DH were located primarily near the coast, coinciding with some of the variables studied. Temperature, altitude, and the human poverty index were the most relevant variables in explaining the incidence of D/DH, while temperature was the most significant variable in the multiple analyses. The analyses made it possible to correlate a higher incidence of D/DH with lower-altitude cantons, higher temperature, and a high human poverty index ranking. This information is relevant as a first step toward prioritizing and optimizing actions for the prevention and control of this disease.
Alimohammadian, Masoomeh; Majidi, Azam; Yaseri, Mehdi; Ahmadi, Batoul; Islami, Farhad; Derakhshan, Mohammad; Delavari, Alireza; Amani, Mohammad; Feyz-Sani, Akbar; Poustchi, Hossein; Pourshams, Akram; Sadjadi, Amir Mahdi; Khoshnia, Masoud; Qaravi, Samad; Abnet, Christian C; Dawsey, Sanford; Brennan, Paul; Kamangar, Farin; Boffetta, Paolo; Sadjadi, Alireza; Malekzadeh, Reza
2017-05-09
To investigate the impact of gender on multimorbidity in northern Iran. A cross-sectional analysis of the Golestan cohort data. Golestan Province, Iran. 49 946 residents (age 40-75 years) of Golestan Province, Iran. Researchers collected data related to multimorbidity, defined as co-existence of two or more chronic diseases in an individual, at the beginning of a representative cohort study which recruited its participants from 2004 to 2008. The researchers utilised simple and multiple Poisson regression models with robust variances to examine the simultaneous effects of multiple factors. Women had a 25.0% prevalence of multimorbidity, whereas men had a 13.4% prevalence (p<0.001). Women of all age-groups had a higher prevalence of multimorbidity. Of note, multimorbidity began at a lower age (40-49 years) in women (17.3%) compared with men (8.6%) of the same age (p<0.001). This study identified significant interactions between gender as well as socioeconomic status, ethnicity, physical activity, marital status, education level and smoking (p<0.01). Prevention and control of multimorbidity requires health promotion programmes to increase public awareness about the modifiable risk factors, particularly among women. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Barbosa, João Paulo Dos Anjos Souza; Basso, Luciano; Seabra, André; Prista, Antonio; Tani, Go; Maia, José António Ribeiro; Forjaz, Cláudia Lúcia De Moraes
2016-08-01
Negative associations between physical activity (PA), physical fitness and multiple metabolic risk factors (MMRF) in youths from populations with low PA are reported. The persistence of this association in moderately-to highly active populations is not, however, well established. The aim of the present study was to investigate this association in a Brazilian city with high frequency of active youths. We assessed 122 subjects (9.9 ± 1.3 years) from Muzambinho city. Body mass index, waist circumference, glycaemia, cholesterolaemia, systolic and diastolic blood pressures were measured. Maximal handgrip strength and one-mile walk/run test were used. Leisure time PA was assessed by interview. Poisson regression was used in the analysis. The model explained 11% of the total variance. Only relative muscular strength and one-mile walk/run were statistically significant (p < .05). Those who needed more time to cover the one-mile walk/run test had an increased in metabolic risk of 11%, and those with greater strength reduced the risk by about 82%. In conclusion, children and youths from an active population who need less time to cover the one-mile walk/run test or who had greater muscular strength showed a reduced metabolic risk. These results suggest that even in children and youths with high leisure time PA, a greater aerobic fitness and strength might help to further reduce their MMRF.
Logistic regression for dichotomized counts.
Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W
2016-12-01
Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.
Miglietta, Alessandro; Quinten, Chantal; Lopalco, Pier Luigi; Duffell, Erika
2018-01-01
Hepatitis B prevention in European Union/European Economic Area (EU/EEA) countries relies on vaccination programmes. We describe the epidemiology of acute hepatitis B virus (HBV) at country and EU/EEA level during 2006–2014. Using a multi-level mixed-effects Poisson regression model we assessed differences in the acute HBV infection notification rates between groups of countries that started universal HBV vaccination before/in vs after 1995; implemented or not a catch-up strategy; reached a vaccine coverage ≥ 95% vs < 95% and had a hepatitis B surface antigen prevalence ≥ 1% vs < 1%. Joinpoint regression analysis was used to assess trends by groups of countries, and additional Poisson regression models to evaluate the association between three-dose HBV vaccine coverage and acute HBV infection notification rates at country and EU/EEA level. The EU/EEA acute HBV infection notification rate decreased from 1.6 per 100,000 population in 2006 to 0.7 in 2014. No differences (p > 0.05) were found in the acute HBV infection notification rates between groups of countries, while as vaccine coverage increased, such rates decreased (p < 0.01). Countries with universal HBV vaccination before 1995, a catch-up strategy, and a vaccine coverage ≥ 95% had significant decreasing trends (p < 0.01). Ending HBV transmission in Europe by 2030 will require high vaccine coverage delivered through universal programmes, supported, where appropriate, by catch-up vaccination campaigns. PMID:29439751
Borda, Alfredo; Sanz, Belén; Otero, Laura; Blasco, Teresa; García-Gómez, Francisco J; de Andrés, Fuencisla
2011-01-01
To analyze the association between travel time and participation in a breast cancer screening program adjusted for contextual variables in the province of Segovia (Spain). We performed an ecological study using the following data sources: the Breast Cancer Early Detection Program of the Primary Care Management of Segovia, the Population and Housing Census for 2001 and the municipal register for 2006-2007. The study period comprised January 2006 to December 2007. Dependent variables consisted of the municipal participation rate and the desired level of municipal participation (greater than or equal to 70%). The key independent variable was travel time from the municipality to the mammography unit. Covariables consisted of the municipalities' demographic and socioeconomic factors. We performed univariate and multivariate Poisson regression analyses of the participation rate, and logistic regression of the desired participation level. The sample was composed of 178 municipalities. The mean participation rate was 75.2%. The desired level of participation (≥ 70%) was achieved in 119 municipalities (67%). In the multivariate Poisson and logistic regression analyses, longer travel time was associated with a lower participation rate and with lower participation after adjustment was made for geographic density, age, socioeconomic status and dependency ratio, with a relative risk index of 0.88 (95% CI: 0.81-0.96) and an odds ratio of 0.22 (95% CI: 0.1-0.47), respectively. Travel time to the mammography unit may help to explain participation in breast cancer screening programs. Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.
RECURRENT STROKE IN THE WARFARIN VERSUS ASPIRIN IN REDUCED EJECTION FRACTION (WARCEF) TRIAL
Pullicino, Patrick M.; Qian, Min; Sacco, Ralph L.; Freudenberger, Ron; Graham, Susan; Teerlink, John R.; Mann, Douglas; Di Tullio, Marco R.; Ponikowski, Piotr; Lok, Dirk J.; Anker, Stefan D.; Lip, Gregory Y.H.; Estol, Conrado J.; Levin, Bruce; Mohr, J.P.; Thompson, John L. P.; Homma, Shunichi
2014-01-01
Background and Purpose WARCEF randomized 2305 patients in sinus rhythm with ejection fraction (EF) ≤35% to warfarin (INR 2.0–3.5) or aspirin 325 mg. Warfarin reduced the incident ischemic stroke (IIS) hazard rate by 48% over aspirin in a secondary analysis. The IIS rate in heart failure (HF) is too low to warrant routine anticoagulation but epidemiologic studies show that prior stroke increases the stroke risk in HF. We here explore IIS rates in WARCEF patients with and without baseline stroke to look for risk factors for IIS and determine if a subgroup with an IIS rate high enough to give a clinically relevant stroke risk reduction can be identified. Methods We compared potential stroke risk factors between patients with baseline stroke and those without using the exact conditional score test for Poisson variables. We looked for risk factors for IIS, by comparing IIS rates between different risk factors. For EF we tried cutoff points of 10%, 15% and 20%. 15% was used as it was the highest EF that was associated with a significant increase in IIS rate. IIS and EF strata were balanced as to warfarin/aspirin assignment by the stratified randomized design. A multiple Poisson regression examined the simultaneous effects of all risk factors on IIS rate. IIS rates per hundred patient years (/100PY) were calculated in patient groups with significant risk factors. Missing values were assigned the modal value. Results Twenty of 248 (8.1%) patients with baseline stroke and 64 of 2048 (3.1%) without had IIS. IIS rate in patients with baseline stroke (2.37/100PY) was greater than patients without (0.89/100PY)(rate ratio 2.68, p<0.001). Fourteen of 219 (6.4%) patients with ejection fraction (EF)<15% and 70 of 2079 (3.4%) with EF ≥15% had IIS. In the multiple regression analysis stroke at baseline (p<0.001) and EF<15% vs. ≥15% (p=.005) remained significant predictors of IIS. IIS rate was 2.04/100PY in patients with EF<15% and 0.95/100PY in patients with EF ≥15% (p=0.009). IIS rate in patients with baseline stroke and reduced EF was 5.88/100PY with EF<15% decreasing to 2.62/100PY with EF<30%. Conclusions In a WARCEF exploratory analysis, prior stroke and EF<15% were risk factors for IIS. Further research is needed to determine if a clinically relevant stroke risk reduction is obtainable with warfarin in HF patients with prior stroke and reduced EF. PMID:25300706
2013-06-01
during the design process. For instance, the detector could be calibrated with incoherent il- lumination and a separate calibration could be performed...Poisson dis- tribution is often employed as a statistical distribution for the detected images. How- ever, due to the highly coherent nature of laser
IRT-ZIP Modeling for Multivariate Zero-Inflated Count Data
ERIC Educational Resources Information Center
Wang, Lijuan
2010-01-01
This study introduces an item response theory-zero-inflated Poisson (IRT-ZIP) model to investigate psychometric properties of multiple items and predict individuals' latent trait scores for multivariate zero-inflated count data. In the model, two link functions are used to capture two processes of the zero-inflated count data. Item parameters are…
Lu, Liming; Luo, Gaoquan; Xiao, Fang
2013-08-01
This study aims to assess the quality of reports and their correlates in randomized controlled trials (RCTs) of immunotherapy for Guillain-Barré syndrome (GBS). A search was performed in multiple databases of reports published between April 1992 and November 2012. Reporting quality was assessed by items of the Consolidated Standards of Reporting Trials (CONSORT) 2010 Statement. An overall quality score (OQS) and a key methodological index score (MIS) were calculated for each trial. Factors associated with OQS and MIS were then identified. A total of 19 RCTs were included in the full text. The median OQS was 7.0, with a range of 1-10. However, the quality of reporting in items of 'flow chart' and 'ancillary analyses' was poor with a positive rate of less than 40%. The median MIS was 0 with a range of 0-2. Twelve (63.2%) did not report any of the three key methodological items. Specifically, the mean OQS increased by approximately 2.73 for manuscripts published in the New England Journal of Medicine, The Lancet, Pediatrics and Neurology (95% CI: 0.35-5.12; p < 0.05). Multivariate linear regression and the Poisson regression model could not be presented as the number of included trials was too small. The reporting quality in RCTs on immunotherapy for GBS was poor, which indicated that reporting in RCTs of immunotherapy for GBS needed substantial improvement in order to meet the guideline of the CONSORT Statement.
Krolikowski, Maciej P; Black, Amanda M; Palacios-Derflingher, Luz; Blake, Tracy A; Schneider, Kathryn J; Emery, Carolyn A
2017-02-01
Ice hockey is a popular winter sport in Canada. Concussions account for the greatest proportion of all injuries in youth ice hockey. In 2011, a policy change enforcing "zero tolerance for head contact" was implemented in all leagues in Canada. To determine if the risk of game-related concussions and more severe concussions (ie, resulting in >10 days of time loss) and the mechanisms of a concussion differed for Pee Wee class (ages 11-12 years) and Bantam class (ages 13-14 years) players after the 2011 "zero tolerance for head contact" policy change compared with players in similar divisions before the policy change. Cohort study; Level of evidence, 3. The retrospective cohort included Pee Wee (most elite 70%, 2007-2008; n = 891) and Bantam (most elite 30%, 2008-2009; n = 378) players before the rule change and Pee Wee (2011-2012; n = 588) and Bantam (2011-2012; n = 242) players in the same levels of play after the policy change. Suspected concussions were identified by a team designate and referred to a sport medicine physician for diagnosis. Incidence rate ratios (IRRs) were estimated based on multiple Poisson regression analysis, controlling for clustering by team and other important covariates and offset by game-exposure hours. Incidence rates based on the mechanisms of a concussion were estimated based on univariate Poisson regression analysis. The risk of game-related concussions increased after the head contact rule in Pee Wee (IRR, 1.85; 95% CI, 1.20-2.86) and Bantam (IRR, 2.48; 95% CI, 1.17-5.24) players. The risk of more severe concussions increased after the head contact rule in Pee Wee (IRR, 4.12; 95% CI, 2.00-8.50) and Bantam (IRR, 7.91; 95% CI, 3.13-19.94) players. The rates of concussions due to body checking and direct head contact increased after the rule change. The "zero tolerance for head contact" policy change did not reduce the risk of game-related concussions in Pee Wee or Bantam class ice hockey players. Increased concussion awareness and education after the policy change may have contributed to the increased risk of concussions found after the policy change.
Added sugars and periodontal disease in young adults: an analysis of NHANES III data.
Lula, Estevam C O; Ribeiro, Cecilia C C; Hugo, Fernando N; Alves, Cláudia M C; Silva, Antônio A M
2014-10-01
Added sugar consumption seems to trigger a hyperinflammatory state and may result in visceral adiposity, dyslipidemia, and insulin resistance. These conditions are risk factors for periodontal disease. However, the role of sugar intake in the cause of periodontal disease has not been adequately studied. We evaluated the association between the frequency of added sugar consumption and periodontal disease in young adults by using NHANES III data. Data from 2437 young adults (aged 18-25 y) who participated in NHANES III (1988-1994) were analyzed. We estimated the frequency of added sugar consumption by using food-frequency questionnaire responses. We considered periodontal disease to be present in teeth with bleeding on probing and a probing depth ≥3 mm at one or more sites. We evaluated this outcome as a discrete variable in Poisson regression models and as a categorical variable in multinomial logistic regression models adjusted for sex, age, race-ethnicity, education, poverty-income ratio, tobacco exposure, previous diagnosis of diabetes, and body mass index. A high consumption of added sugars was associated with a greater prevalence of periodontal disease in middle [prevalence ratio (PR): 1.39; 95% CI: 1.02, 1.89] and upper (PR: 1.42; 95% CI: 1.08, 1.85) tertiles of consumption in the adjusted Poisson regression model. The upper tertile of added sugar intake was associated with periodontal disease in ≥2 teeth (PR: 1.73; 95% CI: 1.19, 2.52) but not with periodontal disease in only one tooth (PR: 0.85; 95% CI: 0.54, 1.34) in the adjusted multinomial logistic regression model. A high frequency of consumption of added sugars is associated with periodontal disease, independent of traditional risk factors, suggesting that this consumption pattern may contribute to the systemic inflammation observed in periodontal disease and associated noncommunicable diseases. © 2014 American Society for Nutrition.
A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.
Chen, Li; Wang, Chi; Qin, Zhaohui S; Wu, Hao
2015-06-15
ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. 'peak detection'), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed. In this work, we develop a statistical method to perform quantitative comparison of multiple ChIP-seq datasets and detect genomic regions showing differential protein binding or histone modification. We first detect peaks from all datasets and then union them to form a single set of candidate regions. The read counts from IP experiment at the candidate regions are assumed to follow Poisson distribution. The underlying Poisson rates are modeled as an experiment-specific function of artifacts and biological signals. We then obtain the estimated biological signals and compare them through the hypothesis testing procedure in a linear model framework. Simulations and real data analyses demonstrate that the proposed method provides more accurate and robust results compared with existing ones. An R software package ChIPComp is freely available at http://web1.sph.emory.edu/users/hwu30/software/ChIPComp.html. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Age and the economics of an emergency medical admission-what factors determine costs?
McCabe, J J; Cournane, S; Byrne, D; Conway, R; O'Riordan, D; Silke, B
2017-02-01
The ageing of the population may be anticipated to increase demand on hospital resources. We have investigated the relationship between hospital episode costs and age profile in a single centre. All Emergency Medical admissions (33 732 episodes) to an Irish hospital over a 6-year period, categorized into three age groups, were evaluated against total hospital episode costs. Univariate and adjusted incidence rate ratios (IRRs) were calculated using zero truncated Poisson regression. The total hospital episode cost increased with age ( P < 0.001). The multi-variable Poisson regression model demonstrated that the most important drivers of overall costs were Acute Illness Severity-IRR 1.36 (95% CI: 1.30, 1.41), Sepsis Status -1.46 (95% CI: 1.42, 1.51) and Chronic Disabling Disease Score -1.25 (95% CI: 1.22, 1.27) and the Age Group as exemplified for those 85 years IRR 1.23 (95% CI: 1.15, 1.32). Total hospital episode costs are a product of clinical complexity with contributions from the Acute Illness Severity, Co-Morbidity, Chronic Disabling Disease Score and Sepsis Status. However age is also an important contributor and an increasing patient age profile will have a predictable impact on total hospital episode costs. © The Author 2016. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Redelmeier, Donald A; Tibshirani, Robert J
2018-06-01
To demonstrate analytic approaches for matched studies where two controls are linked to each case and events are accumulating counts rather than binary outcomes. A secondary intent is to clarify the distinction between total risk and excess risk (unmatched vs. matched perspectives). We review past research testing whether elections can lead to increased traffic risks. The results are reinterpreted by analyzing both the total count of individuals in fatal crashes and the excess count of individuals in fatal crashes, each time accounting for the matched double controls. Overall, 1,546 individuals were in fatal crashes on the 10 election days (average = 155/d), and 2,593 individuals were in fatal crashes on the 20 control days (average = 130/d). Poisson regression of total counts yielded a relative risk of 1.19 (95% confidence interval: 1.12-1.27). Poisson regression of excess counts yielded a relative risk of 3.22 (95% confidence interval: 2.72-3.80). The discrepancy between analyses of total counts and excess counts replicated with alternative statistical models and was visualized in graphical displays. Available approaches provide methods for analyzing count data in matched designs with double controls and help clarify the distinction between increases in total risk and increases in excess risk. Copyright © 2018 Elsevier Inc. All rights reserved.
WINPEPI updated: computer programs for epidemiologists, and their teaching potential
2011-01-01
Background The WINPEPI computer programs for epidemiologists are designed for use in practice and research in the health field and as learning or teaching aids. The programs are free, and can be downloaded from the Internet. Numerous additions have been made in recent years. Implementation There are now seven WINPEPI programs: DESCRIBE, for use in descriptive epidemiology; COMPARE2, for use in comparisons of two independent groups or samples; PAIRSetc, for use in comparisons of paired and other matched observations; LOGISTIC, for logistic regression analysis; POISSON, for Poisson regression analysis; WHATIS, a "ready reckoner" utility program; and ETCETERA, for miscellaneous other procedures. The programs now contain 122 modules, each of which provides a number, sometimes a large number, of statistical procedures. The programs are accompanied by a Finder that indicates which modules are appropriate for different purposes. The manuals explain the uses, limitations and applicability of the procedures, and furnish formulae and references. Conclusions WINPEPI is a handy resource for a wide variety of statistical routines used by epidemiologists. Because of its ready availability, portability, ease of use, and versatility, WINPEPI has a considerable potential as a learning and teaching aid, both with respect to practical procedures in the planning and analysis of epidemiological studies, and with respect to important epidemiological concepts. It can also be used as an aid in the teaching of general basic statistics. PMID:21288353
Tuberculosis and the role of war in the modern era.
Drobniewski, F A; Verlander, N Q
2000-12-01
Tuberculosis (TB) remains a major global health problem; historically, major wars have increased TB notifications. This study evaluated whether modern conflicts worldwide affected TB notifications between 1975 and 1995. Dates of conflicts were obtained and matched with national TB notification data reported to the World Health Organization. Overall notification rates were calculated pre and post conflict. Poisson regression analysis was applied to all conflicts with sufficient data for detailed trend analysis. Thirty-six conflicts were identified, for which 3-year population and notification data were obtained. Overall crude TB notification rates were 81.9 and 105.1/100,000 pre and post start of conflict in these countries. Sufficient data existed in 16 countries to apply Poisson regression analysis to model 5-year pre and post start of conflict trends. This analysis indicated that the risk of presenting with TB in any country 2.5 years after the outbreak of conflict relative to 2.5 years before the outbreak was 1.016 (95%CI 0.9435-1.095). The modelling suggested that in the modern era war may not significantly damage efforts to control TB in the long term. This might be due to the limited scale of most of these conflicts compared to the large-scale civilian disruption associated with 'world wars'. The management of TB should be considered in planning post-conflict refugee and reconstruction programmes.
Luck, Tobias; Motzek, Tom; Luppa, Melanie; Matschinger, Herbert; Fleischer, Steffen; Sesselmann, Yves; Roling, Gudrun; Beutner, Katrin; König, Hans-Helmut; Behrens, Johann; Riedel-Heller, Steffi G
2013-01-01
Background Falls in older people are a major public health issue, but the underlying causes are complex. We sought to evaluate the effectiveness of preventive home visits as a multifactorial, individualized strategy to reduce falls in community-dwelling older people. Methods Data were derived from a prospective randomized controlled trial with follow-up examination after 18 months. Two hundred and thirty participants (≥80 years of age) with functional impairment were randomized to intervention and control groups. The intervention group received up to three preventive home visits including risk assessment, home counseling intervention, and a booster session. The control group received no preventive home visits. Structured interviews at baseline and follow-up provided information concerning falls in both study groups. Random-effects Poisson regression evaluated the effect of preventive home visits on the number of falls controlling for covariates. Results Random-effects Poisson regression showed a significant increase in the number of falls between baseline and follow-up in the control group (incidence rate ratio 1.96) and a significant decrease in the intervention group (incidence rate ratio 0.63) controlling for age, sex, family status, level of care, and impairment in activities of daily living. Conclusion Our results indicate that a preventive home visiting program can be effective in reducing falls in community-dwelling older people. PMID:23788832
Using perinatal morbidity scoring tools as a primary study outcome.
Hutcheon, Jennifer A; Bodnar, Lisa M; Platt, Robert W
2017-11-01
Perinatal morbidity scores are tools that score or weight different adverse events according to their relative severity. Perinatal morbidity scores are appealing for maternal-infant health researchers because they provide a way to capture a broad range of adverse events to mother and newborn while recognising that some events are considered more serious than others. However, they have proved difficult to implement as a primary outcome in applied research studies because of challenges in testing if the scores are significantly different between two or more study groups. We outline these challenges and describe a solution, based on Poisson regression, that allows differences in perinatal morbidity scores to be formally evaluated. The approach is illustrated using an existing maternal-neonatal scoring tool, the Adverse Outcome Index, to evaluate the safety of labour and delivery before and after the closure of obstetrical services in small rural communities. Applying the proposed Poisson regression to the case study showed a protective risk ratio for adverse outcome following closures as compared with the original analysis, where no difference was found. This approach opens the door for considerably broader use of perinatal morbidity scoring tools as a primary outcome in applied population and clinical maternal-infant health research studies. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Models for forecasting the flowering of Cornicabra olive groves.
Rojo, Jesús; Pérez-Badia, Rosa
2015-11-01
This study examined the impact of weather-related variables on flowering phenology in the Cornicabra olive tree and constructed models based on linear and Poisson regression to forecast the onset and length of the pre-flowering and flowering phenophases. Spain is the world's leading olive oil producer, and the Cornicabra variety is the second largest Spanish variety in terms of surface area. However, there has been little phenological research into this variety. Phenological observations were made over a 5-year period (2009-2013) at four sampling sites in the province of Toledo (central Spain). Results showed that the onset of the pre-flowering phase is governed largely by temperature, which displayed a positive correlation with the temperature in the start of dormancy (November) and a negative correlation during the months prior to budburst (January, February and March). A similar relationship was recorded for the onset of flowering. Other weather-related variables, including solar radiation and rainfall, also influenced the succession of olive flowering phenophases. Linear models proved the most suitable for forecasting the onset and length of the pre-flowering period and the onset of flowering. The onset and length of pre-flowering can be predicted up to 1 or 2 months prior to budburst, whilst the onset of flowering can be forecast up to 3 months beforehand. By contrast, a nonlinear model using Poisson regression was best suited to predict the length of the flowering period.
Atmospheric pollutants and hospital admissions due to pneumonia in children
Negrisoli, Juliana; Nascimento, Luiz Fernando C.
2013-01-01
OBJECTIVE: To analyze the relationship between exposure to air pollutants and hospitalizations due to pneumonia in children of Sorocaba, São Paulo, Brazil. METHODS: Time series ecological study, from 2007 to 2008. Daily data were obtained from the State Environmental Agency for Pollution Control for particulate matter, nitric oxide, nitrogen dioxide, ozone, besides air temperature and relative humidity. The data concerning pneumonia admissions were collected in the public health system of Sorocaba. Correlations between the variables of interest using Pearson cofficient were calculated. Models with lags from zero to five days after exposure to pollutants were performed to analyze the association between the exposure to environmental pollutants and hospital admissions. The analysis used the generalized linear model of Poisson regression, being significant p<0.05. RESULTS: There were 1,825 admissions for pneumonia, with a daily mean of 2.5±2.1. There was a strong correlation between pollutants and hospital admissions, except for ozone. Regarding the Poisson regression analysis with the multi-pollutant model, only nitrogen dioxide was statistically significant in the same day (relative risk - RR=1.016), as well as particulate matter with a lag of four days (RR=1.009) after exposure to pollutants. CONCLUSIONS: There was an acute effect of exposure to nitrogen dioxide and a later effect of exposure to particulate matter on children hospitalizations for pneumonia in Sorocaba. PMID:24473956
Rice, LaShanta J.; Jiang, Chengsheng; Wilson, Sacoby M.; Burwell-Naney, Kristen; Samantapudi, Ashok; Zhang, Hongmei
2014-01-01
Background: Studies have demonstrated a relationship between segregation and level of education, occupational opportunities, and risk behaviors, yet a paucity of research has elucidated the association between racial residential segregation, socioeconomic deprivation, and lifetime cancer risk. Objectives: We examined estimated lifetime cancer risk from air toxics by racial composition, segregation, and deprivation in census tracts in Metropolitan Charleston. Methods: Segregation indices were used to measure the distribution of groups of people from different races within neighborhoods. The Townsend Index was used to measure economic deprivation in the study area. Poisson multivariate regressions were applied to assess the association of lifetime cancer risk with segregation indices and Townsend Index along with several sociodemographic measures. Results: Lifetime cancer risk from all pollution sources was 28 persons/million for half of the census tracts in Metropolitan Charleston. Isolation Index and Townsend Index both showed significant correlation with lifetime cancer risk from different sources. This significance still holds after adjusting for other sociodemographic measures in a Poisson regression, and these two indices have stronger effect on lifetime cancer risk compared to the effects of sociodemographic measures. Conclusions: We found that material deprivation, measured by the Townsend Index and segregation measured by the Isolation index, introduced high impact on lifetime cancer risk by air toxics at the census tract level. PMID:24852759
Concurrent generation of multivariate mixed data with variables of dissimilar types.
Amatya, Anup; Demirtas, Hakan
2016-01-01
Data sets originating from wide range of research studies are composed of multiple variables that are correlated and of dissimilar types, primarily of count, binary/ordinal and continuous attributes. The present paper builds on the previous works on multivariate data generation and develops a framework for generating multivariate mixed data with a pre-specified correlation matrix. The generated data consist of components that are marginally count, binary, ordinal and continuous, where the count and continuous variables follow the generalized Poisson and normal distributions, respectively. The use of the generalized Poisson distribution provides a flexible mechanism which allows under- and over-dispersed count variables generally encountered in practice. A step-by-step algorithm is provided and its performance is evaluated using simulated and real-data scenarios.
Hurdle models for multilevel zero-inflated data via h-likelihood.
Molas, Marek; Lesaffre, Emmanuel
2010-12-30
Count data often exhibit overdispersion. One type of overdispersion arises when there is an excess of zeros in comparison with the standard Poisson distribution. Zero-inflated Poisson and hurdle models have been proposed to perform a valid likelihood-based analysis to account for the surplus of zeros. Further, data often arise in clustered, longitudinal or multiple-membership settings. The proper analysis needs to reflect the design of a study. Typically random effects are used to account for dependencies in the data. We examine the h-likelihood estimation and inference framework for hurdle models with random effects for complex designs. We extend the h-likelihood procedures to fit hurdle models, thereby extending h-likelihood to truncated distributions. Two applications of the methodology are presented. Copyright © 2010 John Wiley & Sons, Ltd.
Determining X-ray source intensity and confidence bounds in crowded fields
DOE Office of Scientific and Technical Information (OSTI.GOV)
Primini, F. A.; Kashyap, V. L., E-mail: fap@head.cfa.harvard.edu
We present a rigorous description of the general problem of aperture photometry in high-energy astrophysics photon-count images, in which the statistical noise model is Poisson, not Gaussian. We compute the full posterior probability density function for the expected source intensity for various cases of interest, including the important cases in which both source and background apertures contain contributions from the source, and when multiple source apertures partially overlap. A Bayesian approach offers the advantages of allowing one to (1) include explicit prior information on source intensities, (2) propagate posterior distributions as priors for future observations, and (3) use Poisson likelihoods,more » making the treatment valid in the low-counts regime. Elements of this approach have been implemented in the Chandra Source Catalog.« less
Castell, Stefanie; Schwab, Frank; Geffers, Christine; Bongartz, Hannah; Brunkhorst, Frank M.; Gastmeier, Petra; Mikolajczyk, Rafael T.
2014-01-01
Early and appropriate blood culture sampling is recommended as a standard of care for patients with suspected bloodstream infections (BSI) but is rarely taken into account when quality indicators for BSI are evaluated. To date, sampling of about 100 to 200 blood culture sets per 1,000 patient-days is recommended as the target range for blood culture rates. However, the empirical basis of this recommendation is not clear. The aim of the current study was to analyze the association between blood culture rates and observed BSI rates and to derive a reference threshold for blood culture rates in intensive care units (ICUs). This study is based on data from 223 ICUs taking part in the German hospital infection surveillance system. We applied locally weighted regression and segmented Poisson regression to assess the association between blood culture rates and BSI rates. Below 80 to 90 blood culture sets per 1,000 patient-days, observed BSI rates increased with increasing blood culture rates, while there was no further increase above this threshold. Segmented Poisson regression located the threshold at 87 (95% confidence interval, 54 to 120) blood culture sets per 1,000 patient-days. Only one-third of the investigated ICUs displayed blood culture rates above this threshold. We provided empirical justification for a blood culture target threshold in ICUs. In the majority of the studied ICUs, blood culture sampling rates were below this threshold. This suggests that a substantial fraction of BSI cases might remain undetected; reporting observed BSI rates as a quality indicator without sufficiently high blood culture rates might be misleading. PMID:25520442
NASA Astrophysics Data System (ADS)
Ramirez, C.; Nyblade, A.; Emry, E. L.; Julià, J.; Sun, X.; Anandakrishnan, S.; Wiens, D. A.; Aster, R. C.; Huerta, A. D.; Winberry, P.; Wilson, T.
2017-12-01
A uniform set of crustal parameters for seismic stations deployed on rock in West Antarctica and the Transantarctic Mountains (TAM) has been obtained to help elucidate similarities and differences in crustal structure within and between several tectonic blocks that make up these regions. P-wave receiver functions have been analysed using the H-κ stacking method to develop estimates of thickness and bulk Poisson's ratio for the crust, and jointly inverted with surface wave dispersion measurements to obtain depth-dependent shear wave velocity models for the crust and uppermost mantle. The results from 33 stations are reported, including three stations for which no previous results were available. The average crustal thickness is 30 ± 5 km along the TAM front, and 38 ± 2 km in the interior of the mountain range. The average Poisson's ratios for these two regions are 0.25 ± 0.03 and 0.26 ± 0.02, respectively, and they have similar average crustal Vs of 3.7 ± 0.1 km s-1. At multiple stations within the TAM, we observe evidence for mafic layering within or at the base of the crust, which may have resulted from the Ferrar magmatic event. The Ellsworth Mountains have an average crustal thickness of 37 ± 2 km, a Poisson's ratio of 0.27, and average crustal Vs of 3.7 ± 0.1 km s-1, similar to the TAM. This similarity is consistent with interpretations of the Ellsworth Mountains as a tectonically rotated TAM block. The Ross Island region has an average Moho depth of 25 ± 1 km, an average crustal Vs of 3.6 ± 0.1 km s-1 and Poisson's ratio of 0.30, consistent with the mafic Cenozoic volcanism found there and its proximity to the Terror Rift. Marie Byrd Land has an average crustal thickness of 30 ± 2 km, Poisson's ratio of 0.25 ± 0.04 and crustal Vs of 3.7 ± 0.1 km s-1. One station (SILY) in Marie Byrd Land is near an area of recent volcanism and deep (25-40 km) seismicity, and has a high Poisson's ratio, consistent with the presence of partial melt in the crust.
Chen, Yi-Lun; Liu, Yao-Chung; Wu, Chia-Hung; Yeh, Chiu-Mei; Chiu, Hsun-I; Lee, Gin-Yi; Lee, Yu-Ting; Hsu, Pei; Lin, Ting-Wei; Gau, Jyh-Pyng; Hsiao, Liang-Tsai; Chiou, Tzeon-Jye; Liu, Jin-Hwang; Liu, Chia-Jen
2018-04-01
Vertebral fractures affect approximately 30% of myeloma patients and lead to a poor impact on survival and life quality. In general, age and body mass index (BMI) are reported to have an important role in vertebral fractures. However, the triangle relationship among age, BMI, and vertebral fractures is still unclear in newly diagnosed multiple myeloma (NDMM) patients. This study recruited consecutive 394 patients with NDMM at Taipei Veterans General Hospital between January 1, 2005 and December 31, 2015. Risk factors for vertebral fractures in NDMM patients were collected and analyzed. The survival curves were demonstrated using Kaplan-Meier estimate. In total, 301 (76.4%) NDMM patients were enrolled in the cohort. In the median follow-up period of 18.0 months, the median survival duration in those with vertebral fractures ≥ 2 was shorter than those with vertebral fracture < 2 (59.3 vs 28.6 months; P = 0.017). In multivariate Poisson regression, BMI < 18.5 kg/m 2 declared increased vertebral fractures compared with BMI ≥ 24.0 kg/m 2 (adjusted RR, 2.79; 95% CI, 1.44-5.43). In multivariable logistic regression, BMI < 18.5 kg/m 2 was an independent risk factor for vertebral fractures ≥ 2 compared with BMI ≥ 24.0 kg/m 2 (adjusted OR, 6.05; 95% CI, 2.43-15.08). Among age stratifications, patients with both old age and low BMI were at a greater risk suffering from increased vertebral fractures, especially in patients > 75 years and BMI < 18.5 kg/m 2 (adjusted RR, 12.22; 95% CI, 3.02-49.40). This is the first study that demonstrated that age had a significant impact on vertebral fractures in NDMM patients with low BMI. Elder patients with low BMI should consider to routinely receive spinal radiographic examinations and regular follow-up. Copyright © 2017 John Wiley & Sons, Ltd.
