EM Adaptive LASSO-A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes.

PubMed

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.

Identifying cholera "hotspots" in Uganda: An analysis of cholera surveillance data from 2011 to 2016

PubMed Central

Bwire, Godfrey; Sack, David A.; Nakinsige, Anne; Naigaga, Martha; Debes, Amanda K.; Ngwa, Moise C.; Brooks, W. Abdullah; Garimoi Orach, Christopher

2017-01-01

Background Despite advance in science and technology for prevention, detection and treatment of cholera, this infectious disease remains a major public health problem in many countries in sub-Saharan Africa, Uganda inclusive. The aim of this study was to identify cholera hotspots in Uganda to guide the development of a roadmap for prevention, control and elimination of cholera in the country. Methodology/Principle findings We obtained district level confirmed cholera outbreak data from 2011 to 2016 from the Ministry of Health, Uganda. Population and rainfall data were obtained from the Uganda Bureau of Statistics, and water, sanitation and hygiene data from the Ministry of Water and Environment. A spatial scan test was performed to identify the significantly high risk clusters. Cholera hotspots were defined as districts whose center fell within a significantly high risk cluster or where a significantly high risk cluster was completely superimposed onto a district. A zero-inflated negative binomial regression model was employed to identify the district level risk factors for cholera. In total 11,030 cases of cholera were reported during the 6-year period. 37(33%) of 112 districts reported cholera outbreaks in one of the six years, and 20 (18%) districts experienced cholera at least twice in those years. We identified 22 districts as high risk for cholera, of which 13 were near a border of Democratic Republic of Congo (DRC), while 9 districts were near a border of Kenya. The relative risk of having cholera inside the high-risk districts (hotspots) were 2 to 22 times higher than elsewhere in the country. In total, 7 million people were within cholera hotspots. The negative binomial component of the ZINB model shows people living near a lake or the Nile river were at increased risk for cholera (incidence rate ratio, IRR = 0.98, 95% CI: 0.97 to 0.99, p < .01); people living near the border of DRC/Kenya or higher incidence rate in the neighboring districts were increased risk for cholera in a district (IRR = 0.99, 95% CI: 0.98 to 1.00, p = .02 and IRR = 1.02, 95% CI: 1.01 to 1.03, p < .01, respectively). The zero inflated component of the ZINB model yielded shorter distance to Kenya or DRC border, higher incidence rate in the neighboring districts, and higher annual rainfall in the district were associated with the risk of having cholera in the district. Conclusions/significance The study identified cholera hotspots during the period 2011–2016. The people located near the international borders, internationally shared lakes and river Nile were at higher risk for cholera outbreaks than elsewhere in the country. Targeting cholera interventions to these locations could prevent and ultimately eliminate cholera in Uganda. PMID:29284003

Identifying cholera "hotspots" in Uganda: An analysis of cholera surveillance data from 2011 to 2016.

PubMed

Bwire, Godfrey; Ali, Mohammad; Sack, David A; Nakinsige, Anne; Naigaga, Martha; Debes, Amanda K; Ngwa, Moise C; Brooks, W Abdullah; Garimoi Orach, Christopher

2017-12-01

Despite advance in science and technology for prevention, detection and treatment of cholera, this infectious disease remains a major public health problem in many countries in sub-Saharan Africa, Uganda inclusive. The aim of this study was to identify cholera hotspots in Uganda to guide the development of a roadmap for prevention, control and elimination of cholera in the country. We obtained district level confirmed cholera outbreak data from 2011 to 2016 from the Ministry of Health, Uganda. Population and rainfall data were obtained from the Uganda Bureau of Statistics, and water, sanitation and hygiene data from the Ministry of Water and Environment. A spatial scan test was performed to identify the significantly high risk clusters. Cholera hotspots were defined as districts whose center fell within a significantly high risk cluster or where a significantly high risk cluster was completely superimposed onto a district. A zero-inflated negative binomial regression model was employed to identify the district level risk factors for cholera. In total 11,030 cases of cholera were reported during the 6-year period. 37(33%) of 112 districts reported cholera outbreaks in one of the six years, and 20 (18%) districts experienced cholera at least twice in those years. We identified 22 districts as high risk for cholera, of which 13 were near a border of Democratic Republic of Congo (DRC), while 9 districts were near a border of Kenya. The relative risk of having cholera inside the high-risk districts (hotspots) were 2 to 22 times higher than elsewhere in the country. In total, 7 million people were within cholera hotspots. The negative binomial component of the ZINB model shows people living near a lake or the Nile river were at increased risk for cholera (incidence rate ratio, IRR = 0.98, 95% CI: 0.97 to 0.99, p < .01); people living near the border of DRC/Kenya or higher incidence rate in the neighboring districts were increased risk for cholera in a district (IRR = 0.99, 95% CI: 0.98 to 1.00, p = .02 and IRR = 1.02, 95% CI: 1.01 to 1.03, p < .01, respectively). The zero inflated component of the ZINB model yielded shorter distance to Kenya or DRC border, higher incidence rate in the neighboring districts, and higher annual rainfall in the district were associated with the risk of having cholera in the district. The study identified cholera hotspots during the period 2011-2016. The people located near the international borders, internationally shared lakes and river Nile were at higher risk for cholera outbreaks than elsewhere in the country. Targeting cholera interventions to these locations could prevent and ultimately eliminate cholera in Uganda.

Predictors and moderators of outcomes of HIV/STD sex risk reduction interventions in substance abuse treatment programs: a pooled analysis of two randomized controlled trials.

PubMed

Crits-Christoph, Paul; Gallop, Robert; Sadicario, Jaclyn S; Markell, Hannah M; Calsyn, Donald A; Tang, Wan; He, Hua; Tu, Xin; Woody, George

2014-01-16

The objective of the current study was to examine predictors and moderators of response to two HIV sexual risk interventions of different content and duration for individuals in substance abuse treatment programs. Participants were recruited from community drug treatment programs participating in the National Institute on Drug Abuse Clinical Trials Network (CTN). Data were pooled from two parallel randomized controlled CTN studies (one with men and one with women) each examining the impact of a multi-session motivational and skills training program, in comparison to a single-session HIV education intervention, on the degree of reduction in unprotected sex from baseline to 3- and 6- month follow-ups. The findings were analyzed using a zero-inflated negative binomial (ZINB) model. Severity of drug use (p < .01), gender (p < .001), and age (p < .001) were significant main effect predictors of number of unprotected sexual occasions (USOs) at follow-up in the non-zero portion of the ZINB model (men, younger participants, and those with greater severity of drug/alcohol abuse have more USOs). Monogamous relationship status (p < .001) and race/ethnicity (p < .001) were significant predictors of having at least one USO vs. none (monogamous individuals and African Americans were more likely to have at least one USO). Significant moderators of intervention effectiveness included recent sex under the influence of drugs/alcohol (p < .01 in non-zero portion of model), duration of abuse of primary drug (p < .05 in non-zero portion of model), and Hispanic ethnicity (p < .01 in the zero portion, p < .05 in the non-zero portion of model). These predictor and moderator findings point to ways in which patients may be selected for the different HIV sexual risk reduction interventions and suggest potential avenues for further development of the interventions for increasing their effectiveness within certain subgroups.

Should the poor have no medicines to cure? A study on the association between social class and social security among the rural migrant workers in urban China.

PubMed

Guan, Ming

2017-11-07

The rampant urbanization and medical marketization in China have resulted in increased vulnerabilities to health and socioeconomic disparities among the rural migrant workers in urban China. In the Chinese context, the socioeconomic characteristics of rural migrant workers have attracted considerable research attention in the recent past years. However, to date, no previous studies have explored the association between the socioeconomic factors and social security among the rural migrant workers in urban China. This study aims to explore the association between socioeconomic inequity and social security inequity and the subsequent associations with medical inequity and reimbursement rejection. Data from a regionally representative sample of 2009 Survey of Migrant Workers in Pearl River Delta in China were used for analyses. Multiple logistic regressions were used to analyze the impacts of socioeconomic factors on the eight dimensions of social security (sick pay, paid leave, maternity pay, medical insurance, pension insurance, occupational injury insurance, unemployment insurance, and maternity insurance) and the impacts of social security on medical reimbursement rejection. The zero-inflated negative binomial regression model (ZINB regression) was adopted to explore the relationship between socioeconomic factors and hospital visits among the rural migrant workers with social security. The study population consisted of 848 rural migrant workers with high income who were young and middle-aged, low-educated, and covered by social security. Reimbursement rejection and abusive supervision for the rural migrant workers were observed. Logistic regression analysis showed that there were significant associations between socioeconomic factors and social security. ZINB regression showed that there were significant associations between socioeconomic factors and hospital visits among the rural migrant workers. Also, several dimensions of social security had significant associations with reimbursement rejections. This study showed that social security inequity, medical inequity, and reimbursement inequity happened to the rural migrant workers simultaneously. Future policy should strengthen health justice and enterprises' medical responsibilities to the employed rural migrant workers.

Valuing Treatment With Infliximab for Ankylosing Spondylitis Using a Willingness-to-Pay Approach.

PubMed

Webers, Casper; Essers, Ivette; van Tubergen, Astrid; Braun, Jürgen; Heldmann, Frank; Baraliakos, Xenofon; Boonen, Annelies

2018-04-01

To investigate willingness to pay (WTP) for treatment with infliximab by patients with ankylosing spondylitis (AS) and explore factors associated with WTP. Data from 85 patients participating in the European AS Infliximab Cohort (EASIC) open-label extension of the AS Study for the Evaluation of Recombinant Infliximab Therapy (ASSERT) were used. WTP was included at baseline in EASIC and comprised a hypothetical scenario exploring whether the patient would be willing to pay for beneficial effects of infliximab and, if so, what amount they would be willing to pay per administration. Factors associated with WTP were explored using zero-inflated negative binomial (ZINB) regressions. Of the 85 patients, 63 (74.1%) were willing to pay, and among these, the mean amount they were willing to pay per administration was €275 (median €100 [interquartile range €50-200]). Multivariable ZINB analysis showed that Assessment of SpondyloArthritis international Society criteria for 20% improvement (ASAS20) response was associated with a 7-fold lower likelihood to pay 0 euros (odds ratio [OR] 0.14 [95% confidence interval (95% CI) 0.03-0.71]) and a 3-fold increase in the amount willing to pay (exp(β) = 3.32 [95% CI 1.44-7.69]). In addition, the country of residence was associated with a lower likelihood to pay 0 euros (OR 0.07 [95% CI 0.02-0.36]), while increased age was associated with the amount willing to pay (exp(β) = 1.05 [95% CI 1.01-1.09]). In a hypothetical scenario, three-quarters of patients with AS receiving long-term infliximab stated that they were willing to pay an out-of-pocket contribution for this treatment. Treatment response contributed to the willingness as well as to the amount patients were willing to pay. © 2017, The Authors. Arthritis Care & Research published by Wiley Periodicals, Inc. on behalf of American College of Rheumatology.

Density of wild prey modulates lynx kill rates on free-ranging domestic sheep.

PubMed

Odden, John; Nilsen, Erlend B; Linnell, John D C

2013-01-01

Understanding the factors shaping the dynamics of carnivore-livestock conflicts is vital to facilitate large carnivore conservation in multi-use landscapes. We investigated how the density of their main wild prey, roe deer Capreolus capreolus, modulates individual Eurasian lynx Lynx lynx kill rates on free-ranging domestic sheep Ovis aries across a range of sheep and roe deer densities. Lynx kill rates on free-ranging domestic sheep were collected in south-eastern Norway from 1995 to 2011 along a gradient of different livestock and wild prey densities using VHF and GPS telemetry. We used zero-inflated negative binomial (ZINB) models including lynx sex, sheep density and an index of roe deer density as explanatory variables to model observed kill rates on sheep, and ranked the models based on their AICc values. The model including the effects of lynx sex and sheep density in the zero-inflation model and the effect of lynx sex and roe deer density in the negative binomial part received most support. Irrespective of sheep density and sex, we found the lowest sheep kill rates in areas with high densities of roe deer. As roe deer density decreased, males killed sheep at higher rates, and this pattern held for both high and low sheep densities. Similarly, females killed sheep at higher rates in areas with high densities of sheep and low densities of roe deer. However, when sheep densities were low females rarely killed sheep irrespective of roe deer density. Our quantification of depredation rates can be the first step towards establishing fairer compensation systems based on more accurate and area specific estimation of losses. This study demonstrates how we can use ecological theory to predict where losses of sheep will be greatest, and can be used to identify areas where mitigation measures are most likely to be needed.

Density of Wild Prey Modulates Lynx Kill Rates on Free-Ranging Domestic Sheep

PubMed Central

Odden, John; Nilsen, Erlend B.; Linnell, John D. C.

2013-01-01

Understanding the factors shaping the dynamics of carnivore–livestock conflicts is vital to facilitate large carnivore conservation in multi-use landscapes. We investigated how the density of their main wild prey, roe deer Capreolus capreolus, modulates individual Eurasian lynx Lynx lynx kill rates on free-ranging domestic sheep Ovis aries across a range of sheep and roe deer densities. Lynx kill rates on free-ranging domestic sheep were collected in south-eastern Norway from 1995 to 2011 along a gradient of different livestock and wild prey densities using VHF and GPS telemetry. We used zero-inflated negative binomial (ZINB) models including lynx sex, sheep density and an index of roe deer density as explanatory variables to model observed kill rates on sheep, and ranked the models based on their AICc values. The model including the effects of lynx sex and sheep density in the zero-inflation model and the effect of lynx sex and roe deer density in the negative binomial part received most support. Irrespective of sheep density and sex, we found the lowest sheep kill rates in areas with high densities of roe deer. As roe deer density decreased, males killed sheep at higher rates, and this pattern held for both high and low sheep densities. Similarly, females killed sheep at higher rates in areas with high densities of sheep and low densities of roe deer. However, when sheep densities were low females rarely killed sheep irrespective of roe deer density. Our quantification of depredation rates can be the first step towards establishing fairer compensation systems based on more accurate and area specific estimation of losses. This study demonstrates how we can use ecological theory to predict where losses of sheep will be greatest, and can be used to identify areas where mitigation measures are most likely to be needed. PMID:24278123

Particulate matter exposure increases JC polyomavirus replication in the human host.

PubMed

Dolci, Maria; Favero, Chiara; Bollati, Valentina; Campo, Laura; Cattaneo, Andrea; Bonzini, Matteo; Villani, Sonia; Ticozzi, Rosalia; Ferrante, Pasquale; Delbue, Serena

2018-05-29

Human polyomaviruses (HPyVs) asymptomatically infect the human population during childhood and establish latency in the host. Viral reactivation and urinary excretion can occur when the immune system is impaired. Exposure to particulate air pollution, including the PM 10 /PM 2.5 components, is a public health problem and has been linked to several disorders. Studies assessing the relationship between PM 10 /PM 2.5 exposure and viral replication are lacking. To investigate the relationship between HPyVs viruria and PM 10 /PM 2.5 exposures. Individual environmental exposure was assessed in 50 healthy adult volunteers using a chemical transport model (CTM) with a municipality resolution for daily PM 10 and monitoring stations data for daily PM 2.5 exposures. For each subject, a urine sample was collected, and HPyVs (JCPyV, BKPyV, MCPyV, HPyV6, HPyV7 and HPyV9) loads were determined. Zero-inflated negative binomial (ZINB) regression was used to model the count data, as it contained excessive zeros. Covariates were chosen by stepwise selection. HPyVs DNA was detected in 54% (median:87.6*10 5 copies/ml) of the urine samples. JCPyV was the prevalent (48%, (median viral load:126*10 5 copies/ml). Considering the load of the most frequently measured HPyVs, JCPyV, in the count-part of the ZINB model, every unitary in PM measured 2 days before urine collection (PM Day -2) was associated with an increase in JCPyV load (PM 10 : +4.0%, p-value = 0.002; PM 2.5 : +3.6%, p-value = 0.005). In the zero-part, the significant predictor was the PM 10 measured 5 days before urine collection (+3%, p-value = 0.03). The environmental levels of PM 10 /PM 2.5 increase the JCPyV viruria. Our findings emphasize the need for studies assessing the influence of air pollution exposure on the risk of viral reactivation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Zero-truncated negative binomial - Erlang distribution

NASA Astrophysics Data System (ADS)

Bodhisuwan, Winai; Pudprommarat, Chookait; Bodhisuwan, Rujira; Saothayanun, Luckhana

2017-11-01

The zero-truncated negative binomial-Erlang distribution is introduced. It is developed from negative binomial-Erlang distribution. In this work, the probability mass function is derived and some properties are included. The parameters of the zero-truncated negative binomial-Erlang distribution are estimated by using the maximum likelihood estimation. Finally, the proposed distribution is applied to real data, the number of methamphetamine in the Bangkok, Thailand. Based on the results, it shows that the zero-truncated negative binomial-Erlang distribution provided a better fit than the zero-truncated Poisson, zero-truncated negative binomial, zero-truncated generalized negative-binomial and zero-truncated Poisson-Lindley distributions for this data.

Gender differences in use of hearing protection devices among farm operators.

PubMed

McCullagh, Marjorie C; Banerjee, Tanima; Yang, James J; Bernick, Janice; Duffy, Sonia; Redman, Richard

2016-01-01

Although farm operators have frequent exposure to hazardous noise and high rates of noise-induced hearing loss, they have low use of hearing protection devices (HPDs). Women represent about one-third of farm operators, and their numbers are climbing. However, among published studies examining use of HPDs in this worker group, none have examined gender-related differences. The purpose of this study was to examine gender-related differences in use of hearing protection and related predictors among farm operators. Data previously collected at farm shows and by telephone were analyzed using t-tests and generalized linear model with zero inflated negative binomial (ZINB) distribution. The difference in rate of hearing protector use between men and women farm operators was not significant. There was no difference between men and women in most hearing protector-related attitudes and beliefs. Although men and women farm operators had similar rates of use of hearing protectors when working in high-noise environments, attitudes about HPD use differed. Specifically, interpersonal role modeling was a predictor of HPD use among women, but not for men. This difference suggests that while farm operators of both genders may benefit from interventions designed to reduce barriers to HPD use (e.g., difficulty communicating with co-workers and hearing warning sounds), farm women have unique needs in relation to cognitive-perceptual factors that predict HPD use. Women farm operators may lack role models for use of HPDs (e.g., in peers and advertising), contributing to their less frequent use of protection.

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

PubMed

Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming

2014-01-01

The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.

Distinguishing between Binomial, Hypergeometric and Negative Binomial Distributions

ERIC Educational Resources Information Center

Wroughton, Jacqueline; Cole, Tarah

2013-01-01

Recognizing the differences between three discrete distributions (Binomial, Hypergeometric and Negative Binomial) can be challenging for students. We present an activity designed to help students differentiate among these distributions. In addition, we present assessment results in the form of pre- and post-tests that were designed to assess the…

Testing a Model of Self-Management of Fluid Intake in Community-Residing Long-Term Indwelling Urinary Catheter Users

PubMed Central

Wilde, Mary H.; Crean, Hugh F.; McMahon, James M.; McDonald, Margaret V.; Tang, Wan; Brasch, Judith; Fairbanks, Eileen; Shah, Shivani; Zhang, Feng

2015-01-01

Background Urinary tract infection and blockage are serious and recurrent challenges for people with long-term indwelling catheters, and these catheter problems cause worry and anxiety when they disrupt normal daily activities. Objectives The goal was to determine whether urinary catheter-related self-management behaviors focusing on fluid intake would mediate fluid intake related self-efficacy toward decreasing catheter-associated urinary tract infection (CAUTI) and/or catheter blockage. Method The sample involved data collected from 180 adult community-living, long-term indwelling urinary catheter users. The authors tested a model of fluid intake self-management (F-SMG) related to fluid intake self-efficacy (F-SE) for key outcomes of CAUTI and blockage. To account for the large number of zeros in both outcomes, a zero inflated negative binomial (ZINB) structural equation model was tested. Results Structurally, F-SE was positively associated with F-SMG, suggesting that higher F-SE predicts more (higher) F-SMG; however, F-SMG was not associated with either the frequency of CAUTI’s or the presence or absence of CAUTI. F-SE was positively related to F-SMG and F-SMG predicted less frequency of catheter blockage, but neither F-SE nor F-SMG predicted the presence or absence of blockage. Discussion Further research is needed to better understand determinants of CAUTI in long-term catheter users and factors which might influence or prevent its occurrence. Increased confidence (self-efficacy) and self-management behaviors to promote fluid intake could be of value in long-term urinary catheter users to decrease catheter blockage. PMID:26938358

Censored Hurdle Negative Binomial Regression (Case Study: Neonatorum Tetanus Case in Indonesia)

NASA Astrophysics Data System (ADS)

Yuli Rusdiana, Riza; Zain, Ismaini; Wulan Purnami, Santi

2017-06-01

Hurdle negative binomial model regression is a method that can be used for discreate dependent variable, excess zero and under- and overdispersion. It uses two parts approach. The first part estimates zero elements from dependent variable is zero hurdle model and the second part estimates not zero elements (non-negative integer) from dependent variable is called truncated negative binomial models. The discrete dependent variable in such cases is censored for some values. The type of censor that will be studied in this research is right censored. This study aims to obtain the parameter estimator hurdle negative binomial regression for right censored dependent variable. In the assessment of parameter estimation methods used Maximum Likelihood Estimator (MLE). Hurdle negative binomial model regression for right censored dependent variable is applied on the number of neonatorum tetanus cases in Indonesia. The type data is count data which contains zero values in some observations and other variety value. This study also aims to obtain the parameter estimator and test statistic censored hurdle negative binomial model. Based on the regression results, the factors that influence neonatorum tetanus case in Indonesia is the percentage of baby health care coverage and neonatal visits.

Choosing a Transformation in Analyses of Insect Counts from Contagious Distributions with Low Means

Treesearch

W.D. Pepper; S.J. Zarnoch; G.L. DeBarr; P. de Groot; C.D. Tangren

1997-01-01

Guidelines based on computer simulation are suggested for choosing a transformation of insect counts from negative binomial distributions with low mean counts and high levels of contagion. Typical values and ranges of negative binomial model parameters were determined by fitting the model to data from 19 entomological field studies. Random sampling of negative binomial...

Statistical inference involving binomial and negative binomial parameters.

PubMed

García-Pérez, Miguel A; Núñez-Antón, Vicente

2009-05-01

Statistical inference about two binomial parameters implies that they are both estimated by binomial sampling. There are occasions in which one aims at testing the equality of two binomial parameters before and after the occurrence of the first success along a sequence of Bernoulli trials. In these cases, the binomial parameter before the first success is estimated by negative binomial sampling whereas that after the first success is estimated by binomial sampling, and both estimates are related. This paper derives statistical tools to test two hypotheses, namely, that both binomial parameters equal some specified value and that both parameters are equal though unknown. Simulation studies are used to show that in small samples both tests are accurate in keeping the nominal Type-I error rates, and also to determine sample size requirements to detect large, medium, and small effects with adequate power. Additional simulations also show that the tests are sufficiently robust to certain violations of their assumptions.

Variability in results from negative binomial models for Lyme disease measured at different spatial scales.

PubMed

Tran, Phoebe; Waller, Lance

2015-01-01

Lyme disease has been the subject of many studies due to increasing incidence rates year after year and the severe complications that can arise in later stages of the disease. Negative binomial models have been used to model Lyme disease in the past with some success. However, there has been little focus on the reliability and consistency of these models when they are used to study Lyme disease at multiple spatial scales. This study seeks to explore how sensitive/consistent negative binomial models are when they are used to study Lyme disease at different spatial scales (at the regional and sub-regional levels). The study area includes the thirteen states in the Northeastern United States with the highest Lyme disease incidence during the 2002-2006 period. Lyme disease incidence at county level for the period of 2002-2006 was linked with several previously identified key landscape and climatic variables in a negative binomial regression model for the Northeastern region and two smaller sub-regions (the New England sub-region and the Mid-Atlantic sub-region). This study found that negative binomial models, indeed, were sensitive/inconsistent when used at different spatial scales. We discuss various plausible explanations for such behavior of negative binomial models. Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context. Copyright © 2014 Elsevier Inc. All rights reserved.

Predicting stem borer density in maize using RapidEye data and generalized linear models

NASA Astrophysics Data System (ADS)

Abdel-Rahman, Elfatih M.; Landmann, Tobias; Kyalo, Richard; Ong'amo, George; Mwalusepo, Sizah; Sulieman, Saad; Ru, Bruno Le

2017-05-01

Average maize yield in eastern Africa is 2.03 t ha-1 as compared to global average of 6.06 t ha-1 due to biotic and abiotic constraints. Amongst the biotic production constraints in Africa, stem borers are the most injurious. In eastern Africa, maize yield losses due to stem borers are currently estimated between 12% and 21% of the total production. The objective of the present study was to explore the possibility of RapidEye spectral data to assess stem borer larva densities in maize fields in two study sites in Kenya. RapidEye images were acquired for the Bomet (western Kenya) test site on the 9th of December 2014 and on 27th of January 2015, and for Machakos (eastern Kenya) a RapidEye image was acquired on the 3rd of January 2015. Five RapidEye spectral bands as well as 30 spectral vegetation indices (SVIs) were utilized to predict per field maize stem borer larva densities using generalized linear models (GLMs), assuming Poisson ('Po') and negative binomial ('NB') distributions. Root mean square error (RMSE) and ratio prediction to deviation (RPD) statistics were used to assess the models performance using a leave-one-out cross-validation approach. The Zero-inflated NB ('ZINB') models outperformed the 'NB' models and stem borer larva densities could only be predicted during the mid growing season in December and early January in both study sites, respectively (RMSE = 0.69-1.06 and RPD = 8.25-19.57). Overall, all models performed similar when all the 30 SVIs (non-nested) and only the significant (nested) SVIs were used. The models developed could improve decision making regarding controlling maize stem borers within integrated pest management (IPM) interventions.

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.

Analysis of generalized negative binomial distributions attached to hyperbolic Landau levels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chhaiba, Hassan, E-mail: chhaiba.hassan@gmail.com; Demni, Nizar, E-mail: nizar.demni@univ-rennes1.fr; Mouayn, Zouhair, E-mail: mouayn@fstbm.ac.ma

2016-07-15

To each hyperbolic Landau level of the Poincaré disc is attached a generalized negative binomial distribution. In this paper, we compute the moment generating function of this distribution and supply its atomic decomposition as a perturbation of the negative binomial distribution by a finitely supported measure. Using the Mandel parameter, we also discuss the nonclassical nature of the associated coherent states. Next, we derive a Lévy-Khintchine-type representation of its characteristic function when the latter does not vanish and deduce that it is quasi-infinitely divisible except for the lowest hyperbolic Landau level corresponding to the negative binomial distribution. By considering themore » total variation of the obtained quasi-Lévy measure, we introduce a new infinitely divisible distribution for which we derive the characteristic function.« less

Library Book Circulation and the Beta-Binomial Distribution.

ERIC Educational Resources Information Center

Gelman, E.; Sichel, H. S.

1987-01-01

Argues that library book circulation is a binomial rather than a Poisson process, and that individual book popularities are continuous beta distributions. Three examples demonstrate the superiority of beta over negative binomial distribution, and it is suggested that a bivariate-binomial process would be helpful in predicting future book…

Comparison of multiplicity distributions to the negative binomial distribution in muon-proton scattering

NASA Astrophysics Data System (ADS)

Arneodo, M.; Arvidson, A.; Aubert, J. J.; Badełek, B.; Beaufays, J.; Bee, C. P.; Benchouk, C.; Berghoff, G.; Bird, I.; Blum, D.; Böhm, E.; de Bouard, X.; Brasse, F. W.; Braun, H.; Broll, C.; Brown, S.; Brück, H.; Calen, H.; Chima, J. S.; Ciborowski, J.; Clifft, R.; Coignet, G.; Combley, F.; Coughlan, J.; D'Agostini, G.; Dahlgren, S.; Dengler, F.; Derado, I.; Dreyer, T.; Drees, J.; Düren, M.; Eckardt, V.; Edwards, A.; Edwards, M.; Ernst, T.; Eszes, G.; Favier, J.; Ferrero, M. I.; Figiel, J.; Flauger, W.; Foster, J.; Ftáčnik, J.; Gabathuler, E.; Gajewski, J.; Gamet, R.; Gayler, J.; Geddes, N.; Grafström, P.; Grard, F.; Haas, J.; Hagberg, E.; Hasert, F. J.; Hayman, P.; Heusse, P.; Jaffré, M.; Jachołkowska, A.; Janata, F.; Jancsó, G.; Johnson, A. S.; Kabuss, E. M.; Kellner, G.; Korbel, V.; Krüger, J.; Kullander, S.; Landgraf, U.; Lanske, D.; Loken, J.; Long, K.; Maire, M.; Malecki, P.; Manz, A.; Maselli, S.; Mohr, W.; Montanet, F.; Montgomery, H. E.; Nagy, E.; Nassalski, J.; Norton, P. R.; Oakham, F. G.; Osborne, A. M.; Pascaud, C.; Pawlik, B.; Payre, P.; Peroni, C.; Peschel, H.; Pessard, H.; Pettinghale, J.; Pietrzyk, B.; Pietrzyk, U.; Pönsgen, B.; Pötsch, M.; Renton, P.; Ribarics, P.; Rith, K.; Rondio, E.; Sandacz, A.; Scheer, M.; Schlagböhmer, A.; Schiemann, H.; Schmitz, N.; Schneegans, M.; Schneider, A.; Scholz, M.; Schröder, T.; Schultze, K.; Sloan, T.; Stier, H. E.; Studt, M.; Taylor, G. N.; Thénard, J. M.; Thompson, J. C.; de La Torre, A.; Toth, J.; Urban, L.; Urban, L.; Wallucks, W.; Whalley, M.; Wheeler, S.; Williams, W. S. C.; Wimpenny, S. J.; Windmolders, R.; Wolf, G.

1987-09-01

The multiplicity distributions of charged hadrons produced in the deep inelastic muon-proton scattering at 280 GeV are analysed in various rapidity intervals, as a function of the total hadronic centre of mass energy W ranging from 4 20 GeV. Multiplicity distributions for the backward and forward hemispheres are also analysed separately. The data can be well parameterized by binomial distributions, extending their range of applicability to the case of lepton-proton scattering. The energy and the rapidity dependence of the parameters is presented and a smooth transition from the negative binomial distribution via Poissonian to the ordinary binomial is observed.

The Difference Calculus and The NEgative Binomial Distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, Kimiko o; Shenton, LR

2007-01-01

In a previous paper we state the dominant term in the third central moment of the maximum likelihood estimator k of the parameter k in the negative binomial probability function where the probability generating function is (p + 1 - pt){sup -k}. A partial sum of the series {Sigma}1/(k + x){sup 3} is involved, where x is a negative binomial random variate. In expectation this sum can only be found numerically using the computer. Here we give a simple definite integral in (0,1) for the generalized case. This means that now we do have a valid expression for {radical}{beta}{sub 11}(k)more » and {radical}{beta}{sub 11}(p). In addition we use the finite difference operator {Delta}, and E = 1 + {Delta} to set up formulas for low order moments. Other examples of the operators are quoted relating to the orthogonal set of polynomials associated with the negative binomial probability function used as a weight function.« less

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

PubMed

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.

Macro-level pedestrian and bicycle crash analysis: Incorporating spatial spillover effects in dual state count models.

PubMed

Cai, Qing; Lee, Jaeyoung; Eluru, Naveen; Abdel-Aty, Mohamed

2016-08-01

This study attempts to explore the viability of dual-state models (i.e., zero-inflated and hurdle models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency analysis. Additionally, spatial spillover effects are explored in the models by employing exogenous variables from neighboring zones. The dual-state models such as zero-inflated negative binomial and hurdle negative binomial models (with and without spatial effects) are compared with the conventional single-state model (i.e., negative binomial). The model comparison for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency. Copyright © 2016 Elsevier Ltd. All rights reserved.

Health care utilization among Medicare-Medicaid dual eligibles: a count data analysis.

PubMed

Moon, Sangho; Shin, Jaeun

2006-04-05

Medicare-Medicaid dual eligibles are the beneficiaries of both Medicare and Medicaid. Dual eligibles satisfy the eligibility conditions for Medicare benefit. Dual eligibles also qualify for Medicaid because they are aged, blind, or disabled and meet the income and asset requirements for receiving Supplement Security Income (SSI) assistance. The objective of this study is to explore the relationship between dual eligibility and health care utilization among Medicare beneficiaries. The household component of the nationally representative Medical Expenditure Panel Survey (MEPS) 1996-2000 is used for the analysis. Total 8,262 Medicare beneficiaries are selected from the MEPS data. The Medicare beneficiary sample includes individuals who are covered by Medicare and do not have private health insurance during a given year. Zero-inflated negative binomial (ZINB) regression model is used to analyse the count data regarding health care utilization: office-based physician visits, hospital inpatient nights, agency-sponsored home health provider days, and total dental visits. Dual eligibility is positively correlated with the likelihood of using hospital inpatient care and agency-sponsored home health services and the frequency of agency-sponsored home health days. Frequency of dental visits is inversely associated with dual eligibility. With respect to racial differences, dually eligible Afro-Americans use more office-based physician and dental services than white duals. Asian duals use more home health services than white duals at the 5% statistical significance level. The dual eligibility programs seem particularly beneficial to Afro-American duals. Dual eligibility has varied impact on health care utilization across service types. More utilization of home healthcare among dual eligibles appears to be the result of delayed realization of their unmet healthcare needs under the traditional Medicare-only program rather than the result of overutilization in response to the expanded benefits of the dual eligibility program. The dual eligibility program is particularly beneficial to Asian and Afro-American duals in association with the provision of home healthcare and dental benefits.

A Mixed-Effects Heterogeneous Negative Binomial Model for Postfire Conifer Regeneration in Northeastern California, USA

Treesearch

Justin S. Crotteau; Martin W. Ritchie; J. Morgan Varner

2014-01-01

Many western USA fire regimes are typified by mixed-severity fire, which compounds the variability inherent to natural regeneration densities in associated forests. Tree regeneration data are often discrete and nonnegative; accordingly, we fit a series of Poisson and negative binomial variation models to conifer seedling counts across four distinct burn severities and...

Prevalence and determinants of childhood mortality in Nigeria.

PubMed

Yaya, Sanni; Ekholuenetale, Michael; Tudeme, Godson; Vaibhav, Shah; Bishwajit, Ghose; Kadio, Bernard

2017-05-22

Childhood mortality has remained a major challenge to public health amongst families in Nigeria and other developing countries. The menace of incessant childhood mortality has been a major concern and this calls for studies to generate new scientific evidence to determine its prevalence and explore predisposing factors associated with it in Nigeria. Data was obtained from Nigeria DHS, 2013. The study outcome variable was the total number of children lost by male partners and female partners respectively who were married. The difference between the numbers of child births and the number of living children was used to determine the number of children lost. Study variables were obtained for 8658 couples captured in the data set. Descriptive statistics were computed to examine the presence of over-dispersion and zero occurrences. Data were analysed using STATA Software version 12.0. Zero-inflated negative binomial (ZINB) regression analysis was carried out to determine the factors associated with childhood mortality. Results of ZINB were reported in terms of IRR and 95% confidence interval (CI). The age (mean ± std.) of male and female participants were 36.88 ± 7.37 and 28.59 ± 7.30 respectively. The data showed that 30.8% women reported loss of children and 37.3% men reported the same problem. The study revealed age (years), region, residence, education, wealth index, age at first birth and religion of father and mother as factors associated with childhood mortality. In terms of education, secondary and tertiary educated fathers exhibited 3.8% and 12.1% lower risk of childhood mortality respectively than non-educated fathers. The results showed that the risk of childhood mortality are 26.7%, 39.7 and 45.9% lower among the mothers having primary, secondary and tertiary education respectively than those with no formal education. The mothers living in rural areas experienced 28.3% increase in childhood mortality than those in urban areas, while the fathers in rural areas experienced 33.5% increase in childhood mortality than the urban areas. The risk of childhood mortality was significantly lower in middle, richer and richest (11.1%, 37.5 and 49%) economic quintiles respectively when compared to the risk of childhood mortality with female spouse who are poorest. Similar results were obtained for the fathers, with reduction in the incidence-rate ratio of 3.3%, 20.2 and 28.7% for middle, richer and richest economic quintiles respectively, compared to the poorest status. Furthermore, region and religion were found to be significant factors associated with childhood mortality in Nigeria. The findings suggested that age, region, residence, education, wealth index, age at first birth and religion of fathers and mothers are key determinants associated with childhood mortality. The correlation between childhood mortality and fathers' and mothers' ages were found to increase the incidence of the outcome for every unit increase in age. The converse was however, true for age at first birth which was also statistically significant. The implication of this study is that policy makers and stakeholders in health care should provide for improved living standards to achieve good life expectancy meeting SDG3.

Use of the negative binomial-truncated Poisson distribution in thunderstorm prediction

NASA Technical Reports Server (NTRS)

Cohen, A. C.

1971-01-01

A probability model is presented for the distribution of thunderstorms over a small area given that thunderstorm events (1 or more thunderstorms) are occurring over a larger area. The model incorporates the negative binomial and truncated Poisson distributions. Probability tables for Cape Kennedy for spring, summer, and fall months and seasons are presented. The computer program used to compute these probabilities is appended.

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Treesearch

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

Poisson and negative binomial item count techniques for surveys with sensitive question.

PubMed

Tian, Guo-Liang; Tang, Man-Lai; Wu, Qin; Liu, Yin

2017-04-01

Although the item count technique is useful in surveys with sensitive questions, privacy of those respondents who possess the sensitive characteristic of interest may not be well protected due to a defect in its original design. In this article, we propose two new survey designs (namely the Poisson item count technique and negative binomial item count technique) which replace several independent Bernoulli random variables required by the original item count technique with a single Poisson or negative binomial random variable, respectively. The proposed models not only provide closed form variance estimate and confidence interval within [0, 1] for the sensitive proportion, but also simplify the survey design of the original item count technique. Most importantly, the new designs do not leak respondents' privacy. Empirical results show that the proposed techniques perform satisfactorily in the sense that it yields accurate parameter estimate and confidence interval.

Data mining of tree-based models to analyze freeway accident frequency.

PubMed

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.

Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: case studies from Malaysian federal roads.

PubMed

Hosseinpour, Mehdi; Yahaya, Ahmad Shukri; Sadullah, Ahmad Farhan

2014-01-01

Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Injuries in children with extra physical education in primary schools.

PubMed

Rexen, Christina Trifonov; Andersen, Lars Bo; Ersbøll, Annette Kjær; Jespersen, Eva; Franz, Claudia; Wedderkopp, Niels

2014-04-01

(1) Examine the influence of extra physical education (EPE) on the number of musculoskeletal injuries in public schools accounting for organized sports participation (OSP) outside school. (2) Examine the major injury subgroup: growth-related overuse (GRO) through the overuse-related injury group. A longitudinal controlled school-based study among Danish public schools. At baseline, 1216 children participated age 6.2-12.4 yr. Six schools (701 children) with EPE and four control schools (515 children) were followed up with weekly automated mobile phone text messages for information on musculoskeletal problems and OSP. Health care personnel diagnosed the children according to the World Health Organization's International Classification of Diseases, Tenth Revision. Data were analyzed using a two-part zero-inflated negative binomial (ZINB) regression model. School type had no influence on the odds of sustaining an injury but increased the probability of sustaining a higher injury count for children with injuries, with total injuries by a factor of 1.29 (95% confidence interval [CI] = 1.07-1.56), overuse by a factor of 1.29 (95% CI = 1.06-1.55), and GRO by a factor of 1.38 (95% CI = 1.02-1.80). Weekly mean OSP decreased the odds of belonging to the group of children with no injuries, by a factor of 0.29 (95% CI = 0.14-0.58), 0.26 (95% CI = 0.14-0.48), and 0.17 (95% CI = 0.06-0.52) for total, overuse, and GRO, respectively. OSP also increased the probability of sustaining a higher injury count for children with injuries by a factor of 1.11 (95% CI = 1.02-1.22), 1.10 (95% CI = 1.00-1.22), and 1.14 (95% CI = 1.00-1.30), respectively. Children enrolled in EPE schools with high OSP have the highest odds of injury and a high probability of sustaining a higher injury count compared to their peers at schools with normal PE. Special attention should be assigned to these children during compulsory PE.

Dispersion and sampling of adult Dermacentor andersoni in rangeland in Western North America.

PubMed

Rochon, K; Scoles, G A; Lysyk, T J

2012-03-01

A fixed precision sampling plan was developed for off-host populations of adult Rocky Mountain wood tick, Dermacentor andersoni (Stiles) based on data collected by dragging at 13 locations in Alberta, Canada; Washington; and Oregon. In total, 222 site-date combinations were sampled. Each site-date combination was considered a sample, and each sample ranged in size from 86 to 250 10 m2 quadrats. Analysis of simulated quadrats ranging in size from 10 to 50 m2 indicated that the most precise sample unit was the 10 m2 quadrat. Samples taken when abundance < 0.04 ticks per 10 m2 were more likely to not depart significantly from statistical randomness than samples taken when abundance was greater. Data were grouped into ten abundance classes and assessed for fit to the Poisson and negative binomial distributions. The Poisson distribution fit only data in abundance classes < 0.02 ticks per 10 m2, while the negative binomial distribution fit data from all abundance classes. A negative binomial distribution with common k = 0.3742 fit data in eight of the 10 abundance classes. Both the Taylor and Iwao mean-variance relationships were fit and used to predict sample sizes for a fixed level of precision. Sample sizes predicted using the Taylor model tended to underestimate actual sample sizes, while sample sizes estimated using the Iwao model tended to overestimate actual sample sizes. Using a negative binomial with common k provided estimates of required sample sizes closest to empirically calculated sample sizes.

An examination of sources of sensitivity of consumer surplus estimates in travel cost models.

PubMed

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.

Solving the problem of negative populations in approximate accelerated stochastic simulations using the representative reaction approach.

PubMed

Kadam, Shantanu; Vanka, Kumar

2013-02-15

Methods based on the stochastic formulation of chemical kinetics have the potential to accurately reproduce the dynamical behavior of various biochemical systems of interest. However, the computational expense makes them impractical for the study of real systems. Attempts to render these methods practical have led to the development of accelerated methods, where the reaction numbers are modeled by Poisson random numbers. However, for certain systems, such methods give rise to physically unrealistic negative numbers for species populations. The methods which make use of binomial variables, in place of Poisson random numbers, have since become popular, and have been partially successful in addressing this problem. In this manuscript, the development of two new computational methods, based on the representative reaction approach (RRA), has been discussed. The new methods endeavor to solve the problem of negative numbers, by making use of tools like the stochastic simulation algorithm and the binomial method, in conjunction with the RRA. It is found that these newly developed methods perform better than other binomial methods used for stochastic simulations, in resolving the problem of negative populations. Copyright © 2012 Wiley Periodicals, Inc.

Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation

USGS Publications Warehouse

Zipkin, Elise F.; Leirness, Jeffery B.; Kinlan, Brian P.; O'Connell, Allan F.; Silverman, Emily D.

2014-01-01

Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are becoming increasingly popular for group size modeling. Choosing appropriate statistical distributions for modeling flock size data is fundamental to accurately estimating population summaries, determining required survey effort, and assessing and propagating uncertainty through decision-making processes.

Selecting the right statistical model for analysis of insect count data by using information theoretic measures.

PubMed

Sileshi, G

2006-10-01

Researchers and regulatory agencies often make statistical inferences from insect count data using modelling approaches that assume homogeneous variance. Such models do not allow for formal appraisal of variability which in its different forms is the subject of interest in ecology. Therefore, the objectives of this paper were to (i) compare models suitable for handling variance heterogeneity and (ii) select optimal models to ensure valid statistical inferences from insect count data. The log-normal, standard Poisson, Poisson corrected for overdispersion, zero-inflated Poisson, the negative binomial distribution and zero-inflated negative binomial models were compared using six count datasets on foliage-dwelling insects and five families of soil-dwelling insects. Akaike's and Schwarz Bayesian information criteria were used for comparing the various models. Over 50% of the counts were zeros even in locally abundant species such as Ootheca bennigseni Weise, Mesoplatys ochroptera Stål and Diaecoderus spp. The Poisson model after correction for overdispersion and the standard negative binomial distribution model provided better description of the probability distribution of seven out of the 11 insects than the log-normal, standard Poisson, zero-inflated Poisson or zero-inflated negative binomial models. It is concluded that excess zeros and variance heterogeneity are common data phenomena in insect counts. If not properly modelled, these properties can invalidate the normal distribution assumptions resulting in biased estimation of ecological effects and jeopardizing the integrity of the scientific inferences. Therefore, it is recommended that statistical models appropriate for handling these data properties be selected using objective criteria to ensure efficient statistical inference.

Distribution pattern of public transport passenger in Yogyakarta, Indonesia

NASA Astrophysics Data System (ADS)

Narendra, Alfa; Malkhamah, Siti; Sopha, Bertha Maya

2018-03-01

The arrival and departure distribution pattern of Trans Jogja bus passenger is one of the fundamental model for simulation. The purpose of this paper is to build models of passengers flows. This research used passengers data from January to May 2014. There is no policy that change the operation system affecting the nature of this pattern nowadays. The roads, buses, land uses, schedule, and people are relatively still the same. The data then categorized based on the direction, days, and location. Moreover, each category was fitted into some well-known discrete distributions. Those distributions are compared based on its AIC value and BIC. The chosen distribution model has the smallest AIC and BIC value and the negative binomial distribution found has the smallest AIC and BIC value. Probability mass function (PMF) plots of those models were compared to draw generic model from each categorical negative binomial distribution models. The value of accepted generic negative binomial distribution is 0.7064 and 1.4504 of mu. The minimum and maximum passenger vector value of distribution are is 0 and 41.

Modeling number of claims and prediction of total claim amount

NASA Astrophysics Data System (ADS)

Acar, Aslıhan Şentürk; Karabey, Uǧur

2017-07-01

In this study we focus on annual number of claims of a private health insurance data set which belongs to a local insurance company in Turkey. In addition to Poisson model and negative binomial model, zero-inflated Poisson model and zero-inflated negative binomial model are used to model the number of claims in order to take into account excess zeros. To investigate the impact of different distributional assumptions for the number of claims on the prediction of total claim amount, predictive performances of candidate models are compared by using root mean square error (RMSE) and mean absolute error (MAE) criteria.

Modelling parasite aggregation: disentangling statistical and ecological approaches.

PubMed

Yakob, Laith; Soares Magalhães, Ricardo J; Gray, Darren J; Milinovich, Gabriel; Wardrop, Nicola; Dunning, Rebecca; Barendregt, Jan; Bieri, Franziska; Williams, Gail M; Clements, Archie C A

2014-05-01

The overdispersion in macroparasite infection intensity among host populations is commonly simulated using a constant negative binomial aggregation parameter. We describe an alternative to utilising the negative binomial approach and demonstrate important disparities in intervention efficacy projections that can come about from opting for pattern-fitting models that are not process-explicit. We present model output in the context of the epidemiology and control of soil-transmitted helminths due to the significant public health burden imposed by these parasites, but our methods are applicable to other infections with demonstrable aggregation in parasite numbers among hosts. Copyright © 2014. Published by Elsevier Ltd.

FluBreaks: early epidemic detection from Google flu trends.

PubMed

Pervaiz, Fahad; Pervaiz, Mansoor; Abdur Rehman, Nabeel; Saif, Umar

2012-10-04

The Google Flu Trends service was launched in 2008 to track changes in the volume of online search queries related to flu-like symptoms. Over the last few years, the trend data produced by this service has shown a consistent relationship with the actual number of flu reports collected by the US Centers for Disease Control and Prevention (CDC), often identifying increases in flu cases weeks in advance of CDC records. However, contrary to popular belief, Google Flu Trends is not an early epidemic detection system. Instead, it is designed as a baseline indicator of the trend, or changes, in the number of disease cases. To evaluate whether these trends can be used as a basis for an early warning system for epidemics. We present the first detailed algorithmic analysis of how Google Flu Trends can be used as a basis for building a fully automated system for early warning of epidemics in advance of methods used by the CDC. Based on our work, we present a novel early epidemic detection system, called FluBreaks (dritte.org/flubreaks), based on Google Flu Trends data. We compared the accuracy and practicality of three types of algorithms: normal distribution algorithms, Poisson distribution algorithms, and negative binomial distribution algorithms. We explored the relative merits of these methods, and related our findings to changes in Internet penetration and population size for the regions in Google Flu Trends providing data. Across our performance metrics of percentage true-positives (RTP), percentage false-positives (RFP), percentage overlap (OT), and percentage early alarms (EA), Poisson- and negative binomial-based algorithms performed better in all except RFP. Poisson-based algorithms had average values of 99%, 28%, 71%, and 76% for RTP, RFP, OT, and EA, respectively, whereas negative binomial-based algorithms had average values of 97.8%, 17.8%, 60%, and 55% for RTP, RFP, OT, and EA, respectively. Moreover, the EA was also affected by the region's population size. Regions with larger populations (regions 4 and 6) had higher values of EA than region 10 (which had the smallest population) for negative binomial- and Poisson-based algorithms. The difference was 12.5% and 13.5% on average in negative binomial- and Poisson-based algorithms, respectively. We present the first detailed comparative analysis of popular early epidemic detection algorithms on Google Flu Trends data. We note that realizing this opportunity requires moving beyond the cumulative sum and historical limits method-based normal distribution approaches, traditionally employed by the CDC, to negative binomial- and Poisson-based algorithms to deal with potentially noisy search query data from regions with varying population and Internet penetrations. Based on our work, we have developed FluBreaks, an early warning system for flu epidemics using Google Flu Trends.

A big data approach to the development of mixed-effects models for seizure count data.

PubMed

Tharayil, Joseph J; Chiang, Sharon; Moss, Robert; Stern, John M; Theodore, William H; Goldenholz, Daniel M

2017-05-01

Our objective was to develop a generalized linear mixed model for predicting seizure count that is useful in the design and analysis of clinical trials. This model also may benefit the design and interpretation of seizure-recording paradigms. Most existing seizure count models do not include children, and there is currently no consensus regarding the most suitable model that can be applied to children and adults. Therefore, an additional objective was to develop a model that accounts for both adult and pediatric epilepsy. Using data from SeizureTracker.com, a patient-reported seizure diary tool with >1.2 million recorded seizures across 8 years, we evaluated the appropriateness of Poisson, negative binomial, zero-inflated negative binomial, and modified negative binomial models for seizure count data based on minimization of the Bayesian information criterion. Generalized linear mixed-effects models were used to account for demographic and etiologic covariates and for autocorrelation structure. Holdout cross-validation was used to evaluate predictive accuracy in simulating seizure frequencies. For both adults and children, we found that a negative binomial model with autocorrelation over 1 day was optimal. Using holdout cross-validation, the proposed model was found to provide accurate simulation of seizure counts for patients with up to four seizures per day. The optimal model can be used to generate more realistic simulated patient data with very few input parameters. The availability of a parsimonious, realistic virtual patient model can be of great utility in simulations of phase II/III clinical trials, epilepsy monitoring units, outpatient biosensors, and mobile Health (mHealth) applications. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Bayesian inference for disease prevalence using negative binomial group testing

PubMed Central

Pritchard, Nicholas A.; Tebbs, Joshua M.

2011-01-01

Group testing, also known as pooled testing, and inverse sampling are both widely used methods of data collection when the goal is to estimate a small proportion. Taking a Bayesian approach, we consider the new problem of estimating disease prevalence from group testing when inverse (negative binomial) sampling is used. Using different distributions to incorporate prior knowledge of disease incidence and different loss functions, we derive closed form expressions for posterior distributions and resulting point and credible interval estimators. We then evaluate our new estimators, on Bayesian and classical grounds, and apply our methods to a West Nile Virus data set. PMID:21259308

Use of negative binomial distribution to describe the presence of Anisakis in Thyrsites atun.

PubMed

Peña-Rehbein, Patricio; De los Ríos-Escalante, Patricio

2012-01-01

Nematodes of the genus Anisakis have marine fishes as intermediate hosts. One of these hosts is Thyrsites atun, an important fishery resource in Chile between 38 and 41° S. This paper describes the frequency and number of Anisakis nematodes in the internal organs of Thyrsites atun. An analysis based on spatial distribution models showed that the parasites tend to be clustered. The variation in the number of parasites per host could be described by the negative binomial distribution. The maximum observed number of parasites was nine parasites per host. The environmental and zoonotic aspects of the study are also discussed.

Selecting a distributional assumption for modelling relative densities of benthic macroinvertebrates

USGS Publications Warehouse

Gray, B.R.

2005-01-01

The selection of a distributional assumption suitable for modelling macroinvertebrate density data is typically challenging. Macroinvertebrate data often exhibit substantially larger variances than expected under a standard count assumption, that of the Poisson distribution. Such overdispersion may derive from multiple sources, including heterogeneity of habitat (historically and spatially), differing life histories for organisms collected within a single collection in space and time, and autocorrelation. Taken to extreme, heterogeneity of habitat may be argued to explain the frequent large proportions of zero observations in macroinvertebrate data. Sampling locations may consist of habitats defined qualitatively as either suitable or unsuitable. The former category may yield random or stochastic zeroes and the latter structural zeroes. Heterogeneity among counts may be accommodated by treating the count mean itself as a random variable, while extra zeroes may be accommodated using zero-modified count assumptions, including zero-inflated and two-stage (or hurdle) approaches. These and linear assumptions (following log- and square root-transformations) were evaluated using 9 years of mayfly density data from a 52 km, ninth-order reach of the Upper Mississippi River (n = 959). The data exhibited substantial overdispersion relative to that expected under a Poisson assumption (i.e. variance:mean ratio = 23 ??? 1), and 43% of the sampling locations yielded zero mayflies. Based on the Akaike Information Criterion (AIC), count models were improved most by treating the count mean as a random variable (via a Poisson-gamma distributional assumption) and secondarily by zero modification (i.e. improvements in AIC values = 9184 units and 47-48 units, respectively). Zeroes were underestimated by the Poisson, log-transform and square root-transform models, slightly by the standard negative binomial model but not by the zero-modified models (61%, 24%, 32%, 7%, and 0%, respectively). However, the zero-modified Poisson models underestimated small counts (1 ??? y ??? 4) and overestimated intermediate counts (7 ??? y ??? 23). Counts greater than zero were estimated well by zero-modified negative binomial models, while counts greater than one were also estimated well by the standard negative binomial model. Based on AIC and percent zero estimation criteria, the two-stage and zero-inflated models performed similarly. The above inferences were largely confirmed when the models were used to predict values from a separate, evaluation data set (n = 110). An exception was that, using the evaluation data set, the standard negative binomial model appeared superior to its zero-modified counterparts using the AIC (but not percent zero criteria). This and other evidence suggest that a negative binomial distributional assumption should be routinely considered when modelling benthic macroinvertebrate data from low flow environments. Whether negative binomial models should themselves be routinely examined for extra zeroes requires, from a statistical perspective, more investigation. However, this question may best be answered by ecological arguments that may be specific to the sampled species and locations. ?? 2004 Elsevier B.V. All rights reserved.

Identifiability in N-mixture models: a large-scale screening test with bird data.

PubMed

Kéry, Marc

2018-02-01

Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

Distribution pattern of phthirapterans infesting certain common Indian birds.

PubMed

Saxena, A K; Kumar, Sandeep; Gupta, Nidhi; Mitra, J D; Ali, S A; Srivastava, Roshni

2007-08-01

The prevalence and frequency distribution patterns of 10 phthirapteran species infesting house sparrows, Indian parakeets, common mynas, and white breasted kingfishers were recorded in the district of Rampur, India, during 2004-05. The sample mean abundances, mean intensities, range of infestations, variance to mean ratios, values of the exponent of the negative binomial distribution, and the indices of discrepancy were also computed. Frequency distribution patterns of all phthirapteran species were skewed, but the observed frequencies did not correspond to the negative binomial distribution. Thus, adult-nymph ratios varied in different species from 1:0.53 to 1:1.25. Sex ratios of different phthirapteran species ranged from 1:1.10 to 1:1.65 and were female biased.

Sample size determination for a three-arm equivalence trial of Poisson and negative binomial responses.

PubMed

Chang, Yu-Wei; Tsong, Yi; Zhao, Zhigen

2017-01-01

Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression.

PubMed

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.

A methodology to design heuristics for model selection based on the characteristics of data: Application to investigate when the Negative Binomial Lindley (NB-L) is preferred over the Negative Binomial (NB).

PubMed

Shirazi, Mohammadali; Dhavala, Soma Sekhar; Lord, Dominique; Geedipally, Srinivas Reddy

2017-10-01

Safety analysts usually use post-modeling methods, such as the Goodness-of-Fit statistics or the Likelihood Ratio Test, to decide between two or more competitive distributions or models. Such metrics require all competitive distributions to be fitted to the data before any comparisons can be accomplished. Given the continuous growth in introducing new statistical distributions, choosing the best one using such post-modeling methods is not a trivial task, in addition to all theoretical or numerical issues the analyst may face during the analysis. Furthermore, and most importantly, these measures or tests do not provide any intuitions into why a specific distribution (or model) is preferred over another (Goodness-of-Logic). This paper ponders into these issues by proposing a methodology to design heuristics for Model Selection based on the characteristics of data, in terms of descriptive summary statistics, before fitting the models. The proposed methodology employs two analytic tools: (1) Monte-Carlo Simulations and (2) Machine Learning Classifiers, to design easy heuristics to predict the label of the 'most-likely-true' distribution for analyzing data. The proposed methodology was applied to investigate when the recently introduced Negative Binomial Lindley (NB-L) distribution is preferred over the Negative Binomial (NB) distribution. Heuristics were designed to select the 'most-likely-true' distribution between these two distributions, given a set of prescribed summary statistics of data. The proposed heuristics were successfully compared against classical tests for several real or observed datasets. Not only they are easy to use and do not need any post-modeling inputs, but also, using these heuristics, the analyst can attain useful information about why the NB-L is preferred over the NB - or vice versa- when modeling data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Binomial test statistics using Psi functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, Kimiko o

2007-01-01

For the negative binomial model (probability generating function (p + 1 - pt){sup -k}) a logarithmic derivative is the Psi function difference {psi}(k + x) - {psi}(k); this and its derivatives lead to a test statistic to decide on the validity of a specified model. The test statistic uses a data base so there exists a comparison available between theory and application. Note that the test function is not dominated by outliers. Applications to (i) Fisher's tick data, (ii) accidents data, (iii) Weldon's dice data are included.

Spatiotemporal and random parameter panel data models of traffic crash fatalities in Vietnam.

PubMed

Truong, Long T; Kieu, Le-Minh; Vu, Tuan A

2016-09-01

This paper investigates factors associated with traffic crash fatalities in 63 provinces of Vietnam during the period from 2012 to 2014. Random effect negative binomial (RENB) and random parameter negative binomial (RPNB) panel data models are adopted to consider spatial heterogeneity across provinces. In addition, a spatiotemporal model with conditional autoregressive priors (ST-CAR) is utilised to account for spatiotemporal autocorrelation in the data. The statistical comparison indicates the ST-CAR model outperforms the RENB and RPNB models. Estimation results provide several significant findings. For example, traffic crash fatalities tend to be higher in provinces with greater numbers of level crossings. Passenger distance travelled and road lengths are also positively associated with fatalities. However, hospital densities are negatively associated with fatalities. The safety impact of the national highway 1A, the main transport corridor of the country, is also highlighted. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comparison of different ways of including baseline counts in negative binomial models for data from falls prevention trials.