Rowe, Christopher; Santos, Glenn-Milo; Vittinghoff, Eric; Wheeler, Eliza; Davidson, Peter; Coffin, Philip O
2015-08-01
To describe characteristics of participants and overdose reversals associated with a community-based naloxone distribution program and identify predictors of obtaining naloxone refills and using naloxone for overdose reversal. Bivariate statistical tests were used to compare characteristics of participants who obtained refills and reported overdose reversals versus those who did not. We fitted multiple logistic regression models to identify predictors of refills and reversals; zero-inflated multiple Poisson regression models were used to identify predictors of number of refills and reversals. San Francisco, California, USA. Naloxone program participants registered and reversals reported from 2010 to 2013. Baseline characteristics of participants and reported characteristics of reversals. A total of 2500 participants were registered and 702 reversals were reported from 2010 to 2013. Participants who had witnessed an overdose [adjusted odds ratio (AOR)=2.02, 95% confidence interval (CI)= 1.53-2.66; AOR = 2.73, 95% CI = 1.73-4.30] or used heroin (AOR = 1.85, 95% CI = 1.44-2.37; AOR = 2.19, 95% CI = 1.54-3.13) or methamphetamine (AOR=1.71, 95% CI=1.37-2.15; AOR=1.61, 95% CI=1.18-2.19) had higher odds of obtaining a refill and reporting a reversal, respectively. African American (AOR = 0.63, 95% CI = 0.45-0.88) and Latino (AOR = 0.65, 95% CI = 0.43-1.00) participants had lower odds of obtaining a naloxone refill, whereas Latino participants who obtained at least one refill reported a higher number of refills [incidence rate ratio (IRR) = 1.33 (1.05-1.69)]. Community naloxone distribution programs are capable of reaching sizeable populations of high-risk individuals and facilitating large numbers of overdose reversals. Community members most likely to engage with a naloxone program and use naloxone to reverse an overdose are active drug users. © 2015 Society for the Study of Addiction.
Simultaneous measurement of the Young's modulus and the Poisson ratio of thin elastic layers.
Gross, Wolfgang; Kress, Holger
2017-02-07
The behavior of cells and tissue is greatly influenced by the mechanical properties of their environment. For studies on the interactions between cells and soft matrices, especially those applying traction force microscopy the characterization of the mechanical properties of thin substrate layers is essential. Various techniques to measure the elastic modulus are available. Methods to accurately measure the Poisson ratio of such substrates are rare and often imply either a combination of multiple techniques or additional equipment which is not needed for the actual biological studies. Here we describe a novel technique to measure both parameters, the Youngs's modulus and the Poisson ratio in a single experiment. The technique requires only a standard inverted epifluorescence microscope. As a model system, we chose cross-linked polyacrylamide and poly-N-isopropylacrylamide hydrogels which are known to obey Hooke's law. We place millimeter-sized steel spheres on the substrates which indent the surface. The data are evaluated using a previously published model which takes finite thickness effects of the substrate layer into account. We demonstrate experimentally for the first time that the application of the model allows the simultaneous determination of both the Young's modulus and the Poisson ratio. Since the method is easy to adapt and comes without the need of special equipment, we envision the technique to become a standard tool for the characterization of substrates for a wide range of investigations of cell and tissue behavior in various mechanical environments as well as other samples, including biological materials.
Normal forms for Poisson maps and symplectic groupoids around Poisson transversals
NASA Astrophysics Data System (ADS)
Frejlich, Pedro; Mărcuț, Ioan
2018-03-01
Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.
Normal forms for Poisson maps and symplectic groupoids around Poisson transversals.
Frejlich, Pedro; Mărcuț, Ioan
2018-01-01
Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.
What are hierarchical models and how do we analyze them?
Royle, Andy
2016-01-01
In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood and Bayesian perspectives. We go through the mechanics of maximizing the likelihood and characterizing the posterior distribution by Markov chain Monte Carlo (MCMC) methods. We give a general perspective on topics such as model selection and assessment of model fit, although we demonstrate these topics in practice in later chapters (especially Chapters 5, 6, 7, and 10 Chapter 5 Chapter 6 Chapter 7 Chapter 10)
Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung
NASA Astrophysics Data System (ADS)
Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani
2017-03-01
Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.
Statistical Analyses of Raw Material Data for MTM45-1/CF7442A-36% RW: CMH Cure Cycle
NASA Technical Reports Server (NTRS)
Coroneos, Rula; Pai, Shantaram, S.; Murthy, Pappu
2013-01-01
This report describes statistical characterization of physical properties of the composite material system MTM45-1/CF7442A, which has been tested and is currently being considered for use on spacecraft structures. This composite system is made of 6K plain weave graphite fibers in a highly toughened resin system. This report summarizes the distribution types and statistical details of the tests and the conditions for the experimental data generated. These distributions will be used in multivariate regression analyses to help determine material and design allowables for similar material systems and to establish a procedure for other material systems. Additionally, these distributions will be used in future probabilistic analyses of spacecraft structures. The specific properties that are characterized are the ultimate strength, modulus, and Poisson??s ratio by using a commercially available statistical package. Results are displayed using graphical and semigraphical methods and are included in the accompanying appendixes.
Trends in abundance of collared lemmings near Cape Churchill, Manitoba, Canada
Reiter, M.E.; Andersen, D.E.
2008-01-01
Regular, multiannual cycles observed in the population abundance of small mammals in many arctic and subarctic ecosystems have stimulated substantial research, particularly among population ecologists. Hypotheses of mechanisms generating regular cycles include predator-prey interactions, limitation of food resources, and migration or dispersal, as well as abiotic factors such as cyclic climatic variation and environmental stochasticity. In 2004 and 2005, we used indirect methods to estimate trends in population size of Richardson's collared lemmings (Dicrostonyx richardsoni) retrospectively, and evaluated the extent of synchrony between lemming populations at 2 coastal tundra study areas separated by approximately 60 km near Cape Churchill, Manitoba, Canada. We collected scars on willow plants (Salix) resulting from lemming feeding. Ages of scars ranged from 0 to 13 years at both study areas. Scar-age frequency appeared cyclic and we used nonlinear Poisson regression to model the observed scar-age frequency. Lemming populations cycled with 2.8-year periodicity and the phase of the cycle was synchronous between the 2 study areas. We suggest that our approach could be applied in multiple settings and may provide the most efficient way to gather data on small mammals across both space and time in a diversity of landscapes. ?? 2008 American Society of Mammalogists.
Martins, Laura B Motta; da Costa-Paiva, Lúcia Helena S; Osis, Maria José D; de Sousa, Maria Helena; Pinto-Neto, Aarão M; Tadini, Valdir
2006-02-01
This study aimed to compare knowledge about STD/AIDS and identify the factors associated with adequate knowledge and consistent use of male condoms in teenagers from public and private schools in the city of São Paulo, Brazil. We selected 1,594 adolescents ranging 12 to 19 years of age in 13 public schools and 5 private schools to complete a questionnaire on knowledge of STD/AIDS and use of male condoms. Prevalence ratios were computed with a 95% confidence interval. The score on STD knowledge used a cutoff point corresponding to 50% of correct answers. Statistical tests were chi-square and Poisson multiple regression. Consistent use of male condoms was 60% in private and 57.1% in public schools (p > 0.05) and was associated with male gender and lower socioeconomic status. Female gender, higher schooling, enrollment in private school, Caucasian race, and being single were associated with higher knowledge of STDs. Teenagers from public and private schools have adequate knowledge of STD prevention, however this does not include the adoption of effective prevention. Educational programs and STD/AIDS awareness-raising should be expanded in order to minimize vulnerability.
Grégori, Gérald; Rajwa, Bartek; Patsekin, Valery; Jones, James; Furuki, Motohiro; Yamamoto, Masanobu; Paul Robinson, J
2014-01-01
Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.
Belon, Ana Paula; da Silveira, Naoko Yanagizawa Jardim; Barros, Marilisa Berti de Azevedo; Baldo, Caroline; da Silva, Marta Maria Alves
2012-09-01
The scope of this study is to analyze the differences in the profile of emergency care for external causes between public and private emergency departments. With data come from VIVA-Campinas 2009, the association between the nature of healthcare and the characteristics of the victims was verified using the chi-square test. Using Poisson regression, proportion ratios of care in the public and private network were estimated. In the sample of 1094 victims, 67.8% were treated by public health. Traffic accidents, animal-related accidents, and assaults were 2 times higher in public units, whereas collisions with objects and sprains were 75% and 2.7 times higher in private units. Cranium-encephalic trauma/polytrauma and cuts/lacerations were 3.8 times and 61% more frequent in public care, while victims with no injuries, with dislocations/sprains or fractures being predominant in private care. Head and multiple organ injuries, road accident and work-related injuries, the use of public transport or mobile emergency care services/ambulances were predominant in public care. Revealing significant differences in care in public and private care can contribute to the organization of healthcare.
Doubova, Svetlana V; Sánchez-García, Sergio; Infante-Castañeda, Claudia; Pérez-Cuevas, Ricardo
2016-09-09
To analyze the factors associated with regular physical exercise and routine consumption of fruits and vegetables, and both healthy behaviors among Mexican older adults. We conducted a secondary data analysis of the baseline data (2014) of the Study on Obesity, Sarcopenia and Fragility in older adults affiliated with the Mexican Institute of Social Security. The study included 948 adults who were ≥60 years of age. Multiple Poisson regression was performed. Routine consumption of fruits and vegetables was reported by 53.8 % of older adults, 42.7 % reported engaging in regular physical exercise and 23.1 % reported participating in both types of healthy behaviors. Women, adults with a stable income, those with a self-perception of good health and those with a history of physical exercise at the age of 50 years had an increased likelihood of engaging in healthy eating and regular physical activity. Many older adults do not routinely consume fruits and vegetables or engage in regular physical exercise despite the fact that most have a fixed income and a social network. It is relevant to conduct research-based interventions that take into account the contextual factors to promote healthy behaviors.
A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation
Wilkinson, Darren J.; Jayathilake, Pahala Gedara; Rushton, Steve P.; Bridgens, Ben; Li, Bowen; Zuliani, Paolo
2018-01-01
We investigate the feasibility of using a surrogate-based method to emulate the deformation and detachment behaviour of a biofilm in response to hydrodynamic shear stress. The influence of shear force, growth rate and viscoelastic parameters on the patterns of growth, structure and resulting shape of microbial biofilms was examined. We develop a statistical modelling approach to this problem, using combination of Bayesian Poisson regression and dynamic linear models for the emulation. We observe that the hydrodynamic shear force affects biofilm deformation in line with some literature. Sensitivity results also showed that the expected number of shear events, shear flow, yield coefficient for heterotrophic bacteria and extracellular polymeric substance (EPS) stiffness per unit EPS mass are the four principal mechanisms governing the bacteria detachment in this study. The sensitivity of the model parameters is temporally dynamic, emphasising the significance of conducting the sensitivity analysis across multiple time points. The surrogate models are shown to perform well, and produced ≈ 480 fold increase in computational efficiency. We conclude that a surrogate-based approach is effective, and resulting biofilm structure is determined primarily by a balance between bacteria growth, viscoelastic parameters and applied shear stress. PMID:29649240
Moderating role of the MAOA genotype in antisocial behaviour.
Fergusson, David M; Boden, Joseph M; Horwood, L John; Miller, Allison; Kennedy, Martin A
2012-02-01
Recent studies have examined gene×environment (G×E) interactions involving the monoamine oxidase A (MAOA) gene in moderating the associations between exposure to adversity and antisocial behaviour. The present study examined a novel method for assessing interactions between a single gene and multiple risk factors related to environmental and personal adversity. To test the hypothesis that the presence of the low-activity MAOA genotype was associated with an increased response to a series of risk factors. Participants were 399 males from the Christchurch Health and Development Study who had complete data on: (a) MAOA promoter region variable number tandem repeat genotype; (b) antisocial behaviour (criminal offending) to age 30 and convictions to age 21; and (c) maternal smoking during pregnancy, IQ, childhood maltreatment and school failure. Poisson regression models were fitted to three antisocial behaviour outcomes (property/violent offending ages 15-30; and convictions ages 17-21), using measures of exposure to adverse childhood circumstances. The analyses revealed consistent evidence of G x E interactions, such that those with the low-activity MAOA variant who were exposed to adversity in childhood were significantly more likely to report offending in late adolescence and early adulthood. The present findings add to the evidence suggesting that there is a stable G x E interaction involving MAOA, a range of adverse environmental and personal factors, and antisocial behaviour across the life course. These analyses also demonstrate the utility of using multiple environmental/personal exposures to test G×E interactions.
Laura, Angelici; Mirko, Piola; Tommaso, Cavalleri; Giorgia, Randi; Francesca, Cortini; Roberto, Bergamaschi; Andrea, Baccarelli A; Alberto, Bertazzi Pier; Cecilia, Pesatori Angela; Valentina, Bollati
2016-01-01
Background Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating disease of the central nervous system, characterized by recurrent relapses of inflammation that cause mild to severe disability. Exposure to airborne particulate matter (PM) has been associated with acute increases in systemic inflammatory responses and neuroinflammation. In the present study, we hypothesize that exposure to PM < 10 µm in diameter (PM10) might increase the occurrence of MS-related hospitalizations. Methods We obtained daily concentrations of PM10 from 53 monitoring sites covering the study area and we identified 8287 MS-related hospitalization through hospital admission-discharge records of the Lombardy region, Italy, between 2001 and 2009. We used a Poisson regression analysis to investigate the association between exposure to PM10 and risk of hospitalization. Results A higher RR of hospital admission for MS relapse was associated with exposure to PM10 at different time intervals. The maximum effect of PM10 on MS hospitalization was found for exposure between days 0 and 7: Hospital admission for MS increased 42% (95%CI 1.39–1.45) on the days preceded by one week with PM10 levels in the highest quartile. The p-value for trend across quartiles was < 0.001. Conclusions These data support the hypothesis that air pollution may have a role in determining MS occurrence and relapses. Our findings could open new avenues for determining the pathogenic mechanisms of MS and potentially be applied to other autoimmune diseases. PMID:26624240
School-Level Correlates of Adolescent Tobacco, Alcohol and Marijuana Use
Hill, Danielle; Mrug, Sylvie
2016-01-01
Background School-level characteristics are related to students’ substance use, but little research systematically examined multiple school characteristics in relation to different types of substance use across grade levels. Objectives This study examines multiple school-level characteristics as correlates of students’ tobacco, alcohol, marijuana, and combined substance use across three grade levels. Methods Students (N = 23,615) from 42 urban and suburban middle schools and 24 high schools in the U.S. reported on their tobacco, alcohol, and marijuana use. Students’ mean age was 14 years; 47% were male, 53% African American and 41% Caucasian. School-level data included poverty, racial composition, academic achievement, student-teacher ratio, absenteeism, and school size. Multilevel logistic and Poisson regressions tested associations between school-level predictors and adolescent substance use in middle school, early high school and late high school. Results School-level poverty, more ethnic minority students, low achievement, and higher absenteeism were related to alcohol, marijuana and combined substance use, particularly at lower grade levels. By contrast, cigarette smoking was more prevalent in more affluent high schools with more White students. After adjusting for other school characteristics, absenteeism emerged as the most consistent predictor of student substance use. Conclusions/Importance Interventions addressing absenteeism and truancy in middle and high schools may help prevent student substance use. Schools serving poor, urban, and mostly minority students may benefit from interventions targeting alcohol and marijuana use, whereas interventions focusing on tobacco use prevention may be more relevant for schools serving more affluent and predominantly White students. PMID:26584423
[Physical inactivity and associated factors in adults, São Paulo, Brazil].
Zanchetta, Luane Margarete; Barros, Marilisa Berti de Azevedo; César, Chester Luiz Galvão; Carandina, Luana; Goldbaum, Moisés; Alves, Maria Cecília Goi Porto
2010-09-01
To analyze the prevalence of overall and leisure time physical inactivity and associated factors and types of exercises or sports modalities according to schooling in 2,050 adults from 18 to 59 years of age - state of São Paulo, Brazil. Population-based cross-sectional study with a stratified sample of clusters performed in multiple stages. Physical inactivity was determined using the short version of the International Physical Activity Questionnaire - IPAQ and by a question on the regular practice of leisure time physical activity. Data analysis took the sample design into account. Prevalence of physical inactivity during leisure was higher among women. Poisson multiple regression model in man indicated that overall sedentarism was lower among single and separated men, students and without car in the household. Leisure physical inactivity was greater among men over forty years, among those with less schooling and full-time students. Overall physical inactivity was more prevalent among woman with more schooling, with less qualified occupations and widows. Leisure physical inactivity decreased with age and schooling. Among modalities practiced for leisure, walking was more prevalent among women and football was more prevalent among men. Most modalities were directly associated with schooling; approximately 25% of the individuals with more than 12 years of schooling practiced walking. These results suggest that interventions and public policies to promote physical activity should consider differences in gender and socioeconomic status as well as the preferences for different modalities and the context in which the physical activity is practiced.
Zeroth Poisson Homology, Foliated Cohomology and Perfect Poisson Manifolds
NASA Astrophysics Data System (ADS)
Martínez-Torres, David; Miranda, Eva
2018-01-01
We prove that, for compact regular Poisson manifolds, the zeroth homology group is isomorphic to the top foliated cohomology group, and we give some applications. In particular, we show that, for regular unimodular Poisson manifolds, top Poisson and foliated cohomology groups are isomorphic. Inspired by the symplectic setting, we define what a perfect Poisson manifold is. We use these Poisson homology computations to provide families of perfect Poisson manifolds.
Major stressful life events in adulthood and risk of multiple sclerosis.
Nielsen, Nete Munk; Bager, Peter; Simonsen, Jacob; Hviid, Anders; Stenager, Egon; Brønnum-Hansen, Henrik; Koch-Henriksen, Nils; Frisch, Morten
2014-10-01
It is unclear whether psychological stress is associated with increased risk of multiple sclerosis (MS). We studied the association between major stressful life events and MS in a nationwide cohort study using death of a child or a spouse or marital dissolution as indicators of severe stress. We created two study cohorts based on all Danish men and women born 1950-1992. One cohort consisted of all persons who became parents between 1968 and 2010, and another cohort consisted of all persons who married between 1968 and 2010. Members of both cohorts were followed for MS between 1982 and 2010 using data from the National Multiple Sclerosis Registry. Associations between major stressful life events and risk of MS were evaluated by means of MS incidence rate ratios (RR) with 95% confidence interval (CI) obtained in Poisson regression analyses. During approximately 30 million person-years of follow-up, bereaved parents experienced no unusual risk of MS compared with parents who did not lose a child (RR=1.12 (95% CI 0.89 to 1.38)). Likewise, neither divorced (RR=0.98 (95% CI 0.89 to 1.06)) nor widowed (RR=0.98 (95% CI 0.71 to 1.32) persons were at any unusual risk of MS compared with married persons of the same sex. Our national cohort study provides little evidence for a causal association between major stressful life events (as exemplified by divorce or the loss of a child or a spouse) and subsequent MS risk. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Short-term effects of multiple ozone metrics on daily mortality in a megacity of China.
Li, Tiantian; Yan, Meilin; Ma, Wenjun; Ban, Jie; Liu, Tao; Lin, Hualiang; Liu, Zhaorong
2015-06-01
Epidemiological studies have widely demonstrated association between ambient ozone and mortality, though controversy remains, and most of them only use a certain metric to assess ozone levels. However, in China, few studies have investigated the acute effects of ambient ozone, and rare studies have compared health effects of multiple daily metrics of ozone. The present analysis aimed to explore variability of estimated health effects by using multiple temporal ozone metrics. Six metrics of ozone, 1-h maximum, maximum 8-h average, 24-h average, daytime average, nighttime average, and commute average, were used in a time-series study to investigate acute mortality associated with ambient ozone pollution in Guangzhou, China, using 3 years of daily data (2006-2008). We used generalized linear models with Poisson regression incorporating natural spline functions to analyze the mortality, ozone, and covariate data. We also examined the association by season. Daily 1- and 8-h maximum, 24-h average, and daytime average concentrations yielded statistically significant associations with mortality. An interquartile range (IQR) of O3 metric increase of each ozone metric (lag 2) corresponds to 2.92 % (95 % confidence interval (CI) 0.24 to 5.66), 3.60 % (95 % CI, 0.92 to 8.49), 3.03 % (95 % CI, 0.57 to 15.8), and 3.31 % (95 % CI, 0.69 to 10.4) increase in daily non-accidental mortality, respectively. Nighttime and commute metrics were weakly associated with increased mortality rate. The associations between ozone and mortality appeared to be more evident during cool season than in the warm season. Results were robust to adjustment for co-pollutants, weather, and time trend. In conclusion, these results indicated that ozone, as a widespread pollutant, adversely affects mortality in Guangzhou.
Magnet-related injury rates in children: a single hospital experience.
Agbo, Chioma; Lee, Lois; Chiang, Vincent; Landscahft, Assaf; Kimia, Tomer; Monuteaux, Michael C; Kimia, Amir A
2013-07-01
The ingestion of multiple magnets simultaneously or the placement of magnets in both nares can lead to serious injury resulting from the attraction of the magnets across the tissues. The impact of mandatory standards for toys containing magnets has not been thoroughly investigated. The aim of the present study was to describe the emergency department (ED) visit rate for magnet-related injuries. We performed a retrospective study of children evaluated for magnet-related injuries from 1995 to 2012 in an urban tertiary care pediatric ED. We identified cases using a computerized text-search methodology followed by manual chart review. We included children evaluated for magnet ingestion or impaction in the ears, nose, vagina, or rectum. We assessed the type and number of magnets as well as management and required interventions. A Poisson regression model was used to analyze rates of injury over time. We identified 112 cases of magnet injuries. The median patient age was 6 years (IQR 3.5, 10), and 54% were male. Compared to before 2006, the rate for all magnet-related injuries in 2007-2012 (incidence rate ratio 3.44; 95% confidence interval 2.3-5.11) as well as multiple magnet-related injuries (incidence rate ratio 7.54; 95% confidence interval 3.51-16.19) increased. Swallowed magnets accounted for 86% of the injuries. Thirteen patients had endoscopy performed for magnet removal (12%), and 4 (4%) had a surgical intervention. Magnets from toys account for the majority of the injuries. The number of ED visits for magnet-related injuries in children may be rising and are underreported, with an increase in the proportion of multiple magnets involvement. In our case series, mandatory standard for toys had no mitigating effect.
A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield
NASA Astrophysics Data System (ADS)
Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan
2018-04-01
In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.
Application of the sine-Poisson equation in solar magnetostatics
NASA Technical Reports Server (NTRS)
Webb, G. M.; Zank, G. P.
1990-01-01
Solutions of the sine-Poisson equations are used to construct a class of isothermal magnetostatic atmospheres, with one ignorable coordinate corresponding to a uniform gravitational field in a plane geometry. The distributed current in the model (j) is directed along the x-axis, where x is the horizontal ignorable coordinate; (j) varies as the sine of the magnetostatic potential and falls off exponentially with distance vertical to the base with an e-folding distance equal to the gravitational scale height. Solutions for the magnetostatic potential A corresponding to the one-soliton, two-soliton, and breather solutions of the sine-Gordon equation are studied. Depending on the values of the free parameters in the soliton solutions, horizontally periodic magnetostatic structures are obtained possessing either a single X-type neutral point, multiple neural X-points, or solutions without X-points.
Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.
2012-01-01
Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.
NASA Technical Reports Server (NTRS)
Schwartz, Joel D.; Lee, Mihye; Kinney, Patrick L.; Yang, Suijia; Mills, David; Sarofim, Marcus C.; Jones, Russell; Streeter, Richard; St. Juliana, Alexis; Peers, Jennifer;
2015-01-01
Background: A warming climate will affect future temperature-attributable premature deaths. This analysis is the first to project these deaths at a near national scale for the United States using city and month-specific temperature-mortality relationships. Methods: We used Poisson regressions to model temperature-attributable premature mortality as a function of daily average temperature in 209 U.S. cities by month. We used climate data to group cities into clusters and applied an Empirical Bayes adjustment to improve model stability and calculate cluster-based month-specific temperature-mortality functions. Using data from two climate models, we calculated future daily average temperatures in each city under Representative Concentration Pathway 6.0. Holding population constant at 2010 levels, we combined the temperature data and cluster-based temperature-mortality functions to project city-specific temperature-attributable premature deaths for multiple future years which correspond to a single reporting year. Results within the reporting periods are then averaged to account for potential climate variability and reported as a change from a 1990 baseline in the future reporting years of 2030, 2050 and 2100. Results: We found temperature-mortality relationships that vary by location and time of year. In general, the largest mortality response during hotter months (April - September) was in July in cities with cooler average conditions. The largest mortality response during colder months (October-March) was at the beginning (October) and end (March) of the period. Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990. However, the magnitude and sign of the change varied by cluster and city. Conclusions: We found increasing future premature deaths across the 209 modeled U.S. cities using two climate model projections, based on constant temperature-mortality relationships from 1997 to 2006 without any future adaptation. However, results varied by location, with some locations showing net reductions in premature temperature-attributable deaths with climate change.
Vilella, Karina Duarte; Fraiz, Fabian Calixto; Benelli, Elaine Machado; Assunção, Luciana Reichert da Silva
This study evaluated the effect of oral health literacy (OHL) on the retention of health information in pregnant women. A total of 175 pregnant women were randomly assigned to standard oral (spoken), written and control intervention groups. With the exception of the control group, the interventions investigated the eating habits and oral hygiene among children under 2 years of age. The participants' answers before the interventions (pre-test), 15 min after the interventions (post-test) and 4 weeks after the interventions (follow-up test) were used to estimate the knowledge score (KS). Information acquisition was determined by comparing pre-test and post-test results, while retention of information was based comparing pre-test and follow-up test results. OHL was analysed by BREALD-30. The data were assessed by nonparametric tests and Poisson regression models with robust variance (α = 0.05). By the end of the follow-up period, 162 pregnant women had been assessed. The BREALD-30 mean was 22.3 (SD = 4.80). Regardless of the type of intervention, pregnant women with low OHL had lower knowledge scores in the three assessments. Participants with low OHL showed higher acquisition and retention of information in the standard oral health intervention. Multiple regression models demonstrated that OHL was independently associated with KS, age, socioeconomic status and type of intervention. The results suggest a negative effect of low OHL on retention of information. Only the standard, spoken oral health intervention could address the differences in literacy levels.
Harrison, Christopher M; Britt, Helena C; Charles, Janice
2011-08-15
Previous research with the Australian Morbidity and Treatment Survey (1990-1991) showed significant differences in general practitioner characteristics and patient mix of male and female GPs. Even after adjusting for these, it was seen that male and female GPs managed different types of medical conditions. The proportion of female GPs increased from 19.6% in 1990-1991 to 37.1% in 2009-2010. This study investigates whether differences remain two decades later. Analysis of 2009-2010 Bettering the Evaluation and Care of Health (BEACH) data examining GP characteristics, patient encounter characteristics, patient reasons for encounter (RFE), problem types managed and management methods used, by GP sex. Whether GP sex was an independent predictor of problem types being managed, or management methods used, was tested using multiple logistic regressions and Poisson regression. 988 GPs recorded 98 800 GP-patient encounters. Adjusted differences in clinical activity of male and female GPs. After adjustment, compared with male GPs, females recorded more RFEs about general and unspecified issues and endocrine, female genital, pregnancy and family planning problems; and fewer concerning the musculoskeletal, respiratory, skin and male genital systems. Female GPs managed more general and unspecified, digestive, circulatory, psychological, endocrine, female genital and social problems; recorded nearly 20% more clinical treatments and referrals; recorded nearly 10% more imaging and pathology tests; and 4.3% fewer medications. After two decades, even with increased numbers of female GPs, the differences in problems managed by male and female GPs remain, and will probably continue. Female GPs use more resources per encounter, but may not use more resources in terms of annual patient care.
An evaluation of asthma interventions for preteen students.
Clark, Noreen M; Shah, Smita; Dodge, Julia A; Thomas, Lara J; Andridge, Rebecca R; Little, Roderick J A
2010-02-01
Asthma is a serious problem for low-income preteens living in disadvantaged communities. Among the chronic diseases of childhood and adolescence, asthma has the highest prevalence and related health care use. School-based asthma interventions have proven successful for older and younger students, but results have not been demonstrated for those in middle school. This randomized controlled study screened students 10-13 years of age in 19 middle schools in low-income communities in Detroit, Michigan. Of the 6,872 students who were screened, 1,292 students were identified with asthma. Schools were matched and randomly assigned to Program 1 or 2 or control. Baseline, 12, and 24 months data were collected by telephone (parents), at school (students) and from school system records. Measures were the students' asthma symptoms, quality of life, academic performance, self-regulation, and asthma management practices. Data were analyzed using multiple imputation with sequential regression analysis. Mixed models and Poisson regressions were used to develop final models. Neither program produced significant change in asthma symptoms or quality of life. One produced improved school grades (p = .02). The other enhanced self-regulation (p = .01) at 24 months. Both slowed the decline in self-regulation in undiagnosed preteens at 12 months and increased self-regulation at 24 months (p = .04; p = .003). Programs had effects on academic performance and self-regulation capacities of students. More developmentally focused interventions may be needed for students at this transitional stage. Disruptive factors in the schools may have reduced both program impact and the potential for outcome assessment.
An Evaluation of Asthma Interventions for Preteen Students
Clark, Noreen M.; Shah, Smita; Dodge, Julia A.; Thomas, Lara J.; Andridge, Rebecca R.; Little, Roderick J.A.
2013-01-01
Background Asthma is a serious problem for low income, pre teens living in disadvantaged communities. Asthma prevalence and health care use are the highest of the chronic diseases of childhood and adolescence. School based asthma interventions have proven successful for older and younger students but results have not been demonstrated for those in middle school. Methods This randomized controlled study involved 6872 students 10–13 years of age and assessed two programs, 1) self-management and 2) self-management plus peer involvement, provided in 19 middle schools in low income, communities. 1292 students were identified with asthma. Schools were matched and randomly assigned to program one or two or control. Baseline, 12, and 24 months data were collected by telephone (parents), at school (students) and from school system records. Measures were the students’ asthma symptoms, quality of life, academic performance, self-regulation and asthma management practices. Data were analyzed using multiple imputation with sequential regression analysis. Mixed models and Poisson regressions were used to develop final models. Results Neither program produced change in asthma symptoms or quality of life. One produced improved school grades (p=0.02). The other enhanced self-regulation (p=0.01) at 24 months. Both slowed the decline in self-regulation in undiagnosed preteens at 12 months and increased self regulation at 24 months (p=0.04; p=0.003). Conclusion Programs had effects on academic performance and self-regulation capacities of students. More developmentally focused interventions may be needed for students at this transitional stage. Disruptive factors in the schools may have reduced both program impact and the potential for outcome assessment. PMID:20236406
Ruple-Czerniak, A A; Aceto, H W; Bender, J B; Paradis, M R; Shaw, S P; Van Metre, D C; Weese, J S; Wilson, D A; Wilson, J; Morley, P S
2014-07-01
Methods that can be used to estimate rates of healthcare-associated infections and other nosocomial events have not been well established for use in equine hospitals. Traditional laboratory-based surveillance is expensive and cannot be applied in all of these settings. To evaluate the use of a syndromic surveillance system for estimating rates of occurrence of healthcare-associated infections among hospitalised equine cases. Multicentre, prospective longitudinal study. This study included weaned equids (n = 297) that were admitted for gastrointestinal disorders at one of 5 participating veterinary referral hospitals during a 12-week period in 2006. A survey form was completed by the primary clinician to summarise basic case information, procedures and treatments the horse received, and whether one or more of 7 predefined nosocomial syndromes were recognised at any point during hospitalisation. Adjusted rates of nosocomial events were estimated using Poisson regression. Risk factors associated with the risk of developing a nosocomial event were analysed using multivariable logistic regression. Among the study population, 95 nosocomial events were reported to have occurred in 65 horses. Controlling for differences among hospitals, 19.7% (95% confidence interval, 14.5-26.7) of the study population was reported to have had at least one nosocomial event recognised during hospitalisation. The most commonly reported nosocomial syndromes that were unrelated to the reason for hospitalisation were surgical site inflammation and i.v. catheter site inflammation. Syndromic surveillance systems can be standardised successfully for use across multiple hospitals without interfering with established organisational structures, in order to provide useful estimates of rates related to healthcare-associated infections. © 2013 EVJ Ltd.
Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando H.; Montesinos-López, José C.; Singh, Pawan; Juliana, Philomin; Salinas-Ruiz, Josafhat
2017-01-01
When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait at a time taking into account genotype × environment interaction (G × E), because there is a lack of comprehensive models that simultaneously take into account the correlated counting traits and G × E. For this reason, in this study we propose a multiple-trait and multiple-environment model for count data. The proposed model was developed under the Bayesian paradigm for which we developed a Markov Chain Monte Carlo (MCMC) with noninformative priors. This allows obtaining all required full conditional distributions of the parameters leading to an exact Gibbs sampler for the posterior distribution. Our model was tested with simulated data and a real data set. Results show that the proposed multi-trait, multi-environment model is an attractive alternative for modeling multiple count traits measured in multiple environments. PMID:28364037
Electronic health record analysis via deep poisson factor models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Henao, Ricardo; Lu, James T.; Lucas, Joseph E.
Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less
Electronic health record analysis via deep poisson factor models
Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...
2016-01-01
Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less
DISCRETE COMPOUND POISSON PROCESSES AND TABLES OF THE GEOMETRIC POISSON DISTRIBUTION.
A concise summary of the salient properties of discrete Poisson processes , with emphasis on comparing the geometric and logarithmic Poisson processes . The...the geometric Poisson process are given for 176 sets of parameter values. New discrete compound Poisson processes are also introduced. These...processes have properties that are particularly relevant when the summation of several different Poisson processes is to be analyzed. This study provides the
Gingival enlargement in orthodontic patients: Effect of treatment duration.