PubMed

Zheng, Han; Kimber, Alan; Goodwin, Victoria A; Pickering, Ruth M

2018-01-01

A common design for a falls prevention trial is to assess falling at baseline, randomize participants into an intervention or control group, and ask them to record the number of falls they experience during a follow-up period of time. This paper addresses how best to include the baseline count in the analysis of the follow-up count of falls in negative binomial (NB) regression. We examine the performance of various approaches in simulated datasets where both counts are generated from a mixed Poisson distribution with shared random subject effect. Including the baseline count after log-transformation as a regressor in NB regression (NB-logged) or as an offset (NB-offset) resulted in greater power than including the untransformed baseline count (NB-unlogged). Cook and Wei's conditional negative binomial (CNB) model replicates the underlying process generating the data. In our motivating dataset, a statistically significant intervention effect resulted from the NB-logged, NB-offset, and CNB models, but not from NB-unlogged, and large, outlying baseline counts were overly influential in NB-unlogged but not in NB-logged. We conclude that there is little to lose by including the log-transformed baseline count in standard NB regression compared to CNB for moderate to larger sized datasets. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Binomial leap methods for simulating stochastic chemical kinetics.

PubMed

Tian, Tianhai; Burrage, Kevin

2004-12-01

This paper discusses efficient simulation methods for stochastic chemical kinetics. Based on the tau-leap and midpoint tau-leap methods of Gillespie [D. T. Gillespie, J. Chem. Phys. 115, 1716 (2001)], binomial random variables are used in these leap methods rather than Poisson random variables. The motivation for this approach is to improve the efficiency of the Poisson leap methods by using larger stepsizes. Unlike Poisson random variables whose range of sample values is from zero to infinity, binomial random variables have a finite range of sample values. This probabilistic property has been used to restrict possible reaction numbers and to avoid negative molecular numbers in stochastic simulations when larger stepsize is used. In this approach a binomial random variable is defined for a single reaction channel in order to keep the reaction number of this channel below the numbers of molecules that undergo this reaction channel. A sampling technique is also designed for the total reaction number of a reactant species that undergoes two or more reaction channels. Samples for the total reaction number are not greater than the molecular number of this species. In addition, probability properties of the binomial random variables provide stepsize conditions for restricting reaction numbers in a chosen time interval. These stepsize conditions are important properties of robust leap control strategies. Numerical results indicate that the proposed binomial leap methods can be applied to a wide range of chemical reaction systems with very good accuracy and significant improvement on efficiency over existing approaches. (c) 2004 American Institute of Physics.

Football goal distributions and extremal statistics

NASA Astrophysics Data System (ADS)

Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.

2002-12-01

We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.

Pricing American Asian options with higher moments in the underlying distribution

NASA Astrophysics Data System (ADS)

Lo, Keng-Hsin; Wang, Kehluh; Hsu, Ming-Feng

2009-01-01

We develop a modified Edgeworth binomial model with higher moment consideration for pricing American Asian options. With lognormal underlying distribution for benchmark comparison, our algorithm is as precise as that of Chalasani et al. [P. Chalasani, S. Jha, F. Egriboyun, A. Varikooty, A refined binomial lattice for pricing American Asian options, Rev. Derivatives Res. 3 (1) (1999) 85-105] if the number of the time steps increases. If the underlying distribution displays negative skewness and leptokurtosis as often observed for stock index returns, our estimates can work better than those in Chalasani et al. [P. Chalasani, S. Jha, F. Egriboyun, A. Varikooty, A refined binomial lattice for pricing American Asian options, Rev. Derivatives Res. 3 (1) (1999) 85-105] and are very similar to the benchmarks in Hull and White [J. Hull, A. White, Efficient procedures for valuing European and American path-dependent options, J. Derivatives 1 (Fall) (1993) 21-31]. The numerical analysis shows that our modified Edgeworth binomial model can value American Asian options with greater accuracy and speed given higher moments in their underlying distribution.

Development of enhanced pavement deterioration curves.

DOT National Transportation Integrated Search

2016-10-01

This report describes the research performed by the Center for Sustainable Transportation Infrastructure (CSTI) at the Virginia Tech Transportation Institute (VTTI) to develop a pavement condition prediction model, using (negative binomial) regressio...

Indicators of Terrorism Vulnerability in Africa

DTIC Science & Technology

2015-03-26

the terror threat and vulnerabilities across Africa. Key words: Terrorism, Africa, Negative Binomial Regression, Classification Tree iv I would like...31 Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Log -likelihood...70 viii Page 5.3 Classification Tree Description

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts.

PubMed

Preisser, John S; Long, D Leann; Stamm, John W

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two data sets, one consisting of fictional dmft counts in 2 groups and the other on DMFS among schoolchildren from a randomized clinical trial comparing 3 toothpaste formulations to prevent incident dental caries, are analyzed with negative binomial hurdle, zero-inflated negative binomial, and marginalized zero-inflated negative binomial models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the randomized clinical trial were similar despite their distinctive interpretations. The choice of statistical model class should match the study's purpose, while accounting for the broad decline in children's caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. © 2017 S. Karger AG, Basel.

Zero-state Markov switching count-data models: an empirical assessment.

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2010-01-01

In this study, a two-state Markov switching count-data model is proposed as an alternative to zero-inflated models to account for the preponderance of zeros sometimes observed in transportation count data, such as the number of accidents occurring on a roadway segment over some period of time. For this accident-frequency case, zero-inflated models assume the existence of two states: one of the states is a zero-accident count state, which has accident probabilities that are so low that they cannot be statistically distinguished from zero, and the other state is a normal-count state, in which counts can be non-negative integers that are generated by some counting process, for example, a Poisson or negative binomial. While zero-inflated models have come under some criticism with regard to accident-frequency applications - one fact is undeniable - in many applications they provide a statistically superior fit to the data. The Markov switching approach we propose seeks to overcome some of the criticism associated with the zero-accident state of the zero-inflated model by allowing individual roadway segments to switch between zero and normal-count states over time. An important advantage of this Markov switching approach is that it allows for the direct statistical estimation of the specific roadway-segment state (i.e., zero-accident or normal-count state) whereas traditional zero-inflated models do not. To demonstrate the applicability of this approach, a two-state Markov switching negative binomial model (estimated with Bayesian inference) and standard zero-inflated negative binomial models are estimated using five-year accident frequencies on Indiana interstate highway segments. It is shown that the Markov switching model is a viable alternative and results in a superior statistical fit relative to the zero-inflated models.

Application of a hurdle negative binomial count data model to demand for bass fishing in the southeastern United States.

PubMed

Bilgic, Abdulbaki; Florkowski, Wojciech J

2007-06-01

This paper identifies factors that influence the demand for a bass fishing trip taken in the southeastern United States using a hurdle negative binomial count data model. The probability of fishing for a bass is estimated in the first stage and the fishing trip frequency is estimated in the second stage for individuals reporting bass fishing trips in the Southeast. The applied approach allows the decomposition of the effects of factors responsible for the decision to take a trip and the trip number. Calculated partial and total elasticities indicate a highly inelastic demand for the number of fishing trips as trip costs increase. However, the demand can be expected to increase if anglers experience a success measured by the number of caught fish or their size. Benefit estimates based on alternative estimation methods differ substantially, suggesting the need for testing each modeling approach applied in empirical studies.

A comparative study of count models: application to pedestrian-vehicle crashes along Malaysia federal roads.

PubMed

Hosseinpour, Mehdi; Pour, Mehdi Hossein; Prasetijo, Joewono; Yahaya, Ahmad Shukri; Ghadiri, Seyed Mohammad Reza

2013-01-01

The objective of this study was to examine the effects of various roadway characteristics on the incidence of pedestrian-vehicle crashes by developing a set of crash prediction models on 543 km of Malaysia federal roads over a 4-year time span between 2007 and 2010. Four count models including the Poisson, negative binomial (NB), hurdle Poisson (HP), and hurdle negative binomial (HNB) models were developed and compared to model the number of pedestrian crashes. The results indicated the presence of overdispersion in the pedestrian crashes (PCs) and showed that it is due to excess zero rather than variability in the crash data. To handle the issue, the hurdle Poisson model was found to be the best model among the considered models in terms of comparative measures. Moreover, the variables average daily traffic, heavy vehicle traffic, speed limit, land use, and area type were significantly associated with PCs.

Analyzing crash frequency in freeway tunnels: A correlated random parameters approach.

PubMed

Hou, Qinzhong; Tarko, Andrew P; Meng, Xianghai

2018-02-01

The majority of past road safety studies focused on open road segments while only a few focused on tunnels. Moreover, the past tunnel studies produced some inconsistent results about the safety effects of the traffic patterns, the tunnel design, and the pavement conditions. The effects of these conditions therefore remain unknown, especially for freeway tunnels in China. The study presented in this paper investigated the safety effects of these various factors utilizing a four-year period (2009-2012) of data as well as three models: 1) a random effects negative binomial model (RENB), 2) an uncorrelated random parameters negative binomial model (URPNB), and 3) a correlated random parameters negative binomial model (CRPNB). Of these three, the results showed that the CRPNB model provided better goodness-of-fit and offered more insights into the factors that contribute to tunnel safety. The CRPNB was not only able to allocate the part of the otherwise unobserved heterogeneity to the individual model parameters but also was able to estimate the cross-correlations between these parameters. Furthermore, the study results showed that traffic volume, tunnel length, proportion of heavy trucks, curvature, and pavement rutting were associated with higher frequencies of traffic crashes, while the distance to the tunnel wall, distance to the adjacent tunnel, distress ratio, International Roughness Index (IRI), and friction coefficient were associated with lower crash frequencies. In addition, the effects of the heterogeneity of the proportion of heavy trucks, the curvature, the rutting depth, and the friction coefficient were identified and their inter-correlations were analyzed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimation of the cure rate in Iranian breast cancer patients.

PubMed

Rahimzadeh, Mitra; Baghestani, Ahmad Reza; Gohari, Mahmood Reza; Pourhoseingholi, Mohamad Amin

2014-01-01

Although the Cox's proportional hazard model is the popular approach for survival analysis to investigate significant risk factors of cancer patient survival, it is not appropriate in the case of log-term disease free survival. Recently, cure rate models have been introduced to distinguish between clinical determinants of cure and variables associated with the time to event of interest. The aim of this study was to use a cure rate model to determine the clinical associated factors for cure rates of patients with breast cancer (BC). This prospective cohort study covered 305 patients with BC, admitted at Shahid Faiazbakhsh Hospital, Tehran, during 2006 to 2008 and followed until April 2012. Cases of patient death were confirmed by telephone contact. For data analysis, a non-mixed cure rate model with Poisson distribution and negative binomial distribution were employed. All analyses were carried out using a developed Macro in WinBugs. Deviance information criteria (DIC) were employed to find the best model. The overall 1-year, 3-year and 5-year relative survival rates were 97%, 89% and 74%. Metastasis and stage of BC were the significant factors, but age was significant only in negative binomial model. The DIC also showed that the negative binomial model had a better fit. This study indicated that, metastasis and stage of BC were identified as the clinical criteria for cure rates. There are limited studies on BC survival which employed these cure rate models to identify the clinical factors associated with cure. These models are better than Cox, in the case of long-term survival.

Estimating spatial and temporal components of variation in count data using negative binomial mixed models

USGS Publications Warehouse

Irwin, Brian J.; Wagner, Tyler; Bence, James R.; Kepler, Megan V.; Liu, Weihai; Hayes, Daniel B.

2013-01-01

Partitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.

Evaluation of surrogate measures for pedestrian safety in various road and roadside environments.

DOT National Transportation Integrated Search

2012-10-01

This report presents an investigation of pedestrian conflicts and crash count models to learn which exposure measures and roadway or roadside characteristics significantly influence pedestrian safety at road crossings. Negative binomial models were e...

Lotka's Law and Institutional Productivity.

ERIC Educational Resources Information Center

Kumar, Suresh; Sharma, Praveen; Garg, K. C.

1998-01-01

Examines the applicability of Lotka's Law, negative binomial distribution, and lognormal distribution for institutional productivity in the same way as it is to authors and their productivity. Results indicate that none of the distributions are applicable for institutional productivity in engineering sciences. (Author/LRW)

QNB: differential RNA methylation analysis for count-based small-sample sequencing data with a quad-negative binomial model.

PubMed

Liu, Lian; Zhang, Shao-Wu; Huang, Yufei; Meng, Jia

2017-08-31

As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to high throughput sequencing techniques, such as, MeRIP-Seq, transcriptome-wide RNA methylation profile is now available in the form of count-based data, with which it is often of interests to study the dynamics at epitranscriptomic layer. However, the sample size of RNA methylation experiment is usually very small due to its costs; and additionally, there usually exist a large number of genes whose methylation level cannot be accurately estimated due to their low expression level, making differential RNA methylation analysis a difficult task. We present QNB, a statistical approach for differential RNA methylation analysis with count-based small-sample sequencing data. Compared with previous approaches such as DRME model based on a statistical test covering the IP samples only with 2 negative binomial distributions, QNB is based on 4 independent negative binomial distributions with their variances and means linked by local regressions, and in the way, the input control samples are also properly taken care of. In addition, different from DRME approach, which relies only the input control sample only for estimating the background, QNB uses a more robust estimator for gene expression by combining information from both input and IP samples, which could largely improve the testing performance for very lowly expressed genes. QNB showed improved performance on both simulated and real MeRIP-Seq datasets when compared with competing algorithms. And the QNB model is also applicable to other datasets related RNA modifications, including but not limited to RNA bisulfite sequencing, m 1 A-Seq, Par-CLIP, RIP-Seq, etc.

An analytical framework for estimating aquatic species density from environmental DNA

USGS Publications Warehouse

Chambert, Thierry; Pilliod, David S.; Goldberg, Caren S.; Doi, Hideyuki; Takahara, Teruhiko

2018-01-01

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Regular exercise and related factors in patients with Parkinson's disease: Applying zero-inflated negative binomial modeling of exercise count data.

PubMed

Lee, JuHee; Park, Chang Gi; Choi, Moonki

2016-05-01

This study was conducted to identify risk factors that influence regular exercise among patients with Parkinson's disease in Korea. Parkinson's disease is prevalent in the elderly, and may lead to a sedentary lifestyle. Exercise can enhance physical and psychological health. However, patients with Parkinson's disease are less likely to exercise than are other populations due to physical disability. A secondary data analysis and cross-sectional descriptive study were conducted. A convenience sample of 106 patients with Parkinson's disease was recruited at an outpatient neurology clinic of a tertiary hospital in Korea. Demographic characteristics, disease-related characteristics (including disease duration and motor symptoms), self-efficacy for exercise, balance, and exercise level were investigated. Negative binomial regression and zero-inflated negative binomial regression for exercise count data were utilized to determine factors involved in exercise. The mean age of participants was 65.85 ± 8.77 years, and the mean duration of Parkinson's disease was 7.23 ± 6.02 years. Most participants indicated that they engaged in regular exercise (80.19%). Approximately half of participants exercised at least 5 days per week for 30 min, as recommended (51.9%). Motor symptoms were a significant predictor of exercise in the count model, and self-efficacy for exercise was a significant predictor of exercise in the zero model. Severity of motor symptoms was related to frequency of exercise. Self-efficacy contributed to the probability of exercise. Symptom management and improvement of self-efficacy for exercise are important to encourage regular exercise in patients with Parkinson's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Factors Associated with Hospital Length of Stay among Cancer Patients with Febrile Neutropenia

PubMed Central

Rosa, Regis G.; Goldani, Luciano Z.

2014-01-01

Purpose This study sought to evaluate factors associated with hospital length of stay in cancer patients with febrile neutropenia. Methods A prospective cohort study was performed at a single tertiary referral hospital in southern Brazil from October 2009 to August 2011. All adult cancer patients with febrile neutropenia admitted to the hematology ward were evaluated. Stepwise random-effects negative binomial regression was performed to identify risk factors for prolonged length of hospital stay. Results In total, 307 cases of febrile neutropenia were evaluated. The overall median length of hospital stay was 16 days (interquartile range 18 days). According to multiple negative binomial regression analysis, hematologic neoplasms (P = 0.003), high-dose chemotherapy regimens (P<0.001), duration of neutropenia (P<0.001), and bloodstream infection involving Gram-negative multi-drug-resistant bacteria (P = 0.003) were positively associated with prolonged hospital length of stay in patients with febrile neutropenia. The condition index showed no evidence of multi-collinearity effect among the independent variables. Conclusions Hematologic neoplasms, high-dose chemotherapy regimens, prolonged periods of neutropenia, and bloodstream infection with Gram-negative multi-drug-resistant bacteria are predictors of prolonged length hospital of stay among adult cancer patients with febrile neutropenia. PMID:25285790

Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data

PubMed Central

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

Yes, the GIGP Really Does Work--And Is Workable!

ERIC Educational Resources Information Center

Burrell, Quentin L.; Fenton, Michael R.

1993-01-01

Discusses the generalized inverse Gaussian-Poisson (GIGP) process for informetric modeling. Negative binomial distribution is discussed, construction of the GIGP process is explained, zero-truncated GIGP is considered, and applications of the process with journals, library circulation statistics, and database index terms are described. (50…

The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.

PubMed

Nakagawa, Shinichi; Johnson, Paul C D; Schielzeth, Holger

2017-09-01

The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called [Formula: see text] for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments. © 2017 The Author(s).

School Violence: The Role of Parental and Community Involvement

ERIC Educational Resources Information Center

Lesneskie, Eric; Block, Steven

2017-01-01

This study utilizes the School Survey on Crime and Safety to identify variables that predict lower levels of violence from four domains: school security, school climate, parental involvement, and community involvement. Negative binomial regression was performed and the findings indicate that statistically significant results come from all four…

Predicting Children's Asthma Hospitalizations: Rural and Urban Differences in Texas

ERIC Educational Resources Information Center

Grineski, Sara E.

2009-01-01

Asthma is the number one chronic health condition facing children today; however, little is known about rural-urban inequalities in asthma. This "area effects on health" study examines rural-urban differences in childhood asthma hospitalizations within the state of Texas using negative binomial regression models. Effects associated with…

An Alternate Approach to Alternating Sums: A Method to DIE for

ERIC Educational Resources Information Center

Benjamin, Arthur T.; Quinn, Jennifer J.

2008-01-01

Positive sums count. Alternating sums match. Alternating sums of binomial coefficients, Fibonacci numbers, and other combinatorial quantities are analyzed using sign-reversing involutions. In particular, we describe the quantity being considered, match positive and negative terms through an Involution, and count the Exceptions to the matching rule…

Transportation safety data and analysis : Volume 2, Calibration of the highway safety manual and development of new safety performance functions.

DOT National Transportation Integrated Search

2011-03-01

This report documents the calibration of the Highway Safety Manual (HSM) safety performance function (SPF) : for rural two-lane two-way roadway segments in Utah and the development of new models using negative : binomial and hierarchical Bayesian mod...

General Strain Theory as a Basis for the Design of School Interventions

ERIC Educational Resources Information Center

Moon, Byongook; Morash, Merry

2013-01-01

The research described in this article applies general strain theory to identify possible points of intervention for reducing delinquency of students in two middle schools. Data were collected from 296 youths, and separate negative binomial regression analyses were used to identify predictors of violent, property, and status delinquency. Emotional…

A New Zero-Inflated Negative Binomial Methodology for Latent Category Identification

ERIC Educational Resources Information Center

Blanchard, Simon J.; DeSarbo, Wayne S.

2013-01-01

We introduce a new statistical procedure for the identification of unobserved categories that vary between individuals and in which objects may span multiple categories. This procedure can be used to analyze data from a proposed sorting task in which individuals may simultaneously assign objects to multiple piles. The results of a synthetic…

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…

Socio-environmental predictors of Barmah forest virus transmission in coastal areas, Queensland, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; Dale, Pat; McMichael, Anthony J; Tong, Shilu

2009-02-01

To assess the socio-environmental predictors of Barmah forest virus (BFV) transmission in coastal areas, Queensland, Australia. Data on BFV notified cases, climate, tidal levels and socioeconomic index for area (SEIFA) in six coastal cities, Queensland, for the period 1992-2001 were obtained from the relevant government agencies. Negative binomial regression models were used to assess the socio-environmental predictors of BFV transmission. The results show that maximum and minimum temperature, rainfall, relative humidity, high and low tide were statistically significantly associated with BFV incidence at lags 0-2 months. The fitted negative binomial regression models indicate a significant independent association of each of maximum temperature (beta = 0.139, P = 0.000), high tide (beta = 0.005, P = 0.000) and SEIFA index (beta = -0.010, P = 0.000) with BFV transmission after adjustment for confounding variables. The transmission of BFV disease in Queensland coastal areas seemed to be determined by a combination of local social and environmental factors. The model developed in this study may have applications in the control and prevention of BFV disease in these areas.

Mental health status and healthcare utilization among community dwelling older adults.

PubMed

Adepoju, Omolola; Lin, Szu-Hsuan; Mileski, Michael; Kruse, Clemens Scott; Mask, Andrew

2018-04-27

Shifts in mental health utilization patterns are necessary to allow for meaningful access to care for vulnerable populations. There have been long standing issues in how mental health is provided, which has caused problems in that care being efficacious for those seeking it. To assess the relationship between mental health status and healthcare utilization among adults ≥65 years. A negative binomial regression model was used to assess the relationship between mental health status and healthcare utilization related to office-based physician visits, while a two-part model, consisting of logistic regression and negative binomial regression, was used to separately model emergency visits and inpatient services. The receipt of care in office-based settings were marginally higher for subjects with mental health difficulties. Both probabilities and counts of inpatient hospitalizations were similar across mental health categories. The count of ER visits was similar across mental health categories; however, the probability of having an emergency department visit was marginally higher for older adults who reported mental health difficulties in 2012. These findings are encouraging and lend promise to the recent initiatives on addressing gaps in mental healthcare services.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.

PubMed

Gierliński, Marek; Cole, Christian; Schofield, Pietà; Schurch, Nicholas J; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J

2015-11-15

High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of 'bad' replicates, which can drastically affect the gene read-count distribution. RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. g.j.barton@dundee.ac.uk. © The Author 2015. Published by Oxford University Press.

Analysis of overdispersed count data: application to the Human Papillomavirus Infection in Men (HIM) Study.

PubMed

Lee, J-H; Han, G; Fulp, W J; Giuliano, A R

2012-06-01

The Poisson model can be applied to the count of events occurring within a specific time period. The main feature of the Poisson model is the assumption that the mean and variance of the count data are equal. However, this equal mean-variance relationship rarely occurs in observational data. In most cases, the observed variance is larger than the assumed variance, which is called overdispersion. Further, when the observed data involve excessive zero counts, the problem of overdispersion results in underestimating the variance of the estimated parameter, and thus produces a misleading conclusion. We illustrated the use of four models for overdispersed count data that may be attributed to excessive zeros. These are Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial models. The example data in this article deal with the number of incidents involving human papillomavirus infection. The four models resulted in differing statistical inferences. The Poisson model, which is widely used in epidemiology research, underestimated the standard errors and overstated the significance of some covariates.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment

PubMed Central

Cole, Christian; Schofield, Pietà; Schurch, Nicholas J.; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J.

2015-01-01

Motivation: High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. Results: A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of ‘bad’ replicates, which can drastically affect the gene read-count distribution. Availability and implementation: RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. Contact: g.j.barton@dundee.ac.uk PMID:26206307

Simplified pupal surveys of Aedes aegypti (L.) for entomologic surveillance and dengue control.

PubMed

Barrera, Roberto

2009-07-01

Pupal surveys of Aedes aegypti (L.) are useful indicators of risk for dengue transmission, although sample sizes for reliable estimations can be large. This study explores two methods for making pupal surveys more practical yet reliable and used data from 10 pupal surveys conducted in Puerto Rico during 2004-2008. The number of pupae per person for each sampling followed a negative binomial distribution, thus showing aggregation. One method found a common aggregation parameter (k) for the negative binomial distribution, a finding that enabled the application of a sequential sampling method requiring few samples to determine whether the number of pupae/person was above a vector density threshold for dengue transmission. A second approach used the finding that the mean number of pupae/person is correlated with the proportion of pupa-infested households and calculated equivalent threshold proportions of pupa-positive households. A sequential sampling program was also developed for this method to determine whether observed proportions of infested households were above threshold levels. These methods can be used to validate entomological thresholds for dengue transmission.

Modeling left-turn crash occurrence at signalized intersections by conflicting patterns.

PubMed

Wang, Xuesong; Abdel-Aty, Mohamed

2008-01-01

In order to better understand the underlying crash mechanisms, left-turn crashes occurring at 197 four-legged signalized intersections over 6 years were classified into nine patterns based on vehicle maneuvers and then were assigned to intersection approaches. Crash frequency of each pattern was modeled at the approach level by mainly using Generalized Estimating Equations (GEE) with the Negative Binomial as the link function to account for the correlation among the crash data. GEE with a binomial logit link function was also applied for patterns with fewer crashes. The Cumulative Residuals test shows that, for correlated left-turn crashes, GEE models usually outperformed basic Negative Binomial models. The estimation results show that there are obvious differences in the factors that cause the occurrence of different left-turn collision patterns. For example, for each pattern, the traffic flows to which the colliding vehicles belong are identified to be significant. The width of the crossing distance (represented by the number of through lanes on the opposing approach of the left-turning traffic) is associated with more left-turn traffic colliding with opposing through traffic (Pattern 5), but with less left-turning traffic colliding with near-side crossing through traffic (Pattern 8). The safety effectiveness of the left-turning signal is not consistent for different crash patterns; "protected" phasing is correlated with fewer Pattern 5 crashes, but with more Pattern 8 crashes. The study indicates that in order to develop efficient countermeasures for left-turn crashes and improve safety at signalized intersections, left-turn crashes should be considered in different patterns.

Relationship between suicide rate and economic growth and stock market in the People's Republic of China: 2004-2013.

PubMed

Yin, Honglei; Xu, Lin; Shao, Yechang; Li, Liping; Wan, Chengsong

2016-01-01

The objective of this study was to estimate the features of suicide rate and its association with economic development and stock market during the past decade in the People's Republic of China. Official data were gathered and analyzed in the People's Republic of China during the period 2004-2013. Nationwide suicide rate was stratified by four year age-groups, sex, urban/rural areas, and regions (East, Central, and West). Annual economic indexes including gross domestic product (GDP) per capita and rural and urban income per capita were all adjusted for inflation. Variation coefficient of market index (VCMI) was also included as an economic index to measure the fluctuation of the stock market. Negative binomial regression was performed to examine the time trend of region-level suicide rates and effects of sex, age, urban/rural area, region, and economic index on the suicide rates. Suicide rates of each age-group, sex, urban/rural area, and region were generally decreased from 2004 to 2013, while annual GDP per capita and rural and urban income per capita were generally increased by year. VCMI fluctuated largely, which peaked around 2009 and decreased after that time. Negative binomial regression showed that the decreased suicide rate in East and Central rural areas was the main cause of the decrease in suicide rate in the People's Republic of China. Suicide rate in the People's Republic of China for the study period increased with age and was higher in rural than in urban area, higher in males than in females, and the highest in the Central region. When GDP per capita increased by 2,787 RMB, the suicide rate decreased by 0.498 times. VCMI showed no significant relationship with suicide rate in the negative binomial regression. Suicide rate decreased in 2004-2013; varied among different age-groups, sex, urban/rural areas, and regions; and was negatively associated with the economic growth in the People's Republic of China. Stock market showed no relationship with suicide rate, but this finding needs to be verified in a future study.

Relationship between suicide rate and economic growth and stock market in the People’s Republic of China: 2004–2013

PubMed Central

Yin, Honglei; Xu, Lin; Shao, Yechang; Li, Liping; Wan, Chengsong

2016-01-01

Objectives The objective of this study was to estimate the features of suicide rate and its association with economic development and stock market during the past decade in the People’s Republic of China. Methods Official data were gathered and analyzed in the People’s Republic of China during the period 2004–2013. Nationwide suicide rate was stratified by four year age-groups, sex, urban/rural areas, and regions (East, Central, and West). Annual economic indexes including gross domestic product (GDP) per capita and rural and urban income per capita were all adjusted for inflation. Variation coefficient of market index (VCMI) was also included as an economic index to measure the fluctuation of the stock market. Negative binomial regression was performed to examine the time trend of region-level suicide rates and effects of sex, age, urban/rural area, region, and economic index on the suicide rates. Results Suicide rates of each age-group, sex, urban/rural area, and region were generally decreased from 2004 to 2013, while annual GDP per capita and rural and urban income per capita were generally increased by year. VCMI fluctuated largely, which peaked around 2009 and decreased after that time. Negative binomial regression showed that the decreased suicide rate in East and Central rural areas was the main cause of the decrease in suicide rate in the People’s Republic of China. Suicide rate in the People’s Republic of China for the study period increased with age and was higher in rural than in urban area, higher in males than in females, and the highest in the Central region. When GDP per capita increased by 2,787 RMB, the suicide rate decreased by 0.498 times. VCMI showed no significant relationship with suicide rate in the negative binomial regression. Conclusion Suicide rate decreased in 2004–2013; varied among different age-groups, sex, urban/rural areas, and regions; and was negatively associated with the economic growth in the People’s Republic of China. Stock market showed no relationship with suicide rate, but this finding needs to be verified in a future study. PMID:27994468

Estimating safety effects of pavement management factors utilizing Bayesian random effect models.

PubMed

Jiang, Ximiao; Huang, Baoshan; Zaretzki, Russell L; Richards, Stephen; Yan, Xuedong

2013-01-01

Previous studies of pavement management factors that relate to the occurrence of traffic-related crashes are rare. Traditional research has mostly employed summary statistics of bidirectional pavement quality measurements in extended longitudinal road segments over a long time period, which may cause a loss of important information and result in biased parameter estimates. The research presented in this article focuses on crash risk of roadways with overall fair to good pavement quality. Real-time and location-specific data were employed to estimate the effects of pavement management factors on the occurrence of crashes. This research is based on the crash data and corresponding pavement quality data for the Tennessee state route highways from 2004 to 2009. The potential temporal and spatial correlations among observations caused by unobserved factors were considered. Overall 6 models were built accounting for no correlation, temporal correlation only, and both the temporal and spatial correlations. These models included Poisson, negative binomial (NB), one random effect Poisson and negative binomial (OREP, ORENB), and two random effect Poisson and negative binomial (TREP, TRENB) models. The Bayesian method was employed to construct these models. The inference is based on the posterior distribution from the Markov chain Monte Carlo (MCMC) simulation. These models were compared using the deviance information criterion. Analysis of the posterior distribution of parameter coefficients indicates that the pavement management factors indexed by Present Serviceability Index (PSI) and Pavement Distress Index (PDI) had significant impacts on the occurrence of crashes, whereas the variable rutting depth was not significant. Among other factors, lane width, median width, type of terrain, and posted speed limit were significant in affecting crash frequency. The findings of this study indicate that a reduction in pavement roughness would reduce the likelihood of traffic-related crashes. Hence, maintaining a low level of pavement roughness is strongly suggested. In addition, the results suggested that the temporal correlation among observations was significant and that the ORENB model outperformed all other models.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

USGS Publications Warehouse

Dorazio, Robert M.; Martin, Juulien; Edwards, Holly H.

2013-01-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts.

PubMed

Dorazio, Robert M; Martin, Julien; Edwards, Holly H

2013-07-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Perceived Prevalence of Teasing and Bullying Predicts High School Dropout Rates

ERIC Educational Resources Information Center

Cornell, Dewey; Gregory, Anne; Huang, Francis; Fan, Xitao

2013-01-01

This prospective study of 276 Virginia public high schools found that the prevalence of teasing and bullying (PTB) as perceived by both 9th-grade students and teachers was predictive of dropout rates for this cohort 4 years later. Negative binomial regression indicated that one standard deviation increases in student- and teacher-reported PTB were…

The Influence of Television Advertisements on Promoting Calls to Telephone Quitlines

ERIC Educational Resources Information Center

Farrelly, Matthew; Mann, Nathan; Watson, Kimberly; Pechacek, Terry

2013-01-01

The aim of the study was to assess the relative effectiveness of cessation, secondhand smoke and other tobacco control television advertisements in promoting quitlines in nine states from 2002 through 2005. Quarterly, the number of individuals who used quitlines per 10 000 adult smokers in a media market are measured. Negative binomial regression…

Modeling Zero-Inflated and Overdispersed Count Data: An Empirical Study of School Suspensions

ERIC Educational Resources Information Center

Desjardins, Christopher David

2016-01-01

The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative…

Some considerations for excess zeroes in substance abuse research.

PubMed

Bandyopadhyay, Dipankar; DeSantis, Stacia M; Korte, Jeffrey E; Brady, Kathleen T

2011-09-01

Count data collected in substance abuse research often come with an excess of "zeroes," which are typically handled using zero-inflated regression models. However, there is a need to consider the design aspects of those studies before using such a statistical model to ascertain the sources of zeroes. We sought to illustrate hurdle models as alternatives to zero-inflated models to validate a two-stage decision-making process in situations of "excess zeroes." We use data from a study of 45 cocaine-dependent subjects where the primary scientific question was to evaluate whether study participation influences drug-seeking behavior. The outcome, "the frequency (count) of cocaine use days per week," is bounded (ranging from 0 to 7). We fit and compare binomial, Poisson, negative binomial, and the hurdle version of these models to study the effect of gender, age, time, and study participation on cocaine use. The hurdle binomial model provides the best fit. Gender and time are not predictive of use. Higher odds of use versus no use are associated with age; however once use is experienced, odds of further use decrease with increase in age. Participation was associated with higher odds of no-cocaine use; once there is use, participation reduced the odds of further use. Age and study participation are significantly predictive of cocaine-use behavior. The two-stage decision process as modeled by a hurdle binomial model (appropriate for bounded count data with excess zeroes) provides interesting insights into the study of covariate effects on count responses of substance use, when all enrolled subjects are believed to be "at-risk" of use.

Spatial Distribution of Adult Anthonomus grandis Boheman (Coleoptera: Curculionidae) and Damage to Cotton Flower Buds Due to Feeding and Oviposition.

PubMed

Grigolli, J F J; Souza, L A; Fernandes, M G; Busoli, A C

2017-08-01

The cotton boll weevil Anthonomus grandis Boheman (Coleoptera: Curculionidae) is the main pest in cotton crop around the world, directly affecting cotton production. In order to establish a sequential sampling plan, it is crucial to understand the spatial distribution of the pest population and the damage it causes to the crop through the different developmental stages of cotton plants. Therefore, this study aimed to investigate the spatial distribution of adults in the cultivation area and their oviposition and feeding behavior throughout the development of the cotton plants. The experiment was conducted in Maracaju, Mato Grosso do Sul, Brazil, in the 2012/2013 and 2013/2014 growing seasons, in an area of 10,000 m 2 , planted with the cotton cultivar FM 993. The experimental area was divided into 100 plots of 100 m 2 (10 × 10 m) each, and five plants per plot were sampled weekly throughout the crop cycle. The number of flower buds with feeding and oviposition punctures and of adult A. grandis was recorded throughout the crop cycle in five plants per plot. After determining the aggregation indices (variance/mean ratio, Morisita's index, exponent k of the negative binomial distribution, and Green's coefficient) and adjusting the frequencies observed in the field to the distribution of frequencies (Poisson, negative binomial, and positive binomial) using the chi-squared test, it was observed that flower buds with punctures derived from feeding, oviposition, and feeding + oviposition showed an aggregated distribution in the cultivation area until 85 days after emergence and a random distribution after this stage. The adults of A. grandis presented a random distribution in the cultivation area.

[Spatial epidemiological study on malaria epidemics in Hainan province].

PubMed

Wen, Liang; Shi, Run-He; Fang, Li-Qun; Xu, De-Zhong; Li, Cheng-Yi; Wang, Yong; Yuan, Zheng-Quan; Zhang, Hui

2008-06-01

To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics. Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0. The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST). Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Single-vehicle crashes along rural mountainous highways in Malaysia: An application of random parameters negative binomial model.

PubMed

Rusli, Rusdi; Haque, Md Mazharul; King, Mark; Voon, Wong Shaw

2017-05-01

Mountainous highways generally associate with complex driving environment because of constrained road geometries, limited cross-section elements, inappropriate roadside features, and adverse weather conditions. As a result, single-vehicle (SV) crashes are overrepresented along mountainous roads, particularly in developing countries, but little attention is known about the roadway geometric, traffic and weather factors contributing to these SV crashes. As such, the main objective of the present study is to investigate SV crashes using detailed data obtained from a rigorous site survey and existing databases. The final dataset included a total of 56 variables representing road geometries including horizontal and vertical alignment, traffic characteristics, real-time weather condition, cross-sectional elements, roadside features, and spatial characteristics. To account for structured heterogeneities resulting from multiple observations within a site and other unobserved heterogeneities, the study applied a random parameters negative binomial model. Results suggest that rainfall during the crash is positively associated with SV crashes, but real-time visibility is negatively associated. The presence of a road shoulder, particularly a bitumen shoulder or wider shoulders, along mountainous highways is associated with less SV crashes. While speeding along downgrade slopes increases the likelihood of SV crashes, proper delineation decreases the likelihood. Findings of this study have significant implications for designing safer highways in mountainous areas, particularly in the context of a developing country. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Model Comparison for Count Data with a Positively Skewed Distribution with an Application to the Number of University Mathematics Courses Completed

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…

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…

Which Types of Televised Anti-Tobacco Campaigns Prompt More Quitline Calls from Disadvantaged Groups?

ERIC Educational Resources Information Center

Durkin, Sarah J.; Wakefield, Melanie A.; Spittal, Matthew J.

2011-01-01

To examine the efficacy of different types of mass media ads in driving lower socio-economic smokers (SES) to utilize quitlines. This study collected all 33 719 calls to the Victorian quitline in Australia over a 2-year period. Negative binomial regressions examined the relationship between weekly levels of exposure to different types of…

Togetherness among Plasmodium falciparum gametocytes: interpretation through simulation and consequences for malaria transmission.

PubMed

Gaillard, F O; Boudin, C; Chau, N P; Robert, V; Pichon, G

2003-11-01

Previous experimental gametocyte infections of Anopheles arabiensis on 3 volunteers naturally infected with Plasmodium falciparum were conducted in Senegal. They showed that gametocyte counts in the mosquitoes are, like macroparasite intakes, heterogeneous (overdispersed). They followed a negative binomial distribution, the overdispersion coefficient seeming constant (k = 3.1). To try to explain this heterogeneity, we used an individual-based model (IBM), simulating the behaviour of gametocytes in the human blood circulation and their ingestion by mosquitoes. The hypothesis was that there exists a clustering of the gametocytes in the capillaries. From a series of simulations, in the case of clustering the following results were obtained: (i) the distribution of the gametocytes ingested by the mosquitoes followed a negative binomial, (ii) the k coefficient significantly increased with the density of circulating gametocytes. To validate this model result, 2 more experiments were conducted in Cameroon. Pooled experiments showed a distinct density dependency of the k-values. The simulation results and the experimental results were thus in agreement and suggested that an aggregation process at the microscopic level might produce the density-dependent overdispersion at the macroscopic level. Simulations also suggested that the clustering of gametocytes might facilitate fertilization of gametes.

Effectiveness on Early Childhood Caries of an Oral Health Promotion Program for Medical Providers

PubMed Central

Widmer-Racich, Katina; Sevick, Carter; Starzyk, Erin J.; Mauritson, Katya; Hambidge, Simon J.

2017-01-01

Objectives. To assess an oral health promotion (OHP) intervention for medical providers’ impact on early childhood caries (ECC). Methods. We implemented a quasiexperimental OHP intervention in 8 federally qualified health centers that trained medical providers on ECC risk assessment, oral examination and instruction, dental referral, and fluoride varnish applications (FVAs). We measured OHP delivery by FVA count at medical visits. We measured the intervention’s impact on ECC in 3 unique cohorts of children aged 3 to 4 years in 2009 (preintervention; n = 202), 2011 (midintervention; n = 420), and 2015 (≥ 4 FVAs; n = 153). We compared numbers of decayed, missing, and filled tooth surfaces using adjusted zero-inflated negative binomial models. Results. Across 3 unique cohorts, the FVA mean (range) count was 0.0 (0), 1.1 (0–7), and 4.5 (4–7) in 2009, 2011, and 2015, respectively. In adjusted zero-inflated negative binomial models analyses, children in the 2015 cohort had significantly fewer decayed, missing, and filled tooth surfaces than did children in previous cohorts. Conclusions. An OHP intervention targeting medical providers reduced ECC when children received 4 or more FVAs at a medical visit by age 3 years. PMID:28661802

Co-Infestation and Spatial Distribution of Bactrocera carambolae and Anastrepha spp. (Diptera: Tephritidae) in Common Guava in the Eastern Amazon

PubMed Central

Deus, E. G.; Godoy, W. A. C.; Sousa, M. S. M.; Lopes, G. N.; Jesus-Barros, C. R.; Silva, J. G.; Adaime, R.

2016-01-01

Field infestation and spatial distribution of introduced Bactrocera carambolae Drew and Hancock and native species of Anastrepha in common guavas [Psidium guajava (L.)] were investigated in the eastern Amazon. Fruit sampling was carried out in the municipalities of Calçoene and Oiapoque in the state of Amapá, Brazil. The frequency distribution of larvae in fruit was fitted to the negative binomial distribution. Anastrepha striata was more abundant in both sampled areas in comparison to Anastrepha fraterculus (Wiedemann) and B. carambolae. The frequency distribution analysis of adults revealed an aggregated pattern for B. carambolae as well as for A. fraterculus and Anastrepha striata Schiner, described by the negative binomial distribution. Although the populations of Anastrepha spp. may have suffered some impact due to the presence of B. carambolae, the results are still not robust enough to indicate effective reduction in the abundance of Anastrepha spp. caused by B. carambolae in a general sense. The high degree of aggregation observed for both species suggests interspecific co-occurrence with the simultaneous presence of both species in the analysed fruit. Moreover, a significant fraction of uninfested guavas also indicated absence of competitive displacement. PMID:27638949

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits.

PubMed

Neelon, Brian; Chang, Howard H; Ling, Qiang; Hastings, Nicole S

2016-12-01

Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components-one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce dependence between the components and provide spatial and temporal smoothing across adjacent spatial units and time periods, resulting in improved inferences. To accommodate potential overdispersion, we consider a range of parametric specifications for the positive counts, including truncated negative binomial and generalized Poisson distributions. We adopt a Bayesian inferential approach, and posterior computation is handled conveniently within standard Bayesian software. Our results indicate that the negative binomial and generalized Poisson hurdle models vastly outperform the Poisson hurdle model, demonstrating that overdispersed hurdle models provide a useful approach to analyzing zero-inflated spatiotemporal data. © The Author(s) 2014.

A Time Series Analysis: Weather Factors, Human Migration and Malaria Cases in Endemic Area of Purworejo, Indonesia, 2005–2014

PubMed Central

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

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

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.

Impact of early childhood caries on oral health-related quality of life of preschool children.

PubMed

Li, M Y; Zhi, Q H; Zhou, Y; Qiu, R M; Lin, H C

2015-03-01

Child oral health-related quality of life (COHRQoL) has been assessed in developed areas; however, it remains unstudied in mainland China. Studies on COHRQoL would benefit a large number of children in China suffering from oral health problems such as dental caries. This study explored the relationship between COHRQoL and early childhood caries, adjusted by socioeconomic factors, in 3- to 4-year-old children in a region of southern China. In this study, 1062 children aged 3-4 years were recruited by cluster sampling and their oral health statuses were examined by a trained dentist. The Chinese version of the Early Childhood Oral Health Impact Scale (ECOHIS) and questions about the children's socioeconomic conditions were completed by the children's parents. A negative binomial regression analysis was used to assess the prevalence of early childhood caries among the children and its influence on COHRQoL. The total ECOHIS scores of the returned scale sets ranged from 0 to 31, and their average scores was 3.1±5.1. The negative binomial analysis showed that the dmfs indices were significantly associated with the ECOHIS score and subscale scores (P<0.05). The multivariate adjusted model showed that a higher dmft index was associated with greater negative impact on COHRQoL (RR = 1.10; 95% CI = 1.07, 1.13; P < 0.05). However, demographic and socioeconomic factors were not associated with COHRQoL (P>0.05). The severity of early childhood caries has a negative impact on the oral health-related quality of life of preschool children and their parents.

CUMBIN - CUMULATIVE BINOMIAL PROGRAMS

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative binomial program, CUMBIN, is one of a set of three programs which calculate cumulative binomial probability distributions for arbitrary inputs. The three programs, CUMBIN, NEWTONP (NPO-17556), and CROSSER (NPO-17557), can be used independently of one another. CUMBIN can be used by statisticians and users of statistical procedures, test planners, designers, and numerical analysts. The program has been used for reliability/availability calculations. CUMBIN calculates the probability that a system of n components has at least k operating if the probability that any one operating is p and the components are independent. Equivalently, this is the reliability of a k-out-of-n system having independent components with common reliability p. CUMBIN can evaluate the incomplete beta distribution for two positive integer arguments. CUMBIN can also evaluate the cumulative F distribution and the negative binomial distribution, and can determine the sample size in a test design. CUMBIN is designed to work well with all integer values 0 < k <= n. To run the program, the user simply runs the executable version and inputs the information requested by the program. The program is not designed to weed out incorrect inputs, so the user must take care to make sure the inputs are correct. Once all input has been entered, the program calculates and lists the result. The CUMBIN program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly with most C compilers. The program format is interactive. It has been implemented under DOS 3.2 and has a memory requirement of 26K. CUMBIN was developed in 1988.

Do Barriers to Crime Prevention Moderate the Effects of Situational Crime Prevention Policies on Violent Crime in High Schools?

ERIC Educational Resources Information Center

Sevigny, Eric L.; Zhang, Gary

2018-01-01

This study investigates how barriers to school-based crime prevention programming moderate the effects of situational crime prevention (SCP) policies on levels of violent crime in U.S. public high schools. Using data from the 2008 School Survey on Crime and Safety, we estimate a series of negative binomial regression models with interactions to…

Evaluation of the Johne's disease risk assessment and management plan on dairy farms in Ontario, Canada.

PubMed

Pieper, Laura; Sorge, Ulrike S; DeVries, Trevor J; Godkin, Ann; Lissemore, Kerry; Kelton, David F

2015-10-01

Johne's disease (JD) is a production-limiting gastrointestinal disease in cattle. To minimize the effects of JD, the Ontario dairy industry launched the Ontario Johne's Education and Management Assistance Program in 2010. As part of the program, trained veterinarians conducted a risk assessment and management plan (RAMP), an on-farm questionnaire where high RAMP scores are associated with high risk of JD transmission. Subsequently, veterinarians recommended farm-specific management practices for JD prevention. Milk or serum ELISA results from the milking herd were used to determine the herd ELISA status (HES) and within-herd prevalence. After 3.5 yr of implementation of the program, the aim of this study was to evaluate the associations among RAMP scores, HES, and recommendations. Data from 2,103 herds were available for the analyses. A zero-inflated negative binomial model for the prediction of the number of ELISA-positive animals per farm was built. The model included individual RAMP questions about purchasing animals in the logistic portion, indicating risks for between-herd transmission, and purchasing bulls, birth of calves outside the designated calving area, colostrum and milk feeding management, and adult cow environmental hygiene in the negative binomial portion, indicating risk factors for within-herd transmission. However, farms which fed low-risk milk compared with milk replacer had fewer seropositive animals. The model additionally included the JD herd history in the negative binomial and the logistic portion, indicating that herds with a JD herd history were more likely to have at least 1 positive animal and to have a higher number of positive animals. Generally, a positive association was noted between RAMP scores and the odds of receiving a recommendation for the respective risk area; however, the relationship was not always linear. For general JD risk and calving area risk, seropositive herds had higher odds of receiving recommendations compared with seronegative herds if the section scores were low. This study suggests that the RAMP is a valuable tool to assess the risk for JD transmission within and between herds and to determine farm-specific recommendations for JD prevention. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predictive accuracy of particle filtering in dynamic models supporting outbreak projections.

PubMed

Safarishahrbijari, Anahita; Teyhouee, Aydin; Waldner, Cheryl; Liu, Juxin; Osgood, Nathaniel D

2017-09-26

While a new generation of computational statistics algorithms and availability of data streams raises the potential for recurrently regrounding dynamic models with incoming observations, the effectiveness of such arrangements can be highly subject to specifics of the configuration (e.g., frequency of sampling and representation of behaviour change), and there has been little attempt to identify effective configurations. Combining dynamic models with particle filtering, we explored a solution focusing on creating quickly formulated models regrounded automatically and recurrently as new data becomes available. Given a latent underlying case count, we assumed that observed incident case counts followed a negative binomial distribution. In accordance with the condensation algorithm, each such observation led to updating of particle weights. We evaluated the effectiveness of various particle filtering configurations against each other and against an approach without particle filtering according to the accuracy of the model in predicting future prevalence, given data to a certain point and a norm-based discrepancy metric. We examined the effectiveness of particle filtering under varying times between observations, negative binomial dispersion parameters, and rates with which the contact rate could evolve. We observed that more frequent observations of empirical data yielded super-linearly improved accuracy in model predictions. We further found that for the data studied here, the most favourable assumptions to make regarding the parameters associated with the negative binomial distribution and changes in contact rate were robust across observation frequency and the observation point in the outbreak. Combining dynamic models with particle filtering can perform well in projecting future evolution of an outbreak. Most importantly, the remarkable improvements in predictive accuracy resulting from more frequent sampling suggest that investments to achieve efficient reporting mechanisms may be more than paid back by improved planning capacity. The robustness of the results on particle filter configuration in this case study suggests that it may be possible to formulate effective standard guidelines and regularized approaches for such techniques in particular epidemiological contexts. Most importantly, the work tentatively suggests potential for health decision makers to secure strong guidance when anticipating outbreak evolution for emerging infectious diseases by combining even very rough models with particle filtering method.

Not in My Back Yard: A Comparative Analysis of Crime Around Publicly Funded Drug Treatment Centers, Liquor Stores, Convenience Stores, and Corner Stores in One Mid-Atlantic City.

PubMed

Furr-Holden, C Debra M; Milam, Adam J; Nesoff, Elizabeth D; Johnson, Renee M; Fakunle, David O; Jennings, Jacky M; Thorpe, Roland J

2016-01-01

This research examined whether publicly funded drug treatment centers (DTCs) were associated with violent crime in excess of the violence happening around other commercial businesses. Violent crime data and locations of community entities were geocoded and mapped. DTCs and other retail outlets were matched based on a Neighborhood Disadvantage score at the census tract level. Street network buffers ranging from 100 to 1,400 feet were placed around each location. Negative binomial regression models were used to estimate the relationship between the count of violent crimes and the distance from each business type. Compared with the mean count of violent crime around drug treatment centers, the mean count of violent crime (M = 2.87) was significantly higher around liquor stores (M = 3.98; t test; p < .01) and corner stores (M = 3.78; t test; p < .01), and there was no statistically significant difference between the count around convenience stores (M = 2.65; t test; p = .32). In the adjusted negative binomial regression models, there was a negative and significant relationship between the count of violent crime and the distance from drug treatment centers (β = -.069, p < .01), liquor stores (β = -.081, p < .01), corner stores (β = -.116, p < .01), and convenience stores (β = -.154, p < .01). Violent crime associated with drug treatment centers is similar to that associated with liquor stores and is less frequent than that associated with convenience stores and corner stores.

Sequential sampling of ribes populations in the control of white pine blister rust (Cronartium ribicola Fischer) in California

Treesearch

Harold R. Offord

1966-01-01

Sequential sampling based on a negative binomial distribution of ribes populations required less than half the time taken by regular systematic line transect sampling in a comparison test. It gave the same control decision as the regular method in 9 of 13 field trials. A computer program that permits sequential plans to be built readily for other white pine regions is...

Logistic quantile regression provides improved estimates for bounded avian counts: a case study of California Spotted Owl fledgling production

Treesearch

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...

Oral health of schoolchildren in Western Australia.

PubMed

Arrow, P

2016-09-01

The West Australian School Dental Service (SDS) provides free, statewide, primary dental care to schoolchildren aged 5-17 years. This study reports on an evaluation of the oral health of children examined during the 2014 calendar year. Children were sampled, based on their date of birth, and SDS clinicians collected the clinical information. Weighted mean values of caries experience were presented. Negative binomial regression modelling was undertaken to test for factors of significance in the rate of caries occurrence. Data from children aged 5-15 years were used (girls = 4616, boys = 4900). Mean dmft (5-10-year-olds), 1.42 SE 0.03; mean DMFT (6-15-year-olds), 0.51 SE 0.01. Negative binomial regression model of permanent tooth caries found higher rates of caries in children who were from non-fluoridated areas (RR 2.1); Aboriginal (RR 2.4); had gingival inflammation (RR 1.5); lower ICSEA level (RR 1.4); and recalled at more than 24-month interval (RR 1.8). The study highlighted poor dental health associated with living in non-fluoridated areas, Aboriginal identity, poor oral hygiene, lower socioeconomic level and having extended intervals between dental checkups. Timely assessments and preventive measures targeted at groups, including extending community water fluoridation, may assist in further improving the oral health of children in Western Australia. © 2015 Australian Dental Association.

Characterizing environmental risk factors for West Nile virus in Quebec, Canada, using clinical data in humans and serology in pet dogs.

PubMed

Rocheleau, J P; Michel, P; Lindsay, L R; Drebot, M; Dibernardo, A; Ogden, N H; Fortin, A; Arsenault, J

2017-10-01

The identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.

Negative Binomial Process Count and Mixture Modeling.

PubMed

Zhou, Mingyuan; Carin, Lawrence

2015-02-01

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process for count modeling. A draw from the NB process consists of a Poisson distributed finite number of distinct atoms, each of which is associated with a logarithmic distributed number of data samples. We reveal relationships between various count- and mixture-modeling distributions and construct a Poisson-logarithmic bivariate distribution that connects the NB and Chinese restaurant table distributions. Fundamental properties of the models are developed, and we derive efficient Bayesian inference. It is shown that with augmentation and normalization, the NB process and gamma-NB process can be reduced to the Dirichlet process and hierarchical Dirichlet process, respectively. These relationships highlight theoretical, structural, and computational advantages of the NB process. A variety of NB processes, including the beta-geometric, beta-NB, marked-beta-NB, marked-gamma-NB and zero-inflated-NB processes, with distinct sharing mechanisms, are also constructed. These models are applied to topic modeling, with connections made to existing algorithms under Poisson factor analysis. Example results show the importance of inferring both the NB dispersion and probability parameters.

Community covariates of malnutrition based mortality among older adults.

PubMed

Lee, Matthew R; Berthelot, Emily R

2010-05-01

The purpose of this study was to identify community level covariates of malnutrition-based mortality among older adults. A community level framework was delineated which explains rates of malnutrition-related mortality among older adults as a function of community levels of socioeconomic disadvantage, disability, and social isolation among members of this group. County level data on malnutrition mortality of people 65 years of age and older for the period 2000-2003 were drawn from the CDC WONDER system databases. County level measures of older adult socioeconomic disadvantage, disability, and social isolation were derived from the 2000 US Census of Population and Housing. Negative binomial regression models adjusting for the size of the population at risk, racial composition, urbanism, and region were estimated to assess the relationships among these indicators. Results from negative binomial regression analysis yielded the following: a standard deviation increase in socioeconomic/physical disadvantage was associated with a 12% increase in the rate of malnutrition mortality among older adults (p < 0.001), whereas a standard deviation increase in social isolation was associated with a 5% increase in malnutrition mortality among older adults (p < 0.05). Community patterns of malnutrition based mortality among older adults are partly a function of levels of socioeconomic and physical disadvantage and social isolation among older adults. 2010 Elsevier Inc. All rights reserved.

Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

PubMed

Mi, Gu; Di, Yanming; Schafer, Daniel W

2015-01-01

This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

Forecasting asthma-related hospital admissions in London using negative binomial models.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

2013-05-01

Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

Accident prediction model for public highway-rail grade crossings.

PubMed

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.

Association between adherence to physical activity guidelines and health-related quality of life among individuals with physician-diagnosed arthritis.

PubMed

Austin, Shamly; Qu, Haiyan; Shewchuk, Richard M

2012-10-01

To examine the association between adherence to physical activity guidelines and health-related quality of life (HRQOL) among individuals with arthritis. A cross-sectional sample with 33,071 US adults, 45 years or older with physician-diagnosed arthritis was obtained from 2007 Behavioral Risk Factor Surveillance System survey. We conducted negative binomial regression analysis to examine HRQOL as a function of adherence to physical activity guidelines controlling for physicians' recommendations for physical activity, age, sex, race, education, marital status, employment, annual income, health insurance, personal physician, emotional support, body mass index, activity limitations, health status, and co-morbidities based on Behavioral Model of Health Services Utilization. Descriptive statistics showed that 60% adults with arthritis did not adhere to physical activity guidelines, mean physically and mentally unhealthy days were 7.7 and 4.4 days, respectively. Results from negative binomial regression indicated that individuals who did not adhere to physical activity guidelines had 1.14 days more physically unhealthy days and 1.12 days more mentally unhealthy days than those who adhered controlling for covariates. Adherence to physical activity is important to improve HRQOL for individuals with arthritis. However, adherence is low among this population. Interventions are required to engage individuals with arthritis in physical activity.

Technical and biological variance structure in mRNA-Seq data: life in the real world

PubMed Central

2012-01-01

Background mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts have classically been assumed to follow a Poisson distribution in which the variance is equal to the mean. The Negative Binomial distribution which allows for over-dispersion, i.e., for the variance to be greater than the mean, is commonly used to model count data as well. Results In mRNA-Seq data from 25 subjects, we found technical variation to generally follow a Poisson distribution as has been reported previously and biological variability was over-dispersed relative to the Poisson model. The mean-variance relationship across all genes was quadratic, in keeping with a Negative Binomial (NB) distribution. Over-dispersed Poisson and NB distributional assumptions demonstrated marked improvements in goodness-of-fit (GOF) over the standard Poisson model assumptions, but with evidence of over-fitting in some genes. Modeling of experimental effects improved GOF for high variance genes but increased the over-fitting problem. Conclusions These conclusions will guide development of analytical strategies for accurate modeling of variance structure in these data and sample size determination which in turn will aid in the identification of true biological signals that inform our understanding of biological systems. PMID:22769017

Design and analysis of three-arm trials with negative binomially distributed endpoints.

PubMed

Mütze, Tobias; Munk, Axel; Friede, Tim

2016-02-20

A three-arm clinical trial design with an experimental treatment, an active control, and a placebo control, commonly referred to as the gold standard design, enables testing of non-inferiority or superiority of the experimental treatment compared with the active control. In this paper, we propose methods for designing and analyzing three-arm trials with negative binomially distributed endpoints. In particular, we develop a Wald-type test with a restricted maximum-likelihood variance estimator for testing non-inferiority or superiority. For this test, sample size and power formulas as well as optimal sample size allocations will be derived. The performance of the proposed test will be assessed in an extensive simulation study with regard to type I error rate, power, sample size, and sample size allocation. For the purpose of comparison, Wald-type statistics with a sample variance estimator and an unrestricted maximum-likelihood estimator are included in the simulation study. We found that the proposed Wald-type test with a restricted variance estimator performed well across the considered scenarios and is therefore recommended for application in clinical trials. The methods proposed are motivated and illustrated by a recent clinical trial in multiple sclerosis. The R package ThreeArmedTrials, which implements the methods discussed in this paper, is available on CRAN. Copyright © 2015 John Wiley & Sons, Ltd.

Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach

USGS Publications Warehouse

Martin, Julien; Royle, J. Andrew; MacKenzie, Darryl I.; Edwards, Holly H.; Kery, Marc; Gardner, Beth

2011-01-01

Summary 1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost-effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non-independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians). 2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non-independent detection of individuals. We simulated correlated behaviour using beta-binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter. 3. Fitting binomial mixture models to data that followed a beta-binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta-binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness-of-fit procedure to evaluate the fit of beta-binomial mixture models. 4. We illustrate our approach by fitting both binomial and beta-binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta-binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness-of-fit when analysing ecological data with N-mixture models. Indeed, both the simulations and the goodness-of-fit procedure highlighted the limitations of the standard binomial mixture model for aerial manatee surveys. 5. Overestimation of abundance by binomial mixture models owing to non-independent detections is problematic for ecological studies, but also for conservation. For example, in the case of endangered species, it could lead to inappropriate management decisions, such as downlisting. These issues will be increasingly relevant as more ecologists apply flexible N-mixture models to ecological data.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach

PubMed Central

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2018-01-01

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach, and has several attractive features compared to the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, since the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. PMID:26303591

A Note on a Family of Alternating Sums of Products of Binomial Numbers

ERIC Educational Resources Information Center

Gauthier, N.