Pinto, Alice Souza; Alves, Luana Severo; Zenkner, Júlio Eduardo do Amaral; Zanatta, Fabrício Batistin; Maltz, Marisa
2017-10-01
In this study, we aimed to assess the effect of the duration of fixed orthodontic treatment on gingival enlargement (GE) in adolescents and young adults. The sample consisted of 260 subjects (ages, 10-30 years) divided into 4 groups: patients with no fixed orthodontic appliances (G0) and patients undergoing orthodontic treatment for 1 year (G1), 2 years (G2), or 3 years (G3). Participants completed a structured questionnaire on sociodemographic characteristics and oral hygiene habits. Clinical examinations were conducted by a calibrated examiner and included the plaque index, the gingival index, and the Seymour index. Poisson regression models were used to assess the association between group and GE. We observed increasing means of plaque, gingivitis, and GE in G0, G1, and G2. No significant differences were observed between G2 and G3. Adjusted Poisson regression analysis showed that patients undergoing orthodontic treatment had a 20 to 28-fold increased risk for GE than did those without orthodontic appliances (G1, rate ratio [RR] = 20.2, 95% CI = 9.0-45.3; G2, RR = 27.0, 95% CI = 12.1-60.3; G3 = 28.1; 95% CI = 12.6-62.5). The duration of orthodontic treatment significantly influenced the occurrence of GE. Oral hygiene instructions and motivational activities should target adolescents and young adults undergoing orthodontic treatment. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.
Hogan, Jennifer N.; Daniels, Miles E.; Watson, Fred G.; Conrad, Patricia A.; Oates, Stori C.; Miller, Melissa A.; Hardin, Dane; Byrne, Barbara A.; Dominik, Clare; Melli, Ann; Jessup, David A.
2012-01-01
Fecal pathogen contamination of watersheds worldwide is increasingly recognized, and natural wetlands may have an important role in mitigating fecal pathogen pollution flowing downstream. Given that waterborne protozoa, such as Cryptosporidium and Giardia, are transported within surface waters, this study evaluated associations between fecal protozoa and various wetland-specific and environmental risk factors. This study focused on three distinct coastal California wetlands: (i) a tidally influenced slough bordered by urban and agricultural areas, (ii) a seasonal wetland adjacent to a dairy, and (iii) a constructed wetland that receives agricultural runoff. Wetland type, seasonality, rainfall, and various water quality parameters were evaluated using longitudinal Poisson regression to model effects on concentrations of protozoa and indicator bacteria (Escherichia coli and total coliform). Among wetland types, the dairy wetland exhibited the highest protozoal and bacterial concentrations, and despite significant reductions in microbe concentrations, the wetland could still be seen to influence water quality in the downstream tidal wetland. Additionally, recent rainfall events were associated with higher protozoal and bacterial counts in wetland water samples across all wetland types. Notably, detection of E. coli concentrations greater than a 400 most probable number (MPN) per 100 ml was associated with higher Cryptosporidium oocyst and Giardia cyst concentrations. These findings show that natural wetlands draining agricultural and livestock operation runoff into human-utilized waterways should be considered potential sources of pathogens and that wetlands can be instrumental in reducing pathogen loads to downstream waters. PMID:22427504
Albornoz, Claudia; Villegas, Jorge; Sylvester, Marilu; Peña, Veronica; Bravo, Iside
2011-06-01
Chile is located in the Ring of Fire, in South America. An earthquake 8.8° affected 80% of the population in February 27th, 2010. This study was conducted to assess any change in burns profile caused by the earthquake. This was an ecologic study. We compared the 4 months following the earthquake in 2009 and 2010. age, TBSA, deep TBSA, agent, specific mortality rate and rate of admissions to the National burn Center of Chile. Mann-Whitney test and a Poisson regression were performed. Age, agent, TBSA and deep TBSA percentages did not show any difference. Mortality rate was lower in 2010 (0.52 versus 1.22 per 1,000,000 habitants) but no meaningful difference was found (Poisson regression p = 0.06). Admission rate was lower in 2010, 4.6 versus 5.6 per 1,000,000 habitants, but no differences were found (p = 0.26). There was not any admissions directly related to the earthquake. As we do not have incidence registries in Chile, we propose to use the rate of admission to the National Burn Reference Center as an incidence estimator. There was not any significant difference in the burn profile, probably because of the time of the earthquake (3 am). We conclude the earthquake did not affect the way the Chilean people get burned. Copyright © 2011 Elsevier Ltd and ISBI. All rights reserved.
Nikkhoo, Mohammad; Hsu, Yu-Chun; Haghpanahi, Mohammad; Parnianpour, Mohamad; Wang, Jaw-Lin
2013-06-01
Finite element analysis is an effective tool to evaluate the material properties of living tissue. For an interactive optimization procedure, the finite element analysis usually needs many simulations to reach a reasonable solution. The meta-model analysis of finite element simulation can be used to reduce the computation of a structure with complex geometry or a material with composite constitutive equations. The intervertebral disc is a complex, heterogeneous, and hydrated porous structure. A poroelastic finite element model can be used to observe the fluid transferring, pressure deviation, and other properties within the disc. Defining reasonable poroelastic material properties of the anulus fibrosus and nucleus pulposus is critical for the quality of the simulation. We developed a material property updating protocol, which is basically a fitting algorithm consisted of finite element simulations and a quadratic response surface regression. This protocol was used to find the material properties, such as the hydraulic permeability, elastic modulus, and Poisson's ratio, of intact and degenerated porcine discs. The results showed that the in vitro disc experimental deformations were well fitted with limited finite element simulations and a quadratic response surface regression. The comparison of material properties of intact and degenerated discs showed that the hydraulic permeability significantly decreased but Poisson's ratio significantly increased for the degenerated discs. This study shows that the developed protocol is efficient and effective in defining material properties of a complex structure such as the intervertebral disc.
Fukuda, Yoshiharu; Nakamura, Keiko; Takano, Takehito
2007-03-01
To formulate an index representing area deprivation and elucidate the relation between the index and mortality in Japan. Ecological study for prefectures (N=47) and municipalities (N=3366) across Japan. Based on socioeconomic indicators of seven domains of deprivation (i.e. unemployment, overcrowding, low social class and poverty, low education, no home ownership, low income and vulnerable group), an index was formulated using the z-scoring method. The relation between the index and mortality was examined by correlation analysis, hierarchical Poisson regression and comparison of standardized mortality ratio according to the index. The deprivation index ranged from -7.48 to 10.98 for prefectures and from -16.97 to 13.82 for municipalities. The index was significantly positively correlated with prefectural mortality, especially in the population aged under 74 years: r=0.65 for men and r=0.41 for women. At the municipal level, hierarchical Poisson regression showed a significant positive coefficient of the index to mortality for both men and women, and excess mortality in the most deprived fifth compared to the least deprived fifth was 26.4% in men and 11.8% in women. We formulated a deprivation index, which was substantially related to mortality at the prefectural and municipal levels. This study highlights the higher risk of dying among populations in socially disadvantaged areas and encourages the use of indices representing area socioeconomic conditions for further studies of area effects on health.
Remontet, L; Bossard, N; Belot, A; Estève, J
2007-05-10
Relative survival provides a measure of the proportion of patients dying from the disease under study without requiring the knowledge of the cause of death. We propose an overall strategy based on regression models to estimate the relative survival and model the effects of potential prognostic factors. The baseline hazard was modelled until 10 years follow-up using parametric continuous functions. Six models including cubic regression splines were considered and the Akaike Information Criterion was used to select the final model. This approach yielded smooth and reliable estimates of mortality hazard and allowed us to deal with sparse data taking into account all the available information. Splines were also used to model simultaneously non-linear effects of continuous covariates and time-dependent hazard ratios. This led to a graphical representation of the hazard ratio that can be useful for clinical interpretation. Estimates of these models were obtained by likelihood maximization. We showed that these estimates could be also obtained using standard algorithms for Poisson regression. Copyright 2006 John Wiley & Sons, Ltd.
Stamm, John W.; Long, D. Leann; Kincade, Megan E.
2012-01-01
Over the past five to ten years, zero-inflated count regression models have been increasingly applied to the analysis of dental caries indices (e.g., DMFT, dfms, etc). The main reason for that is linked to the broad decline in children’s caries experience, such that dmf and DMF indices more frequently generate low or even zero counts. This article specifically reviews the application of zero-inflated Poisson and zero-inflated negative binomial regression models to dental caries, with emphasis on the description of the models and the interpretation of fitted model results given the study goals. The review finds that interpretations provided in the published caries research are often imprecise or inadvertently misleading, particularly with respect to failing to discriminate between inference for the class of susceptible persons defined by such models and inference for the sampled population in terms of overall exposure effects. Recommendations are provided to enhance the use as well as the interpretation and reporting of results of count regression models when applied to epidemiological studies of dental caries. PMID:22710271
Predicting spatio-temporal failure in large scale observational and micro scale experimental systems
NASA Astrophysics Data System (ADS)
de las Heras, Alejandro; Hu, Yong
2006-10-01
Forecasting has become an essential part of modern thought, but the practical limitations still are manifold. We addressed future rates of change by comparing models that take into account time, and models that focus more on space. Cox regression confirmed that linear change can be safely assumed in the short-term. Spatially explicit Poisson regression, provided a ceiling value for the number of deforestation spots. With several observed and estimated rates, it was decided to forecast using the more robust assumptions. A Markov-chain cellular automaton thus projected 5-year deforestation in the Amazonian Arc of Deforestation, showing that even a stable rate of change would largely deplete the forest area. More generally, resolution and implementation of the existing models could explain many of the modelling difficulties still affecting forecasting.
Xiao, Hong; Tian, Huai-yu; Zhang, Xi-xing; Zhao, Jian; Zhu, Pei-juan; Liu, Ru-chun; Chen, Tian-mu; Dai, Xiang-yu; Lin, Xiao-ling
2011-10-01
To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS. A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission. The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases). Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.
Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard
2016-10-01
In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value <0.001). However, the flexible piecewise exponential model showed the smallest overdispersion parameter (3.2 versus 21.3) for non-flexible piecewise exponential models. We showed that there were no major differences between methods. However, using a flexible piecewise regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.
Method for resonant measurement
Rhodes, G.W.; Migliori, A.; Dixon, R.D.
1996-03-05
A method of measurement of objects to determine object flaws, Poisson`s ratio ({sigma}) and shear modulus ({mu}) is shown and described. First, the frequency for expected degenerate responses is determined for one or more input frequencies and then splitting of degenerate resonant modes are observed to identify the presence of flaws in the object. Poisson`s ratio and the shear modulus can be determined by identification of resonances dependent only on the shear modulus, and then using that shear modulus to find Poisson`s ratio using other modes dependent on both the shear modulus and Poisson`s ratio. 1 fig.
NASA Technical Reports Server (NTRS)
Grant, J.; Kaul, R.; Taylor, S.; Myer, G.; Jackson, K.; Osei, A.; Sharma, A.
2003-01-01
Multiple Fiber Bragg-gratings are embedded in carbon-epoxy laminates as well as in composite wound pressure vessel. Structural properties of such composites are investigated. The measurements include stress-strain relation in laminates and Poisson's ratio in several specimens with varying orientation of the optical fiber Bragg-sensor with respect to the carbon fiber in an epoxy matrix. Additionally, fiber Bragg gratings are bonded on the surface of these laminates and cylinders fabricated out of carbon-epoxy composites and multiple points are monitored and compared for strain measurements at several locations.
NASA Technical Reports Server (NTRS)
Ortega, J. M.
1986-01-01
Various graduate research activities in the field of computer science are reported. Among the topics discussed are: (1) failure probabilities in multi-version software; (2) Gaussian Elimination on parallel computers; (3) three dimensional Poisson solvers on parallel/vector computers; (4) automated task decomposition for multiple robot arms; (5) multi-color incomplete cholesky conjugate gradient methods on the Cyber 205; and (6) parallel implementation of iterative methods for solving linear equations.
Jones, Andrew M; Lomas, James; Moore, Peter T; Rice, Nigel
2016-10-01
We conduct a quasi-Monte-Carlo comparison of the recent developments in parametric and semiparametric regression methods for healthcare costs, both against each other and against standard practice. The population of English National Health Service hospital in-patient episodes for the financial year 2007-2008 (summed for each patient) is randomly divided into two equally sized subpopulations to form an estimation set and a validation set. Evaluating out-of-sample using the validation set, a conditional density approximation estimator shows considerable promise in forecasting conditional means, performing best for accuracy of forecasting and among the best four for bias and goodness of fit. The best performing model for bias is linear regression with square-root-transformed dependent variables, whereas a generalized linear model with square-root link function and Poisson distribution performs best in terms of goodness of fit. Commonly used models utilizing a log-link are shown to perform badly relative to other models considered in our comparison.
Does Group-Level Commitment Predict Employee Well-Being?: A Prospective Analysis.
Clausen, Thomas; Christensen, Karl Bang; Nielsen, Karina
2015-11-01
To investigate the links between group-level affective organizational commitment (AOC) and individual-level psychological well-being, self-reported sickness absence, and sleep disturbances. A total of 5085 care workers from 301 workgroups in the Danish eldercare services participated in both waves of the study (T1 [2005] and T2 [2006]). The three outcomes were analyzed using linear multilevel regression analysis, multilevel Poisson regression analysis, and multilevel logistic regression analysis, respectively. Group-level AOC (T1) significantly predicted individual-level psychological well-being, self-reported sickness absence, and sleep disturbances (T2). The association between group-level AOC (T1) and psychological well-being (T2) was fully mediated by individual-level AOC (T1), and the associations between group-level AOC (T1) and self-reported sickness absence and sleep disturbances (T2) were partially mediated by individual-level AOC (T1). Group-level AOC is an important predictor of employee well-being in contemporary health care organizations.
Multiple Correlation versus Multiple Regression.
ERIC Educational Resources Information Center
Huberty, Carl J.
2003-01-01
Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)
Properties of the Bivariate Delayed Poisson Process
1974-07-01
and Lewis (1972) in their Berkeley Symposium paper and here their analysis of the bivariate Poisson processes (without Poisson noise) is carried... Poisson processes . They cannot, however, be independent Poisson processes because their events are associated in pairs by the displace- ment centres...process because its marginal processes for events of each type are themselves (univariate) Poisson processes . Cox and Lewis (1972) assumed a
Statistical Modeling Reveals the Effect of Absolute Humidity on Dengue in Singapore
Xu, Hai-Yan; Fu, Xiuju; Lee, Lionel Kim Hock; Ma, Stefan; Goh, Kee Tai; Wong, Jiancheng; Habibullah, Mohamed Salahuddin; Lee, Gary Kee Khoon; Lim, Tian Kuay; Tambyah, Paul Anantharajah; Lim, Chin Leong; Ng, Lee Ching
2014-01-01
Weather factors are widely studied for their effects on indicating dengue incidence trends. However, these studies have been limited due to the complex epidemiology of dengue, which involves dynamic interplay of multiple factors such as herd immunity within a population, distinct serotypes of the virus, environmental factors and intervention programs. In this study, we investigate the impact of weather factors on dengue in Singapore, considering the disease epidemiology and profile of virus serotypes. A Poisson regression combined with Distributed Lag Non-linear Model (DLNM) was used to evaluate and compare the impact of weekly Absolute Humidity (AH) and other weather factors (mean temperature, minimum temperature, maximum temperature, rainfall, relative humidity and wind speed) on dengue incidence from 2001 to 2009. The same analysis was also performed on three sub-periods, defined by predominant circulating serotypes. The performance of DLNM regression models were then evaluated through the Akaike's Information Criterion. From the correlation and DLNM regression modeling analyses of the studied period, AH was found to be a better predictor for modeling dengue incidence than the other unique weather variables. Whilst mean temperature (MeanT) also showed significant correlation with dengue incidence, the relationship between AH or MeanT and dengue incidence, however, varied in the three sub-periods. Our results showed that AH had a more stable impact on dengue incidence than temperature when virological factors were taken into consideration. AH appeared to be the most consistent factor in modeling dengue incidence in Singapore. Considering the changes in dominant serotypes, the improvements in vector control programs and the inconsistent weather patterns observed in the sub-periods, the impact of weather on dengue is modulated by these other factors. Future studies on the impact of climate change on dengue need to take all the other contributing factors into consideration in order to make meaningful public policy recommendations. PMID:24786517
Statistical modeling reveals the effect of absolute humidity on dengue in Singapore.
Xu, Hai-Yan; Fu, Xiuju; Lee, Lionel Kim Hock; Ma, Stefan; Goh, Kee Tai; Wong, Jiancheng; Habibullah, Mohamed Salahuddin; Lee, Gary Kee Khoon; Lim, Tian Kuay; Tambyah, Paul Anantharajah; Lim, Chin Leong; Ng, Lee Ching
2014-05-01
Weather factors are widely studied for their effects on indicating dengue incidence trends. However, these studies have been limited due to the complex epidemiology of dengue, which involves dynamic interplay of multiple factors such as herd immunity within a population, distinct serotypes of the virus, environmental factors and intervention programs. In this study, we investigate the impact of weather factors on dengue in Singapore, considering the disease epidemiology and profile of virus serotypes. A Poisson regression combined with Distributed Lag Non-linear Model (DLNM) was used to evaluate and compare the impact of weekly Absolute Humidity (AH) and other weather factors (mean temperature, minimum temperature, maximum temperature, rainfall, relative humidity and wind speed) on dengue incidence from 2001 to 2009. The same analysis was also performed on three sub-periods, defined by predominant circulating serotypes. The performance of DLNM regression models were then evaluated through the Akaike's Information Criterion. From the correlation and DLNM regression modeling analyses of the studied period, AH was found to be a better predictor for modeling dengue incidence than the other unique weather variables. Whilst mean temperature (MeanT) also showed significant correlation with dengue incidence, the relationship between AH or MeanT and dengue incidence, however, varied in the three sub-periods. Our results showed that AH had a more stable impact on dengue incidence than temperature when virological factors were taken into consideration. AH appeared to be the most consistent factor in modeling dengue incidence in Singapore. Considering the changes in dominant serotypes, the improvements in vector control programs and the inconsistent weather patterns observed in the sub-periods, the impact of weather on dengue is modulated by these other factors. Future studies on the impact of climate change on dengue need to take all the other contributing factors into consideration in order to make meaningful public policy recommendations.
ERIC Educational Resources Information Center
Jaccard, James; And Others
1990-01-01
Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)
Tobit analysis of vehicle accident rates on interstate highways.
Anastasopoulos, Panagiotis Ch; Tarko, Andrew P; Mannering, Fred L
2008-03-01
There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.
Competitive Swimming and Racial Disparities in Drowning
Myers, Samuel L.; Cuesta, Ana M.; Lai, Yufeng
2018-01-01
This paper provides compelling evidence of an inverse relationship between competitive swimming rates and drowning rates using Centers for Disease Control and Prevention (CDC) data on fatal drowning rates and membership rates from USA Swimming, the governing organization of competitive swimming in the United States. Tobit and Poisson regression models are estimated using panel data by state from 1999–2007 separately for males, females, African Americans and whites. The strong inverse relationship between competitive swimming rates and unintentional deaths through fatal drowning is most pronounced among African Americans males.
Spatial event cluster detection using an approximate normal distribution.
Torabi, Mahmoud; Rosychuk, Rhonda J
2008-12-12
In geographic surveillance of disease, areas with large numbers of disease cases are to be identified so that investigations of the causes of high disease rates can be pursued. Areas with high rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. Typically cluster detection tests are applied to incident or prevalent cases of disease, but surveillance of disease-related events, where an individual may have multiple events, may also be of interest. Previously, a compound Poisson approach that detects clusters of events by testing individual areas that may be combined with their neighbours has been proposed. However, the relevant probabilities from the compound Poisson distribution are obtained from a recursion relation that can be cumbersome if the number of events are large or analyses by strata are performed. We propose a simpler approach that uses an approximate normal distribution. This method is very easy to implement and is applicable to situations where the population sizes are large and the population distribution by important strata may differ by area. We demonstrate the approach on pediatric self-inflicted injury presentations to emergency departments and compare the results for probabilities based on the recursion and the normal approach. We also implement a Monte Carlo simulation to study the performance of the proposed approach. In a self-inflicted injury data example, the normal approach identifies twelve out of thirteen of the same clusters as the compound Poisson approach, noting that the compound Poisson method detects twelve significant clusters in total. Through simulation studies, the normal approach well approximates the compound Poisson approach for a variety of different population sizes and case and event thresholds. A drawback of the compound Poisson approach is that the relevant probabilities must be determined through a recursion relation and such calculations can be computationally intensive if the cluster size is relatively large or if analyses are conducted with strata variables. On the other hand, the normal approach is very flexible, easily implemented, and hence, more appealing for users. Moreover, the concepts may be more easily conveyed to non-statisticians interested in understanding the methodology associated with cluster detection test results.
Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results
ERIC Educational Resources Information Center
Warne, Russell T.
2011-01-01
Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…
Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha
2012-05-01
Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.
Roberts, Sarah T; Flaherty, Brian P; Deya, Ruth; Masese, Linnet; Ngina, Jacqueline; McClelland, R Scott; Simoni, Jane; Graham, Susan M
2018-03-30
Gender-based violence (GBV) is common among female sex workers (FSWs) and is associated with multiple HIV risk factors, including poor mental health, high-risk sexual behavior, and sexually transmitted infections (STIs). Prior studies have focused on GBV of one type (e.g. physical or sexual) or from one kind of perpetrator (e.g., clients or regular partners), but many FSWs experience overlapping types of violence from multiple perpetrators, with varying frequency and severity. We examined the association between lifetime patterns of GBV and HIV risk factors in 283 FSWs in Mombasa, Kenya. Patterns of GBV were identified with latent class analysis based on physical, sexual, or emotional violence from multiple perpetrators. Cross-sectional outcomes included depressive symptoms, post-traumatic stress disorder (PTSD) symptoms, disordered alcohol and other drug use, number of sex partners, self-reported unprotected sex, prostate-specific antigen (PSA) in vaginal secretions, and a combined unprotected sex indicator based on self-report or PSA detection. We also measured HIV/STI incidence over 12 months following GBV assessment. Associations between GBV patterns and each outcome were modeled separately using linear regression for mental health outcomes and Poisson regression for sexual risk outcomes. Lifetime prevalence of GBV was 87%. We identified 4 GBV patterns, labeled Low (21% prevalence), Sexual (23%), Physical/Moderate Emotional (18%), and Severe (39%). Compared to women with Low GBV, those with Severe GBV had higher scores for depressive symptoms, PTSD symptoms, and disordered alcohol use, and had more sex partners. Women with Sexual GBV had higher scores for disordered alcohol use than women with Low GBV, but similar sexual risk behavior. Women with Physical/Moderate Emotional GBV had more sex partners and a higher prevalence of unprotected sex than women with Low GBV, but no differences in mental health. HIV/STI incidence did not differ significantly by GBV pattern. The prevalence of GBV was extremely high in this sample of Kenyan FSWs, and different GBV patterns were associated with distinct mental health and sexual risk outcomes. Increased understanding of how health consequences vary by GBV type and severity could lead to more effective programs to reduce HIV risk in this vulnerable population.
Inouye, David I.; Ravikumar, Pradeep; Dhillon, Inderjit S.
2016-01-01
We develop Square Root Graphical Models (SQR), a novel class of parametric graphical models that provides multivariate generalizations of univariate exponential family distributions. Previous multivariate graphical models (Yang et al., 2015) did not allow positive dependencies for the exponential and Poisson generalizations. However, in many real-world datasets, variables clearly have positive dependencies. For example, the airport delay time in New York—modeled as an exponential distribution—is positively related to the delay time in Boston. With this motivation, we give an example of our model class derived from the univariate exponential distribution that allows for almost arbitrary positive and negative dependencies with only a mild condition on the parameter matrix—a condition akin to the positive definiteness of the Gaussian covariance matrix. Our Poisson generalization allows for both positive and negative dependencies without any constraints on the parameter values. We also develop parameter estimation methods using node-wise regressions with ℓ1 regularization and likelihood approximation methods using sampling. Finally, we demonstrate our exponential generalization on a synthetic dataset and a real-world dataset of airport delay times. PMID:27563373
Patterns of multisite pain and associations with risk factors
Coggon, David; Ntani, Georgia; Palmer, Keith T.; Felli, Vanda E.; Harari, Raul; Barrero, Lope H.; Felknor, Sarah A.; Gimeno, David; Cattrell, Anna; Vargas-Prada, Sergio; Bonzini, Matteo; Solidaki, Eleni; Merisalu, Eda; Habib, Rima R.; Sadeghian, Farideh; Masood Kadir, M.; Warnakulasuriya, Sudath S.P.; Matsudaira, Ko; Nyantumbu, Busisiwe; Sim, Malcolm R.; Harcombe, Helen; Cox, Ken; Marziale, Maria H.; Sarquis, Leila M.; Harari, Florencia; Freire, Rocio; Harari, Natalia; Monroy, Magda V.; Quintana, Leonardo A.; Rojas, Marianela; Salazar Vega, Eduardo J.; Harris, E. Clare; Serra, Consol; Martinez, J. Miguel; Delclos, George; Benavides, Fernando G.; Carugno, Michele; Ferrario, Marco M.; Pesatori, Angela C.; Chatzi, Leda; Bitsios, Panos; Kogevinas, Manolis; Oha, Kristel; Sirk, Tuuli; Sadeghian, Ali; Peiris-John, Roshini J.; Sathiakumar, Nalini; Wickremasinghe, A. Rajitha; Yoshimura, Noriko; Kelsall, Helen L.; Hoe, Victor C.W; Urquhart, Donna M.; Derrett, Sarah; McBride, David; Herbison, Peter; Gray, Andrew
2013-01-01
To explore definitions for multisite pain, and compare associations with risk factors for different patterns of musculoskeletal pain, we analysed cross-sectional data from the Cultural and Psychosocial Influences on Disability (CUPID) study. The study sample comprised 12,410 adults aged 20–59 years from 47 occupational groups in 18 countries. A standardised questionnaire was used to collect information about pain in the past month at each of 10 anatomical sites, and about potential risk factors. Associations with pain outcomes were assessed by Poisson regression, and characterised by prevalence rate ratios (PRRs). Extensive pain, affecting 6–10 anatomical sites, was reported much more frequently than would be expected if the occurrence of pain at each site were independent (674 participants vs 41.9 expected). In comparison with pain involving only 1–3 sites, it showed much stronger associations (relative to no pain) with risk factors such as female sex (PRR 1.6 vs 1.1), older age (PRR 2.6 vs 1.1), somatising tendency (PRR 4.6 vs 1.3), and exposure to multiple physically stressing occupational activities (PRR 5.0 vs 1.4). After adjustment for number of sites with pain, these risk factors showed no additional association with a distribution of pain that was widespread according to the frequently used American College of Rheumatology criteria. Our analysis supports the classification of pain at multiple anatomical sites simply by the number of sites affected, and suggests that extensive pain differs importantly in its associations with risk factors from pain that is limited to only a small number of anatomical sites. PMID:23727463
Revisiting the Table 2 fallacy: A motivating example examining preeclampsia and preterm birth.
Bandoli, Gretchen; Palmsten, Kristin; Chambers, Christina D; Jelliffe-Pawlowski, Laura L; Baer, Rebecca J; Thompson, Caroline A
2018-05-21
A "Table Fallacy," as coined by Westreich and Greenland, reports multiple adjusted effect estimates from a single model. This practice, which remains common in published literature, can be problematic when different types of effect estimates are presented together in a single table. The purpose of this paper is to quantitatively illustrate this potential for misinterpretation with an example estimating the effects of preeclampsia on preterm birth. We analysed a retrospective population-based cohort of 2 963 888 singleton births in California between 2007 and 2012. We performed a modified Poisson regression to calculate the total effect of preeclampsia on the risk of PTB, adjusting for previous preterm birth. pregnancy alcohol abuse, maternal education, and maternal socio-demographic factors (Model 1). In subsequent models, we report the total effects of previous preterm birth, alcohol abuse, and education on the risk of PTB, comparing and contrasting the controlled direct effects, total effects, and confounded effect estimates, resulting from Model 1. The effect estimate for previous preterm birth (a controlled direct effect in Model 1) increased 10% when estimated as a total effect. The risk ratio for alcohol abuse, biased due to an uncontrolled confounder in Model 1, was reduced by 23% when adjusted for drug abuse. The risk ratio for maternal education, solely a predictor of the outcome, was essentially unchanged. Reporting multiple effect estimates from a single model may lead to misinterpretation and lack of reproducibility. This example highlights the need for careful consideration of the types of effects estimated in statistical models. © 2018 John Wiley & Sons Ltd.
Airline Safety Improvement Through Experience with Near-Misses: A Cautionary Tale.
Madsen, Peter; Dillon, Robin L; Tinsley, Catherine H
2016-05-01
In recent years, the U.S. commercial airline industry has achieved unprecedented levels of safety, with the statistical risk associated with U.S. commercial aviation falling to 0.003 fatalities per 100 million passengers. But decades of research on organizational learning show that success often breeds complacency and failure inspires improvement. With accidents as rare events, can the airline industry continue safety advancements? This question is complicated by the complex system in which the industry operates where chance combinations of multiple factors contribute to what are largely probabilistic (rather than deterministic) outcomes. Thus, some apparent successes are realized because of good fortune rather than good processes, and this research intends to bring attention to these events, the near-misses. The processes that create these near-misses could pose a threat if multiple contributing factors combine in adverse ways without the intervention of good fortune. Yet, near-misses (if recognized as such) can, theoretically, offer a mechanism for continuing safety improvements, above and beyond learning gleaned from observable failure. We test whether or not this learning is apparent in the airline industry. Using data from 1990 to 2007, fixed effects Poisson regressions show that airlines learn from accidents (their own and others), and from one category of near-misses-those where the possible dangers are salient. Unfortunately, airlines do not improve following near-miss incidents when the focal event has no clear warnings of significant danger. Therefore, while airlines need to and can learn from certain near-misses, we conclude with recommendations for improving airline learning from all near-misses. © 2015 Society for Risk Analysis.
Moderating role of the MAOA genotype in antisocial behaviour
Fergusson, David M.; Boden, Joseph M.; Horwood, L. John; Miller, Allison; Kennedy, Martin A.
2012-01-01
Background Recent studies have examined gene×environment (G×E) interactions involving the monoamine oxidase A (MAOA) gene in moderating the associations between exposure to adversity and antisocial behaviour. The present study examined a novel method for assessing interactions between a single gene and multiple risk factors related to environmental and personal adversity. Aims To test the hypothesis that the presence of the low-activity MAOA genotype was associated with an increased response to a series of risk factors. Method Participants were 399 males from the Christchurch Health and Development Study who had complete data on: (a) MAOA promoter region variable number tandem repeat genotype; (b) antisocial behaviour (criminal offending) to age 30 and convictions to age 21; and (c) maternal smoking during pregnancy, IQ, childhood maltreatment and school failure. Results Poisson regression models were fitted to three antisocial behaviour outcomes (property/violent offending ages 15–30; and convictions ages 17–21), using measures of exposure to adverse childhood circumstances. The analyses revealed consistent evidence of G x E interactions, such that those with the low-activity MAOA variant who were exposed to adversity in childhood were significantly more likely to report offending in late adolescence and early adulthood. Conclusions The present findings add to the evidence suggesting that there is a stable G x E interaction involving MAOA, a range of adverse environmental and personal factors, and antisocial behaviour across the life course. These analyses also demonstrate the utility of using multiple environmental/personal exposures to test G×E interactions. PMID:22297589
Multiple Chronic Conditions and Hospitalizations Among Recipients of Long-Term Services and Supports
Van Cleave, Janet H.; Egleston, Brian L.; Abbott, Katherine M.; Hirschman, Karen B.; Rao, Aditi; Naylor, Mary D.
2016-01-01
Background Among older adults receiving long term-services and supports (LTSS), debilitating hospitalizations is a pervasive clinical and research problem. Multiple chronic conditions (MCC) are prevalent in LTSS recipients. However, the combination of MCC and diseases associated with hospitalizations of LTSS recipients is unclear. Objective The purpose of this analysis was to determine the association between classes of MCC in newly enrolled LTSS recipients and the number of hospitalizations over a one-year period following enrollment. Methods This report is based on secondary analysis of extant data from a longitudinal cohort study of 470 new recipients of LTSS, ages 60 years and older, receiving services in assisted living facilities, nursing homes, or through home- and community-based services. Using baseline chronic conditions reported in medical records, latent class analysis (LCA) was used to identify classes of MCC and posterior probabilities of membership in each class. Poisson regressions were used to estimate the relative ratio between posterior probabilities of class membership and number of hospitalizations during the 3 month period prior to the start of LTSS (baseline) and then every three months forward through 12 months. Results Three latent MCC-based classes named Cardiopulmonary, Cerebrovascular/Paralysis, and All Other Conditions were identified. The Cardiopulmonary class was associated with elevated numbers of hospitalization compared to the All Other Conditions class (relative ratio [RR] = 1.88, 95% CI [1.33, 2.65], p < .001). Conclusion Older LTSS recipients with a combination of MCCs that includes cardiopulmonary conditions have increased risk for hospitalization. PMID:27801713
Kauhl, Boris; Heil, Jeanne; Hoebe, Christian J P A; Schweikart, Jürgen; Krafft, Thomas; Dukers-Muijrers, Nicole H T M
2015-01-01
Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants. Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002-2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine local differences of the association between HCV risk and population-based determinants. HCV prevalence varied geographically and clustered in urban areas. The main population at risk were middle-aged males, non-western immigrants and divorced persons. Socio-economic determinants consisted of one-person households, persons with low income and mean property value. However, the association between HCV risk and demographic as well as socio-economic determinants displayed strong regional and intra-urban differences. The detection of local hotspots in our study may serve as a basis for prioritization of areas for future targeted interventions. Demographic and socio-economic determinants associated with HCV risk show regional differences underlining that a one-size-fits-all approach even within small geographic areas may not be appropriate. Future screening interventions need to consider the spatially varying association between HCV risk and associated demographic and socio-economic determinants.
Fractional Poisson Fields and Martingales
NASA Astrophysics Data System (ADS)
Aletti, Giacomo; Leonenko, Nikolai; Merzbach, Ely
2018-02-01
We present new properties for the Fractional Poisson process (FPP) and the Fractional Poisson field on the plane. A martingale characterization for FPPs is given. We extend this result to Fractional Poisson fields, obtaining some other characterizations. The fractional differential equations are studied. We consider a more general Mixed-Fractional Poisson process and show that this process is the stochastic solution of a system of fractional differential-difference equations. Finally, we give some simulations of the Fractional Poisson field on the plane.
On a Poisson homogeneous space of bilinear forms with a Poisson-Lie action
NASA Astrophysics Data System (ADS)
Chekhov, L. O.; Mazzocco, M.