2013-01-01

We study the following family of integral-valued alternating sums, where -infinity equal to or less than m equal to or less than infinity and n equal to or greater than 0 are integers [equation omitted]. We first consider h[subscript m](n) for m and n non-negative integers and show that it is of the form 2[superscript n + 2m] - P[subscript m](n),…

[Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

PubMed

Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

2017-03-10

To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

PubMed

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

Not in My Back Yard: A Comparative Analysis of Crime Around Publicly Funded Drug Treatment Centers, Liquor Stores, Convenience Stores, and Corner Stores in One Mid-Atlantic City

PubMed Central

Furr-Holden, C. Debra M.; Milam, Adam J.; Nesoff, Elizabeth D.; Johnson, Renee M.; Fakunle, David O.; Jennings, Jacky M.; Thorpe, Roland J.

2016-01-01

Objective: This research examined whether publicly funded drug treatment centers (DTCs) were associated with violent crime in excess of the violence happening around other commercial businesses. Method: Violent crime data and locations of community entities were geocoded and mapped. DTCs and other retail outlets were matched based on a Neighborhood Disadvantage score at the census tract level. Street network buffers ranging from 100 to 1,400 feet were placed around each location. Negative binomial regression models were used to estimate the relationship between the count of violent crimes and the distance from each business type. Results: Compared with the mean count of violent crime around drug treatment centers, the mean count of violent crime (M = 2.87) was significantly higher around liquor stores (M = 3.98; t test; p < .01) and corner stores (M = 3.78; t test; p < .01), and there was no statistically significant difference between the count around convenience stores (M = 2.65; t test; p = .32). In the adjusted negative binomial regression models, there was a negative and significant relationship between the count of violent crime and the distance from drug treatment centers (β = -.069, p < .01), liquor stores (β = -.081, p < .01), corner stores (β = -.116, p < .01), and convenience stores (β = -.154, p < .01). Conclusions: Violent crime associated with drug treatment centers is similar to that associated with liquor stores and is less frequent than that associated with convenience stores and corner stores. PMID:26751351

Modeling avian abundance from replicated counts using binomial mixture models

USGS Publications Warehouse

Kery, Marc; Royle, J. Andrew; Schmid, Hans

2005-01-01

Abundance estimation in ecology is usually accomplished by capture–recapture, removal, or distance sampling methods. These may be hard to implement at large spatial scales. In contrast, binomial mixture models enable abundance estimation without individual identification, based simply on temporally and spatially replicated counts. Here, we evaluate mixture models using data from the national breeding bird monitoring program in Switzerland, where some 250 1-km2 quadrats are surveyed using the territory mapping method three times during each breeding season. We chose eight species with contrasting distribution (wide–narrow), abundance (high–low), and detectability (easy–difficult). Abundance was modeled as a random effect with a Poisson or negative binomial distribution, with mean affected by forest cover, elevation, and route length. Detectability was a logit-linear function of survey date, survey date-by-elevation, and sampling effort (time per transect unit). Resulting covariate effects and parameter estimates were consistent with expectations. Detectability per territory (for three surveys) ranged from 0.66 to 0.94 (mean 0.84) for easy species, and from 0.16 to 0.83 (mean 0.53) for difficult species, depended on survey effort for two easy and all four difficult species, and changed seasonally for three easy and three difficult species. Abundance was positively related to route length in three high-abundance and one low-abundance (one easy and three difficult) species, and increased with forest cover in five forest species, decreased for two nonforest species, and was unaffected for a generalist species. Abundance estimates under the most parsimonious mixture models were between 1.1 and 8.9 (median 1.8) times greater than estimates based on territory mapping; hence, three surveys were insufficient to detect all territories for each species. We conclude that binomial mixture models are an important new approach for estimating abundance corrected for detectability when only repeated-count data are available. Future developments envisioned include estimation of trend, occupancy, and total regional abundance.

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data.

PubMed

Holsclaw, Tracy; Hallgren, Kevin A; Steyvers, Mark; Smyth, Padhraic; Atkins, David C

2015-12-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased Type I and Type II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in online supplemental materials. (c) 2016 APA, all rights reserved).

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data

PubMed Central

Holsclaw, Tracy; Hallgren, Kevin A.; Steyvers, Mark; Smyth, Padhraic; Atkins, David C.

2015-01-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non-normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased type-I and type-II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally-technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in supplementary materials. PMID:26098126

Magnitude of virologic blips is associated with a higher risk for virologic rebound in HIV-infected individuals: a recurrent events analysis.

PubMed

Grennan, J Troy; Loutfy, Mona R; Su, DeSheng; Harrigan, P Richard; Cooper, Curtis; Klein, Marina; Machouf, Nima; Montaner, Julio S G; Rourke, Sean; Tsoukas, Christos; Hogg, Bob; Raboud, Janet

2012-04-15

The importance of human immunodeficiency virus (HIV) blip magnitude on virologic rebound has been raised in clinical guidelines relating to viral load assays. Antiretroviral-naive individuals initiating combination antiretroviral therapy (cART) after 1 January 2000 and achieving virologic suppression were studied. Negative binomial models were used to identify blip correlates. Recurrent event models were used to determine the association between blips and rebound by incorporating multiple periods of virologic suppression per individual. 3550 participants (82% male; median age, 40 years) were included. In a multivariable negative binomial regression model, the Amplicor assay was associated with a lower blip rate than branched DNA (rate ratio, 0.69; P < .01), controlling for age, sex, region, baseline HIV-1 RNA and CD4 count, AIDS-defining illnesses, year of cART initiation, cART type, and HIV-1 RNA testing frequency. In a multivariable recurrent event model controlling for age, sex, intravenous drug use, cART start year, cART type, assay type, and HIV-1 RNA testing frequency, blips of 500-999 copies/mL were associated with virologic rebound (hazard ratio, 2.70; P = .002), whereas blips of 50-499 were not. HIV-1 RNA assay was an important determinant of blip rates and should be considered in clinical guidelines. Blips ≥500 copies/mL were associated with increased rebound risk.

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling the distribution of colonial species to improve estimation of plankton concentration in ballast water

NASA Astrophysics Data System (ADS)

Rajakaruna, Harshana; VandenByllaardt, Julie; Kydd, Jocelyn; Bailey, Sarah

2018-03-01

The International Maritime Organization (IMO) has set limits on allowable plankton concentrations in ballast water discharge to minimize aquatic invasions globally. Previous guidance on ballast water sampling and compliance decision thresholds was based on the assumption that probability distributions of plankton are Poisson when spatially homogenous, or negative binomial when heterogeneous. We propose a hierarchical probability model, which incorporates distributions at the level of particles (i.e., discrete individuals plus colonies per unit volume) and also within particles (i.e., individuals per particle) to estimate the average plankton concentration in ballast water. We examined the performance of the models using data for plankton in the size class ≥ 10 μm and < 50 μm, collected from five different depths of a ballast tank of a commercial ship in three independent surveys. We show that the data fit to the negative binomial and the hierarchical probability models equally well, with both models performing better than the Poisson model at the scale of our sampling. The hierarchical probability model, which accounts for both the individuals and the colonies in a sample, reduces the uncertainty associated with the concentration estimation, and improves the power of rejecting the decision on ship's compliance when a ship does not truly comply with the standard. We show examples of how to test ballast water compliance using the above models.

A statistical model to estimate the impact of a hepatitis A vaccination programme.

PubMed

Oviedo, Manuel; Pilar Muñoz, M; Domínguez, Angela; Borras, Eva; Carmona, Gloria

2008-11-11

A program of routine hepatitis A+B vaccination in preadolescents was introduced in 1998 in Catalonia, a region situated in the northeast of Spain. The objective of this study was to quantify the reduction in the incidence of hepatitis A in order to differentiate the natural reduction of the incidence of hepatitis A from that produced due to the vaccination programme and to predict the evolution of the disease in forthcoming years. A generalized linear model (GLM) using negative binomial regression was used to estimate the incidence rates of hepatitis A in Catalonia by year, age group and vaccination. Introduction of the vaccine reduced cases by 5.5 by year (p-value<0.001), but there was a significant interaction between the year of report and vaccination that smoothed this reduction (p-value<0.001). The reduction was not equal in all age groups, being greater in the 12-18 years age group, which fell from a mean rate of 8.15 per 100,000 person/years in the pre-vaccination period (1992-1998) to 1.4 in the vaccination period (1999-2005). The model predicts the evolution accurately for the group of vaccinated subjects. Negative binomial regression is more appropriate than Poisson regression when observed variance exceeds the observed mean (overdispersed count data), can cause a variable apparently contribute more on the model of what really makes it.

Finite mixture modeling approach for developing crash modification factors in highway safety analysis.

PubMed

Park, Byung-Jung; Lord, Dominique; Wu, Lingtao

2016-10-28

This study aimed to investigate the relative performance of two models (negative binomial (NB) model and two-component finite mixture of negative binomial models (FMNB-2)) in terms of developing crash modification factors (CMFs). Crash data on rural multilane divided highways in California and Texas were modeled with the two models, and crash modification functions (CMFunctions) were derived. The resultant CMFunction estimated from the FMNB-2 model showed several good properties over that from the NB model. First, the safety effect of a covariate was better reflected by the CMFunction developed using the FMNB-2 model, since the model takes into account the differential responsiveness of crash frequency to the covariate. Second, the CMFunction derived from the FMNB-2 model is able to capture nonlinear relationships between covariate and safety. Finally, following the same concept as those for NB models, the combined CMFs of multiple treatments were estimated using the FMNB-2 model. The results indicated that they are not the simple multiplicative of single ones (i.e., their safety effects are not independent under FMNB-2 models). Adjustment Factors (AFs) were then developed. It is revealed that current Highway Safety Manual's method could over- or under-estimate the combined CMFs under particular combination of covariates. Safety analysts are encouraged to consider using the FMNB-2 models for developing CMFs and AFs. Copyright © 2016 Elsevier Ltd. All rights reserved.

nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing data.

PubMed

Zhang, Changsheng; Cai, Hongmin; Huang, Jingying; Song, Yan

2016-09-17

Variations in DNA copy number have an important contribution to the development of several diseases, including autism, schizophrenia and cancer. Single-cell sequencing technology allows the dissection of genomic heterogeneity at the single-cell level, thereby providing important evolutionary information about cancer cells. In contrast to traditional bulk sequencing, single-cell sequencing requires the amplification of the whole genome of a single cell to accumulate enough samples for sequencing. However, the amplification process inevitably introduces amplification bias, resulting in an over-dispersing portion of the sequencing data. Recent study has manifested that the over-dispersed portion of the single-cell sequencing data could be well modelled by negative binomial distributions. We developed a read-depth based method, nbCNV to detect the copy number variants (CNVs). The nbCNV method uses two constraints-sparsity and smoothness to fit the CNV patterns under the assumption that the read signals are negatively binomially distributed. The problem of CNV detection was formulated as a quadratic optimization problem, and was solved by an efficient numerical solution based on the classical alternating direction minimization method. Extensive experiments to compare nbCNV with existing benchmark models were conducted on both simulated data and empirical single-cell sequencing data. The results of those experiments demonstrate that nbCNV achieves superior performance and high robustness for the detection of CNVs in single-cell sequencing data.

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.

PubMed

Harrison, Xavier A

2015-01-01

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.

M-Bonomial Coefficients and Their Identities

ERIC Educational Resources Information Center

Asiru, Muniru A.

2010-01-01

In this note, we introduce M-bonomial coefficients or (M-bonacci binomial coefficients). These are similar to the binomial and the Fibonomial (or Fibonacci-binomial) coefficients and can be displayed in a triangle similar to Pascal's triangle from which some identities become obvious.

Some characteristics of repeated sickness absence

PubMed Central

Ferguson, David

1972-01-01

Ferguson, D. (1972).Brit. J. industr. Med.,29, 420-431. Some characteristics of repeated sickness absence. Several studies have shown that frequency of absence attributed to sickness is not distributed randomly but tends to follow the negative binomial distribution, and this has been taken to support the concept of `proneness' to such absence. Thus, the distribution of sickness absence resembles that of minor injury at work demonstrated over 50 years ago. Because the investigation of proneness to absence does not appear to have been reported by others in Australia, the opportunity was taken, during a wider study of health among telegraphists in a large communications undertaking, to analyse some characteristics of repeated sickness absence. The records of medically certified and uncertified sickness absence of all 769 telegraphists continuously employed in all State capitals over a two-and-a-half-year period were compared with those of 411 clerks and 415 mechanics and, in Sydney, 380 mail sorters and 80 of their supervisors. All telegraphists in Sydney, Melbourne, and Brisbane, and all mail sorters in Sydney, who were available and willing were later medically examined. From their absence pattern repeaters (employees who had had eight or more certified absences in two and a half years) were separated into three types based on a presumptive origin in chance, recurrent disease and symptomatic non-specific disorder. The observed distribution of individual frequency of certified absence over the full two-and-a-half-year period of study followed that expected from the univariate negative binomial, using maximum likelihood estimators, rather than the poisson distribution, in three of the four occupational groups in Sydney. Limited correlational and bivariate analysis supported the interpretation of proneness ascribed to the univariate fit. In the two groups studied, frequency of uncertified absence could not be fitted by the negative binomial, although the numbers of such absences in individuals in successive years were relatively highly correlated. All types of repeater were commoner in Sydney than in the other capital city offices, which differed little from each other. Repeaters were more common among those whose absence was attributed to neurosis, alimentary and upper respiratory tract disorder, and injury. Out of more than 90 health, personal, social, and industrial attributes determined at examination, only two (ethanol habit and adverse attitude to pay) showed any statistically significant association when telegraphist repeaters in Sydney were compared with employees who were rarely absent. Though repeating tended to be associated with chronic or recurrent ill health revealed at examination, one quarter of repeaters had little such ill health and one quarter of rarely absent employees had much. It was concluded that, in the population studied, the fitting of the negative binomial to frequency of certified sickness absence could, in the circumstances of the study, reasonably be given an interpretation of proneness. In that population also repeating varies geographically and occupationally, and is poorly associated with disease and other attributes uncovered at examination, with the exception of the ethanol habit. Repeaters are more often neurotic than employees who are rarely absent but also are more often stable double jobbers. The repeater should be identified for what help may be given him, if needed, otherwise it would seem more profitable to attack those features in work design and organization which influence motivation to come to work. Social factors which predispose to repeated absence are less amenable to modification. PMID:4636662

Traumatic Brain Injury among US Active Duty Military Personnel and Negative Drinking-Related Consequences

PubMed Central

Adams, Rachel Sayko; Larson, Mary Jo; Corrigan, John D.; Ritter, Grant A.; Williams, Thomas V.

2013-01-01

This study used the 2008 Department of Defense Survey of Health Related Behaviors among Active Duty Military Personnel to determine whether traumatic brain injury (TBI) is associated with past year drinking-related consequences. The study sample included currently-drinking personnel who had a combat deployment in the past year and were home for ≥6 months (N = 3,350). Negative binomial regression models were used to assess the incidence rate ratios of consequences, by TBI-level. Experiencing a TBI with a loss of consciousness >20 minutes was significantly associated with consequences independent of demographics, combat exposure, posttraumatic stress disorder, and binge drinking. The study’s limitations are noted. PMID:23869456

Performance and structure of single-mode bosonic codes

NASA Astrophysics Data System (ADS)

Albert, Victor V.; Noh, Kyungjoo; Duivenvoorden, Kasper; Young, Dylan J.; Brierley, R. T.; Reinhold, Philip; Vuillot, Christophe; Li, Linshu; Shen, Chao; Girvin, S. M.; Terhal, Barbara M.; Jiang, Liang

2018-03-01

The early Gottesman, Kitaev, and Preskill (GKP) proposal for encoding a qubit in an oscillator has recently been followed by cat- and binomial-code proposals. Numerically optimized codes have also been proposed, and we introduce codes of this type here. These codes have yet to be compared using the same error model; we provide such a comparison by determining the entanglement fidelity of all codes with respect to the bosonic pure-loss channel (i.e., photon loss) after the optimal recovery operation. We then compare achievable communication rates of the combined encoding-error-recovery channel by calculating the channel's hashing bound for each code. Cat and binomial codes perform similarly, with binomial codes outperforming cat codes at small loss rates. Despite not being designed to protect against the pure-loss channel, GKP codes significantly outperform all other codes for most values of the loss rate. We show that the performance of GKP and some binomial codes increases monotonically with increasing average photon number of the codes. In order to corroborate our numerical evidence of the cat-binomial-GKP order of performance occurring at small loss rates, we analytically evaluate the quantum error-correction conditions of those codes. For GKP codes, we find an essential singularity in the entanglement fidelity in the limit of vanishing loss rate. In addition to comparing the codes, we draw parallels between binomial codes and discrete-variable systems. First, we characterize one- and two-mode binomial as well as multiqubit permutation-invariant codes in terms of spin-coherent states. Such a characterization allows us to introduce check operators and error-correction procedures for binomial codes. Second, we introduce a generalization of spin-coherent states, extending our characterization to qudit binomial codes and yielding a multiqudit code.

Resources predicting positive and negative affect during the experience of stress: a study of older Asian Indian immigrants in the United States.

PubMed

Diwan, Sadhna; Jonnalagadda, Satya S; Balaswamy, Shantha

2004-10-01

Using the life stress model of psychological well-being, in this study we examined risks and resources predicting the occurrence of both positive and negative affect among older Asian Indian immigrants who experienced stressful life events. We collected data through a telephone survey of 226 respondents (aged 50 years and older) in the Southeastern United States. We used hierarchical, negative binomial regression analyses to examine correlates of positive and negative affect. Different coping resources influenced positive and negative affect when stressful life events were controlled for. Being female was a common risk factor for poorer positive and increased negative affect. Satisfaction with friendships and a cultural or ethnic identity that is either bicultural or more American were predictive of greater positive affect. Greater religiosity and increased mastery were resources predicting less negative affect. Cognitive and structural interventions that increase opportunities for social integration, increasing mastery, and addressing spiritual concerns are discussed as ways of coping with stress to improve the well-being of individuals in this immigrant community.

Distribution of chewing lice upon the polygynous peacock Pavo cristatus.

PubMed

Stewart, I R; Clark, F; Petrie, M

1996-04-01

An opportunistic survey of louse distribution upon the peacock Pavo cristatus was undertaken following a cull of 23 birds from an English zoo. After complete skin and feather dissolution, 2 species of lice were retrieved, Goniodes pavonis and Amyrsidea minuta. The distribution of both louse species could be described by a negative binomial model. The significance of this is discussed in relation to transmission dynamics of lice in the atypical avian mating system found in the peacock, which involves no male parental care.

Problems on Divisibility of Binomial Coefficients

ERIC Educational Resources Information Center

Osler, Thomas J.; Smoak, James

2004-01-01

Twelve unusual problems involving divisibility of the binomial coefficients are represented in this article. The problems are listed in "The Problems" section. All twelve problems have short solutions which are listed in "The Solutions" section. These problems could be assigned to students in any course in which the binomial theorem and Pascal's…

Application of binomial-edited CPMG to shale characterization

USGS Publications Warehouse

Washburn, Kathryn E.; Birdwell, Justin E.

2014-01-01

Unconventional shale resources may contain a significant amount of hydrogen in organic solids such as kerogen, but it is not possible to directly detect these solids with many NMR systems. Binomial-edited pulse sequences capitalize on magnetization transfer between solids, semi-solids, and liquids to provide an indirect method of detecting solid organic materials in shales. When the organic solids can be directly measured, binomial-editing helps distinguish between different phases. We applied a binomial-edited CPMG pulse sequence to a range of natural and experimentally-altered shale samples. The most substantial signal loss is seen in shales rich in organic solids while fluids associated with inorganic pores seem essentially unaffected. This suggests that binomial-editing is a potential method for determining fluid locations, solid organic content, and kerogen–bitumen discrimination.

A Three-Parameter Generalisation of the Beta-Binomial Distribution with Applications

DTIC Science & Technology

1987-07-01

York. Rust, R.T. and Klompmaker, J.E. (1981). Improving the estimation procedure for the beta binomial t.v. exposure model. Journal of Marketing ... Research . 18, 442-448. Sabavala, D.J. and Morrison, D.G. (1977). Television show loyalty: a beta- binomial model using recall data. Journal of Advertiuing

Jump-and-return sandwiches: A new family of binomial-like selective inversion sequences with improved performance

NASA Astrophysics Data System (ADS)

Brenner, Tom; Chen, Johnny; Stait-Gardner, Tim; Zheng, Gang; Matsukawa, Shingo; Price, William S.

2018-03-01

A new family of binomial-like inversion sequences, named jump-and-return sandwiches (JRS), has been developed by inserting a binomial-like sequence into a standard jump-and-return sequence, discovered through use of a stochastic Genetic Algorithm optimisation. Compared to currently used binomial-like inversion sequences (e.g., 3-9-19 and W5), the new sequences afford wider inversion bands and narrower non-inversion bands with an equal number of pulses. As an example, two jump-and-return sandwich 10-pulse sequences achieved 95% inversion at offsets corresponding to 9.4% and 10.3% of the non-inversion band spacing, compared to 14.7% for the binomial-like W5 inversion sequence, i.e., they afforded non-inversion bands about two thirds the width of the W5 non-inversion band.

Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data

USGS Publications Warehouse

Counihan, Timothy D.; Chapman, Colin G.

2018-01-01

The goals were to (i) determine if river discharge and water temperature during various early life history stages were predictors of age‐0 White Sturgeon, Acipenser transmontanus, recruitment, and (ii) provide an example of how over‐dispersed catch data, including data with many zero observations, can be used to better understand the effects of regulated rivers on the productivity of depressed sturgeon populations. An information theoretic approach was used to develop and select negative binomial and zero‐inflated negative binomial models that model the relation of age‐0 White Sturgeon survey data from three contiguous Columbia River reservoirs to river discharge and water temperature during spawning, egg incubation, larval, and post‐larval phases. Age‐0 White Sturgeon were collected with small mesh gill nets in The Dalles and John Day reservoirs from 1997 to 2014 and a bottom trawl in Bonneville Reservoir from 1989 to 2006. Results suggest that seasonal river discharge was positively correlated with age‐0 recruitment; notably that discharge, 16 June–31 July was positively correlated to age‐0 recruitment in all three reservoirs. The best approximating models for two of the three reservoirs also suggest that seasonal water temperature may be a determinant of age‐0 recruitment. Our research demonstrates how over‐dispersed catch data can be used to better understand the effects of environmental conditions on sturgeon populations caused by the construction and operation of dams.

Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.

PubMed

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.

[Epidemiology of scrub typhus and influencing factors in Yunnan province, 2006-2013].

PubMed

Sun, Y; Shi, C; Li, X L; Fang, L Q; Cao, W C

2018-01-10

Objective: To understand the epidemiological characteristics of scrub typhu s and influencing factors in Yunnan province, and provide further information for the prevention and control of scrub typhus. Methods: Based on the incidence data of scrub typhus reported in Yunnan from 2006 to 2013, the epidemiological characteristics of scrub typhus were analyzed and related environmental factors were identified with panel negative binomial regression model. Results: A total of 8 980 scrub typhus cases were reported during 2006-2013 in Yunnan. The average annual incidence was 2.46/100 000, with an uptrend observed. Natural focus expansion was found, affecting 71.3% of the counties in 2013. The epidemic mainly occurred in summer and autumn with the incidence peak during July-October. The annual incidence was higher in females than in males. More cases occurred in children and farmers, the proportions of cases in farmers and pre-school aged children showed an obvious increase. Panel negative binomial regression model indicated that the transmission risk of scrub typhus was positive associated with monthly temperature and monthly relative humidity. Furthermore, an "U" pattern between the risk and the increased coverage of cropland and grassland as well as an "inverted-U" pattern between the risk and increased coverage of shrub were observed. Conclusion: It is necessary to strengthen the scrub typhus surveillance in warm and moist areas as well as the areas with high coverage of cropland and grassland in Yunnan, and the health education in children and farmers who are at high risk.

Use of clinical practice guidelines by dentists: findings from the Japanese dental practice-based research network.

PubMed

Kakudate, Naoki; Yokoyama, Yoko; Sumida, Futoshi; Matsumoto, Yuki; Gordan, Valeria V; Gilbert, Gregg H

2017-02-01

The objectives of this study were to: (1) examine differences in the use of dental clinical practice guidelines among Japanese dentists, and (2) identify characteristics associated with the number of guidelines used by participating dentists. We conducted a cross-sectional study consisting of a questionnaire survey in Japan between July 2014 and May 2015. The study queried dentists working in outpatient dental practices who are affiliated with the Dental Practice-Based Research Network Japan (n = 148). They were asked whether they have used each of 15 Japanese dental clinical guidelines. Associations between the number of guidelines used by participants and specific characteristics were analysed via negative binomial regression analysis. The mean number of guidelines used by participating dentists was 2.5 ± 2.9 [standard deviation (SD)]. Rate of use of guidelines showed substantial variation, from 5% to 34% among dentists. The proportion of dentists that used guidelines was the highest among oral medicine specialists, who had the highest proportion for 10 of 15 guidelines. Negative binomial regression analysis identified three factors significantly associated with the number of guidelines used: 'years since graduation from dental school', 'specialty practice' and 'practice busyness'. These results suggest that the use of clinical practice guidelines by Japanese dentists may still be inadequate. Training in the use of the guidelines could be given to dental students as undergraduate education and to young clinicians as continuing education. © 2016 John Wiley & Sons, Ltd.

A preliminary investigation of the relationships between historical crash and naturalistic driving.

PubMed

Pande, Anurag; Chand, Sai; Saxena, Neeraj; Dixit, Vinayak; Loy, James; Wolshon, Brian; Kent, Joshua D

2017-04-01

This paper describes a project that was undertaken using naturalistic driving data collected via Global Positioning System (GPS) devices to demonstrate a proof-of-concept for proactive safety assessments of crash-prone locations. The main hypothesis for the study is that the segments where drivers have to apply hard braking (higher jerks) more frequently might be the "unsafe" segments with more crashes over a long-term. The linear referencing methodology in ArcMap was used to link the GPS data with roadway characteristic data of US Highway 101 northbound (NB) and southbound (SB) in San Luis Obispo, California. The process used to merge GPS data with quarter-mile freeway segments for traditional crash frequency analysis is also discussed in the paper. A negative binomial regression analyses showed that proportion of high magnitude jerks while decelerating on freeway segments (from the driving data) was significantly related with the long-term crash frequency of those segments. A random parameter negative binomial model with uniformly distributed parameter for ADT and a fixed parameter for jerk provided a statistically significant estimate for quarter-mile segments. The results also indicated that roadway curvature and the presence of auxiliary lane are not significantly related with crash frequency for the highway segments under consideration. The results from this exploration are promising since the data used to derive the explanatory variable(s) can be collected using most off-the-shelf GPS devices, including many smartphones. Copyright © 2017 Elsevier Ltd. All rights reserved.

GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

PubMed Central

Di, Yanming; Schafer, Daniel W.; Wilhelm, Larry J.; Fox, Samuel E.; Sullivan, Christopher M.; Curzon, Aron D.; Carrington, James C.; Mockler, Todd C.; Chang, Jeff H.

2011-01-01

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts. PMID:21998647

Revealing Word Order: Using Serial Position in Binomials to Predict Properties of the Speaker

ERIC Educational Resources Information Center

Iliev, Rumen; Smirnova, Anastasia

2016-01-01

Three studies test the link between word order in binomials and psychological and demographic characteristics of a speaker. While linguists have already suggested that psychological, cultural and societal factors are important in choosing word order in binomials, the vast majority of relevant research was focused on general factors and on broadly…

Jump-and-return sandwiches: A new family of binomial-like selective inversion sequences with improved performance.

PubMed

Brenner, Tom; Chen, Johnny; Stait-Gardner, Tim; Zheng, Gang; Matsukawa, Shingo; Price, William S

2018-03-01

A new family of binomial-like inversion sequences, named jump-and-return sandwiches (JRS), has been developed by inserting a binomial-like sequence into a standard jump-and-return sequence, discovered through use of a stochastic Genetic Algorithm optimisation. Compared to currently used binomial-like inversion sequences (e.g., 3-9-19 and W5), the new sequences afford wider inversion bands and narrower non-inversion bands with an equal number of pulses. As an example, two jump-and-return sandwich 10-pulse sequences achieved 95% inversion at offsets corresponding to 9.4% and 10.3% of the non-inversion band spacing, compared to 14.7% for the binomial-like W5 inversion sequence, i.e., they afforded non-inversion bands about two thirds the width of the W5 non-inversion band. Copyright © 2018 Elsevier Inc. All rights reserved.

Negative Urgency, Distress Tolerance, and Substance Abuse Among College Students

PubMed Central

Kaiser, Alison J.; Milich, Richard; Lynam, Donald R.; Charnigo, Richard J.

2012-01-01

Objective Negative affect has been consistently linked with substance use/problems in prior research. The present study sought to build upon these findings by exploring how an individual’s characteristic responding to negative affect impacts substance abuse risk. Trait negative affect was examined in relation to substance abuse outcomes along with two variables tapping into response to negative affect: Distress Tolerance, an individual’s perceived ability to tolerate negative affect, and Negative Urgency, the tendency to act rashly while experiencing distress. Method Participants were 525 first-year college students (48.1% male, 81.1% Caucasian), who completed self-report measures assessing personality traits and alcohol-related problems, and a structured interview assessing past and current substance use. Relations were tested using Zero-Inflated Negative Binomial regression models, and each of the personality variables was tested in a model on its own, and in a model where all three traits were accounted for. Results Negative Urgency emerged as the best predictor, relating to every one of the substance use outcome variables even when trait negative affect and Distress Tolerance were accounted for. Conclusions These findings suggest that Negative Urgency is an important factor to consider in developing prevention and intervention efforts aimed at reducing substance use and problems. PMID:22698894

Cyclical absenteeism among private sector, public sector and self-employed workers.

PubMed

Pfeifer, Christian

2013-03-01

This research note analyzes differences in the number of absent working days and doctor visits and in their cyclicality between private sector, public sector and self-employed workers. For this purpose, I used large-scale German survey data for the years 1995 to 2007 to estimate random effects negative binomial (count data) models. The main findings are as follows. (i) Public sector workers have on average more absent working days than private sector and self-employed workers. Self-employed workers have fewer absent working days and doctor visits than dependent employed workers. (ii) The regional unemployment rate is on average negatively correlated with the number of absent working days among private and public sector workers as well as among self-employed men. The correlations between regional unemployment rate and doctor visits are only significantly negative among private sector workers. Copyright © 2012 John Wiley & Sons, Ltd.

Adjusted Wald Confidence Interval for a Difference of Binomial Proportions Based on Paired Data

ERIC Educational Resources Information Center

Bonett, Douglas G.; Price, Robert M.

2012-01-01

Adjusted Wald intervals for binomial proportions in one-sample and two-sample designs have been shown to perform about as well as the best available methods. The adjusted Wald intervals are easy to compute and have been incorporated into introductory statistics courses. An adjusted Wald interval for paired binomial proportions is proposed here and…

On the p, q-binomial distribution and the Ising model

NASA Astrophysics Data System (ADS)

Lundow, P. H.; Rosengren, A.

2010-08-01

We employ p, q-binomial coefficients, a generalisation of the binomial coefficients, to describe the magnetisation distributions of the Ising model. For the complete graph this distribution corresponds exactly to the limit case p = q. We apply our investigation to the simple d-dimensional lattices for d = 1, 2, 3, 4, 5 and fit p, q-binomial distributions to our data, some of which are exact but most are sampled. For d = 1 and d = 5, the magnetisation distributions are remarkably well-fitted by p,q-binomial distributions. For d = 4 we are only slightly less successful, while for d = 2, 3 we see some deviations (with exceptions!) between the p, q-binomial and the Ising distribution. However, at certain temperatures near T c the statistical moments of the fitted distribution agree with the moments of the sampled data within the precision of sampling. We begin the paper by giving results of the behaviour of the p, q-distribution and its moment growth exponents given a certain parameterisation of p, q. Since the moment exponents are known for the Ising model (or at least approximately for d = 3) we can predict how p, q should behave and compare this to our measured p, q. The results speak in favour of the p, q-binomial distribution's correctness regarding its general behaviour in comparison to the Ising model. The full extent to which they correctly model the Ising distribution, however, is not settled.

Tobit analysis of vehicle accident rates on interstate highways.

PubMed

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.

Assessment of some important factors affecting the singing-ground survey

USGS Publications Warehouse

Tautin, J.

1982-01-01

A brief history of the procedures used to analyze singing-ground survey data is outlined. Some weaknesses associated with the analytical procedures are discussed, and preliminary results of efforts to improve the procedures are presented. The most significant finding to date is that counts made by new observers need not be omitted when calculating an index of the woodcock population. Also, the distribution of woodcock heard singing, with respect to time after sunset, affirms the appropriateness of recommended starting times for counting woodcock. Woodcock count data fit the negative binomial probability distribution.

Population Characteristics and the Nature of Egg Shells of two Phthirapteran Species Parasitizing Indian Cattle Egrets

PubMed Central

Ahmad, Aftab; Khan, Vikram; Badola, Smita; Arya, Gaurav; Bansal, Nayanci; Saxena, A. K.

2010-01-01

The prevalence, intensities of infestation, range of infestation and population composition of two phthirapteran species, Ardeicola expallidus Blagoveshtchensky (Phthiraptera: Philopteridae) and Ciconiphilus decimfasciatus Boisduval and Lacordaire (Menoponidae) on seventy cattle egrets were recorded during August 2004 to March 2005, in India. The frequency distribution patterns of both the species were skewed but did not correspond to the negative binomial model. The oviposition sites, egg laying patterns and the nature of the eggs of the two species were markedly different. PMID:21067416

Neighborhood educational disparities in active commuting among women: the effect of distance between the place of residence and the place of work/study (an ACTI-Cités study).

PubMed

Perchoux, Camille; Nazare, Julie-Anne; Benmarhnia, Tarik; Salze, Paul; Feuillet, Thierry; Hercberg, Serge; Hess, Franck; Menai, Mehdi; Weber, Christiane; Charreire, Hélène; Enaux, Christophe; Oppert, Jean-Michel; Simon, Chantal

2017-06-12

Active transportation has been associated with favorable health outcomes. Previous research highlighted the influence of neighborhood educational level on active transportation. However, little is known regarding the effect of commuting distance on social disparities in active commuting. In this regard, women have been poorly studied. The objective of this paper was to evaluate the relationship between neighborhood educational level and active commuting, and to assess whether the commuting distance modifies this relationship in adult women. This cross-sectional study is based on a subsample of women from the Nutrinet-Santé web-cohort (N = 1169). Binomial, log-binomial and negative binomial regressions were used to assess the associations between neighborhood education level and (i) the likelihood of reporting any active commuting time, and (ii) the share of commuting time made by active transportation modes. Potential effect measure modification of distance to work on the previous associations was assessed both on the additive and the multiplicative scales. Neighborhood education level was positively associated with the probability of reporting any active commuting time (relative risk = 1.774; p < 0.05) and the share of commuting time spent active (relative risk = 1.423; p < 0.05). The impact of neighborhood education was greater at long distances to work for both outcomes. Our results suggest that neighborhood educational disparities in active commuting tend to increase with commuting distance among women. Further research is needed to provide geographically driven guidance for health promotion intervention aiming at reducing disparities in active transportation among socioeconomic groups.

C-5A Cargo Deck Low-Frequency Vibration Environment

DTIC Science & Technology

1975-02-01

SAMPLE VIBRATION CALCULATIONS 13 1. Normal Distribution 13 2. Binomial Distribution 15 IV CONCLUSIONS 17 -! V REFERENCES 18 t: FEiCENDIJJ PAGS 2LANKNOT...Calculation for Binomial Distribution 108 (Vertical Acceleration, Right Rear Cargo Deck) xi I. INTRODUCTION The availability of large transport...the end of taxi. These peaks could then be used directly to compile the probability of occurrence of specific values of acceleration using the binomial

Impact of cigarette smoking on utilization of nursing home services.

PubMed

Warner, Kenneth E; McCammon, Ryan J; Fries, Brant E; Langa, Kenneth M

2013-11-01

Few studies have examined the effects of smoking on nursing home utilization, generally using poor data on smoking status. No previous study has distinguished utilization for recent from long-term quitters. Using the Health and Retirement Study, we assessed nursing home utilization by never-smokers, long-term quitters (quit >3 years), recent quitters (quit ≤3 years), and current smokers. We used logistic regression to evaluate the likelihood of a nursing home admission. For those with an admission, we used negative binomial regression on the number of nursing home nights. Finally, we employed zero-inflated negative binomial regression to estimate nights for the full sample. Controlling for other variables, compared with never-smokers, long-term quitters have an odds ratio (OR) for nursing home admission of 1.18 (95% CI: 1.07-1.2), current smokers 1.39 (1.23-1.57), and recent quitters 1.55 (1.29-1.87). The probability of admission rises rapidly with age and is lower for African Americans and Hispanics, more affluent respondents, respondents with a spouse present in the home, and respondents with a living child. Given admission, smoking status is not associated with length of stay (LOS). LOS is longer for older respondents and women and shorter for more affluent respondents and those with spouses present. Compared with otherwise identical never-smokers, former and current smokers have a significantly increased risk of nursing home admission. That recent quitters are at greatest risk of admission is consistent with evidence that many stop smoking because they are sick, often due to smoking.

Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model.

PubMed

Sun, Xiaoxiao; Dalpiaz, David; Wu, Di; S Liu, Jun; Zhong, Wenxuan; Ma, Ping

2016-08-26

Accurate identification of differentially expressed (DE) genes in time course RNA-Seq data is crucial for understanding the dynamics of transcriptional regulatory network. However, most of the available methods treat gene expressions at different time points as replicates and test the significance of the mean expression difference between treatments or conditions irrespective of time. They thus fail to identify many DE genes with different profiles across time. In this article, we propose a negative binomial mixed-effect model (NBMM) to identify DE genes in time course RNA-Seq data. In the NBMM, mean gene expression is characterized by a fixed effect, and time dependency is described by random effects. The NBMM is very flexible and can be fitted to both unreplicated and replicated time course RNA-Seq data via a penalized likelihood method. By comparing gene expression profiles over time, we further classify the DE genes into two subtypes to enhance the understanding of expression dynamics. A significance test for detecting DE genes is derived using a Kullback-Leibler distance ratio. Additionally, a significance test for gene sets is developed using a gene set score. Simulation analysis shows that the NBMM outperforms currently available methods for detecting DE genes and gene sets. Moreover, our real data analysis of fruit fly developmental time course RNA-Seq data demonstrates the NBMM identifies biologically relevant genes which are well justified by gene ontology analysis. The proposed method is powerful and efficient to detect biologically relevant DE genes and gene sets in time course RNA-Seq data.

Robust inference in the negative binomial regression model with an application to falls data.

PubMed

Aeberhard, William H; Cantoni, Eva; Heritier, Stephane

2014-12-01

A popular way to model overdispersed count data, such as the number of falls reported during intervention studies, is by means of the negative binomial (NB) distribution. Classical estimating methods are well-known to be sensitive to model misspecifications, taking the form of patients falling much more than expected in such intervention studies where the NB regression model is used. We extend in this article two approaches for building robust M-estimators of the regression parameters in the class of generalized linear models to the NB distribution. The first approach achieves robustness in the response by applying a bounded function on the Pearson residuals arising in the maximum likelihood estimating equations, while the second approach achieves robustness by bounding the unscaled deviance components. For both approaches, we explore different choices for the bounding functions. Through a unified notation, we show how close these approaches may actually be as long as the bounding functions are chosen and tuned appropriately, and provide the asymptotic distributions of the resulting estimators. Moreover, we introduce a robust weighted maximum likelihood estimator for the overdispersion parameter, specific to the NB distribution. Simulations under various settings show that redescending bounding functions yield estimates with smaller biases under contamination while keeping high efficiency at the assumed model, and this for both approaches. We present an application to a recent randomized controlled trial measuring the effectiveness of an exercise program at reducing the number of falls among people suffering from Parkinsons disease to illustrate the diagnostic use of such robust procedures and their need for reliable inference. © 2014, The International Biometric Society.

Association between month of birth and melanoma risk: fact or fiction?

PubMed

Fiessler, Cornelia; Pfahlberg, Annette B; Keller, Andrea K; Radespiel-Tröger, Martin; Uter, Wolfgang; Gefeller, Olaf

2017-04-01

Evidence on the effect of ultraviolet radiation (UVR) exposure in infancy on melanoma risk in later life is scarce. Three recent studies suggest that people born in spring carry a higher melanoma risk. Our study aimed at verifying whether such a seasonal pattern of melanoma risk actually exists. Data from the population-based Cancer Registry Bavaria (CRB) on the birth months of 28 374 incident melanoma cases between 2002 and 2012 were analysed and compared with data from the Bavarian State Office for Statistics and Data Processing on the birth month distribution in the Bavarian population. Crude and adjusted analyses using negative binomial regression models were performed in the total study group and supplemented by several subgroup analyses. In the crude analysis, the birth months March-May were over-represented among melanoma cases. Negative binomial regression models adjusted only for sex and birth year revealed a seasonal association between melanoma risk and birth month with 13-21% higher relative incidence rates for March, April and May compared with the reference December. However, after additionally adjusting for the birth month distribution of the Bavarian population, these risk estimates decreased markedly and no association with the birth month was observed any more. Similar results emerged in all subgroup analyses. Our large registry-based study provides no evidence that people born in spring carry a higher risk for developing melanoma in later life and thus lends no support to the hypothesis of higher UVR susceptibility during the first months of life. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Dental Caries and Enamel Defects in Very Low Birth Weight Adolescents

PubMed Central

Nelson, S.; Albert, J.M.; Lombardi, G.; Wishnek, S.; Asaad, G.; Kirchner, H.L.; Singer, L.T.

2011-01-01

Objectives The purpose of this study was to examine developmental enamel defects and dental caries in very low birth weight adolescents with high risk (HR-VLBW) and low risk (LR-VLBW) compared to full-term (term) adolescents. Methods The sample consisted of 224 subjects (80 HR-VLBW, 59 LR-VLBW, 85 term adolescents) recruited from an ongoing longitudinal study. Sociodemographic and medical information was available from birth. Dental examination of the adolescent at the 14-year visit included: enamel defects (opacity and hypoplasia); decayed, missing, filled teeth of incisors and molars (DMFT-IM) and of overall permanent teeth (DMFT); Simplified Oral Hygiene Index for debris/calculus on teeth, and sealant presence. A caregiver questionnaire completed simultaneously assessed dental behavior, access, insurance status and prevention factors. Hierarchical analysis utilized the zero-inflated negative binomial model and zero-inflated Poisson model. Results The zero-inflated negative binomial model controlling for sociodemographic variables indicated that the LR-VLBW group had an estimated 75% increase (p < 0.05) in number of demarcated opacities in the incisors and first molar teeth compared to the term group. Hierarchical modeling indicated that demarcated opacities were a significant predictor of DMFT-IM after control for relevant covariates. The term adolescents had significantly increased DMFT-IM and DMFT scores compared to the LR-VLBW adolescents. Conclusion LR-VLBW was a significant risk factor for increased enamel defects in the permanent incisors and first molars. Term children had increased caries compared to the LR-VLBW group. The effect of birth group and enamel defects on caries has to be investigated longitudinally from birth. PMID:20975268

Hopelessness as a Predictor of Suicide Ideation in Depressed Male and Female Adolescent Youth.

PubMed

Wolfe, Kristin L; Nakonezny, Paul A; Owen, Victoria J; Rial, Katherine V; Moorehead, Alexandra P; Kennard, Beth D; Emslie, Graham J

2017-12-21

We examined hopelessness as a predictor of suicide ideation in depressed youth after acute medication treatment. A total of 158 depressed adolescents were administered the Children's Depression Rating Scale-Revised (CDRS-R) and Columbia Suicide Severity Rating Scale (C-SSRS) as part of a larger battery at baseline and at weekly visits across 6 weeks of acute fluoxetine treatment. The Beck Hopelessness Scale (BHS) was administered at baseline and week 6. A negative binomial regression model via a generalized estimating equation analysis of repeated measures was used to estimate suicide ideation over the 6 weeks of acute treatment from baseline measure of hopelessness. Depression severity and gender were included as covariates in the model. The negative binomial analysis was also conducted separately for the sample of males and females (in a gender-stratified analysis). Mean CDRS-R total scores were 60.30 ± 8.93 at baseline and 34.65 ± 10.41 at week 6. Mean baseline and week 6 BHS scores were 9.57 ± 5.51 and 5.59 ± 5.38, respectively. Per the C-SSRS, 43.04% and 83.54% reported having no suicide ideation at baseline and at week 6, respectively. The analyses revealed that baseline hopelessness was positively related to suicide ideation over treatment (p = .0027), independent of changes in depression severity. This significant finding persisted only for females (p = .0024). These results indicate the importance of early identification of hopelessness. © 2017 The American Association of Suicidology.

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model.

PubMed

Kim, Dae-Hwan; Ramjan, Lucie M; Mak, Kwok-Kei

2016-01-01

Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea. A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience. Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes. Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

The Effect of Sharrows, Painted Bicycle Lanes and Physically Protected Paths on the Severity of Bicycle Injuries Caused by Motor Vehicles.

PubMed

Wall, Stephen P; Lee, David C; Frangos, Spiros G; Sethi, Monica; Heyer, Jessica H; Ayoung-Chee, Patricia; DiMaggio, Charles J

2016-01-01

We conducted individual and ecologic analyses of prospectively collected data from 839 injured bicyclists who collided with motorized vehicles and presented to Bellevue Hospital, an urban Level-1 trauma center in New York City, from December 2008 to August 2014. Variables included demographics, scene information, rider behaviors, bicycle route availability, and whether the collision occurred before the road segment was converted to a bicycle route. We used negative binomial modeling to assess the risk of injury occurrence following bicycle path or lane implementation. We dichotomized U.S. National Trauma Data Bank Injury Severity Scores (ISS) into none/mild (0-8) versus moderate, severe, or critical (>8) and used adjusted multivariable logistic regression to model the association of ISS with collision proximity to sharrows (i.e., bicycle lanes designated for sharing with cars), painted bicycle lanes, or physically protected paths. Negative binomial modeling of monthly counts, while adjusting for pedestrian activity, revealed that physically protected paths were associated with 23% fewer injuries. Painted bicycle lanes reduced injury risk by nearly 90% (IDR 0.09, 95% CI 0.02-0.33). Holding all else equal, compared to no bicycle route, a bicycle injury nearby sharrows was nearly twice as likely to be moderate, severe, or critical (adjusted odds ratio 1.94; 95% confidence interval (CI) 0.91-4.15). Painted bicycle lanes and physically protected paths were 1.52 (95% CI 0.85-2.71) and 1.66 (95% CI 0.85-3.22) times as likely to be associated with more than mild injury respectively.

Generalized seasonal autoregressive integrated moving average models for count data with application to malaria time series with low case numbers.

PubMed

Briët, Olivier J T; Amerasinghe, Priyanie H; Vounatsou, Penelope

2013-01-01

With the renewed drive towards malaria elimination, there is a need for improved surveillance tools. While time series analysis is an important tool for surveillance, prediction and for measuring interventions' impact, approximations by commonly used Gaussian methods are prone to inaccuracies when case counts are low. Therefore, statistical methods appropriate for count data are required, especially during "consolidation" and "pre-elimination" phases. Generalized autoregressive moving average (GARMA) models were extended to generalized seasonal autoregressive integrated moving average (GSARIMA) models for parsimonious observation-driven modelling of non Gaussian, non stationary and/or seasonal time series of count data. The models were applied to monthly malaria case time series in a district in Sri Lanka, where malaria has decreased dramatically in recent years. The malaria series showed long-term changes in the mean, unstable variance and seasonality. After fitting negative-binomial Bayesian models, both a GSARIMA and a GARIMA deterministic seasonality model were selected based on different criteria. Posterior predictive distributions indicated that negative-binomial models provided better predictions than Gaussian models, especially when counts were low. The G(S)ARIMA models were able to capture the autocorrelation in the series. G(S)ARIMA models may be particularly useful in the drive towards malaria elimination, since episode count series are often seasonal and non-stationary, especially when control is increased. Although building and fitting GSARIMA models is laborious, they may provide more realistic prediction distributions than do Gaussian methods and may be more suitable when counts are low.

Dispersion models and sampling of cacao mirid bug Sahlbergella singularis (Hemiptera: Miridae) on Theobroma Cacao in southern Cameroon.

PubMed

Bisseleua, D H B; Vidal, Stefan

2011-02-01

The spatio-temporal distribution of Sahlbergella singularis Haglung, a major pest of cacao trees (Theobroma cacao) (Malvaceae), was studied for 2 yr in traditional cacao forest gardens in the humid forest area of southern Cameroon. The first objective was to analyze the dispersion of this insect on cacao trees. The second objective was to develop sampling plans based on fixed levels of precision for estimating S. singularis populations. The following models were used to analyze the data: Taylor's power law, Iwao's patchiness regression, the Nachman model, and the negative binomial distribution. Our results document that Taylor's power law was a better fit for the data than the Iwao and Nachman models. Taylor's b and Iwao's β were both significantly >1, indicating that S. singularis aggregated on specific trees. This result was further supported by the calculated common k of 1.75444. Iwao's α was significantly <0, indicating that the basic distribution component of S. singularis was the individual insect. Comparison of negative binomial (NBD) and Nachman models indicated that the NBD model was appropriate for studying S. singularis distribution. Optimal sample sizes for fixed precision levels of 0.10, 0.15, and 0.25 were estimated with Taylor's regression coefficients. Required sample sizes increased dramatically with increasing levels of precision. This is the first study on S. singularis dispersion in cacao plantations. Sampling plans, presented here, should be a tool for research on population dynamics and pest management decisions of mirid bugs on cacao. © 2011 Entomological Society of America

Generalized Seasonal Autoregressive Integrated Moving Average Models for Count Data with Application to Malaria Time Series with Low Case Numbers

PubMed Central

Briët, Olivier J. T.; Amerasinghe, Priyanie H.; Vounatsou, Penelope

2013-01-01

Introduction With the renewed drive towards malaria elimination, there is a need for improved surveillance tools. While time series analysis is an important tool for surveillance, prediction and for measuring interventions’ impact, approximations by commonly used Gaussian methods are prone to inaccuracies when case counts are low. Therefore, statistical methods appropriate for count data are required, especially during “consolidation” and “pre-elimination” phases. Methods Generalized autoregressive moving average (GARMA) models were extended to generalized seasonal autoregressive integrated moving average (GSARIMA) models for parsimonious observation-driven modelling of non Gaussian, non stationary and/or seasonal time series of count data. The models were applied to monthly malaria case time series in a district in Sri Lanka, where malaria has decreased dramatically in recent years. Results The malaria series showed long-term changes in the mean, unstable variance and seasonality. After fitting negative-binomial Bayesian models, both a GSARIMA and a GARIMA deterministic seasonality model were selected based on different criteria. Posterior predictive distributions indicated that negative-binomial models provided better predictions than Gaussian models, especially when counts were low. The G(S)ARIMA models were able to capture the autocorrelation in the series. Conclusions G(S)ARIMA models may be particularly useful in the drive towards malaria elimination, since episode count series are often seasonal and non-stationary, especially when control is increased. Although building and fitting GSARIMA models is laborious, they may provide more realistic prediction distributions than do Gaussian methods and may be more suitable when counts are low. PMID:23785448

Individual-level exposure to disaster, neighborhood environmental characteristics, and their independent and combined associations with depressive symptoms in women.

PubMed

Gaston, Symielle A; Volaufova, Julia; Peters, Edward S; Ferguson, Tekeda F; Robinson, William T; Nugent, Nicole; Trapido, Edward J; Rung, Ariane L

2017-09-01

The severity of the stress response to experiencing disaster depends on individual exposure and background stress prior to the event. To date, there is limited research on the interaction between neighborhood environmental stress and experiencing an oil spill, and their effects on depression. The objective of the current study was to assess if the association between exposure to the Deepwater Horizon Oil Spill (DHOS) and depressive symptoms varied by neighborhood characteristics. US Census data (2010) and longitudinal data collected in two waves (2012-2014 and 2014-2016) from female residents [N = 889 (Wave I), 737 (Wave II)] of an area highly affected by the DHOS were analyzed. Multilevel and individual-level negative binomial regressions were performed to estimate associations with depressive symptoms in both waves. An interaction term was included to estimate effect modification of the association between DHOS exposure and depressive symptoms by neighborhood characteristics. Generalized estimating equations were applied to the negative binomial regression testing longitudinal associations. Census tract-level neighborhood characteristics were not associated with depressive symptoms. Exposure to the DHOS and neighborhood physical disorder were associated with depressive symptoms cross-sectionally. There was no evidence of effect modification; however, physical/environmental exposure to the DHOS was associated with increased depressive symptoms only among women living in areas with physical disorder. Exposure to the DHOS remained associated with depressive symptoms over time. Findings support the enduring consequences of disaster exposure on depressive symptoms in women and identify potential targets for post-disaster intervention based on residential characteristics.

Linking parasite populations in hosts to parasite populations in space through Taylor's law and the negative binomial distribution

PubMed Central

Poulin, Robert; Lagrue, Clément

2017-01-01

The spatial distribution of individuals of any species is a basic concern of ecology. The spatial distribution of parasites matters to control and conservation of parasites that affect human and nonhuman populations. This paper develops a quantitative theory to predict the spatial distribution of parasites based on the distribution of parasites in hosts and the spatial distribution of hosts. Four models are tested against observations of metazoan hosts and their parasites in littoral zones of four lakes in Otago, New Zealand. These models differ in two dichotomous assumptions, constituting a 2 × 2 theoretical design. One assumption specifies whether the variance function of the number of parasites per host individual is described by Taylor's law (TL) or the negative binomial distribution (NBD). The other assumption specifies whether the numbers of parasite individuals within each host in a square meter of habitat are independent or perfectly correlated among host individuals. We find empirically that the variance–mean relationship of the numbers of parasites per square meter is very well described by TL but is not well described by NBD. Two models that posit perfect correlation of the parasite loads of hosts in a square meter of habitat approximate observations much better than two models that posit independence of parasite loads of hosts in a square meter, regardless of whether the variance–mean relationship of parasites per host individual obeys TL or NBD. We infer that high local interhost correlations in parasite load strongly influence the spatial distribution of parasites. Local hotspots could influence control and conservation of parasites. PMID:27994156

Sickness absence and psychosocial job quality: an analysis from a longitudinal survey of working Australians, 2005-2012.

PubMed

Milner, Allison; Butterworth, Peter; Bentley, Rebecca; Kavanagh, Anne M; LaMontagne, Anthony D

2015-05-15

Sickness absence is associated with adverse health, organizational, and societal outcomes. Using data from a longitudinal cohort study of working Australians (the Household, Income and Labour Dynamics in Australia (HILDA) Survey), we examined the relationship between changes in individuals' overall psychosocial job quality and variation in sickness absence. The outcome variables were paid sickness absence (yes/no) and number of days of paid sickness absence in the past year (2005-2012). The main exposure variable was psychosocial job quality, measured using a psychosocial job quality index (levels of job control, demands and complexity, insecurity, and perceptions of unfair pay). Analysis was conducted using longitudinal fixed-effects logistic regression models and negative binomial regression models. There was a dose-response relationship between the number of psychosocial job stressors reported by an individual and the odds of paid sickness absence (1 adversity: odds ratio (OR) = 1.26, 95% confidence interval (CI): 1.09, 1.45 (P = 0.002); 2 adversities: OR = 1.28, 95% CI: 1.09, 1.51 (P = 0.002); ≥3 adversities: OR = 1.58, 95% CI: 1.29, 1.94 (P < 0.001)). The negative binomial regression models also indicated that respondents reported a greater number of days of sickness absence in response to worsening psychosocial job quality. These results suggest that workplace interventions aiming to improve the quality of work could help reduce sickness absence. © 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.

Probabilistic assessment of precipitation-triggered landslides using historical records of landslide occurence, Seattle, Washington

USGS Publications Warehouse

Coe, J.A.; Michael, J.A.; Crovelli, R.A.; Savage, W.Z.; Laprade, W.T.; Nashem, W.D.

2004-01-01

Ninety years of historical landslide records were used as input to the Poisson and binomial probability models. Results from these models show that, for precipitation-triggered landslides, approximately 9 percent of the area of Seattle has annual exceedance probabilities of 1 percent or greater. Application of the Poisson model for estimating the future occurrence of individual landslides results in a worst-case scenario map, with a maximum annual exceedance probability of 25 percent on a hillslope near Duwamish Head in West Seattle. Application of the binomial model for estimating the future occurrence of a year with one or more landslides results in a map with a maximum annual exceedance probability of 17 percent (also near Duwamish Head). Slope and geology both play a role in localizing the occurrence of landslides in Seattle. A positive correlation exists between slope and mean exceedance probability, with probability tending to increase as slope increases. Sixty-four percent of all historical landslide locations are within 150 m (500 ft, horizontal distance) of the Esperance Sand/Lawton Clay contact, but within this zone, no positive or negative correlation exists between exceedance probability and distance to the contact.

Binomial Baseball.

ERIC Educational Resources Information Center

Levin, Eugene M.

1981-01-01

Student access to programmable calculators and computer terminals, coupled with a familiarity with baseball, provides opportunities to enhance their understanding of the binomial distribution and other aspects of analysis. (MP)

Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods.

PubMed

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.

New Class of Quantum Error-Correcting Codes for a Bosonic Mode

NASA Astrophysics Data System (ADS)

Michael, Marios H.; Silveri, Matti; Brierley, R. T.; Albert, Victor V.; Salmilehto, Juha; Jiang, Liang; Girvin, S. M.

2016-07-01

We construct a new class of quantum error-correcting codes for a bosonic mode, which are advantageous for applications in quantum memories, communication, and scalable computation. These "binomial quantum codes" are formed from a finite superposition of Fock states weighted with binomial coefficients. The binomial codes can exactly correct errors that are polynomial up to a specific degree in bosonic creation and annihilation operators, including amplitude damping and displacement noise as well as boson addition and dephasing errors. For realistic continuous-time dissipative evolution, the codes can perform approximate quantum error correction to any given order in the time step between error detection measurements. We present an explicit approximate quantum error recovery operation based on projective measurements and unitary operations. The binomial codes are tailored for detecting boson loss and gain errors by means of measurements of the generalized number parity. We discuss optimization of the binomial codes and demonstrate that by relaxing the parity structure, codes with even lower unrecoverable error rates can be achieved. The binomial codes are related to existing two-mode bosonic codes, but offer the advantage of requiring only a single bosonic mode to correct amplitude damping as well as the ability to correct other errors. Our codes are similar in spirit to "cat codes" based on superpositions of the coherent states but offer several advantages such as smaller mean boson number, exact rather than approximate orthonormality of the code words, and an explicit unitary operation for repumping energy into the bosonic mode. The binomial quantum codes are realizable with current superconducting circuit technology, and they should prove useful in other quantum technologies, including bosonic quantum memories, photonic quantum communication, and optical-to-microwave up- and down-conversion.

Quantifying the safety effects of horizontal curves on two-way, two-lane rural roads.

PubMed

Gooch, Jeffrey P; Gayah, Vikash V; Donnell, Eric T

2016-07-01

The objective of this study is to quantify the safety performance of horizontal curves on two-way, two-lane rural roads relative to tangent segments. Past research is limited by small samples sizes, outdated statistical evaluation methods, and unreported standard errors. This study overcomes these drawbacks by using the propensity scores-potential outcomes framework. The impact of adjacent curves on horizontal curve safety is also explored using a cross-sectional regression model of only horizontal curves. The models estimated in the present study used eight years of crash data (2005-2012) obtained from over 10,000 miles of state-owned two-lane rural roads in Pennsylvania. These data included information on roadway geometry (e.g., horizontal curvature, lane width, and shoulder width), traffic volume, roadside hazard rating, and the presence of various low-cost safety countermeasures (e.g., centerline and shoulder rumble strips, curve and intersection warning pavement markings, and aggressive driving pavement dots). Crash prediction is performed by means of mixed effects negative binomial regression using the explanatory variables noted previously, as well as attributes of adjacent horizontal curves. The results indicate that both the presence of a horizontal curve and its degree of curvature must be considered when predicting the frequency of total crashes on horizontal curves. Both are associated with an increase in crash frequency, which is consistent with previous findings in the literature. Mixed effects negative binomial regression models for total crash frequency on horizontal curves indicate that the distance to adjacent curves is not statistically significant. However, the degree of curvature of adjacent curves in close proximity (within 0.75 miles) was found to be statistically significant and negatively correlated with crash frequency on the subject curve. This is logical, as drivers exiting a sharp curve are likely to be driving slower and with more awareness as they approach the next horizontal curve. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

PubMed

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.

Speech-discrimination scores modeled as a binomial variable.

PubMed

Thornton, A R; Raffin, M J

1978-09-01

Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.

Possibility and Challenges of Conversion of Current Virus Species Names to Linnaean Binomials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Postler, Thomas S.; Clawson, Anna N.; Amarasinghe, Gaya K.

Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authorsmore » of this article expected when conceiving the experiment. [Arenaviridae; binomials; ICTV; International Committee on Taxonomy of Viruses; Mononegavirales; virus nomenclature; virus taxonomy.]« less

Charged particle multiplicities in deep inelastic scattering at HERA

NASA Astrophysics Data System (ADS)

Aid, S.; Anderson, M.; Andreev, V.; Andrieu, B.; Appuhn, R.-D.; Babaev, A.; Bähr, J.; Bán, J.; Ban, Y.; Baranov, P.; Barrelet, E.; Barschke, R.; Bartel, W.; Barth, M.; Bassler, U.; Beck, H. P.; Behrend, H.-J.; Belousov, A.; Berger, Ch.; Bernardi, G.; Bertrand-Coremans, G.; Besançon, M.; Beyer, R.; Biddulph, P.; Bispham, P.; Bizot, J. C.; Blobel, V.; Borras, K.; Botterweck, F.; Boudry, V.; Braemer, A.; Braunschweig, W.; Brisson, V.; Bruel, P.; Bruncko, D.; Brune, C.; Buchholz, R.; Büngener, L.; Bürger, J.; Büsser, F. W.; Buniatian, A.; Burke, S.; Burton, M. J.; Calvet, D.; Campbell, A. J.; Carli, T.; Charlet, M.; Clarke, D.; Clegg, A. B.; Clerbaux, B.; Cocks, S.; Contreras, J. G.; Cormack, C.; Coughlan, J. A.; Courau, A.; Cousinou, M.-C.; Cozzika, G.; Criegee, L.; Cussans, D. G.; Cvach, J.; Dagoret, S.; Dainton, J. B.; Dau, W. D.; Daum, K.; David, M.; Davis, C. L.; Delcourt, B.; de Roeck, A.; de Wolf, E. A.; Dirkmann, M.; Dixon, P.; di Nezza, P.; Dlugosz, W.; Dollfus, C.; Dowell, J. D.; Dreis, H. B.; Droutskoi, A.; Dünger, O.; Duhm, H.; Ebert, J.; Ebert, T. R.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Eisenhandler, E.; Elsen, E.; Erdmann, M.; Erdmann, W.; Evrard, E.; Fahr, A. B.; Favart, L.; Fedotov, A.; Feeken, D.; Felst, R.; Feltesse, J.; Ferencei, J.; Ferrarotto, F.; Flamm, K.; Fleischer, M.; Flieser, M.; Flügge, G.; Fomenko, A.; Fominykh, B.; Formánek, J.; Foster, J. M.; Franke, G.; Fretwurst, E.; Gabathuler, E.; Gabathuler, K.; Gaede, F.; Garvey, J.; Gayler, J.; Gebauer, M.; Genzel, H.; Gerhards, R.; Glazov, A.; Goerlach, U.; Goerlich, L.; Gogitidze, N.; Goldberg, M.; Goldner, D.; Golec-Biernat, K.; Gonzalez-Pineiro, B.; Gorelov, I.; Grab, C.; Grässler, H.; Greenshaw, T.; Griffiths, R. K.; Grindhammer, G.; Gruber, A.; Gruber, C.; Haack, J.; Hadig, T.; Haidt, D.; Hajduk, L.; Hampel, M.; Haynes, W. J.; Heinzelmann, G.; Henderson, R. C. W.; Henschel, H.; Herynek, I.; Hess, M. F.; Hewitt, K.; Hildesheim, W.; Hiller, K. H.; Hilton, C. D.; Hladký, J.; Hoeger, K. C.; Höppner, M.; Hoffmann, D.; Holtom, T.; Horisberger, R.; Hudgson, V. L.; Hütte, M.; Ibbotson, M.; Itterbeck, H.; Jacholkowska, A.; Jacobsson, C.; Jaffre, M.; Janoth, J.; Jansen, T.; Jönsson, L.; Johnson, D. P.; Jung, H.; Kalmus, P. I. P.; Kander, M.; Kant, D.; Kaschowitz, R.; Kathage, U.; Katzy, J.; Kaufmann, H. H.; Kaufmann, O.; Kazarian, S.; Kenyon, I. R.; Kermiche, S.; Keuker, C.; Kiesling, C.; Klein, M.; Kleinwort, C.; Knies, G.; Köhler, T.; Köhne, J. H.; Kolanoski, H.; Kole, F.; Kolya, S. D.; Korbel, V.; Korn, M.; Kostka, P.; Kotelnikov, S. K.; Krämerkämper, T.; Krasny, M. W.; Krehbiel, H.; Krücker, D.; Küster, H.; Kuhlen, M.; Kurča, T.; Kurzhöfer, J.; Lacour, D.; Laforge, B.; Lander, R.; Landon, M. P. J.; Lange, W.; Langenegger, U.; Laporte, J.-F.; Lebedev, A.; Lehner, F.; Levonian, S.; Lindström, G.; Lindstroem, M.; Link, J.; Linsel, F.; Lipinski, J.; List, B.; Lobo, G.; Lomas, J. W.; Lopez, G. C.; Lubimov, V.; Lüke, D.; Magnussen, N.; Malinovski, E.; Mani, S.; Maraček, R.; Marage, P.; Marks, J.; Marshall, R.; Martens, J.; Martin, G.; Martin, R.; Martyn, H.-U.; Martyniak, J.; Mavroidis, T.; Maxfield, S. J.; McMahon, S. J.; Mehta, A.; Meier, K.; Meyer, A.; Meyer, A.; Meyer, H.; Meyer, J.; Meyer, P.-O.; Migliori, A.; Mikocki, S.; Milstead, D.; Moeck, J.; Moreau, F.; Morris, J. V.; Mroczko, E.; Müller, D.; Müller, G.; Müller, K.; Müller, M.; Murín, P.; Nagovizin, V.; Nahnhauer, R.; Naroska, B.; Naumann, Th.; Négri, I.; Newman, P. R.; Newton, D.; Nguyen, H. K.; Nicholls, T. C.; Niebergall, F.; Niebuhr, C.; Niedzballa, Ch.; Niggli, H.; Nisius, R.; Nowak, G.; Noyes, G. W.; Nyberg-Werther, M.; Oakden, M.; Oberlack, H.; Olsson, J. E.; Ozerov, D.; Palmen, P.; Panaro, E.; Panitch, A.; Pascaud, C.; Patel, G. D.; Pawletta, H.; Peppel, E.; Perez, E.; Phillips, J. P.; Pieuchot, A.; Pitzl, D.; Pope, G.; Prell, S.; Rabbertz, K.; Rädel, G.; Reimer, P.; Reinshagen, S.; Rick, H.; Riech, V.; Riedlberger, J.; Riepenhausen, F.; Riess, S.; Rizvi, E.; Robertson, S. M.; Robmann, P.; Roloff, H. E.; Roosen, R.; Rosenbauer, K.; Rostovtsev, A.; Rouse, F.; Royon, C.; Rüter, K.; Rusakov, S.; Rybicki, K.; Sankey, D. P. C.; Schacht, P.; Schiek, S.; Schleif, S.; Schleper, P.; von Schlippe, W.; Schmidt, D.; Schmidt, G.; Schöning, A.; Schröder, V.; Schuhmann, E.; Schwab, B.; Sefkow, F.; Seidel, M.; Sell, R.; Semenov, A.; Shekelyan, V.; Sheviakov, I.; Shtarkov, L. N.; Siegmon, G.; Siewert, U.; Sirois, Y.; Skillicorn, I. O.; Smirnov, P.; Smith, J. R.; Solochenko, V.; Soloviev, Y.; Specka, A.; Spiekermann, J.; Spielman, S.; Spitzer, H.; Squinabol, F.; Steenbock, M.; Steffen, P.; Steinberg, R.; Steiner, H.; Steinhart, J.; Stella, B.; Stellberger, A.; Stier, J.; Stiewe, J.; Stößlein, U.; Stolze, K.; Straumann, U.; Struczinski, W.; Sutton, J. P.; Tapprogge, S.; Taševský, M.; Tchernyshov, V.; Tchetchelnitski, S.; Theissen, J.; Thiebaux, C.; Thompson, G.; Truöl, P.; Tsipolitis, G.; Turnau, J.; Tutas, J.; Uelkes, P.; Usik, A.; Valkár, S.; Valkárová, A.; Vallée, C.; Vandenplas, D.; van Esch, P.; van Mechelen, P.; Vazdik, Y.; Verrecchia, P.; Villet, G.; Wacker, K.; Wagener, A.; Wagener, M.; Walther, A.; Waugh, B.; Weber, G.; Weber, M.; Wegener, D.; Wegner, A.; Wengler, T.; Werner, M.; West, L. R.; Wilksen, T.; Willard, S.; Winde, M.; Winter, G.-G.; Wittek, C.; Wobisch, M.; Wünsch, E.; Žáček, J.; Zarbock, D.; Zhang, Z.; Zhokin, A.; Zini, P.; Zomer, F.; Zsembery, J.; Zuber, K.; Zurnedden, M.

1996-12-01

Using the H1 detector at HERA, charged particle multiplicity distributions in deep inelastic e + p scattering have been measured over a large kinematical region. The evolution with W and Q 2 of the multiplicity distribution and of the multiplicity moments in pseudorapidity domains of varying size is studied in the current fragmentation region of the hadronic centre-of-mass frame. The results are compared with data from fixed target lepton-nucleon interactions, e + e - annihilations and hadron-hadron collisions as well as with expectations from QCD based parton models. Fits to the Negative Binomial and Lognormal distributions are presented.

The influence of neighborhood characteristics on the relationship between discrimination and increased drug-using social ties among illicit drug users.

PubMed

Crawford, Natalie D; Borrell, Luisa N; Galea, Sandro; Ford, Chandra; Latkin, Carl; Fuller, Crystal M

2013-04-01

Social discrimination may isolate drug users into higher risk relationships, particularly in disadvantaged neighborhood environments where drug trade occurs. We used negative binomial regression accounting for clustering of individuals within their recruitment neighborhood to investigate the relationship between high-risk drug ties with various forms of social discrimination, neighborhood minority composition, poverty and education. Results show that experiencing discrimination due to drug use is significantly associated with more drug ties in neighborhoods with fewer blacks. Future social network and discrimination research should assess the role of neighborhood social cohesion.

Neighborhood characteristics contribute to urban alcohol availability: Accounting for race/ethnicity and social disorganization.

PubMed

Snowden, Aleksandra J

2016-01-01

This study examined the role that race/ethnicity and social disorganization play in alcohol availability in Milwaukee, Wisconsin, census block groups. This study estimated negative binomial regression models to examine separately the relationship between neighborhood racial/ethnic composition and social disorganization levels for (1) total, (2) on-premise, and (3) off-premise alcohol outlets. Results of this study suggest that proportion Hispanic was positively associated with total and with off-premise alcohol outlets. Second, proportion African American was negatively associated with on-premise alcohol outlets and positively associated with off-premise alcohol outlets. Proportion Asian was not associated with total, on-premise, or off-premise alcohol outlets. However, the effects of race/ethnicity on alcohol availability were either unrelated or negatively related to alcohol outlet availability once neighborhood social disorganization levels were taken into account, and social disorganization was positively and significantly associated with all alcohol outlet types. Neighborhood characteristics contribute to alcohol availability and must be considered in any efforts aimed toward prevention of alcohol-related negative health and social outcomes.

The five-factor model of impulsivity-like traits and emotional lability in aggressive behavior.

PubMed

Dvorak, Robert D; Pearson, Matthew R; Kuvaas, Nicholas J

2013-01-01

Factors that increase automatic psychological processes may result in impulsive action and, consequently, aggressive behavior. The current cross-sectional study examined the association between the five-factor model of impulsivity-like traits (negative urgency, positive urgency, premeditation, perseverance, and sensation seeking), emotional lability, and physically aggressive behaviors among college students (n = 481) in a negative binomial hurdle model. In the logistic portion of the model, emotional lability was related to a higher likelihood of engaging in aggressive acts in the past 6 months. The association between emotional lability and the likelihood of aggressive behavior was moderated by two impulsivity-like traits: negative urgency and positive urgency. Specifically, emotional lability was related to engaging in aggressive acts among those with high negative urgency, and among those with low positive urgency. In the count portion of the model, emotional lability was uniquely related to the number of aggressive acts in the past 6 months. Our results indicate that emotional lability and facets of impulsivity interactively relate to engagement in aggressive behavior, suggesting that these variables be integrated into models of aggression. © 2013 Wiley Periodicals, Inc.

A Monte Carlo Risk Analysis of Life Cycle Cost Prediction.

DTIC Science & Technology

1975-09-01

process which occurs with each FLU failure. With this in mind there is no alternative other than the binomial distribution. 24 GOR/SM/75D-6 With all of...Weibull distribution of failures as selected by user. For each failure of the ith FLU, the model then samples from the binomial distribution to deter- mine...which is sampled from the binomial . Neither of the two conditions for normality are met, i.e., that RTS Ie close to .5 and the number of samples close

Statistical methods for the beta-binomial model in teratology.

PubMed Central

Yamamoto, E; Yanagimoto, T

1994-01-01

The beta-binomial model is widely used for analyzing teratological data involving littermates. Recent developments in statistical analyses of teratological data are briefly reviewed with emphasis on the model. For statistical inference of the parameters in the beta-binomial distribution, separation of the likelihood introduces an likelihood inference. This leads to reducing biases of estimators and also to improving accuracy of empirical significance levels of tests. Separate inference of the parameters can be conducted in a unified way. PMID:8187716

The Binomial Distribution in Shooting

ERIC Educational Resources Information Center

Chalikias, Miltiadis S.

2009-01-01

The binomial distribution is used to predict the winner of the 49th International Shooting Sport Federation World Championship in double trap shooting held in 2006 in Zagreb, Croatia. The outcome of the competition was definitely unexpected.

Trends in incidence of occupational asthma, contact dermatitis, noise-induced hearing loss, carpal tunnel syndrome and upper limb musculoskeletal disorders in European countries from 2000 to 2012.

PubMed

Stocks, S Jill; McNamee, Roseanne; van der Molen, Henk F; Paris, Christophe; Urban, Pavel; Campo, Giuseppe; Sauni, Riitta; Martínez Jarreta, Begoña; Valenty, Madeleine; Godderis, Lode; Miedinger, David; Jacquetin, Pascal; Gravseth, Hans M; Bonneterre, Vincent; Telle-Lamberton, Maylis; Bensefa-Colas, Lynda; Faye, Serge; Mylle, Godewina; Wannag, Axel; Samant, Yogindra; Pal, Teake; Scholz-Odermatt, Stefan; Papale, Adriano; Schouteden, Martijn; Colosio, Claudio; Mattioli, Stefano; Agius, Raymond

2015-04-01

The European Union (EU) strategy for health and safety at work underlines the need to reduce the incidence of occupational diseases (OD), but European statistics to evaluate this common goal are scarce. We aim to estimate and compare changes in incidence over time for occupational asthma, contact dermatitis, noise-induced hearing loss (NIHL), carpal tunnel syndrome (CTS) and upper limb musculoskeletal disorders across 10 European countries. OD surveillance systems that potentially reflected nationally representative trends in incidence within Belgium, the Czech Republic, Finland, France, Italy, the Netherlands, Norway, Spain, Switzerland and the UK provided data. Case counts were analysed using a negative binomial regression model with year as the main covariate. Many systems collected data from networks of 'centres', requiring the use of a multilevel negative binomial model. Some models made allowance for changes in compensation or reporting rules. Reports of contact dermatitis and asthma, conditions with shorter time between exposure to causal substances and OD, were consistently declining with only a few exceptions. For OD with physical causal exposures there was more variation between countries. Reported NIHL was increasing in Belgium, Spain, Switzerland and the Netherlands and decreasing elsewhere. Trends in CTS and upper limb musculoskeletal disorders varied widely within and between countries. This is the first direct comparison of trends in OD within Europe and is consistent with a positive impact of European initiatives addressing exposures relevant to asthma and contact dermatitis. Taking a more flexible approach allowed comparisons of surveillance data between and within countries without harmonisation of data collection methods. 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.

Risk factors related to Toxoplasma gondii seroprevalence in indoor-housed Dutch dairy goats.

PubMed

Deng, Huifang; Dam-Deisz, Cecile; Luttikholt, Saskia; Maas, Miriam; Nielen, Mirjam; Swart, Arno; Vellema, Piet; van der Giessen, Joke; Opsteegh, Marieke

2016-02-01

Toxoplasma gondii can cause disease in goats, but also has impact on human health through food-borne transmission. Our aims were to determine the seroprevalence of T. gondii infection in indoor-housed Dutch dairy goats and to identify the risk factors related to T. gondii seroprevalence. Fifty-two out of ninety approached farmers with indoor-kept goats (58%) participated by answering a standardized questionnaire and contributing 32 goat blood samples each. Serum samples were tested for T. gondii SAG1 antibodies by ELISA and results showed that the frequency distribution of the log10-transformed OD-values fitted well with a binary mixture of a shifted gamma and a shifted reflected gamma distribution. The overall animal seroprevalence was 13.3% (95% CI: 11.7–14.9%), and at least one seropositive animal was found on 61.5% (95% CI: 48.3–74.7%) of the farms. To evaluate potential risk factors on herd level, three modeling strategies (Poisson, negative binomial and zero-inflated) were compared. The negative binomial model fitted the data best with the number of cats (1–4 cats: IR: 2.6, 95% CI: 1.1–6.5; > = 5 cats:IR: 14.2, 95% CI: 3.9–51.1) and mean animal age (IR: 1.5, 95% CI: 1.1–2.1) related to herd positivity. In conclusion, the ELISA test was 100% sensitive and specific based on binary mixture analysis. T. gondii infection is prevalent in indoor housed Dutch dairy goats but at a lower overall animal level seroprevalence than outdoor farmed goats in other European countries, and cat exposure is an important risk factor.

Dental enamel defects, caries experience and oral health-related quality of life: a cohort study.

PubMed

Arrow, P

2017-06-01

The impact of enamel defects of the first permanent molars on caries experience and child oral health-related quality of life was evaluated in a cohort study. Children who participated in a study of enamel defects of the first permanent molars 8 years earlier were invited for a follow-up assessment. Consenting children completed the Child Perception Questionnaire and the faces Modified Child Dental Anxiety Scale, and were examined by two calibrated examiners. ANOVA, Kruskal-Wallis, negative binomial and logistic regression were used for data analyses. One hundred and eleven children returned a completed questionnaire and 91 were clinically examined. Negative binomial regression found that oral health impacts were associated with gender (boys, risk ratio (RR) = 0.73, P = 0.03) and decayed, missing or filled permanent teeth (DMFT) (RR = 1.1, P = 0.04). The mean DMFT of children were sound (0.9, standard deviation (SD) = 1.4), diffuse defects (0.8, SD = 1.7), demarcated defects (1.5, SD = 1.4) and pit defects (1.3, SD = 2.3) (Kruskal-Wallis, P = 0.05). Logistic regression of first permanent molar caries found higher odds of caries experience with baseline primary tooth caries experience (odds ratio (OR) = 1.5, P = 0.01), the number of teeth affected by enamel defects (OR = 1.9, P = 0.05) and lower odds with the presence of diffuse enamel defects (OR = 0.1, P = 0.04). The presence of diffuse enamel defects was associated with lower odds of caries experience. © 2016 Australian Dental Association.

Dental plaque, preventive care, and tooth brushing associated with dental caries in primary teeth in schoolchildren ages 6–9 years of Leon, Nicaragua

PubMed Central

del Socorro Herrera, Miriam; Medina-Solis, Carlo Eduardo; Minaya-Sánchez, Mirna; Pontigo-Loyola, América Patricia; Villalobos-Rodelo, Juan José; Islas-Granillo, Horacio; de la Rosa-Santillana, Rubén; Maupomé, Gerardo

2013-01-01

Background Our study aimed to evaluate the effect of various risk indicators for dental caries on primary teeth of Nicaraguan children (from Leon, Nicaragua) ages 6 to 9, using the negative binomial regression model. Material/Methods A cross-sectional study was carried out to collect clinical, demographic, socioeconomic, and behavioral data from 794 schoolchildren ages 6 to 9 years, randomly selected from 25 schools in the city of León, Nicaragua. Clinical examinations for dental caries (dmft index) were performed by 2 trained and standardized examiners. Socio-demographic, socioeconomic, and behavioral data were self-reported using questionnaires. Multivariate negative binomial regression (NBR) analysis was used. Results Mean age was 7.49±1.12 years. Boys accounted for 50.1% of the sample. Mean dmft was 3.54±3.13 and caries prevalence (dmft >0) was 77.6%. In the NBR multivariate model (p<0.05), for each year of age, the expected mean dmft decreased by 7.5%. Brushing teeth at least once a day and having received preventive dental care in the last year before data collection were associated with declines in the expected mean dmft by 19.5% and 69.6%, respectively. Presence of dental plaque increased the expected mean dmft by 395.5%. Conclusions The proportion of students with caries in this sample was high. We found associations between dental caries in the primary dentition and dental plaque, brushing teeth at least once a day, and having received preventive dental care. To improve oral health, school programs and/or age-appropriate interventions need to be developed based on the specific profile of caries experience and the associated risk indicators. PMID:24247119

Frequency distribution of Echinococcus multilocularis and other helminths of foxes in Kyrgyzstan

PubMed Central

I., Ziadinov; P., Deplazes; A., Mathis; B., Mutunova; K., Abdykerimov; R., Nurgaziev; P.R, Torgerson

2010-01-01

Echinococcosis is a major emerging zoonosis in central Asia. A study of the helminth fauna of foxes from Naryn Oblast in central Kyrgyzstan was undertaken to investigate the abundance of Echinococcus multilocularis in a district where a high prevalence of this parasite had previously been detected in dogs. A total of 151 foxes (Vulpes vulpes) were investigated in a necropsy study. Of these 96 (64%) were infected with E. multilocularis with a mean abundance of 8669 parasites per fox. This indicates that red foxes are a major definitive host of E. multilocularis in this country. This also demonstrates that the abundance and prevalence of E. multilocularis in the natural definitive host are likely to be high in geographical regions where there is a concomitant high prevalence in alternative definitive hosts such as dogs. In addition Mesocestoides spp., Dipylidium caninum, Taenia spp., Toxocara canis, Toxascaris leonina, Capillaria and Acanthocephala spp. were found in 99 (66%), 50 (33%), 48 (32%), 46 (30%), 9 (6%), 34 (23%) and 2 (1%) of foxes, respectively. The prevalence but not the abundance of E. multilocularis decreased with age. The abundance of Dipylidium caninum also decreased with age. The frequency distribution of E. multilocularis and Mesocestoides spp. followed a zero inflated negative binomial distribution, whilst all other helminths had a negative binomial distribution. This demonstrates that the frequency distribution of positive counts and not just the frequency of zeros in the data set can determine if a zero inflated or non-zero inflated model is more appropriate. This is because the prevalences of E. multolocularis and Mesocestoides spp. were the highest (and hence had fewest zero counts) yet the parasite distribution nevertheless gave a better fit to the zero inflated models. PMID:20434845

Mycophenolic Acid Pharmacokinetics and Relapse in Children with Steroid–Dependent Idiopathic Nephrotic Syndrome

PubMed Central

Tellier, Stéphanie; Dallocchio, Aymeric; Guigonis, Vincent; Saint-Marcoux, Frank; Llanas, Brigitte; Ichay, Lydia; Bandin, Flavio; Godron, Astrid; Morin, Denis; Brochard, Karine; Gandia, Peggy; Bouchet, Stéphane; Marquet, Pierre; Decramer, Stéphane

2016-01-01

Background and objectives Therapeutic drug monitoring of mycophenolic acid can improve clinical outcome in organ transplantation and lupus, but data are scarce in idiopathic nephrotic syndrome. The aim of our study was to investigate whether mycophenolic acid pharmacokinetics are associated with disease control in children receiving mycophenolate mofetil for the treatment of steroid–dependent nephrotic syndrome. Design, setting, participants, & measurements This was a retrospective multicenter study including 95 children with steroid–dependent nephrotic syndrome treated with mycophenolate mofetil with or without steroids. Area under the concentration-time curve of mycophenolic acid was determined in all children on the basis of sampling times at 20, 60, and 180 minutes postdose, using Bayesian estimation. The association between a threshold value of the area under the concentration-time curve of mycophenolic acid and the relapse rate was assessed using a negative binomial model. Results In total, 140 areas under the concentration-time curve of mycophenolic acid were analyzed. The findings indicate individual dose adaptation in 53 patients (38%) to achieve an area under the concentration-time curve target of 30–60 mg·h/L. In a multivariable negative binomial model including sex, age at disease onset, time to start of mycophenolate mofetil, previous immunomodulatory treatment, and concomitant prednisone dose, a level of area under the concentration-time curve of mycophenolic acid >45 mg·h/L was significantly associated with a lower relapse rate (rate ratio, 0.65; 95% confidence interval, 0.46 to 0.89; P=0.01). Conclusions Therapeutic drug monitoring leading to individualized dosing may improve the efficacy of mycophenolate mofetil in steroid–dependent nephrotic syndrome. Additional prospective studies are warranted to determine the optimal target for area under the concentration-time curve of mycophenolic acid in this population. PMID:27445161

Mycophenolic Acid Pharmacokinetics and Relapse in Children with Steroid-Dependent Idiopathic Nephrotic Syndrome.

PubMed

Tellier, Stéphanie; Dallocchio, Aymeric; Guigonis, Vincent; Saint-Marcoux, Frank; Llanas, Brigitte; Ichay, Lydia; Bandin, Flavio; Godron, Astrid; Morin, Denis; Brochard, Karine; Gandia, Peggy; Bouchet, Stéphane; Marquet, Pierre; Decramer, Stéphane; Harambat, Jérôme

2016-10-07

Therapeutic drug monitoring of mycophenolic acid can improve clinical outcome in organ transplantation and lupus, but data are scarce in idiopathic nephrotic syndrome. The aim of our study was to investigate whether mycophenolic acid pharmacokinetics are associated with disease control in children receiving mycophenolate mofetil for the treatment of steroid-dependent nephrotic syndrome. This was a retrospective multicenter study including 95 children with steroid-dependent nephrotic syndrome treated with mycophenolate mofetil with or without steroids. Area under the concentration-time curve of mycophenolic acid was determined in all children on the basis of sampling times at 20, 60, and 180 minutes postdose, using Bayesian estimation. The association between a threshold value of the area under the concentration-time curve of mycophenolic acid and the relapse rate was assessed using a negative binomial model. In total, 140 areas under the concentration-time curve of mycophenolic acid were analyzed. The findings indicate individual dose adaptation in 53 patients (38%) to achieve an area under the concentration-time curve target of 30-60 mg·h/L. In a multivariable negative binomial model including sex, age at disease onset, time to start of mycophenolate mofetil, previous immunomodulatory treatment, and concomitant prednisone dose, a level of area under the concentration-time curve of mycophenolic acid >45 mg·h/L was significantly associated with a lower relapse rate (rate ratio, 0.65; 95% confidence interval, 0.46 to 0.89; P =0.01). Therapeutic drug monitoring leading to individualized dosing may improve the efficacy of mycophenolate mofetil in steroid-dependent nephrotic syndrome. Additional prospective studies are warranted to determine the optimal target for area under the concentration-time curve of mycophenolic acid in this population. Copyright © 2016 by the American Society of Nephrology.

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gingival recession and associated factors in a homogeneous Mexican adult male population: A cross-sectional study

PubMed Central

Minaya-Sánchez, Mirna; Medina-Solís, Carlo E.; Vallejos-Sánchez, Ana A.; Marquez-Corona, Maria L.; Pontigo-Loyola, América P.; Islas-Granillo, Horacio; Maupomé, Gerardo

2012-01-01

Background: Diverse variables are implicated in the pathogenesis of gingival recession; more detailed knowledge about the relationship between the clinical presentation of gingival recession and assorted risk indicators may lead to improved patient monitoring, early intervention, and subsequent prevention. The objective was to evaluate clinically gingival recession in a homogeneous Mexican adult male population and to determine the strength of association with related factors. Method: A cross-sectional study was carried out in a largely homogeneous group in terms of ethnic background, socioeconomic status, gender, occupation, and medical/dental insurance, in Campeche, Mexico. Periodontal examinations were undertaken to determine diverse clinical dental variables. All periodontal clinical examinations were assessed using the Florida Probe System, a dental chair and one examiner. Questionnaires were used to collect diverse risk indicators. Statistical analyses were undertaken with negative binomial regression models. Results: The mean number of sites with gingival recession per subject was 6.73±5.81; the prevalence was 87.6%. In the negative binomial regression model we observed that for (i) each year of age, and (ii) each percentage unit of increase in sites with plaque, and (iii) with suppuration, mean sites with gingival recession increased 2.9%, 1.0% and 13.0%, respectively. Having a spouse was associated with gingival recession. Conclusions: We observed association between gingival recession, and sociodemographic and clinical parameters. Patients need to be educated about risk indicators for gingival recession as well as the preventive maneuvers that may be implemented to minimize its occurrence. The potential of improved oral self-care to prevent a largely benign condition such as gingival recession is important, given the associated disorders that may ensue root exposure, such as root caries and root hypersensitivity. Key words:Oral health, periodontal health, gingival recession, adults, Mexico. PMID:22549678

Recurrent suicide attempts in patients with depressive and anxiety disorders: the role of borderline personality traits.

PubMed

Stringer, Barbara; van Meijel, Berno; Eikelenboom, Merijn; Koekkoek, Bauke; Licht, Carmilla M M; Kerkhof, Ad J F M; Penninx, Brenda W J H; Beekman, Aartjan T F

2013-10-01

The presence of a comorbid borderline personality disorder (BPD) may be associated with an increase of suicidal behaviors in patients with depressive and anxiety disorders. The aim of this study is to examine the role of borderline personality traits on recurrent suicide attempts. The Netherlands Study on Depression and Anxiety included 1838 respondents with lifetime depressive and/or anxiety disorders, of whom 309 reported at least one previous suicide attempt. A univariable negative binomial regression analysis was performed to examine the association between comorbid borderline personality traits and suicide attempts. Univariable and multivariable negative binomial regression analyses were performed to identify risk factors for the number of recurrent suicide attempts in four clusters (type and severity of axis-I disorders, BPD traits, determinants of suicide attempts and socio-demographics). In the total sample the suicide attempt rate ratio increased with 33% for every unit increase in BPD traits. A lifetime diagnosis of dysthymia and comorbid BPD traits, especially the symptoms anger and fights, were independently and significantly associated with recurrent suicide attempts in the final model (n=309). The screening of personality disorders was added to the NESDA assessments at the 4-year follow-up for the first time. Therefore we were not able to examine the influence of comorbid BPD traits on suicide attempts over time. Persons with a lifetime diagnosis of dysthymia combined with borderline personality traits especially difficulties in coping with anger seemed to be at high risk for recurrent suicide attempts. For clinical practice, it is recommended to screen for comorbid borderline personality traits and to strengthen the patient's coping skills with regard to anger. © 2013 Elsevier B.V. All rights reserved.

Analysing recurrent hospitalizations in heart failure: a review of statistical methodology, with application to CHARM-Preserved.

PubMed

Rogers, Jennifer K; Pocock, Stuart J; McMurray, John J V; Granger, Christopher B; Michelson, Eric L; Östergren, Jan; Pfeffer, Marc A; Solomon, Scott D; Swedberg, Karl; Yusuf, Salim

2014-01-01

Heart failure is characterized by recurrent hospitalizations, but often only the first event is considered in clinical trial reports. In chronic diseases, such as heart failure, analysing all events gives a more complete picture of treatment benefit. We describe methods of analysing repeat hospitalizations, and illustrate their value in one major trial. The Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity (CHARM)-Preserved study compared candesartan with placebo in 3023 patients with heart failure and preserved systolic function. The heart failure hospitalization rates were 12.5 and 8.9 per 100 patient-years in the placebo and candesartan groups, respectively. The repeat hospitalizations were analysed using the Andersen-Gill, Poisson, and negative binomial methods. Death was incorporated into analyses by treating it as an additional event. The win ratio method and a method that jointly models hospitalizations and mortality were also considered. Using repeat events gave larger treatment benefits than time to first event analysis. The negative binomial method for the composite of recurrent heart failure hospitalizations and cardiovascular death gave a rate ratio of 0.75 [95% confidence interval (CI) 0.62-0.91, P = 0.003], whereas the hazard ratio for time to first heart failure hospitalization or cardiovascular death was 0.86 (95% CI 0.74-1.00, P = 0.050). In patients with preserved EF, candesartan reduces the rate of admissions for worsening heart failure, to a greater extent than apparent from analysing only first hospitalizations. Recurrent events should be routinely incorporated into the analysis of future clinical trials in heart failure. © 2013 The Authors. European Journal of Heart Failure © 2013 European Society of Cardiology.

Prediction of different ovarian responses using anti-Müllerian hormone following a long agonist treatment protocol for IVF.

PubMed

Heidar, Z; Bakhtiyari, M; Mirzamoradi, M; Zadehmodarres, S; Sarfjoo, F S; Mansournia, M A

2015-09-01

The purpose of this study was to predict the poor and excessive ovarian response using anti-Müllerian hormone (AMH) levels following a long agonist protocol in IVF candidates. Through a prospective cohort study, the type of relationship and appropriate scale for AMH were determined using the fractional polynomial regression. To determine the effect of AMH on the outcomes of ovarian stimulation and different ovarian responses, the multi-nominal and negative binomial regression models were fitted using backward stepwise method. The ovarian response of study subject who entered a standard long-term treatment cycle with GnRH agonist was evaluated using prediction model, separately and in combined models with (ROC) curves. The use of standard long-term treatments with GnRH agonist led to positive pregnancy test results in 30% of treated patients. With each unit increase in the log of AMH, the odds ratio of having poor response compared to normal response decreases by 64% (OR 0.36, 95% CI 0.19-0.68). Also the results of negative binomial regression model indicated that for one unit increase in the log of AMH blood levels, the odds of releasing an oocyte increased 24% (OR 1.24, 95% CI 1.14-1.35). The optimal cut-off points of AMH for predicting excessive and poor ovarian responses were 3.4 and 1.2 ng/ml, respectively, with area under curves of 0.69 (0.60-0.77) and 0.76 (0.66-0.86), respectively. By considering the age of the patient undergoing infertility treatment as a variable affecting ovulation, use of AMH levels showed to be a good test to discriminate between different ovarian responses.

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials

PubMed Central

Verhey, Leonard H.; Signori, Alessio; Arnold, Douglas L.; Bar-Or, Amit; Sadovnick, A. Dessa; Marrie, Ruth Ann; Banwell, Brenda

2013-01-01

Objective: To estimate sample sizes for pediatric multiple sclerosis (MS) trials using new T2 lesion count, annualized relapse rate (ARR), and time to first relapse (TTFR) endpoints. Methods: Poisson and negative binomial models were fit to new T2 lesion and relapse count data, and negative binomial time-to-event and exponential models were fit to TTFR data of 42 children with MS enrolled in a national prospective cohort study. Simulations were performed by resampling from the best-fitting model of new T2 lesion count, number of relapses, or TTFR, under various assumptions of the effect size, trial duration, and model parameters. Results: Assuming a 50% reduction in new T2 lesions over 6 months, 90 patients/arm are required, whereas 165 patients/arm are required for a 40% treatment effect. Sample sizes for 2-year trials using relapse-related endpoints are lower than that for 1-year trials. For 2-year trials and a conservative assumption of overdispersion (ϑ), sample sizes range from 70 patients/arm (using ARR) to 105 patients/arm (TTFR) for a 50% reduction in relapses, and 230 patients/arm (ARR) to 365 patients/arm (TTFR) for a 30% relapse reduction. Assuming a less conservative ϑ, 2-year trials using ARR require 45 patients/arm (60 patients/arm for TTFR) for a 50% reduction in relapses and 145 patients/arm (200 patients/arm for TTFR) for a 30% reduction. Conclusion: Six-month phase II trials using new T2 lesion count as an endpoint are feasible in the pediatric MS population; however, trials powered on ARR or TTFR will need to be 2 years in duration and will require multicentered collaboration. PMID:23966255

Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

PubMed

Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

2017-02-06

Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

Assessing historical rate changes in global tsunami occurrence

USGS Publications Warehouse

Geist, E.L.; Parsons, T.

2011-01-01

The global catalogue of tsunami events is examined to determine if transient variations in tsunami rates are consistent with a Poisson process commonly assumed for tsunami hazard assessments. The primary data analyzed are tsunamis with maximum sizes >1m. The record of these tsunamis appears to be complete since approximately 1890. A secondary data set of tsunamis >0.1m is also analyzed that appears to be complete since approximately 1960. Various kernel density estimates used to determine the rate distribution with time indicate a prominent rate change in global tsunamis during the mid-1990s. Less prominent rate changes occur in the early- and mid-20th century. To determine whether these rate fluctuations are anomalous, the distribution of annual event numbers for the tsunami catalogue is compared to Poisson and negative binomial distributions, the latter of which includes the effects of temporal clustering. Compared to a Poisson distribution, the negative binomial distribution model provides a consistent fit to tsunami event numbers for the >1m data set, but the Poisson null hypothesis cannot be falsified for the shorter duration >0.1m data set. Temporal clustering of tsunami sources is also indicated by the distribution of interevent times for both data sets. Tsunami event clusters consist only of two to four events, in contrast to protracted sequences of earthquakes that make up foreshock-main shock-aftershock sequences. From past studies of seismicity, it is likely that there is a physical triggering mechanism responsible for events within the tsunami source 'mini-clusters'. In conclusion, prominent transient rate increases in the occurrence of global tsunamis appear to be caused by temporal grouping of geographically distinct mini-clusters, in addition to the random preferential location of global M >7 earthquakes along offshore fault zones.

Quality of maternity care and its determinants along the continuum in Kenya: A structural equation modeling analysis

PubMed Central

Mendez, Bomar Rojas

2017-01-01

Background Improving access to delivery services does not guarantee access to quality obstetric care and better survival, and therefore, concerns for quality of maternal and newborn care in low- and middle-income countries have been raised. Our study explored characteristics associated with the quality of initial assessment, intrapartum, and immediate postpartum and newborn care, and further assessed the relationships along the continuum of care. Methods The 2010 Service Provision Assessment data of Kenya for 627 routine deliveries of women aged 15–49 were used. Quality of care measures were assessed using recently validated quality of care measures during initial assessment, intrapartum, and postpartum periods. Data were analyzed with negative binomial regression and structural equation modeling technique. Results The negative binomial regression results identified a number of determinants of quality, such as the level of health facilities, managing authority, presence of delivery fee, central electricity supply and clinical guideline for maternal and neonatal care. Our structural equation modeling (SEM) further demonstrated that facility characteristics were important determinants of quality for initial assessment and postpartum care, while characteristics at the provider level became more important in shaping the quality of intrapartum care. Furthermore we also noted that quality of initial assessment had a positive association with quality of intrapartum care (β = 0.71, p < 0.001), which in turn was positively associated with the quality of newborn and immediate postpartum care (β = 1.29, p = 0.004). Conclusions A continued focus on quality of care along the continuum of maternity care is important not only to mothers but also their newborns. Policymakers should therefore ensure that required resources, as well as adequate supervision and emphasis on the quality of obstetric care, are available. PMID:28520771

Factors Associated with Dental Caries in a Group of American Indian Children at age 36 Months

PubMed Central

Warren, John J.; Blanchette, Derek; Dawson, Deborah V.; Marshall, Teresa A.; Phipps, Kathy R.; Starr, Delores; Drake, David R.

2015-01-01

Objectives Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This paper reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Methods Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28 and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary and behavioral factors. Non-parametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Results Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only non-cavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (p<0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. Conclusions By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size and maternal factors, but further analyses are needed to better understand caries in this population. PMID:26544674

Household expenditure on leprosy outpatient services in the Indian health system: A comparative study

PubMed Central

Suryawanshi, Pramilesh; Raikwar, Akash; Arif, Mohammad; Richardus, Jan Hendrik

2018-01-01

Background Leprosy is a major public health problem in many low and middle income countries, especially in India, and contributes considerably to the global burden of the disease. Leprosy and poverty are closely associated, and therefore the economic burden of leprosy is a concern. However, evidence on patient’s expenditure is scarce. In this study, we estimate the expenditure in primary care (outpatient) by leprosy households in two different public health settings. Methodology/Principal findings We performed a cross-sectional study, comparing the Union Territory of Dadra and Nagar Haveli with the Umbergaon block of Valsad, Gujrat, India. A household (HH) survey was conducted between May and October, 2016. We calculated direct and indirect expenditure by zero inflated negative binomial and negative binomial regression. The sampled households were comparable on socioeconomic indicators. The mean direct expenditure was USD 6.5 (95% CI: 2.4–17.9) in Dadra and Nagar Haveli and USD 5.4 (95% CI: 3.8–7.9) per visit in Umbergaon. The mean indirect expenditure was USD 8.7 (95% CI: 7.2–10.6) in Dadra and Nagar Haveli and USD 12.4 (95% CI: 7.0–21.9) in Umbergaon. The age of the leprosy patients and type of health facilities were the major predictors of total expenditure on leprosy primary care. The higher the age, the higher the expenditure at both sites. The private facilities are more expensive than the government facilities at both sites. If the public health system is enhanced, government facilities are the first preference for patients. Conclusions/Significance An enhanced public health system reduces the patient’s expenditure and improves the health seeking behaviour. We recommend investing in health system strengthening to reduce the economic burden of leprosy. PMID:29300747

Homicide mortality rates in Canada, 2000-2009: Youth at increased risk.

PubMed

Basham, C Andrew; Snider, Carolyn

2016-10-20

To estimate and compare Canadian homicide mortality rates (HMRs) and trends in HMRs across age groups, with a focus on trends for youth. Data for the period of 2000 to 2009 were collected from Statistics Canada's CANSIM (Canadian Statistical Information Management) Table 102-0540 with the following ICD-10-CA coded external causes of death: X85 to Y09 (assault) and Y87.1 (sequelae of assault). Annual population counts from 2000 to 2009 were obtained from Statistics Canada's CANSIM Table 051-0001. Both death and population counts were organized into five-year age groups. A random effects negative binomial regression analysis was conducted to estimate age group-specific rates, rate ratios, and trends in homicide mortality. There were 9,878 homicide deaths in Canada during the study period. The increase in the overall homicide mortality rate (HMR) of 0.3% per year was not statistically significant (95% CI: -1.1% to +1.8%). Canadians aged 15-19 years and 20-24 years had the highest HMRs during the study period, and experienced statistically significant annual increases in their HMRs of 3% and 4% respectively (p < 0.05). A general, though not statistically significant, decrease in the HMR was observed for all age groups 50+ years. A fixed effects negative binomial regression model showed that the HMR for males was higher than for females over the study period [RRfemale/male = 0.473 (95% CI: 0.361, 0.621)], but no significant difference in sex-specific trends in the HMR was found. An increasing risk of homicide mortality was identified among Canadian youth, ages 15-24, over the 10-year study period. Research that seeks to understand the reasons for the increased homicide risk facing Canada's youth, and public policy responses to reduce this risk, are warranted.

Predicting length of stay from an electronic patient record system: a primary total knee replacement example.

PubMed

Carter, Evelene M; Potts, Henry W W

2014-04-04

To investigate whether factors can be identified that significantly affect hospital length of stay from those available in an electronic patient record system, using primary total knee replacements as an example. To investigate whether a model can be produced to predict the length of stay based on these factors to help resource planning and patient expectations on their length of stay. Data were extracted from the electronic patient record system for discharges from primary total knee operations from January 2007 to December 2011 (n=2,130) at one UK hospital and analysed for their effect on length of stay using Mann-Whitney and Kruskal-Wallis tests for discrete data and Spearman's correlation coefficient for continuous data. Models for predicting length of stay for primary total knee replacements were tested using the Poisson regression and the negative binomial modelling techniques. Factors found to have a significant effect on length of stay were age, gender, consultant, discharge destination, deprivation and ethnicity. Applying a negative binomial model to these variables was successful. The model predicted the length of stay of those patients who stayed 4-6 days (~50% of admissions) with 75% accuracy within 2 days (model data). Overall, the model predicted the total days stayed over 5 years to be only 88 days more than actual, a 6.9% uplift (test data). Valuable information can be found about length of stay from the analysis of variables easily extracted from an electronic patient record system. Models can be successfully created to help improve resource planning and from which a simple decision support system can be produced to help patient expectation on their length of stay.

Dental plaque, preventive care, and tooth brushing associated with dental caries in primary teeth in schoolchildren ages 6-9 years of Leon, Nicaragua.

PubMed

Herrera, Miriam del Socorro; Medina-Solís, Carlo Eduardo; Minaya-Sánchez, Mirna; Pontigo-Loyola, América Patricia; Villalobos-Rodelo, Juan José; Islas-Granillo, Horacio; de la Rosa-Santillana, Rubén; Maupomé, Gerardo

2013-11-19

Our study aimed to evaluate the effect of various risk indicators for dental caries on primary teeth of Nicaraguan children (from Leon, Nicaragua) ages 6 to 9, using the negative binomial regression model. A cross-sectional study was carried out to collect clinical, demographic, socioeconomic, and behavioral data from 794 schoolchildren ages 6 to 9 years, randomly selected from 25 schools in the city of León, Nicaragua. Clinical examinations for dental caries (dmft index) were performed by 2 trained and standardized examiners. Socio-demographic, socioeconomic, and behavioral data were self-reported using questionnaires. Multivariate negative binomial regression (NBR) analysis was used. Mean age was 7.49 ± 1.12 years. Boys accounted for 50.1% of the sample. Mean dmft was 3.54 ± 3.13 and caries prevalence (dmft >0) was 77.6%. In the NBR multivariate model (p<0.05), for each year of age, the expected mean dmft decreased by 7.5%. Brushing teeth at least once a day and having received preventive dental care in the last year before data collection were associated with declines in the expected mean dmft by 19.5% and 69.6%, respectively. Presence of dental plaque increased the expected mean dmft by 395.5%. The proportion of students with caries in this sample was high. We found associations between dental caries in the primary dentition and dental plaque, brushing teeth at least once a day, and having received preventive dental care. To improve oral health, school programs and/or age-appropriate interventions need to be developed based on the specific profile of caries experience and the associated risk indicators.

Estimating relative risks in multicenter studies with a small number of centers - which methods to use? A simulation study.

PubMed

Pedroza, Claudia; Truong, Van Thi Thanh

2017-11-02

Analyses of multicenter studies often need to account for center clustering to ensure valid inference. For binary outcomes, it is particularly challenging to properly adjust for center when the number of centers or total sample size is small, or when there are few events per center. Our objective was to evaluate the performance of generalized estimating equation (GEE) log-binomial and Poisson models, generalized linear mixed models (GLMMs) assuming binomial and Poisson distributions, and a Bayesian binomial GLMM to account for center effect in these scenarios. We conducted a simulation study with few centers (≤30) and 50 or fewer subjects per center, using both a randomized controlled trial and an observational study design to estimate relative risk. We compared the GEE and GLMM models with a log-binomial model without adjustment for clustering in terms of bias, root mean square error (RMSE), and coverage. For the Bayesian GLMM, we used informative neutral priors that are skeptical of large treatment effects that are almost never observed in studies of medical interventions. All frequentist methods exhibited little bias, and the RMSE was very similar across the models. The binomial GLMM had poor convergence rates, ranging from 27% to 85%, but performed well otherwise. The results show that both GEE models need to use small sample corrections for robust SEs to achieve proper coverage of 95% CIs. The Bayesian GLMM had similar convergence rates but resulted in slightly more biased estimates for the smallest sample sizes. However, it had the smallest RMSE and good coverage across all scenarios. These results were very similar for both study designs. For the analyses of multicenter studies with a binary outcome and few centers, we recommend adjustment for center with either a GEE log-binomial or Poisson model with appropriate small sample corrections or a Bayesian binomial GLMM with informative priors.

The magnetisation distribution of the Ising model - a new approach

NASA Astrophysics Data System (ADS)

Hakan Lundow, Per; Rosengren, Anders

2010-03-01

A completely new approach to the Ising model in 1 to 5 dimensions is developed. We employ a generalisation of the binomial coefficients to describe the magnetisation distributions of the Ising model. For the complete graph this distribution is exact. For simple lattices of dimensions d=1 and d=5 the magnetisation distributions are remarkably well-fitted by the generalized binomial distributions. For d=4 we are only slightly less successful, while for d=2,3 we see some deviations (with exceptions!) between the generalized binomial and the Ising distribution. The results speak in favour of the generalized binomial distribution's correctness regarding their general behaviour in comparison to the Ising model. A theoretical analysis of the distribution's moments also lends support their being correct asymptotically, including the logarithmic corrections in d=4. The full extent to which they correctly model the Ising distribution, and for which graph families, is not settled though.

Phase transition and information cascade in a voting model

NASA Astrophysics Data System (ADS)

Hisakado, M.; Mori, S.

2010-08-01

In this paper, we introduce a voting model that is similar to a Keynesian beauty contest and analyse it from a mathematical point of view. There are two types of voters—copycat and independent—and two candidates. Our voting model is a binomial distribution (independent voters) doped in a beta binomial distribution (copycat voters). We find that the phase transition in this system is at the upper limit of t, where t is the time (or the number of the votes). Our model contains three phases. If copycats constitute a majority or even half of the total voters, the voting rate converges more slowly than it would in a binomial distribution. If independents constitute the majority of voters, the voting rate converges at the same rate as it would in a binomial distribution. We also study why it is difficult to estimate the conclusion of a Keynesian beauty contest when there is an information cascade.

Abstract knowledge versus direct experience in processing of binomial expressions

PubMed Central

Morgan, Emily; Levy, Roger

2016-01-01

We ask whether word order preferences for binomial expressions of the form A and B (e.g. bread and butter) are driven by abstract linguistic knowledge of ordering constraints referencing the semantic, phonological, and lexical properties of the constituent words, or by prior direct experience with the specific items in questions. Using forced-choice and self-paced reading tasks, we demonstrate that online processing of never-before-seen binomials is influenced by abstract knowledge of ordering constraints, which we estimate with a probabilistic model. In contrast, online processing of highly frequent binomials is primarily driven by direct experience, which we estimate from corpus frequency counts. We propose a trade-off wherein processing of novel expressions relies upon abstract knowledge, while reliance upon direct experience increases with increased exposure to an expression. Our findings support theories of language processing in which both compositional generation and direct, holistic reuse of multi-word expressions play crucial roles. PMID:27776281

Novel formulation of the ℳ model through the Generalized-K distribution for atmospheric optical channels.

PubMed

Garrido-Balsells, José María; Jurado-Navas, Antonio; Paris, José Francisco; Castillo-Vazquez, Miguel; Puerta-Notario, Antonio

2015-03-09

In this paper, a novel and deeper physical interpretation on the recently published Málaga or ℳ statistical distribution is provided. This distribution, which is having a wide acceptance by the scientific community, models the optical irradiance scintillation induced by the atmospheric turbulence. Here, the analytical expressions previously published are modified in order to express them by a mixture of the known Generalized-K and discrete Binomial and Negative Binomial distributions. In particular, the probability density function (pdf) of the ℳ model is now obtained as a linear combination of these Generalized-K pdf, in which the coefficients depend directly on the parameters of the ℳ distribution. In this way, the Málaga model can be physically interpreted as a superposition of different optical sub-channels each of them described by the corresponding Generalized-K fading model and weighted by the ℳ dependent coefficients. The expressions here proposed are simpler than the equations of the original ℳ model and are validated by means of numerical simulations by generating ℳ -distributed random sequences and their associated histogram. This novel interpretation of the Málaga statistical distribution provides a valuable tool for analyzing the performance of atmospheric optical channels for every turbulence condition.

Referent group proximity, social norms, and context: alcohol use in a low-use environment.

PubMed

Cox, Jared M; Bates, Scott C

2011-01-01

The purpose of this study was to investigate the relationship between perceived normative use of alcohol and reported consumption in an environment where relatively little alcohol use occurs. A total of 585 undergraduate students completed an online survey on alcohol use in March 2006. Participants reported personal alcohol use and perceptions of use by "friends," "the average student," and "the average student who drinks." Due to the large number of students reporting zero alcohol use, zero-inflated negative binomial regression was used to analyze the data. Results showed that perceptions of use and beliefs about the acceptability of use by proximal groups were strongly and positively correlated with personal alcohol use. Perceptions of distal groups were either not correlated or were correlated negatively with personal use. These findings suggest that the use of distal referent groups for a social norms campaign in a low-use environment may have paradoxical effects.

Narrow log-periodic modulations in non-Markovian random walks

NASA Astrophysics Data System (ADS)

Diniz, R. M. B.; Cressoni, J. C.; da Silva, M. A. A.; Mariz, A. M.; de Araújo, J. M.

2017-12-01

What are the necessary ingredients for log-periodicity to appear in the dynamics of a random walk model? Can they be subtle enough to be overlooked? Previous studies suggest that long-range damaged memory and negative feedback together are necessary conditions for the emergence of log-periodic oscillations. The role of negative feedback would then be crucial, forcing the system to change direction. In this paper we show that small-amplitude log-periodic oscillations can emerge when the system is driven by positive feedback. Due to their very small amplitude, these oscillations can easily be mistaken for numerical finite-size effects. The models we use consist of discrete-time random walks with strong memory correlations where the decision process is taken from memory profiles based either on a binomial distribution or on a delta distribution. Anomalous superdiffusive behavior and log-periodic modulations are shown to arise in the large time limit for convenient choices of the models parameters.

Identity Conflict and Sexual Risk for Black and Latino YMSM.

PubMed

Corsbie-Massay, Charisse L'Pree; Miller, Lynn C; Christensen, John L; Appleby, Paul R; Godoy, Carlos; Read, Stephen J

2017-06-01

Young (aged 18-30) Black and Latino men who have sex with men are at a higher risk of contracting HIV than their White counterparts. In order to better understand the unique nature of sexual risk-taking, we examined the extent to which ethnic group, ethnic identity, and sexual pride predicted condomless anal sex with casual partners among 161 young men who have sex with men (YMSM) who identify as Black or Latino. Negative binomial regressions were conducted using a cross-sectional design. Sexual pride was a negative predictor of condomless anal sex across all participants, but this effect was moderated by ethnic exploration and ethnic group; the relationship between sexual pride and condomless anal sex was strengthened by greater ethnic exploration among Latino YMSM, and weakened by greater ethnic exploration among Black YMSM. Implications for intersectional identity, identity conflict, and HIV prevention among young gay men of color are discussed.

Using linked household-level data sets to explain consumer response to bovine spongiform encepalopathy (BSE) in Canada.

PubMed

Wang, Xin; Maynard, Leigh J; Butler, J S; Goddard, Ellen W

2011-01-01

Household-level Canadian meat purchases from 2002 to 2008 and a Food Opinions Survey conducted in 2008 were used to explore consumer responses to bovine spongiform encephalopathy (BSE) at the national level in Canada. Consumption in terms of the number of unit purchases was analyzed with a random-effects negative binomial model. In this study, household heterogeneity in meat purchases was partially explained using data from a self-reported food opinions survey. Of special interest was the hypothesis that consumers responded consistently to BSE in a one-time survey and in actual meat purchase behavior spanning years. Regional differences appeared, with consumers in eastern Canada reacting most negatively to BSE. Consumers responded more to the perception that food decision makers are honest about food safety than to the perception that they are knowledgeable, in maintaining beef purchases during BSE events.

Factors related to the number of fast food meals obtained by college meal plan students.

PubMed

Dingman, Deirdre A; Schulz, Mark R; Wyrick, David L; Bibeau, Daniel L; Gupta, Sat N

2014-01-01

This study tested whether days on campus, financial access through a meal plan, and health consciousness were associated with number of meals that college students obtained from fast food restaurants. In April 2013, all students currently enrolled in a meal plan were invited to participate in an online survey (N = 1,246). Students were asked to report the total number of meals eaten in the past week and where they obtained them. Negative binomial regression was used, and it was found that the number of meals obtained from fast food restaurants was positively associated with financial access and negatively associated with health consciousness. An association between days on campus and the number of meals obtained from fast food restaurants was not found. Increasing levels of health consciousness and reducing access to fast food restaurants through flex plans may reduce college students' consumption of fast food.

LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

PubMed

He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

2006-05-01

Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

[Nursing: the meaning of this profession to nurses. A first approach].

PubMed

Luchesi, Luciana Barizon; Santos, Claudia Benedita dos

2005-01-01

In an attempt to understand, tell and, why not, participate a little in the history of Nursing, we proposed to study the prejudices and negative stereotypes that have permeated this profession over time. This is a before-after experimental type of study in a population of adolescents regularly enrolled in the eleventh grade of a Brazilian public school. The intervention took the form of a lecture about the profession and a questionnaire with closed questions which was applied before and after the lecture. Conclusions were based on the results of binomial and McNemar's non-parametric tests for the significance of changes. Although the statistically significant presence of prejudice and negatives stereotypes was not found, the results of the intervention were in line with expectations, since the changes(or tendency towards changes) took place exactly in those subgroups that showed a greater frequency of stereotypes.

A new zero-inflated negative binomial methodology for latent category identification.

PubMed

Blanchard, Simon J; DeSarbo, Wayne S

2013-04-01

We introduce a new statistical procedure for the identification of unobserved categories that vary between individuals and in which objects may span multiple categories. This procedure can be used to analyze data from a proposed sorting task in which individuals may simultaneously assign objects to multiple piles. The results of a synthetic example and a consumer psychology study involving categories of restaurant brands illustrate how the application of the proposed methodology to the new sorting task can account for a variety of categorization phenomena including multiple category memberships and for heterogeneity through individual differences in the saliency of latent category structures.

Probing the statistics of primordial fluctuations and their evolution

NASA Technical Reports Server (NTRS)

Gaztanaga, Enrique; Yokoyama, Jun'ichi

1993-01-01

The statistical distribution of fluctuations on various scales is analyzed in terms of the counts in cells of smoothed density fields, using volume-limited samples of galaxy redshift catalogs. It is shown that the distribution on large scales, with volume average of the two-point correlation function of the smoothed field less than about 0.05, is consistent with Gaussian. Statistics are shown to agree remarkably well with the negative binomial distribution, which has hierarchial correlations and a Gaussian behavior at large scales. If these observed properties correspond to the matter distribution, they suggest that our universe started with Gaussian fluctuations and evolved keeping hierarchial form.

Negative Binomial Fits to Multiplicity Distributions from Central Collisions of (16)O+Cu at 14.6A GeV/c and Intermittency

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.