2017-12-01
Let \\mathscr A be the space of bilinear forms on C^N with defining matrices A endowed with a quadratic Poisson structure of reflection equation type. The paper begins with a short description of previous studies of the structure, and then this structure is extended to systems of bilinear forms whose dynamics is governed by the natural action A\\mapsto B ABT} of the {GL}_N Poisson-Lie group on \\mathscr A. A classification is given of all possible quadratic brackets on (B, A)\\in {GL}_N× \\mathscr A preserving the Poisson property of the action, thus endowing \\mathscr A with the structure of a Poisson homogeneous space. Besides the product Poisson structure on {GL}_N× \\mathscr A, there are two other (mutually dual) structures, which (unlike the product Poisson structure) admit reductions by the Dirac procedure to a space of bilinear forms with block upper triangular defining matrices. Further generalisations of this construction are considered, to triples (B,C, A)\\in {GL}_N× {GL}_N× \\mathscr A with the Poisson action A\\mapsto B ACT}, and it is shown that \\mathscr A then acquires the structure of a Poisson symmetric space. Generalisations to chains of transformations and to the quantum and quantum affine algebras are investigated, as well as the relations between constructions of Poisson symmetric spaces and the Poisson groupoid. Bibliography: 30 titles.
Yates, Tuppett M.; Luthar, Suniya S.; Tracy, Allison J.
2015-01-01
This investigation examined process-level pathways to nonsuicidal self-injury (NSSI; e.g., self-cutting, -burning, -hitting) in 2 cohorts of suburban, upper-middle-class youths: a cross-sectional sample of 9th–12th graders (n = 1,036, 51.9% girls) on the West Coast and a longitudinal sample followed annually from the 6th through 12th grades (n = 245, 53.1% girls) on the East Coast. High rates of NSSI were found in both the cross-sectional (37.2%) and the longitudinal (26.1%) samples. Zero-inflated Poisson regression models estimated process-level pathways from perceived parental criticism to NSSI via youth-reported alienation toward parents. Pathways toward the initiation of NSSI were distinct from those accounting for its frequency. Parental criticism was associated with increased NSSI, and youth alienation toward parents emerged as a relevant process underlying this pathway, particularly for boys. The specificity of these pathways was explored by examining separate trajectories toward delinquent outcomes. The findings illustrate the prominence of NSSI among “privileged” youths, the salience of the caregiving environment in NSSI, the importance of parental alienation in explaining these relations, and the value of incorporating multiple systems in treatment approaches for adolescents who self-injure. PMID:18229983
Differences on Primary Care Labor Perceptions in Medical Students from 11 Latin American Countries
Mayta-Tristán, Percy; Montenegro-Idrogo, Juan José; Mejia, Christian R.; Abudinén A., Gabriel; Azucas-Peralta, Rita; Barrezueta-Fernandez, Jorge; Cerna-Urrutia, Luis; DaSilva-DeAbreu, Adrián; Mondragón-Cardona, Alvaro; Moya, Geovanna; Valverde-Solano, Christian D.; Theodorus-Villar, Rhanniel; Vizárraga-León, Maribel
2016-01-01
Background The shortage in Latin-American Primary Care (PC) workforce may be due to negative perceptions about it. These perceptions might be probably influenced by particular features of health systems and academic environments, thus varying between countries. Methods Observational, analytic and cross-sectional multicountry study that evaluated 9,561 first and fifth-year medical students from 63 medical schools of 11 Latin American countries through a survey. Perceptions on PC work was evaluated through a previously validated scale. Tertiles of the scores were created in order to compare the different countries. Crude and adjusted prevalence ratios were calculated using simple and multiple Poisson regression with robust variance. Results Approximately 53% of subjects were female; mean age was 20.4±2.9 years; 35.5% were fifth-year students. Statistically significant differences were found between the study subjects’ country, using Peru as reference. Students from Chile, Colombia, Mexico and Paraguay perceived PC work more positively, while those from Ecuador showed a less favorable position. No differences were found among perceptions of Bolivian, Salvadoran, Honduran and Venezuelan students when compared to their Peruvian peers. Conclusions Perceptions of PC among medical students from Latin America vary according to country. Considering such differences can be of major importance for potential local specific interventions. PMID:27414643
2014-01-01
Background Internet risk has been recognised as a child safety problem, but evidence is insufficient to conclude that a child’s online risk exposure can lead to physical harm. This study aims to explore the ecological relationship between Internet risk exposure and unnatural child death. Methods Multiple secondary data sources were used: online exposure to content about self-harm, cyberbullying, and Internet addiction data (EU Kids Online survey, 2010); and mortality data (European Detailed Mortality Database, 2010 or the latest year if not available) of 24 European countries. Correlations were found using quasi-Poisson regression. Countries’ prevalence rates of psychiatric problems (European Social Survey Round 3 and 6, 2006 and 2012) were used to test for possible spuriousness. Results This study finds that countries with higher rates of cyberbullying were more likely to have a higher incidence of unnatural child death. A 1 percent rise in the prevalence of cyberbullying translated into a 28% increase in risk of unnatural child death (95% CI: 2%-57%). No evidence was found to substantiate confounding effect of the national prevalence of depressive symptoms or traditional bullying. Conclusions Explanations are given for the findings. We conclude that intervention programs designed to serve as precautionary measures for risk minimisation should be considered. PMID:25079144
Yates, Tuppett M; Tracy, Allison J; Luthar, Suniya S
2008-02-01
This investigation examined process-level pathways to nonsuicidal self-injury (NSSI; e.g., self-cutting, -burning, -hitting) in 2 cohorts of suburban, upper-middle-class youths: a cross-sectional sample of 9th-12th graders (n = 1,036, 51.9% girls) on the West Coast and a longitudinal sample followed annually from the 6th through 12th grades (n = 245, 53.1% girls) on the East Coast. High rates of NSSI were found in both the cross-sectional (37.2%) and the longitudinal (26.1%) samples. Zero-inflated Poisson regression models estimated process-level pathways from perceived parental criticism to NSSI via youth-reported alienation toward parents. Pathways toward the initiation of NSSI were distinct from those accounting for its frequency. Parental criticism was associated with increased NSSI, and youth alienation toward parents emerged as a relevant process underlying this pathway, particularly for boys. The specificity of these pathways was explored by examining separate trajectories toward delinquent outcomes. The findings illustrate the prominence of NSSI among "privileged" youths, the salience of the caregiving environment in NSSI, the importance of parental alienation in explaining these relations, and the value of incorporating multiple systems in treatment approaches for adolescents who self-injure.
Schwab-Reese, Laura M; Schafer, Ellen J; Ashida, Sato
2017-07-01
Poor maternal mental health during the postpartum period can have significant effects on the health of mothers, infants, and families. The findings from cross-sectional studies suggest that stress and social support are related to maternal mental health. This study contributes to the literature through the use of longitudinal data, and examines moderation and mediation among these factors. In 2012-2013, mothers completed surveys assessing stress, social support, and depressive and anxiety symptoms following birth (n = 125), and 3 months (n = 110) and 6 months (n = 99) after birth. The authors examined temporal associations, moderation, and mediation of social support on the relationship between stress and postpartum depressive and anxiety symptoms using modified Poisson regression models and the counterfactual approach to mediation. Current levels of stress and social support were associated with depressive and anxiety symptoms, both independently and when considered together at multiple time points. Social support did not strongly moderate or mediate the relationships between stress and maternal mental health. Interventions to reduce current perceptions of stress and increase social support for mothers during the postpartum period may help improve maternal mental health symptoms. Efforts are needed to assess the current needs of mothers continuously.
Silveira, Erika Aparecida; Santos, Annelisa Silva E Alves de Carvalho; Falco, Marianne de Oliveira; Cardoso, Rodrigo de Castro; Vitorino, Priscila Valverde de Oliveira
2018-08-01
The aim of this study was to determine the prevalence of physical inactivity and whether it is associated with sociodemographic, lifestyle, clinical, anthropometric, and body composition variables in people living with HIV/AIDS (PLWHA). This study makes use of data from a cohort of 288 adults aged ≥19 years, conducted between October 2009 and July 2011. The variables studied were sex, age, education, income, skin color, tobacco use, alcohol intake, body mass index, body fat percentage, waist circumference, and waist-hip ratio, length of HIV/AIDS diagnosis, use of antiretroviral therapy and length of its use, CD4, hypertension (HT) and diabetes mellitus. Physical inactivity was defined as a score below 600 metabolic equivalent minutes/week according to the International Physical Activity Questionnaire - Short Version. Poisson multiple regression was applied in the multivariate analysis with a significance level of 5%. The prevalence of physical inactivity was 44.1%. Education of ≤4 years of study (prevalence ratio [PR]: 1.71) and HT (PR: 1.49) were associated with physical inactivity. Physical inactivity was highly prevalent in PLWHA and associated with low educational level and HT. We highlight the simultaneous association between two cardiometabolic risk factors, HT and physical inactivity.
Anderson, Craig L.
2009-01-01
Objectives. We estimated the effectiveness of child restraints in preventing death during motor vehicle collisions among children 3 years or younger. Methods. We conducted a matched cohort study using Fatality Analysis Reporting System data from 1996 to 2005. We estimated death risk ratios using conditional Poisson regression, bootstrapping, multiple imputation, and a sensitivity analysis of misclassification bias. We examined possible effect modification by selected factors. Results. The estimated death risk ratios comparing child safety seats with no restraint were 0.27 (95% confidence interval [CI] = 0.21, 0.34) for infants, 0.24 (95% CI = 0.19, 0.30) for children aged 1 year, 0.40 (95% CI = 0.32, 0.51) for those aged 2 years, and 0.41 (95% CI = 0.33, 0.52) for those aged 3 years. Estimated safety seat effectiveness was greater during rollover collisions, in rural environments, and in light trucks. We estimated seat belts to be as effective as safety seats in preventing death for children aged 2 and 3 years. Conclusions. Child safety seats are highly effective in reducing the risk of death during severe traffic collisions and generally outperform seat belts. Parents should be encouraged to use child safety seats in favor of seat belts. PMID:19059860
Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando H; Montesinos-López, José C; Singh, Pawan; Juliana, Philomin; Salinas-Ruiz, Josafhat
2017-05-05
When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait at a time taking into account genotype × environment interaction (G × E), because there is a lack of comprehensive models that simultaneously take into account the correlated counting traits and G × E. For this reason, in this study we propose a multiple-trait and multiple-environment model for count data. The proposed model was developed under the Bayesian paradigm for which we developed a Markov Chain Monte Carlo (MCMC) with noninformative priors. This allows obtaining all required full conditional distributions of the parameters leading to an exact Gibbs sampler for the posterior distribution. Our model was tested with simulated data and a real data set. Results show that the proposed multi-trait, multi-environment model is an attractive alternative for modeling multiple count traits measured in multiple environments. Copyright © 2017 Montesinos-López et al.
Moineddin, Rahim; Meaney, Christopher; Agha, Mohammad; Zagorski, Brandon; Glazier, Richard Henry
2011-08-19
Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research. Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of increased emergency department utilization. Six different multiple regression models for count data were fitted to assess the influence of predictors on demand for emergency department services, including: Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial. Comparison of competing models was assessed by the Vuong test statistic. The CCHS cycle 2.1 respondents were a roughly equal mix of males (50.4%) and females (49.6%). The majority (86.2%) were young-middle aged adults between the ages of 20-64, living in predominantly urban environments (85.9%), with mid-high household incomes (92.2%) and well-educated, receiving at least a high-school diploma (84.1%). Many participants reported no chronic disease (51.9%), fell into a small number (0-5) of ambulatory diagnostic groups (62.3%), and perceived their health status as good/excellent (88.1%); however, were projected to have high Resource Utilization Band levels of health resource utilization (68.2%). These factors were largely stable for CCHS cycle 3.1 respondents. Factors influencing demand for emergency department services varied according to the severity of triage scores at initial presentation. For example, although a non-significant predictor of the odds of emergency department utilization in high severity cases, access to a primary care physician was a statistically significant predictor of the likelihood of emergency department utilization (OR: 0.69; 95% CI OR: 0.63-0.75) and the rate of emergency department utilization (RR: 0.57; 95% CI RR: 0.50-0.66) in low severity cases. Using a theoretically appropriate hurdle negative binomial regression model this unique study illustrates that access to a primary care physician is an important predictor of both the odds and rate of emergency department utilization in Ontario. Restructuring primary care services, with aims of increasing access to undersupplied populations may result in decreased emergency department utilization rates by approximately 43% for low severity triage level cases.
Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki
2014-12-01
This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.
Ugarte-Gil, M F; Gamboa-Cárdenas, R V; Zevallos, F; Medina, M; Cucho-Venegas, J M; Perich-Campos, R A; Alfaro-Lozano, J L; Rodriguez-Bellido, Z; Alarcón, G S; Pastor-Asurza, C A
2014-09-01
to determine whether prolactin levels are independently associated with disease damage in systemic lupus erythematosus (SLE) patients. these cross-sectional analyses were conducted in SLE patient members of the Almenara Lupus Cohort who were seen between January 2012 and June 2013. Disease damage was ascertained with the System Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) damage index (SDI). Prolactin was measured in ng/ml. The association between prolactin levels and the SDI (total and its domains) was evaluated using Spearman's correlation. Subsequently, adjusted Poisson regression models were performed to evaluate these associations. 160 patients were included. 147 (91.9%) were female; their median age at diagnosis was 33.4 (interquartile range (IQR): 26.0-44.3) years; their disease duration was 5.5 (IQR: 2.6-9.7) years. The median prolactin value was 16.8 (IQR: 11.8-24.5) ng/ml. After adjusting for confounders in the Poisson regression model the estimated rate ratios (RR) and 95% confidence interval (CI) for each 10 ng/ml increment of prolactin were 1.13 (95% CI 1.60-1.20, p<0.001) for the total SDI score, 1.15 (1.03-1.28, p=0.003) for the renal domain and 1.41 (1.11-1.79, p=0.003) for the cardiac/peripheral vascular domains. there was a positive association between prolactin levels and the SDI (overall and its renal and cardiac/peripheral vascular domains), independently of other well-known risk factors. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
Sight Impairment registration due to stroke-A small yet significant rise?
Bunce, Catey; Zekite, Antra; Wormald, Richard; Rowe, Fiona
2017-12-01
In the United Kingdom, when an individual's sight falls to and remains at a certain threshold, they may be offered registration as sight impaired. Recent analysis of causes of registrable sight impairment in England/Wales indicated that visual impairment due to stroke had increased as a proportionate cause of sight loss. We aim to assess whether there is evidence of an increase in incidence of certification for sight impairment due to stroke in England/Wales between 2008 and 2014. The number of certifications with a main cause of sight impairment being stroke was obtained from the Certifications Office London. Directly standardized rates per 100,000 were computed with 95% confidence intervals and examined. Poisson regression was used to assess evidence of trend over time. In the year ending 31st March 2008, 992 people were newly certified with stroke with an estimated DSR of 2.1 (2.0 to 2.2) per 100,000 persons at risk. In the year ending March 31st 2014, there were 1310 certifications with a DSR of 2.5 (2.4 to 2.7). Figures were higher for men than women. Poisson regression indicated an estimated incidence rate ratio of 1.03 per year with 95% confidence intervals of 1.028 to 1.051, P < .001. These data suggest a small but statistically significant increase in the incidence of certifiable visual impairment due to stroke between 2008 and 2014. Figures are, however, considerably lower than estimated, perhaps suggesting that more should be done to address the visual needs of those who have suffered stroke.
Datamining approaches for modeling tumor control probability.
Naqa, Issam El; Deasy, Joseph O; Mu, Yi; Huang, Ellen; Hope, Andrew J; Lindsay, Patricia E; Apte, Aditya; Alaly, James; Bradley, Jeffrey D
2010-11-01
Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.
NASA Astrophysics Data System (ADS)
Zhang, Xinchang; Zhong, Shanshan; Wu, Zhiwei; Li, Yun
2017-06-01
This study investigates the typhoon genesis frequency (TGF) in the dominant season (July to October) in Western North Pacific (WNP) using observed data in 1965-2015. Of particular interest is the predictability of the TGF and associated preseason sea surface temperature (SST) in the Pacific. It is found that, the TGF is positively related to a tri-polar pattern of April SST anomalies in North Pacific (NP{T}_{Apr}), while it is negatively related to SST anomalies over the Coral Sea (CSS{T}_{Apr}) off east coast of Australia. The NP{T}_{Apr} leads to large anomalous cyclonic circulation over North Pacific. The anomalous southwesterly weakens the northeast trade wind, decreases evaporation, and induces warm water in central tropical North Pacific. As such, the warming effect amplifies the temperature gradient in central tropical North Pacific, which in turn maintains the cyclonic wind anomaly in the west tropical Pacific, which favors the typhoon genesis in WNP. In the South Pacific, the CSS{T}_{Apr} supports the typhoon formation over the WNP by (a) strengthening the cross-equatorial flows and enhancing the Inter-tropical Convergence Zone; (b) weakening southeast and northeast trade wind, and keeping continuous warming in the center of tropical Pacific. The influence of both NP{T}_{Apr} and CSS{T}_{Apr} can persistently affect the zonal wind in the tropical Pacific and induce conditions favorable for the typhoon genesis in the typhoon season. A Poisson regression model using NP{T}_{Apr} and CSS}{T}_{Apr} is developed to predict the TGF and a promising skill is achieved.
Spatial variation of pneumonia hospitalization risk in Twin Cities metro area, Minnesota.
Iroh Tam, P Y; Krzyzanowski, B; Oakes, J M; Kne, L; Manson, S
2017-11-01
Fine resolution spatial variability in pneumonia hospitalization may identify correlates with socioeconomic, demographic and environmental factors. We performed a retrospective study within the Fairview Health System network of Minnesota. Patients 2 months of age and older hospitalized with pneumonia between 2011 and 2015 were geocoded to their census block group, and pneumonia hospitalization risk was analyzed in relation to socioeconomic, demographic and environmental factors. Spatial analyses were performed using Esri's ArcGIS software, and multivariate Poisson regression was used. Hospital encounters of 17 840 patients were included in the analysis. Multivariate Poisson regression identified several significant associations, including a 40% increased risk of pneumonia hospitalization among census block groups with large, compared with small, populations of ⩾65 years, a 56% increased risk among census block groups in the bottom (first) quartile of median household income compared to the top (fourth) quartile, a 44% higher risk in the fourth quartile of average nitrogen dioxide emissions compared with the first quartile, and a 47% higher risk in the fourth quartile of average annual solar insolation compared to the first quartile. After adjusting for income, moving from the first to the second quartile of the race/ethnic diversity index resulted in a 21% significantly increased risk of pneumonia hospitalization. In conclusion, the risk of pneumonia hospitalization at the census-block level is associated with age, income, race/ethnic diversity index, air quality, and solar insolation, and varies by region-specific factors. Identifying correlates using fine spatial analysis provides opportunities for targeted prevention and control.
Jenkins, Lucille; Webb, Theresa; Browne, Nick; Afifi, A A; Kraus, Jess
2005-05-01
The purpose of this study was to determine whether the Motion Picture Association of America's ratings system distinguishes among the 3 primary rating categories (PG, PG-13, and R) with respect to violence based on a study of the 100 top-grossing films of 1994. The Motion Picture Association of America assigns age-based ratings for every film that is released in the United States accompanied by the reasons for the rating. A data abstraction instrument was designed to code each act of violence within the sample of 100 films. A series of Poisson regression models were used to examine the association among rating, seriousness of violence, and primary reason for the rating assignment. The total average number of violent acts within each film by rating category increased from PG (14) to PG-13 (20) to R (32). However, using results from the Poisson models, it is clear that the rating does not predict the frequency of violence in films. For all 3 rating categories, the predicted number of violent acts is almost identical for films with violence as a primary descriptor and films with the highest level of seriousness (R = 62.4 acts, PG-13 = 55.2 acts, and PG = 56.1 acts). The regression analysis shows that the rating does not predict the frequency of violence that occurs in films. Frequency of violence alone is not the most important criterion for the assignment of rating. The content descriptors and average seriousness of films are better measures of the violence than rating assignment.
Yen, A M-F; Liou, H-H; Lin, H-L; Chen, T H-H
2006-01-01
The study aimed to develop a predictive model to deal with data fraught with heterogeneity that cannot be explained by sampling variation or measured covariates. The random-effect Poisson regression model was first proposed to deal with over-dispersion for data fraught with heterogeneity after making allowance for measured covariates. Bayesian acyclic graphic model in conjunction with Markov Chain Monte Carlo (MCMC) technique was then applied to estimate the parameters of both relevant covariates and random effect. Predictive distribution was then generated to compare the predicted with the observed for the Bayesian model with and without random effect. Data from repeated measurement of episodes among 44 patients with intractable epilepsy were used as an illustration. The application of Poisson regression without taking heterogeneity into account to epilepsy data yielded a large value of heterogeneity (heterogeneity factor = 17.90, deviance = 1485, degree of freedom (df) = 83). After taking the random effect into account, the value of heterogeneity factor was greatly reduced (heterogeneity factor = 0.52, deviance = 42.5, df = 81). The Pearson chi2 for the comparison between the expected seizure frequencies and the observed ones at two and three months of the model with and without random effect were 34.27 (p = 1.00) and 1799.90 (p < 0.0001), respectively. The Bayesian acyclic model using the MCMC method was demonstrated to have great potential for disease prediction while data show over-dispersion attributed either to correlated property or to subject-to-subject variability.
A comprehensive review of prehospital and in-hospital delay times in acute stroke care.
Evenson, K R; Foraker, R E; Morris, D L; Rosamond, W D
2009-06-01
The purpose of this study was to systematically review and summarize prehospital and in-hospital stroke evaluation and treatment delay times. We identified 123 unique peer-reviewed studies published from 1981 to 2007 of prehospital and in-hospital delay time for evaluation and treatment of patients with stroke, transient ischemic attack, or stroke-like symptoms. Based on studies of 65 different population groups, the weighted Poisson regression indicated a 6.0% annual decline (P<0.001) in hours/year for prehospital delay, defined from symptom onset to emergency department arrival. For in-hospital delay, the weighted Poisson regression models indicated no meaningful changes in delay time from emergency department arrival to emergency department evaluation (3.1%, P=0.49 based on 12 population groups). There was a 10.2% annual decline in hours/year from emergency department arrival to neurology evaluation or notification (P=0.23 based on 16 population groups) and a 10.7% annual decline in hours/year for delay time from emergency department arrival to initiation of computed tomography (P=0.11 based on 23 population groups). Only one study reported on times from arrival to computed tomography scan interpretation, two studies on arrival to drug administration, and no studies on arrival to transfer to an in-patient setting, precluding generalizations. Prehospital delay continues to contribute the largest proportion of delay time. The next decade provides opportunities to establish more effective community-based interventions worldwide. It will be crucial to have effective stroke surveillance systems in place to better understand and improve both prehospital and in-hospital delays for acute stroke care.
Escobedo, Angel A; Almirall, Pedro; Rumbaut, Raisa; Rodríguez-Morales, Alfonso J
2015-01-01
Climate change and variability are common phenomena affecting various infectious diseases. Many studies have been performed on vector-borne diseases; however, few studies have addressed such influences on intestinal parasitic diseases (e.g., giardiasis). In this study, using nonlinear Poisson regression models, we assessed the potential associations between macroclimatic variation and giardiasis cases in children and school workers from three provinces of Cuba in the context of large sampling and parasitological assessment. Between 2010 and 2012, 293,019 subjects were assessed, resulting in 6357 positive for Giardia (216.95 cases/10,000 pop.; 95%CI 211.7-222.2). The variation in time for those giardiasis rates ranged from 35.8 to 525.8 cases/10,000 pop. Nonlinear Poisson regression models between the ONI index and the giardiasis incidence indicated a significant association (p<0.01). With lower values of ONI, lower incidence of giardiasis was observed at Havana (pseudo r(2)=0.0576; p<0.001) and Guantánamo (pseudo r(2)=0.0376; p<0.001). Although these results are preliminary and the magnitude of association is not higher, the results were of statistical significance. This result indicates the need to assess in detail in further studies the impact of additional macroclimatic and microclimatic variables on the epidemiology of this still important intestinal parasitic disease, not only in Cuba but also in other countries of the Caribbean and Latin American region. Copyright © 2014 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.
Taracido Trunk, M; Figueiras, A; Castro Lareo, I
1999-01-01
In the Autonomous Region of Galicia, no study has been made of the impacts of air pollution on human health, despite the fact that several of its major cities have moderate levels of pollution. Therefore, we have considered the need of making this study in the city of Vigo. The main objective of this analysis is that of analyzing the short-term impact of air pollution on the daily death rate for all reasons in the city of Vigo throughout the 1991-1994 period, by using the procedure for analysis set out as part of the EMECAM Project. The daily fluctuations in the number of deaths for all causes with the exception of the external ones are listed with the daily fluctuations of sulfur dioxide and particles using Poisson regression models. A non-parametric model is also used in order to better control the confusion variables. Using the Poisson regression model, no significant relationships have been found to exist between the pollutants and the death rate. In the non-parametric model, a relationship was found between the concentration of particles on the day immediately prior to the date of death and the death rate, an effect which remains unchanged on including the autoregressive terms. Particle-based air pollution is a health risk despite the average levels of this pollutant falling within the air quality guideline levels in the city of Vigo.
Berlin, Claudia; Busato, André; Rosemann, Thomas; Djalali, Sima; Maessen, Maud
2014-07-03
Avoidable hospitalizations (AH) are hospital admissions for diseases and conditions that could have been prevented by appropriate ambulatory care. We examine regional variation of AH in Switzerland and the factors that determine AH. We used hospital service areas, and data from 2008-2010 hospital discharges in Switzerland to examine regional variation in AH. Age and sex standardized AH were the outcome variable, and year of admission, primary care physician density, medical specialist density, rurality, hospital bed density and type of hospital reimbursement system were explanatory variables in our multilevel poisson regression. Regional differences in AH were as high as 12-fold. Poisson regression showed significant increase of all AH over time. There was a significantly lower rate of all AH in areas with more primary care physicians. Rates increased in areas with more specialists. Rates of all AH also increased where the proportion of residences in rural communities increased. Regional hospital capacity and type of hospital reimbursement did not have significant associations. Inconsistent patterns of significant determinants were found for disease specific analyses. The identification of regions with high and low AH rates is a starting point for future studies on unwarranted medical procedures, and may help to reduce their incidence. AH have complex multifactorial origins and this study demonstrates that rurality and physician density are relevant determinants. The results are helpful to improve the performance of the outpatient sector with emphasis on local context. Rural and urban differences in health care delivery remain a cause of concern in Switzerland.
Shimaponda-Mataa, Nzooma M; Tembo-Mwase, Enala; Gebreslasie, Michael; Achia, Thomas N O; Mukaratirwa, Samson
2017-11-01
Although malaria morbidity and mortality are greatly reduced globally owing to great control efforts, the disease remains the main contributor. In Zambia, all provinces are malaria endemic. However, the transmission intensities vary mainly depending on environmental factors as they interact with the vectors. Generally in Africa, possibly due to the varying perspectives and methods used, there is variation on the relative importance of malaria risk determinants. In Zambia, the role climatic factors play on malaria case rates has not been determined in combination of space and time using robust methods in modelling. This is critical considering the reversal in malaria reduction after the year 2010 and the variation by transmission zones. Using a geoadditive or structured additive semiparametric Poisson regression model, we determined the influence of climatic factors on malaria incidence in four endemic provinces of Zambia. We demonstrate a strong positive association between malaria incidence and precipitation as well as minimum temperature. The risk of malaria was 95% lower in Lusaka (ARR=0.05, 95% CI=0.04-0.06) and 68% lower in the Western Province (ARR=0.31, 95% CI=0.25-0.41) compared to Luapula Province. North-western Province did not vary from Luapula Province. The effects of geographical region are clearly demonstrated by the unique behaviour and effects of minimum and maximum temperatures in the four provinces. Environmental factors such as landscape in urbanised places may also be playing a role. Copyright © 2017 Elsevier B.V. All rights reserved.
Xie, Bing; Nguyen, Trung Hai; Minh, David D. L.
2017-01-01
We demonstrate the feasibility of estimating protein-ligand binding free energies using multiple rigid receptor configurations. Based on T4 lysozyme snapshots extracted from six alchemical binding free energy calculations with a flexible receptor, binding free energies were estimated for a total of 141 ligands. For 24 ligands, the calculations reproduced flexible-receptor estimates with a correlation coefficient of 0.90 and a root mean square error of 1.59 kcal/mol. The accuracy of calculations based on Poisson-Boltzmann/Surface Area implicit solvent was comparable to previously reported free energy calculations. PMID:28430432
NASA Technical Reports Server (NTRS)
Tannenbaum, M. J.
1994-01-01
The concept of "Intermittency" was introduced by Bialas and Peschanski to try to explain the "large" fluctuations of multiplicity in restricted intervals of rapidity or pseudorapidity. A formalism was proposed to to study non-statistical (more precisely, non-Poisson) fluctuations as a function of the size of rapidity interval, and it was further suggested that the "spikes" in the rapidity fluctuations were evidence of fractal or intermittent behavior, in analogy to turbulence in fluid dynamics which is characterized by self-similar fluctuations at all scales-the absence of well defined scale of length.
ERIC Educational Resources Information Center
Shear, Benjamin R.; Zumbo, Bruno D.
2013-01-01
Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…
Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis
ERIC Educational Resources Information Center
Williams, Ryan T.
2012-01-01
Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…
John W. Edwards; Susan C. Loeb; David C. Guynn
1994-01-01
Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...
On the Singularity of the Vlasov-Poisson System
DOE Office of Scientific and Technical Information (OSTI.GOV)
and Hong Qin, Jian Zheng
2013-04-26
The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker- Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency v approaches zero. However, we show that the colllisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the approaching zero from the positive side.
On the singularity of the Vlasov-Poisson system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Jian; Qin, Hong; Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08550
2013-09-15
The Vlasov-Poisson system can be viewed as the collisionless limit of the corresponding Fokker-Planck-Poisson system. It is reasonable to expect that the result of Landau damping can also be obtained from the Fokker-Planck-Poisson system when the collision frequency ν approaches zero. However, we show that the collisionless Vlasov-Poisson system is a singular limit of the collisional Fokker-Planck-Poisson system, and Landau's result can be recovered only as the ν approaches zero from the positive side.
Building Regression Models: The Importance of Graphics.
ERIC Educational Resources Information Center
Dunn, Richard
1989-01-01
Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)
Testing Different Model Building Procedures Using Multiple Regression.
ERIC Educational Resources Information Center
Thayer, Jerome D.
The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…
Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.
ERIC Educational Resources Information Center
Smith, Kent W.; Sasaki, M. S.
1979-01-01
A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)
Gurung, Arun Bahadur; Aguan, Kripamoy; Mitra, Sivaprasad; Bhattacharjee, Atanu
2017-06-01
In Alzheimer's disease (AD), the level of Acetylcholine (ACh) neurotransmitter is reduced. Since Acetylcholinesterase (AChE) cleaves ACh, inhibitors of AChE are very much sought after for AD treatment. The side effects of current inhibitors necessitate development of newer AChE inhibitors. Isoalloxazine derivatives have proved to be promising (AChE) inhibitors. However, their structure-activity relationship studies have not been reported till date. In the present work, various quantitative structure-activity relationship (QSAR) building methods such as multiple linear regression (MLR), partial least squares ,and principal component regression were employed to derive 3D-QSAR models using steric and electrostatic field descriptors. Statistically significant model was obtained using MLR coupled with stepwise selection method having r 2 = .9405, cross validated r 2 (q 2 ) = .6683, and a high predictability (pred_r 2 = .6206 and standard error, pred_r 2 se = .2491). Steric and electrostatic contribution plot revealed three electrostatic fields E_496, E_386 and E_577 and one steric field S_60 contributing towards biological activity. A ligand-based 3D-pharmacophore model was generated consisting of eight pharmacophore features. Isoalloxazine derivatives were docked against human AChE, which revealed critical residues implicated in hydrogen bonds as well as hydrophobic interactions. The binding modes of docked complexes (AChE_IA1 and AChE_IA14) were validated by molecular dynamics simulation which showed their stable trajectories in terms of root mean square deviation and molecular mechanics/Poisson-Boltzmann surface area binding free energy analysis revealed key residues contributing significantly to overall binding energy. The present study may be useful in the design of more potent Isoalloxazine derivatives as AChE inhibitors.
Xirasagar, Sudha; Chung, Shiu-Dong; Tsai, Ming-Chieh; Chen, Chao-Hung
2017-01-01
Patients with gastroesophageal reflux disease (GERD) present with comorbid complications with implications for healthcare utilization. To date, little is known about the effects of GERD treatment with a proton-pump inhibitor (PPI) on patients’ subsequent healthcare utilization for acute respiratory infections (ARIs). This population-based study compared ARI episodes captured through outpatient visits, one year before and one year after GERD patients received PPI treatment. We used retrospective data from the Longitudinal Health Insurance Database 2005 in Taiwan, comparing 21,486 patients diagnosed with GERD from 2010 to 2012 with 21,486 age-sex matched comparison patients without GERD. Annual ARI episodes represented by ambulatory care visits for ARI (visits during a 7-day period bundled into one episode), were compared between the patient groups during the 1-year period before and after the index date (date of GERD diagnosis for study patients, first ambulatory visit in the same year for their matched comparison counterpart). Multiple regression analysis using a difference-in-difference approach was performed to estimate the adjusted association between GERD treatment and the subsequent annual ARI rate. We found that the mean annual ARI episode rate among GERD patients reduced by 11.4%, from 4.39 before PPI treatment, to 3.89 following treatment (mean change = -0.5 visit, 95% confidence interval (CI) = (-0.64, -0.36)). In Poisson regression analysis, GERD treatment showed an independent association with the annual ARI rate, showing a negative estimate (with p<0.001). The study suggests that GERD treatment with PPIs may help reduce healthcare visits for ARIs, highlighting the importance of treatment-seeking by GERD patients and compliance with treatment. PMID:28222168
The cumulative effect of air pollutants on the acute exacerbation of COPD in Shanghai, China.
Sun, Xian Wen; Chen, Pei Li; Ren, Lei; Lin, Ying Ni; Zhou, Jian Ping; Ni, Lei; Li, Qing Yun
2018-05-01
Epidemiologic studies have shown the effect of air pollutants on acute exacerbation of chronic obstructive pulmonary disease (AECOPD). However, little is known regarding the dose-response relationship. This study aimed to investigate the cumulative effect of air pollutants on AECOPD. We collected 101 patients with AECOPD from November 2010 through August 2011 in Shanghai. Multiple logistic regression was used to estimate associations between air pollutants and AECOPD. Poisson regression was then applied to determine the cumulative effect of air pollutants including particulate matter 10 (PM10), PM2.5, nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ) and ozone (O 3 ) on AECOPD, of which the seasonal variation was further explored. The monthly episodes of AECOPD were associated with the concentrations of PM2.5 (r=0.884, p<0.05) and NO 2 (r=0.763, p<0.05). The cutoff value of PM2.5 and NO 2 for predicting AECOPD was 83.0μg/m 3 and 53.5μg/m 3 , respectively. It showed that per 10μg/m 3 increment in PM2.5 increased the relative risks (RR) for AECOPD was 1.09 with 3days cumulative effect in cold season, whereas 7days in warm season. The RR for AECOPD for per 10μg/m 3 increment in NO 2 was 1.07, with a 5-day cumulative effect without seasonal variation. High consecutive levels of PM2.5 and NO 2 increase the risk of developing AECOPD. Cumulative effect of PM2.5 and NO 2 appears before the exacerbation onset. These gradations were more evident in the PM2.5 during different seasons. Copyright © 2017 Elsevier B.V. All rights reserved.