Definite Integrals, Some Involving Residue Theory Evaluated by Maple Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, Kimiko o

2010-01-01

The calculus of residue is applied to evaluate certain integrals in the range (-{infinity} to {infinity}) using the Maple symbolic code. These integrals are of the form {integral}{sub -{infinity}}{sup {infinity}} cos(x)/[(x{sup 2} + a{sup 2})(x{sup 2} + b{sup 2}) (x{sup 2} + c{sup 2})]dx and similar extensions. The Maple code is also applied to expressions in maximum likelihood estimator moments when sampling from the negative binomial distribution. In general the Maple code approach to the integrals gives correct answers to specified decimal places, but the symbolic result may be extremely long and complex.

On extinction time of a generalized endemic chain-binomial model.

PubMed

Aydogmus, Ozgur

2016-09-01

We considered a chain-binomial epidemic model not conferring immunity after infection. Mean field dynamics of the model has been analyzed and conditions for the existence of a stable endemic equilibrium are determined. The behavior of the chain-binomial process is probabilistically linked to the mean field equation. As a result of this link, we were able to show that the mean extinction time of the epidemic increases at least exponentially as the population size grows. We also present simulation results for the process to validate our analytical findings. Copyright © 2016 Elsevier Inc. All rights reserved.

Solar San Diego: The Impact of Binomial Rate Structures on Real PV Systems; Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

VanGeet, O.; Brown, E.; Blair, T.

2008-05-01

There is confusion in the marketplace regarding the impact of solar photovoltaics (PV) on the user's actual electricity bill under California Net Energy Metering, particularly with binomial tariffs (those that include both demand and energy charges) and time-of-use (TOU) rate structures. The City of San Diego has extensive real-time electrical metering on most of its buildings and PV systems, with interval data for overall consumption and PV electrical production available for multiple years. This paper uses 2007 PV-system data from two city facilities to illustrate the impacts of binomial rate designs. The analysis will determine the energy and demand savingsmore » that the PV systems are achieving relative to the absence of systems. A financial analysis of PV-system performance under various rate structures is presented. The data revealed that actual demand and energy use benefits of binomial tariffs increase in summer months, when solar resources allow for maximized electricity production. In a binomial tariff system, varying on- and semi-peak times can result in approximately $1,100 change in demand charges per month over not having a PV system in place, an approximate 30% cost savings. The PV systems are also shown to have a 30%-50% reduction in facility energy charges in 2007.« less

Comparison and Field Validation of Binomial Sampling Plans for Oligonychus perseae (Acari: Tetranychidae) on Hass Avocado in Southern California.

PubMed

Lara, Jesus R; Hoddle, Mark S

2015-08-01

Oligonychus perseae Tuttle, Baker, & Abatiello is a foliar pest of 'Hass' avocados [Persea americana Miller (Lauraceae)]. The recommended action threshold is 50-100 motile mites per leaf, but this count range and other ecological factors associated with O. perseae infestations limit the application of enumerative sampling plans in the field. Consequently, a comprehensive modeling approach was implemented to compare the practical application of various binomial sampling models for decision-making of O. perseae in California. An initial set of sequential binomial sampling models were developed using three mean-proportion modeling techniques (i.e., Taylor's power law, maximum likelihood, and an empirical model) in combination with two-leaf infestation tally thresholds of either one or two mites. Model performance was evaluated using a robust mite count database consisting of >20,000 Hass avocado leaves infested with varying densities of O. perseae and collected from multiple locations. Operating characteristic and average sample number results for sequential binomial models were used as the basis to develop and validate a standardized fixed-size binomial sampling model with guidelines on sample tree and leaf selection within blocks of avocado trees. This final validated model requires a leaf sampling cost of 30 leaves and takes into account the spatial dynamics of O. perseae to make reliable mite density classifications for a 50-mite action threshold. Recommendations for implementing this fixed-size binomial sampling plan to assess densities of O. perseae in commercial California avocado orchards are discussed. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Depressive Symptoms, Religious Coping, and Cigarette Smoking Among Post-secondary Vocational Students

PubMed Central

Horton, Karissa D.; Loukas, Alexandra

2014-01-01

Depressive symptoms are associated with increased levels of cigarette smoking, yet not every individual experiencing depressive symptoms smokes. This study examined whether religious coping moderated the impact of depressive symptoms on past 30-day cigarette use among a racially/ethnically diverse sample of 963 post-secondary vocational students (46.8% women; mean age = 25 years). Results from negative binomial regression analyses indicated that depressive symptoms increased the likelihood of cigarette smoking (quantity-frequency measure of cigarette use) for female students, whereas positive religious coping decreased the likelihood of smoking for female students. Consistent with religious coping theory and as expected, negative religious coping moderated the depressive symptoms-smoking relationship such that negative religious coping exacerbated the impact of depressive symptoms on cigarette smoking among females. Positive religious coping also moderated the depressive symptoms-cigarette smoking relationship for females. However, contrary to expectations, high levels of positive religious coping exacerbated the likelihood of cigarette smoking among females with high levels of depressive symptoms. Surprisingly, neither depressive symptoms nor positive or negative religious coping contributed to the likelihood of males’ smoking. Study limitations and suggestions for directions in future research are discussed. PMID:23276324

Using the Binomial Series to Prove the Arithmetic Mean-Geometric Mean Inequality

ERIC Educational Resources Information Center

Persky, Ronald L.

2003-01-01

In 1968, Leon Gerber compared (1 + x)[superscript a] to its kth partial sum as a binomial series. His result is stated and, as an application of this result, a proof of the arithmetic mean-geometric mean inequality is presented.

Four Bootstrap Confidence Intervals for the Binomial-Error Model.

ERIC Educational Resources Information Center

Lin, Miao-Hsiang; Hsiung, Chao A.

1992-01-01

Four bootstrap methods are identified for constructing confidence intervals for the binomial-error model. The extent to which similar results are obtained and the theoretical foundation of each method and its relevance and ranges of modeling the true score uncertainty are discussed. (SLD)

Possibility and Challenges of Conversion of Current Virus Species Names to Linnaean Binomials.

PubMed

Postler, Thomas S; Clawson, Anna N; Amarasinghe, Gaya K; Basler, Christopher F; Bavari, Sbina; Benko, Mária; Blasdell, Kim R; Briese, Thomas; Buchmeier, Michael J; Bukreyev, Alexander; Calisher, Charles H; Chandran, Kartik; Charrel, Rémi; Clegg, Christopher S; Collins, Peter L; Juan Carlos, De La Torre; Derisi, Joseph L; Dietzgen, Ralf G; Dolnik, Olga; Dürrwald, Ralf; Dye, John M; Easton, Andrew J; Emonet, Sébastian; Formenty, Pierre; Fouchier, Ron A M; Ghedin, Elodie; Gonzalez, Jean-Paul; Harrach, Balázs; Hewson, Roger; Horie, Masayuki; Jiang, Dàohóng; Kobinger, Gary; Kondo, Hideki; Kropinski, Andrew M; Krupovic, Mart; Kurath, Gael; Lamb, Robert A; Leroy, Eric M; Lukashevich, Igor S; Maisner, Andrea; Mushegian, Arcady R; Netesov, Sergey V; Nowotny, Norbert; Patterson, Jean L; Payne, Susan L; PaWeska, Janusz T; Peters, Clarence J; Radoshitzky, Sheli R; Rima, Bertus K; Romanowski, Victor; Rubbenstroth, Dennis; Sabanadzovic, Sead; Sanfaçon, Hélène; Salvato, Maria S; Schwemmle, Martin; Smither, Sophie J; Stenglein, Mark D; Stone, David M; Takada, Ayato; Tesh, Robert B; Tomonaga, Keizo; Tordo, Noël; Towner, Jonathan S; Vasilakis, Nikos; Volchkov, Viktor E; Wahl-Jensen, Victoria; Walker, Peter J; Wang, Lin-Fa; Varsani, Arvind; Whitfield, Anna E; Zerbini, F Murilo; Kuhn, Jens H

2017-05-01

Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authors of this article expected when conceiving the experiment. [Arenaviridae; binomials; ICTV; International Committee on Taxonomy of Viruses; Mononegavirales; virus nomenclature; virus taxonomy.]. Published by Oxford University Press on behalf of Society of Systematic Biologists 2016. This work is written by a US Government employee and is in the public domain in the US.

The arcsine is asinine: the analysis of proportions in ecology.

PubMed

Warton, David I; Hui, Francis K C

2011-01-01

The arcsine square root transformation has long been standard procedure when analyzing proportional data in ecology, with applications in data sets containing binomial and non-binomial response variables. Here, we argue that the arcsine transform should not be used in either circumstance. For binomial data, logistic regression has greater interpretability and higher power than analyses of transformed data. However, it is important to check the data for additional unexplained variation, i.e., overdispersion, and to account for it via the inclusion of random effects in the model if found. For non-binomial data, the arcsine transform is undesirable on the grounds of interpretability, and because it can produce nonsensical predictions. The logit transformation is proposed as an alternative approach to address these issues. Examples are presented in both cases to illustrate these advantages, comparing various methods of analyzing proportions including untransformed, arcsine- and logit-transformed linear models and logistic regression (with or without random effects). Simulations demonstrate that logistic regression usually provides a gain in power over other methods.

[The reentrant binomial model of nuclear anomalies growth in rhabdomyosarcoma RA-23 cell populations under increasing doze of rare ionizing radiation].

PubMed

Alekseeva, N P; Alekseev, A O; Vakhtin, Iu B; Kravtsov, V Iu; Kuzovatov, S N; Skorikova, T I

2008-01-01

Distributions of nuclear morphology anomalies in transplantable rabdomiosarcoma RA-23 cell populations were investigated under effect of ionizing radiation from 0 to 45 Gy. Internuclear bridges, nuclear protrusions and dumbbell-shaped nuclei were accepted for morphological anomalies. Empirical distributions of the number of anomalies per 100 nuclei were used. The adequate model of reentrant binomial distribution has been found. The sum of binomial random variables with binomial number of summands has such distribution. Averages of these random variables were named, accordingly, internal and external average reentrant components. Their maximum likelihood estimations were received. Statistical properties of these estimations were investigated by means of statistical modeling. It has been received that at equally significant correlation between the radiation dose and the average of nuclear anomalies in cell populations after two-three cellular cycles from the moment of irradiation in vivo the irradiation doze significantly correlates with internal average reentrant component, and in remote descendants of cell transplants irradiated in vitro - with external one.

On Models for Binomial Data with Random Numbers of Trials

PubMed Central

Comulada, W. Scott; Weiss, Robert E.

2010-01-01

Summary A binomial outcome is a count s of the number of successes out of the total number of independent trials n = s + f, where f is a count of the failures. The n are random variables not fixed by design in many studies. Joint modeling of (s, f) can provide additional insight into the science and into the probability π of success that cannot be directly incorporated by the logistic regression model. Observations where n = 0 are excluded from the binomial analysis yet may be important to understanding how π is influenced by covariates. Correlation between s and f may exist and be of direct interest. We propose Bayesian multivariate Poisson models for the bivariate response (s, f), correlated through random effects. We extend our models to the analysis of longitudinal and multivariate longitudinal binomial outcomes. Our methodology was motivated by two disparate examples, one from teratology and one from an HIV tertiary intervention study. PMID:17688514

Spiritual and ceremonial plants in North America: an assessment of Moerman's ethnobotanical database comparing Residual, Binomial, Bayesian and Imprecise Dirichlet Model (IDM) analysis.

PubMed

Turi, Christina E; Murch, Susan J

2013-07-09

Ethnobotanical research and the study of plants used for rituals, ceremonies and to connect with the spirit world have led to the discovery of many novel psychoactive compounds such as nicotine, caffeine, and cocaine. In North America, spiritual and ceremonial uses of plants are well documented and can be accessed online via the University of Michigan's Native American Ethnobotany Database. The objective of the study was to compare Residual, Bayesian, Binomial and Imprecise Dirichlet Model (IDM) analyses of ritual, ceremonial and spiritual plants in Moerman's ethnobotanical database and to identify genera that may be good candidates for the discovery of novel psychoactive compounds. The database was queried with the following format "Family Name AND Ceremonial OR Spiritual" for 263 North American botanical families. Spiritual and ceremonial flora consisted of 86 families with 517 species belonging to 292 genera. Spiritual taxa were then grouped further into ceremonial medicines and items categories. Residual, Bayesian, Binomial and IDM analysis were performed to identify over and under-utilized families. The 4 statistical approaches were in good agreement when identifying under-utilized families but large families (>393 species) were underemphasized by Binomial, Bayesian and IDM approaches for over-utilization. Residual, Binomial, and IDM analysis identified similar families as over-utilized in the medium (92-392 species) and small (<92 species) classes. The families Apiaceae, Asteraceae, Ericacea, Pinaceae and Salicaceae were identified as significantly over-utilized as ceremonial medicines in medium and large sized families. Analysis of genera within the Apiaceae and Asteraceae suggest that the genus Ligusticum and Artemisia are good candidates for facilitating the discovery of novel psychoactive compounds. The 4 statistical approaches were not consistent in the selection of over-utilization of flora. Residual analysis revealed overall trends that were supported by Binomial analysis when separated into small, medium and large families. The Bayesian, Binomial and IDM approaches identified different genera as potentially important. Species belonging to the genus Artemisia and Ligusticum were most consistently identified and may be valuable in future studies of the ethnopharmacology. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Sampling--how big a sample?

PubMed

Aitken, C G

1999-07-01

It is thought that, in a consignment of discrete units, a certain proportion of the units contain illegal material. A sample of the consignment is to be inspected. Various methods for the determination of the sample size are compared. The consignment will be considered as a random sample from some super-population of units, a certain proportion of which contain drugs. For large consignments, a probability distribution, known as the beta distribution, for the proportion of the consignment which contains illegal material is obtained. This distribution is based on prior beliefs about the proportion. Under certain specific conditions the beta distribution gives the same numerical results as an approach based on the binomial distribution. The binomial distribution provides a probability for the number of units in a sample which contain illegal material, conditional on knowing the proportion of the consignment which contains illegal material. This is in contrast to the beta distribution which provides probabilities for the proportion of a consignment which contains illegal material, conditional on knowing the number of units in the sample which contain illegal material. The interpretation when the beta distribution is used is much more intuitively satisfactory. It is also much more flexible in its ability to cater for prior beliefs which may vary given the different circumstances of different crimes. For small consignments, a distribution, known as the beta-binomial distribution, for the number of units in the consignment which are found to contain illegal material, is obtained, based on prior beliefs about the number of units in the consignment which are thought to contain illegal material. As with the beta and binomial distributions for large samples, it is shown that, in certain specific conditions, the beta-binomial and hypergeometric distributions give the same numerical results. However, the beta-binomial distribution, as with the beta distribution, has a more intuitively satisfactory interpretation and greater flexibility. The beta and the beta-binomial distributions provide methods for the determination of the minimum sample size to be taken from a consignment in order to satisfy a certain criterion. The criterion requires the specification of a proportion and a probability.

Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006-2011.

PubMed

Faires, Meredith C; Pearl, David L; Ciccotelli, William A; Berke, Olaf; Reid-Smith, Richard J; Weese, J Scott

2014-05-12

In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007-2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital personnel. The identification of time periods with decreased or increased CDI rates may have been a result of specific hospital events. Understanding the clustering of CDIs can aid in the interpretation of surveillance data and lead to the development of better early detection systems.

Selecting Tools to Model Integer and Binomial Multiplication

ERIC Educational Resources Information Center

Pratt, Sarah Smitherman; Eddy, Colleen M.

2017-01-01

Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

Enumerative and binomial sampling plans for citrus mealybug (Homoptera: pseudococcidae) in citrus groves.

PubMed

Martínez-Ferrer, María Teresa; Ripollés, José Luís; Garcia-Marí, Ferran

2006-06-01

The spatial distribution of the citrus mealybug, Planococcus citri (Risso) (Homoptera: Pseudococcidae), was studied in citrus groves in northeastern Spain. Constant precision sampling plans were designed for all developmental stages of citrus mealybug under the fruit calyx, for late stages on fruit, and for females on trunks and main branches; more than 66, 286, and 101 data sets, respectively, were collected from nine commercial fields during 1992-1998. Dispersion parameters were determined using Taylor's power law, giving aggregated spatial patterns for citrus mealybug populations in three locations of the tree sampled. A significant relationship between the number of insects per organ and the percentage of occupied organs was established using either Wilson and Room's binomial model or Kono and Sugino's empirical formula. Constant precision (E = 0.25) sampling plans (i.e., enumerative plans) for estimating mean densities were developed using Green's equation and the two binomial models. For making management decisions, enumerative counts may be less labor-intensive than binomial sampling. Therefore, we recommend enumerative sampling plans for the use in an integrated pest management program in citrus. Required sample sizes for the range of population densities near current management thresholds, in the three plant locations calyx, fruit, and trunk were 50, 110-330, and 30, respectively. Binomial sampling, especially the empirical model, required a higher sample size to achieve equivalent levels of precision.

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

Estimating the Parameters of the Beta-Binomial Distribution.

ERIC Educational Resources Information Center

Wilcox, Rand R.

1979-01-01

For some situations the beta-binomial distribution might be used to describe the marginal distribution of test scores for a particular population of examinees. Several different methods of approximating the maximum likelihood estimate were investigated, and it was found that the Newton-Raphson method should be used when it yields admissable…

Multilevel Models for Binary Data

ERIC Educational Resources Information Center

Powers, Daniel A.

2012-01-01

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

The gap between suicide characteristics in the print media and in the population.

PubMed

Niederkrotenthaler, Thomas; Till, Benedikt; Herberth, Arno; Voracek, Martin; Kapusta, Nestor D; Etzersdorfer, Elmar; Strauss, Markus; Sonneck, Gernot

2009-08-01

Programmes to educate media professionals about suicide are increasingly established, but information about which suicide cases are most likely to be reported in the mass media is sparse. We applied binomial tests to compare frequencies of social characteristics of all domestic suicides in the 13 largest Austrian print media in 2005 with frequencies of suicide characteristics in the population. Additionally, each reported suicide case was linked to its respective entry in the suicide database. We performed a logistic regression analysis, with presence of an article as outcome, and sex of the suicide case, age, religious affiliation, family status, conduction of an autopsy and location of the suicide as explaining variables. Time of the year and federal state where the suicide happened was controlled for. Binomial tests showed that suicides involving murder or murder attempt were over-represented in the media. Reporting on mental disorders was under-represented. In the regression analysis, the likelihood of a report was negatively associated with the age of suicide cases. Foreign citizenship was a further predictor of a suicide report. The methods of drowning, jumping, shooting and rare methods were more likely to be reported than hanging, which is the most frequent suicide method in Austria. Suicide characteristics in the media are not representative of the population. The identified discrepancies provide a basis for tailor-made education of mass media professionals.

Possibility and Challenges of Conversion of Current Virus Species Names to Linnaean Binomials

PubMed Central

Postler, Thomas S.; Clawson, Anna N.; Amarasinghe, Gaya K.; Basler, Christopher F.; Bavari, Sbina; Benkő, Mária; Blasdell, Kim R.; Briese, Thomas; Buchmeier, Michael J.; Bukreyev, Alexander; Calisher, Charles H.; Chandran, Kartik; Charrel, Rémi; Clegg, Christopher S.; Collins, Peter L.; Juan Carlos, De La Torre; Derisi, Joseph L.; Dietzgen, Ralf G.; Dolnik, Olga; Dürrwald, Ralf; Dye, John M.; Easton, Andrew J.; Emonet, Sébastian; Formenty, Pierre; Fouchier, Ron A. M.; Ghedin, Elodie; Gonzalez, Jean-Paul; Harrach, Balázs; Hewson, Roger; Horie, Masayuki; Jiāng, Dàohóng; Kobinger, Gary; Kondo, Hideki; Kropinski, Andrew M.; Krupovic, Mart; Kurath, Gael; Lamb, Robert A.; Leroy, Eric M.; Lukashevich, Igor S.; Maisner, Andrea; Mushegian, Arcady R.; Netesov, Sergey V.; Nowotny, Norbert; Patterson, Jean L.; Payne, Susan L.; PaWeska, Janusz T.; Peters, Clarence J.; Radoshitzky, Sheli R.; Rima, Bertus K.; Romanowski, Victor; Rubbenstroth, Dennis; Sabanadzovic, Sead; Sanfaçon, Hélène; Salvato, Maria S.; Schwemmle, Martin; Smither, Sophie J.; Stenglein, Mark D.; Stone, David M.; Takada, Ayato; Tesh, Robert B.; Tomonaga, Keizo; Tordo, Noël; Towner, Jonathan S.; Vasilakis, Nikos; Volchkov, Viktor E.; Wahl-Jensen, Victoria; Walker, Peter J.; Wang, Lin-Fa; Varsani, Arvind; Whitfield, Anna E.; Zerbini, F. Murilo; Kuhn, Jens H.

2017-01-01

Abstract Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authors of this article expected when conceiving the experiment. PMID:27798405

Void probability as a function of the void's shape and scale-invariant models

NASA Technical Reports Server (NTRS)

Elizalde, E.; Gaztanaga, E.

1991-01-01

The dependence of counts in cells on the shape of the cell for the large scale galaxy distribution is studied. A very concrete prediction can be done concerning the void distribution for scale invariant models. The prediction is tested on a sample of the CfA catalog, and good agreement is found. It is observed that the probability of a cell to be occupied is bigger for some elongated cells. A phenomenological scale invariant model for the observed distribution of the counts in cells, an extension of the negative binomial distribution, is presented in order to illustrate how this dependence can be quantitatively determined. An original, intuitive derivation of this model is presented.

Analysis of overdispersed count data by mixtures of Poisson variables and Poisson processes.

PubMed

Hougaard, P; Lee, M L; Whitmore, G A

1997-12-01

Count data often show overdispersion compared to the Poisson distribution. Overdispersion is typically modeled by a random effect for the mean, based on the gamma distribution, leading to the negative binomial distribution for the count. This paper considers a larger family of mixture distributions, including the inverse Gaussian mixture distribution. It is demonstrated that it gives a significantly better fit for a data set on the frequency of epileptic seizures. The same approach can be used to generate counting processes from Poisson processes, where the rate or the time is random. A random rate corresponds to variation between patients, whereas a random time corresponds to variation within patients.

The coverage of a random sample from a biological community.

PubMed

Engen, S

1975-03-01

A taxonomic group will frequently have a large number of species with small abundances. When a sample is drawn at random from this group, one is therefore faced with the problem that a large proportion of the species will not be discovered. A general definition of quantitative measures of "sample coverage" is proposed, and the problem of statistical inference is considered for two special cases, (1) the actual total relative abundance of those species that are represented in the sample, and (2) their relative contribution to the information index of diversity. The analysis is based on a extended version of the negative binomial species frequency model. The results are tabulated.

Utilization of accident databases and fuzzy sets to estimate frequency of HazMat transport accidents.

PubMed

Qiao, Yuanhua; Keren, Nir; Mannan, M Sam

2009-08-15

Risk assessment and management of transportation of hazardous materials (HazMat) require the estimation of accident frequency. This paper presents a methodology to estimate hazardous materials transportation accident frequency by utilizing publicly available databases and expert knowledge. The estimation process addresses route-dependent and route-independent variables. Negative binomial regression is applied to an analysis of the Department of Public Safety (DPS) accident database to derive basic accident frequency as a function of route-dependent variables, while the effects of route-independent variables are modeled by fuzzy logic. The integrated methodology provides the basis for an overall transportation risk analysis, which can be used later to develop a decision support system.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.

PubMed

Van den Berge, Koen; Perraudeau, Fanny; Soneson, Charlotte; Love, Michael I; Risso, Davide; Vert, Jean-Philippe; Robinson, Mark D; Dudoit, Sandrine; Clement, Lieven

2018-02-26

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.

Statistical procedures for analyzing mental health services data.

PubMed

Elhai, Jon D; Calhoun, Patrick S; Ford, Julian D

2008-08-15

In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.

Emotional Support, Negative Interaction and DSM IV Lifetime Disorders among Older African Americans: Findings from the National Survey of American Life (NSAL)

PubMed Central

Lincoln, Karen D.; Taylor, Robert Joseph; Bullard, Kai McKeever; Chatters, Linda M.; Himle, Joseph A.; Woodward, Amanda Toler; Jackson, James S.

2010-01-01

Objectives Both emotional support and negative interaction with family members have been linked to mental health. However, few studies have examined the associations between emotional support and negative interaction and psychiatric disorders in late life. This study investigated the relationship between emotional support and negative interaction on lifetime prevalence of mood and anxiety disorders among older African Americans. Design The analyses utilized the National Survey of American Life. Methods Logistic regression and negative binomial regression analyses were used to examine the effect of emotional support and negative interaction with family members on the prevalence of lifetime DSM-IV mood and anxiety disorders. Participants Data from 786 African Americans aged 55 years and older were used. Measurement The DSM-IV World Mental Health Composite International Diagnostic Interview (WMH-CIDI) was used to assess mental disorders. Three dependent variables were investigated: the prevalence of lifetime mood disorders, the prevalence of lifetime anxiety disorders, and the total number of lifetime mood and anxiety disorders. Results Multivariate analysis found that emotional support was not associated with any of the three dependent variables. Negative interaction was significantly and positively associated with the odds of having a lifetime mood disorder, a lifetime anxiety disorder and the number of lifetime mood and anxiety disorders. Conclusions This is the first study to investigate the relationship between emotional support, negative interaction with family members and psychiatric disorders among older African Americans. Negative interaction was a risk factor for mood and anxiety disorders among older African Americans, whereas emotional support was not significant. PMID:20157904

Binomial Coefficients Modulo a Prime--A Visualization Approach to Undergraduate Research

ERIC Educational Resources Information Center

Bardzell, Michael; Poimenidou, Eirini

2011-01-01

In this article we present, as a case study, results of undergraduate research involving binomial coefficients modulo a prime "p." We will discuss how undergraduates were involved in the project, even with a minimal mathematical background beforehand. There are two main avenues of exploration described to discover these binomial…

Using the β-binomial distribution to characterize forest health

Treesearch

S.J. Zarnoch; R.L. Anderson; R.M. Sheffield

1995-01-01

The β-binomial distribution is suggested as a model for describing and analyzing the dichotomous data obtained from programs monitoring the health of forests in the United States. Maximum likelihood estimation of the parameters is given as well as asymptotic likelihood ratio tests. The procedure is illustrated with data on dogwood anthracnose infection (caused...

Integer Solutions of Binomial Coefficients

ERIC Educational Resources Information Center

Gilbertson, Nicholas J.

2016-01-01

A good formula is like a good story, rich in description, powerful in communication, and eye-opening to readers. The formula presented in this article for determining the coefficients of the binomial expansion of (x + y)n is one such "good read." The beauty of this formula is in its simplicity--both describing a quantitative situation…

Confidence Intervals for Weighted Composite Scores under the Compound Binomial Error Model

ERIC Educational Resources Information Center

Kim, Kyung Yong; Lee, Won-Chan

2018-01-01

Reporting confidence intervals with test scores helps test users make important decisions about examinees by providing information about the precision of test scores. Although a variety of estimation procedures based on the binomial error model are available for computing intervals for test scores, these procedures assume that items are randomly…

Discrimination of numerical proportions: A comparison of binomial and Gaussian models.

PubMed

Raidvee, Aire; Lember, Jüri; Allik, Jüri

2017-01-01

Observers discriminated the numerical proportion of two sets of elements (N = 9, 13, 33, and 65) that differed either by color or orientation. According to the standard Thurstonian approach, the accuracy of proportion discrimination is determined by irreducible noise in the nervous system that stochastically transforms the number of presented visual elements onto a continuum of psychological states representing numerosity. As an alternative to this customary approach, we propose a Thurstonian-binomial model, which assumes discrete perceptual states, each of which is associated with a certain visual element. It is shown that the probability β with which each visual element can be noticed and registered by the perceptual system can explain data of numerical proportion discrimination at least as well as the continuous Thurstonian-Gaussian model, and better, if the greater parsimony of the Thurstonian-binomial model is taken into account using AIC model selection. We conclude that Gaussian and binomial models represent two different fundamental principles-internal noise vs. using only a fraction of available information-which are both plausible descriptions of visual perception.

Evaluation of an operational malaria outbreak identification and response system in Mpumalanga Province, South Africa.

PubMed

Coleman, Marlize; Coleman, Michael; Mabuza, Aaron M; Kok, Gerdalize; Coetzee, Maureen; Durrheim, David N

2008-04-27

To evaluate the performance of a novel malaria outbreak identification system in the epidemic prone rural area of Mpumalanga Province, South Africa, for timely identification of malaria outbreaks and guiding integrated public health responses. Using five years of historical notification data, two binomial thresholds were determined for each primary health care facility in the highest malaria risk area of Mpumalanga province. Whenever the thresholds were exceeded at health facility level (tier 1), primary health care staff notified the malaria control programme, which then confirmed adequate stocks of malaria treatment to manage potential increased cases. The cases were followed up at household level to verify the likely source of infection. The binomial thresholds were reviewed at village/town level (tier 2) to determine whether additional response measures were required. In addition, an automated electronic outbreak identification system at town/village level (tier 2) was integrated into the case notification database (tier 3) to ensure that unexpected increases in case notification were not missed.The performance of these binomial outbreak thresholds was evaluated against other currently recommended thresholds using retrospective data. The acceptability of the system at primary health care level was evaluated through structured interviews with health facility staff. Eighty four percent of health facilities reported outbreaks within 24 hours (n = 95), 92% (n = 104) within 48 hours and 100% (n = 113) within 72 hours. Appropriate response to all malaria outbreaks (n = 113, tier 1, n = 46, tier 2) were achieved within 24 hours. The system was positively viewed by all health facility staff. When compared to other epidemiological systems for a specified 12 month outbreak season (June 2003 to July 2004) the binomial exact thresholds produced one false weekly outbreak, the C-sum 12 weekly outbreaks and the mean + 2 SD nine false weekly outbreaks. Exceeding the binomial level 1 threshold triggered an alert four weeks prior to an outbreak, but exceeding the binomial level 2 threshold identified an outbreak as it occurred. The malaria outbreak surveillance system using binomial thresholds achieved its primary goal of identifying outbreaks early facilitating appropriate local public health responses aimed at averting a possible large-scale epidemic in a low, and unstable, malaria transmission setting.

Smisc - A collection of miscellaneous functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Landon Sego, PNNL

2015-08-31

A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAsmore » d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an ".Rdata" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).« less

I Remember You: Independence and the Binomial Model

ERIC Educational Resources Information Center

Levine, Douglas W.; Rockhill, Beverly

2006-01-01

We focus on the problem of ignoring statistical independence. A binomial experiment is used to determine whether judges could match, based on looks alone, dogs to their owners. The experimental design introduces dependencies such that the probability of a given judge correctly matching a dog and an owner changes from trial to trial. We show how…

Possibility and challenges of conversion of current virus species names to Linnaean binomials

USGS Publications Warehouse

Thomas, Postler; Clawson, Anna N.; Amarasinghe, Gaya K.; Basler, Christopher F.; Bavari, Sina; Benko, Maria; Blasdell, Kim R.; Briese, Thomas; Buchmeier, Michael J.; Bukreyev, Alexander; Calisher, Charles H.; Chandran, Kartik; Charrel, Remi; Clegg, Christopher S.; Collins, Peter L.; De la Torre, Juan Carlos; DeRisi, Joseph L.; Dietzgen, Ralf G.; Dolnik, Olga; Durrwald, Ralf; Dye, John M.; Easton, Andrew J.; Emonet, Sebastian; Formenty, Pierre; Fouchier, Ron A. M.; Ghedin, Elodie; Gonzalez, Jean-Paul; Harrach, Balazs; Hewson, Roger; Horie, Masayuki; Jiang, Daohong; Kobinger, Gary P.; Kondo, Hideki; Kropinski, Andrew; Krupovic, Mart; Kurath, Gael; Lamb, Robert A.; Leroy, Eric M.; Lukashevich, Igor S.; Maisner, Andrea; Mushegian, Arcady; Netesov, Sergey V.; Nowotny, Norbert; Patterson, Jean L.; Payne, Susan L.; Paweska, Janusz T.; Peters, C.J.; Radoshitzky, Sheli; Rima, Bertus K.; Romanowski, Victor; Rubbenstroth, Dennis; Sabanadzovic, Sead; Sanfacon, Helene; Salvato , Maria; Schwemmle, Martin; Smither, Sophie J.; Stenglein, Mark; Stone, D.M.; Takada , Ayato; Tesh, Robert B.; Tomonaga, Keizo; Tordo, N.; Towner, Jonathan S.; Vasilakis, Nikos; Volchkov, Victor E.; Jensen, Victoria; Walker, Peter J.; Wang, Lin-Fa; Varsani, Arvind; Whitfield , Anna E.; Zerbini, Francisco Murilo; Kuhn, Jens H.

2017-01-01

Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authors of this article expected when conceiving the experiment.

Predictors and outcomes of non-adherence in patients receiving maintenance hemodialysis.

PubMed

Tohme, Fadi; Mor, Maria K; Pena-Polanco, Julio; Green, Jamie A; Fine, Michael J; Palevsky, Paul M; Weisbord, Steven D

2017-08-01

Predictors of and outcomes associated with non-adherent behavior among patients on chronic hemodialysis (HD) have been incompletely elucidated. We conducted a post hoc analysis of data from the SMILE trial to identify patient factors associated with non-adherence to dialysis-related treatments and the associations of non-adherence with clinical outcomes. We defined non-adherence as missed HD and abbreviated HD. We used negative binomial regression to model the associations of demographic and clinical factors with measures of non-adherence, and negative binomial and Cox regression to analyze the associations of non-adherence with hospitalizations and mortality, respectively. We followed 286 patients for up to 24 months. Factors independently associated with missing HD included Tuesday/Thursday/Saturday HD schedule [incident rate ratio (IRR) 1.85, p < 0.01], current smoking (IRR 2.22, p < 0.01), higher pain score (IRR 1.04, p < 0.01), lower healthy literacy (IRR 3.01, p < 0.01), lower baseline quality of life (IRR 0.89, p = 0.01), and younger age (IRR 1.35, p < 0.01). Factors independently associated with abbreviating HD included dialysis vintage (IRR 1.07, p < 0.01), higher pain score (IRR 1.02, p < 0.01), current non-smoking (IRR 1.32, p = 0.03), and younger age (IRR 1.22, p < 0.01). Abbreviating HD was independently associated with an increased number of total (IRR 1.70, p < 0.01) and ESRD-related (IRR 1.66, p < 0.01) hospitalizations, while missing HD was independently associated with mortality (HR 2.36, p = 0.04). We identified several previously described and novel factors independently associated with non-adherence to HD-related treatments, and independent associations of non-adherence with hospitalization and mortality. These findings should inform the development and implementation of interventions to improve adherence and reduce health resource utilization.

Inhomogeneity of the density of Parascaris spp. eggs in faeces of individual foals and the use of hypothesis testing for treatment decision making.

PubMed

Wilkes, E J A; Cowling, A; Woodgate, R G; Hughes, K J

2016-10-15

Faecal egg counts (FEC) are used widely for monitoring of parasite infection in animals, treatment decision-making and estimation of anthelmintic efficacy. When a single count or sample mean is used as a point estimate of the expectation of the egg distribution over some time interval, the variability in the egg density is not accounted for. Although variability, including quantifying sources, of egg count data has been described, the spatiotemporal distribution of nematode eggs in faeces is not well understood. We believe that statistical inference about the mean egg count for treatment decision-making has not been used previously. The aim of this study was to examine the density of Parascaris eggs in solution and faeces and to describe the use of hypothesis testing for decision-making. Faeces from two foals with Parascaris burdens were mixed with magnesium sulphate solution and 30 McMaster chambers were examined to determine the egg distribution in a well-mixed solution. To examine the distribution of eggs in faeces from an individual animal, three faecal piles from a foal with a known Parascaris burden were obtained, from which 81 counts were performed. A single faecal sample was also collected daily from 20 foals on three consecutive days and a FEC was performed on three separate portions of each sample. As appropriate, Poisson or negative binomial confidence intervals for the distribution mean were calculated. Parascaris eggs in a well-mixed solution conformed to a homogeneous Poisson process, while the egg density in faeces was not homogeneous, but aggregated. This study provides an extension from homogeneous to inhomogeneous Poisson processes, leading to an understanding of why Poisson and negative binomial distributions correspondingly provide a good fit for egg count data. The application of one-sided hypothesis tests for decision-making is presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimating influenza and respiratory syncytial virus-associated mortality in Western Kenya using health and demographic surveillance system data, 2007-2013.

PubMed

Emukule, Gideon O; Spreeuwenberg, Peter; Chaves, Sandra S; Mott, Joshua A; Tempia, Stefano; Bigogo, Godfrey; Nyawanda, Bryan; Nyaguara, Amek; Widdowson, Marc-Alain; van der Velden, Koos; Paget, John W

2017-01-01

Influenza and respiratory syncytial virus (RSV) associated mortality has not been well-established in tropical Africa. We used the negative binomial regression method and the rate-difference method (i.e. deaths during low and high influenza/RSV activity months), to estimate excess mortality attributable to influenza and RSV using verbal autopsy data collected through a health and demographic surveillance system in Western Kenya, 2007-2013. Excess mortality rates were calculated for a) all-cause mortality, b) respiratory deaths (including pneumonia), c) HIV-related deaths, and d) pulmonary tuberculosis (TB) related deaths. Using the negative binomial regression method, the mean annual all-cause excess mortality rate associated with influenza and RSV was 14.1 (95% confidence interval [CI] 0.0-93.3) and 17.1 (95% CI 0.0-111.5) per 100,000 person-years (PY) respectively; and 10.5 (95% CI 0.0-28.5) and 7.3 (95% CI 0.0-27.3) per 100,000 PY for respiratory deaths, respectively. Highest mortality rates associated with influenza were among ≥50 years, particularly among persons with TB (41.6[95% CI 0.0-122.7]); and with RSV were among <5 years. Using the rate-difference method, the excess mortality rate for influenza and RSV was 44.8 (95% CI 36.8-54.4) and 19.7 (95% CI 14.7-26.5) per 100,000 PY, respectively, for all-cause deaths; and 9.6 (95% CI 6.3-14.7) and 6.6 (95% CI 3.9-11.0) per 100,000 PY, respectively, for respiratory deaths. Our study shows a substantial excess mortality associated with influenza and RSV in Western Kenya, especially among children <5 years and older persons with TB, supporting recommendations for influenza vaccination and efforts to develop RSV vaccines.

Effects of Cognition, Function, and Behavioral and Psychological Symptoms on Medicare Expenditures and Health Care Utilization for Persons With Dementia.

PubMed

Jutkowitz, Eric; Kane, Robert L; Dowd, Bryan; Gaugler, Joseph E; MacLehose, Richard F; Kuntz, Karen M

2017-06-01

Clinical features of dementia (cognition, function, and behavioral/psychological symptoms [BPSD]) may differentially affect Medicare expenditures/health care utilization. We linked cross-sectional data from the Aging, Demographics, and Memory Study to Medicare data to evaluate the association between dementia clinical features among those with dementia and Medicare expenditures/health care utilization (n = 234). Cognition was evaluated using the Mini-Mental State Examination (MMSE). Function was evaluated as the number of functional limitations (0-10). BPSD was evaluated as the number of symptoms (0-12). Expenditures were estimated with a generalized linear model (log-link and gamma distribution). Number of hospitalizations, institutional outpatient visits, and physician visits were estimated with a negative binomial regression. Medicare covered skilled nursing days were estimated with a zero-inflated negative binomial model. Cognition and BPSD were not associated with expenditures. Among individuals with less than seven functional limitations, one additional limitation was associated with $123 (95% confidence interval: $19-$227) additional monthly Medicare spending. Better cognition and poorer function were associated with more hospitalizations among those with an MMSE less than three and less than six functional limitations, respectively. BPSD had no effect on hospitalizations. Poorer function and fewer BPSD were associated with more skilled nursing among individuals with one to seven functional limitations and more than four symptoms, respectively. Cognition had no effect on skilled nursing care. No clinical feature was associated with institutional outpatient care. Of individuals with an MMSE less than 15, poorer cognition was associated with fewer physician visits. Among those with more than six functional limitations, poorer function was associated with fewer physician visits. Poorer function, not cognition or BPSD, was associated with higher Medicare expenditures. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Factors associated with dental caries in a group of American Indian children at age 36 months.

PubMed

Warren, John J; Blanchette, Derek; Dawson, Deborah V; Marshall, Teresa A; Phipps, Kathy R; Starr, Delores; Drake, David R

2016-04-01

Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This article reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children, and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28, and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary, and behavioral factors. Nonparametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only noncavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added-sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (P < 0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size, and maternal factors, but further analyses are needed to better understand caries in this population. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effect of Breastfeeding Promotion on Early Childhood Caries and Breastfeeding Duration among 5 Year Old Children in Eastern Uganda: A Cluster Randomized Trial.

PubMed

Birungi, Nancy; Fadnes, Lars T; Okullo, Isaac; Kasangaki, Arabat; Nankabirwa, Victoria; Ndeezi, Grace; Tumwine, James K; Tylleskär, Thorkild; Lie, Stein Atle; Åstrøm, Anne Nordrehaug

2015-01-01

Although several studies have shown short term health benefits of exclusive breastfeeding (EBF), its long term consequences have not been studied extensively in low-income contexts. This study assessed the impact of an EBF promotion initiative for 6 months on early childhood caries (ECC) and breastfeeding duration in children aged 5 years in Mbale, Eastern Uganda. Participants were recruited from the Ugandan site of the PROMISE- EBF cluster randomised trial (ClinicalTrials.gov no: NCT00397150). A total of 765 pregnant women from 24 clusters were included in the ratio 1:1 to receive peer counselled promotion of EBF as the intervention or standard of care. At the 5 year follow-up, ECC was recorded under field conditions using the World Health Organization's decayed missing filled tooth (dmft) index. Adjusted negative binomial and linear regression were used in the analysis. Mean breastfeeding duration in the intervention and control groups (n=417) were 21.8 (CI 20.7-22.9) and 21.3(CI 20.7-21.9) months, respectively. The mean dmft was 1.5 (standard deviation [SD] 2.9) and 1.7 (SD 2.9) in the intervention and control groups, respectively. Corresponding prevalence estimates of ECC were 38% and 41%. Negative binomial regression analysis adjusted for cluster effects and loss-to-follow-up by inverse probability weights (IPW) showed an incidence-rate ratio (IRR) of 0.91 (95% CI 0.65-1.2). Comparing the effect of the trial arm on breastfeeding duration showed a difference in months of 0.48 (-0.72 to 1.7). PROMISE EBF trial did not impact on early childhood caries or breastfeeding duration at 5 years of age. This study contributes to the body of evidence that promotion of exclusive breastfeeding does not raise oral health concerns. However, the high burden of caries calls for efforts to improve the oral health condition in this setting. ClinicalTrials.gov NCT00397150.

Factors associated with the frequency of monitoring of liver enzymes, renal function and lipid laboratory markers among individuals initiating combination antiretroviral therapy: a cohort study.

PubMed

Gillis, Jennifer; Bayoumi, Ahmed M; Burchell, Ann N; Cooper, Curtis; Klein, Marina B; Loutfy, Mona; Machouf, Nima; Montaner, Julio Sg; Tsoukas, Chris; Hogg, Robert S; Raboud, Janet

2015-10-26

As the average age of the HIV-positive population increases, there is increasing need to monitor patients for the development of comorbidities as well as for drug toxicities. We examined factors associated with the frequency of measurement of liver enzymes, renal function tests, and lipid levels among participants of the Canadian Observational Cohort (CANOC) collaboration which follows people who initiated HIV antiretroviral therapy in 2000 or later. We used zero-inflated negative binomial regression models to examine the associations of demographic and clinical characteristics with the rates of measurement during follow-up. Generalized estimating equations with a logit link were used to examine factors associated with gaps of 12 months or more between measurements. Electronic laboratory data were available for 3940 of 7718 CANOC participants. The median duration of electronic follow-up was 3.5 years. The median (interquartile) rates of tests per year were 2.76 (1.60, 3.73), 2.55 (1.44, 3.38) and 1.42 (0.50, 2.52) for liver, renal and lipid parameters, respectively. In multivariable zero-inflated negative binomial regression models, individuals infected through injection drug use (IDU) were significantly less likely to have any measurements. Among participants with at least one measurement, rates of measurement of liver, renal and lipid tests were significantly lower for younger individuals and Aboriginal Peoples. Hepatitis C co-infected individuals with a history of IDU had lower rates of measurement and were at greater risk of having 12 month gaps between measurements. Hepatitis C co-infected participants infected through IDU were at increased risk of gaps in testing, despite publicly funded health care and increased risk of comorbid conditions. This should be taken into consideration in analyses examining factors associated with outcomes based on laboratory parameters.

Random parameter models of interstate crash frequencies by severity, number of vehicles involved, collision and location type.

PubMed

Venkataraman, Narayan; Ulfarsson, Gudmundur F; Shankar, Venky N

2013-10-01

A nine-year (1999-2007) continuous panel of crash histories on interstates in Washington State, USA, was used to estimate random parameter negative binomial (RPNB) models for various aggregations of crashes. A total of 21 different models were assessed in terms of four ways to aggregate crashes, by: (a) severity, (b) number of vehicles involved, (c) crash type, and by (d) location characteristics. The models within these aggregations include specifications for all severities (property damage only, possible injury, evident injury, disabling injury, and fatality), number of vehicles involved (one-vehicle to five-or-more-vehicle), crash type (sideswipe, same direction, overturn, head-on, fixed object, rear-end, and other), and location types (urban interchange, rural interchange, urban non-interchange, rural non-interchange). A total of 1153 directional road segments comprising of the seven Washington State interstates were analyzed, yielding statistical models of crash frequency based on 10,377 observations. These results suggest that in general there was a significant improvement in log-likelihood when using RPNB compared to a fixed parameter negative binomial baseline model. Heterogeneity effects are most noticeable for lighting type, road curvature, and traffic volume (ADT). Median lighting or right-side lighting are linked to increased crash frequencies in many models for more than half of the road segments compared to both-sides lighting. Both-sides lighting thereby appears to generally lead to a safety improvement. Traffic volume has a random parameter but the effect is always toward increasing crash frequencies as expected. However that the effect is random shows that the effect of traffic volume on crash frequency is complex and varies by road segment. The number of lanes has a random parameter effect only in the interchange type models. The results show that road segment-specific insights into crash frequency occurrence can lead to improved design policy and project prioritization. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cocoa Farmers’ Compliance with Safety Precautions in Spraying Agrochemicals and Use of Personal Protective Equipment (PPE) in Cameroon

PubMed Central

2018-01-01

The inability of farmers to comply with essential precautions in the course of spraying agrochemicals remains a policy dilemma, especially in developing countries. The objectives of this paper were to assess compliance of cocoa farmers with agrochemical safety measures, analyse the factors explaining involvement of cocoa farmers in the practice of reusing agrochemical containers and wearing of personal protective equipment (PPE). Data were collected with structured questionnaires from 667 cocoa farmers from the Centre and South West regions in Cameroon. Data analyses were carried out with Probit regression and Negative Binomial regression models. The results showed that average cocoa farm sizes were 3.55 ha and 2.82 ha in South West and Centre regions, respectively, and 89.80% and 42.64% complied with manufacturers’ instructions in the use of insecticides. Eating or drinking while spraying insecticides and fungicides was reported by 4.20% and 5.10% of all farmers in the two regions, respectively. However, 37.78% and 57.57% of all farmers wore hand gloves and safety boots while spraying insecticides in the South West and Centre regions of Cameroon, respectively. In addition, 7.80% of all the farmers would wash agrochemical containers and use them at home, while 42.43% would wash and use them on their farms. Probit regression results showed that probability of reusing agrochemical containers was significantly influenced (p < 0.05) by region of residence of cocoa farmers, gender, possession of formal education and farming as primary occupation. The Negative Binomial regression results showed that the log of number PPE worn was significantly influenced (p < 0.10) by region, marital status, attainment of formal education, good health, awareness of manufacturers’ instructions, land area and contact index. It was among others concluded that efforts to train farmers on the need to be familiar with manufacturers’ instructions and use PPE would enhance their safety in the course of spraying agrochemicals. PMID:29438333

Cocoa Farmers' Compliance with Safety Precautions in Spraying Agrochemicals and Use of Personal Protective Equipment (PPE) in Cameroon.

PubMed

Oyekale, Abayomi Samuel

2018-02-13

The inability of farmers to comply with essential precautions in the course of spraying agrochemicals remains a policy dilemma, especially in developing countries. The objectives of this paper were to assess compliance of cocoa farmers with agrochemical safety measures, analyse the factors explaining involvement of cocoa farmers in the practice of reusing agrochemical containers and wearing of personal protective equipment (PPE). Data were collected with structured questionnaires from 667 cocoa farmers from the Centre and South West regions in Cameroon. Data analyses were carried out with Probit regression and Negative Binomial regression models. The results showed that average cocoa farm sizes were 3.55 ha and 2.82 ha in South West and Centre regions, respectively, and 89.80% and 42.64% complied with manufacturers' instructions in the use of insecticides. Eating or drinking while spraying insecticides and fungicides was reported by 4.20% and 5.10% of all farmers in the two regions, respectively. However, 37.78% and 57.57% of all farmers wore hand gloves and safety boots while spraying insecticides in the South West and Centre regions of Cameroon, respectively. In addition, 7.80% of all the farmers would wash agrochemical containers and use them at home, while 42.43% would wash and use them on their farms. Probit regression results showed that probability of reusing agrochemical containers was significantly influenced ( p < 0.05) by region of residence of cocoa farmers, gender, possession of formal education and farming as primary occupation. The Negative Binomial regression results showed that the log of number PPE worn was significantly influenced ( p < 0.10) by region, marital status, attainment of formal education, good health, awareness of manufacturers' instructions, land area and contact index. It was among others concluded that efforts to train farmers on the need to be familiar with manufacturers' instructions and use PPE would enhance their safety in the course of spraying agrochemicals.

Detection of influenza-like illness aberrations by directly monitoring Pearson residuals of fitted negative binomial regression models.

PubMed

Chan, Ta-Chien; Teng, Yung-Chu; Hwang, Jing-Shiang

2015-02-21

Emerging novel influenza outbreaks have increasingly been a threat to the public and a major concern of public health departments. Real-time data in seamless surveillance systems such as health insurance claims data for influenza-like illnesses (ILI) are ready for analysis, making it highly desirable to develop practical techniques to analyze such readymade data for outbreak detection so that the public can receive timely influenza epidemic warnings. This study proposes a simple and effective approach to analyze area-based health insurance claims data including outpatient and emergency department (ED) visits for early detection of any aberrations of ILI. The health insurance claims data during 2004-2009 from a national health insurance research database were used for developing early detection methods. The proposed approach fitted the daily new ILI visits and monitored the Pearson residuals directly for aberration detection. First, negative binomial regression was used for both outpatient and ED visits to adjust for potentially influential factors such as holidays, weekends, seasons, temporal dependence and temperature. Second, if the Pearson residuals exceeded 1.96, aberration signals were issued. The empirical validation of the model was done in 2008 and 2009. In addition, we designed a simulation study to compare the time of outbreak detection, non-detection probability and false alarm rate between the proposed method and modified CUSUM. The model successfully detected the aberrations of 2009 pandemic (H1N1) influenza virus in northern, central and southern Taiwan. The proposed approach was more sensitive in identifying aberrations in ED visits than those in outpatient visits. Simulation studies demonstrated that the proposed approach could detect the aberrations earlier, and with lower non-detection probability and mean false alarm rate in detecting aberrations compared to modified CUSUM methods. The proposed simple approach was able to filter out temporal trends, adjust for temperature, and issue warning signals for the first wave of the influenza epidemic in a timely and accurate manner.

Differential Associations of UPPS-P Impulsivity Traits With Alcohol Problems.

PubMed

McCarty, Kayleigh N; Morris, David H; Hatz, Laura E; McCarthy, Denis M

2017-07-01

The UPPS-P model posits that impulsivity comprises five factors: positive urgency, negative urgency, lack of planning, lack of perseverance, and sensation seeking. Negative and positive urgency are the traits most consistently associated with alcohol problems. However, previous work has examined alcohol problems either individually or in the aggregate, rather than examining multiple problem domains simultaneously. Recent work has also questioned the utility of distinguishing between positive and negative urgency, as this distinction did not meaningfully differ in predicting domains of psychopathology. The aims of this study were to address these issues by (a) testing unique associations of UPPS-P with specific domains of alcohol problems and (b) determining the utility of distinguishing between positive and negative urgency as risk factors for specific alcohol problems. Associations between UPPS-P traits and alcohol problem domains were examined in two cross-sectional data sets using negative binomial regression models. In both samples, negative urgency was associated with social/interpersonal, self-perception, risky behaviors, and blackout drinking problems. Positive urgency was associated with academic/occupational and physiological dependence problems. Both urgency traits were associated with impaired control and self-care problems. Associations for other UPPS-P traits did not replicate across samples. Results indicate that negative and positive urgency have differential associations with alcohol problem domains. Results also suggest a distinction between the type of alcohol problems associated with these traits-negative urgency was associated with problems experienced during a drinking episode, whereas positive urgency was associated with alcohol problems that result from longer-term drinking trends.

Influx of multidrug-resistant organisms by country-to-country transfer of patients.

PubMed

Mutters, Nico T; Günther, Frank; Sander, Anja; Mischnik, Alexander; Frank, Uwe

2015-10-28

Multidrug-resistant organisms (MDRO) are a worldwide problem. International migration and travel facilitate the spread of MDRO. Therefore the goal of our study was to assess the risk of influx of MDRO from patients transferred to one of Central Europe's largest hospitals from abroad. A mono-centre study was conducted. All patients transferred from other countries were screened; additional data was collected on comorbidities, etc. Presence of carbapenemases of multidrug-resistant Gram-negatives was confirmed by PCR. The association between length of stay, being colonized and/or infected by a MDRO, country of origin, diagnosis and other factors was assessed by binomial regression analyses. From 2012 to 2013, one fifth of all patients were colonized with MDRO (Methicillin-resistant Staphylococcus aureus [4.1 %], Vancomycin-resistant Enterococci [2.9 %], multidrug-resistant Gram-negatives [12.8 %] and extensively drug-resistant Gram-negatives [3.4 %]). The Gram-negatives carried a variety of carbapenemases including OXA, VIM, KPC and NDM. The length of stay was significantly prolonged by 77.2 % in patients colonized with a MDRO, compared to those not colonized (p<0.0001). Country-to-Country transfer of patients to European hospitals represents a high risk of introduction of MDRO and infection control specialists should endorse containment and screening measures.

How does the emotive content of televised anti-smoking mass media campaigns influence monthly calls to the NHS Stop Smoking helpline in England?

PubMed

Richardson, Sol; Langley, Tessa; Szatkowski, Lisa; Sims, Michelle; Gilmore, Anna; McNeill, Ann; Lewis, Sarah

2014-12-01

To investigate the effects of different types of televised mass media campaign content on calls to the English NHS Stop Smoking helpline. We used UK government-funded televised tobacco control campaigns from April 2005 to April 2010, categorised as either "positive" (eliciting happiness, satisfaction or hope) or "negative" (eliciting fear, guilt or disgust). We built negative binomial generalised additive models (GAMs) with linear and smooth terms for monthly per capita exposure to each campaign type (expressed as Gross Ratings Points, or GRPs) to determine their effect on calls in the same month. We adjusted for seasonal trends, inflation-adjusted weighted average cigarette prices and other tobacco control policies. We found non-linear associations between exposure to positive and negative emotive campaigns and quitline calls. The rate of calls increased more than 50% as exposure to positive campaigns increased from 0 to 400 GRPs (rate ratio: 1.58, 95% CI: 1.25-2.01). An increase in calls in response to negative emotive campaigns was only apparent after monthly exposure exceeded 400 GRPs. While positive campaigns were most effective at increasing quitline calls, those with negative emotive content were also found to impact on call rates but only at higher levels of exposure. Copyright © 2014. Published by Elsevier Inc.

Hospital support services and the impacts of outsourcing on occupational health and safety.

PubMed

Siganporia, Pearl; Astrakianakis, George; Alamgir, Hasanat; Ostry, Aleck; Nicol, Anne-Marie; Koehoorn, Mieke

2016-10-01

Outsourcing labor is linked to negative impacts on occupational health and safety (OHS). In British Columbia, Canada, provincial health care service providers outsource support services such as cleaners and food service workers (CFSWs) to external contractors. This study investigates the impact of outsourcing on the occupational health safety of hospital CFSWs through a mixed methods approach. Worker's compensation data for hospital CFSWs were analyzed by negative binomial and multiple linear regressions supplemented by iterative thematic analysis of telephone interviews of the same job groups. Non-significant decreases in injury rates and days lost per injury were observed in outsourced CFSWs post outsourcing. Significant decreases (P < 0.05) were observed in average costs per injury for cleaners post outsourcing. Outsourced workers interviewed implied instances of underreporting workplace injuries. This mixed methods study describes the impact of outsourcing on OHS of healthcare workers in British Columbia. Results will be helpful for policy-makers and workplace regulators to assess program effectiveness for outsourced workers.

Hospital support services and the impacts of outsourcing on occupational health and safety

PubMed Central

Alamgir, Hasanat; Ostry, Aleck; Nicol, Anne-Marie; Koehoorn, Mieke

2016-01-01

Background Outsourcing labor is linked to negative impacts on occupational health and safety (OHS). In British Columbia, Canada, provincial health care service providers outsource support services such as cleaners and food service workers (CFSWs) to external contractors. Objectives This study investigates the impact of outsourcing on the occupational health safety of hospital CFSWs through a mixed methods approach. Methods Worker’s compensation data for hospital CFSWs were analyzed by negative binomial and multiple linear regressions supplemented by iterative thematic analysis of telephone interviews of the same job groups. Results Non-significant decreases in injury rates and days lost per injury were observed in outsourced CFSWs post outsourcing. Significant decreases (P < 0.05) were observed in average costs per injury for cleaners post outsourcing. Outsourced workers interviewed implied instances of underreporting workplace injuries. Conclusions This mixed methods study describes the impact of outsourcing on OHS of healthcare workers in British Columbia. Results will be helpful for policy-makers and workplace regulators to assess program effectiveness for outsourced workers. PMID:27696988

Supply-side response to declining heroin purity: fentanyl overdose episode in New Jersey.

PubMed

Hempstead, Katherine; Yildirim, Emel O

2014-06-01

The inelastic price demand observations characteristic of illegal drug markets have led to the conclusion that the burden of a negative supply shock would be completely reflected to consumers. This paper argues that the increasing availability of prescription opioids may threaten heroin sellers' profit margin and force them to find alternative methods to compensate buyers in the event of a supply shock. We investigate the 2006 fentanyl overdose episode in New Jersey and argue that the introduction of non-pharmaceutical fentanyl, its spatial distribution, and the timing of overdose deaths may have been related to trends in heroin purity. Using medical examiner data, as well as data from the Drug Enforcement Administration, Office of Diversion Control on retail sales of prescription opioids in a negative binomial specification, we show that month-to-month fluctuations in heroin purity have a significant effect on fentanyl-related overdoses, particularly in those areas where prescription opioids are highly available. Copyright © 2013 John Wiley & Sons, Ltd.

Single- and multiple-pulse noncoherent detection statistics associated with partially developed speckle.

PubMed

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.

Alcohol expectancies and alcohol outcomes: effects of the use of protective behavioral strategies.