Personality traits as an endophenotype in genetic studies on suicidality in bipolar disorder.
Pawlak, J; Dmitrzak-Węglarz, M; Maciukiewicz, M; Kapelski, P; Czerski, P; Leszczyńska-Rodziewicz, A; Zaremba, D; Hauser, J
2017-04-01
Introduction The influence of personality traits on suicidal behaviour risk has been well documented. Personality traits and suicidal behaviour are partially genetically determined and personality has been described as an endophenotype of suicidal behaviour. The aim of this study was to investigate a possible association between personality traits with suicidal behaviour and selected serotonergic gene polymorphisms. In the study we included 156 patients meeting DSM-IV criteria for bipolar disorder (BP) and 93 healthy controls. The personality dimensions were assessed using the Temperament and Character Inventory (TCI). We genotyped two selected polymorphisms of the tryptophan hydroxylase 1 (TPH1) gene (rs1800532 218A>C and rs1799913 779A>C) and polymorphism in the promoter region of serotonin transporter gene (5-HTTLPR, rs25531) related to serotoninergic neurotransmission. Multiple poisson regression, logistic regression and Kruskal-Wallis tests were applied. We found numerous differences between the BP patients and the control group in terms of their TCI dimensions/subdimensions. Significant differences were found between patients with, and without, suicidal attempts in fatigability and asthenia (Ha4), as well as in harm avoidance (Ha). We also found that the interactions between TCI subdimensions (the interaction of disordiness (Ns4) and spiritual acceptance (St3), disordiness (Ns4) and integrated conscience (C5), extravagance (Ns3) and resourcefulness (Sd3)) were significantly contributing for suicidal behaviour risk. We found association between all studied genetic polymorphisms and several TCI dimensions and subdimensions. Our results confirm that personality traits are partially determined by genes. Both personality traits and the interactions between temperament and character traits, may be helpful in predicting suicidal behaviour.
Child abuse and work stress in adulthood: Evidence from a population-based study.
Sampasa-Kanyinga, Hugues; Nilsen, Wendy; Colman, Ian
2018-03-01
The objective of this study was to examine the association between child abuse and work stress in adulthood. We used data from the 2012 Canadian Community Health Survey (CCHS) Mental Health, a nationally representative cross-sectional survey of Canadians. This study included all participants aged 20years or older who reported being employed the past 12months (N=14,581). Child physical abuse, sexual abuse, and exposure to intimate partner violence were assessed in relation to several work stress-related indicators. Multiple linear and Poisson regression models adjusted for age, sex, education, household income, marital status, occupation group, and any lifetime mental disorder. Child abuse was significantly associated with greater odds of high work stress (IRR: 1.29; 95% CI: 1.16-1.43) in adulthood. More specifically, child abuse was associated with greater odds of job dissatisfaction (IRR: 1.69; 95% CI: 1.31-2.18), job insecurity (IRR: 1.56; 95% CI: 1.27-1.91), and self-perceived low support (IRR: 1.33; 95% CI: 1.22-1.46). It was also associated with high levels of psychological demand (b=0.348; 95% CI: 0.229-0.467) and job strain (b=0.031; 95% CI: 0.019-0.043). Examination of the Karasek's Demand-Control Model using multinomial logistic regression analyses indicated that child abuse was significantly associated with high strain (RRR:1.39; 95% CI: 1.14-1.72) and active (RRR: 1.56; 95% CI: 1.28-1.90) jobs. These findings suggest the negative influence of child abuse on work experience. Success in preventing child abuse may help reduce work-related stress in adulthood. Copyright © 2017 Elsevier Inc. All rights reserved.
Ostro, Bart; Feng, Wen-Ying; Broadwin, Rachel; Green, Shelley; Lipsett, Michael
2007-01-01
Several epidemiologic studies provide evidence of an association between daily mortality and particulate matter < 2.5 pm in diameter (PM2.5). Little is known, however, about the relative effects of PM2.5 constituents. We examined associations between 19 PM2.5 components and daily mortality in six California counties. We obtained daily data from 2000 to 2003 on mortality and PM2.5 mass and components, including elemental and organic carbon (EC and OC), nitrates, sulfates, and various metals. We examined associations of PM2.5 and its constituents with daily counts of several mortality categories: all-cause, cardiovascular, respiratory, and mortality age > 65 years. Poisson regressions incorporating natural splines were used to control for time-varying covariates. Effect estimates were determined for each component in each county and then combined using a random-effects model. PM2.5 mass and several constituents were associated with multiple mortality categories, especially cardiovascular deaths. For example, for a 3-day lag, the latter increased by 1.6, 2.1, 1.6, and 1.5% for PM2.5, EC, OC, and nitrates based on interquartile ranges of 14.6, 0.8, 4.6, and 5.5 pg/m(3), respectively. Stronger associations were observed between mortality and additional pollutants, including sulfates and several metals, during the cool season. This multicounty analysis adds to the growing body of evidence linking PM2.5 with mortality and indicates that excess risks may vary among specific PM2.5 components. Therefore, the use of regression coefficients based on PM2.5 mass may underestimate associations with some PM2.5 components. Also, our findings support the hypothesis that combustion-associated pollutants are particularly important in California.
Jilcott Pitts, Stephanie B; Wu, Qiang; McGuirt, Jared T; Crawford, Thomas W; Keyserling, Thomas C; Ammerman, Alice S
2013-11-01
We examined associations between access to food venues (farmers’ markets and supermarkets), shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, U.S.A. Access to food venues was measured using a Geographic Information System incorporating distance, seasonality and business hours, to quantify access to farmers’ markets. Produce consumption was assessed by self-report of eating five or more fruits and vegetables daily. BMI and blood pressure were assessed by clinical measurements. Poisson regression with robust variance was used for dichotomous outcomes and multiple linear regression was used for continuous outcomes. As the study occurred in a university town and university students are likely to have different shopping patterns from non-students, we stratified analyses by student status. Eastern North Carolina. Low-income women of reproductive age (18–44 years) with valid address information accessing family planning services at a local health department (n 400). Over a quarter reported ever shopping at farmers’ markets (114/400). A larger percentage of women who shopped at farmers’ markets consumed five or more fruits and vegetables daily (42.1%) than those who did not (24.0%; P < 0.001). The mean objectively measured distance to the farmers’ markets where women reported shopping was 11.4 (SD 9.0) km (7.1 (SD 5.6) miles), while the mean distance to the farmers’ market closest to the residence was 4.0 (SD 3.7) km (2.5 (SD 2.3) miles). Among non-students, those who shopped at farmers’ markets were more likely to consume five or more servings of fruits and vegetables daily. Future research should further explore potential health benefits of farmers’ markets.
Camargo, L B; Fell, C; Bonini, G C; Marquezan, M; Imparato, J C P; Mendes, F M; Raggio, D P
2011-12-01
To evaluate the degree of knowledge, use and teaching of atraumatic restorative treatment (ART) of paediatric dentistry lecturers in dental schools throughout Brazil. A structured questionnaire was applied, containing questions regarding the use of ART, socio-demographic characteristics and academic degree background. Descriptive analysis and Poisson's regression were conducted in order to verify the association between exploratory variables and ART teaching (α=5%). Of the 721 questionnaires sent to dental schools, approximately 40% were returned (n=285). Some 98.2% of the participants teach ART. Concerning dental lecturers who teach ART, in multiple regression model, considering ART indication (emergency versus restorative treatment) the lecturers residents of the Mid-West (PR=1.66; CI:1.13-2.45) and Northeast region (PR=1.33; CI:1.02-1.72) and lecturers who use ART regularly (PR=3.73; CI:2.11-5.59) teach ART as restorative treatment. When the question was about reason for using ART (conservative technique versus other techniques failures/fast treatment), lecturers with a longer period of TG (time elapsed since graduation) (PR=1.30; CI:1.08- 1.56) and also lecturers who use ART regularly (PR=2.87; CI:1.95-4.22), teach it as being a conservative technique. Regarding the patients' age covered by ART (versus without limitation), women (PR=1.26; CI:1.06-1.50) and lecturers who use ART regularly (PR=1.28; CI:1.06-1.54), teach that there is no age restriction. ART has been widely taught in Brazilian dental schools, is regularly used in lecturer's clinical practices and has positively influenced the appropriate teaching of this technique.
Hu, Wen-Long; Chen, Hsuan-Ju; Li, Tsai-Chung; Tsai, Pei-Yuan; Chen, Hsin-Ping; Huang, Meng-Hsuan; Su, Fang-Yen
2015-01-01
Objective Combinations of Chinese herbal products (CHPs) are widely used for ischemic heart disease (IHD) in Taiwan. We analyzed the usage and frequency of CHPs prescribed for patients with IHD. Methods A nationwide population-based cross-sectional study was conducted, 53531 patients from a random sample of one million in the National Health Insurance Research Database (NHIRD) from 2000 to 2010 were enrolled. Descriptive statistics, the multiple logistic regression method and Poisson regression analysis were employed to estimate the adjusted odds ratios (aORs) and adjusted risk ratios (aRRs) for utilization of CHPs. Results The mean age of traditional Chinese medicine (TCM) nonusers was significantly higher than that of TCM users. Zhi-Gan-Cao-Tang (24.85%) was the most commonly prescribed formula CHPs, followed by Xue-Fu-Zhu-Yu-Tang (16.53%) and Sheng-Mai-San (16.00%). The most commonly prescribed single CHPs were Dan Shen (29.30%), Yu Jin (7.44%), and Ge Gen (6.03%). After multivariate adjustment, patients with IHD younger than 29 years had 2.62 times higher odds to use TCM than those 60 years or older. Residents living in Central Taiwan, having hyperlipidemia or cardiac dysrhythmias also have higher odds to use TCM. On the contrary, those who were males, who had diabetes mellitus (DM), hypertension, stroke, myocardial infarction (MI) were less likely to use TCM. Conclusions Zhi-Gan-Cao-Tang and Dan Shen are the most commonly prescribed CHPs for IHD in Taiwan. Our results should be taken into account by physicians when devising individualized therapy for IHD. Further large-scale, randomized clinical trials are warranted in order to determine the effectiveness and safety of these herbal medicines. PMID:26322893
The effects of particulate air pollution on daily deaths: a multi-city case crossover analysis
Schwartz, J
2004-01-01
Background: Numerous studies have reported that day-to-day changes in particulate air pollution are associated with day-to-day changes in deaths. Recently, several reports have indicated that the software used to control for season and weather in some of these studies had deficiencies. Aims: To investigate the use of the case-crossover design as an alternative. Methods: This approach compares the exposure of each case to their exposure on a nearby day, when they did not die. Hence it controls for seasonal patterns and for all slowly varying covariates (age, smoking, etc) by matching rather than complex modelling. A key feature is that temperature can also be controlled by matching. This approach was applied to a study of 14 US cities. Weather and day of the week were controlled for in the regression. Results: A 10 µg/m3 increase in PM10 was associated with a 0.36% increase in daily deaths from internal causes (95% CI 0.22% to 0.50%). Results were little changed if, instead of symmetrical sampling of control days the time stratified method was applied, when control days were matched on temperature, or when more lags of winter time temperatures were used. Similar results were found using a Poisson regression, but the case-crossover method has the advantage of simplicity in modelling, and of combining matched strata across multiple locations in a single stage analysis. Conclusions: Despite the considerable differences in analytical design, the previously reported associations of particles with mortality persisted in this study. The association appeared quite linear. Case-crossover designs represent an attractive method to control for season and weather by matching. PMID:15550600
Lopiano, Kenneth K; Young, Linda J; Gotway, Carol A
2014-09-01
Spatially referenced datasets arising from multiple sources are routinely combined to assess relationships among various outcomes and covariates. The geographical units associated with the data, such as the geographical coordinates or areal-level administrative units, are often spatially misaligned, that is, observed at different locations or aggregated over different geographical units. As a result, the covariate is often predicted at the locations where the response is observed. The method used to align disparate datasets must be accounted for when subsequently modeling the aligned data. Here we consider the case where kriging is used to align datasets in point-to-point and point-to-areal misalignment problems when the response variable is non-normally distributed. If the relationship is modeled using generalized linear models, the additional uncertainty induced from using the kriging mean as a covariate introduces a Berkson error structure. In this article, we develop a pseudo-penalized quasi-likelihood algorithm to account for the additional uncertainty when estimating regression parameters and associated measures of uncertainty. The method is applied to a point-to-point example assessing the relationship between low-birth weights and PM2.5 levels after the onset of the largest wildfire in Florida history, the Bugaboo scrub fire. A point-to-areal misalignment problem is presented where the relationship between asthma events in Florida's counties and PM2.5 levels after the onset of the fire is assessed. Finally, the method is evaluated using a simulation study. Our results indicate the method performs well in terms of coverage for 95% confidence intervals and naive methods that ignore the additional uncertainty tend to underestimate the variability associated with parameter estimates. The underestimation is most profound in Poisson regression models. © 2014, The International Biometric Society.
On the fractal characterization of Paretian Poisson processes
NASA Astrophysics Data System (ADS)
Eliazar, Iddo I.; Sokolov, Igor M.
2012-06-01
Paretian Poisson processes are Poisson processes which are defined on the positive half-line, have maximal points, and are quantified by power-law intensities. Paretian Poisson processes are elemental in statistical physics, and are the bedrock of a host of power-law statistics ranging from Pareto's law to anomalous diffusion. In this paper we establish evenness-based fractal characterizations of Paretian Poisson processes. Considering an array of socioeconomic evenness-based measures of statistical heterogeneity, we show that: amongst the realm of Poisson processes which are defined on the positive half-line, and have maximal points, Paretian Poisson processes are the unique class of 'fractal processes' exhibiting scale-invariance. The results established in this paper are diametric to previous results asserting that the scale-invariance of Poisson processes-with respect to physical randomness-based measures of statistical heterogeneity-is characterized by exponential Poissonian intensities.
Treatment of singularities in cracked bodies
NASA Technical Reports Server (NTRS)
Shivakumar, K. N.; Raju, I. S.
1990-01-01
Three-dimensional finite-element analyses of middle-crack tension (M-T) and bend specimens subjected to mode I loadings were performed to study the stress singularity along the crack front. The specimen was modeled using 20-node isoparametric elements. The displacements and stresses from the analysis were used to estimate the power of singularities using a log-log regression analysis along the crack front. The analyses showed that finite-sized cracked bodies have two singular stress fields of the form rho = C sub o (theta, z) r to the -1/2 power + D sub o (theta, phi) R to the lambda rho power. The first term is the cylindrical singularity with the power -1/2 and is dominant over the middle 96 pct (for Poisson's ratio = 0.3) of the crack front and becomes nearly zero at the free surface. The second singularity is a vertex singularity with the vertex point located at the intersection of the crack front and the free surface. The second term is dominant at the free surface and becomes nearly zero away from the boundary layer. The thickness of the boundary layer depends on Poisson's ratio of the material and is independent of the specimen type. The thickness of the boundary layer varied from 0 pct to about 5 pct of the total specimen thickness as Poisson's ratio varied from 0.0 to 0.45. Because there are two singular stress fields near the free surface, the strain energy release rate (G) is an appropriate parameter to measure the severity of the crack.
Treatment of singularities in cracked bodies
NASA Technical Reports Server (NTRS)
Shivakumar, K. N.; Raju, I. S.
1989-01-01
Three-dimensional finite-element analyses of middle-crack tension (M-T) and bend specimens subjected to mode I loadings were performed to study the stress singularity along the crack front. The specimen was modeled using 20-node isoparametric elements. The displacements and stresses from the analysis were used to estimate the power of singularities using a log-log regression analysis along the crack front. The analyses showed that finite-sized cracked bodies have two singular stress fields of the form rho = C sub o (theta, z) r to the -1/2 power + D sub o (theta, phi) R to the lambda rho power. The first term is the cylindrical singularity with the power -1/2 and is dominant over the middle 96 pct (for Poisson's ratio = 0.3) of the crack front and becomes nearly zero at the free surface. The second singularity is a vertex singularity with the vertex point located at the intersection of the crack front and the free surface. The second term is dominant at the free surface and becomes nearly zero away from the the boundary layer. The thickness of the boundary layer depends on Poisson's ratio of the material and is independent of the specimen type. The thickness of the boundary layer varied from 0 pct to about 5 pct of the total specimen thickness as Poisson's ratio varied from 0.0 to 0.45. Because there are two singular stress fields near the free surface, the strain energy release rate (G) is an appropriate parameter to measure the severity of the crack.
Evaluating for a geospatial relationship between radon levels and thyroid cancer in Pennsylvania.
Goyal, Neerav; Camacho, Fabian; Mangano, Joseph; Goldenberg, David
2015-01-01
To determine whether there is an association between radon levels and the rise in incidence of thyroid cancer in Pennsylvania. Epidemiological study of the state of Pennsylvania. We used information from the Pennsylvania Cancer Registry and the Pennsylvania Department of Energy. From the registry, information regarding thyroid incidence by county and zip code was recorded. Information regarding radon levels per county was recorded from the state. Poisson regression models were fit predicting county-level thyroid incidence and change as a function of radon/lagged radon levels. To account for measurement error in the radon levels, a Bayesian Model extending the Poisson models was fit. Geospatial clustering analysis was also performed. No association was noted between cumulative radon levels and thyroid incidence. In the Poisson modeling, no significant association was noted between county radon level and thyroid cancer incidence (P = .23). Looking for a lag between the radon level and its effect, no significant effect was seen with a lag of 0 to 6 years between exposure and effect (P = .063 to P = .59). The Bayesian models also failed to show a statistically significant association. A cluster of high thyroid cancer incidence was found in western Pennsylvania. Through a variety of models, no association was elicited between annual radon levels recorded in Pennsylvania and the rising incidence of thyroid cancer. However, a cluster of thyroid cancer incidence was found in western Pennsylvania. Further studies may be helpful in looking for other exposures or associations. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.
NASA Astrophysics Data System (ADS)
Jurčo, Branislav; Schupp, Peter; Vysoký, Jan
2014-06-01
We generalize noncommutative gauge theory using Nambu-Poisson structures to obtain a new type of gauge theory with higher brackets and gauge fields. The approach is based on covariant coordinates and higher versions of the Seiberg-Witten map. We construct a covariant Nambu-Poisson gauge theory action, give its first order expansion in the Nambu-Poisson tensor and relate it to a Nambu-Poisson matrix model.
Multiple-Instance Regression with Structured Data
NASA Technical Reports Server (NTRS)
Wagstaff, Kiri L.; Lane, Terran; Roper, Alex
2008-01-01
We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu Benzhuo; Holst, Michael J.; Center for Theoretical Biological Physics, University of California San Diego, La Jolla, CA 92093
2010-09-20
In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for simulating electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised formore » time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.« less
Lu, Benzhuo; Holst, Michael J.; McCammon, J. Andrew; Zhou, Y. C.
2010-01-01
In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems. PMID:21709855
Lu, Benzhuo; Holst, Michael J; McCammon, J Andrew; Zhou, Y C
2010-09-20
In this paper we developed accurate finite element methods for solving 3-D Poisson-Nernst-Planck (PNP) equations with singular permanent charges for electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst-Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams-Bashforth-Crank-Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst-Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.
Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R
2012-01-01
The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.
A Three-dimensional Polymer Scaffolding Material Exhibiting a Zero Poisson's Ratio.
Soman, Pranav; Fozdar, David Y; Lee, Jin Woo; Phadke, Ameya; Varghese, Shyni; Chen, Shaochen
2012-05-14
Poisson's ratio describes the degree to which a material contracts (expands) transversally when axially strained. A material with a zero Poisson's ratio does not transversally deform in response to an axial strain (stretching). In tissue engineering applications, scaffolding having a zero Poisson's ratio (ZPR) may be more suitable for emulating the behavior of native tissues and accommodating and transmitting forces to the host tissue site during wound healing (or tissue regrowth). For example, scaffolding with a zero Poisson's ratio may be beneficial in the engineering of cartilage, ligament, corneal, and brain tissues, which are known to possess Poisson's ratios of nearly zero. Here, we report a 3D biomaterial constructed from polyethylene glycol (PEG) exhibiting in-plane Poisson's ratios of zero for large values of axial strain. We use digital micro-mirror device projection printing (DMD-PP) to create single- and double-layer scaffolds composed of semi re-entrant pores whose arrangement and deformation mechanisms contribute the zero Poisson's ratio. Strain experiments prove the zero Poisson's behavior of the scaffolds and that the addition of layers does not change the Poisson's ratio. Human mesenchymal stem cells (hMSCs) cultured on biomaterials with zero Poisson's ratio demonstrate the feasibility of utilizing these novel materials for biological applications which require little to no transverse deformations resulting from axial strains. Techniques used in this work allow Poisson's ratio to be both scale-independent and independent of the choice of strut material for strains in the elastic regime, and therefore ZPR behavior can be imparted to a variety of photocurable biomaterial.
From Loss of Memory to Poisson.
ERIC Educational Resources Information Center
Johnson, Bruce R.
1983-01-01
A way of presenting the Poisson process and deriving the Poisson distribution for upper-division courses in probability or mathematical statistics is presented. The main feature of the approach lies in the formulation of Poisson postulates with immediate intuitive appeal. (MNS)
Nonlocal Poisson-Fermi model for ionic solvent.
Xie, Dexuan; Liu, Jinn-Liang; Eisenberg, Bob
2016-07-01
We propose a nonlocal Poisson-Fermi model for ionic solvent that includes ion size effects and polarization correlations among water molecules in the calculation of electrostatic potential. It includes the previous Poisson-Fermi models as special cases, and its solution is the convolution of a solution of the corresponding nonlocal Poisson dielectric model with a Yukawa-like kernel function. The Fermi distribution is shown to be a set of optimal ionic concentration functions in the sense of minimizing an electrostatic potential free energy. Numerical results are reported to show the difference between a Poisson-Fermi solution and a corresponding Poisson solution.
Nonlinear Poisson Equation for Heterogeneous Media
Hu, Langhua; Wei, Guo-Wei
2012-01-01
The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. PMID:22947937
Qi, Cong; Gu, Yiyang; Sun, Qing; Gu, Hongliang; Xu, Bo; Gu, Qing; Xiao, Jing; Lian, Yulong
2017-05-01
We assessed the risk of liver injuries following low doses of N,N-dimethylformamide (DMF) below threshold limit values (20 mg/m) among leather industry workers and comparison groups. A cohort of 429 workers from a leather factory and 466 non-exposed subjects in China were followed for 4 years. Poisson regression and piece-wise linear regression were used to examine the relationship between DMF and liver injury. Workers exposed to a cumulative dose of DMF were significantly more likely than non-exposed workers to develop liver injury. A nonlinear relationship between DMF and liver injury was observed, and a threshold of the cumulative DMF dose for liver injury was 7.30 (mg/m) year. The findings indicate the importance of taking action to reduce DMF occupational exposure limits for promoting worker health.
Utility of correlation techniques in gravity and magnetic interpretation
NASA Technical Reports Server (NTRS)
Chandler, V. W.; Koski, J. S.; Braice, L. W.; Hinze, W. J.
1977-01-01
Internal correspondence uses Poisson's Theorem in a moving-window linear regression analysis between the anomalous first vertical derivative of gravity and total magnetic field reduced to the pole. The regression parameters provide critical information on source characteristics. The correlation coefficient indicates the strength of the relation between magnetics and gravity. Slope value gives delta j/delta sigma estimates of the anomalous source. The intercept furnishes information on anomaly interference. Cluster analysis consists of the classification of subsets of data into groups of similarity based on correlation of selected characteristics of the anomalies. Model studies are used to illustrate implementation and interpretation procedures of these methods, particularly internal correspondence. Analysis of the results of applying these methods to data from the midcontinent and a transcontinental profile shows they can be useful in identifying crustal provinces, providing information on horizontal and vertical variations of physical properties over province size zones, validating long wavelength anomalies, and isolating geomagnetic field removal problems.
Tighe, Elizabeth L.; Schatschneider, Christopher
2015-01-01
The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in Adult Basic Education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. PMID:25351773
An Analysis of the Number of Medical Malpractice Claims and Their Amounts
Bonetti, Marco; Cirillo, Pasquale; Musile Tanzi, Paola; Trinchero, Elisabetta
2016-01-01
Starting from an extensive database, pooling 9 years of data from the top three insurance brokers in Italy, and containing 38125 reported claims due to alleged cases of medical malpractice, we use an inhomogeneous Poisson process to model the number of medical malpractice claims in Italy. The intensity of the process is allowed to vary over time, and it depends on a set of covariates, like the size of the hospital, the medical department and the complexity of the medical operations performed. We choose the combination medical department by hospital as the unit of analysis. Together with the number of claims, we also model the associated amounts paid by insurance companies, using a two-stage regression model. In particular, we use logistic regression for the probability that a claim is closed with a zero payment, whereas, conditionally on the fact that an amount is strictly positive, we make use of lognormal regression to model it as a function of several covariates. The model produces estimates and forecasts that are relevant to both insurance companies and hospitals, for quality assurance, service improvement and cost reduction. PMID:27077661
ℓ(p)-Norm multikernel learning approach for stock market price forecasting.
Shao, Xigao; Wu, Kun; Liao, Bifeng
2012-01-01
Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.
Saint-Venant end effects for materials with negative Poisson's ratios
NASA Technical Reports Server (NTRS)
Lakes, R. S.
1992-01-01
Results are presented from an analysis of Saint-Venant end effects for materials with negative Poisson's ratio. Examples are presented showing that slow decay of end stress occurs in circular cylinders of negative Poisson's ratio, whereas a sandwich panel containing rigid face sheets and a compliant core exhibits no anomalous effects for negative Poisson's ratio (but exhibits slow stress decay for core Poisson's ratios approaching 0.5). In sand panels with stiff but not perfectly rigid face sheets, a negative Poisson's ratio results in end stress decay, which is faster than it would be otherwise. It is suggested that the slow decay previously predicted for sandwich strips in plane deformation as a result of the geometry can be mitigated by the use of a negative Poisson's ratio material for the core.
Poisson's ratio of fiber-reinforced composites
NASA Astrophysics Data System (ADS)
Christiansson, Henrik; Helsing, Johan
1996-05-01
Poisson's ratio flow diagrams, that is, the Poisson's ratio versus the fiber fraction, are obtained numerically for hexagonal arrays of elastic circular fibers in an elastic matrix. High numerical accuracy is achieved through the use of an interface integral equation method. Questions concerning fixed point theorems and the validity of existing asymptotic relations are investigated and partially resolved. Our findings for the transverse effective Poisson's ratio, together with earlier results for random systems by other authors, make it possible to formulate a general statement for Poisson's ratio flow diagrams: For composites with circular fibers and where the phase Poisson's ratios are equal to 1/3, the system with the lowest stiffness ratio has the highest Poisson's ratio. For other choices of the elastic moduli for the phases, no simple statement can be made.
Li, Jun; Tibshirani, Robert
2015-01-01
We discuss the identification of features that are associated with an outcome in RNA-Sequencing (RNA-Seq) and other sequencing-based comparative genomic experiments. RNA-Seq data takes the form of counts, so models based on the normal distribution are generally unsuitable. The problem is especially challenging because different sequencing experiments may generate quite different total numbers of reads, or ‘sequencing depths’. Existing methods for this problem are based on Poisson or negative binomial models: they are useful but can be heavily influenced by ‘outliers’ in the data. We introduce a simple, nonparametric method with resampling to account for the different sequencing depths. The new method is more robust than parametric methods. It can be applied to data with quantitative, survival, two-class or multiple-class outcomes. We compare our proposed method to Poisson and negative binomial-based methods in simulated and real data sets, and find that our method discovers more consistent patterns than competing methods. PMID:22127579
Grayscale inhomogeneity correction method for multiple mosaicked electron microscope images
NASA Astrophysics Data System (ADS)
Zhou, Fangxu; Chen, Xi; Sun, Rong; Han, Hua
2018-04-01
Electron microscope image stitching is highly desired to acquire microscopic resolution images of large target scenes in neuroscience. However, the result of multiple Mosaicked electron microscope images may exist severe gray scale inhomogeneity due to the instability of the electron microscope system and registration errors, which degrade the visual effect of the mosaicked EM images and aggravate the difficulty of follow-up treatment, such as automatic object recognition. Consequently, the grayscale correction method for multiple mosaicked electron microscope images is indispensable in these areas. Different from most previous grayscale correction methods, this paper designs a grayscale correction process for multiple EM images which tackles the difficulty of the multiple images monochrome correction and achieves the consistency of grayscale in the overlap regions. We adjust overall grayscale of the mosaicked images with the location and grayscale information of manual selected seed images, and then fuse local overlap regions between adjacent images using Poisson image editing. Experimental result demonstrates the effectiveness of our proposed method.
Characterization of Nonhomogeneous Poisson Processes Via Moment Conditions.
1986-08-01
Poisson processes play an important role in many fields. The Poisson process is one of the simplest counting processes and is a building block for...place of independent increments. This provides a somewhat different viewpoint for examining Poisson processes . In addition, new characterizations for
Constructions and classifications of projective Poisson varieties.
Pym, Brent
2018-01-01
This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.
Constructions and classifications of projective Poisson varieties
NASA Astrophysics Data System (ADS)
Pym, Brent
2018-03-01
This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.
Advanced statistics: linear regression, part II: multiple linear regression.
Marill, Keith A
2004-01-01
The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.
ERIC Educational Resources Information Center
Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.
2010-01-01
Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…
Spatial clustering and risk factors of malaria infections in Bata district, Equatorial Guinea.
Gómez-Barroso, Diana; García-Carrasco, Emely; Herrador, Zaida; Ncogo, Policarpo; Romay-Barja, María; Ondo Mangue, Martín Eka; Nseng, Gloria; Riloha, Matilde; Santana, Maria Angeles; Valladares, Basilio; Aparicio, Pilar; Benito, Agustín
2017-04-12
The transmission of malaria is intense in the majority of the countries of sub-Saharan Africa, particularly in those that are located along the Equatorial strip. The present study aimed to describe the current distribution of malaria prevalence among children and its environment-related factors as well as to detect malaria spatial clusters in the district of Bata, in Equatorial Guinea. From June to August 2013 a representative cross-sectional survey using a multistage, stratified, cluster-selected sample was carried out of children in urban and rural areas of Bata District. All children were tested for malaria using rapid diagnostic tests (RDTs). Results were linked to each household by global position system data. Two cluster analysis methods were used: hot spot analysis using the Getis-Ord Gi statistic, and the SaTScan™ spatial statistic estimates, based on the assumption of a Poisson distribution to detect spatial clusters. In addition, univariate associations and Poisson regression model were used to explore the association between malaria prevalence at household level with different environmental factors. A total of 1416 children aged 2 months to 15 years living in 417 households were included in this study. Malaria prevalence by RDTs was 47.53%, being highest in the age group 6-15 years (63.24%, p < 0.001). Those children living in rural areas were there malaria risk is greater (65.81%) (p < 0.001). Malaria prevalence was higher in those houses located <1 km from a river and <3 km to a forest (IRR: 1.31; 95% CI 1.13-1.51 and IRR: 1.44; 95% CI 1.25-1.66, respectively). Poisson regression analysis also showed a decrease in malaria prevalence with altitude (IRR: 0.73; 95% CI 0.62-0.86). A significant cluster inland of the district, in rural areas has been found. This study reveals a high prevalence of RDT-based malaria among children in Bata district. Those households situated in inland rural areas, near to a river, a green area and/or at low altitude were a risk factor for malaria. Spatial tools can help policy makers to promote new recommendations for malaria control.
Monitoring Poisson observations using combined applications of Shewhart and EWMA charts
NASA Astrophysics Data System (ADS)
Abujiya, Mu'azu Ramat
2017-11-01
The Shewhart and exponentially weighted moving average (EWMA) charts for nonconformities are the most widely used procedures of choice for monitoring Poisson observations in modern industries. Individually, the Shewhart EWMA charts are only sensitive to large and small shifts, respectively. To enhance the detection abilities of the two schemes in monitoring all kinds of shifts in Poisson count data, this study examines the performance of combined applications of the Shewhart, and EWMA Poisson control charts. Furthermore, the study proposes modifications based on well-structured statistical data collection technique, ranked set sampling (RSS), to detect shifts in the mean of a Poisson process more quickly. The relative performance of the proposed Shewhart-EWMA Poisson location charts is evaluated in terms of the average run length (ARL), standard deviation of the run length (SDRL), median run length (MRL), average ratio ARL (ARARL), average extra quadratic loss (AEQL) and performance comparison index (PCI). Consequently, all the new Poisson control charts based on RSS method are generally more superior than most of the existing schemes for monitoring Poisson processes. The use of these combined Shewhart-EWMA Poisson charts is illustrated with an example to demonstrate the practical implementation of the design procedure.
Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'.
de Nijs, Robin
2015-07-21
In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties, also in the case of rounding off of the images.
Mai, H M; Irons, P C; Kabir, J; Thompson, P N
2013-09-01
Brucellosis and campylobacteriosis are economically important diseases affecting bovine reproductive efficiency in Nigeria. A questionnaire-based survey was conducted in 271 cattle herds in Adamawa, Kaduna and Kano states of northern Nigeria using multistage cluster sampling. Serum from 4745 mature animals was tested for Brucella antibodies using the Rose-Bengal plate test and positives were confirmed in series-testing protocol using competitive enzyme-linked immunosorbent assay. Preputial scrapings from 602 bulls were tested using culture and identification for Campylobacter fetus. For each disease, a herd was classified as positive if one or more animals tested positive. For each herd, information on potential managemental and environmental risk factors was collected through a questionnaire administered during an interview with the manager, owner or herdsman. Multiple logistic regression models were used to model the odds of herd infection for each disease. A zero-inflated Poisson model was used to model the count of Brucella-positive animals within herds, with the number tested as an exposure variable. The presence of small ruminants (sheep and/or goats) on the same farm, and buying-in of >3 new animals in the previous year or failure to practice quarantine were associated with increased odds of herd-level campylobacteriosis and brucellosis, as well as increased within-herd counts of Brucella-positive animals. In addition, high rainfall, initial acquisition of animals from markets, practice of gynaecological examination and failure to practice herd prophylactic measures were positively associated with the odds of C. fetus infection in the herd. Herd size of >15, pastoral management system and presence of handling facility on the farm were associated with increased odds, and gynaecological examination with reduced odds of herd-level Brucella seropositivity. Furthermore, the zero-inflated Poisson model showed that borrowing or sharing of bulls was associated with higher counts, and provision of mineral supplement with lower counts of Brucella-positive cattle within herds. Identification of risk factors for bovine campylobacteriosis and brucellosis can help to identify appropriate control measures, and the use of zero-inflated count model can provide more specific information on these risk factors. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Wang, Fengwen
2018-05-01
This paper presents a systematic approach for designing 3D auxetic lattice materials, which exhibit constant negative Poisson's ratios over large strain intervals. A unit cell model mimicking tensile tests is established and based on the proposed model, the secant Poisson's ratio is defined as the negative ratio between the lateral and the longitudinal engineering strains. The optimization problem for designing a material unit cell with a target Poisson's ratio is formulated to minimize the average lateral engineering stresses under the prescribed deformations. Numerical results demonstrate that 3D auxetic lattice materials with constant Poisson's ratios can be achieved by the proposed optimization formulation and that two sets of material architectures are obtained by imposing different symmetry on the unit cell. Moreover, inspired by the topology-optimized material architecture, a subsequent shape optimization is proposed by parametrizing material architectures using super-ellipsoids. By designing two geometrical parameters, simple optimized material microstructures with different target Poisson's ratios are obtained. By interpolating these two parameters as polynomial functions of Poisson's ratios, material architectures for any Poisson's ratio in the interval of ν ∈ [ - 0.78 , 0.00 ] are explicitly presented. Numerical evaluations show that interpolated auxetic lattice materials exhibit constant Poisson's ratios in the target strain interval of [0.00, 0.20] and that 3D auxetic lattice material architectures with programmable Poisson's ratio are achievable.
Nonlinear Poisson equation for heterogeneous media.
Hu, Langhua; Wei, Guo-Wei
2012-08-22
The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Crash data modeling with a generalized estimator.
Ye, Zhirui; Xu, Yueru; Lord, Dominique
2018-08-01
The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.
Marginalized zero-altered models for longitudinal count data.
Tabb, Loni Philip; Tchetgen, Eric J Tchetgen; Wellenius, Greg A; Coull, Brent A
2016-10-01
Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias.
Marginalized zero-altered models for longitudinal count data
Tabb, Loni Philip; Tchetgen, Eric J. Tchetgen; Wellenius, Greg A.; Coull, Brent A.
2015-01-01
Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias. PMID:27867423
Icaza N, M Gloria; Núñez F, M Loreto; Torres A, Francisco J; Díaz S, Nora L; Várela G, David E
2007-11-01
Maps have played a critical role in public health since 1855, when John Snow associated a cholera outbreak with contaminated water source in London. After cardiovascular diseases, cancer is the second leading cause of death in Chile. Cancer was responsible for 22.7% of all deaths in 1997-2004 period. To describe the geographical distribution of stomach, trachea, bronchi and lung cancer mortality. Mortality statistics for the years 1997-2004, published by the National Statistics Institute and Chilean Ministry of Health, were used. The standardized mortality ratio (SMR) for sex and age quinquennium was calculated for 341 counties in the country. A hierarchical Bayesian analysis of Poisson regression models for SMR was performed. The maps were developed using adjusted SMR (or smoothed) by the Poisson model. There is an excess mortality caused by stomach cancer in south central Chile, from Teno to Valdivia. There is an excess mortality caused by trachea, bronchi and lung cancer in northern Chile, from Copiapó to Iquique. The geographical analysis of mortality caused by cancer shows cluster of counties with an excess risk. These areas should be considered for health care decision making and resource allocation.
Impact of Homeland Security Alert level on calls to a law enforcement peer support hotline.
Omer, Saad B; Barnett, Daniel J; Castellano, Cherie; Wierzba, Rachel K; Hiremath, Girish S; Balicer, Ran D; Everly, George S
2007-01-01
The Homeland Security Advisory System (HSAS) was established by the Department of Homeland Security to communicate the risk of a terrorist event. In order to explore the potential psychological impacts of HSAS we analyzed the effects of terror alerts on the law enforcement community. We used data from the New Jersey Cop 2 Cop crisis intervention hotline. Incidence Rate Ratios--interpreted as average relative increases in the daily number of calls to the Cop 2 Cop hotline during an increased alert period--were computed from Poisson models. The hotline received a total of 4,145 initial calls during the study period. The mean daily number of calls was higher during alert level elevation compared to prior 7 days (7.68 vs. 8.00). In the Poisson regression analysis, the Incidence Rate Ratios of number of calls received during elevated alert levels compared to the reference period of seven days preceding each change in alert were close to 1, with confidence intervals crossing 1 (i.e. not statistically significant) for all lag periods evaluated. This investigation, in the context of New Jersey law enforcement personnel, does not support the concern that elevating the alert status places undue stress upon alert recipients.
Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats
2009-06-19
In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session > or = 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors.
Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats
2009-01-01
Background In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Methods Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Results Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session ≥ 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). Conclusion By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors. PMID:19545386
Nichols, Linda; Stirling, Christine; Otahal, Petr; Stankovich, Jim; Gall, Seana
2018-03-01
Aneurysmal subarachnoid hemorrhage (aSAH) incidence is not well studied. Varied definitions of "subarachnoid hemorrhage" have led to a lack of clarity regarding aSAH incidence. The impact of area-level socioeconomic disadvantage and geographical location on the incidence of aSAH also remains unclear. Using a population-based statewide study, we examined the incidence of aSAH in relation to socioeconomic disadvantage and geographical location. A retrospective cohort study of nontraumatic subarachnoid hemorrhages from 2010 to 2014 was undertaken. Researchers manually collected data from multiple overlapping sources including statewide administrative databases, individual digital medical records, and death registers. Age-standardized rates (ASRs) per 100,000 person years were calculated using the 2001 Australian population. Differences in incidence rate ratios were calculated by age, sex, area-level socioeconomic status, and geographical location using Poisson regression. The cohort of 237 cases (mean age, 61.0 years) with a female predominance of 166 (70.04%) included 159 confirmed aSAH, 52 community-based deaths, and 26 probable cases. The ASR for aSAH was 9.99 (95% confidence interval [CI], 8.69-11.29). A significant association between area-level socioeconomic disadvantage and incidence was observed, with the rate of aSAH in disadvantaged geographical areas being 1.40 times higher than that in advantaged areas (95% CI, 1.11-1.82; P = .012). This study uses a comprehensive search of multiple data sources to define a new baseline of aSAH within an Australian population. This study presents a higher incidence rate of aSAH with socioeconomic variations. As a key risk factor that may explain this paradox, addressing socioeconomic inequalities is important for effective prevention and management interventions. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.
van Hedel, Karen; van Lenthe, Frank J; Avendano, Mauricio; Bopp, Matthias; Esnaola, Santiago; Kovács, Katalin; Martikainen, Pekka; Regidor, Enrique; Mackenbach, Johan P
2015-01-01
Aims Labour force activity and marriage share some of the pathways through which they potentially influence health. In this paper, we examine whether marriage and labour force participation interact in the way they influence mortality in the United States and six European countries. Methods We used data from the US National Health Interview Survey linked to the National Death Index, and national mortality registry data for Austria, England/Wales, Finland, Hungary, Norway and Spain (Basque country) during 1999-2007 for men and women aged 30-59 at baseline. Poisson regression was used to estimate both additive (the relative excess risk due to interaction) and multiplicative interactions between marriage and labour force activity on mortality. Results Labour force inactivity was associated with higher mortality, but this association was stronger for unmarried than married individuals. Likewise, being unmarried was associated with higher mortality, but this association was stronger for inactive than for active individuals. To illustrate, among US women out of the labour force, being unmarried was associated with a 3.98 (95%CI:3.28-4.82) times higher risk of dying than being married, whereas the relative risk was 2.49 (95%CI:2.10-2.94) for women active in the labour market. Although this interaction between marriage and labour force activity was only significant for women on a multiplicative scale, there was a significant additive interaction for both men and women. The pattern was similar across all countries. Conclusions Marriage attenuates the increased mortality risk associated with labour force inactivity, while labour force activity attenuates the mortality risk associated with being unmarried. Our study emphasizes the importance of public health and social policies that improve the health and well-being of men and women who are both unmarried and inactive. PMID:25868643
Oyama, Sakiko; Hibberd, Elizabeth E; Myers, Joseph B
2017-07-01
Shoulder and elbow injuries are commonplace in high school baseball. Although altered shoulder range of motion (ROM) and humeral retrotorsion angles have been associated with injuries, the efficacy of preseason screening of these characteristics remains controversial. We conducted preseason screenings for shoulder internal and external rotation ROM and humeral retrotorsion on 832 high school baseball players and tracked their exposure and incidence on throwing-related shoulder and elbow injuries during a subsequent season. Poisson regression with robust error variance was used to determine whether preseason screening could identify injury risk in baseball players and whether the injury risk was higher for pitchers compared with players who do not pitch. Shoulder rotation ROM or humeral retrotorsion at preseason did not predict the risk of throwing-related upper extremity injury (P = .15-.89). Injury risk was 3.84 higher for baseball players who pitched compared with those who did not (95% confidence interval, 1.72-8.56; P = .001). Preseason measures of shoulder ROM and humeral retrotorsion may not be effective in identifying players who are at increased injury risk. Because shoulder ROM is a measure that fluctuates under a variety of influences, future study should investigate whether taking multiple measurements during a season can identify at-risk players. The usefulness of preseason screening may also depend on rigor of participation in sports. Future studies should investigate how preseason shoulder characteristics and participation factors (ie, pitch count and frequency, competitive level, pitching in multiple leagues) interact to predict injury risk in baseball players. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.
Callaway, Libby; Enticott, Joanne; Farnworth, Louise; McDonald, Rachael; Migliorini, Christine; Willer, Barry
2017-06-01
Australia's National Disability Insurance Scheme (NDIS) is designed to influence home, social and economic participation for Scheme participants. Given the major disability reform underway, this pilot study aimed to: (i) examine community integration outcomes of people with spinal cord injury (SCI); (ii) compare findings with multiple matched controls and (iii) consider findings within the context of Australia's NDIS. Setting: Victoria, Australia. Matched analysis (people with and without SCI). Community Integration Questionnaire (CIQ). n = 40 adults with SCI (M age = 52.8 years; 61% male; 77% traumatic SCI). Matched analyses from each SCI subject aged <70 years (n = 31) with four CIQ normative data subjects (from n = 1927) was undertaken, with key demographic variables matched (age range, gender, living location and living situation). Risk of low CIQ score as a function of SCI was also examined using conditional Poisson regression. With key demographic variables held constant, small to medium effect sizes were found in favour of the normative sample, with statistically significant differences in home (ρ = 0.003) and productivity integration (ρ = 0.02). Relative risk of low home integration was significant in the SCI cohort (conditional RR (95% CI) = 3.1 (1.5-6.3), ρ = 0.001). Relative risk of low CIQ total, social integration and productivity scores did not reach significance. This cohort of SCI participants was less integrated into home and productive occupations than matched norms, holding implications for planning and allocation of supports to influence outcomes within an NDIS. Further research is necessary to understand community integration outcomes in larger matched samples. © 2016 Occupational Therapy Australia.
Cumulative poor psychosocial and behavioral health among low-income women at 6 weeks postpartum.
Walker, Lorraine O; Sterling, Bobbie Sue; Guy, Sarah; Mahometa, Michael J
2013-01-01
During the postpartum period, women may experience unfavorable psychosocial and behavioral health in multiple domains with adverse effects on parenting and maternal and infant health. Yet, little is known about the accumulation of poor health across the domains of depressive symptoms; body image; diet and physical activity; substance use including smoking and alcohol; and general self-care at 6 weeks postpartum, the usual end of maternity care. The aims of this study were to evaluate relationships among the domains comprising psychosocial and behavioral health and to examine the distribution and risk factors associated with cumulative poor psychosocial and behavioral health at 6 weeks postpartum. This study was a secondary analysis of cumulative poor health assessed by self-report scales for depressive symptoms, body image dissatisfaction, diet and exercise, substance use, and general self-care among 419 low-income White, African American, and Hispanic women at 6 weeks postpartum. Multivariable Poisson and logistic regression were used in key analyses. The correlation among psychosocial and behavioral domains had a range of r = .50-.00. In this sample of women, 45% had two or more domains in which they had poor health. The model testing risk factors for cumulative poor health was significant (likelihood ratio chi-square = 39.26, df = 11, p < 0.05), with two significant factors: not exclusively breastfeeding (odds ratio [OR] = 1.459, 95% confidence interval [CI] [1.119, 1.901]) and Hispanic ethnicity (OR = 0.707, 95% CI [0.582, 0.858], psuedo-R = .029). Within individual domains, significant risk factors (body mass index, not exclusively breastfeeding, ethnicity, education level, and parity) varied by domain. Many low-income women postpartum have poor psychosocial and behavioral health in multiple domains, which constitute areas for health promotion and early disease prevention.
Razzaghi, Hilda; Dawson, April; Grosse, Scott D.; Allori, Alexander C.; Kirby, Russell S.; Olney, Richard S.; Correia, Jane; Cassell, Cynthia H.
2015-01-01
Background Little is known about population-based maternal, child, and system characteristics associated with high hospital resource use for children with orofacial clefts (OFC) in the US. Methods This was a statewide, population-based, retrospective observational study of children with OFC born between 1998 and 2006, identified by the Florida Birth Defects Registry whose records were linked with longitudinal hospital discharge records. We stratified the descriptive results by cleft type [cleft lip with cleft palate (CLP), cleft lip (CL) and cleft palate (CP)] and by isolated vs. non-isolated OFC (accompanied by other coded major birth defects). We used Poisson regression to analyze associations between selected characteristics and high hospital resource use (≥90th percentile of estimated hospitalized days and inpatient costs) for birth, post-birth, and total hospitalizations initiated before age two years. Results Our analysis included 2,129 children with OFC. Infants who were born low birth weight (<2500 grams) were significantly more likely to have high birth hospitalization costs for CLP [adjusted prevalence ratio (aPR): 1.6 (95% confidence interval (CI): 1.0–2.7)], CL [aPR: 3.0 (95% CI: 1.1–8.1)], and CP [aPR: 2.3 (95% CI: 1.3–4.0)]. Presence of multiple birth defects was significantly associated with a three- to eleven-fold and a three- to nine-fold increase in the prevalence of high costs and number of hospitalized days, respectively; at birth, post-birth before age two years and overall hospitalizations. Conclusion Children with CP had the greatest hospital resources use. Additionally, the presence of multiple birth defects contributed to greater inpatient days and costs for children with OFC. PMID:25721952
Gabbe, Belinda J.; Simpson, Pam M.; Lyons, Ronan A.; Ameratunga, Shanthi; Harrison, James E.; Derrett, Sarah; Polinder, Suzanne; Davie, Gabrielle; Rivara, Frederick P.
2014-01-01
Objective To determine associations between the number of injuries sustained and three measures of disability 12-months post-injury for hospitalised patients. Methods Data from 27,840 adult (18+ years) participants, hospitalised for injury, were extracted for analysis from the Validating and Improving injury Burden Estimates (Injury-VIBES) Study. Modified Poisson and linear regression analyses were used to estimate relative risks and mean differences, respectively, for a range of outcomes (Glasgow Outcome Scale-Extended, GOS-E; EQ-5D and 12-item Short Form health survey physical and mental component summary scores, PCS-12 and MCS-12) according to the number of injuries sustained, adjusted for age, sex and contributing study. Findings More than half (54%) of patients had an injury to more than one ICD-10 body region and 62% had sustained more than one Global Burden of Disease injury type. The adjusted relative risk of a poor functional recovery (GOS-E<7) and of reporting problems on each of the items of the EQ-5D increased by 5–10% for each additional injury type, or body region, injured. Adjusted mean PCS-12 and MCS-12 scores worsened with each additional injury type, or body region, injured by 1.3–1.5 points and 0.5 points, respectively. Conclusions Consistent and strong relationships exist between the number of injury types and body regions injured and 12-month functional and health status outcomes. Existing composite measures of anatomical injury severity such as the NISS or ISS, which use up to three diagnoses only, may be insufficient for characterising or accounting for multiple injuries in disability studies. Future studies should consider the impact of multiple injuries to avoid under-estimation of injury burden. PMID:25501651
Leone, Sebastiano; Shanyinde, Milensu; Cozzi Lepri, Alessandro; Lampe, Fiona C; Caramello, Pietro; Costantini, Andrea; Giacometti, Andrea; De Luca, Andrea; Cingolani, Antonella; Ceccherini Silberstein, Francesca; Puoti, Massimo; Gori, Andrea; d'Arminio Monforte, Antonella
2018-05-01
To evaluate incidence rates of and predictors for any antiretroviral (ART) drug discontinuation by HCV infection status in a large Italian cohort of HIV infected patients. All patients enrolled in ICONA who started combination antiretroviral therapy (cART) containing abacavir or tenofovir or emtricitabine or lamivudine plus efavirenz or rilpivirine or atazanavir/r or darunavir/r (DRV/r) or lopinavir/r or dolutegravir or elvitegravir or raltegravir were included. Multivariate Poisson regression models were used to determine factors independently associated with single ART drug discontinuation. Inverse probability weighting method to control for potential informative censoring was applied. Data from 10,637 patients were analyzed and 1,030 (9.7%) were HCV-Ab positive. Overall, there were 15,464 ART discontinuations due to any reason in 82,415.9 person-years of follow-up (PYFU) for an incidence rate (IR) of 18.8 (95% confidence interval [95%CI] 18.5-19.1) per 100 PYFU. No difference in IR of ART discontinuation due to any reason between HCV-infected and -uninfected patients was found. In a multivariable Poisson regression model, HCV-infected participants were at higher risk of darunavir/r discontinuation due to any reason (adjusted incidence rate ratio = 1.5, 95%CI 1.01-2.22, p value = 0.045) independently of demographics, HIV-related, ART and life-style factors. Among DRV/r treated patients, we found that HCV-viremic patients had twice the risk of ART discontinuation due to any reason than HCV-aviremic patients. In conclusion, HIV/HCV coinfected patients had a marginal risk increase of DRV/r discontinuation due to any reason compared with those without coinfection.
Del Brutto, Oscar H; Mera, Robertino M; Zambrano, Mauricio; Del Brutto, Victor J
2017-02-01
Background There is no information on stroke incidence in rural areas of Latin America, where living conditions and cardiovascular risk factors are different from urban centers. Aim Using a population-based prospective cohort study design, we aimed to assess risk factors influencing stroke incidence in community-dwelling adults living in rural Ecuador. Methods First-ever strokes occurring from 1 June 2012 to 31 May 2016, in Atahualpa residents aged ≥40 years, were identified from yearly door-to-door surveys and other overlapping sources. Poisson regression models adjusted for demographics, cardiovascular risk factors, edentulism and the length of observation time per subject were used to estimate stroke incidence rate ratio as well as factors influencing such incidence. Results Of 807 stroke-free individuals prospectively enrolled in the Atahualpa Project, follow-up was achieved in 718 (89%), contributing 2,499 years of follow-up (average 3.48 ± 0.95 years). Overall stroke incidence rate was 2.97 per 100 person-years of follow-up (95% CI: 1.73-4.2), which increased to 4.77 (95% CI: 1.61-14.1) when only persons aged ≥57 years were considered. Poisson regression models, adjusted for relevant confounders, showed that high blood pressure (IRR: 5.24; 95% CI: 2.55-7.93) and severe edentulism (IRR: 5.06; 95% CI: 2.28-7.85) were the factors independently increasing stroke incidence. Conclusions Stroke incidence in this rural setting is comparable to that reported from the developed world. Besides age and high blood pressure, severe edentulism is a major factor independently predicting incident strokes. Public awareness of the consequences of poor dental care might reduce stroke incidence in rural settings.
Ni, Wei; Ding, Guoyong; Li, Yifei; Li, Hongkai; Jiang, Baofa
2014-01-01
Xinxiang, a city in Henan Province, suffered from frequent floods due to persistent and heavy precipitation from 2004 to 2010. In the same period, dysentery was a common public health problem in Xinxiang, with the proportion of reported cases being the third highest among all the notified infectious diseases. We focused on dysentery disease consequences of different degrees of floods and examined the association between floods and the morbidity of dysentery on the basis of longitudinal data during the study period. A time-series Poisson regression model was conducted to examine the relationship between 10 times different degrees of floods and the monthly morbidity of dysentery from 2004 to 2010 in Xinxiang. Relative risks (RRs) of moderate and severe floods on the morbidity of dysentery were calculated in this paper. In addition, we estimated the attributable contributions of moderate and severe floods to the morbidity of dysentery. A total of 7591 cases of dysentery were notified in Xinxiang during the study period. The effect of floods on dysentery was shown with a 0-month lag. Regression analysis showed that the risk of moderate and severe floods on the morbidity of dysentery was 1.55 (95% CI: 1.42-1.670) and 1.74 (95% CI: 1.56-1.94), respectively. The attributable risk proportions (ARPs) of moderate and severe floods to the morbidity of dysentery were 35.53 and 42.48%, respectively. This study confirms that floods have significantly increased the risk of dysentery in the study area. In addition, severe floods have a higher proportional contribution to the morbidity of dysentery than moderate floods. Public health action should be taken to avoid and control a potential risk of dysentery epidemics after floods.
Ni, Wei; Ding, Guoyong; Li, Yifei; Li, Hongkai; Jiang, Baofa
2014-01-01
Background Xinxiang, a city in Henan Province, suffered from frequent floods due to persistent and heavy precipitation from 2004 to 2010. In the same period, dysentery was a common public health problem in Xinxiang, with the proportion of reported cases being the third highest among all the notified infectious diseases. Objectives We focused on dysentery disease consequences of different degrees of floods and examined the association between floods and the morbidity of dysentery on the basis of longitudinal data during the study period. Design A time-series Poisson regression model was conducted to examine the relationship between 10 times different degrees of floods and the monthly morbidity of dysentery from 2004 to 2010 in Xinxiang. Relative risks (RRs) of moderate and severe floods on the morbidity of dysentery were calculated in this paper. In addition, we estimated the attributable contributions of moderate and severe floods to the morbidity of dysentery. Results A total of 7591 cases of dysentery were notified in Xinxiang during the study period. The effect of floods on dysentery was shown with a 0-month lag. Regression analysis showed that the risk of moderate and severe floods on the morbidity of dysentery was 1.55 (95% CI: 1.42–1.670) and 1.74 (95% CI: 1.56–1.94), respectively. The attributable risk proportions (ARPs) of moderate and severe floods to the morbidity of dysentery were 35.53 and 42.48%, respectively. Conclusions This study confirms that floods have significantly increased the risk of dysentery in the study area. In addition, severe floods have a higher proportional contribution to the morbidity of dysentery than moderate floods. Public health action should be taken to avoid and control a potential risk of dysentery epidemics after floods. PMID:25098726
Shkolnikov, Vladimir M; Jasilionis, Domantas; Andreev, Evgeny M; Jdanov, Dmitri A; Stankuniene, Vladislava; Ambrozaitiene, Dalia
2007-04-01
Earlier studies have found large and increasing with time differences in mortality by education and marital status in post-Soviet countries. Their results are based on independent tabulations of population and deaths counts (unlinked data). The present study provides the first census-linked estimates of group-specific mortality and the first comparison between census-linked and unlinked mortality estimates for a post-Soviet country. The study is based on a data set linking 140,000 deaths occurring in 2001-2004 in Lithuania with the population census of 2001. The same socio-demographic information about the deceased is available from both the census and death records. Cross-tabulations and Poisson regressions are used to compare linked and unlinked data. Linked and unlinked estimates of life expectancies and mortality rate ratios are calculated with standard life table techniques and Poisson regressions. For the two socio-demographic variables under study, the values from the death records partly differ from those from the census records. The deviations are especially significant for education, with 72-73%, 66-67%, and 82-84% matching for higher education, secondary education, and lower education, respectively. For marital status, deviations are less frequent. For education and marital status, unlinked estimates tend to overstate mortality in disadvantaged groups and they understate mortality in advantaged groups. The differences in inter-group life expectancy and the mortality rate ratios thus are significantly overestimated in the unlinked data. Socio-demographic differences in mortality previously observed in Lithuania and possibly other post-Soviet countries are overestimated. The growth in inequalities over the 1990s is real but might be overstated. The results of this study confirm the existence of large and widening health inequalities but call for better data.
Katano, Sayuri; Nakamura, Yasuyuki; Nakamura, Aki; Murakami, Yoshitaka; Tanaka, Taichiro; Nakagawa, Hideaki; Takebayashi, Toru; Yamato, Hiroshi; Okayama, Akira; Miura, Katsuyuki; Okamura, Tomonori; Ueshima, Hirotsugu
2010-06-30
To examine the relation between lifestyle and the number of metabolic syndrome (MetS) diagnostic components in a general population, and to find a means of preventing the development of MetS components. We examined baseline data from 3,365 participants (2,714 men and 651 women) aged 19 to 69 years who underwent a physical examination, lifestyle survey, and blood chemical examination. The physical activity of each participant was classified according to the International Physical Activity Questionnaire (IPAQ). We defined four components for MetS in this study as follows: 1) high BP: systolic BP > or = 130 mmHg or diastolic BP > or = 85 mmHg, or the use of antihypertensive drugs; 2) dyslipidemia: high-density lipoprotein-cholesterol concentration < 40 mg/dL, triglycerides concentration > or = 150 mg/dL, or on medication for dyslipidemia; 3) Impaired glucose tolerance: fasting blood sugar level > or = 110 mg/d, or if less than 8 hours after meals > or = 140 mg/dL), or on medication for diabetes mellitus; 4) obesity: body mass index > or = 25 kg/m(2). Those who had 0 to 4 MetS diagnostic components accounted for 1,726, 949, 484, 190, and 16 participants, respectively, in the Poisson distribution. Poisson regression analysis revealed that independent factors contributing to the number of MetS diagnostic components were being male (regression coefficient b=0.600, p < 0.01), age (b=0.027, p < 0.01), IPAQ class (b=-0.272, p= 0.03), and alcohol consumption (b=0.020, p=0.01). The contribution of current smoking was not statistically significant (b=-0.067, p=0.76). Moderate physical activity was inversely associated with the number of MetS diagnostic components, whereas smoking was not associated.
Burn mortality in patients with preexisting cardiovascular disease.
Knowlin, Laquanda; Reid, Trista; Williams, Felicia; Cairns, Bruce; Charles, Anthony
2017-08-01
Burn shock, a complex process, which develops following burn leads to severe and unique derangement of cardiovascular function. Patients with preexisting comorbidities such as cardiovascular diseases may be more susceptible. We therefore sought to examine the impact of preexisting cardiovascular disease on burn outcomes. A retrospective analysis of patients admitted to a regional burn center from 2002 to 2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA, pre-existing comorbidities, and length of ICU/hospital stay. Bivariate analysis was performed and Poisson regression modeling was utilized to estimate the incidence of being in the ICU and mortality. There were a total of 5332 adult patients admitted over the study period. 6% (n=428) had a preexisting cardiovascular disease. Cardiovascular disease patients had a higher mortality rate (16%) compared to those without cardiovascular disease (3%, p<0.001). The adjusted Poisson regression model to estimate incidence risk of being in intensive care unit in patients with cardiovascular disease was 33% higher compared to those without cardiovascular disease (IRR=1.33, 95% CI=1.22-1.47). The risk for mortality is 42% higher (IRR=1.42, 95% CI=1.10-1.84) for patients with pre-existing cardiovascular disease compared to those without cardiovascular disease after controlling for other covariates. Preexisting cardiovascular disease significantly increases the risk of intensive care unit admission and mortality in burn patients. Given the increasing number of Americans with cardiovascular diseases, there will likely be a greater number of individuals at risk for worse outcomes following burn. This knowledge can help with burn prognostication. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.
Association between quality of care and complications after abdominal surgery.
Bergman, Simon; Deban, Melina; Martelli, Vanessa; Monette, Michèle; Sourial, Nadia; Hamadani, Fadi; Teasdale, Debby; Holcroft, Christina; Zakrzewski, Helena; Fraser, Shannon
2014-09-01
Measuring the quality of surgical care is essential to identifying areas of weakness in the delivery of effective surgical care and to improving patient outcomes. Our objectives were to (1) assess the quality of surgical care delivered to adult patients; and (2) determine the association between quality of surgical care and postoperative complications. This retrospective, pilot, cohort study was conducted at a single university-affiliated institution. Using the institution's National Surgical Quality Improvement Program database (2009-2010), 273 consecutive patients ≥18 years of age who underwent elective major abdominal operations were selected. Adherence to 10 process-based quality indicators (QIs) was measured and quantified by calculating a patient quality score (no. of QIs passed/no. of QIs eligible). A pass rate for each individual QI was also calculated. The association between quality of surgical care and postoperative complications was assessed using an incidence rate ratio, which was estimated from a Poisson regression. The mean overall patient quality score was 67.2 ± 14.4% (range, 25-100%). The mean QI pass rate was 65.9 ± 26.1%, which varied widely from 9.6% (oral intake documentation) to 95.6% (prophylactic antibiotics). Poisson regression revealed that as the quality score increased, the incidence of postoperative complications decreased (incidence rate ratio, 0.19; P = .011). A sensitivity analysis revealed that this association was likely driven by the postoperative ambulation QI. Higher quality scores, mainly driven by early ambulation, were associated with fewer postoperative complications. QIs with unacceptably low adherence were identified as targets for future quality improvement initiatives. Copyright © 2014 Mosby, Inc. All rights reserved.
Wall-Wieler, Elizabeth; Roos, Leslie L; Brownell, Marni; Nickel, Nathan; Chateau, Dan; Singal, Deepa
2018-03-01
The objective of this study is to examine suicide attempts and completions among mothers who had a child taken into care by child protection services (CPS). These mothers were compared with their biological sisters who did not have a child taken into care and with mothers who received services from CPS but did not have a child taken into care. A retrospective cohort of mothers whose first child was born in Manitoba, Canada, between April 1, 1992, and March 31, 2015, is used. Rates among discordant biological sisters (1872 families) were compared using fixed-effects Poisson regression models, and mothers involved with CPS (children in care [ n = 1872] and received services [ n = 9590]) were compared using a Poisson regression model. Compared with their biological sisters and mothers who received services, the adjusted incidence rate ratio (aIRR) of death by suicide was greater among mothers whose child was taken into care by CPS (aIRR = 4.46 [95% confidence interval (CI), 1.39-14.33] and ARR = 3.45 [95% CI, 1.61-7.40], respectively). Incidence rates of suicide attempts were higher among mothers with a child taken into care compared with their sisters (aIRR = 2.15; 95% CI, 1.40-3.30) and mothers receiving services (aIRR = 2.82; 95% CI, 2.03-3.92). Mothers who had a child taken into care had significantly higher rates of suicide attempts and completions. When children are taken into care, physician and social workers should inquire about maternal suicidal behaviour and provide appropriate mental health.
Durkin, Michael J; Feng, Qianxi; Warren, Kyle; Lockhart, Peter B; Thornhill, Martin H; Munshi, Kiraat D; Henderson, Rochelle R; Hsueh, Kevin; Fraser, Victoria J
2018-05-01
The purpose of this study was to assess dental antibiotic prescribing trends over time, to quantify the number and types of antibiotics dentists prescribe inappropriately, and to estimate the excess health care costs of inappropriate antibiotic prescribing with the use of a large cohort of general dentists in the United States. We used a quasi-Poisson regression model to analyze antibiotic prescriptions trends by general dentists between January 1, 2013, and December 31, 2015, with the use of data from Express Scripts Holding Company, a large pharmacy benefits manager. We evaluated antibiotic duration and appropriateness for general dentists. Appropriateness was evaluated by reviewing the antibiotic prescribed and the duration of the prescription. Overall, the number and rate of antibiotic prescriptions prescribed by general dentists remained stable in our cohort. During the 3-year study period, approximately 14% of antibiotic prescriptions were deemed inappropriate, based on the antibiotic prescribed, antibiotic treatment duration, or both indicators. The quasi-Poisson regression model, which adjusted for number of beneficiaries covered, revealed a small but statistically significant decrease in the monthly rate of inappropriate antibiotic prescriptions by 0.32% (95% confidence interval, 0.14% to 0.50%; P = .001). Overall antibiotic prescribing practices among general dentists in this cohort remained stable over time. The rate of inappropriate antibiotic prescriptions by general dentists decreased slightly over time. From these authors' definition of appropriate antibiotic prescription choice and duration, inappropriate antibiotic prescriptions are common (14% of all antibiotic prescriptions) among general dentists. Further analyses with the use of chart review, administrative data sets, or other approaches are needed to better evaluate antibiotic prescribing practices among dentists. Copyright © 2018 American Dental Association. Published by Elsevier Inc. All rights reserved.
Rothman, Linda; Perry, Daniel; Buliung, Ron; Macarthur, Colin; To, Teresa; Macpherson, Alison; Larsen, Kristian; Howard, Andrew
2015-07-31
The presence of school crossing guards has been associated with more walking and more pedestrian-motor vehicle collisions (PMVCs) in area-level cross-sectional analyses. The objectives of the study were to (1) Determine the effect on PMVC rates of newly implemented crossing guards in Toronto, Canada (2) Determine where collisions were located in relation to crossing guards throughout the city, and whether they occurred during school travel times. School crossing guards with 50 m buffers were mapped along with police-reported child PMVCs from 2000-2011. (1) A quasi-experimental study identified all age collision counts near newly implemented guards before and after implementation, modeled using repeated measures Poisson regression adjusted for season and built environment variables. (2) A retrospective cohort study of all child PMVCS throughout the city to determine the proportions of child PMVCs which occurred during school travel times and at guard locations. There were 27,827 PMVCs, with 260 PMVCs at the locations of 58 newly implemented guards. Repeated measures adjusted Poisson regression found PMVCs rates remained unchanged at guard locations after implementation (IRR 1.02, 95 % CI 0.74, 1.39). There were 568 guards citywide with 1850 child PMVCs that occurred at guard locations. The majority of child PMVCs occurred outside school travel times (n = 1155, 62 %) and of those that occurred during school travel times, only 95 (13.7 %) were at a guard location. School crossing guards are a simple roadway modification to increase walking to school without apparent detrimental safety effects. Other more permanent interventions are necessary to address the frequency of child PMVCs occurring away from the location of crossing guards, and outside of school travel times.