PubMed

Grazioli, Véronique S; Lewis, Melissa A; Garberson, Lisa A; Fossos-Wong, Nicole; Lee, Christine M; Larimer, Mary E

2015-05-01

Alcohol expectancies (AEs) are positively associated with drinking behaviors, whereas the use of protective behavioural strategies (PBS) is negatively related to alcohol outcomes among young adults. PBS have been shown to weaken relationships between some alcohol risk factors and alcohol outcomes. This study aimed to examine longitudinally the moderating effect of PBS on the relationships between AEs and alcohol outcomes among young adults. Participants (N = 188; 61.7% female) were U.S. young adults participating in a larger longitudinal study. Measures of PBS, AEs, alcohol use, and related consequences were used from the baseline and 12-month follow-up assessments. Negative binomial hurdle models found that PBS (total score) significantly moderated the relationship between positive AEs and consequences, such that among high school seniors endorsing higher positive AEs, those using more PBS in high school reported fewer negative consequences 1 year later. PBS (Manner of Drinking) also moderated the relationship between negative AEs and alcohol use, revealing the use of PBS in high school as having a protective function against later drinking among participants with high positive AEs. Last, PBS (Serious Harm Reduction) significantly moderated the associations between positive AEs and alcohol use and between negative AEs and consequences, such that participants with higher AEs and higher PBS use in high school were at greatest risk for drinking and experiencing negative consequences later. Overall, these findings suggest that PBS use may be protective by weakening relationships between positive AEs and alcohol outcomes. Limitations and future directions are discussed.

Raw and Central Moments of Binomial Random Variables via Stirling Numbers

ERIC Educational Resources Information Center

Griffiths, Martin

2013-01-01

We consider here the problem of calculating the moments of binomial random variables. It is shown how formulae for both the raw and the central moments of such random variables may be obtained in a recursive manner utilizing Stirling numbers of the first kind. Suggestions are also provided as to how students might be encouraged to explore this…

Using beta binomials to estimate classification uncertainty for ensemble models.

PubMed

Clark, Robert D; Liang, Wenkel; Lee, Adam C; Lawless, Michael S; Fraczkiewicz, Robert; Waldman, Marvin

2014-01-01

Quantitative structure-activity (QSAR) models have enormous potential for reducing drug discovery and development costs as well as the need for animal testing. Great strides have been made in estimating their overall reliability, but to fully realize that potential, researchers and regulators need to know how confident they can be in individual predictions. Submodels in an ensemble model which have been trained on different subsets of a shared training pool represent multiple samples of the model space, and the degree of agreement among them contains information on the reliability of ensemble predictions. For artificial neural network ensembles (ANNEs) using two different methods for determining ensemble classification - one using vote tallies and the other averaging individual network outputs - we have found that the distribution of predictions across positive vote tallies can be reasonably well-modeled as a beta binomial distribution, as can the distribution of errors. Together, these two distributions can be used to estimate the probability that a given predictive classification will be in error. Large data sets comprised of logP, Ames mutagenicity, and CYP2D6 inhibition data are used to illustrate and validate the method. The distributions of predictions and errors for the training pool accurately predicted the distribution of predictions and errors for large external validation sets, even when the number of positive and negative examples in the training pool were not balanced. Moreover, the likelihood of a given compound being prospectively misclassified as a function of the degree of consensus between networks in the ensemble could in most cases be estimated accurately from the fitted beta binomial distributions for the training pool. Confidence in an individual predictive classification by an ensemble model can be accurately assessed by examining the distributions of predictions and errors as a function of the degree of agreement among the constituent submodels. Further, ensemble uncertainty estimation can often be improved by adjusting the voting or classification threshold based on the parameters of the error distribution. Finally, the profiles for models whose predictive uncertainty estimates are not reliable provide clues to that effect without the need for comparison to an external test set.

Performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data.

PubMed

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.

A crash-prediction model for multilane roads.

PubMed

Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra

2007-07-01

Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.

DEsingle for detecting three types of differential expression in single-cell RNA-seq data.

PubMed

Miao, Zhun; Deng, Ke; Wang, Xiaowo; Zhang, Xuegong

2018-04-24

The excessive amount of zeros in single-cell RNA-seq data include "real" zeros due to the on-off nature of gene transcription in single cells and "dropout" zeros due to technical reasons. Existing differential expression (DE) analysis methods cannot distinguish these two types of zeros. We developed an R package DEsingle which employed Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect 3 types of DE genes in single-cell RNA-seq data with higher accuracy. The R package DEsingle is freely available at https://github.com/miaozhun/DEsingle and is under Bioconductor's consideration now. zhangxg@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online.

AMP: Assembly Matching Pursuit.

PubMed

Biswas, S; Jojic, V

2013-01-01

Metagenomics, the study of the total genetic material isolated from a biological host, promises to reveal host-microbe or microbe-microbe interactions that may help to personalize medicine or improve agronomic practice. We introduce a method that discovers metagenomic units (MGUs) relevant for phenotype prediction through sequence-based dictionary learning. The method aggregates patient-specific dictionaries and estimates MGU abundances in order to summarize a whole population and yield universally predictive biomarkers. We analyze the impact of Gaussian, Poisson, and Negative Binomial read count models in guiding dictionary construction by examining classification efficiency on a number of synthetic datasets and a real dataset from Ref. 1. Each outperforms standard methods of dictionary composition, such as random projection and orthogonal matching pursuit. Additionally, the predictive MGUs they recover are biologically relevant.

A review on models for count data with extra zeros

NASA Astrophysics Data System (ADS)

Zamri, Nik Sarah Nik; Zamzuri, Zamira Hasanah

2017-04-01

Typically, the zero inflated models are usually used in modelling count data with excess zeros. The existence of the extra zeros could be structural zeros or random which occur by chance. These types of data are commonly found in various disciplines such as finance, insurance, biomedical, econometrical, ecology, and health sciences. As found in the literature, the most popular zero inflated models used are zero inflated Poisson and zero inflated negative binomial. Recently, more complex models have been developed to account for overdispersion and unobserved heterogeneity. In addition, more extended distributions are also considered in modelling data with this feature. In this paper, we review related literature, provide a recent development and summary on models for count data with extra zeros.

The Association between Romantic Relationships and Delinquency in Adolescence and Young Adulthood

PubMed Central

Cui, Ming; Ueno, Koji; Fincham, Frank D.; Donnellan, M. Brent; Wickrama, K. A. S.

2011-01-01

This study examined the association between romantic relationships and delinquency in adolescence and young adulthood. Using a large, longitudinal, and nationally representative sample, results from negative binomial regressions showed a positive association between romantic involvement and delinquency in adolescence. Further, the cumulative number of romantic relationships from adolescence to young adulthood was positively related to delinquency in young adulthood even controlling for earlier delinquency in adolescence. These analyses also controlled for the effects of participant gender, age at initial assessment, puberty, race/ethnicity, and other demographic characteristics (e.g., family structure and parents’ education). Findings are discussed in terms of their implications for understanding the role of romantic relationships in the development of young people and for stimulating future research questions. PMID:22984343

Factors affecting road mortality of white-tailed deer in eastern South Dakota

USGS Publications Warehouse

Grovenburg, Troy W.; Jenks, Jonathan A.; Klaver, Robert W.; Monteith, Kevin L.; Galster, Dwight H.; Schauer, Ron J.; Morlock, Wilbert W.; Delger, Joshua A.

2008-01-01

White-tailed deer (Odocoileus virginianus) mortalities (n = 4,433) caused by collisions with automobiles during 2003 were modeled in 35 counties in eastern South Dakota. Seventeen independent variables and 5 independent variable interactions were evaluated to explain deer mortalities. A negative binomial regression model (Ln Y = 1.25 – 0.12 [percentage tree coverage] + 0.0002 [county area] + 5.39 [county hunter success rate] + 0.0023 [vehicle proxy 96–104 km/hr roads], model deviance = 33.43, χ2 = 27.53, df = 27) was chosen using a combination of a priori model selection and AICc. Management options include use of the model to predict road mortalities and to increase the number of hunting licenses, which could result in fewer DVCs.

Void probability as a function of the void's shape and scale-invariant models. [in studies of spacial galactic distribution

NASA Technical Reports Server (NTRS)

Elizalde, E.; Gaztanaga, E.

1992-01-01

The dependence of counts in cells on the shape of the cell for the large scale galaxy distribution is studied. A very concrete prediction can be done concerning the void distribution for scale invariant models. The prediction is tested on a sample of the CfA catalog, and good agreement is found. It is observed that the probability of a cell to be occupied is bigger for some elongated cells. A phenomenological scale invariant model for the observed distribution of the counts in cells, an extension of the negative binomial distribution, is presented in order to illustrate how this dependence can be quantitatively determined. An original, intuitive derivation of this model is presented.

Demonstration of fundamental statistics by studying timing of electronics signals in a physics-based laboratory

NASA Astrophysics Data System (ADS)

Beach, Shaun E.; Semkow, Thomas M.; Remling, David J.; Bradt, Clayton J.

2017-07-01

We have developed accessible methods to demonstrate fundamental statistics in several phenomena, in the context of teaching electronic signal processing in a physics-based college-level curriculum. A relationship between the exponential time-interval distribution and Poisson counting distribution for a Markov process with constant rate is derived in a novel way and demonstrated using nuclear counting. Negative binomial statistics is demonstrated as a model for overdispersion and justified by the effect of electronic noise in nuclear counting. The statistics of digital packets on a computer network are shown to be compatible with the fractal-point stochastic process leading to a power-law as well as generalized inverse Gaussian density distributions of time intervals between packets.

Non-normal Distributions Commonly Used in Health, Education, and Social Sciences: A Systematic Review

PubMed Central

Bono, Roser; Blanca, María J.; Arnau, Jaume; Gómez-Benito, Juana

2017-01-01

Statistical analysis is crucial for research and the choice of analytical technique should take into account the specific distribution of data. Although the data obtained from health, educational, and social sciences research are often not normally distributed, there are very few studies detailing which distributions are most likely to represent data in these disciplines. The aim of this systematic review was to determine the frequency of appearance of the most common non-normal distributions in the health, educational, and social sciences. The search was carried out in the Web of Science database, from which we retrieved the abstracts of papers published between 2010 and 2015. The selection was made on the basis of the title and the abstract, and was performed independently by two reviewers. The inter-rater reliability for article selection was high (Cohen’s kappa = 0.84), and agreement regarding the type of distribution reached 96.5%. A total of 262 abstracts were included in the final review. The distribution of the response variable was reported in 231 of these abstracts, while in the remaining 31 it was merely stated that the distribution was non-normal. In terms of their frequency of appearance, the most-common non-normal distributions can be ranked in descending order as follows: gamma, negative binomial, multinomial, binomial, lognormal, and exponential. In addition to identifying the distributions most commonly used in empirical studies these results will help researchers to decide which distributions should be included in simulation studies examining statistical procedures. PMID:28959227

Generalized empirical Bayesian methods for discovery of differential data in high-throughput biology.

PubMed

Hardcastle, Thomas J

2016-01-15

High-throughput data are now commonplace in biological research. Rapidly changing technologies and application mean that novel methods for detecting differential behaviour that account for a 'large P, small n' setting are required at an increasing rate. The development of such methods is, in general, being done on an ad hoc basis, requiring further development cycles and a lack of standardization between analyses. We present here a generalized method for identifying differential behaviour within high-throughput biological data through empirical Bayesian methods. This approach is based on our baySeq algorithm for identification of differential expression in RNA-seq data based on a negative binomial distribution, and in paired data based on a beta-binomial distribution. Here we show how the same empirical Bayesian approach can be applied to any parametric distribution, removing the need for lengthy development of novel methods for differently distributed data. Comparisons with existing methods developed to address specific problems in high-throughput biological data show that these generic methods can achieve equivalent or better performance. A number of enhancements to the basic algorithm are also presented to increase flexibility and reduce computational costs. The methods are implemented in the R baySeq (v2) package, available on Bioconductor http://www.bioconductor.org/packages/release/bioc/html/baySeq.html. tjh48@cam.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Quantification of integrated HIV DNA by repetitive-sampling Alu-HIV PCR on the basis of poisson statistics.

PubMed

De Spiegelaere, Ward; Malatinkova, Eva; Lynch, Lindsay; Van Nieuwerburgh, Filip; Messiaen, Peter; O'Doherty, Una; Vandekerckhove, Linos

2014-06-01

Quantification of integrated proviral HIV DNA by repetitive-sampling Alu-HIV PCR is a candidate virological tool to monitor the HIV reservoir in patients. However, the experimental procedures and data analysis of the assay are complex and hinder its widespread use. Here, we provide an improved and simplified data analysis method by adopting binomial and Poisson statistics. A modified analysis method on the basis of Poisson statistics was used to analyze the binomial data of positive and negative reactions from a 42-replicate Alu-HIV PCR by use of dilutions of an integration standard and on samples of 57 HIV-infected patients. Results were compared with the quantitative output of the previously described Alu-HIV PCR method. Poisson-based quantification of the Alu-HIV PCR was linearly correlated with the standard dilution series, indicating that absolute quantification with the Poisson method is a valid alternative for data analysis of repetitive-sampling Alu-HIV PCR data. Quantitative outputs of patient samples assessed by the Poisson method correlated with the previously described Alu-HIV PCR analysis, indicating that this method is a valid alternative for quantifying integrated HIV DNA. Poisson-based analysis of the Alu-HIV PCR data enables absolute quantification without the need of a standard dilution curve. Implementation of the CI estimation permits improved qualitative analysis of the data and provides a statistical basis for the required minimal number of technical replicates. © 2014 The American Association for Clinical Chemistry.

Orchestrating Semiotic Leaps from Tacit to Cultural Quantitative Reasoning--The Case of Anticipating Experimental Outcomes of a Quasi-Binomial Random Generator

ERIC Educational Resources Information Center

Abrahamson, Dor

2009-01-01

This article reports on a case study from a design-based research project that investigated how students make sense of the disciplinary tools they are taught to use, and specifically, what personal, interpersonal, and material resources support this process. The probability topic of binomial distribution was selected due to robust documentation of…

Children at risk: A comparison of child pedestrian traffic collisions in Santiago, Chile, and Seoul, South Korea.

PubMed

Blazquez, Carola; Lee, Jae Seung; Zegras, Christopher

2016-01-01

We examine and compare pedestrian-vehicle collisions and injury outcomes involving school-age children between 5 and 18 years of age in the capital cities of Santiago, Chile, and Seoul, South Korea. We conduct descriptive analysis of the child pedestrian-vehicle collision (P-VC) data (904 collisions for Santiago and 3,505 for Seoul) reported by the police between 2010 and 2011. We also statistically analyze factors associated with child P-VCs, by both incident severity and age group, using 3 regression models: negative binomial, probit, and spatial lag models. Descriptive statistics suggest that child pedestrians in Seoul have a higher risk of being involved in traffic crashes than their counterparts in Santiago. However, in Seoul a greater proportion of children are unharmed as a result of these incidents, whereas more child pedestrians are killed in Santiago. Younger children in Seoul suffer more injuries from P-VCs than in Santiago. The majority of P-VCs in both cities tend to occur in the afternoon and evening, at intersections in Santiago and at midblock locations in Seoul. Our model results suggest that the resident population of children is positively associated with P-VCs in both cities, and school concentrations apparently increase P-VC risk among older children in Santiago. Bus stops are associated with higher P-VCs in Seoul, and subway stations relate to higher P-VCs among older children in Santiago. Zone-level land use mix was negatively related to child P-VCs in Seoul but not in Santiago. Arterial roads are associated with fewer P-VCs, especially for younger children in both cities. A share of collector roads is associated with increased P-VCs in Seoul but fewer P-VCs in Santiago. Hilliness is related to fewer P-VCs in both cities. Differences in these model results for Santiago and Seoul warrant additional analysis, as do the differences in results across model type (negative binomial versus spatial lag models). To reduce child P-VCs, this study suggests the need to assess subway station and bus stop area conditions in Santiago and Seoul, respectively; areas with high density of schools in Santiago; areas with greater concentrations of children in both cities; and collector roads in Seoul.

Enumerative and binomial sequential sampling plans for the multicolored Asian lady beetle (Coleoptera: Coccinellidae) in wine grapes.

PubMed

Galvan, T L; Burkness, E C; Hutchison, W D

2007-06-01

To develop a practical integrated pest management (IPM) system for the multicolored Asian lady beetle, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), in wine grapes, we assessed the spatial distribution of H. axyridis and developed eight sampling plans to estimate adult density or infestation level in grape clusters. We used 49 data sets collected from commercial vineyards in 2004 and 2005, in Minnesota and Wisconsin. Enumerative plans were developed using two precision levels (0.10 and 0.25); the six binomial plans reflected six unique action thresholds (3, 7, 12, 18, 22, and 31% of cluster samples infested with at least one H. axyridis). The spatial distribution of H. axyridis in wine grapes was aggregated, independent of cultivar and year, but it was more randomly distributed as mean density declined. The average sample number (ASN) for each sampling plan was determined using resampling software. For research purposes, an enumerative plan with a precision level of 0.10 (SE/X) resulted in a mean ASN of 546 clusters. For IPM applications, the enumerative plan with a precision level of 0.25 resulted in a mean ASN of 180 clusters. In contrast, the binomial plans resulted in much lower ASNs and provided high probabilities of arriving at correct "treat or no-treat" decisions, making these plans more efficient for IPM applications. For a tally threshold of one adult per cluster, the operating characteristic curves for the six action thresholds provided binomial sequential sampling plans with mean ASNs of only 19-26 clusters, and probabilities of making correct decisions between 83 and 96%. The benefits of the binomial sampling plans are discussed within the context of improving IPM programs for wine grapes.

Relation between social information processing and intimate partner violence in dating couples.

PubMed

Setchell, Sarah; Fritz, Patti Timmons; Glasgow, Jillian

2017-07-01

We used couple-level data to predict physical acts of intimate partner violence (IPV) from self-reported negative emotions and social information-processing (SIP) abilities among 100 dating couples (n = 200; mean age = 21.45 years). Participants read a series of hypothetical conflict situation vignettes and responded to questionnaires to assess negative emotions and various facets of SIP including attributions for partner behavior, generation of response alternatives, and response selection. We conducted a series of negative binomial mixed-model regressions based on the actor-partner interdependence model (APIM; Kenny, Kashy, & Cook, 2006, Dyadic data analysis. New York, NY: Guilford Press). There were significant results for the response generation and negative emotion models. Participants who generated fewer coping response alternatives were at greater risk of victimization (actor effect). Women were at greater risk of victimization if they had partners who generated fewer coping response alternatives (sex by partner interaction effect). Generation of less competent coping response alternatives predicted greater risk of perpetration among men, whereas generation of more competent coping response alternatives predicted greater risk of victimization among women (sex by actor interaction effects). Two significant actor by partner interaction effects were found for the negative emotion models. Participants who reported discrepant levels of negative emotions from their partners were at greatest risk of perpetration. Participants who reported high levels of negative emotions were at greatest risk of victimization if they had partners who reported low levels of negative emotions. This research has implications for researchers and clinicians interested in addressing the problem of IPV. Aggr. Behav. 43:329-341, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A form of 'parental presence/absence' (PPA) technique for the child patient with dental behaviour management problems.

PubMed

Kotsanos, N; Coolidge, T; Velonis, D; Arapostathis, K N

2009-06-01

This paper reports on the use of early introduction of a specific parental presence/absence (PPA) behavioural technique to manage the initially uncooperative child. Using a prospective design, 440 healthy children aged 3 to 10 years visited a paediatric dental practice within 33 months. Children exhibiting initially Frankl 'negative' and 'definitely negative' behaviour were empathically offered parental presence only if they were cooperative. Otherwise, the parent stepped out until behaviour improvement. t-tests and Chi-square tests were used to compare characteristics of initially cooperative and uncooperative children, as well as proportions of parents who were asked to leave the surgery. The technique's success was assessed by a one sample binomial test. 75 of the children presented as Frankl either 'negative' (30) or 'definitely negative' (45) at their first visit; 70 (93.3%, p<0.001) responded to the PPA technique by displaying positive behaviour as their first visit progressed. 38 responded without the need to ask the parent to exit the practice room, while the other 32 responded only after their parent exited. 52 children had additional appointments, and 8 required an application of PPA at a second appointment; all children cooperated in all subsequent appointments. Early and empathic application of the PPA technique appears very successful in managing initially uncooperative child patients, suggesting that a randomised controlled trial of the technique is warranted.

The influence of impulsiveness on binge eating and problem gambling: A prospective study of gender differences in Canadian adults.

PubMed

Farstad, Sarah M; von Ranson, Kristin M; Hodgins, David C; El-Guebaly, Nady; Casey, David M; Schopflocher, Don P

2015-09-01

This study investigated the degree to which facets of impulsiveness predicted future binge eating and problem gambling, 2 theorized forms of behavioral addiction. Participants were 596 women and 406 men from 4 age cohorts randomly recruited from a Canadian province. Participants completed self-report measures of 3 facets of impulsiveness (negative urgency, sensation seeking, lack of persistence), binge-eating frequency, and problem-gambling symptoms. Impulsiveness was assessed at baseline, and assessments of binge eating and problem gambling were followed up after 3 years. Weighted data were analyzed using zero-inflated negative binomial and Poisson regression models. We found evidence of transdiagnostic and disorder-specific predictors of binge eating and problem gambling. Negative urgency emerged as a common predictor of binge eating and problem gambling among women and men. There were disorder-specific personality traits identified among men only: High lack-of-persistence scores predicted binge eating and high sensation-seeking scores predicted problem gambling. Among women, younger age predicted binge eating and older age predicted problem gambling. Thus, there are gender differences in facets of impulsiveness that longitudinally predict binge eating and problem gambling, suggesting that treatments for these behaviors should consider gender-specific personality and demographic traits in addition to the common personality trait of negative urgency. (c) 2015 APA, all rights reserved).

How does the emotive content of televised anti-smoking mass media campaigns influence monthly calls to the NHS Stop Smoking helpline in England?

PubMed Central

Richardson, Sol; Langley, Tessa; Szatkowski, Lisa; Sims, Michelle; Gilmore, Anna; McNeill, Ann; Lewis, Sarah

2014-01-01

Objective To investigate the effects of different types of televised mass media campaign content on calls to the English NHS Stop Smoking helpline. Method We used UK government-funded televised tobacco control campaigns from April 2005 to April 2010, categorised as either “positive” (eliciting happiness, satisfaction or hope) or “negative” (eliciting fear, guilt or disgust). We built negative binomial generalised additive models (GAMs) with linear and smooth terms for monthly per capita exposure to each campaign type (expressed as Gross Ratings Points, or GRPs) to determine their effect on calls in the same month. We adjusted for seasonal trends, inflation-adjusted weighted average cigarette prices and other tobacco control policies. Results We found non-linear associations between exposure to positive and negative emotive campaigns and quitline calls. The rate of calls increased more than 50% as exposure to positive campaigns increased from 0 to 400 GRPs (rate ratio: 1.58, 95% CI: 1.25–2.01). An increase in calls in response to negative emotive campaigns was only apparent after monthly exposure exceeded 400 GRPs. Conclusion While positive campaigns were most effective at increasing quitline calls, those with negative emotive content were also found to impact on call rates but only at higher levels of exposure. PMID:25197004

Use of the binomial distribution to predict impairment: application in a nonclinical sample.

PubMed

Axelrod, Bradley N; Wall, Jacqueline R; Estes, Bradley W

2008-01-01

A mathematical model based on the binomial theory was developed to illustrate when abnormal score variations occur by chance in a multitest battery (Ingraham & Aiken, 1996). It has been successfully used as a comparison for obtained test scores in clinical samples, but not in nonclinical samples. In the current study, this model has been applied to demographically corrected scores on the Halstead-Reitan Neuropsychological Test Battery, obtained from a sample of 94 nonclinical college students. Results found that 15% of the sample had impairments suggested by the Halstead Impairment Index, using criteria established by Reitan and Wolfson (1993). In addition, one-half of the sample obtained impaired scores on one or two tests. These results were compared to that predicted by the binomial model and found to be consistent. The model therefore serves as a useful resource for clinicians considering the probability of impaired test performance.

Crime Seasonality: Examining the Temporal Fluctuations of Property Crime in Cities With Varying Climates.

PubMed

Linning, Shannon J; Andresen, Martin A; Brantingham, Paul J

2017-12-01

This study investigates whether crime patterns fluctuate periodically throughout the year using data containing different property crime types in two Canadian cities with differing climates. Using police report data, a series of ordinary least squares (OLS; Vancouver, British Columbia) and negative binomial (Ottawa, Ontario) regressions were employed to examine the corresponding temporal patterns of property crime in Vancouver (2003-2013) and Ottawa (2006-2008). Moreover, both aggregate and disaggregate models were run to examine whether different weather and temporal variables had a distinctive impact on particular offences. Overall, results suggest that cities that experience greater variations in weather throughout the year have more distinct increases of property offences in the summer months and that different climate variables affect certain crime types, thus advocating for disaggregate analysis in the future.

The effect of laminar air flow and door openings on operating room contamination.

PubMed

Smith, Eric B; Raphael, Ibrahim J; Maltenfort, Mitchell G; Honsawek, Sittisak; Dolan, Kyle; Younkins, Elizabeth A

2013-10-01

We evaluate the association of laminar airflow (LAF) and OR traffic with intraoperative contamination rates. Two sterile basins were placed in each room during 81 cases, one inside and one outside the LAF. One Replicate Organism Detection and Counting (RODAC) plate from each basin was sent for culture at successive 30-minute intervals from incision time until wound closure. At successive 30-minute intervals more plates were contaminated outside than inside the LAF. A negative binomial model showed that the bacteria colony forming units (CFU) depended on whether there were any door openings (P=0.02) and the presence of LAF (P=0.003). LAF decreases CFU by 36.6%. LAF independently reduces the risk of contamination and microbial counts for surgeries lasting 90 minutes or less. © 2013.

The impact of texting bans on motor vehicle crash-related hospitalizations.

PubMed

Ferdinand, Alva O; Menachemi, Nir; Blackburn, Justin L; Sen, Bisakha; Nelson, Leonard; Morrisey, Michael

2015-05-01

We used a panel design and the Nationwide Inpatient Sample from 19 states between 2003 and 2010 to examine the impact of texting bans on crash-related hospitalizations. We conducted conditional negative binomial regressions with state, year, and month fixed effects to examine changes in crash-related hospitalizations in states after the enactment of a texting ban relative to those in states without such bans. Results indicate that texting bans were associated with a 7% reduction in crash-related hospitalizations among all age groups. Texting bans were significantly associated with reductions in hospitalizations among those aged 22 to 64 years and those aged 65 years or older. Marginal reductions were seen among adolescents. States that have not passed strict texting bans should consider doing so.

Epidemiological study of the intestinal helminths of wild boar (Sus scrofa) and mouflon (Ovis gmelini musimon) in central Italy.

PubMed

Magi, M; Bertani, M; Dell'Omodarme, M; Prati, M C

2002-12-01

Since 1995 the population of wild ungulates increased significantly in the "Parco provinciale dei Monti Livornesi" (Livorno, Tuscany, Central Italy). We studied the intestinal macroparasites of two hosts, the wild boar (Sus scrofa) and the mouflon (Ovis gmelini musimon). In the case of wild boars we found a dominant parasite species, Globocephalus urosubulatus. For this parasite the frequency distribution of the number of parasites per host agrees with a negative binomial distribution. There is not a significant correlation between the age of the animals and the parasitosis. Furthermore the mean parasite burden of male and female wild boars does not differ significantly. In the case of mouflons we found a dominant parasite species Nematodirus filicollis with Trichuris ovis as codominant species.

Misconduct Within the "Four Walls": Does Organizational Justice Matter in Explaining Prison Officers' Misconduct and Job Stress?

PubMed

Boateng, Francis D; Hsieh, Ming-Li

2018-06-01

Primarily, this article examines the role of organizational justice in understanding prison officers' behavior. The authors surveyed 169 correctional officers across five correctional facilities in Ghana to explore the role of three organizational justice dimensions in prison misconduct and job stress. Results from the negative binomial and ordinal logistic analyses revealed the significant contributions of two dimensions of organizational justice in explaining misconduct and stress among officers. Officers who had higher perceptions of distributive fairness and interaction in the organization had lower odds of receiving misconduct-related complaints. Also, greater interaction was found to be associated with reduced job stress among prison officers. In addition, several officers' characteristics were found to predict the number of times officers received misconduct complaints.

Linking crime guns: the impact of ballistics imaging technology on the productivity of the Boston Police Department's Ballistics Unit.

PubMed

Braga, Anthony A; Pierce, Glenn L

2004-07-01

Ballistics imaging technology has received national attention as a potent tool for moving the law enforcement response to violent gun criminals forward by linking multiple crime scenes to one firearm. This study examines the impact of ballistics imaging technology on the productivity of the Boston Police Department's Ballistics Unit. Using negative binomial regression models to analyze times series data on ballistics matches, we find that ballistics imaging technology was associated with a more than sixfold increase in the monthly number of ballistics matches made by the Boston Police Department's Ballistics Unit. Cost-effectiveness estimates and qualitative evidence also suggest that ballistics imaging technology allows law enforcement agencies to make hits that would not have been possible using traditional ballistics methods.

Civic communities and urban violence.

PubMed

Doucet, Jessica M; Lee, Matthew R

2015-07-01

Civic communities have a spirit of entrepreneurialism, a locally invested population and an institutional structure fostering civic engagement. Prior research, mainly confined to studying rural communities and fairly large geographic areas, has demonstrated that civic communities have lower rates of violence. The current study analyzes the associations between the components of civic communities and homicide rates for New Orleans neighborhoods (census tracts) in the years following Hurricane Katrina. Results from negative binomial regression models adjusting for spatial autocorrelation reveal that community homicide rates are lower where an entrepreneurial business climate is more pronounced and where there is more local investment. Additionally, an interaction between the availability of civic institutions and resource disadvantage reveals that the protective effects of civic institutions are only evident in disadvantaged communities. Copyright © 2015 Elsevier Inc. All rights reserved.

Bursts of Self-Conscious Emotions in the Daily Lives of Emerging Adults.

PubMed

Conroy, David E; Ram, Nilam; Pincus, Aaron L; Rebar, Amanda L

Self-conscious emotions play a role in regulating daily achievement strivings, social behavior, and health, but little is known about the processes underlying their daily manifestation. Emerging adults (n = 182) completed daily diaries for eight days and multilevel models were estimated to evaluate whether, how much, and why their emotions varied from day-to-day. Within-person variation in authentic pride was normally-distributed across people and days whereas the other emotions were burst-like and characterized by zero-inflated, negative binomial distributions. Perceiving social interactions as generally communal increased the odds of hubristic pride activation and reduced the odds of guilt activation; daily communal behavior reduced guilt intensity. Results illuminated processes through which meaning about the self-in-relation-to-others is constructed during a critical period of development.

Infant Mortality and Income in 4 World Cities: New York, London, Paris, and Tokyo

PubMed Central

Rodwin, Victor G.; Neuberg, Leland G.

2005-01-01

Objectives. We investigated the association between average income or deprivation and infant mortality rate across neighborhoods of 4 world cities. Methods. Using a maximum likelihood negative binomial regression model that controls for births, we analyzed data for 1988–1992 and 1993–1997. Results. In Manhattan, for both periods, we found an association (.05% significance level) between income and infant mortality. In Tokyo, for both periods, and in Paris and London for period 1, we found none (5% significance level). For period 2, the association just missed statistical significance for Paris, whereas for London it was significant (5% level). Conclusions. In stark contrast to Tokyo, Paris, and London, the association of income and infant mortality rate was strongly evident in Manhattan. PMID:15623865

The Impact of Texting Bans on Motor Vehicle Crash–Related Hospitalizations

PubMed Central

Menachemi, Nir; Blackburn, Justin L.; Sen, Bisakha; Nelson, Leonard; Morrisey, Michael

2015-01-01

We used a panel design and the Nationwide Inpatient Sample from 19 states between 2003 and 2010 to examine the impact of texting bans on crash-related hospitalizations. We conducted conditional negative binomial regressions with state, year, and month fixed effects to examine changes in crash-related hospitalizations in states after the enactment of a texting ban relative to those in states without such bans. Results indicate that texting bans were associated with a 7% reduction in crash-related hospitalizations among all age groups. Texting bans were significantly associated with reductions in hospitalizations among those aged 22 to 64 years and those aged 65 years or older. Marginal reductions were seen among adolescents. States that have not passed strict texting bans should consider doing so. PMID:25790409

Willingness to pay for non angler recreation at the lower Snake River reservoirs

USGS Publications Warehouse

McKean, J.R.; Johnson, D.; Taylor, R.G.; Johnson, Richard L.

2005-01-01

This study applied the travel cost method to estimate demand for non angler recreation at the impounded Snake River in eastern Washington. Net value per person per recreation trip is estimated for the full non angler sample and separately for camping, boating, water-skiing, and swimming/picnicking. Certain recreation activities would be reduced or eliminated and new activities would be added if the dams were breached to protect endangered salmon and steelhead. The effect of breaching on non angling benefits was found by subtracting our benefits estimate from the projected non angling benefits with breaching. Major issues in demand model specification and definition of the price variables are discussed. The estimation method selected was truncated negative binomial regression with adjustment for self selection bias.

Gun control and suicide: the impact of state firearm regulations in the United States, 1995-2004.

PubMed

Rodríguez Andrés, Antonio; Hempstead, Katherine

2011-06-01

To empirically assess the impact of firearm regulation on male suicides. A negative binomial regression model was applied by using a panel of state level data for the years 1995-2004. The model was used to identify the association between several firearm regulations and male suicide rates. Our empirical analysis suggest that firearms regulations which function to reduce overall gun availability have a significant deterrent effect on male suicide, while regulations that seek to prohibit high risk individuals from owning firearms have a lesser effect. Restricting access to lethal means has been identified as an effective approach to suicide prevention, and firearms regulations are one way to reduce gun availability. The analysis suggests that gun control measures such as permit and licensing requirements have a negative effect on suicide rates among males. Since there is considerable heterogeneity among states with regard to gun control, these results suggest that there are opportunities for many states to reduce suicide by expanding their firearms regulations. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

The Healthy Immigrant Effect on Mental Health: Determinants and Implications for Mental Health Policy in Spain.

PubMed

Rivera, Berta; Casal, Bruno; Currais, Luis

2016-07-01

Since the mid-1990s, Spain has started to receive a great number of migrant populations. The migration process can have a significantly negative impact on mental health of immigrant population and, consequently, generate implications for the delivery of mental health services. The aim of this article is to provide empirical evidence to demonstrate that the mental health of immigrants in Spain deteriorates the longer they are resident in the country. An empirical approach to this relationship is carried out with data from the National Survey of Health of Spain 2011-2012 and poisson and negative binomial models. Results show that immigrants who reside <10 years in Spain appear to be in a better state of mental health than that observed for the national population. Studying health disparities in the foreign population and its evolution are relevant to ensure the population's access to health services and care. The need for further research is especially true in the case of the immigrant population's mental health in Spain because there is scant evidence available on their situation.

Association between Low-density lipoprotein cholesterol and occipital periventricular hyperintensities in a group of Chinese patients: an observational study.

PubMed

Duan, Dazhi; Shen, Lin; Cui, Chun; Shu, Tongsheng; Zheng, Jian

2017-02-27

While occipital periventricular hyperintensities (OPVHs) are among the most common mild white matter hyperintensities, the clinical factors associated with OPVHs remain unclear. In this study, we investigated the role of clinical factors in development of pure OPVHs. This study included 97 patients with OPVHs and 73 healthy controls. Univariate analysis of clinical factors in OPVH patients and controls was followed by binomial logistic regression analysis to identify clinical factors significantly associated with OPVHs. Univariate analysis indicated that age, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein-B (Apo-B) levels differed significantly between the OPVH patients and controls (p < 0.05). Age and gender were correlated with OPVH scores (p < 0.05), while LDL-C, triglycerides, Apo-B and TC were anti-correlated with OPVHs scores (p < 0.05). Multivariate analysis indicated that LDL-C is negatively correlated with OPVHs (p < 0.05), and age is positively correlated with OPVHs (p < 0.001). In summary, LDL-C was negatively and age was positively associated with OPVHs among Chinese patients in a hospital.

Area characteristics and admission rates of people with schizophrenia and affective disorders in a German rural catchment area.

PubMed

Losert, C; Schmauß, M; Becker, T; Kilian, R

2012-12-01

Studies in urban areas identified environmental risk factors for mental illness, but little research on this topic has been performed in rural areas. Hospital admission rates were computed for 174 rural municipalities in the catchment area of the state psychiatric hospital in Günzburg in years 2006 to 2009 and combined with structural and socio-economic data. Relationships of overall and diagnosis-specific admission rates with municipality characteristics were analysed by means of negative binomial regression models. Admission rates of patients with a diagnosis of schizophrenia and affective disorder combined decrease with increasing population growth, population density, average income and green areas, while admission rates are positively correlated with commuter balance, income inequality, unemployment rates and traffic areas. Admission rates for schizophrenia are negatively related to population growth, average income and agricultural areas, but positively related to mobility index, income inequality and unemployment rate. Admission rates for affective disorders are negatively related to population growth, population density, average income and green areas, while higher admission rates are correlated with commuter balance, high income inequality, unemployment rate and traffic-related areas. Effects of wealth, economic inequality, population density and structural area characteristics influence psychiatric admission rates also in rural areas.

On the Relationship between Molecular Hit Rates in High-Throughput Screening and Molecular Descriptors.

PubMed

Hansson, Mari; Pemberton, John; Engkvist, Ola; Feierberg, Isabella; Brive, Lars; Jarvis, Philip; Zander-Balderud, Linda; Chen, Hongming

2014-06-01

High-throughput screening (HTS) is widely used in the pharmaceutical industry to identify novel chemical starting points for drug discovery projects. The current study focuses on the relationship between molecular hit rate in recent in-house HTS and four common molecular descriptors: lipophilicity (ClogP), size (heavy atom count, HEV), fraction of sp(3)-hybridized carbons (Fsp3), and fraction of molecular framework (f(MF)). The molecular hit rate is defined as the fraction of times the molecule has been assigned as active in the HTS campaigns where it has been screened. Beta-binomial statistical models were built to model the molecular hit rate as a function of these descriptors. The advantage of the beta-binomial statistical models is that the correlation between the descriptors is taken into account. Higher degree polynomial terms of the descriptors were also added into the beta-binomial statistic model to improve the model quality. The relative influence of different molecular descriptors on molecular hit rate has been estimated, taking into account that the descriptors are correlated to each other through applying beta-binomial statistical modeling. The results show that ClogP has the largest influence on the molecular hit rate, followed by Fsp3 and HEV. f(MF) has only a minor influence besides its correlation with the other molecular descriptors. © 2013 Society for Laboratory Automation and Screening.

The Sequential Probability Ratio Test: An efficient alternative to exact binomial testing for Clean Water Act 303(d) evaluation.

PubMed

Chen, Connie; Gribble, Matthew O; Bartroff, Jay; Bay, Steven M; Goldstein, Larry

2017-05-01

The United States's Clean Water Act stipulates in section 303(d) that states must identify impaired water bodies for which total maximum daily loads (TMDLs) of pollution inputs into water bodies are developed. Decision-making procedures about how to list, or delist, water bodies as impaired, or not, per Clean Water Act 303(d) differ across states. In states such as California, whether or not a particular monitoring sample suggests that water quality is impaired can be regarded as a binary outcome variable, and California's current regulatory framework invokes a version of the exact binomial test to consolidate evidence across samples and assess whether the overall water body complies with the Clean Water Act. Here, we contrast the performance of California's exact binomial test with one potential alternative, the Sequential Probability Ratio Test (SPRT). The SPRT uses a sequential testing framework, testing samples as they become available and evaluating evidence as it emerges, rather than measuring all the samples and calculating a test statistic at the end of the data collection process. Through simulations and theoretical derivations, we demonstrate that the SPRT on average requires fewer samples to be measured to have comparable Type I and Type II error rates as the current fixed-sample binomial test. Policymakers might consider efficient alternatives such as SPRT to current procedure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Football fever: goal distributions and non-Gaussian statistics

NASA Astrophysics Data System (ADS)

Bittner, E.; Nußbaumer, A.; Janke, W.; Weigel, M.

2009-02-01

Analyzing football score data with statistical techniques, we investigate how the not purely random, but highly co-operative nature of the game is reflected in averaged properties such as the probability distributions of scored goals for the home and away teams. As it turns out, especially the tails of the distributions are not well described by the Poissonian or binomial model resulting from the assumption of uncorrelated random events. Instead, a good effective description of the data is provided by less basic distributions such as the negative binomial one or the probability densities of extreme value statistics. To understand this behavior from a microscopical point of view, however, no waiting time problem or extremal process need be invoked. Instead, modifying the Bernoulli random process underlying the Poissonian model to include a simple component of self-affirmation seems to describe the data surprisingly well and allows to understand the observed deviation from Gaussian statistics. The phenomenological distributions used before can be understood as special cases within this framework. We analyzed historical football score data from many leagues in Europe as well as from international tournaments, including data from all past tournaments of the “FIFA World Cup” series, and found the proposed models to be applicable rather universally. In particular, here we analyze the results of the German women’s premier football league and consider the two separate German men’s premier leagues in the East and West during the cold war times as well as the unified league after 1990 to see how scoring in football and the component of self-affirmation depend on cultural and political circumstances.

Higher moments of net-proton multiplicity distributions in a heavy-ion event pile-up scenario

NASA Astrophysics Data System (ADS)

Garg, P.; Mishra, D. K.

2017-10-01

High-luminosity modern accelerators, like the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) and Large Hadron Collider (LHC) at European Organization for Nuclear Research (CERN), inherently have event pile-up scenarios which significantly contribute to physics events as a background. While state-of-the-art tracking algorithms and detector concepts take care of these event pile-up scenarios, several offline analytical techniques are used to remove such events from the physics analysis. It is still difficult to identify the remaining pile-up events in an event sample for physics analysis. Since the fraction of these events is significantly small, it may not be as serious of an issue for other analyses as it would be for an event-by-event analysis. Particularly when the characteristics of the multiplicity distribution are observable, one needs to be very careful. In the present work, we demonstrate how a small fraction of residual pile-up events can change the moments and their ratios of an event-by-event net-proton multiplicity distribution, which are sensitive to the dynamical fluctuations due to the QCD critical point. For this study, we assume that the individual event-by-event proton and antiproton multiplicity distributions follow Poisson, negative binomial, or binomial distributions. We observe a significant effect in cumulants and their ratios of net-proton multiplicity distributions due to pile-up events, particularly at lower energies. It might be crucial to estimate the fraction of pile-up events in the data sample while interpreting the experimental observable for the critical point.

Does the name really matter? The importance of botanical nomenclature and plant taxonomy in biomedical research.

PubMed

Bennett, Bradley C; Balick, Michael J

2014-03-28

Medical research on plant-derived compounds requires a breadth of expertise from field to laboratory and clinical skills. Too often basic botanical skills are evidently lacking, especially with respect to plant taxonomy and botanical nomenclature. Binomial and familial names, synonyms and author citations are often misconstrued. The correct botanical name, linked to a vouchered specimen, is the sine qua non of phytomedical research. Without the unique identifier of a proper binomial, research cannot accurately be linked to the existing literature. Perhaps more significant, is the ambiguity of species determinations that ensues of from poor taxonomic practices. This uncertainty, not surprisingly, obstructs reproducibility of results-the cornerstone of science. Based on our combined six decades of experience with medicinal plants, we discuss the problems of inaccurate taxonomy and botanical nomenclature in biomedical research. This problems appear all too frequently in manuscripts and grant applications that we review and they extend to the published literature. We also review the literature on the importance of taxonomy in other disciplines that relate to medicinal plant research. In most cases, questions regarding orthography, synonymy, author citations, and current family designations of most plant binomials can be resolved using widely-available online databases and other electronic resources. Some complex problems require consultation with a professional plant taxonomist, which also is important for accurate identification of voucher specimens. Researchers should provide the currently accepted binomial and complete author citation, provide relevant synonyms, and employ the Angiosperm Phylogeny Group III family name. Taxonomy is a vital adjunct not only to plant-medicine research but to virtually every field of science. Medicinal plant researchers can increase the precision and utility of their investigations by following sound practices with respect to botanical nomenclature. Correct spellings, accepted binomials, author citations, synonyms, and current family designations can readily be found on reliable online databases. When questions arise, researcher should consult plant taxonomists. © 2013 Published by Elsevier Ireland Ltd.

Problem drinking among Flemish students: beverage type, early drinking onset and negative personal & social consequences.

PubMed

De Bruyn, Sara; Wouters, Edwin; Ponnet, Koen; Van Damme, Joris; Maes, Lea; Van Hal, Guido

2018-02-12

Although alcohol is socially accepted in most Western societies, studies are clear about its associated negative consequences, especially among university and college students. Studies on the relationship between alcohol-related consequences and both beverage type and drinking onset, however, are scarce, especially in a European context. The aim of this research was, therefore, twofold: (1) What is the relationship between beverage type and the negative consequences experienced by students? and (2) Are these consequences determined by early drinking onset? We will examine these questions within the context of a wide range of alcohol-related consequences. The analyses are based on data collected by the inter-university project 'Head in the clouds?', measuring alcohol use among students in Flanders (Belgium). In total, a large dataset consisting of information from 19,253 anonymously participating students was available. Negative consequences were measured using a shortened version of the Core Alcohol and Drug Survey (CADS_D). Data were analysed using negative binomial regression. Results vary depending on the type of alcohol-related consequences: Personal negative consequences occur frequently among daily beer drinkers. However, a high rate of social negative consequences was recorded for both daily beer drinkers and daily spirits drinkers. Finally, early drinking onset was significantly associated with both personal and social negative consequences, and this association was especially strong between beer and spirits drinking onset and social negative consequences. Numerous negative consequences, both personal and social, are related to frequent beer and spirits drinking. Our findings indicate a close association between drinking beer and personal negative consequences as well as between drinking beer and/or spirits and social negative consequences. Similarly, early drinking onset has a major influence on the rates of both personal and social negative consequences. The earlier students started drinking, the more negative consequences they experienced during college or university. Several (policy) interventions are discussed. This study is the first to incorporate detailed information on both beverage type and drinking onset, and its associated negative consequences, as measured by the CADS_D, in a large student population.

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

Effect of Breastfeeding Promotion on Early Childhood Caries and Breastfeeding Duration among 5 Year Old Children in Eastern Uganda: A Cluster Randomized Trial

PubMed Central

Birungi, Nancy; Fadnes, Lars T.; Okullo, Isaac; Kasangaki, Arabat; Nankabirwa, Victoria; Ndeezi, Grace; Tumwine, James K.; Tylleskär, Thorkild; Lie, Stein Atle; Åstrøm, Anne Nordrehaug

2015-01-01

Background Although several studies have shown short term health benefits of exclusive breastfeeding (EBF), its long term consequences have not been studied extensively in low-income contexts. This study assessed the impact of an EBF promotion initiative for 6 months on early childhood caries (ECC) and breastfeeding duration in children aged 5 years in Mbale, Eastern Uganda. Methods Participants were recruited from the Ugandan site of the PROMISE- EBF cluster randomised trial (ClinicalTrials.gov no: NCT00397150). A total of 765 pregnant women from 24 clusters were included in the ratio 1:1 to receive peer counselled promotion of EBF as the intervention or standard of care. At the 5 year follow-up, ECC was recorded under field conditions using the World Health Organization’s decayed missing filled tooth (dmft) index. Adjusted negative binomial and linear regression were used in the analysis. Results Mean breastfeeding duration in the intervention and control groups (n=417) were 21.8 (CI 20.7–22.9) and 21.3(CI 20.7–21.9) months, respectively. The mean dmft was 1.5 (standard deviation [SD] 2.9) and 1.7 (SD 2.9) in the intervention and control groups, respectively. Corresponding prevalence estimates of ECC were 38% and 41%. Negative binomial regression analysis adjusted for cluster effects and loss-to-follow-up by inverse probability weights (IPW) showed an incidence-rate ratio (IRR) of 0.91 (95% CI 0.65–1.2). Comparing the effect of the trial arm on breastfeeding duration showed a difference in months of 0.48 (-0.72 to 1.7). Conclusion PROMISE EBF trial did not impact on early childhood caries or breastfeeding duration at 5 years of age. This study contributes to the body of evidence that promotion of exclusive breastfeeding does not raise oral health concerns. However, the high burden of caries calls for efforts to improve the oral health condition in this setting. Trial Registration ClinicalTrials.gov NCT00397150 PMID:25938681

Reducing falls after hospital discharge: a protocol for a randomised controlled trial evaluating an individualised multimodal falls education programme for older adults.

PubMed

Hill, Anne-Marie; Etherton-Beer, Christopher; McPhail, Steven M; Morris, Meg E; Flicker, Leon; Shorr, Ronald; Bulsara, Max; Lee, Den-Ching; Francis-Coad, Jacqueline; Waldron, Nicholas; Boudville, Amanda; Haines, Terry

2017-02-02

Older adults frequently fall after discharge from hospital. Older people may have low self-perceived risk of falls and poor knowledge about falls prevention. The primary aim of the study is to evaluate the effect of providing tailored falls prevention education in addition to usual care on falls rates in older people after discharge from hospital compared to providing a social intervention in addition to usual care. The 'Back to My Best' study is a multisite, single blind, parallel-group randomised controlled trial with blinded outcome assessment and intention-to-treat analysis, adhering to CONSORT guidelines. Patients (n=390) (aged 60 years or older; score more than 7/10 on the Abbreviated Mental Test Score; discharged to community settings) from aged care rehabilitation wards in three hospitals will be recruited and randomly assigned to one of two groups. Participants allocated to the control group shall receive usual care plus a social visit. Participants allocated to the experimental group shall receive usual care and a falls prevention programme incorporating a video, workbook and individualised follow-up from an expert health professional to foster capability and motivation to engage in falls prevention strategies. The primary outcome is falls rates in the first 6 months after discharge, analysed using negative binomial regression with adjustment for participant's length of observation in the study. Secondary outcomes are injurious falls rates, the proportion of people who become fallers, functional status and health-related quality of life. Healthcare resource use will be captured from four sources for 6 months after discharge. The study is powered to detect a 30% relative reduction in the rate of falls (negative binomial incidence ratio 0.70) for a control rate of 0.80 falls per person over 6 months. Results will be presented in peer-reviewed journals and at conferences worldwide. This study is approved by hospital and university Human Research Ethics Committees. ACTRN12615000784516. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Maternal and Child Supplementation with Lipid-Based Nutrient Supplements, but Not Child Supplementation Alone, Decreases Self-Reported Household Food Insecurity in Some Settings

PubMed Central

Ayifah, Emmanuel; Arimond, Mary; Arnold, Charles D; Cummins, Joseph; Matias, Susana L; Ashorn, Ulla; Lartey, Anna; Maleta, Kenneth M; Vosti, Stephen A; Dewey, Kathryn G

2017-01-01

Background: It is unknown whether self-reported measures of household food insecurity change in response to food-based nutrient supplementation. Objective: We assessed the impacts of providing lipid-based nutrient supplements (LNSs) to women during pregnancy and postpartum and/or to their children on self-reported household food insecurity in Malawi [DOSE and DYAD trial in Malawi (DYAD-M)], Ghana [DYAD trial in Ghana (DYAD-G)], and Bangladesh [Rang-Din Nutrition Study (RDNS) trial]. Methods: Longitudinal household food-insecurity data were collected during 3 individually randomized trials and 1 cluster-randomized trial testing the efficacy or effectiveness of LNSs (generally 118 kcal/d). Seasonally adjusted Household Food Insecurity Access Scale (HFIAS) scores were constructed for 1127 DOSE households, 732 DYAD-M households, 1109 DYAD-G households, and 3671 RDNS households. The impact of providing LNSs to women during pregnancy and the first 6 mo postpartum and/or to their children from 6 to 18–24 mo on seasonally adjusted HFIAS scores was assessed by using negative binomial models (DOSE, DYAD-M, and DYAD-G trials) and mixed-effect negative binomial models (RDNS trial). Results: In the DOSE and DYAD-G trials, seasonally adjusted HFIAS scores were not different between the LNS and non-LNS groups. In the DYAD-M trial, the average household food-insecurity scores were 14% lower (P = 0.01) in LNS households than in non-LNS households. In the RDNS trial, compared with non-LNS households, food-insecurity scores were 17% lower (P = 0.02) during pregnancy and the first 6 mo postpartum and 15% lower (P = 0.02) at 6–24 mo postpartum in LNS households. Conclusions: The daily provision of LNSs to mothers and their children throughout much of the “first 1000 d” may improve household food security in some settings, which could be viewed as an additional benefit that may accrue in households should policy makers choose to invest in LNSs to promote child growth and development. These trials were registered at clinicaltrials.gov as NCT00945698 (DOSE) NCT01239693 (DYAD-M), NCT00970866 (DYAD-G) and NCT01715038 (RDNS). PMID:28978680

An empirical tool to evaluate the safety of cyclists: Community based, macro-level collision prediction models using negative binomial regression.

PubMed

Wei, Feng; Lovegrove, Gordon

2013-12-01

Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists' road safety at a macro level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-level and macro-level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle-auto collisions at a community-based, macro-level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle-auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial-local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low levels of bicycle use (<4%), we can initially expect to see an increase in bicycle collisions as cycle mode share increases. However, as bicycle mode share increases beyond some unknown 'critical' level, our hypothesis also predicts a net safety improvement. To test this hypothesis and to further explore the statistical relationships between bicycle mode split and overall road safety, future research needs to pursue further development and application of community-based, macro-level CPMs. Copyright © 2012. Published by Elsevier Ltd.

Comparing ELISA test-positive prevalence, risk factors and management recommendations for Johne's disease prevention between organic and conventional dairy farms in Ontario, Canada.

PubMed

Pieper, Laura; Sorge, Ulrike S; DeVries, Trevor; Godkin, Ann; Lissemore, Kerry; Kelton, David

2015-11-01

Johne's disease (JD) is a chronic, infectious disease in cattle. Between 2010 and 2013, a voluntary JD control program was successfully launched in Ontario, Canada, including a Risk Assessment and Management Plan (RAMP) and JD ELISA testing of the entire milking herd. Over the last decade, the organic dairy sector has been growing. However, organic farming regulations and philosophies may influence the risk for JD transmission on Ontario organic dairy farms. The aim of this cross-sectional study was to investigate differences in JD ELISA test positive prevalence, risk factors for JD and recommendations for JD prevention between organic and conventional dairy herds in Ontario. RAMP results (i.e. RAMP scores and recommendations) and ELISA results were available for 2103 dairy herds, including 42 organic herds. If available, additional data on milk production, milk quality, and herd characteristics were gathered. Organic and conventional herds had a similar herd-level JD ELISA test-positive prevalence (26.2% and 27.2%, respectively). Organic herds (4.2%) had a higher within-herd JD ELISA test-positive prevalence compared to conventional herds (2.3%) if they had at least one JD test-positive animal on the farm. Organic farms had lower risk scores for biosecurity (9 points lower), and higher scores in the calving (7 points higher) and the calf-rearing management areas (4 points higher). After accounting for RAMP score, organic farms received fewer recommendations for the calving management area (Odds Ratio=0.41) and more recommendations in the adult cow management area (Odds Ratio=2.70). A zero-inflated negative binomial model was built with purchase of animals and the herd size included in the logistic portion of the model. Herd type (organic or conventional), colostrum and milk feeding practices, average bulk tank somatic cell count, and presence of non-Holstein breeds were included in the negative binomial portion of the model. Organic farms had a higher number of test positive animals (Count Ratio=2.02). Further research is necessary to investigate the apparent disconnect between risk factors and recommendations on organic dairy farms. Copyright © 2015 Elsevier B.V. All rights reserved.

Maternal and Child Supplementation with Lipid-Based Nutrient Supplements, but Not Child Supplementation Alone, Decreases Self-Reported Household Food Insecurity in Some Settings.

PubMed

Adams, Katherine P; Ayifah, Emmanuel; Phiri, Thokozani E; Mridha, Malay K; Adu-Afarwuah, Seth; Arimond, Mary; Arnold, Charles D; Cummins, Joseph; Hussain, Sohrab; Kumwenda, Chiza; Matias, Susana L; Ashorn, Ulla; Lartey, Anna; Maleta, Kenneth M; Vosti, Stephen A; Dewey, Kathryn G

2017-12-01

Background: It is unknown whether self-reported measures of household food insecurity change in response to food-based nutrient supplementation. Objective: We assessed the impacts of providing lipid-based nutrient supplements (LNSs) to women during pregnancy and postpartum and/or to their children on self-reported household food insecurity in Malawi [DOSE and DYAD trial in Malawi (DYAD-M)], Ghana [DYAD trial in Ghana (DYAD-G)], and Bangladesh [Rang-Din Nutrition Study (RDNS) trial]. Methods: Longitudinal household food-insecurity data were collected during 3 individually randomized trials and 1 cluster-randomized trial testing the efficacy or effectiveness of LNSs (generally 118 kcal/d). Seasonally adjusted Household Food Insecurity Access Scale (HFIAS) scores were constructed for 1127 DOSE households, 732 DYAD-M households, 1109 DYAD-G households, and 3671 RDNS households. The impact of providing LNSs to women during pregnancy and the first 6 mo postpartum and/or to their children from 6 to 18-24 mo on seasonally adjusted HFIAS scores was assessed by using negative binomial models (DOSE, DYAD-M, and DYAD-G trials) and mixed-effect negative binomial models (RDNS trial). Results: In the DOSE and DYAD-G trials, seasonally adjusted HFIAS scores were not different between the LNS and non-LNS groups. In the DYAD-M trial, the average household food-insecurity scores were 14% lower ( P = 0.01) in LNS households than in non-LNS households. In the RDNS trial, compared with non-LNS households, food-insecurity scores were 17% lower ( P = 0.02) during pregnancy and the first 6 mo postpartum and 15% lower ( P = 0.02) at 6-24 mo postpartum in LNS households. Conclusions: The daily provision of LNSs to mothers and their children throughout much of the "first 1000 d" may improve household food security in some settings, which could be viewed as an additional benefit that may accrue in households should policy makers choose to invest in LNSs to promote child growth and development. These trials were registered at clinicaltrials.gov as NCT00945698 (DOSE) NCT01239693 (DYAD-M), NCT00970866 (DYAD-G) and NCT01715038 (RDNS).

Reducing falls after hospital discharge: a protocol for a randomised controlled trial evaluating an individualised multimodal falls education programme for older adults

PubMed Central

Hill, Anne-Marie; Etherton-Beer, Christopher; McPhail, Steven M; Morris, Meg E; Flicker, Leon; Bulsara, Max; Lee, Den-Ching; Francis-Coad, Jacqueline; Waldron, Nicholas; Boudville, Amanda; Haines, Terry

2017-01-01

Introduction Older adults frequently fall after discharge from hospital. Older people may have low self-perceived risk of falls and poor knowledge about falls prevention. The primary aim of the study is to evaluate the effect of providing tailored falls prevention education in addition to usual care on falls rates in older people after discharge from hospital compared to providing a social intervention in addition to usual care. Methods and analyses The ‘Back to My Best’ study is a multisite, single blind, parallel-group randomised controlled trial with blinded outcome assessment and intention-to-treat analysis, adhering to CONSORT guidelines. Patients (n=390) (aged 60 years or older; score more than 7/10 on the Abbreviated Mental Test Score; discharged to community settings) from aged care rehabilitation wards in three hospitals will be recruited and randomly assigned to one of two groups. Participants allocated to the control group shall receive usual care plus a social visit. Participants allocated to the experimental group shall receive usual care and a falls prevention programme incorporating a video, workbook and individualised follow-up from an expert health professional to foster capability and motivation to engage in falls prevention strategies. The primary outcome is falls rates in the first 6 months after discharge, analysed using negative binomial regression with adjustment for participant's length of observation in the study. Secondary outcomes are injurious falls rates, the proportion of people who become fallers, functional status and health-related quality of life. Healthcare resource use will be captured from four sources for 6 months after discharge. The study is powered to detect a 30% relative reduction in the rate of falls (negative binomial incidence ratio 0.70) for a control rate of 0.80 falls per person over 6 months. Ethics and dissemination Results will be presented in peer-reviewed journals and at conferences worldwide. This study is approved by hospital and university Human Research Ethics Committees. Trial registration number ACTRN12615000784516. PMID:28153933

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018

PubMed Central

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-01-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks. PMID:29717695

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018.