Kuroda, Yujiro; Iwasa, Hajime; Goto, Aya; Yoshida, Kazuki; Matsuda, Kumiko; Iwamitsu, Yumi; Yasumura, Seiji
2017-09-03
This study examined the incidence of depression and associated factors among elderly persons from Iitate village after the March 2011 earthquake. This was a prospective cohort study. As a baseline survey, in May 2010 a self-assessment Basic Checklist (BCL) was distributed to 1611 elderly villagers, of which 1277 responded. Of these respondents, 885 without a tendency to depression (69.3%) were given a follow-up survey in May 2013. The BCL was used to assess depression tendency, instrumental activities of daily living (IADL), physical function, nutritional status, oral function, homeboundness, cognitive function and social activities. Univariate analysis was used to examine differences in risk between those with a presence of depression tendency (PDT) and those without (non-PDT) depending on demographic and BCL variables. Variables found to be significant were analysed by Poisson regression analysis. Of the 438 respondents in the second survey, 163 (37.2%) showed depression tendency. PDT risk was significantly increased by female gender, age, history of diabetes and cognitive disorder. It was significantly reduced by increased IADL. Engagement in social activities decreased PDT risk in rental accommodation. Renters faced a higher risk of PDT than persons evacuated in groups to purpose-built housing. The inclusion of social activities in the multivariate Poisson regression analysis weakened this effect. Female gender, a history of diabetes, reduced IADL and a tendency to cognitive disorder each independently affected PDT risk. These findings may inform future responses to earthquakes and the technical disasters that may accompany them. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Bosque-Prous, Marina; Kunst, Anton E; Brugal, M Teresa; Espelt, Albert
2017-08-01
The aim was to compare alcohol drinking patterns in economically active people aged 50-64 years before the last economic crisis (2006) and during the crisis (2013). Cross-sectional study with data from 25 479 economically active people aged 50-64 years resident in 11 European countries who participated in wave 2 or wave 5 of the SHARE project (2006 and 2013). The outcome variables were hazardous drinking, abstention in previous 3 months and the weekly average number of drinks per drinker. The prevalence ratios of hazardous drinking and abstention, comparing the prevalence in 2013 vs. 2006, were estimated with Poisson regression models with robust variance, and the changes in the number of drinks per week with Poisson regression models. The prevalence of hazardous drinking decreased among both men (PR = 0.75; 95%CI = 0.63-0.92) and women (PR = 0.91; 95%CI = 0.72-1.15), although the latter decrease was smaller and not statistically significant. The proportion of abstainers increased among both men (PR = 1.11; 95%CI = 0.99-1.29) and women (PR = 1.18; 95%CI = 1.07-1.30), although the former increase was smaller and not statistically significant. The weekly average number of drinks per drinker decreased in men and women. The decreases in consumption were larger in Italy and Spain. From 2006 to 2013, the amount of alcohol consumed by late working age drinkers decreased in Europe, with more pronounced declines in the countries hardest hit by the economic crisis. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
van Oeffelen, Louise; Biekram, Manisha; Poeran, Jashvant; Hukkelhoven, Chantal; Galjaard, Sander; van der Meijden, Wim; Op de Coul, Eline
2018-01-18
This paper provides an update on the incidence of neonatal herpes, guideline adherence by health care professionals (HCP), and trends in genital herpes simplex virus (HSV) infection during pregnancy in the Netherlands. Questionnaires were sent to all hospitals inquiring about numbers and characteristics of neonatal and maternal HSV infections, and guideline adherence between 2012 and 2015. Longitudinal trends were investigated from 1999 onwards using survey data and Perinatal Registry of the Netherlands data (Perined). Trends were smoothed with Poisson regression splines. Risk indicators for neonatal and maternal HSV infections were examined with Poisson regression analyses. Neonatal herpes incidence was 4.8/100,000 live births based on survey data (2012-2015) and 3.4/100,000 based on Perined (2012-2014). Mortality rate was 23% (7/30). Neonatal herpes incidence increased slightly over time as did the prevalence of genital HSV infection among pregnant women. Non-Western ethnicity (RR 1.9, 95%CI 1.5-2.5) and age <20 years (RR 2.3, 95%CI 1.2-4.7) were associated with genital herpes during pregnancy. In Perined, none of the neonatal herpes cases had a mother diagnosed with an active genital herpes infection during pregnancy. Preventive measures to reduce vertical herpes transmission (such as caesarean section) were less commonly reported by HCP in 2012-2015 compared to 2006-2011. Neonatal herpes incidence in the Netherlands slowly increased over the last 15 years. An increased genital HSV prevalence during pregnancy or, to lower extent, the decreased guideline adherence by HCP may be responsible. A rise in asymptomatic maternal HSV shedding is also plausible, emphasizing the challenges in preventing neonatal herpes.
Inequalities in financial risk protection in Bangladesh: an assessment of universal health coverage.
Islam, Md Rashedul; Rahman, Md Shafiur; Islam, Zobida; Nurs, Cherri Zhang B; Sultana, Papia; Rahman, Md Mizanur
2017-04-04
Financial risk protection and equity are major components of universal health coverage (UHC), which is defined as ensuring access to health services for all citizens without any undue financial burden. We investigated progress towards UHC financial risk indicators and assessed variability of inequalities in financial risk protection indicators by wealth quintile. We further examined the determinants of different financial hardship indicators related to healthcare costs. A cross-sectional, three-stage probability survey was conducted in Bangladesh, which collected information from 1600 households from August to November 2011. Catastrophic health payments, impoverishment, and distress financing (borrowing or selling assets) were treated as financial hardship indicators in UHC. Poisson regression models were used to identify the determinants of catastrophic payment, impoverishment and distress financing separately. Slope, relative and concentration indices of inequalities were used to assess wealth-based inequalities in financial hardship indicators. The study found that around 9% of households incurred catastrophic payments, 7% faced distress financing, and 6% experienced impoverishing health payments in Bangladesh. Slope index of inequality indicated that the incidence of catastrophic health payment and distress financing among the richest households were 12 and 9 percentage points lower than the poorest households respectively. Multivariable Poisson regression models revealed that all UHC financial hardship indicators were significantly higher among household that had members who received inpatient care or were in the poorest quintile. The presence of a member with chronic illness in a household increased the risk of impoverishment by nearly double. This study identified a greater inequality in UHC financial hardship indicators. Rich households in Bangladesh were facing disproportionately less financial hardship than the poor ones. Households can be protected from financial hardship associated with healthcare costs by implementing risk pooling mechanism, increasing GDP spending on health, and properly monitoring subsidized programs in public health facilities.
Access to Transportation and Health Care Visits for Medicaid Enrollees With Diabetes.
Thomas, Leela V; Wedel, Kenneth R; Christopher, Jan E
2018-03-01
Diabetes is a chronic condition that requires frequent health care visits for its management. Individuals without nonemergency medical transportation often miss appointments and do not receive optimal care. This study aims to evaluate the association between Medicaid-provided nonemergency medical transportation and diabetes care visits. A retrospective analysis was conducted of demographic and claims data obtained from the Oklahoma Medicaid program. Participants consisted of Medicaid enrollees with diabetes who made at least 1 visit for diabetes care in a year. The sample was predominantly female and white, with an average age of 46.38 years. Two zero-truncated Poisson regression models were estimated to assess the independent effect of transportation use on number of diabetes care visits. Use of nonemergency medical transportation is a significant predictor of diabetes care visits. Zero-truncated Poisson regression coefficients showed a positive association between the use of transportation and number of visits (0.6563, P < .001). Age, gender, race/ethnicity, area of residence, and presence of additional chronic conditions had independent associations with number of visits. Older enrollees were likely to make more visits than younger enrollees with diabetes (0.02382); controlling for all other factors in the model, rural residents made more visits than urban; women made fewer visits than men (-0.09312; P < .001); and minorities made fewer visits than whites, with pronounced differences for Hispanics and Asians compared to whites. Findings underscore the importance of ensuring transportation to Medicaid populations with diabetes, particularly in the rural areas where the prevalence of diabetes and complications are higher and the availability of medical resources lower than in the urban areas. © 2017 National Rural Health Association.
El Kassas, M; Funk, A L; Salaheldin, M; Shimakawa, Y; Eltabbakh, M; Jean, K; El Tahan, A; Sweedy, A T; Afify, S; Youssef, N F; Esmat, G; Fontanet, A
2018-06-01
In Egypt, hepatocellular carcinoma (HCC) is the most common form of cancer and direct-acting antivirals (DAA) are administered on a large scale to patients with chronic HCV infection to reduce the risk. In this unique setting, we aimed to determine the association of DAA exposure with early-phase HCC recurrence in patients with a history of HCV-related liver cancer. This was a prospective cohort study of an HCV-infected population from one Egyptian specialized HCC management centre starting from the time of successful HCC intervention. The incidence rates of HCC recurrence between DAA-exposed and nonexposed patients were compared, starting from date of HCC complete radiological response and censoring after 2 years. DAA exposure was treated as time varying. Two Poisson regressions models were used to control for potential differences in the exposed and nonexposed group; multivariable adjustment and balancing using inverse probability of treatment weighting (IPTW). We included 116 patients: 53 treated with DAAs and 63 not treated with DAAs. There was 37.7% and 25.4% recurrence in each group after a median of 16.0 and 23.0 months of follow-up, respectively. Poisson regression using IPTW demonstrated an association between DAAs and HCC recurrence with an incidence rate ratio of 3.83 (95% CI: 2.02-7.25), which was similar in the multivariable-adjusted model and various sensitivity analyses. These results add important evidence towards the possible role of DAAs in HCC recurrence and stress the need for further mechanistic studies and clinical trials to accurately confirm this role and to identify patient characteristics that may be associated with this event. © 2017 John Wiley & Sons Ltd.
Nistal-Nuño, Beatriz
2017-03-31
In Chile, a new law introduced in March 2012 lowered the blood alcohol concentration (BAC) limit for impaired drivers from 0.1% to 0.08% and the BAC limit for driving under the influence of alcohol from 0.05% to 0.03%, but its effectiveness remains uncertain. The goal of this investigation was to evaluate the effects of this enactment on road traffic injuries and fatalities in Chile. A retrospective cohort study. Data were analyzed using a descriptive and a Generalized Linear Models approach, type of Poisson regression, to analyze deaths and injuries in a series of additive Log-Linear Models accounting for the effects of law implementation, month influence, a linear time trend and population exposure. A review of national databases in Chile was conducted from 2003 to 2014 to evaluate the monthly rates of traffic fatalities and injuries associated to alcohol and in total. It was observed a decrease by 28.1 percent in the monthly rate of traffic fatalities related to alcohol as compared to before the law (P<0.001). Adding a linear time trend as a predictor, the decrease was by 20.9 percent (P<0.001).There was a reduction in the monthly rate of traffic injuries related to alcohol by 10.5 percent as compared to before the law (P<0.001). Adding a linear time trend as a predictor, the decrease was by 24.8 percent (P<0.001). Positive results followed from this new 'zero-tolerance' law implemented in 2012 in Chile. Chile experienced a significant reduction in alcohol-related traffic fatalities and injuries, being a successful public health intervention.
Effect of smoke-free legislation on the incidence of sudden circulatory arrest in the Netherlands.
de Korte-de Boer, Dianne; Kotz, Daniel; Viechtbauer, Wolfgang; van Haren, Emiel; Grommen, Devina; de Munter, Michelle; Coenen, Harry; Gorgels, Anton P M; van Schayck, Onno C P
2012-07-01
To investigate whether smoke-free legislation in the Netherlands led to a decreased incidence of out-of-hospital sudden circulatory arrest (SCA). Smoke-free legislation was implemented in two phases: a workplace ban in 2004 and an extension of this ban to the hospitality sector on 1 July 2008. Weekly incidence data on SCA were obtained from the ambulance registry of South Limburg, the Netherlands. Three time periods were distinguished: the pre-ban period (1 January 2002-1 January 2004), the first post-ban period (1 January 2004-1 July 2008) and the second post-ban period (1 July 2008-1 May 2010). Trends in absolute SCA incidence were analysed using Poisson regression, adjusted for population size, ambient temperature, air pollution and influenza rates. A total of 2305 SCA cases were observed (mean weekly incidence 5.3±2.3 SD). The adjusted Poisson regression model showed a small but significant increase in SCA incidence during the pre-ban period (+0.20% cases per week, p=0.044). This trend changed significantly after implementation of the first ban (with -0.24% cases per week, p=0.043), translating into a 6.8% (22 cases) reduction in the number of SCA cases after 1 year of smoke-free legislation. No further decrease was seen after the second smoking ban. After introduction of a nationwide workplace smoking ban in 2004, a significant decrease in the incidence of out-of-hospital SCA was seen in South Limburg. Poor enforcement of the 2008 hospitality sector ban may account for the fact that no further decrease in the incidence of SCA was seen at this time.
Wiebe, Julia C; Santana, Angelo; Medina-Rodríguez, Nathan; Hernández, Marta; Nóvoa, Javier; Mauricio, Dídac; Wägner, Ana M
2014-12-01
A recent Finnish study described reduced fertility in patients with childhood-onset type 1 diabetes. The Type 1 Diabetes Genetics Consortium (T1DGC) is an international programme studying the genetics and pathogenesis of type 1 diabetes that includes families with the disease. Our aim was to assess fertility, defined as number of offspring, in the affected and unaffected siblings included in the T1DGC. Clinical information from participants aged ≥18 years at the time of examination was included in the present analysis. The number of offspring of affected and unaffected siblings was compared (in families including both) and the influence of birth year, disease duration and age of onset was assessed, the last in affected siblings only, using Poisson regression models. A total of 3010 affected and 801 unaffected adult siblings that belonged to 1761 families were assessed. The mean number of offspring was higher in the unaffected than in the affected individuals, and the difference between the two groups was more pronounced in women than men. Poisson regression analysis showed that both sex and birth cohort significantly affected the differences between groups. In the affected siblings, adult onset (≥18 years), female sex and older birth cohort were associated with higher fertility. Patients with type 1 diabetes have fewer children than their unaffected siblings. This effect is more evident in women and in older birth cohorts. Onset of type 1 diabetes as an adult rather than a child is associated with a higher number of offspring, even after accounting for birth cohort and disease duration.
Dement, John M; Epling, Carol; Ostbye, Truls; Pompeii, Lisa A; Hunt, Debra L
2004-12-01
Health care workers (HCWs) are at risk of exposures to human blood and body fluids (BBF). Needlestick injuries and splashes place HCWs at risk for numerous blood-borne infections including human immunodeficiency virus (HIV), hepatitis B (HBV), and hepatitis C (HCV). Utilizing a new comprehensive occupational health surveillance system, the objective of this research was to better define the BBF exposure risk and risk factors among employees of a large tertiary medical center. A population of 24,425 HCWs employed in jobs with potential BBF exposures was followed for BBF exposure events from 1998 to 2002. BBF exposure rates were calculated for strata defined by age, race, gender, occupation, work location, and duration of employment. Poisson regression was used for detailed analyses of risk factors for BBF exposure. The study population reported 2,730 BBF exposures during the study period, resulting in an overall annual rate of 5.5 events/100 FTEs and a rate of 3.9 for percutaneous exposures. Higher rates were observed for males, persons employed less than 4 years, Hispanic employees, and persons less than 45 years of age. Much higher rates were observed for house staff, nurse anesthetists, inpatient nurses, phlebotomists, and surgical/operating room technicians. Poisson regression results strengthened and extended results from stratified analyses. Rates of percutaneous exposures from hollow needles were found to decrease over the study period; however, exposure rates from suture needles appear to be increasing. While continued training efforts need to be directed toward new HCWs, our data also suggest that employees who have been in their job 1-4 years continue to be at higher risk of BBF exposures. This research also points to the need for better safety devices/products and work practices to reduce suture-related injuries.
Chronic arsenic exposure and risk of infant mortality in two areas of Chile.
Hopenhayn-Rich, C; Browning, S R; Hertz-Picciotto, I; Ferreccio, C; Peralta, C; Gibb, H
2000-01-01
Chronic arsenic exposure has been associated with a range of neurologic, vascular, dermatologic, and carcinogenic effects. However, limited research has been directed at the association of arsenic exposure and human reproductive health outcomes. The principal aim of this study was to investigate the trends in infant mortality between two geographic locations in Chile: Antofagasta, which has a well-documented history of arsenic exposure from naturally contaminated water, and Valparaíso, a comparable low-exposure city. The arsenic concentration in Antofagasta's public drinking water supply rose substantially in 1958 with the introduction of a new water source, and remained elevated until 1970. We used a retrospective study design to examine time and location patterns in infant mortality between 1950 and 1996, using univariate statistics, graphical techniques, and Poisson regression analysis. Results of the study document the general declines in late fetal and infant mortality over the study period in both locations. The data also indicate an elevation of the late fetal, neonatal, and postneonatal mortality rates for Antofagasta, relative to Valparaíso, for specific time periods, which generally coincide with the period of highest arsenic concentration in the drinking water of Antofagasta. Poisson regression analysis yielded an elevated and significant association between arsenic exposure and late fetal mortality [rate ratio (RR) = 1.7; 95% confidence interval (CI), 1.5-1.9], neonatal mortality (RR = 1.53; CI, 1.4-1.7), and postneonatal mortality (RR = 1.26; CI, 1.2-1.3) after adjustment for location and calendar time. The findings from this investigation may support a role for arsenic exposure in increasing the risk of late fetal and infant mortality. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:10903622
Sun, Yi; Arning, Martin; Bochmann, Frank; Börger, Jutta; Heitmann, Thomas
2018-06-01
The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT) is a practical instrument that is currently used in the German woodworking and metalworking industries to monitor safety conditions at workplaces. The 12-item scoring system has three subscales rating technical, organizational, and personnel-related conditions in a company. Each item has a rating value ranging from 1 to 9, with higher values indicating higher standard of safety conditions. The reliability of this instrument was evaluated in a cross-sectional survey among 128 companies and its validity among 30,514 companies. The inter-rater reliability of the instrument was examined independently and simultaneously by two well-trained safety engineers. Agreement between the double ratings was quantified by the intraclass correlation coefficient and absolute agreement of the rating values. The content validity of the OSH-MAT was evaluated by quantifying the association between OSH-MAT values and 5-year average injury rates by Poisson regression analysis adjusted for the size of the companies and industrial sectors. The construct validity of OSH-MAT was examined by principle component factor analysis. Our analysis indicated good to very good inter-rater reliability (intraclass correlation coefficient = 0.64-0.74) of OSH-MAT values with an absolute agreement of between 72% and 81%. Factor analysis identified three component subscales that met exactly the structure theory of this instrument. The Poisson regression analysis demonstrated a statistically significant exposure-response relationship between OSH-MAT values and the 5-year average injury rates. These analyses indicate that OSH-MAT is a valid and reliable instrument that can be used effectively to monitor safety conditions at workplaces.
Dzhambov, Angel M; Dimitrova, Donka D
2016-01-01
Type 2 diabetes mellitus (T2DM) is a growing public health problem in Bulgaria. While individual and lifestyle determinants have been researched; till date there has been no study on environmental risks such as road traffic, noise, and air pollution. As a first step toward designing a large-scale population-based survey, we aimed at exploring the overall associations of prevalent T2DM with exposures to road traffic, noise, and air pollution. A total of 513 residents of Plovdiv city, Bulgaria were recruited. Individual data on self-reported doctor-diagnosed T2DM and confounding factors were linked to objective and self-rated exposure indicators. Logistic and log-link Poisson regressions were conducted. In the fully adjusted logistic models, T2DM was positively associated with exposures to Lden 71-80 dB (odds ratio (OR) = 4.49, 95% confidence interval (CI): 1.38, 14.68), fine particulate matter (PM)2.5 25.0-66.8 μg/m3 (OR = 1.32, 95% CI: 0.28, 6.24), benzo alpha pyrene 6.0-14.02 ng/m3 (OR = 1.76, 95% CI: 0.52, 5.98) and high road traffic (OR = 1.40, 95% CI: 0.48, 4.07). Lden remained a significant risk factor in the: Poisson regression model. Other covariates with consistently high multivariate effects were age, gender, body mass index, family history of T2DM, subjective sleep disturbance, and especially bedroom location. We concluded that residential noise exposure might be associated with elevated risk of prevalent T2DM. The inferences made by this research and the lessons learned from its limitations could guide the designing of a longitudinal epidemiological survey in Bulgaria. PMID:27157686
Tayyib, Nahla; Coyer, Fiona; Lewis, Peter A
2015-05-01
This study tested the effectiveness of a pressure ulcer (PU) prevention bundle in reducing the incidence of PUs in critically ill patients in two Saudi intensive care units (ICUs). A two-arm cluster randomized experimental control trial. Participants in the intervention group received the PU prevention bundle, while the control group received standard skin care as per the local ICU policies. Data collected included demographic variables (age, diagnosis, comorbidities, admission trajectory, length of stay) and clinical variables (Braden Scale score, severity of organ function score, mechanical ventilation, PU presence, and staging). All patients were followed every two days from admission through to discharge, death, or up to a maximum of 28 days. Data were analyzed with descriptive correlation statistics, Kaplan-Meier survival analysis, and Poisson regression. The total number of participants recruited was 140: 70 control participants (with a total of 728 days of observation) and 70 intervention participants (784 days of observation). PU cumulative incidence was significantly lower in the intervention group (7.14%) compared to the control group (32.86%). Poisson regression revealed the likelihood of PU development was 70% lower in the intervention group. The intervention group had significantly less Stage I (p = .002) and Stage II PU development (p = .026). Significant improvements were observed in PU-related outcomes with the implementation of the PU prevention bundle in the ICU; PU incidence, severity, and total number of PUs per patient were reduced. Utilizing a bundle approach and standardized nursing language through skin assessment and translation of the knowledge to practice has the potential to impact positively on the quality of care and patient outcome. © 2015 Sigma Theta Tau International.
Pattern of oral-maxillofacial trauma from violence against women and its associated factors.
da Nóbrega, Lorena Marques; Bernardino, Ítalo de Macedo; Barbosa, Kevan Guilherme Nóbrega; E Silva, Jéssica Antoniana Lira; Massoni, Andreza Cristina de Lima Targino; d'Avila, Sérgio
2017-06-01
Violence against women is a global public health problem. The aim of this study was to characterize the profile of women victims of violence and identify factors associated with maxillofacial injuries. A cross-sectional study was performed based on an evaluation of 884 medico-legal and social records of women victims of physical aggression treated at the Center of Forensic Medicine and Dentistry in Brazil. The variables investigated were related to the sociodemographic characteristics of victims, circumstances of aggressions, and patterns of trauma. Descriptive and multivariate statistics using decision tree analysis by the Chi-squared automatic interaction detector (CHAID) algorithm, as well as univariate and multivariate Poisson regression analyses were performed. The occurrence of maxillofacial trauma was 46.4%. The mean age of victims was 29.38 (SD=12.55 years). Based on decision tree, the profile of violence against women can be explained by the aggressor's gender (P<.001) and sociodemographic characteristics of victims, such as marital status (P=.001), place of residence (P=.019), and educational level (P=.014). Based on the final Poisson regression model, women living in suburban areas were more likely to suffer maxillofacial trauma (PR=1.752; CI 95%=1.153-2.662; P=.009) compared to those living in rural areas. Moreover, aggression using a weapon resulted in a lower occurrence of maxillofacial trauma (PR=0.476; CI 95%=0.284-0.799; P=.005) compared to cases of aggression using physical force. The prevalence of oral-maxillofacial trauma was high, and the main associated factors were place of residence and mechanism of aggression. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Berlin, Claudia; Jüni, Peter; Endrich, Olga; Zwahlen, Marcel
2016-01-01
Cardiovascular diseases are the leading cause of death worldwide and in Switzerland. When applied, treatment guidelines for patients with acute ST-segment elevation myocardial infarction (STEMI) improve the clinical outcome and should eliminate treatment differences by sex and age for patients whose clinical situations are identical. In Switzerland, the rate at which STEMI patients receive revascularization may vary by patient and hospital characteristics. To examine all hospitalizations in Switzerland from 2010-2011 to determine if patient or hospital characteristics affected the rate of revascularization (receiving either a percutaneous coronary intervention or a coronary artery bypass grafting) in acute STEMI patients. We used national data sets on hospital stays, and on hospital infrastructure and operating characteristics, for the years 2010 and 2011, to identify all emergency patients admitted with the main diagnosis of acute STEMI. We then calculated the proportion of patients who were treated with revascularization. We used multivariable multilevel Poisson regression to determine if receipt of revascularization varied by patient and hospital characteristics. Of the 9,696 cases we identified, 71.6% received revascularization. Patients were less likely to receive revascularization if they were female, and 80 years or older. In the multivariable multilevel Poisson regression analysis, there was a trend for small-volume hospitals performing fewer revascularizations but this was not statistically significant while being female (Relative Proportion = 0.91, 95% CI: 0.86 to 0.97) and being older than 80 years was still associated with less frequent revascularization. Female and older patients were less likely to receive revascularization. Further research needs to clarify whether this reflects differential application of treatment guidelines or limitations in this kind of routine data.
Serra-Negra, Junia Maria; Paiva, Saul Martins; Abreu, Mauro Henrique; Flores-Mendoza, Carmen Elvira; Pordeus, Isabela Almeida
2013-01-01
Background Tasks can be instruments of stress and may affect the health of children. Sleep bruxism is a multifactorial sleep-related movement disorder that affects children and adults. The aim of the present study was to analyze the association between children’s tasks, personality traits and sleep bruxism. Methods And Findings A cross-sectional, population-based study of 652 randomly selected Brazilian schoolchildren (52% of whom were female), aged from 7 to 10 years was conducted in the city of Belo Horizonte, Brazil. A questionnaire based on criteria proposed by the American Academy of Sleep Medicine (AASM) was completed by parents. In addition, the Neuroticism and Responsibility sub-scales of the Big Five Questionnaire for Children (BFQ-C) were administered to the children. Psychological tests were administered and evaluated by psychologists. The Social Vulnerability Index from the city council database was used to determine the social classification of the families. Chi-square and Poisson regression statistical tests were used with a 95% confidence interval. The majority of families were classified as having low social vulnerability (61.3%), whereas, 38.7% were classified as having high social vulnerability. Regarding extracurricular activities, the majority of girls performed household work (56.4%) and some artistic activity (51.3%) while sporting activities were most common among boys (61%). The results of the Poisson regression model indicated that sleep bruxism was most prevalent in children who scored highly in the Neuroticism sub-scale, and who frequently performed household tasks. Conclusion Children whose personality domain has a high level of Neuroticism and who perform household chores imposed by the family are more vulnerable to sleep bruxism. PMID:24244614
Huang, Shih-Wei; Chi, Wen-Chou; Yen, Chia-Feng; Chang, Kwang-Hwa; Liao, Hua-Fang; Escorpizo, Reuben; Chang, Feng-Hang; Liou, Tsan-Hon
2017-01-01
Background WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) is a feasible tool for assessing functional disability and analysing the risk of institutionalisation among elderly patients with dementia. However, the data for the effect of education on disability status in patients with dementia is lacking. The aim of this large-scale, population-based study was to analyse the effect of education on the disability status of elderly Taiwanese patients with dementia by using WHODAS 2.0. Methods From the Taiwan Data Bank of Persons with Disability, we enrolled 7698 disabled elderly (older than 65 years) patients diagnosed with dementia between July 2012 and January 2014. According to their education status, we categorised these patients with and without formal education (3849 patients each). We controlled for the demographic variables through propensity score matching. The standardised scores of these patients in the six domains of WHODAS 2.0 were evaluated by certified interviewers. Student’s t-test was used for comparing the WHODAS 2.0 scores of patients with dementia in the two aforementioned groups. Poisson regression was applied for analysing the association among all the investigated variables. Results Patients with formal education had low disability status in the domains of getting along and social participation than did patients without formal education. Poisson regression revealed that standardised scores in all domains of WHODAS 2.0—except self-care—were associated with education status. Conclusions This study revealed lower disability status in the WHODAS 2.0 domains of getting along and social participation for patients with dementia with formal education compared with those without formal education. For patients with disability and dementia without formal education, community intervention of social participation should be implemented to maintain better social interaction ability. PMID:28473510
Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression
ERIC Educational Resources Information Center
Beckstead, Jason W.
2012-01-01
The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…
General Nature of Multicollinearity in Multiple Regression Analysis.
ERIC Educational Resources Information Center
Liu, Richard
1981-01-01
Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)
ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting
Shao, Xigao; Wu, Kun; Liao, Bifeng
2012-01-01
Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561
Sample size determination for logistic regression on a logit-normal distribution.
Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance
2017-06-01
Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.
Higher Moments of Net-Kaon Multiplicity Distributions at STAR
NASA Astrophysics Data System (ADS)
Xu, Ji;
2017-01-01
Fluctuations of conserved quantities such as baryon number (B), electric charge number (Q), and strangeness number (S), are sensitive to the correlation length and can be used to probe non-gaussian fluctuations near the critical point. Experimentally, higher moments of the multiplicity distributions have been used to search for the QCD critical point in heavy-ion collisions. In this paper, we report the efficiency-corrected cumulants and their ratios of mid-rapidity (|y| < 0.5) net-kaon multiplicity distributions in Au+Au collisions at = 7.7, 11.5, 14.5, 19.6, 27, 39, 62.4, and 200 GeV collected in 2010, 2011, and 2014 with STAR at RHIC. The centrality and energy dependence of the cumulants and their ratios, are presented. Furthermore, the comparisons with baseline calculations (Poisson) and non-critical-point models (UrQMD) are also discussed.
Data mining of tree-based models to analyze freeway accident frequency.
Chang, Li-Yen; Chen, Wen-Chieh
2005-01-01
Statistical models, such as Poisson or negative binomial regression models, have been employed to analyze vehicle accident frequency for many years. However, these models have their own model assumptions and pre-defined underlying relationship between dependent and independent variables. If these assumptions are violated, the model could lead to erroneous estimation of accident likelihood. Classification and Regression Tree (CART), one of the most widely applied data mining techniques, has been commonly employed in business administration, industry, and engineering. CART does not require any pre-defined underlying relationship between target (dependent) variable and predictors (independent variables) and has been shown to be a powerful tool, particularly for dealing with prediction and classification problems. This study collected the 2001-2002 accident data of National Freeway 1 in Taiwan. A CART model and a negative binomial regression model were developed to establish the empirical relationship between traffic accidents and highway geometric variables, traffic characteristics, and environmental factors. The CART findings indicated that the average daily traffic volume and precipitation variables were the key determinants for freeway accident frequencies. By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies. By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies.
Unimodularity criteria for Poisson structures on foliated manifolds
NASA Astrophysics Data System (ADS)
Pedroza, Andrés; Velasco-Barreras, Eduardo; Vorobiev, Yury
2018-03-01
We study the behavior of the modular class of an orientable Poisson manifold and formulate some unimodularity criteria in the semilocal context, around a (singular) symplectic leaf. Our results generalize some known unimodularity criteria for regular Poisson manifolds related to the notion of the Reeb class. In particular, we show that the unimodularity of the transverse Poisson structure of the leaf is a necessary condition for the semilocal unimodular property. Our main tool is an explicit formula for a bigraded decomposition of modular vector fields of a coupling Poisson structure on a foliated manifold. Moreover, we also exploit the notion of the modular class of a Poisson foliation and its relationship with the Reeb class.
Melchior, Maria; Berkman, Lisa F; Niedhammer, Isabelle; Zins, Marie; Goldberg, Marcel
2007-07-01
Individuals who experience work stress or heavy family demands are at elevated risk of poor mental health. Yet, the cumulative effects of multiple work and family demands are not well known, particularly in men. We studied the association between multiple work and family demands and sickness absence due to non-psychotic psychiatric disorders in a longitudinal study conducted among members of the French GAZEL cohort study (8,869 men, 2,671 women) over a period of 9 years (1995-2003). Work stress and family demands were measured by questionnaire. Medically certified psychiatric sickness absence data were obtained directly from the employer. Rate ratios (RRs) of sickness absence were calculated using Poisson regression models, adjusting for age, marital status, social support, stressful life events, alcohol consumption, body mass and depressive symptoms at baseline. Participants simultaneously exposed to high levels of work and family demands (> or =2 work stress factors and > or =4 dependents) had significantly higher rates of sickness absence due to non-psychotic psychiatric disorders than participants with lower levels of demands (compared to participants exposed to 0-1 work stress factors and with 1-3 dependents, age-adjusted rate ratios were 2.37 (95% CI 1.02-5.52) in men and 6.36 (95% CI 3.38-11.94) in women. After adjusting for baseline socio-demographic, behavioral and health characteristics, these RRs were respectively reduced to 1.82 (95% CI 0.86-3.87) in men, 5.04 (95% CI 2.84-8.90) in women. The effect of multiple work and family demands was strongest for sickness absence due to depression: age-adjusted RRs among participants with the highest level of work and family demands were 4.70 (1.96-11.24) in men, 8.57 (4.26-17.22) in women; fully adjusted RRs: 3.55 (95% CI 1.62-7.77) in men, 6.58 (95%CI 3.46-12.50) in women. Men and women simultaneously exposed to high levels of work stress and family demands are at high risk of experiencing mental health problems, particularly depression.
Cappell, M S; Spray, D C; Bennett, M V
1988-06-28
Protractor muscles in the gastropod mollusc Navanax inermis exhibit typical spontaneous miniature end plate potentials with mean amplitude 1.71 +/- 1.19 (standard deviation) mV. The evoked end plate potential is quantized, with a quantum equal to the miniature end plate potential amplitude. When their rate is stationary, occurrence of miniature end plate potentials is a random, Poisson process. When non-stationary, spontaneous miniature end plate potential occurrence is a non-stationary Poisson process, a Poisson process with the mean frequency changing with time. This extends the random Poisson model for miniature end plate potentials to the frequently observed non-stationary occurrence. Reported deviations from a Poisson process can sometimes be accounted for by the non-stationary Poisson process and more complex models, such as clustered release, are not always needed.
Tighe, Elizabeth L; Schatschneider, Christopher
2016-07-01
The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in adult basic education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82%-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. © Hammill Institute on Disabilities 2014.
Stepwise versus Hierarchical Regression: Pros and Cons
ERIC Educational Resources Information Center
Lewis, Mitzi
2007-01-01
Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…
Calculation of the Poisson cumulative distribution function
NASA Technical Reports Server (NTRS)
Bowerman, Paul N.; Nolty, Robert G.; Scheuer, Ernest M.
1990-01-01
A method for calculating the Poisson cdf (cumulative distribution function) is presented. The method avoids computer underflow and overflow during the process. The computer program uses this technique to calculate the Poisson cdf for arbitrary inputs. An algorithm that determines the Poisson parameter required to yield a specified value of the cdf is presented.
Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading
Sanborn, Brett; Song, Bo
2018-06-03
Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less
Poisson's Ratio of a Hyperelastic Foam Under Quasi-static and Dynamic Loading
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sanborn, Brett; Song, Bo
Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratiomore » of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. Here, the Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.« less
Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.
Khazraee, S Hadi; Sáez-Castillo, Antonio Jose; Geedipally, Srinivas Reddy; Lord, Dominique
2015-05-01
The hyper-Poisson distribution can handle both over- and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation-specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper-Poisson distribution in analyzing motor vehicle crash count data. The hyper-Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway-highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness-of-fit measures indicated that the hyper-Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper-Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway-Maxwell-Poisson model previously developed for the same data set. The advantages of the hyper-Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper-Poisson model can handle both over- and underdispersed crash data. Although not a major issue for the Conway-Maxwell-Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model. © 2014 Society for Risk Analysis.