PubMed

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-04-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks.

Health Communication in Social Media: Message Features Predicting User Engagement on Diabetes-Related Facebook Pages.

PubMed

Rus, Holly M; Cameron, Linda D

2016-10-01

Social media provides unprecedented opportunities for enhancing health communication and health care, including self-management of chronic conditions such as diabetes. Creating messages that engage users is critical for enhancing message impact and dissemination. This study analyzed health communications within ten diabetes-related Facebook pages to identify message features predictive of user engagement. The Common-Sense Model of Illness Self-Regulation and established health communication techniques guided content analyses of 500 Facebook posts. Each post was coded for message features predicted to engage users and numbers of likes, shares, and comments during the week following posting. Multi-level, negative binomial regressions revealed that specific features predicted different forms of engagement. Imagery emerged as a strong predictor; messages with images had higher rates of liking and sharing relative to messages without images. Diabetes consequence information and positive identity predicted higher sharing while negative affect, social support, and crowdsourcing predicted higher commenting. Negative affect, crowdsourcing, and use of external links predicted lower sharing while positive identity predicted lower commenting. The presence of imagery weakened or reversed the positive relationships of several message features with engagement. Diabetes control information and negative affect predicted more likes in text-only messages, but fewer likes when these messages included illustrative imagery. Similar patterns of imagery's attenuating effects emerged for the positive relationships of consequence information, control information, and positive identity with shares and for positive relationships of negative affect and social support with comments. These findings hold promise for guiding communication design in health-related social media.

Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis.

PubMed

Cook, Richard J; Wei, Wei

2003-07-01

The design of clinical trials is typically based on marginal comparisons of a primary response under two or more treatments. The considerable gains in efficiency afforded by models conditional on one or more baseline responses has been extensively studied for Gaussian models. The purpose of this article is to present methods for the design and analysis of clinical trials in which the response is a count or a point process, and a corresponding baseline count is available prior to randomization. The methods are based on a conditional negative binomial model for the response given the baseline count and can be used to examine the effect of introducing selection criteria on power and sample size requirements. We show that designs based on this approach are more efficient than those proposed by McMahon et al. (1994).

Are autism spectrum conditions more prevalent in an information-technology region? A school-based study of three regions in the Netherlands.

PubMed

Roelfsema, Martine T; Hoekstra, Rosa A; Allison, Carrie; Wheelwright, Sally; Brayne, Carol; Matthews, Fiona E; Baron-Cohen, Simon

2012-05-01

We tested for differences in the prevalence of autism spectrum conditions (ASC) in school-aged children in three geographical regions in the Netherlands. Schools were asked to provide the number of children enrolled, the number having a clinical diagnosis of ASC and/or two control neurodevelopmental conditions. Prevalence was evaluated by negative binomial regression and adjustments were made for non-response and size of the schools. The prevalence estimates of ASC in Eindhoven was 229 per 10,000, significantly higher than in Haarlem (84 per 10,000) and Utrecht (57 per 10,000), whilst the prevalence for the control conditions were similar in all regions. Phase two is planned to validate school-reported cases using standardized diagnostic methods and to explore the possible causes for these differences.

Functional limitations as potential mediators of the effects of self-reported vision status on fall risk of older adults.

PubMed

Steinman, Bernard A; Allen, Susan M; Chen, Jie; Pynoos, Jon

2015-02-01

To test whether limitations in mobility and large-muscle functioning mediate self-reported vision status to increase fall risk among respondents age 65 and above. This study used two waves from the Health and Retirement Study. We conducted binary logistic and negative binomial regression analyses to test indirect paths leading from self-reported vision status to falls, via indices of mobility and large-muscle functioning. Limited evidence was found for a mediating effect among women; however, large-muscle groups were implicated as partially mediating risk factors for falls among men with fair self-reported vision status. Implications of these findings are discussed including the need for prioritizing improved muscle strength of older men and women with poor vision as a preventive measure against falls. © The Author(s) 2014.

Child Schooling in Ethiopia: The Role of Maternal Autonomy.

PubMed

Gebremedhin, Tesfaye Alemayehu; Mohanty, Itismita

2016-01-01

This paper examines the effects of maternal autonomy on child schooling outcomes in Ethiopia using a nationally representative Ethiopian Demographic and Health survey for 2011. The empirical strategy uses a Hurdle Negative Binomial Regression model to estimate years of schooling. An ordered probit model is also estimated to examine age grade distortion using a trichotomous dependent variable that captures three states of child schooling. The large sample size and the range of questions available in this dataset allow us to explore the influence of individual and household level social, economic and cultural factors on child schooling. The analysis finds statistically significant effects of maternal autonomy variables on child schooling in Ethiopia. The roles of maternal autonomy and other household-level factors on child schooling are important issues in Ethiopia, where health and education outcomes are poor for large segments of the population.

Comparing statistical methods for analyzing skewed longitudinal count data with many zeros: an example of smoking cessation.

PubMed

Xie, Haiyi; Tao, Jill; McHugo, Gregory J; Drake, Robert E

2013-07-01

Count data with skewness and many zeros are common in substance abuse and addiction research. Zero-adjusting models, especially zero-inflated models, have become increasingly popular in analyzing this type of data. This paper reviews and compares five mixed-effects Poisson family models commonly used to analyze count data with a high proportion of zeros by analyzing a longitudinal outcome: number of smoking quit attempts from the New Hampshire Dual Disorders Study. The findings of our study indicated that count data with many zeros do not necessarily require zero-inflated or other zero-adjusting models. For rare event counts or count data with small means, a simpler model such as the negative binomial model may provide a better fit. Copyright © 2013 Elsevier Inc. All rights reserved.

Firearm homicide in Australia, Canada, and New Zealand: what can we learn from long-term international comparisons?

PubMed

McPhedran, Samara; Baker, Jeanine; Singh, Pooja

2011-01-01

Although firearm homicide remains a topic of interest within criminological and policy discourse, existing research does not generally undertake longitudinal comparisons between countries. However, cross-country comparisons provide insight into whether "local" trends (e.g., declines in firearm homicide in one particular country) differ from broader, international trends. This in turn can improve knowledge about the role of factors such as policing practices and socioeconomic variables in the incidence of lethal violence using firearms. The current study compares long-term firearm homicide trends in three countries with similar social histories but different legislative regimes: Australia, Canada, and New Zealand. Using negative binomial regression, the study found that the most pronounced decline in firearm homicide over the past two decades occurred in New Zealand. Connections between social disadvantage, policing policy, and violence are discussed.

Factors associated with the relationship between motorcycle deaths and economic growth.

PubMed

Law, Teik Hua; Noland, Robert B; Evans, Andrew W

2009-03-01

This paper examines the Kuznets curve relationship for motorcycle deaths. The Kuznets curve describes the inverted U-shape relationship between economic development and, in this case, motorcycle deaths. In early stages of development we expect deaths to increase with increasing motorization. Eventually deaths decrease as technical, policy and political institutions respond to demands for increased safety. We examine this effect as well as some of the factors which might explain the Kuznets relationship: in particular motorcycle helmet laws, medical care and technology improvements, and variables representing the quality of political institutions. We apply a fixed effects negative binomial regression analysis on a panel of 25 countries covering the period 1970-1999. Our results broadly suggest that implementation of road safety regulation, improvement in the quality of political institutions, and medical care and technology developments have contributed to reduced motorcycle deaths.

Bursts of Self-Conscious Emotions in the Daily Lives of Emerging Adults

PubMed Central

Conroy, David E.; Ram, Nilam; Pincus, Aaron L.; Rebar, Amanda L.

2015-01-01

Self-conscious emotions play a role in regulating daily achievement strivings, social behavior, and health, but little is known about the processes underlying their daily manifestation. Emerging adults (n = 182) completed daily diaries for eight days and multilevel models were estimated to evaluate whether, how much, and why their emotions varied from day-to-day. Within-person variation in authentic pride was normally-distributed across people and days whereas the other emotions were burst-like and characterized by zero-inflated, negative binomial distributions. Perceiving social interactions as generally communal increased the odds of hubristic pride activation and reduced the odds of guilt activation; daily communal behavior reduced guilt intensity. Results illuminated processes through which meaning about the self-in-relation-to-others is constructed during a critical period of development. PMID:25859164

Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations

USGS Publications Warehouse

Dorazio, R.M.; Jelks, H.L.; Jordan, F.

2005-01-01

 A statistical modeling framework is described for estimating the abundances of spatially distinct subpopulations of animals surveyed using removal sampling. To illustrate this framework, hierarchical models are developed using the Poisson and negative-binomial distributions to model variation in abundance among subpopulations and using the beta distribution to model variation in capture probabilities. These models are fitted to the removal counts observed in a survey of a federally endangered fish species. The resulting estimates of abundance have similar or better precision than those computed using the conventional approach of analyzing the removal counts of each subpopulation separately. Extension of the hierarchical models to include spatial covariates of abundance is straightforward and may be used to identify important features of an animal's habitat or to predict the abundance of animals at unsampled locations.

Analysis of railroad tank car releases using a generalized binomial model.

PubMed

Liu, Xiang; Hong, Yili

2015-11-01

The United States is experiencing an unprecedented boom in shale oil production, leading to a dramatic growth in petroleum crude oil traffic by rail. In 2014, U.S. railroads carried over 500,000 tank carloads of petroleum crude oil, up from 9500 in 2008 (a 5300% increase). In light of continual growth in crude oil by rail, there is an urgent national need to manage this emerging risk. This need has been underscored in the wake of several recent crude oil release incidents. In contrast to highway transport, which usually involves a tank trailer, a crude oil train can carry a large number of tank cars, having the potential for a large, multiple-tank-car release incident. Previous studies exclusively assumed that railroad tank car releases in the same train accident are mutually independent, thereby estimating the number of tank cars releasing given the total number of tank cars derailed based on a binomial model. This paper specifically accounts for dependent tank car releases within a train accident. We estimate the number of tank cars releasing given the number of tank cars derailed based on a generalized binomial model. The generalized binomial model provides a significantly better description for the empirical tank car accident data through our numerical case study. This research aims to provide a new methodology and new insights regarding the further development of risk management strategies for improving railroad crude oil transportation safety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Diagnostic test accuracy and prevalence inferences based on joint and sequential testing with finite population sampling.

PubMed

Su, Chun-Lung; Gardner, Ian A; Johnson, Wesley O

2004-07-30

The two-test two-population model, originally formulated by Hui and Walter, for estimation of test accuracy and prevalence estimation assumes conditionally independent tests, constant accuracy across populations and binomial sampling. The binomial assumption is incorrect if all individuals in a population e.g. child-care centre, village in Africa, or a cattle herd are sampled or if the sample size is large relative to population size. In this paper, we develop statistical methods for evaluating diagnostic test accuracy and prevalence estimation based on finite sample data in the absence of a gold standard. Moreover, two tests are often applied simultaneously for the purpose of obtaining a 'joint' testing strategy that has either higher overall sensitivity or specificity than either of the two tests considered singly. Sequential versions of such strategies are often applied in order to reduce the cost of testing. We thus discuss joint (simultaneous and sequential) testing strategies and inference for them. Using the developed methods, we analyse two real and one simulated data sets, and we compare 'hypergeometric' and 'binomial-based' inferences. Our findings indicate that the posterior standard deviations for prevalence (but not sensitivity and specificity) based on finite population sampling tend to be smaller than their counterparts for infinite population sampling. Finally, we make recommendations about how small the sample size should be relative to the population size to warrant use of the binomial model for prevalence estimation. Copyright 2004 John Wiley & Sons, Ltd.

Solar San Diego: The Impact of Binomial Rate Structures on Real PV-Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Geet, O.; Brown, E.; Blair, T.

2008-01-01

There is confusion in the marketplace regarding the impact of solar photovoltaics (PV) on the user's actual electricity bill under California Net Energy Metering, particularly with binomial tariffs (those that include both demand and energy charges) and time-of-use (TOU) rate structures. The City of San Diego has extensive real-time electrical metering on most of its buildings and PV systems, with interval data for overall consumption and PV electrical production available for multiple years. This paper uses 2007 PV-system data from two city facilities to illustrate the impacts of binomial rate designs. The analysis will determine the energy and demand savingsmore » that the PV systems are achieving relative to the absence of systems. A financial analysis of PV-system performance under various rates structures is presented. The data revealed that actual demand and energy use benefits of bionomial tariffs increase in summer months, when solar resources allow for maximized electricity production. In a binomial tariff system, varying on- and semi-peak times can result in approximately $1,100 change in demand charges per month over not having a PV system in place, an approximate 30% cost savings. The PV systems are also shown to have a 30%-50% reduction in facility energy charges in 2007. Future work will include combining demand and electricity charges and increasing the breadth of rate structures tested, including the impacts of non-coincident demand charges.« less

Analysis of multiple tank car releases in train accidents.

PubMed

Liu, Xiang; Liu, Chang; Hong, Yili

2017-10-01

There are annually over two million carloads of hazardous materials transported by rail in the United States. The American railroads use large blocks of tank cars to transport petroleum crude oil and other flammable liquids from production to consumption sites. Being different from roadway transport of hazardous materials, a train accident can potentially result in the derailment and release of multiple tank cars, which may result in significant consequences. The prior literature predominantly assumes that the occurrence of multiple tank car releases in a train accident is a series of independent Bernoulli processes, and thus uses the binomial distribution to estimate the total number of tank car releases given the number of tank cars derailing or damaged. This paper shows that the traditional binomial model can incorrectly estimate multiple tank car release probability by magnitudes in certain circumstances, thereby significantly affecting railroad safety and risk analysis. To bridge this knowledge gap, this paper proposes a novel, alternative Correlated Binomial (CB) model that accounts for the possible correlations of multiple tank car releases in the same train. We test three distinct correlation structures in the CB model, and find that they all outperform the conventional binomial model based on empirical tank car accident data. The analysis shows that considering tank car release correlations would result in a significantly improved fit of the empirical data than otherwise. Consequently, it is prudent to consider alternative modeling techniques when analyzing the probability of multiple tank car releases in railroad accidents. Copyright © 2017 Elsevier Ltd. All rights reserved.

A review of statistical estimators for risk-adjusted length of stay: analysis of the Australian and new Zealand Intensive Care Adult Patient Data-Base, 2008-2009.

PubMed

Moran, John L; Solomon, Patricia J

2012-05-16

For the analysis of length-of-stay (LOS) data, which is characteristically right-skewed, a number of statistical estimators have been proposed as alternatives to the traditional ordinary least squares (OLS) regression with log dependent variable. Using a cohort of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 2008-2009, 12 different methods were used for estimation of intensive care (ICU) length of stay. These encompassed risk-adjusted regression analysis of firstly: log LOS using OLS, linear mixed model [LMM], treatment effects, skew-normal and skew-t models; and secondly: unmodified (raw) LOS via OLS, generalised linear models [GLMs] with log-link and 4 different distributions [Poisson, gamma, negative binomial and inverse-Gaussian], extended estimating equations [EEE] and a finite mixture model including a gamma distribution. A fixed covariate list and ICU-site clustering with robust variance were utilised for model fitting with split-sample determination (80%) and validation (20%) data sets, and model simulation was undertaken to establish over-fitting (Copas test). Indices of model specification using Bayesian information criterion [BIC: lower values preferred] and residual analysis as well as predictive performance (R2, concordance correlation coefficient (CCC), mean absolute error [MAE]) were established for each estimator. The data-set consisted of 111663 patients from 131 ICUs; with mean(SD) age 60.6(18.8) years, 43.0% were female, 40.7% were mechanically ventilated and ICU mortality was 7.8%. ICU length-of-stay was 3.4(5.1) (median 1.8, range (0.17-60)) days and demonstrated marked kurtosis and right skew (29.4 and 4.4 respectively). BIC showed considerable spread, from a maximum of 509801 (OLS-raw scale) to a minimum of 210286 (LMM). R2 ranged from 0.22 (LMM) to 0.17 and the CCC from 0.334 (LMM) to 0.149, with MAE 2.2-2.4. Superior residual behaviour was established for the log-scale estimators. There was a general tendency for over-prediction (negative residuals) and for over-fitting, the exception being the GLM negative binomial estimator. The mean-variance function was best approximated by a quadratic function, consistent with log-scale estimation; the link function was estimated (EEE) as 0.152(0.019, 0.285), consistent with a fractional-root function. For ICU length of stay, log-scale estimation, in particular the LMM, appeared to be the most consistently performing estimator(s). Neither the GLM variants nor the skew-regression estimators dominated.

A binomial stochastic kinetic approach to the Michaelis-Menten mechanism

NASA Astrophysics Data System (ADS)

Lente, Gábor

2013-05-01

This Letter presents a new method that gives an analytical approximation of the exact solution of the stochastic Michaelis-Menten mechanism without computationally demanding matrix operations. The method is based on solving the deterministic rate equations and then using the results as guiding variables of calculating probability values using binomial distributions. This principle can be generalized to a number of different kinetic schemes and is expected to be very useful in the evaluation of measurements focusing on the catalytic activity of one or a few individual enzyme molecules.

Taxonomy of the order Mononegavirales: update 2017.

PubMed

Amarasinghe, Gaya K; Bào, Yīmíng; Basler, Christopher F; Bavari, Sina; Beer, Martin; Bejerman, Nicolás; Blasdell, Kim R; Bochnowski, Alisa; Briese, Thomas; Bukreyev, Alexander; Calisher, Charles H; Chandran, Kartik; Collins, Peter L; Dietzgen, Ralf G; Dolnik, Olga; Dürrwald, Ralf; Dye, John M; Easton, Andrew J; Ebihara, Hideki; Fang, Qi; Formenty, Pierre; Fouchier, Ron A M; Ghedin, Elodie; Harding, Robert M; Hewson, Roger; Higgins, Colleen M; Hong, Jian; Horie, Masayuki; James, Anthony P; Jiāng, Dàohóng; Kobinger, Gary P; Kondo, Hideki; Kurath, Gael; Lamb, Robert A; Lee, Benhur; Leroy, Eric M; Li, Ming; Maisner, Andrea; Mühlberger, Elke; Netesov, Sergey V; Nowotny, Norbert; Patterson, Jean L; Payne, Susan L; Paweska, Janusz T; Pearson, Michael N; Randall, Rick E; Revill, Peter A; Rima, Bertus K; Rota, Paul; Rubbenstroth, Dennis; Schwemmle, Martin; Smither, Sophie J; Song, Qisheng; Stone, David M; Takada, Ayato; Terregino, Calogero; Tesh, Robert B; Tomonaga, Keizo; Tordo, Noël; Towner, Jonathan S; Vasilakis, Nikos; Volchkov, Viktor E; Wahl-Jensen, Victoria; Walker, Peter J; Wang, Beibei; Wang, David; Wang, Fei; Wang, Lin-Fa; Werren, John H; Whitfield, Anna E; Yan, Zhichao; Ye, Gongyin; Kuhn, Jens H

2017-08-01

In 2017, the order Mononegavirales was expanded by the inclusion of a total of 69 novel species. Five new rhabdovirus genera and one new nyamivirus genus were established to harbor 41 of these species, whereas the remaining new species were assigned to already established genera. Furthermore, non-Latinized binomial species names replaced all paramyxovirus and pneumovirus species names, thereby accomplishing application of binomial species names throughout the entire order. This article presents the updated taxonomy of the order Mononegavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV).

Categorical Data Analysis Using a Skewed Weibull Regression Model

NASA Astrophysics Data System (ADS)

Caron, Renault; Sinha, Debajyoti; Dey, Dipak; Polpo, Adriano

2018-03-01

In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as frequentist estimation procedures for binomial and multinomial data responses are presented in details. The analysis of two data sets to show the efficiency of the proposed model is performed.

Tuberculosis in HIV-infected South African children with complicated severe acute malnutrition.

PubMed

Adler, H; Archary, M; Mahabeer, P; LaRussa, P; Bobat, R A

2017-04-01

Academic tertiary referral hospital in Durban, South Africa. To describe the incidence and diagnostic challenges of tuberculosis (TB) in human immunodeficiency virus (HIV) infected children with severe acute malnutrition (SAM). Post-hoc analysis of a randomised controlled trial that enrolled antiretroviral therapy naïve, HIV-infected children with SAM. Trial records and hospital laboratory results were explored for clinical diagnoses and bacteriologically confirmed cases of TB. Negative binomial regression was used to explore associations with confirmed cases of TB, excluding cases where the clinical diagnosis was not supported by microbiological confirmation. Of 82 children enrolled in the study, 21 (25.6%) were diagnosed with TB, with bacteriological confirmation in 8 cases. Sputum sampling (as opposed to gastric washings) was associated with an increased risk of subsequent diagnosis of TB (adjusted relative risk [aRR] 1.134, 95%CI 1.02-1.26). Culture-proven bacterial infection during admission was associated with a reduced risk of TB (aRR 0.856, 95%CI 0.748-0.979), which may reflect false-negative microbiological tests secondary to empiric broad-spectrum antibiotics. TB is common in HIV-infected children with SAM. While microbiological confirmation of the diagnosis is feasible, empiric treatment remains common, possibly influenced by suboptimal testing and false-negative TB diagnostics. Rigorous microbiological TB investigation should be integrated into the programmatic management of HIV and SAM.

Examining the Relationship between Marijuana Use, Medical Marijuana Dispensaries, and Abusive and Neglectful Parenting

PubMed Central

Freisthler, Bridget; Gruenewald, Paul J.; Wolf, Jennifer Price

2015-01-01

The current study extends previous research by examining whether and how current marijuana use and the physical availability of marijuana are related to child physical abuse, supervisory neglect, or physical neglect by parents while controlling for child, caregiver, and family characteristics in a general population survey in California. Individual level data on marijuana use and abusive and neglectful parenting were collected during a telephone survey of 3,023 respondents living in 50 mid-size cities in California. Medical marijuana dispensaries and delivery services data were obtained via six websites and official city lists. Data were analyzed using negative binomial and linear mixed effects multilevel models with individuals nested within cities. Current marijuana use was positively related to frequency of child physical abuse and negatively related to physical neglect. There was no relationship between supervisory neglect and marijuana use. Density of medical marijuana dispensaries and delivery services was positively related to frequency of physical abuse. As marijuana use becomes more prevalent, those who work with families, including child welfare workers must screen for how marijuana use may affect a parent’s ability to provide for care for their children, particularly related to physical abuse. PMID:26198452

Spanish language proficiency among providers and Latino clients' engagement in substance abuse treatment.

PubMed

Guerrero, Erick G; Khachikian, Tenie; Kim, Tina; Kong, Yinfei; Vega, William A

2013-12-01

Quality of care, such as provision of services in Spanish, is a common factor believed to improve treatment engagement among Spanish-speaking Latinos in health care. However, there is little evidence that Spanish language proficiency among providers increases treatment access and retention in publicly funded substance abuse treatment. We analyzed client and program data collected in 2010-2011 from publicly funded treatment programs in Los Angeles County, California. An analytic sample of 1903 Latino clients nested within 40 treatment programs located in minority communities was analyzed using multilevel negative binomial regressions on days to initiate and spent in treatment. As hypothesized, Spanish language proficiency was negatively associated with client wait time and positively associated with retention in treatment, after controlling for individual and program characteristics. The path analysis models showed that Spanish language proficiency played a mediating role between professional accreditation and client wait time and retention. These preliminary findings provide an evidentiary base for the role of providers' Spanish language proficiency and Latino engagement in treatment for a population at high risk of treatment dropout. Implications related to health care reform legislation, which seeks to enhance linguistically competent care, are discussed. © 2013.

Work hours and absenteeism among police officers.

PubMed

Fekedulegn, Desta; Burchfiel, Cecil M; Hartley, Tara A; Baughman, Penelope; Charles, Luenda E; Andrew, Michael E; Violanti, John M

2013-01-01

In this study, the cross-sectional association of paid work hours with episodes of work absence was examined in a cohort of police officers. Study subjects were participants from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study examined between 2004 and 2009. Among 395 study participants with complete data, day-by-day work history records during the one-year period prior to date of examination were used to determine episodes of one-day and three day work absence. The Negative binomial regression analysis was used to examine rate ratios (RR) of work absence. Analyses were also stratified by gender. A one-hour increase in total work hours was associated with 5% reduction in rate of one-day work absence (RR = 0.95, 95% CI: 0.92 - 0.98) and with 8% reduction in rate of three-day work absence (RR = 0.92, 95% CI: 0.89 - 0.95). The association of total work hours with episodes of one-day work absence was significant only in men while the association with episodes of three-day work absence was evident in men and women. In conclusion, in this cohort of police officers, work hours were negatively associated with both durations of work absence (one-day, > or = 3 consecutive days).

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

PubMed

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Meteorological factors affecting scrub typhus occurrence: a retrospective study of Yamagata Prefecture, Japan, 1984-2014.

PubMed

Seto, J; Suzuki, Y; Nakao, R; Otani, K; Yahagi, K; Mizuta, K

2017-02-01

Climate change, by its influence on the ecology of vectors might affect the occurrence of vector-borne diseases. This study examines the effects of meteorological factors in Japan on the occurrence of scrub typhus, a mite-borne zoonosis caused by Orientia tsutsugamushi. Using negative binomial regression, we analysed the relationships between meteorological factors (including temperature, rainfall, snowfall) and spring-early summer cases of scrub typhus in Yamagata Prefecture, Japan, during 1984-2014. The average temperature in July and August of the previous year, cumulative rainfall in September of the previous year, snowfall throughout the winter, and maximum depth of snow cover in January and February were positively correlated with the number of scrub typhus cases. By contrast, cumulative rainfall in July of the previous year showed a negative relationship to the number of cases. These associations can be explained by the life-cycle of Leptotrombidium pallidum, a predominant vector of spring-early summer cases of scrub typhus in northern Japan. Our findings show that several meteorological factors are useful to estimate the number of scrub typhus cases before the endemic period. They are applicable to establish an early warning system for scrub typhus in northern Japan.

The effects of temperament, psychopathy, and childhood trauma among delinquent youth: A test of DeLisi and Vaughn's temperament-based theory of crime.

PubMed

DeLisi, Matt; Fox, Bryanna H; Fully, Matthew; Vaughn, Michael G

Recent interest among criminologists on the construct of temperament has been fueled by DeLisi and Vaughn's (2014) temperament-based theory of antisocial behavior. Their theory suggests that core self-regulation capacity and negative emotionality are the most salient temperament features for understanding the emergence and maintenance of antisocial and violent behavior, even among offending populations. The present study tests the relative effects of these temperamental features along with psychopathic traits and trauma in their association with violent and non-violent delinquency in a sample of 252 juvenile offenders. Results from a series of negative binomial regression models indicate that temperament was uniformly more strongly associated with violent and non-violent delinquency than psychopathic traits and childhood traumatic events. Exploratory classification models suggested that temperament and psychopathy possessed similar predictive capacity, but neither surpassed prior history of violence and delinquency as a predictor of future offending. Overall, findings are supportive of DeLisi and Vaughn's temperament-based theory and suggest temperament as conceptualized and measured in the present study may play an important role as a risk factor for violent and non-violent delinquency. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling Polio Data Using the First Order Non-Negative Integer-Valued Autoregressive, INAR(1), Model

NASA Astrophysics Data System (ADS)

Vazifedan, Turaj; Shitan, Mahendran

Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.

Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

PubMed Central

Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

2018-01-01

Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

Metaprop: a Stata command to perform meta-analysis of binomial data.

PubMed

Nyaga, Victoria N; Arbyn, Marc; Aerts, Marc

2014-01-01

Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Appropriate and accessible statistical software is needed to produce the summary statistic of interest. Metaprop is a statistical program implemented to perform meta-analyses of proportions in Stata. It builds further on the existing Stata procedure metan which is typically used to pool effects (risk ratios, odds ratios, differences of risks or means) but which is also used to pool proportions. Metaprop implements procedures which are specific to binomial data and allows computation of exact binomial and score test-based confidence intervals. It provides appropriate methods for dealing with proportions close to or at the margins where the normal approximation procedures often break down, by use of the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances. Metaprop was applied on two published meta-analyses: 1) prevalence of HPV-infection in women with a Pap smear showing ASC-US; 2) cure rate after treatment for cervical precancer using cold coagulation. The first meta-analysis showed a pooled HPV-prevalence of 43% (95% CI: 38%-48%). In the second meta-analysis, the pooled percentage of cured women was 94% (95% CI: 86%-97%). By using metaprop, no studies with 0% or 100% proportions were excluded from the meta-analysis. Furthermore, study specific and pooled confidence intervals always were within admissible values, contrary to the original publication, where metan was used.

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

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.

Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatterjee, Abhijit; Vlachos, Dionisios G.

The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less

Estimating relative risks for common outcome using PROC NLP.

PubMed

Yu, Binbing; Wang, Zhuoqiao

2008-05-01

In cross-sectional or cohort studies with binary outcomes, it is biologically interpretable and of interest to estimate the relative risk or prevalence ratio, especially when the response rates are not rare. Several methods have been used to estimate the relative risk, among which the log-binomial models yield the maximum likelihood estimate (MLE) of the parameters. Because of restrictions on the parameter space, the log-binomial models often run into convergence problems. Some remedies, e.g., the Poisson and Cox regressions, have been proposed. However, these methods may give out-of-bound predicted response probabilities. In this paper, a new computation method using the SAS Nonlinear Programming (NLP) procedure is proposed to find the MLEs. The proposed NLP method was compared to the COPY method, a modified method to fit the log-binomial model. Issues in the implementation are discussed. For illustration, both methods were applied to data on the prevalence of microalbuminuria (micro-protein leakage into urine) for kidney disease patients from the Diabetes Control and Complications Trial. The sample SAS macro for calculating relative risk is provided in the appendix.

The influence of economic incentives linked to road safety indicators on accidents: the case of toll concessions in Spain.

PubMed

Rangel, Thais; Vassallo, José Manuel; Herraiz, Israel

2013-10-01

The goal of this paper is to evaluate whether the incentives incorporated in toll highway concession contracts in order to encourage private operators to adopt measures to reduce accidents are actually effective at improving safety. To this end, we implemented negative binomial regression models using information about highway characteristics and accident data from toll highway concessions in Spain from 2007 to 2009. Our results show that even though road safety is highly influenced by variables that are not managed by the contractor, such as the annual average daily traffic (AADT), the percentage of heavy vehicles on the highway, number of lanes, number of intersections and average speed; the implementation of these incentives has a positive influence on the reduction of accidents and injuries. Consequently, this measure seems to be an effective way of improving safety performance in road networks. Copyright © 2013 Elsevier Ltd. All rights reserved.

Work-related injuries involving a hand or fingers among union carpenters in Washington State, 1989 to 2008.

PubMed

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.

Environmental Risk Factors influencing Bicycle Theft: A Spatial Analysis in London, UK.

PubMed

Mburu, Lucy Waruguru; Helbich, Marco

2016-01-01

Urban authorities are continuously drawing up policies to promote cycling among commuters. However, these initiatives are counterproductive for the targeted objectives because they increase opportunities for bicycle theft. This paper explores Inner London as a case study to address place-specific risk factors for bicycle theft at the street-segment level while controlling for seasonal variation. The presence of certain public amenities (e.g., bicycle stands, railway stations, pawnshops) was evaluated against locations of bicycle theft between 2013 and 2016 and risk effects were estimated using negative binomial regression models. Results showed that a greater level of risk stemmed from land-use facilities than from area-based socioeconomic status. The presence of facilities such as train stations, vacant houses, pawnbrokers and payday lenders increased bicycle theft, but no evidence was found that linked police stations with crime levels. The findings have significant implications for urban crime prevention with respect to non-residential land use.

Assessment of DSM-5 Section II Personality Disorders With the MMPI-2-RF in a Nonclinical Sample.

PubMed

Sellbom, Martin; Smith, Alexander

2017-01-01

The Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF; Ben-Porath & Tellegen, 2008 / 2011 ) is frequently used in clinical practice. However, there has been a dearth of literature on how well this instrument can assess symptoms associated with personality disorders (PDs). This investigation examined a range of hypothesized MMPI-2-RF scales in predicting PD symptoms. We evaluated these associations in a sample of 397 university students who had been administered the MMPI-2-RF and the Structured Clinical Interview for DSM-IV Axis II Disorders-Personality Questionnaire (First, Gibbon, Spitzer, Williams, & Benjamin, 1997 ). Zero-order correlation analyses and negative binomial regression models indicated that a wide range of MMPI-2-RF scale hypotheses were supported; however, the least support was available for predicting schizoid and obsessive-compulsive PDs. Implications for MMPI-2-RF interpretation and PD diagnosis are discussed.

Assessing the Macro-Level Correlates of Malware Infections Using a Routine Activities Framework.

PubMed

Holt, Thomas J; Burruss, George W; Bossler, Adam M

2018-05-01

The ability to gain unauthorized access to computer systems to engage in espionage and data theft poses a massive threat to individuals worldwide. There has been minimal focus, however, on the role of malicious software, or malware, which can automate this process. This study examined the macro-correlates of malware infection at the national level by using an open repository of known malware infections and utilizing a routine activities framework. Negative inflated binomial models for counts indicated that nations with greater technological infrastructure, more political freedoms, and with less organized crime financial impact were more likely to report malware infections. The number of Computer Emergency Response Teams (CERTs) in a nation was not significantly related with reported malware infection. The implications of the study for the understanding of malware infection, routine activity theory, and target-hardening strategies are discussed.

The Effect of Exposure to Ultraviolet Radiation in Infancy on Melanoma Risk.

PubMed

Gefeller, Olaf; Fiessler, Cornelia; Radespiel-Tröger, Martin; Uter, Wolfgang; Pfahlberg, Annette B

2016-01-01

Evidence on the effect of ultraviolet radiation (UVR) exposure in infancy on melanoma risk in later life is scarce. Three recent studies suffering from methodological shortcomings suggested that people born in spring carry a higher melanoma risk. Data from the Bavarian population-based cancer registry on 28374 incident melanoma cases between 2002 and 2012 were analyzed to reexamine this finding. Crude and adjusted analyses - using negative binomial regression models - were performed addressing the relationship. In the crude analysis, the birth months March - May were significantly overrepresented among melanoma cases. However, after additionally adjusting for the birth month distribution of the Bavarian population, the ostensible seasonal effect disappeared. Similar results emerged in all subgroup analyses. Our large registry-based study provides no evidence that people born in spring carry a higher risk for developing melanoma in later life and thus lends no support to the hypothesis of higher UVR-susceptibility during the first months of life.

On Statistical Modeling of Sequencing Noise in High Depth Data to Assess Tumor Evolution

NASA Astrophysics Data System (ADS)

Rabadan, Raul; Bhanot, Gyan; Marsilio, Sonia; Chiorazzi, Nicholas; Pasqualucci, Laura; Khiabanian, Hossein

2018-07-01

One cause of cancer mortality is tumor evolution to therapy-resistant disease. First line therapy often targets the dominant clone, and drug resistance can emerge from preexisting clones that gain fitness through therapy-induced natural selection. Such mutations may be identified using targeted sequencing assays by analysis of noise in high-depth data. Here, we develop a comprehensive, unbiased model for sequencing error background. We find that noise in sufficiently deep DNA sequencing data can be approximated by aggregating negative binomial distributions. Mutations with frequencies above noise may have prognostic value. We evaluate our model with simulated exponentially expanded populations as well as data from cell line and patient sample dilution experiments, demonstrating its utility in prognosticating tumor progression. Our results may have the potential to identify significant mutations that can cause recurrence. These results are relevant in the pretreatment clinical setting to determine appropriate therapy and prepare for potential recurrence pretreatment.

The role of self-efficacy and motivation to explain the effect of motivational interviewing time on changes in risky sexual behavior among people living with HIV: a mediation analysis.

PubMed

Chariyeva, Zulfiya; Golin, Carol E; Earp, Jo Anne; Maman, Suzanne; Suchindran, Chirayath; Zimmer, Catherine

2013-02-01

Little is known about the amount of Motivational Interviewing (MI) needed to reduce risky sexual behavior among People Living with HIV/AIDS (PLWHA) or the roles self-efficacy and motivation to practice safer sex play. Among 183 PLWHA who received safer sex MI and were surveyed every 4 months over a 12 month period, we used hierarchical negative binomial regression models to examine the association between amount of counseling time and sexual risk behavior. We performed mediation analysis to evaluate whether changes in self-efficacy and motivation explained this association. This study found that as MI time and number of provided sessions increased, participants' sexual risk behavior decreased. The effect of MI time and number of sessions on sexual behavior was mediated by self-efficacy but not by motivation to practice safer sex.

The Role of Self-Efficacy and Motivation to Explain the Effect of Motivational Interviewing Time on Changes in Risky Sexual Behavior among People Living with HIV: A Mediation Analysis

PubMed Central

Golin, Carol E.; Earp, Jo Anne; Maman, Suzanne; Suchindran, Chirayath; Zimmer, Catherine

2014-01-01

Little is known about the amount of Motivational Interviewing (MI) needed to reduce risky sexual behavior among People Living with HIV/AIDS (PLWHA) or the roles self-efficacy and motivation to practice safer sex play. Among 183 PLWHA who received safer sex MI and were surveyed every 4 months over a 12 month period, we used hierarchical negative binomial regression models to examine the association between amount of counseling time and sexual risk behavior. We performed mediation analysis to evaluate whether changes in self-efficacy and motivation explained this association. This study found that as MI time and number of provided sessions increased, participants’ sexual risk behavior decreased. The effect of MI time and number of sessions on sexual behavior was mediated by self-efficacy but not by motivation to practice safer sex. PMID:22228069

Adult Children's Education and Parents' Functional Limitations in Mexico.

PubMed

Yahirun, Jenjira J; Sheehan, Connor M; Hayward, Mark D

2016-04-01

This article asks how adult children's education influences older parents' physical health in Mexico, a context where older adults often lack access to institutional resources and rely on kin, primarily children, as a main source of support. Using logistic and negative binomial regression models and data from the first wave of the Mexican Health and Aging Study (N = 9,661), we find that parents whose children all completed high school are less likely to report any functional limitations as well as fewer limitations compared to parents with no children who completed high school. This association remains significant even after accounting for parent and offspring-level characteristics, including parents' income that accounts for children's financial transfers to parents. Future research should aim to understand the mechanisms that explain the association between adult children's education and changes to parents' health over time. © The Author(s) 2015.

Gastrointestinal parasite egg excretion in young calves in periurban livestock production in Mali.

PubMed

Wymann, Monica Natalie; Traore, Koniba; Bonfoh, Bassirou; Tembely, Saïdou; Tembely, Sékouba; Zinsstag, Jakob

2008-04-01

To acquire the information needed to improve parasite control in periurban cattle production in Mali, repeated sampling of faeces of 694 calves kept around Bamako was done in 2003/2004. The effects of season, age, breed, management type, parasite control and presence of sheep on egg and oocyst counts were determined. A Bayesian model was used with a negative binomial distribution and herd and individual effects, to account for the clustering of calves in herds and the repeated sampling. Interviews were conducted to report the current control strategies. We found eggs of Strongyloides papillosus (Age class 0-1 month: prevalence 39%, 2-3 months: 59%, 5-6 months: 42%), strongyles (14%, 24%, 36%), coccidian oocysts (37%, 68%, 64%) and at low prevalence eggs of Toxocara vitulorum, Moniezia sp., Trichuris sp. and Paramphistomum sp. Season and age effects occurred. Reported utilisation of parasite control was high (92%) but monthly recorded use was significantly lower (61%).

The Rainbow Spectrum of RNA Secondary Structures.

PubMed

Li, Thomas J X; Reidys, Christian M

2018-06-01

In this paper, we analyze the length spectrum of rainbows in RNA secondary structures. A rainbow in a secondary structure is a maximal arc with respect to the partial order induced by nesting. We show that there is a significant gap in this length spectrum. We shall prove that there asymptotically almost surely exists a unique longest rainbow of length at least [Formula: see text] and that with high probability any other rainbow has finite length. We show that the distribution of the length of the longest rainbow converges to a discrete limit law and that, for finite k, the distribution of rainbows of length k becomes for large n a negative binomial distribution. We then put the results of this paper into context, comparing the analytical results with those observed in RNA minimum free energy structures, biological RNA structures and relate our findings to the sparsification of folding algorithms.

Encephalitis, Ontario, Canada, 2002-2013.

PubMed

Parpia, Alyssa S; Li, Ye; Chen, Cynthia; Dhar, Badal; Crowcroft, Natasha S

2016-03-01

Encephalitis, a brain inflammation leading to severe illness and often death, is caused by >100 pathogens. To assess the incidence and trends of encephalitis in Ontario, Canada, we obtained data on 6,463 Ontario encephalitis hospitalizations from the hospital Discharge Abstract Database for April 2002-December 2013 and analyzed these data using multiple negative binomial regression. The estimated crude incidence of all-cause encephalitis in Ontario was ≈4.3 cases/100,000 persons/year. Incidence rates for infants <1 year of age and adults >65 years were 3.9 and 3.0 times that of adults 20-44 years of age, respectively. Incidence peaks during August-September in 2002 and 2012 resulted primarily from encephalitis of unknown cause and viral encephalitis. Encephalitis occurred more frequently in older age groups and less frequently in women in Ontario when compared to England, but despite differences in population, vector-borne diseases, climate, and geography, the epidemiology was overall remarkably similar in the two regions.

A Nationwide Study of Discrimination and Chronic Health Conditions Among Asian Americans

PubMed Central

Gee, Gilbert C.; Spencer, Michael S.; Chen, Juan; Takeuchi, David

2007-01-01

Objectives. We examined whether self-reported everyday discrimination was associated with chronic health conditions among a nationally representative sample of Asian Americans. Methods. Data were from the Asian American subsample (n = 2095) of the National Latino and Asian American Study conducted in 2002 and 2003. Regression techniques (negative binomial and logistic) were used to examine the association between discrimination and chronic health conditions. Analyses were conducted for the entire sample and 3 Asian subgroups (Chinese, Vietnamese, and Filipino). Results. Reports of everyday discrimination were associated with many chronic conditions, after we controlled for age, gender, region, per capita income, education, employment, and social desirability bias. Discrimination was also associated with indicators of heart disease, pain, and respiratory illnesses. There were some differences by Asian subgroup. Conclusions. Everyday discrimination may contribute to stress experienced by racial/ethnic minorities and could lead to chronic illness. PMID:17538055

Child Schooling in Ethiopia: The Role of Maternal Autonomy

PubMed Central

Mohanty, Itismita

2016-01-01

This paper examines the effects of maternal autonomy on child schooling outcomes in Ethiopia using a nationally representative Ethiopian Demographic and Health survey for 2011. The empirical strategy uses a Hurdle Negative Binomial Regression model to estimate years of schooling. An ordered probit model is also estimated to examine age grade distortion using a trichotomous dependent variable that captures three states of child schooling. The large sample size and the range of questions available in this dataset allow us to explore the influence of individual and household level social, economic and cultural factors on child schooling. The analysis finds statistically significant effects of maternal autonomy variables on child schooling in Ethiopia. The roles of maternal autonomy and other household-level factors on child schooling are important issues in Ethiopia, where health and education outcomes are poor for large segments of the population. PMID:27942039

Mental Health Symptoms Among Student Service Members/Veterans and Civilian College Students.

PubMed

Cleveland, Sandi D; Branscum, Adam J; Bovbjerg, Viktor E; Thorburn, Sheryl

2015-01-01

The aim of this study was to investigate if and to what extent student service members/veterans differ from civilian college students in the prevalence of self-reported symptoms of poor mental health. The Fall 2011 implementation of the American College Health Association-National College Health Assessment included 27,774 respondents from 44 colleges and universities. Participants were matched using propensity scores, and the prevalence of symptoms was compared using logistic regression and zero-inflated negative binomial regression models. The odds of feeling overwhelmed in the last 12 months were significantly lower among student service members/veterans with a history of hazardous duty (odd ratio [OR] = 0.46, adjusted p value <.05) compared with civilian students. Military service, with and without hazardous duty deployment, was not a significant predictor of the total number of symptoms of poor mental health. Current student service members/veterans may not be disproportionately affected by poor psychological functioning.

Work performance decrements are associated with Australian working conditions, particularly the demand to work longer hours.

PubMed

Holden, Libby; Scuffham, Paul A; Hilton, Michael F; Vecchio, Nerina N; Whiteford, Harvey A

2010-03-01

To demonstrate the importance of including a range of working conditions in models exploring the association between health- and work-related performance. The Australian Work Outcomes Research Cost-benefit study cross-sectional screening data set was used to explore health-related absenteeism and work performance losses on a sample of approximately 78,000 working Australians, including available demographic and working condition factors. Data collected using the World Health Organization Health and Productivity Questionnaire were analyzed with negative binomial logistic regression and multinomial logistic regressions for absenteeism and work performance, respectively. Hours expected to work, annual wage, and job insecurity play a vital role in the association between health- and work-related performance for both work attendance and self-reported work performance. Australian working conditions are contributing to both absenteeism and low work performance, regardless of health status.

A Stab in the Dark?: A Research Note on Temporal Patterns of Street Robbery.

PubMed

Tompson, Lisa; Bowers, Kate

2013-11-01

Test the influence of darkness in the street robbery crime event alongside temperature. Negative binomial regression models tested darkness and temperature as predictors of street robbery. Units of analysis were four 6-hr time intervals in two U.K. study areas that have different levels of darkness and variations of temperature throughout the year. Darkness is a key factor related to robbery events in both study areas. Traversing from full daylight to full darkness increased the predicted volume of robbery by a multiple of 2.6 in London and 1.2 in Glasgow. Temperature was significant only in the London study area. Interaction terms did not enhance the predictive power of the models. Darkness is an important driving factor in seasonal variation of street robbery. A further implication of the research is that time of the day patterns are crucial to understanding seasonal trends in crime data.

Modeling species-abundance relationships in multi-species collections

USGS Publications Warehouse

Peng, S.; Yin, Z.; Ren, H.; Guo, Q.

2003-01-01

Species-abundance relationship is one of the most fundamental aspects of community ecology. Since Motomura first developed the geometric series model to describe the feature of community structure, ecologists have developed many other models to fit the species-abundance data in communities. These models can be classified into empirical and theoretical ones, including (1) statistical models, i.e., negative binomial distribution (and its extension), log-series distribution (and its extension), geometric distribution, lognormal distribution, Poisson-lognormal distribution, (2) niche models, i.e., geometric series, broken stick, overlapping niche, particulate niche, random assortment, dominance pre-emption, dominance decay, random fraction, weighted random fraction, composite niche, Zipf or Zipf-Mandelbrot model, and (3) dynamic models describing community dynamics and restrictive function of environment on community. These models have different characteristics and fit species-abundance data in various communities or collections. Among them, log-series distribution, lognormal distribution, geometric series, and broken stick model have been most widely used.

Understanding poisson regression.

PubMed

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.

Older driver fitness-to-drive evaluation using naturalistic driving data.

PubMed

Guo, Feng; Fang, Youjia; Antin, Jonathan F

2015-09-01

As our driving population continues to age, it is becoming increasingly important to find a small set of easily administered fitness metrics that can meaningfully and reliably identify at-risk seniors requiring more in-depth evaluation of their driving skills and weaknesses. Sixty driver assessment metrics related to fitness-to-drive were examined for 20 seniors who were followed for a year using the naturalistic driving paradigm. Principal component analysis and negative binomial regression modeling approaches were used to develop parsimonious models relating the most highly predictive of the driver assessment metrics to the safety-related outcomes observed in the naturalistic driving data. This study provides important confirmation using naturalistic driving methods of the relationship between contrast sensitivity and crash-related events. The results of this study provide crucial information on the continuing journey to identify metrics and protocols that could be applied to determine seniors' fitness to drive. Published by Elsevier Ltd.

How to retrieve additional information from the multiplicity distributions

NASA Astrophysics Data System (ADS)

Wilk, Grzegorz; Włodarczyk, Zbigniew

2017-01-01

Multiplicity distributions (MDs) P(N) measured in multiparticle production processes are most frequently described by the negative binomial distribution (NBD). However, with increasing collision energy some systematic discrepancies have become more and more apparent. They are usually attributed to the possible multi-source structure of the production process and described using a multi-NBD form of the MD. We investigate the possibility of keeping a single NBD but with its parameters depending on the multiplicity N. This is done by modifying the widely known clan model of particle production leading to the NBD form of P(N). This is then confronted with the approach based on the so-called cascade-stochastic formalism which is based on different types of recurrence relations defining P(N). We demonstrate that a combination of both approaches allows the retrieval of additional valuable information from the MDs, namely the oscillatory behavior of the counting statistics apparently visible in the high energy data.

Host nutrition alters the variance in parasite transmission potential

PubMed Central

Vale, Pedro F.; Choisy, Marc; Little, Tom J.

2013-01-01

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts. PMID:23407498

Host nutrition alters the variance in parasite transmission potential.

PubMed

Vale, Pedro F; Choisy, Marc; Little, Tom J

2013-04-23

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

Potential Economic Benefits of Paid Sick Leave in Reducing Absenteeism Related to the Spread of Influenza-Like Illness.

PubMed

Asfaw, Abay; Rosa, Roger; Pana-Cryan, Regina

2017-09-01

Most U.S. employers are not required to provide paid sick leave (PSL), and there is limited information on the economic return of providing PSL. We estimated potential benefits to employers of PSL in reducing absenteeism related to the spread of influenza-like illness (ILI). We used nationally representative data and a negative binomial random effects model to estimate the impact of PSL in reducing overall absence due to illness or injury. We used published data to compute the share of ILI from the total days of absence, ILI transmission rates at workplaces, wages, and other parameters. Providing PSL could have saved employers $0.63 to $1.88 billion in reduced ILI-related absenteeism costs per year during 2007 to 2014 in 2016 dollars. These findings might help employers consider PSL as an investment rather than as a cost without any return.

Perceived health status and daily activity participation of older Malaysians.

PubMed

Ng, Sor Tho; Tengku-Aizan, Hamid; Tey, Nai Peng

2011-07-01

This article investigates the influence of perceived health status on the daily activity participation of older Malaysians. Data from the Survey on Perceptions of Needs and Problems of the Elderly, which was conducted in 1999, were used. The negative binomial regression results show that older persons with good perceived health status reported more varieties of daily activity participation, especially among the uneducated and those with below-average self-esteem. The multinomial logistic regression model suggests that older persons with good perceived health status tended to engage daily in paid work only or with leisure activities, whereas those perceived to have poor health were more likely to engage in leisure activities only or leisure and family role activities. Promotion of a healthy lifestyle at a younger age encourages every person to monitor and take responsibility for their own health, which is a necessary strategy to ensure active participation at an older age, and thus improve their well-being.

Adult Children’s Education and Parents’ Functional Limitations in Mexico

PubMed Central

Yahirun, Jenjira J.; Sheehan, Connor M.; Hayward, Mark D.

2016-01-01

This article asks how adult children’s education influences older parents’ physical health in Mexico, a context where older adults often lack access to institutional resources and rely on kin, primarily children, as a main source of support. Using logistic and negative binomial regression models and data from the first wave of the Mexican Health and Aging Study (N = 9,661), we find that parents whose children all completed high school are less likely to report any functional limitations as well as fewer limitations compared to parents with no children who completed high school. This association remains significant even after accounting for parent and offspring-level characteristics, including parents’ income that accounts for children’s financial transfers to parents. Future research should aim to understand the mechanisms that explain the association between adult children’s education and changes to parents’ health over time. PMID:26966254

Bio-Ecology of the Louse, Upupicola upupae, Infesting the Common Hoopoe, Upupa epops

PubMed Central

Agarwal, G. P; Ahmad, Aftab; Rashmi, Archna; Arya, Gaurav; Bansal, Nayanci; Saxena, A.K.

2011-01-01

The population characteristics of the louse, Upupicola upupae (Shrank) (Mallophaga: Philopteridae: Ishnocera), infesting the Common Hoopae, Upupa epops L. (Aves: Upupiformes), were recorded during 2007–08 in District Rampur, Uttar Pradesh India. The pattern of frequency distribution of the louse conformed to the negative binomial model. The lice and its nits were reared in vitro at 35 ± 1° C, 75–82 % RH, on a feather diet. The data obtained was used to construct the life table and to determine the intrinsic rate of natural increase (0.035 female/day), the net reproductive rate was 3.67 female eggs/female, the generation time was 37 days, and the doubling time of the population was 19 days. The chaetotaxy of the three nymphal instars has also been noted to record their diagnostic characteristics. Information on egg morphology and antennal sensilla is also presented. PMID:21861650

Assaults on Days of Campaign Rallies During the 2016 US Presidential Election.

PubMed

Morrison, Christopher N; Ukert, Benjamin; Palumbo, Aimee; Dong, Beidi; Jacoby, Sara F; Wiebe, Douglas J

2018-07-01

This study investigates whether assault frequency increased on days and in cities where candidates Donald Trump and Hillary Clinton held campaign rallies prior to the 2016 US Presidential election. We calculated city-level counts of police-reported assaults for 31 rallies for Donald Trump and 38 rallies for Hillary Clinton. Negative binomial models estimated the assault incidence on rally days (day 0) relative to that on eight control days for the same city (days -28, -21, -14, -7, +7, +14, +21, and +28). Cities experienced an increase in assaults (incidence rate ratio [IRR] = 1.12, 95% CI: 1.03-1.22) on the days of Donald Trump's rallies, and no change in assaults on the days of Hillary Clinton's rallies (IRR = 1.00; 95% CI: 0.94-1.06). Assaults increased on days when cities hosted Donald Trump's rallies during the 2016 Presidential election campaign.

Does the Organized Sexual Murderer Better Delay and Avoid Detection?

PubMed

Beauregard, Eric; Martineau, Melissa

2016-01-01

According to the organized-disorganized model, organized sexual murderers adopt specific behaviors during the commission of their crimes that contribute to avoiding police detection. The current study examines the effect of sexual murderers' organized behaviors on their ability to both delay and/or avoid police detection. Using a combination of negative binomial and logistic regression analyses on a sample of 350 sexual murder cases, findings showed that although both measures of delaying and avoiding detection are positively correlated, different behavioral patterns were observed. For instance, offenders who moved the victim's body were more likely to avoid detection but the victim's body was likely to be recovered faster. Moreover, victim characteristics have an impact on both measures; however, this effect disappears for the measure of delaying detection once the organized behaviors are introduced. Implications of the findings are discussed. © The Author(s) 2014.

On Statistical Modeling of Sequencing Noise in High Depth Data to Assess Tumor Evolution

NASA Astrophysics Data System (ADS)

Rabadan, Raul; Bhanot, Gyan; Marsilio, Sonia; Chiorazzi, Nicholas; Pasqualucci, Laura; Khiabanian, Hossein

2017-12-01

One cause of cancer mortality is tumor evolution to therapy-resistant disease. First line therapy often targets the dominant clone, and drug resistance can emerge from preexisting clones that gain fitness through therapy-induced natural selection. Such mutations may be identified using targeted sequencing assays by analysis of noise in high-depth data. Here, we develop a comprehensive, unbiased model for sequencing error background. We find that noise in sufficiently deep DNA sequencing data can be approximated by aggregating negative binomial distributions. Mutations with frequencies above noise may have prognostic value. We evaluate our model with simulated exponentially expanded populations as well as data from cell line and patient sample dilution experiments, demonstrating its utility in prognosticating tumor progression. Our results may have the potential to identify significant mutations that can cause recurrence. These results are relevant in the pretreatment clinical setting to determine appropriate therapy and prepare for potential recurrence pretreatment.

Binomial tree method for pricing a regime-switching volatility stock loans

NASA Astrophysics Data System (ADS)

Putri, Endah R. M.; Zamani, Muhammad S.; Utomo, Daryono B.

2018-03-01

Binomial model with regime switching may represents the price of stock loan which follows the stochastic process. Stock loan is one of alternative that appeal investors to get the liquidity without selling the stock. The stock loan mechanism resembles that of American call option when someone can exercise any time during the contract period. From the resembles both of mechanism, determination price of stock loan can be interpreted from the model of American call option. The simulation result shows the behavior of the price of stock loan under a regime-switching with respect to various interest rate and maturity.

Umbral Calculus and Holonomic Modules in Positive Characteristic

NASA Astrophysics Data System (ADS)

Kochubei, Anatoly N.

2006-03-01

In the framework of analysis over local fields of positive characteristic, we develop algebraic tools for introducing and investigating various polynomial systems. In this survey paper we describe a function field version of umbral calculus developed on the basis of a relation of binomial type satisfied by the Carlitz polynomials. We consider modules over the Weyl-Carlitz ring, a function field counterpart of the Weyl algebra. It is shown that some basic objects of function field arithmetic, like the Carlitz module, Thakur's hypergeometric polynomials, and analogs of binomial coefficients arising in the positive characteristic version of umbral calculus, generate holonomic modules.

Use of Internet viral marketing to promote smoke-free lifestyles among Chinese adolescents.

PubMed

Ip, Patrick; Lam, Tai-Hing; Chan, Sophia Siu-Chee; Ho, Frederick Ka-Wing; Lo, Lewis A; Chiu, Ivy Wing-Sze; Wong, Wilfred Hing-Sang; Chow, Chun-Bong

2014-01-01

Youth smoking is a global public health concern. Health educators are increasingly using Internet-based technologies, but the effectiveness of Internet viral marketing in promoting health remains uncertain. This prospective pilot study assessed the efficacy of an online game-based viral marketing campaign in promoting a smoke-free attitude among Chinese adolescents. One hundred and twenty-one Hong Kong Chinese adolescents aged 10 to 24 were invited to participate in an online multiple-choice quiz game competition designed to deliver tobacco-related health information. Participants were encouraged to refer others to join. A zero-inflated negative binomial model was used to explore the factors contributing to the referral process. Latent transition analysis utilising a pre- and post-game survey was used to detect attitudinal changes toward smoking. The number of participants increased almost eightfold from 121 to 928 (34.6% current or ex-smokers) during the 22-day campaign. Participants exhibited significant attitudinal change, with 73% holding negative attitudes toward smoking after the campaign compared to 57% before it. The transition probabilities from positive to negative and neutral to negative attitudes were 0.52 and 0.48, respectively. It was also found that attempting every 20 quiz questions was associated with lower perceived smoking decision in future (OR = 0.95, p-value <0.01). Our online game-based viral marketing programme was effective in reaching a large number of smoking and non-smoking participants and changing their attitudes toward smoking. It constitutes a promising practical and cost-effective model for engaging young smokers and promulgating smoking-related health information among Chinese adolescents.

Inpatient mortality rates during an era of increased access to HIV testing and ART: A prospective observational study in Lilongwe, Malawi.

PubMed

Matoga, Mitch M; Rosenberg, Nora E; Stanley, Christopher C; LaCourse, Sylvia; Munthali, Charles K; Nsona, Dominic P; Haac, Bryce; Hoffman, Irving; Hosseinipour, Mina C

2018-01-01

In the era of increased access to HIV testing and antiretroviral treatment (ART), the impact of HIV and ART status on inpatient mortality in Malawi is unknown. We prospectively followed adult inpatients at Kamuzu Central Hospital medical wards in Lilongwe, Malawi, between 2011 and 2012, to evaluate causes of mortality, and the impact of HIV and ART status on mortality. We divided the study population into five categories: HIV-negative, new HIV-positive, ART-naïve patients, new ART-initiators, and ART-experienced. We used multivariate binomial regression models to compare risk of death between categories. Among 2911 admitted patients the mean age was 38.5 years, and 50% were women. Eighty-one percent (81%) of patients had a known HIV status at the time of discharge or death. Mortality was 19.4% and varied between 13.9% (HIV-negative patients) and 32.9% (HIV-positive patients on ART ≤1 year). In multivariable analyses adjusted for age, sex and leading causes of mortality, being new HIV-positive (RR = 1.64 95% CI: 1.16-2.32), ART-naive (RR = 2.28 95% CI: 1.66-2.32) or being a new ART-initiator (RR = 2.41 95% CI: 1.85-3.14) were associated with elevated risk of mortality compared to HIV-negative patients. ART-experienced patients had comparable mortality (RR = 1.33 95% CI: 0.94-1.88) to HIV-negative patients. HIV related mortality remains high among medical inpatients, especially among HIV-positive patients who recently initiated ART or have not started ART yet.