Stochastic modeling of soil salinity
NASA Astrophysics Data System (ADS)
Suweis, S.; Porporato, A. M.; Daly, E.; van der Zee, S.; Maritan, A.; Rinaldo, A.
2010-12-01
A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The equations for the probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equations to a single stochastic differential equation (generalized Langevin equation) driven by multiplicative Poisson noise. Generalized Langevin equations with multiplicative white Poisson noise pose the usual Ito (I) or Stratonovich (S) prescription dilemma. Different interpretations lead to different results and then choosing between the I and S prescriptions is crucial to describe correctly the dynamics of the model systems. We show how this choice can be determined by physical information about the timescales involved in the process. We also show that when the multiplicative noise is at most linear in the random variable one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We then apply these results to the generalized Langevin equation that drives the salt mass dynamics. The stationary analytical solutions for the probability density functions of salt mass and concentration provide insight on the interplay of the main soil, plant and climate parameters responsible for long term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in longterm soil salinization trends, with significant consequences, e.g. for climate change impacts on rain fed agriculture.
Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.
Chatzis, Sotirios P; Andreou, Andreas S
2015-11-01
Reliably predicting software defects is one of the most significant tasks in software engineering. Two of the major components of modern software reliability modeling approaches are: 1) extraction of salient features for software system representation, based on appropriately designed software metrics and 2) development of intricate regression models for count data, to allow effective software reliability data modeling and prediction. Surprisingly, research in the latter frontier of count data regression modeling has been rather limited. More specifically, a lack of simple and efficient algorithms for posterior computation has made the Bayesian approaches appear unattractive, and thus underdeveloped in the context of software reliability modeling. In this paper, we try to address these issues by introducing a novel Bayesian regression model for count data, based on the concept of max-margin data modeling, effected in the context of a fully Bayesian model treatment with simple and efficient posterior distribution updates. Our novel approach yields a more discriminative learning technique, making more effective use of our training data during model inference. In addition, it allows of better handling uncertainty in the modeled data, which can be a significant problem when the training data are limited. We derive elegant inference algorithms for our model under the mean-field paradigm and exhibit its effectiveness using the publicly available benchmark data sets.
Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru
2017-09-01
Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Klambauer, Günter; Schwarzbauer, Karin; Mayr, Andreas; Clevert, Djork-Arné; Mitterecker, Andreas; Bodenhofer, Ulrich; Hochreiter, Sepp
2012-05-01
Quantitative analyses of next-generation sequencing (NGS) data, such as the detection of copy number variations (CNVs), remain challenging. Current methods detect CNVs as changes in the depth of coverage along chromosomes. Technological or genomic variations in the depth of coverage thus lead to a high false discovery rate (FDR), even upon correction for GC content. In the context of association studies between CNVs and disease, a high FDR means many false CNVs, thereby decreasing the discovery power of the study after correction for multiple testing. We propose 'Copy Number estimation by a Mixture Of PoissonS' (cn.MOPS), a data processing pipeline for CNV detection in NGS data. In contrast to previous approaches, cn.MOPS incorporates modeling of depths of coverage across samples at each genomic position. Therefore, cn.MOPS is not affected by read count variations along chromosomes. Using a Bayesian approach, cn.MOPS decomposes variations in the depth of coverage across samples into integer copy numbers and noise by means of its mixture components and Poisson distributions, respectively. The noise estimate allows for reducing the FDR by filtering out detections having high noise that are likely to be false detections. We compared cn.MOPS with the five most popular methods for CNV detection in NGS data using four benchmark datasets: (i) simulated data, (ii) NGS data from a male HapMap individual with implanted CNVs from the X chromosome, (iii) data from HapMap individuals with known CNVs, (iv) high coverage data from the 1000 Genomes Project. cn.MOPS outperformed its five competitors in terms of precision (1-FDR) and recall for both gains and losses in all benchmark data sets. The software cn.MOPS is publicly available as an R package at http://www.bioinf.jku.at/software/cnmops/ and at Bioconductor.
Use of Empirical Estimates of Shrinkage in Multiple Regression: A Caution.
ERIC Educational Resources Information Center
Kromrey, Jeffrey D.; Hines, Constance V.
1995-01-01
The accuracy of four empirical techniques to estimate shrinkage in multiple regression was studied through Monte Carlo simulation. None of the techniques provided unbiased estimates of the population squared multiple correlation coefficient, but the normalized jackknife and bootstrap techniques demonstrated marginally acceptable performance with…
Enhance-Synergism and Suppression Effects in Multiple Regression
ERIC Educational Resources Information Center
Lipovetsky, Stan; Conklin, W. Michael
2004-01-01
Relations between pairwise correlations and the coefficient of multiple determination in regression analysis are considered. The conditions for the occurrence of enhance-synergism and suppression effects when multiple determination becomes bigger than the total of squared correlations of the dependent variable with the regressors are discussed. It…
A Martingale Characterization of Mixed Poisson Processes.
1985-10-01
03LA A 11. TITLE (Inciuae Security Clanafication, ",A martingale characterization of mixed Poisson processes " ________________ 12. PERSONAL AUTHOR... POISSON PROCESSES Jostification .......... . ... . . Di.;t ib,,jtion by Availability Codes Dietmar Pfeifer* Technical University Aachen Dist Special and...Mixed Poisson processes play an important role in many branches of applied probability, for instance in insurance mathematics and physics (see Albrecht
1978-12-01
Poisson processes . The method is valid for Poisson processes with any given intensity function. The basic thinning algorithm is modified to exploit several refinements which reduce computer execution time by approximately one-third. The basic and modified thinning programs are compared with the Poisson decomposition and gap-statistics algorithm, which is easily implemented for Poisson processes with intensity functions of the form exp(a sub 0 + a sub 1t + a sub 2 t-squared. The thinning programs are competitive in both execution
Deformation mechanisms in negative Poisson's ratio materials - Structural aspects
NASA Technical Reports Server (NTRS)
Lakes, R.
1991-01-01
Poisson's ratio in materials is governed by the following aspects of the microstructure: the presence of rotational degrees of freedom, non-affine deformation kinematics, or anisotropic structure. Several structural models are examined. The non-affine kinematics are seen to be essential for the production of negative Poisson's ratios for isotropic materials containing central force linkages of positive stiffness. Non-central forces combined with pre-load can also give rise to a negative Poisson's ratio in isotropic materials. A chiral microstructure with non-central force interaction or non-affine deformation can also exhibit a negative Poisson's ratio. Toughness and damage resistance in these materials may be affected by the Poisson's ratio itself, as well as by generalized continuum aspects associated with the microstructure.
Exact solution for the Poisson field in a semi-infinite strip.
Cohen, Yossi; Rothman, Daniel H
2017-04-01
The Poisson equation is associated with many physical processes. Yet exact analytic solutions for the two-dimensional Poisson field are scarce. Here we derive an analytic solution for the Poisson equation with constant forcing in a semi-infinite strip. We provide a method that can be used to solve the field in other intricate geometries. We show that the Poisson flux reveals an inverse square-root singularity at a tip of a slit, and identify a characteristic length scale in which a small perturbation, in a form of a new slit, is screened by the field. We suggest that this length scale expresses itself as a characteristic spacing between tips in real Poisson networks that grow in response to fluxes at tips.
Doubled full shot noise in quantum coherent superconductor-semiconductor junctions.
Lefloch, F; Hoffmann, C; Sanquer, M; Quirion, D
2003-02-14
We performed low temperature shot noise measurements in superconductor (TiN) strongly disordered normal metal (heavily doped Si) weakly transparent junctions. We show that the conductance has a maximum due to coherent multiple Andreev reflections at low energy and that the shot noise is then twice the Poisson noise (S = 4eI). When the subgap conductance reaches its minimum at finite voltage the shot noise changes to the normal value (S = 2eI) due to a large quasiparticle contribution.
An Effect Size for Regression Predictors in Meta-Analysis
ERIC Educational Resources Information Center
Aloe, Ariel M.; Becker, Betsy Jane
2012-01-01
A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…
Regression Analysis: Legal Applications in Institutional Research
ERIC Educational Resources Information Center
Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.
2008-01-01
This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…
RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,
This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)
Incremental Net Effects in Multiple Regression
ERIC Educational Resources Information Center
Lipovetsky, Stan; Conklin, Michael
2005-01-01
A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…
Floating Data and the Problem with Illustrating Multiple Regression.
ERIC Educational Resources Information Center
Sachau, Daniel A.
2000-01-01
Discusses how to introduce basic concepts of multiple regression by creating a large-scale, three-dimensional regression model using the classroom walls and floor. Addresses teaching points that should be covered and reveals student reaction to the model. Finds that the greatest benefit of the model is the low fear, walk-through, nonmathematical…
Getov, Ivan; Petukh, Marharyta; Alexov, Emil
2016-04-07
Folding free energy is an important biophysical characteristic of proteins that reflects the overall stability of the 3D structure of macromolecules. Changes in the amino acid sequence, naturally occurring or made in vitro, may affect the stability of the corresponding protein and thus could be associated with disease. Several approaches that predict the changes of the folding free energy caused by mutations have been proposed, but there is no method that is clearly superior to the others. The optimal goal is not only to accurately predict the folding free energy changes, but also to characterize the structural changes induced by mutations and the physical nature of the predicted folding free energy changes. Here we report a new method to predict the Single Amino Acid Folding free Energy Changes (SAAFEC) based on a knowledge-modified Molecular Mechanics Poisson-Boltzmann (MM/PBSA) approach. The method is comprised of two main components: a MM/PBSA component and a set of knowledge based terms delivered from a statistical study of the biophysical characteristics of proteins. The predictor utilizes a multiple linear regression model with weighted coefficients of various terms optimized against a set of experimental data. The aforementioned approach yields a correlation coefficient of 0.65 when benchmarked against 983 cases from 42 proteins in the ProTherm database. the webserver can be accessed via http://compbio.clemson.edu/SAAFEC/.
Stafoggia, Massimo; Schneider, Alexandra; Cyrys, Josef; Samoli, Evangelia; Andersen, Zorana Jovanovic; Bedada, Getahun Bero; Bellander, Tom; Cattani, Giorgio; Eleftheriadis, Konstantinos; Faustini, Annunziata; Hoffmann, Barbara; Jacquemin, Bénédicte; Katsouyanni, Klea; Massling, Andreas; Pekkanen, Juha; Perez, Noemi; Peters, Annette; Quass, Ulrich; Yli-Tuomi, Tarja; Forastiere, Francesco
2017-03-01
Epidemiologic evidence on the association between short-term exposure to ultrafine particles and mortality is weak, due to the lack of routine measurements of these particles and standardized multicenter studies. We investigated the relationship between ultrafine particles and particulate matter (PM) and daily mortality in eight European urban areas. We collected daily data on nonaccidental and cardiorespiratory mortality, particle number concentrations (as proxy for ultrafine particle number concentration), fine and coarse PM, gases and meteorologic parameters in eight urban areas of Finland, Sweden, Denmark, Germany, Italy, Spain, and Greece, between 1999 and 2013. We applied city-specific time-series Poisson regression models and pooled them with random-effects meta-analysis. We estimated a weak, delayed association between particle number concentration and nonaccidental mortality, with mortality increasing by approximately 0.35% per 10,000 particles/cm increases in particle number concentration occurring 5 to 7 days before death. A similar pattern was found for cause-specific mortality. Estimates decreased after adjustment for fine particles (PM2.5) or nitrogen dioxide (NO2). The stronger association found between particle number concentration and mortality in the warmer season (1.14% increase) became null after adjustment for other pollutants. We found weak evidence of an association between daily ultrafine particles and mortality. Further studies are required with standardized protocols for ultrafine particle data collection in multiple European cities over extended study periods.
Clustering of risk factors for chronic diseases among adolescents from Southern Brazil
Dumith, Samuel C.; Muniz, Ludmila C.; Tassitano, Rafael M.; Hallal, Pedro C.; Menezes, Ana M.B.
2012-01-01
Objective To investigate the clustering of risk behaviors for chronic non-communicable diseases and their associated factors among adolescents from Southern Brazil. Methods In 2008, a survey was conducted with 3990 adolescents aged 14–15 years (mean: 14.3; SD: 0.6) from the 1993 Pelotas Birth Cohort Study. Clustering was determined by comparing observed (O) and expected (E) prevalence of all possible combinations of the four risk factors investigated (smoking, alcohol intake, low fruit intake, and physical inactivity). We carried out Poisson regression to evaluate the effect of individual characteristics on the presence of at least three risk behaviors. Results All risk factors tended to cluster together (O/E prevalence = 3.0), especially smoking and alcohol intake (odds ratio to present on behavior in the presence of other > 5.0). Approximately 15% of adolescents displayed three or more risk behaviors. Females (adjusted OR = 1.55), people 15 years and older (OR = 1.47), with black skin color (OR = 1.23), and of low socioeconomic level (OR = 1.29) were more likely to display three or more risk factors. Conclusion These findings suggest that lifestyle-related risk factors tend to cluster among adolescents. Identifying subgroups at greater risk of simultaneously engaging in multiple risk behaviors may aid in the planning of preventive strategies. PMID:22484392
Ding, Chuan; Chen, Peng; Jiao, Junfeng
2018-03-01
Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual interaction effects and their non-linear effects on automobile-involved pedestrian crashes. This study adopts the approach of Multiple Additive Poisson Regression Trees (MAPRT) to fill such gaps using pedestrian collision data collected from Seattle, Washington. Traffic analysis zones are chosen as the analytical unit. The effects of various factors on pedestrian crash frequency investigated include characteristics the of road network, street elements, land use patterns, and traffic demand. Density and the degree of mixed land use have major effects on pedestrian crash frequency, accounting for approximately 66% of the effects in total. More importantly, some factors show clear non-linear relationships with pedestrian crash frequency, challenging the linearity assumption commonly used in existing studies which employ statistical models. With various accurately identified non-linear relationships between the built environment and pedestrian crashes, this study suggests local agencies to adopt geo-spatial differentiated policies to establish a safe walking environment. These findings, especially the effective ranges of the built environment, provide evidence to support for transport and land use planning, policy recommendations, and road safety programs. Copyright © 2018 Elsevier Ltd. All rights reserved.
Self-management practices among primary care patients with musculoskeletal pain and depression.
Damush, Teresa M; Wu, Jingwei; Bair, Matthew J; Sutherland, Jason M; Kroenke, Kurt
2008-08-01
The objective of this study was to assess the effect of clinical depression on pain self-management practices. We employed a cross-sectional analysis of baseline data from the Stepped Care for Affective disorders and Musculoskeletal Pain (SCAMP) study. Participants included 250 patients with pain and comorbid depression and 250 patients with pain only and were enrolled from urban university and VA primary care clinics. Musculoskeletal pain was defined as low back, hip or knee pain present >or=3 months and with at least a moderate, Brief Pain Inventory severity score >or=5. Depression was defined as a PHQ-9 score >or=10. We used multiple logistic and Poisson regression to assess the relationship between individual and combined effects of depression and pain severity on two core pain self-management skills: exercise duration and cognitive strategies. Depressed patients exercised less per week than did nondepressed patients but showed a trend towards more frequent use of cognitive strategies. On multivariable analysis, depression severity substantially decreased the use of exercise as a pain self-management strategy. In contrast, depression and pain severity interacted to increase the use of cognitive strategies. Depression and pain severity have differential effects on self-management practices. Understanding the differences between preferential strategies of pain patients with and without depression may be useful in tailoring pain self-management programs.
Mutambudzi, Miriam
2017-01-01
Research evaluating the relation of workplace psychosocial factors to mental health among U.S. women of different racial/ethnic backgrounds is limited. This study investigated the relationship between work-related psychosocial factors and mental health among non-Hispanic Black, Hispanic, and non-Hispanic White women using data from the 2010 National Health Interview Survey. Independent variables of interest included job insecurity, workplace harassment, and work-family conflict (WFC). Multiple Poisson regression models were used to examine the associations between the outcome and independent variables. The prevalence of unfavorable mental health was highest among non-Hispanic Black women (36%) compared to Hispanic (34%) and non-Hispanic White (30%) women. A higher proportion of non-Hispanic Black women reported WFC compared to Hispanics and non-Hispanic Whites (χ 2 = 15.50, p < .01), while more Hispanics reported job insecurity (χ 2 = 116.81, p < .01). Prevalence of workplace harassment did not differ significantly by race/ethnicity. Odds of unfavorable mental health were significantly higher for women reporting psychosocial work factors. Unexpectedly, a greater association between psychosocial work factors and unfavorable mental health was observed among non-Hispanic White women compared to non-White women; however, caution should be taken in interpreting these cross-sectional results. Future studies should investigate temporal associations and additional psychosocial variables that were not available for use in the current study.
Significant and Sustained Reduction in Chemotherapy Errors Through Improvement Science.
Weiss, Brian D; Scott, Melissa; Demmel, Kathleen; Kotagal, Uma R; Perentesis, John P; Walsh, Kathleen E
2017-04-01
A majority of children with cancer are now cured with highly complex chemotherapy regimens incorporating multiple drugs and demanding monitoring schedules. The risk for error is high, and errors can occur at any stage in the process, from order generation to pharmacy formulation to bedside drug administration. Our objective was to describe a program to eliminate errors in chemotherapy use among children. To increase reporting of chemotherapy errors, we supplemented the hospital reporting system with a new chemotherapy near-miss reporting system. After the model for improvement, we then implemented several interventions, including a daily chemotherapy huddle, improvements to the preparation and delivery of intravenous therapy, headphones for clinicians ordering chemotherapy, and standards for chemotherapy administration throughout the hospital. Twenty-two months into the project, we saw a centerline shift in our U chart of chemotherapy errors that reached the patient from a baseline rate of 3.8 to 1.9 per 1,000 doses. This shift has been sustained for > 4 years. In Poisson regression analyses, we found an initial increase in error rates, followed by a significant decline in errors after 16 months of improvement work ( P < .001). After the model for improvement, our improvement efforts were associated with significant reductions in chemotherapy errors that reached the patient. Key drivers for our success included error vigilance through a huddle, standardization, and minimization of interruptions during ordering.
Exposure to hepatitis C virus in homeless men in Central Brazil: a cross-sectional study.
Ferreira, Priscilla Martins; Guimarães, Rafael Alves; Souza, Christiane Moreira; Guimarães, Lara Cristina da Cunha; Barros, Cleiciane Vieira de Lima; Caetano, Karlla Antonieta Amorim; Rezza, Giovanni; Spadoni, Lila; Brunini, Sandra Maria
2017-01-18
Homeless men are highly vulnerable to acquisition of the hepatitis C virus (HCV) compared to the general population. In Brazil, a country of continental dimensions, the extent of HCV infection in this population remains unknown. The objective of this study is to investigate the epidemiological profile of exposure to HCV in homeless men in Central Brazil. A Cross-sectional study was conducted in 481 men aged over 18 years attending therapeutic communities specialized in the recovery and reintegration of homeless people. Participants were tested for anti-HCV markers using rapid tests. Poisson regression analysis was used to verify the risk factors associated with exposure to HCV. The prevalence of HCV exposure was 2.5% (95.0% CI: 1.4 to 4.3%) and was associated with age, absence of family life, injection drug use, number of sexual partners, and history of sexually transmitted infections (STI). Participants reported multiple risk behaviors, such as alcohol (78.9%), cocaine (37.1%) and/or crack use (53.1%), and inconsistent condom use (82.6%). Injection drug use was reported by 8.7% of participants. The prevalence of HCV infection among homeless men was relatively high. Several risk behaviors were commonly reported, which shows the high vulnerability of this population. These findings emphasize the need for the development of specific strategies to reduce the risk of HCV among homeless men.
A Count Model to Study the Correlates of 60 Min of Daily Physical Activity in Portuguese Children
Borges, Alessandra; Gomes, Thayse Natacha; Santos, Daniel; Pereira, Sara; dos Santos, Fernanda K.; Chaves, Raquel; Katzmarzyk, Peter T.; Maia, José
2015-01-01
This study aimed to present data on Portuguese children (aged 9–11 years) complying with moderate-to-vigorous physical activity (MVPA) guidelines, and to identify the importance of correlates from multiple domains associated with meeting the guidelines. Physical activity (PA) was objectively assessed by accelerometry throughout seven days on 777 children. A count model using Poisson regression was used to identify the best set of correlates that predicts the variability in meeting the guidelines. Only 3.1% of children met the recommended daily 60 min of MVPA for all seven days of the week. Further, the Cochrane–Armitage chi-square test indicated a linear and negative trend (p < 0.001) from none to all seven days of children complying with the guidelines. The count model explained 22% of the variance in meeting MVPA guidelines daily. Being a girl, having a higher BMI, belonging to families with higher income, sleeping more and taking greater time walking from home to a sporting venue significantly reduced the probability of meeting daily recommended MVPA across the seven days. Furthermore, compared to girls, increasing sleep time in boys increased their chances of compliance with the MVPA recommendations. These results reinforce the relevance of considering different covariates’ roles on PA compliance when designing efficient intervention strategies to promote healthy and active lifestyles in children. PMID:25730296
Sanna, Alice; Le Strat, Yann; Roudot-Thoraval, Françoise; Deuffic Burban, Sylvie; Carrieri, Patrizia; Delarocque-Astagneau, Elisabeth; Larsen, Christine
2017-01-01
Given recent profound improvements in the effectiveness of antiviral treatment for chronic Hepatitis C virus (HCV) infection, we aimed to describe the characteristics of patients referred to hepatology expert centres in France from 2000 to 2007 and from 2010 to 2014, and to identify factors associated with severe liver disease at their first visit for evaluation. We analysed data from two sources covering all of France: the former hepatitis C surveillance network, which included patients between 2000 and 2007, and the ANRS CO22 HEPATHER multi-centre cohort, which included patients between 2012 and 2014. Severe liver disease (SLD) was defined as the presence of either cirrhosis (histological, biochemical or clinical) or hepatocellular carcinoma. Multivariable Poisson regression models were used to identify the factors associated with SLD in complete-case analysis and after multiple imputation. Overall, 16,851 patients were included in the analysis and SLD was diagnosed in 11.6%. SLD at first visit was significantly associated with known risk factors (male sex, history of excessive alcohol intake, HCV genotype 3), late referral to hepatologists after diagnosis and HCV diagnosis at an older age. Providing earlier specialised care and treatment may be an important target for public health action. PMID:28797326
A count model to study the correlates of 60 min of daily physical activity in Portuguese children.
Borges, Alessandra; Gomes, Thayse Natacha; Santos, Daniel; Pereira, Sara; dos Santos, Fernanda K; Chaves, Raquel; Katzmarzyk, Peter T; Maia, José
2015-02-26
This study aimed to present data on Portuguese children (aged 9-11 years) complying with moderate-to-vigorous physical activity (MVPA) guidelines, and to identify the importance of correlates from multiple domains associated with meeting the guidelines. Physical activity (PA) was objectively assessed by accelerometry throughout seven days on 777 children. A count model using Poisson regression was used to identify the best set of correlates that predicts the variability in meeting the guidelines. Only 3.1% of children met the recommended daily 60 min of MVPA for all seven days of the week. Further, the Cochrane-Armitage chi-square test indicated a linear and negative trend (p<0.001) from none to all seven days of children complying with the guidelines. The count model explained 22% of the variance in meeting MVPA guidelines daily. Being a girl, having a higher BMI, belonging to families with higher income, sleeping more and taking greater time walking from home to a sporting venue significantly reduced the probability of meeting daily recommended MVPA across the seven days. Furthermore, compared to girls, increasing sleep time in boys increased their chances of compliance with the MVPA recommendations. These results reinforce the relevance of considering different covariates' roles on PA compliance when designing efficient intervention strategies to promote healthy and active lifestyles in children.
What Happened to Our Environment and Mental Health as a Result of Hurricane Sandy?
Lin, Shao; Lu, Yi; Justino, John; Dong, Guanghui; Lauper, Ursula
2016-06-01
This study describes findings of the impacts of Hurricane Sandy on environmental factors including power outages, air quality, water quality, and weather factors and how these affected mental health during the hurricane. An ecological study was conducted at the county level to describe changes in environmental factors-especially power outages-and their relationships to emergency department (ED) visits for mental health problems by use of a Poisson regression model. We found that many environmental hazards occurred as co-exposures during Hurricane Sandy in addition to flooding. Mental health ED visits corresponded with the peak of maximum daily power blackouts, with a 3-day lag, and were positively associated with power blackouts in Bronx (prevalence ratio [PR]: 8.82, 95% confidence interval [CI]: 1.27-61.42) and Queens (PR: 2.47, 95% CI: 1.05-5.82) counties. A possible dose-response relationship was found between the quantile of maximum blackout percentage and the risk of mental health in the Bronx. We found that multiple co-environmental hazards occurred during Hurricane Sandy, especially power blackouts that mediated this disaster's impacts. The effects of power outage on mental health had large geographic variations and were substantial, especially in communities with low sociodemographic status. These findings may provide new insights for future disaster response and preparedness efforts. (Disaster Med Public Health Preparedness. 2016;10:314-319).
Forcey, G.M.; Linz, G.M.; Thogmartin, W.E.; Bleier, W.J.
2008-01-01
Blackbirds share wetland habitat with many waterfowl species in Bird Conservation Region 11 (BCR 11), the prairie potholes. Because of similar habitat preferences, there may be associations between blackbird populations and populations of one or more species of waterfowl in BCR11. This study models populations of red-winged blackbirds and yellow-headed blackbirds as a function of multiple waterfowl species using data from the North American Breeding Bird Survey within BCR11. For each blackbird species, we created a global model with blackbird abundance modeled as a function of 11 waterfowl species; nuisance effects (year, route, and observer) also were included in the model. Hierarchical Poisson regression models were fit using Markov chain Monte Carlo methods in WinBUGS 1.4.1. Waterfowl abundances were weakly associated with blackbird numbers, and no single waterfowl species showed a strong correlation with any blackbird species. These findings suggest waterfowl abundance from a single species is not likely a good bioindicator of blackbird abundance; however, a global model provided good fit for predicting red-winged blackbird abundance. Increased model complexity may be required for accurate predictions of blackbird abundance; the amount of data required to construct appropriate models may limit this approach for predicting blackbird abundance in the prairie potholes. Copyright ?? Taylor & Francis Group, LLC.
Multiple domains of social support are associated with diabetes self-management among Veterans.
Gray, Kristen E; Hoerster, Katherine D; Reiber, Gayle E; Bastian, Lori A; Nelson, Karin M
2018-01-01
Objectives To examine, among Veterans, relationships of general social support and diabetes-specific social support for physical activity and healthy eating with diabetes self-management behaviors. Methods Patients from VA Puget Sound, Seattle completed a cross-sectional survey in 2012-2013 ( N = 717). We measured (a) general social support and (b) diabetes-specific social support for healthy eating and physical activity with domains reflecting support person participation, encouragement, and sharing ideas. Among 189 self-reporting diabetes patients, we fit linear and modified Poisson regression models estimating associations of social support with diabetes self-management behaviors: adherence to general and diabetes-specific diets and blood glucose monitoring (days/week); physical activity (< vs. ≥150 min/week); and smoking status (smoker/non-smoker). Results General social support was not associated with diabetes self-management. For diabetes-specific social support, higher healthy eating support scores across all domains were associated with better adherence to general and diabetes-specific diets. Higher physical activity support scores were positively associated with ≥150 min/week of physical activity only for the participation domain. Discussion Diabetes-specific social support was a stronger and more consistent correlate of improved self-management than general social support, particularly for lifestyle behaviors. Incorporating family/friends into Veterans' diabetes self-management routines may lead to better self-management and improvements in disease control and outcomes.
Engler, Tânia Mara Nascimento de Miranda; Aguiar, Márcia Helena de Assis; Furtado, Íris Aline Brito; Ribeiro, Samile Pereira; de Oliveira, Pérola; Mello, Paulo Andrade; Padula, Marcele Pescuma Capeletti; Beraldo, Paulo Sérgio Siebra
The objective of this study was to define which stroke-related factors constitute independent variables in the incidence of intestinal constipation (IC) of chronic patients admitted to a hospital rehabilitation program. All patients consecutively admitted for rehabilitation were recruited for the study. In the Poisson multiple regression analysis using a hierarchical model, sociodemographic variables, comorbidities, medication, previous history of constipation, life habits, and stroke-related variables were considered for defining factors associated with IC. A 31% prevalence (95% confidence interval [CI]: 25.3-37.1) of IC was detected. Among the factors associated, female gender (adjusted prevalence ratio [PRadjusted] = 1.79; 95% CI: 1.20-2.68), intestinal complaints prior to stroke (PRadjusted = 3.71; 95% CI: 2.60-5.31), intake of less than 800 ml of fluid per day (PRadjusted = 1.72; 95% CI: 1.20- 2.45), age greater than 65 years at brain injury (PRadjusted = 1.67; 95% CI: 1.01-2.75), and partially impaired anterior brain circulation (PRadjusted = 3.35; 95% CI: 1.02-10.97) were associated with IC. Female gender, elderly, prior history of IC, low fluid intake, and partial impairment of anterior brain circulation were factors independently associated with IC in stroke survivors undergoing rehabilitation. These findings require further validation and may serve toward improving bowel retraining programs for this patient group.
Multiparameter linear least-squares fitting to Poisson data one count at a time
NASA Technical Reports Server (NTRS)
Wheaton, Wm. A.; Dunklee, Alfred L.; Jacobsen, Allan S.; Ling, James C.; Mahoney, William A.; Radocinski, Robert G.
1995-01-01
A standard problem in gamma-ray astronomy data analysis is the decomposition of a set of observed counts, described by Poisson statistics, according to a given multicomponent linear model, with underlying physical count rates or fluxes which are to be estimated from the data. Despite its conceptual simplicity, the linear least-squares (LLSQ) method for solving this problem has generally been limited to situations in which the number n(sub i) of counts in each bin i is not too small, conventionally more than 5-30. It seems to be widely believed that the failure of the LLSQ method for small counts is due to the failure of the Poisson distribution to be even approximately normal for small numbers. The cause is more accurately the strong anticorrelation between the data and the wieghts w(sub i) in the weighted LLSQ method when square root of n(sub i) instead of square root of bar-n(sub i) is used to approximate the uncertainties, sigma(sub i), in the data, where bar-n(sub i) = E(n(sub i)), the expected value of N(sub i). We show in an appendix that, avoiding this approximation, the correct equations for the Poisson LLSQ (PLLSQ) problems are actually identical to those for the maximum likelihood estimate using the exact Poisson distribution. We apply the method to solve a problem in high-resolution gamma-ray spectroscopy for the JPL High-Resolution Gamma-Ray Spectrometer flown on HEAO 3. Systematic error in subtracting the strong, highly variable background encountered in the low-energy gamma-ray region can be significantly reduced by closely pairing source and background data in short segments. Significant results can be built up by weighted averaging of the net fluxes obtained from the subtraction of many individual source/background pairs. Extension of the approach to complex situations, with multiple cosmic sources and realistic background parameterizations, requires a means of efficiently fitting to data from single scans in the narrow (approximately = 1.2 keV, HEAO 3) energy channels of a Ge spectrometer, where the expected number of counts obtained per scan may be very low. Such an analysis system is discussed and compared to the method previously used.
Elghafghuf, Adel; Dufour, Simon; Reyher, Kristen; Dohoo, Ian; Stryhn, Henrik
2014-12-01
Mastitis is a complex disease affecting dairy cows and is considered to be the most costly disease of dairy herds. The hazard of mastitis is a function of many factors, both managerial and environmental, making its control a difficult issue to milk producers. Observational studies of clinical mastitis (CM) often generate datasets with a number of characteristics which influence the analysis of those data: the outcome of interest may be the time to occurrence of a case of mastitis, predictors may change over time (time-dependent predictors), the effects of factors may change over time (time-dependent effects), there are usually multiple hierarchical levels, and datasets may be very large. Analysis of such data often requires expansion of the data into the counting-process format - leading to larger datasets - thus complicating the analysis and requiring excessive computing time. In this study, a nested frailty Cox model with time-dependent predictors and effects was applied to Canadian Bovine Mastitis Research Network data in which 10,831 lactations of 8035 cows from 69 herds were followed through lactation until the first occurrence of CM. The model was fit to the data as a Poisson model with nested normally distributed random effects at the cow and herd levels. Risk factors associated with the hazard of CM during the lactation were identified, such as parity, calving season, herd somatic cell score, pasture access, fore-stripping, and proportion of treated cases of CM in a herd. The analysis showed that most of the predictors had a strong effect early in lactation and also demonstrated substantial variation in the baseline hazard among cows and between herds. A small simulation study for a setting similar to the real data was conducted to evaluate the Poisson maximum likelihood estimation approach with both Gaussian quadrature method and Laplace approximation. Further, the performance of the two methods was compared with the performance of a widely used estimation approach for frailty Cox models based on the penalized partial likelihood. The simulation study showed good performance for the Poisson maximum likelihood approach with Gaussian quadrature and biased variance component estimates for both the Poisson maximum likelihood with Laplace approximation and penalized partial likelihood approaches. Copyright © 2014. Published by Elsevier B.V.
Malt liquor marketing in inner cities: the role of neighborhood racial composition.
McKee, Pat; Jones-Webb, Rhonda; Hannan, Peter; Pham, Lan
2011-01-01
In response to anecdotal reports that African American neighborhoods are targeted for high-alcohol malt liquor advertising, the authors observed alcohol ads on off-premise alcohol outlets, billboards, and transit structures in 10 U.S. cities over 3 years. Malt liquor ads were prevalent on storefronts, but rare on billboards. Using Poisson regression, the authors found that storefront malt liquor ads were more common in neighborhoods with higher percentages of African Americans, even after controlling for social and physical disorder. Results suggest that policymakers attempting to reduce malt liquor-related harms may do well to consider regulations that limit storefront advertising exposure.
Yun, Huifeng; Xie, Fenglong; Baddley, John W; Winthrop, Kevin; Saag, Kenneth G; Curtis, Jeffrey R
2017-07-01
The protection duration of herpes zoster (HZ) vaccination is unclear among patients with autoimmune (AI) diseases. Using 2006-2013 Medicare data, HZ vaccinated patients with AI were matched 1:2 to unvaccinated HZ. Incidence rates (IR) and adjusted risk ratios over time were calculated using Poisson regression. Of 59,627 vaccinated patients, crude IR increased from 0.75/100 person-years during the first year post-vaccination to 1.25 during the seventh year. Vaccinated patients had a significantly lower risk of HZ compared with the unvaccinated through 5 years. HZ vaccination was significantly protective only for about 5 years among patients with AI.