Partitioning Detectability Components in Populations Subject to Within-Season Temporary Emigration Using Binomial Mixture Models

PubMed Central

O’Donnell, Katherine M.; Thompson, Frank R.; Semlitsch, Raymond D.

2015-01-01

Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model’s potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3–5 surveys each spring and fall 2010–2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability. PMID:25775182

Operating characteristics of full count and binomial sampling plans for green peach aphid (Hemiptera: Aphididae) in potato.

PubMed

Kabaluk, J Todd; Binns, Michael R; Vernon, Robert S

2006-06-01

Counts of green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), in potato, Solanum tuberosum L., fields were used to evaluate the performance of the sampling plan from a pest management company. The counts were further used to develop a binomial sampling method, and both full count and binomial plans were evaluated using operating characteristic curves. Taylor's power law provided a good fit of the data (r2 = 0.95), with the relationship between the variance (s2) and mean (m) as ln(s2) = 1.81(+/- 0.02) + 1.55(+/- 0.01) ln(m). A binomial sampling method was developed using the empirical model ln(m) = c + dln(-ln(1 - P(T))), to which the data fit well for tally numbers (T) of 0, 1, 3, 5, 7, and 10. Although T = 3 was considered the most reasonable given its operating characteristics and presumed ease of classification above or below critical densities (i.e., action thresholds) of one and 10 M. persicae per leaf, the full count method is shown to be superior. The mean number of sample sites per field visit by the pest management company was 42 +/- 19, with more than one-half (54%) of the field visits involving sampling 31-50 sample sites, which was acceptable in the context of operating characteristic curves for a critical density of 10 M. persicae per leaf. Based on operating characteristics, actual sample sizes used by the pest management company can be reduced by at least 50%, on average, for a critical density of 10 M. persicae per leaf. For a critical density of one M. persicae per leaf used to avert the spread of potato leaf roll virus, sample sizes from 50 to 100 were considered more suitable.

Bycatch, bait, anglers, and roads: quantifying vector activity and propagule introduction risk across lake ecosystems.

PubMed

Drake, D Andrew R; Mandrak, Nicholas E

2014-06-01

Long implicated in the invasion process, live-bait anglers are highly mobile species vectors with frequent overland transport of fishes. To test hypotheses about the role of anglers in propagule transport, we developed a social-ecological model quantifying the opportunity for species transport beyond the invaded range resulting from bycatch during commercial bait operations, incidental transport, and release to lake ecosystems by anglers. We combined a gravity model with a stochastic, agent-based simulation, representing a 1-yr iteration of live-bait angling and the dynamics of propagule transport at fine spatiotemporal scales (i.e., probability of introducing n propagules per lake per year). A baseline scenario involving round goby (Neogobius melanostomus) indicated that most angling trips were benign; irrespective of lake visitation, anglers failed to purchase and transport propagules (benign trips, median probability P = 0.99912). However, given the large number of probability trials (4.2 million live-bait angling events per year), even the rarest sequence of events (uptake, movement, and deposition of propagules) is anticipated to occur. Risky trips (modal P = 0.00088 trips per year; approximately 1 in 1136) were sufficient to introduce a substantial number of propagules (modal values, Poisson model = 3715 propagules among 1288 lakes per year; zero-inflated negative binomial model = 6722 propagules among 1292 lakes per year). Two patterns of lake-specific introduction risk emerged. Large lakes supporting substantial angling activity experienced propagule pressure likely to surpass demographic barriers to establishment (top 2.5% of lakes with modal outcomes of five to 76 propagules per year; 303 high-risk lakes with three or more propagules, per year). Small or remote lakes were less likely to receive propagules; however, most risk distributions were leptokurtic with a long right tail, indicating the rare occurrence of high propagule loads to most waterbodies. Infestation simulations indicated that the number of high-risk waterbodies could be as great as 1318 (zero-inflated negative binomial), whereas a 90% reduction in bycatch from baseline would reduce the modal number of high risk lakes to zero. Results indicate that the combination of invasive bycatch and live-bait anglers warrants management concern as a species vector, but that risk is confined to a subset of individuals and recipient sites that may be effectively managed with targeted strategies.

Earthquake number forecasts testing

NASA Astrophysics Data System (ADS)

Kagan, Yan Y.

2017-10-01

We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness and kurtosis both tend to zero for large earthquake rates: for the Gaussian law, these values are identically zero. A calculation of the NBD skewness and kurtosis levels based on the values of the first two statistical moments of the distribution, shows rapid increase of these upper moments levels. However, the observed catalogue values of skewness and kurtosis are rising even faster. This means that for small time intervals, the earthquake number distribution is even more heavy-tailed than the NBD predicts. Therefore for small time intervals, we propose using empirical number distributions appropriately smoothed for testing forecasted earthquake numbers.

Impact of a passive social marketing intervention in community pharmacies on oral contraceptive and condom sales: a quasi-experimental study.

PubMed

Farris, Karen B; Aquilino, Mary L; Batra, Peter; Marshall, Vince; Losch, Mary E

2015-02-13

Almost 50% of pregnancies in the United States are unwanted or mistimed. Notably, just over one-half of unintended pregnancies occurred when birth control was being used, suggesting inappropriate or poor use or contraceptive failure. About two-thirds of all women who are of reproductive age use contraceptives, and oral hormonal contraceptives remain the most common contraceptive method. Often, contraceptive products are obtained in community pharmacies. The purpose of this study was to determine whether a pharmacy-based intervention would impact sales of contraceptive products in pharmacies. This study was conducted in Iowa and used a quasi-experimental design including 55 community pharmacies (independent and grocery) in 12 counties as the intervention and 32 grocery pharmacies in 10 counties as a comparison group. The passive intervention was focused towards 18-30 year old women who visited community pharmacies and prompted those of childbearing age to "plan your pregnancy" and "consider using birth control". The intervention was delivered via educational tri-fold brochures, posters and 'shelf talkers.' Data sources for evaluation were contraceptive sales from intervention and comparison pharmacies, and a mixed negative binomial regression was used with study group*time interactions to examine the impact of the intervention on oral contraceptive and condom sales. Data from 2009 were considered baseline sales. From 2009 to 2011, condom sales decreased over time and oral contraceptives sales showed no change. Overall, the units sold were significantly higher in grocery pharmacies than in independent pharmacies for both contraceptive types. In the negative binomial regression for condoms, there was an overall significant interaction between the study group and time variables (p = 0.003), indicating an effect of the intervention, and there was a significant slowing in the drop of sales at time 3 in comparison with time 1 (p < 0.001). There was a statistically significant association between pharmacy type and study group, where the independent intervention pharmacies had a higher proportion of stores with increases in condom sales compared to grocery pharmacies in the intervention or comparison group. A passive community pharmacy-based public health intervention appeared to reduce the decrease in condom sales from baseline, particularly in independent pharmacies, but it did not impact oral contraceptive sales.

Relationship Between Air Pollution, Weather, Traffic, and Traffic-Related Mortality

PubMed Central

Dastoorpoor, Maryam; Idani, Esmaeil; Khanjani, Narges; Goudarzi, Gholamreza; Bahrampour, Abbas

2016-01-01

Background Air pollution and weather are just two of many environmental factors contributing to traffic accidents (RTA). Objectives This study assessed the effects of these factors on traffic accidents and related mortalities in Ahvaz, Iran. Methods In this ecological study, data about RTA, traffic-related mortalities, air pollution (including NO, CO, NO2, NOx PM10, SO2, and O3 rates) and climate data from March 2008 until March 2015 was acquired from the Khuzestan State Police Force, the Environmental Protection Agency and the State Meteorological Department. Statistical analysis was performed with STATA 12 through both crude and adjusted negative binomial regression methods. Results There was a significant positive correlation between increase in the monthly average temperature, the number of rainy days, and the number of frost days with the number of RTA (P < 0.05). Increased monthly average relative humidity, evaporation, and number of sunny days were negatively correlated with the frequency of RTA (P < 0.05). We also observed an inverse significant correlation between monthly average relative humidity, evaporation, and wind speed with traffic accident mortality (P < 0.05). Some air pollutants were negatively associated with the incidence rate of RTA. Conclusions It appears that some weather variables were significantly associated with increased RTA. However, increased levels of air pollutants were not associated with increased rates of RTA and/or related mortalities. Additional studies are recommended to explore this topic in more detail. PMID:28180125

The effect of objectively measured crime on walking in minority adults.

PubMed

McDonald, Noreen C

2008-01-01

Evaluate the relationship between neighborhood crime and the amount of daily walking by minority adults. This was a cross-sectional study of minority adult walking behavior and crime. Setting. Oakland, California was chosen as the study area because of the substantial spatial variation in levels of criminal activity combined with detailed information on walking trips. The study was restricted to minority adults who responded to the 2000 Bay Area Travel Survey and lived in Oakland, California (n = 359). Data on leisure and utilitarian walking were collected through the 2000 Bay Area Travel Survey and combined with crime data from the Oakland Police Department. A negative binomial model was used to test if violent, property, or quality of life crimes had significant associations with daily minutes walked, controlling for individual and neighborhood covariates. The model showed a significant negative association between violent crime and minutes walked per day (b = -.07; p = .016). Neither property nor quality of life crimes were correlated with amount of walking. Reductions in violent crime may increase opportunities for minority residents in urban areas to participate in physical activity such as walking, thereby providing another reason to pursue anticrime measures. Urban designers' efforts to increase physical activity by improving neighborhood walkability may consider violent crime prevention in their designs.

Ascaris and hookworm transmission in preschool children from rural Panama: role of yard environment, soil eggs/larvae and hygiene and play behaviours.

PubMed

Krause, Rachel J; Koski, Kristine G; Pons, Emérita; Sandoval, Nidia; Sinisterra, Odalis; Scott, Marilyn E

2015-10-01

This study explored whether the yard environment and child hygiene and play behaviours were associated with presence and intensity of Ascaris and hookworm in preschool children and with eggs and larvae in soil. Data were collected using questionnaires, a visual survey of the yard, soil samples and fecal samples collected at baseline and following re-infection. The presence of eggs/larvae in soil was associated negatively with water storage (eggs) but positively with dogs (eggs) and distance from home to latrine (larvae). Baseline and re-infection prevalences were: hookworm (28.0%, 3.4%); Ascaris (16.9%, 9.5%); Trichuris (0.9%, 0.7%). Zero-inflated negative binomial regression models revealed a higher baseline hookworm infection if yards had eggs or larvae, more vegetation or garbage, and if the child played with soil. Baseline Ascaris was associated with dirt floor, dogs, exposed soil in yard, open defecation and with less time playing outdoors, whereas Ascaris re-infection was associated with water storage, vegetation cover and garbage near the home and not playing with animals. Our results show complex interactions between infection, the yard environment and child behaviours, and indicate that transmission would be reduced if latrines were closer to the home, and if open defecation and water spillage were reduced.

Law Enforcement Officers' Involvement Level in Hurricane Katrina and Alcohol Use.

PubMed

Heavey, Sarah Cercone; Homish, Gregory G; Andrew, Michael E; McCanlies, Erin; Mnatsakanova, Anna; Violanti, John M; Burchfiel, Cecil M

2015-03-01

The purpose of this work is to examine the relationship between alcohol use and level of involvement during Hurricane Katrina among law enforcement officers, and to investigate whether marital status or previous military training offer resilience against negative outcomes. Officers in the immediate New Orleans geographic area completed surveys that assessed their involvement in Hurricane Katrina and alcohol use (Alcohol Use and Disorders Identification Test (AUDIT) score). Negative binomial regression models were used to analyze level of hazardous alcohol use; interactions were tested to examine protective influences of marriage and prior military training (controlling for age and gender). There was a significant association between heavy involvement in Hurricane Katrina and having a greater AUDIT score (exp(β)[EB]=1.81; 95% CI: 1.03, 3.17; p<0.05), indicating higher levels of hazardous alcohol use. Contrary to original hypotheses, marital status and military training were not protective against alcohol use (p>0.05). These results illustrate an association between law enforcement officers' heavy involvement during Hurricane Katrina and greater levels of hazardous alcohol use when compared to officers with low or moderate involvement. This has important treatment implications for those with high involvement in disasters as they may require targeted interventions to overcome the stress of such experiences.

Work Hours and Absenteeism Among Police Officers

PubMed Central

Fekedulegn, Desta; Burchfiel, Cecil M.; Hartley, Tara A.; Baughman, Penelope; Charles, Luenda E.; Andrew, Michael E.; Violanti, John M.

2015-01-01

In this study, the cross-sectional association of paid work hours with episodes of work absence was examined in a cohort of police officers. Study subjects were participants from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study examined between 2004 and 2009. Among 395 study participants with complete data, day-by-day work history records during the one-year period prior to date of examination were used to determine episodes of one-day and three day work absence. The Negative binomial regression analysis was used to examine rate ratios (RR) of work absence. Analyses were also by gender. A one-hour increase in total work hours was associated with 5% reduction in rate of stratified one-day work absence (RR = 0.95, 95% CI: 0.92 – 0.98) and with 8% reduction in rate of three-day work absence (RR = 0.92, 95% CI: 0.89 – 0.95). The association of total work hours with episodes of one-day work absence was significant only in men while the association with episodes of three-day work absence was evident in men and women. In conclusion, in this cohort of police officers, work hours were negatively associated with both durations of work absence (one-day, ≥ 3 consecutive days). PMID:24707589

A Statistical Tool for Risk Assessment as Function of Number of Retrieved Lymph Nodes from Rectal Cancer Patients.

PubMed

Wu, Zhenyu; Qin, Guoyou; Zhao, Naiqing; Jia, Huixun; Zheng, Xueying

2018-05-16

Although a minimum of 12 lymph nodes (LNs) has been recommended for colorectal cancer, there remains considerable debates for rectal cancer patients. Inadequacy of examined LNs would lead to under-staging, and inappropriate treatment as a consequence. We describe statistical tool that allows an estimate the probability of false-negative nodes. A total of 26,778 adenocarcinoma rectum cancer patients with tumour stage (T stage) 1-3, diagnosed between 2004 and 2013, who did not receive neoadjuvant therapies and had at least one histologically assessed LN, were extracted from the Surveillance, Epidemiology and End Results (SEER) database. A statistical tool using beta-binomial distribution was developed to estimate the probability of an occult nodal disease is truly node-negative as a function of total number of LNs examined and T stage. The probability of falsely identifying a patient as node-negative decreased with an increasing number of nodes examined for each stage. It was estimated to be 72%, 66% and 52% for T1, T2 and T3 patients respectively with a single node examined. To confirm an occult nodal disease with 90% confidence, 5, 9, and 29 nodes need to be examined for patients from stages T1, T2, and T3, respectively. The false-negative rate of the examined lymph nodes in rectal cancer was verified to be dependent preoperatively on the clinical tumour stage. A more accurate nodal staging score was developed to recommend a threshold on the minimum number of examined nodes regarding to the favored level of confidence. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Use of Internet Viral Marketing to Promote Smoke-Free Lifestyles among Chinese Adolescents

PubMed Central

Ip, Patrick; Lam, Tai-Hing; Chan, Sophia Siu-Chee; Ho, Frederick Ka-Wing; Lo, Lewis A.; Chiu, Ivy Wing-Sze; Wong, Wilfred Hing-Sang; Chow, Chun-Bong

2014-01-01

Purpose Youth smoking is a global public health concern. Health educators are increasingly using Internet-based technologies, but the effectiveness of Internet viral marketing in promoting health remains uncertain. This prospective pilot study assessed the efficacy of an online game-based viral marketing campaign in promoting a smoke-free attitude among Chinese adolescents. Methods One hundred and twenty-one Hong Kong Chinese adolescents aged 10 to 24 were invited to participate in an online multiple-choice quiz game competition designed to deliver tobacco-related health information. Participants were encouraged to refer others to join. A zero-inflated negative binomial model was used to explore the factors contributing to the referral process. Latent transition analysis utilising a pre- and post-game survey was used to detect attitudinal changes toward smoking. Results The number of participants increased almost eightfold from 121 to 928 (34.6% current or ex-smokers) during the 22-day campaign. Participants exhibited significant attitudinal change, with 73% holding negative attitudes toward smoking after the campaign compared to 57% before it. The transition probabilities from positive to negative and neutral to negative attitudes were 0.52 and 0.48, respectively. It was also found that attempting every 20 quiz questions was associated with lower perceived smoking decision in future (OR  = 0.95, p-value <0.01). Conclusions Our online game-based viral marketing programme was effective in reaching a large number of smoking and non-smoking participants and changing their attitudes toward smoking. It constitutes a promising practical and cost-effective model for engaging young smokers and promulgating smoking-related health information among Chinese adolescents. PMID:24911010

Finite mixture modeling for vehicle crash data with application to hotspot identification.

PubMed

Park, Byung-Jung; Lord, Dominique; Lee, Chungwon

2014-10-01

The application of finite mixture regression models has recently gained an interest from highway safety researchers because of its considerable potential for addressing unobserved heterogeneity. Finite mixture models assume that the observations of a sample arise from two or more unobserved components with unknown proportions. Both fixed and varying weight parameter models have been shown to be useful for explaining the heterogeneity and the nature of the dispersion in crash data. Given the superior performance of the finite mixture model, this study, using observed and simulated data, investigated the relative performance of the finite mixture model and the traditional negative binomial (NB) model in terms of hotspot identification. For the observed data, rural multilane segment crash data for divided highways in California and Texas were used. The results showed that the difference measured by the percentage deviation in ranking orders was relatively small for this dataset. Nevertheless, the ranking results from the finite mixture model were considered more reliable than the NB model because of the better model specification. This finding was also supported by the simulation study which produced a high number of false positives and negatives when a mis-specified model was used for hotspot identification. Regarding an optimal threshold value for identifying hotspots, another simulation analysis indicated that there is a discrepancy between false discovery (increasing) and false negative rates (decreasing). Since the costs associated with false positives and false negatives are different, it is suggested that the selected optimal threshold value should be decided by considering the trade-offs between these two costs so that unnecessary expenses are minimized. Copyright © 2014 Elsevier Ltd. All rights reserved.

The direct and indirect effects of corruption on motor vehicle crash deaths.

PubMed

Hua, Law Teik; Noland, Robert B; Evans, Andrew W

2010-11-01

Recent empirical research has found that there is an inverted U-shaped or Kuznets relationship between income and motor vehicle crash (MVC) deaths, such that MVC deaths increase as national income increases and decrease after reaching a critical level. Corruption has been identified as one of the underlying factors that could affect this relationship, primarily by undermining institutional development and effective enforcement schemes. The total effect of corruption can be decomposed into two components, a direct and an indirect effect. The direct effect measures the immediate impact of corruption on MVC deaths by undermining effective enforcement and regulations, while the indirect effect captures the impact of corruption on hindering increases in per capita income and the consequent impact of reduced income on MVC deaths. By influencing economic growth, corruption can lead to an increase or decrease in MVC deaths depending on the income level. Using data from 60 countries between 1982 and 2003, these effects are estimated using linear panel and fixed effects negative binomial models. The estimation results suggest that corruption has different direct effects for less developed and highly developed countries. It has a negative (decreasing) effect on MVC deaths for less developed countries and a positive (increasing) effect on MVC deaths for highly developed countries. For highly developed countries, the total effect is positive at lower per capita income levels, but decreases with per capita income and becomes negative at per capita income levels of about US$ 38,248. For less developed countries, the total effect is negative within the sample range and decreases with increased per capita income. In summary, the results of this study suggest that reduction of corruption is likely a necessary condition to effectively tackle road safety problems. 2010 Elsevier Ltd. All rights reserved.

Generalization of multifractal theory within quantum calculus

NASA Astrophysics Data System (ADS)

Olemskoi, A.; Shuda, I.; Borisyuk, V.

2010-03-01

On the basis of the deformed series in quantum calculus, we generalize the partition function and the mass exponent of a multifractal, as well as the average of a random variable distributed over a self-similar set. For the partition function, such expansion is shown to be determined by binomial-type combinations of the Tsallis entropies related to manifold deformations, while the mass exponent expansion generalizes the known relation τq=Dq(q-1). We find the equation for the set of averages related to ordinary, escort, and generalized probabilities in terms of the deformed expansion as well. Multifractals related to the Cantor binomial set, exchange currency series, and porous-surface condensates are considered as examples.

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

P-Hacking in Orthopaedic Literature: A Twist to the Tail.

PubMed

Bin Abd Razak, Hamid Rahmatullah; Ang, Jin-Guang Ernest; Attal, Hersh; Howe, Tet-Sen; Allen, John Carson

2016-10-19

"P-hacking" occurs when researchers preferentially select data or statistical analyses until nonsignificant results become significant. We wanted to evaluate if the phenomenon of p-hacking was evident in orthopaedic literature. We text-mined through all articles published in three top orthopaedic journals in 2015. For anonymity, we cipher-coded the three journals. We included all studies that reported a single p value to answer their main hypothesis. These p values were then charted and frequency graphs were generated to illustrate any evidence of p-hacking. Binomial tests were employed to look for evidence of evidential value and significance of p-hacking. Frequency plots for all three journals revealed evidence of p-hacking. Binomial tests for all three journals were significant for evidence of evidential value (p < 0.0001 for all). However, the binomial test for p-hacking was significant only for one journal (p = 0.0092). P-hacking is an evolving phenomenon that threatens to jeopardize the evidence-based practice of medicine. Although our results show that there is good evidential value for orthopaedic literature published in our top journals, there is some evidence of p-hacking of which authors and readers should be wary. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

Statistical tests to compare motif count exceptionalities

PubMed Central

Robin, Stéphane; Schbath, Sophie; Vandewalle, Vincent

2007-01-01

Background Finding over- or under-represented motifs in biological sequences is now a common task in genomics. Thanks to p-value calculation for motif counts, exceptional motifs are identified and represent candidate functional motifs. The present work addresses the related question of comparing the exceptionality of one motif in two different sequences. Just comparing the motif count p-values in each sequence is indeed not sufficient to decide if this motif is significantly more exceptional in one sequence compared to the other one. A statistical test is required. Results We develop and analyze two statistical tests, an exact binomial one and an asymptotic likelihood ratio test, to decide whether the exceptionality of a given motif is equivalent or significantly different in two sequences of interest. For that purpose, motif occurrences are modeled by Poisson processes, with a special care for overlapping motifs. Both tests can take the sequence compositions into account. As an illustration, we compare the octamer exceptionalities in the Escherichia coli K-12 backbone versus variable strain-specific loops. Conclusion The exact binomial test is particularly adapted for small counts. For large counts, we advise to use the likelihood ratio test which is asymptotic but strongly correlated with the exact binomial test and very simple to use. PMID:17346349

Interrelationships Between Receiver/Relative Operating Characteristics Display, Binomial, Logit, and Bayes' Rule Probability of Detection Methodologies

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2014-01-01

Unknown risks are introduced into failure critical systems when probability of detection (POD) capabilities are accepted without a complete understanding of the statistical method applied and the interpretation of the statistical results. The presence of this risk in the nondestructive evaluation (NDE) community is revealed in common statements about POD. These statements are often interpreted in a variety of ways and therefore, the very existence of the statements identifies the need for a more comprehensive understanding of POD methodologies. Statistical methodologies have data requirements to be met, procedures to be followed, and requirements for validation or demonstration of adequacy of the POD estimates. Risks are further enhanced due to the wide range of statistical methodologies used for determining the POD capability. Receiver/Relative Operating Characteristics (ROC) Display, simple binomial, logistic regression, and Bayes' rule POD methodologies are widely used in determining POD capability. This work focuses on Hit-Miss data to reveal the framework of the interrelationships between Receiver/Relative Operating Characteristics Display, simple binomial, logistic regression, and Bayes' Rule methodologies as they are applied to POD. Knowledge of these interrelationships leads to an intuitive and global understanding of the statistical data, procedural and validation requirements for establishing credible POD estimates.

Spatial distribution and sequential sampling plans for Tuta absoluta (Lepidoptera: Gelechiidae) in greenhouse tomato crops.

PubMed

Cocco, Arturo; Serra, Giuseppe; Lentini, Andrea; Deliperi, Salvatore; Delrio, Gavino

2015-09-01

The within- and between-plant distribution of the tomato leafminer, Tuta absoluta (Meyrick), was investigated in order to define action thresholds based on leaf infestation and to propose enumerative and binomial sequential sampling plans for pest management applications in protected crops. The pest spatial distribution was aggregated between plants, and median leaves were the most suitable sample to evaluate the pest density. Action thresholds of 36 and 48%, 43 and 56% and 60 and 73% infested leaves, corresponding to economic thresholds of 1 and 3% damaged fruits, were defined for tomato cultivars with big, medium and small fruits respectively. Green's method was a more suitable enumerative sampling plan as it required a lower sampling effort. Binomial sampling plans needed lower average sample sizes than enumerative plans to make a treatment decision, with probabilities of error of <0.10. The enumerative sampling plan required 87 or 343 leaves to estimate the population density in extensive or intensive ecological studies respectively. Binomial plans would be more practical and efficient for control purposes, needing average sample sizes of 17, 20 and 14 leaves to take a pest management decision in order to avoid fruit damage higher than 1% in cultivars with big, medium and small fruits respectively. © 2014 Society of Chemical Industry.

Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference.

PubMed

Dahabreh, Issa J; Trikalinos, Thomas A; Lau, Joseph; Schmid, Christopher H

2017-03-01

To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests). We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach. We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction. The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and specificity. Bayesian methods fully quantify uncertainty and their ability to incorporate external evidence may be useful for imprecisely estimated parameters. Copyright © 2017 Elsevier Inc. All rights reserved.

The Binomial Model in Fluctuation Analysis of Quantal Neurotransmitter Release

PubMed Central

Quastel, D. M. J.

1997-01-01

The mathematics of the binomial model for quantal neurotransmitter release is considered in general terms, to explore what information might be extractable from statistical aspects of data. For an array of N statistically independent release sites, each with a release probability p, the compound binomial always pertains, with = N

, p′ ≡ 1 - var(m)/ =

(1 + cvp2) and n′ ≡ /p′ = N/(1 + cvp2), where m is the output/stimulus and cvp2 is var(p)/

2. Unless n′ is invariant with ambient conditions or stimulation paradigms, the simple binomial (cvp = 0) is untenable and n′ is neither N nor the number of “active” sites or sites with a quantum available. At each site p = popA, where po is the output probability if a site is “eligible” or “filled” despite previous quantal discharge, and pA (eligibility probability) depends at least on the replenishment rate, po, and interstimulus time. Assuming stochastic replenishment, a simple algorithm allows calculation of the full statistical composition of outputs for any hypothetical combinations of po's and refill rates, for any stimulation paradigm and spontaneous release. A rise in n′ (reduced cvp) tends to occur whenever po varies widely between sites, with a raised stimulation frequency or factors tending to increase po's. Unlike and var(m) at equilibrium, output changes early in trains of stimuli, and covariances, potentially provide information about whether changes in reflect change in or in . Formulae are derived for variance and third moments of postsynaptic responses, which depend on the quantal mix in the signals. A new, easily computed function, the area product, gives noise-unbiased variance of a series of synaptic signals and its peristimulus time distribution, which is modified by the unit channel composition of quantal responses and if the signals reflect mixed responses from synapses with different quantal time course. PMID:9017200

Kinetics of low-temperature transitions and a reaction rate theory from non-equilibrium distributions

PubMed Central

Aquilanti, Vincenzo; Coutinho, Nayara Dantas

2017-01-01

This article surveys the empirical information which originated both by laboratory experiments and by computational simulations, and expands previous understanding of the rates of chemical processes in the low-temperature range, where deviations from linearity of Arrhenius plots were revealed. The phenomenological two-parameter Arrhenius equation requires improvement for applications where interpolation or extrapolations are demanded in various areas of modern science. Based on Tolman's theorem, the dependence of the reciprocal of the apparent activation energy as a function of reciprocal absolute temperature permits the introduction of a deviation parameter d covering uniformly a variety of rate processes, from those where quantum mechanical tunnelling is significant and d < 0, to those where d > 0, corresponding to the Pareto–Tsallis statistical weights: these generalize the Boltzmann–Gibbs weight, which is recovered for d = 0. It is shown here how the weights arise, relaxing the thermodynamic equilibrium limit, either for a binomial distribution if d > 0 or for a negative binomial distribution if d < 0, formally corresponding to Fermion-like or Boson-like statistics, respectively. The current status of the phenomenology is illustrated emphasizing case studies; specifically (i) the super-Arrhenius kinetics, where transport phenomena accelerate processes as the temperature increases; (ii) the sub-Arrhenius kinetics, where quantum mechanical tunnelling propitiates low-temperature reactivity; (iii) the anti-Arrhenius kinetics, where processes with no energetic obstacles are rate-limited by molecular reorientation requirements. Particular attention is given for case (i) to the treatment of diffusion and viscosity, for case (ii) to formulation of a transition rate theory for chemical kinetics including quantum mechanical tunnelling, and for case (iii) to the stereodirectional specificity of the dynamics of reactions strongly hindered by the increase of temperature. This article is part of the themed issue ‘Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces’. PMID:28320904

Kinetics of low-temperature transitions and a reaction rate theory from non-equilibrium distributions.

PubMed

Aquilanti, Vincenzo; Coutinho, Nayara Dantas; Carvalho-Silva, Valter Henrique

2017-04-28

This article surveys the empirical information which originated both by laboratory experiments and by computational simulations, and expands previous understanding of the rates of chemical processes in the low-temperature range, where deviations from linearity of Arrhenius plots were revealed. The phenomenological two-parameter Arrhenius equation requires improvement for applications where interpolation or extrapolations are demanded in various areas of modern science. Based on Tolman's theorem, the dependence of the reciprocal of the apparent activation energy as a function of reciprocal absolute temperature permits the introduction of a deviation parameter d covering uniformly a variety of rate processes, from those where quantum mechanical tunnelling is significant and d  < 0, to those where d  > 0, corresponding to the Pareto-Tsallis statistical weights: these generalize the Boltzmann-Gibbs weight, which is recovered for d  = 0. It is shown here how the weights arise, relaxing the thermodynamic equilibrium limit, either for a binomial distribution if d  > 0 or for a negative binomial distribution if d  < 0, formally corresponding to Fermion-like or Boson-like statistics, respectively. The current status of the phenomenology is illustrated emphasizing case studies; specifically (i) the super -Arrhenius kinetics, where transport phenomena accelerate processes as the temperature increases; (ii) the sub -Arrhenius kinetics, where quantum mechanical tunnelling propitiates low-temperature reactivity; (iii) the anti -Arrhenius kinetics, where processes with no energetic obstacles are rate-limited by molecular reorientation requirements. Particular attention is given for case (i) to the treatment of diffusion and viscosity, for case (ii) to formulation of a transition rate theory for chemical kinetics including quantum mechanical tunnelling, and for case (iii) to the stereodirectional specificity of the dynamics of reactions strongly hindered by the increase of temperature.This article is part of the themed issue 'Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces'. © 2017 The Author(s).

Seasonal changes in spatial patterns of two annual plants in the Chihuahuan Desert, USA

USGS Publications Warehouse

Yin, Z.-Y.; Guo, Q.; Ren, H.; Peng, S.-L.

2005-01-01

Spatial pattern of a biotic population may change over time as its component individuals grow or die out, but whether this is the case for desert annual plants is largely unknown. Here we examined seasonal changes in spatial patterns of two annuals, Eriogonum abertianum and Haplopappus gracilis, in initial (winter) and final (summer) densities. The density was measured as the number of individuals from 384 permanent quadrats (each 0.5 m × 0.5 m) in the Chihuahuan Desert near Portal, Arizona, USA. We used three probability distributions (binomial, Poisson, and negative binomial or NB) that represent three basic spatial patterns (regular, random, and clumped) to fit the observed frequency distributions of densities of the two annuals. Both species showed clear clumped patterns as characterized by the NB and had similar inverse J-shaped frequency distribution curves in two density categories. Also, both species displayed a reduced degree of aggregation from winter to summer after the spring drought (massive die-off), as indicated by the increased k-parameter of the NB and decreased values of another NB parameter p, variance/mean ratio, Lloyd’s Index of Patchiness, and David and Moore’s Index of Clumping. Further, we hypothesized that while the NB (i.e., Poisson-logarithmic) well fits the distribution of individuals per quadrat, its components, the Poisson and logarithmic, may describe the distributions of clumps per quadrat and of individuals per clump, respectively. We thus obtained the means and variances for (1) individuals per quadrat, (2) clumps per quadrat, and (3) individuals per clump. The results showed that the decrease of the density from winter to summer for each plant resulted from the decrease of individuals per clump, rather than from the decrease of clumps per quadrat. The great similarities between the two annuals indicate that our observed temporal changes in spatial patterns may be common among desert annual plants.

The Relationship Between Gun Ownership and Stranger and Nonstranger Firearm Homicide Rates in the United States, 1981–2010

PubMed Central

Negussie, Yamrot; Vanture, Sarah; Pleskunas, Jane; Ross, Craig S.; King, Charles

2014-01-01

Objectives. We examined the relationship between gun ownership and stranger versus nonstranger homicide rates. Methods. Using data from the Supplemental Homicide Reports of the Federal Bureau of Investigation’s Uniform Crime Reports for all 50 states for 1981 to 2010, we modeled stranger and nonstranger homicide rates as a function of state-level gun ownership, measured by a proxy, controlling for potential confounders. We used a negative binomial regression model with fixed effects for year, accounting for clustering of observations among states by using generalized estimating equations. Results. We found no robust, statistically significant correlation between gun ownership and stranger firearm homicide rates. However, we found a positive and significant association between gun ownership and nonstranger firearm homicide rates. The incidence rate ratio for nonstranger firearm homicide rate associated with gun ownership was 1.014 (95% confidence interval = 1.009, 1.019). Conclusions. Our findings challenge the argument that gun ownership deters violent crime, in particular, homicides. PMID:25121817

Twenty years of workers' compensation costs due to falls from height among union carpenters, Washington state.

PubMed

Lipscomb, Hester J; Schoenfisch, Ashley L; Cameron, Wilfrid; Kucera, Kristen L; Adams, Darrin; Silverstein, Barbara A

2014-09-01

Falls from height (FFH) are a longstanding, serious problem in construction. We report workers' compensation (WC) payments associated with FFH among a cohort (n = 24,830; 1989-2008) of carpenters. Mean/median payments, cost rates, and adjusted rate ratios based on hours worked were calculated using negative-binomial regression. Over the 20-year period FFH accounted for $66.6 million in WC payments or $700 per year for each full-time equivalent (2,000 hr of work). FFH were responsible for 5.5% of injuries but 15.1% of costs. Cost declines were observed, but not monotonically. Reductions were more pronounced for indemnity than medical care. Mean costs were 2.3 times greater among carpenters over 50 than those under 30; cost rates were only modestly higher. Significant progress has been made in reducing WC payments associated with FFH in this cohort particularly through 1996; primary gains reflect reduction in frequency of falls. FFH that occur remain costly. © 2014 Wiley Periodicals, Inc.

The relationship between social support and adolescent dating violence: a comparison across genders.

PubMed

Richards, Tara N; Branch, Kathryn A

2012-05-01

Although much research has focused on the function of social support in adult intimate partner violence, little is known about the role of social support in adolescent dating violence. This study is an exploratory analysis of the independent impact of social support from friends and family on the risk of adolescent dating violence perpetration and victimization among a large sample of youth (n = 970). Approximately, 21% of the sample reported experiencing victimization in a dating relationship whereas 23% indicated perpetrating dating violence. Male youth reported significantly more involvement in dating violence as both perpetrators and victims. Negative binomial regression modeling indicated that increased levels of support from friends was associated with significantly less dating violence perpetration and victimization; however, when gendered models were explored, the protective role of social support was only maintained for female youth. Family support was not significantly related to dating violence in any model. Implications for dating violence curriculum and future research are addressed.

Environmental Risk Factors influencing Bicycle Theft: A Spatial Analysis in London, UK

PubMed Central

Helbich, Marco

2016-01-01

Urban authorities are continuously drawing up policies to promote cycling among commuters. However, these initiatives are counterproductive for the targeted objectives because they increase opportunities for bicycle theft. This paper explores Inner London as a case study to address place-specific risk factors for bicycle theft at the street-segment level while controlling for seasonal variation. The presence of certain public amenities (e.g., bicycle stands, railway stations, pawnshops) was evaluated against locations of bicycle theft between 2013 and 2016 and risk effects were estimated using negative binomial regression models. Results showed that a greater level of risk stemmed from land-use facilities than from area-based socioeconomic status. The presence of facilities such as train stations, vacant houses, pawnbrokers and payday lenders increased bicycle theft, but no evidence was found that linked police stations with crime levels. The findings have significant implications for urban crime prevention with respect to non-residential land use. PMID:27643788

The relationship between gun ownership and stranger and nonstranger firearm homicide rates in the United States, 1981-2010.

PubMed

Siegel, Michael; Negussie, Yamrot; Vanture, Sarah; Pleskunas, Jane; Ross, Craig S; King, Charles

2014-10-01

We examined the relationship between gun ownership and stranger versus nonstranger homicide rates. Using data from the Supplemental Homicide Reports of the Federal Bureau of Investigation's Uniform Crime Reports for all 50 states for 1981 to 2010, we modeled stranger and nonstranger homicide rates as a function of state-level gun ownership, measured by a proxy, controlling for potential confounders. We used a negative binomial regression model with fixed effects for year, accounting for clustering of observations among states by using generalized estimating equations. We found no robust, statistically significant correlation between gun ownership and stranger firearm homicide rates. However, we found a positive and significant association between gun ownership and nonstranger firearm homicide rates. The incidence rate ratio for nonstranger firearm homicide rate associated with gun ownership was 1.014 (95% confidence interval=1.009, 1.019). Our findings challenge the argument that gun ownership deters violent crime, in particular, homicides.

Mean Streets and Mental Health: Depression and Post-Traumatic Stress Disorder at Crime Hot Spots.

PubMed

Weisburd, David; Cave, Breanne; Nelson, Matthew; White, Clair; Haviland, Amelia; Ready, Justin; Lawton, Brian; Sikkema, Kathleen

2018-03-07

This study explores the relationship between mental health and place at microgeographic units of analysis. We examine self-reported symptomology for depression and PTSD for 2,724 survey respondents interviewed in three types of randomly selected street segments: violent crime hot spots, cool spots, and cold spots. We find that the mean symptomology score is 61% higher for depression in violent crime hot spots than cold spots, and 85% higher for PTSD. Overall, we estimate that 14.8% of residents of violent crime hot spots meet thresholds for moderate depression or a diagnosis of PTSD. This can be compared to only 6.5% of residents at the cold spots. Using PSM and weighted negative binomial regression approaches we show that observable selection factors are not responsible for the relationships identified. Examining geographic influences, we find an important area effect of violent crime for both mental health measures, and an additional impact of the specific street of residence for PTSD. © Society for Community Research and Action 2018.

Remote sensing of earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1988-01-01

Two monographs and 85 journal and conference papers on remote sensing of earth terrain have been published, sponsored by NASA Contract NAG5-270. A multivariate K-distribution is proposed to model the statistics of fully polarimetric data from earth terrain with polarizations HH, HV, VH, and VV. In this approach, correlated polarizations of radar signals, as characterized by a covariance matrix, are treated as the sum of N n-dimensional random vectors; N obeys the negative binomial distribution with a parameter alpha and mean bar N. Subsequently, and n-dimensional K-distribution, with either zero or non-zero mean, is developed in the limit of infinite bar N or illuminated area. The probability density function (PDF) of the K-distributed vector normalized by its Euclidean norm is independent of the parameter alpha and is the same as that derived from a zero-mean Gaussian-distributed random vector. The above model is well supported by experimental data provided by MIT Lincoln Laboratory and the Jet Propulsion Laboratory in the form of polarimetric measurements.

Measuring demand for flat water recreation using a two-stage/disequilibrium travel cost model with adjustment for overdispersion and self-selection

NASA Astrophysics Data System (ADS)

McKean, John R.; Johnson, Donn; Taylor, R. Garth

2003-04-01

An alternate travel cost model is applied to an on-site sample to estimate the value of flat water recreation on the impounded lower Snake River. Four contiguous reservoirs would be eliminated if the dams are breached to protect endangered Pacific salmon and steelhead trout. The empirical method applies truncated negative binomial regression with adjustment for endogenous stratification. The two-stage decision model assumes that recreationists allocate their time among work and leisure prior to deciding among consumer goods. The allocation of time and money among goods in the second stage is conditional on the predetermined work time and income. The second stage is a disequilibrium labor market which also applies if employers set work hours or if recreationists are not in the labor force. When work time is either predetermined, fixed by contract, or nonexistent, recreationists must consider separate prices and budgets for time and money.

Predicting Binge Drinking in College Students: Rational Beliefs, Stress, or Loneliness?

PubMed

Chen, Yixin; Feeley, Thomas Hugh

2015-01-01

We proposed a conceptual model to predict binge-drinking behavior among college students, based on the theory of planned behavior and the stress-coping hypothesis. A two-wave online survey was conducted with predictors and drinking behavior measured separately over 2 weeks' time. In the Wave 1 survey, 279 students at a public university in the United States answered questions assessing key predictors and individual characteristics. In the Wave 2 survey, 179 participants returned and reported their drinking behavior over 2 weeks' time. After conducting a negative binomial regression, we found that more favorable attitude toward drinking and less perceived control of drinking at Wave 1 were associated with more binge drinking at Wave 2; subjective norm at Wave 1 was not a significant predictor of binge drinking at Wave 2; students with higher stress at Wave 1 engaged in more binge drinking at Wave 2, but those with higher loneliness did not. Implications of findings are discussed. © The Author(s) 2016.

Healthcare use and cost in dementia caregivers: Longitudinal results from the Predictors Caregiver Study

PubMed Central

Zhu, Carolyn W.; Scarmeas, Nikolaos; Ornstein, Katherine; Albert, Marilyn; Brandt, Jason; Blacker, Deborah; Sano, Mary; Stern, Yaakov

2014-01-01

OBJECTIVE: To examine the effects of caregiver and patient characteristics on caregivers’ medical care use and cost. METHODS: 147 caregiver/patient dyads were followed annually for 6 years in 3 academic AD centers in the US. Logistic, negative binomial, and generalized linear mixed models were used to examine overall effects of caregiver/patient characteristics on caregivers’ hospitalizations, doctor visits, outpatient tests and procedures, and prescription and over-the-counter medications. RESULTS: Patients’ comorbid conditions and dependence were associated with increased healthcare use and costs of caregivers. Increases in caregiver depressive symptoms are associated with increases in multiple domains of caregivers’ healthcare use and costs. DISCUSSION: Findings suggest that we should expand our focus on dementia patients to include family caregivers to obtain a fuller picture of effects of caregiving. Primary care providers should integrate caregivers’ needs in healthcare planning and delivery. Clinical interventions that treat patients and caregivers as a whole will likely achieve the greatest beneficial effects. PMID:24637299

Self-affirmation model for football goal distributions

NASA Astrophysics Data System (ADS)

Bittner, E.; Nußbaumer, A.; Janke, W.; Weigel, M.

2007-06-01

Analyzing football score data with statistical techniques, we investigate how the highly co-operative nature of the game is reflected in averaged properties such as the distributions of scored goals for the home and away teams. It turns out that in particular the tails of the distributions are not well described by independent Bernoulli trials, but rather well modeled by negative binomial or generalized extreme value distributions. To understand this behavior from first principles, we suggest to modify the Bernoulli random process to include a simple component of self-affirmation which seems to describe the data surprisingly well and allows to interpret the observed deviation from Gaussian statistics. The phenomenological distributions used before can be understood as special cases within this framework. We analyzed historical football score data from many leagues in Europe as well as from international tournaments and found the proposed models to be applicable rather universally. In particular, here we compare men's and women's leagues and the separate German leagues during the cold war times and find some remarkable differences.

The Impact of a Pay-for-Performance Program on Central Line-Associated Blood Stream Infections in Pennsylvania.

PubMed

Bastian, Nathaniel D; Kang, Hyojung; Nembhard, Harriet B; Bloschichak, Andrew; Griffin, Paul M

2016-01-01

Healthcare associated infections have significantly contributed to the rising cost of hospital care in the United States. The implementation of pay-for-performance (P4P) programs has been one approach to improve quality at a reduced cost. We quantify the impact of Highmark's Quality Blue (QB) hospital P4P program on central line-associated blood stream infections (CLABSI) in Pennsylvania. The impact of years of participation in QB on CLABSI is also evaluated. Data from 149 Pennsylvania hospitals on CLABSI from 2008-2013 are used. Negative binomial regression and fixed effects panel regression are performed. Hospitals participating in QB have 0.727 times the CLABSI as those hospitals that do not participate. Hospitals participating for four or more years have on average 3.13 fewer CLABSI per year compared to those participating for less than four years. Highmark's P4P program has shown improved outcomes with regards to CLABSI, but further research is needed to determine if QB is cost effective.

Searching for the Kinkeepers: Historian Gender, Age, and Type 2 Diabetes Family History.

PubMed

Giordimaina, Alicia M; Sheldon, Jane P; Kiedrowski, Lesli A; Jayaratne, Toby Epstein

2015-12-01

Kinkeepers facilitate family communication and may be key to family medical history collection and dissemination. Middle-aged women are frequently kinkeepers. Using type 2 diabetes (T2DM) as a model, we explored whether the predicted gender and age effects of kinkeeping can be extended to family medical historians. Through a U.S. telephone survey, nondiabetic Mexican Americans (n = 385), Blacks (n = 387), and Whites (n = 396) reported family histories of T2DM. Negative binomial regressions used age and gender to predict the number of affected relatives reported. Models were examined for the gender gap, parabolic age effect, and gender-by-age interaction predicted by kinkeeping. Results demonstrated support for gender and parabolic age effects but only among Whites. Kinkeeping may have application to the study of White family medical historians, but not Black or Mexican American historians, perhaps because of differences in family structure, salience of T2DM, and/or gender roles. © 2015 Society for Public Health Education.

Health care usage among immigrants and native-born elderly populations in eleven European countries: results from SHARE

PubMed Central

Guillén, Montserrat; Crimmins, Eileen M.

2013-01-01

Differences in health care utilization of immigrants 50 years of age and older relative to the native-born populations in eleven European countries are investigated. Negative binomial and zero-inflated Poisson regression are used to examine differences between immigrants and native-borns in number of doctor visits, visits to general practitioners, and hospital stays using the 2004 Survey of Health, Ageing, and Retirement in Europe database. In the pooled European sample and in some individual countries, older immigrants use from 13 to 20% more health services than native-borns after demographic characteristics are controlled. After controlling for the need for health care, differences between immigrants and native-borns in the use of physicians, but not hospitals, are reduced by about half. These are not changed much with the incorporation of indicators of socioeconomic status and extra insurance coverage. Higher country-level relative expenditures on health, paying physicians a fee-for-service, and physician density are associated with higher usage of physician services among immigrants. PMID:21660564

The spatial extent of the effect of foreclosures on crime.

PubMed

Payton, Seth B; Stucky, Thomas D; Ottensmann, John R

2015-01-01

Although neighborhood stability has long been considered a substantial determinant of crime, foreclosures have not been the subject of concerted research among criminologists until recently. A number of recent studies have examined the linkage between home foreclosures and crime. Though generally finding a significant relationship, studies have used different approaches and units of analysis. This variation led us to examine the spatial extent to which foreclosures affect a relatively small surrounding area. In this paper, we consider the spatial extent of the foreclosure effect on crime by estimating fixed effect negative binomial models using geocoded UCR data for 2003-2008 and foreclosure data to predict crime counts using the number of foreclosures within various small area radii. Results show that, independently and jointly, foreclosures are a predictor of crime up to at least a distance of 2250 feet. Importantly, that effect declines with distance. We conclude with a discussion of the implications of those findings. Copyright © 2014 Elsevier Inc. All rights reserved.

Musculoskeletal disorders and associated healthcare costs among family members of injured workers.

PubMed

Asfaw, Abay; Pana-Cryan, Regina; Bushnell, Tim; Sauter, Steven

2015-11-01

Research has infrequently looked beyond the injured worker when gauging the burden of occupational injury. We explored the relationship between occupational injury and musculoskeletal disorders (MSDs) among family members of injured workers. We used 2005 and 2006 Truven Health Analytics databases, which contain information on workers' compensation and family healthcare claims. We used descriptive analyses, and negative binomial and two-part models. Family members of severely injured workers had a 15% increase in the total number of MSD outpatient claims and a 34% increase in the mean cost of MSD claims compared to family members of non-severely injured workers within 3 months after injury. Extrapolating cost results to the national level implies that severe occupational injury would be associated with between $29 and $33 million additional cost of family member outpatient MSD claims. Occupational injury can impose a formerly unrecognized health burden on family members of injured workers. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Regional Differences in the Growing Incidence of Dengue Fever in Vietnam Explained by Weather Variability

PubMed Central

Vu, Ha Hai; Okumura, Junko; Hashizume, Masahiro; Tran, Duong Nhu; Yamamoto, Taro

2014-01-01

Dengue fever is a major health problem in Vietnam, but its incidence differs from province to province. To understand this at the local level, we assessed the effect of four weather components (humidity, rainfall, temperature and sunshine) on the number of dengue cases in nine provinces of Vietnam. Monthly data from 1999 to 2009 were analysed by time-series regression using negative binomial models. A test for heterogeneity was applied to assess the weather-dengue association in the provinces. Those associations were significantly heterogeneous (for temperature, humidity, and sunshine: P < 0.001 heterogeneity test; for rainfall: P = 0.018 heterogeneity test). This confirms that weather components strongly affect dengue transmission at a lag time of 0 to 3 months, with considerable variation in their influence among different areas in Vietnam. This finding may promote the strategic prevention of dengue disease by suggesting specific plans at the local level, rather than a nationally unified approach. PMID:24808744

Encephalitis, Ontario, Canada, 2002–2013

PubMed Central

Parpia, Alyssa S.; Li, Ye; Chen, Cynthia; Dhar, Badal

2016-01-01

Encephalitis, a brain inflammation leading to severe illness and often death, is caused by >100 pathogens. To assess the incidence and trends of encephalitis in Ontario, Canada, we obtained data on 6,463 Ontario encephalitis hospitalizations from the hospital Discharge Abstract Database for April 2002–December 2013 and analyzed these data using multiple negative binomial regression. The estimated crude incidence of all-cause encephalitis in Ontario was ≈4.3 cases/100,000 persons/year. Incidence rates for infants <1 year of age and adults >65 years were 3.9 and 3.0 times that of adults 20–44 years of age, respectively. Incidence peaks during August–September in 2002 and 2012 resulted primarily from encephalitis of unknown cause and viral encephalitis. Encephalitis occurred more frequently in older age groups and less frequently in women in Ontario when compared to England, but despite differences in population, vector-borne diseases, climate, and geography, the epidemiology was overall remarkably similar in the two regions. PMID:26890626

Hospitalization for primary care susceptible conditions, health spending and Family Health Strategy: an analysis of trends.

PubMed

Morimoto, Tissiani; Costa, Juvenal Soares Dias da

2017-03-01

The goal of this study was to analyze the trend over time of hospitalizations due to conditions susceptible to primary healthcare (HCSPC), and how it relates to healthcare spending and Family Health Strategy (FHS) coverage in the city of São Leopoldo, Rio Grande do Sul State, Brazil, between 2003 and 2012. This is an ecological, time-trend study. We used secondary data available in the Unified Healthcare System Hospital Data System, the Primary Care Department and Public Health Budget Data System. The analysis compared HCSPC using three-year moving averages and Poisson regressions or negative binomials. We found no statistical significance in decreasing HCSPC indicators and primary care spending in the period analyzed. Healthcare spending, per-capita spending and FHS coverage increased significantly, but we found no correlation with HCSPC. The results show that, despite increases in the funds invested and population covered by FHS, they are still insufficient to deliver the level of care the population requires.

Self-reported discrimination and health-related quality of life among Whites, Blacks, Mexicans and Central Americans.

PubMed

Otiniano, Angie Denisse; Gee, Gilbert C

2012-04-01

This study investigates whether self-reported racial discrimination is related to poor health-related quality of life (HRQoL). Analyses focused on Whites (n = 52,571), Blacks (n = 4,343), Mexicans (n = 12,336), Central Americans (n = 1,504), Multi-ethnic Latinos (n = 1,102), and Other Latinos (n = 1,828) who participated in the 2003 and 2005 California Health Interview survey. Logistic and negative binomial regression was used to examine the association between HRQoL (assessed with the CDC unhealthy days measures) and self-reported racial discrimination. Discrimination was reported by 10% of Whites, 57% of Blacks, and 24-31% of the Latino groups. These reports were associated with increased number of unhealthy days, disability days, and poor self-rated health, even after, controlling for education and other factors. This association did not consistently vary by race/ethnicity. Racial discrimination may be a risk factor for poor HRQoL among diverse groups. Future research should examine the factors that may reduce potential exposure to racial discrimination.

Predictors of Depression and Musculoskeletal Disorder Related Work Disability Among Young, Middle-Aged, and Aging Employees.

PubMed

Ervasti, Jenni; Mattila-Holappa, Pauliina; Joensuu, Matti; Pentti, Jaana; Lallukka, Tea; Kivimäki, Mika; Vahtera, Jussi; Virtanen, Marianna

2017-01-01

The aim of this study was to investigate the level and predictors of work disability in different age groups. We followed young (18 to 34 years), middle-aged (35 to 50 years), and aging (>50 years) employees (n = 70,417) for 7 years (2005 to 2011) for all-cause and cause-specific work disability (sickness absence and disability pension). Using negative binomial regression, we obtained both relative risk estimates and absolute rates, that is, days of work disability per person-year. The greatest relative difference in all-cause, and specifically depression-related work disability, was between young women and young men, and between employees with low versus high levels of education. Aging employees with a low education and chronic somatic disease had the highest levels of musculoskeletal disorder related work disability. The predictors of work disability vary by age and diagnosis. These results help target age-specific measures for the prevention of permanent work disability.

Occupational class differences in suicide: evidence of changes over time and during the global financial crisis in Australia.

PubMed

Milner, Alison J; Niven, Heather; LaMontagne, Anthony D

2015-09-21

Previous research showed an increase in Australian suicide rates during the Global Financial Crisis (GFC). There has been no research investigating whether suicide rates by occupational class changed during the GFC. The aim of this study was to investigate whether the GFC-associated increase in suicide rates in employed Australians may have masked changes by occupational class. Negative binomial regression models were used to investigate Rate Ratios (RRs) in suicide by occupational class. Years of the GFC (2007, 2008, 2009) were compared to the baseline years 2001-2006. There were widening disparities between a number of the lower class occupations and the highest class occupations during the years 2007, 2008, and 2009 for males, but less evidence of differences for females. Occupational disparities in suicide rates widened over the GFC period. There is a need for programs to be responsive to economic downturns, and to prioritise the occupational groups most affected.

Selection and quantification of infection endpoints for trials of vaccines against intestinal helminths

PubMed Central

Alexander, Neal; Cundill, Bonnie; Sabatelli, Lorenzo; Bethony, Jeffrey M.; Diemert, David; Hotez, Peter; Smith, Peter G.; Rodrigues, Laura C.; Brooker, Simon

2011-01-01

Vaccines against human helminths are being developed but the choice of optimal parasitological endpoints and effect measures to assess their efficacy has received little attention. Assuming negative binomial distributions for the parasite counts, we rank the statistical power of three measures of efficacy: ratio of mean parasite intensity at the end of the trial, the odds ratio of infection at the end of the trial, and the rate ratio of incidence of infection during the trial. We also use a modelling approach to estimate the likely impact of trial interventions on the force of infection, and hence statistical power. We conclude that (1) final mean parasite intensity is a suitable endpoint for later phase vaccine trials, and (2) mass effects of trial interventions are unlikely to appreciably reduce the force of infection in the community – and hence statistical power – unless there is a combination of high vaccine efficacy and a large proportion of the population enrolled. PMID:21435404

Double-edged sword of interdisciplinary knowledge flow from hard sciences to humanities and social sciences: Evidence from China

PubMed Central

Liu, Meijun; Shi, Dongbo

2017-01-01

Humanities and Social Sciences (HSS) increasingly absorb knowledge from Hard Sciences, i.e., Science, Technology, Agriculture and Medicine (STAM), as testified by a growing number of citations. However, whether citing more Hard Sciences brings more citations to HSS remains to be investigated. Based on China’s HSS articles indexed by the Web of Science during 1998–2014, this paper estimated two-way fixed effects negative binomial models, with journal effects and year effects. Findings include: (1) An inverse U-shaped curve was observed between the percentage of STAM references to the HSS articles and the number of citations they received; (2) STAM contributed increasing knowledge to China’s HSS, while Science and Technology knowledge contributed more citations to HSS articles. It is recommended that research policy should be adjusted to encourage HSS researchers to adequately integrate STAM knowledge when conducting interdisciplinary research, as over-cited STAM knowledge may jeopardize the readability of HSS articles. PMID:28934277

Abuse and diversion of buprenorphine sublingual tablets and film.

PubMed

Lavonas, Eric J; Severtson, S Geoffrey; Martinez, Erin M; Bucher-Bartelson, Becki; Le Lait, Marie-Claire; Green, Jody L; Murrelle, Lenn E; Cicero, Theodore J; Kurtz, Steven P; Rosenblum, Andrew; Surratt, Hilary L; Dart, Richard C

2014-07-01

Buprenorphine abuse is common worldwide. Rates of abuse and diversion of three sublingual buprenorphine formulations (single ingredient tablets; naloxone combination tablets and film) were compared. Data were obtained from the Researched Abuse, Diversion, and Addiction-Related Surveillance (RADARS) System Poison Center, Drug Diversion, Opioid Treatment (OTP), Survey of Key Informants' Patients (SKIP), and College Survey Programs through December 2012. To control for drug availability, event ratios (rates) were calculated quarterly, based on the number of patients filling prescriptions for each formulation ("unique recipients of a dispensed drug," URDD) and averaged and compared using negative binomial regression. Abuse rates in the OTP, SKIP, and College Survey Programs were greatest for single ingredient tablets, and abuse rates in the Poison Center Program and illicit diversion rates were greatest for the combination tablets. Combination film rates were significantly less than rates for either tablet formulation in all programs. No geographic pattern could be discerned. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Workplace discrimination and health among Filipinos in the United States.

PubMed

de Castro, Arnold B; Gee, Gilbert C; Takeuchi, David T

2008-03-01

We examined the association between work discrimination and morbidity among Filipinos in the United States, independent of more-global measures of discrimination. Data were collected from the Filipino American Community Epidemiological Survey. Our analysis focused on 1652 participants who were employed at the time of data collection, and we used negative binomial regression to determine the association between work discrimination and health conditions. The report of workplace discrimination specific to being Filipino was associated with an increased number of health conditions. This association persisted even after we controlled for everyday discrimination, a general assessment of discrimination; job concerns, a general assessment of unpleasant work circumstances; having immigrated for employment reasons; job category; income; education; gender; and other sociodemographic factors. Racial discrimination in the workplace was positively associated with poor health among Filipino Americans after we controlled for reports of everyday discrimination and general concerns about one's job. This finding shows the importance of considering the work setting as a source of discrimination and its effect on morbidity among racial minorities.

Foodborne and Waterborne Infections in Elderly Community and Long-Term Care Facility Residents, Victoria, Australia

PubMed Central

Gregory, Joy; Lalor, Karin; Hall, Gillian V.; Becker, Niels

2012-01-01

We calculated rates of foodborne and waterborne infections reported to the health department in Victoria, Australia, during 2000–2009 for elderly residents of long-term care facilities (LTCFs) and the community. We used negative binomial regression to estimate incidence rate ratios, adjusting for age, sex, and reporting period. We analyzed 8,277 infections in elderly persons. Rates of campylobacteriosis, legionellosis, listeriosis, toxigenic Escherichia coli infections, and shigellosis were higher in community residents, and rates of Salmonella infection were higher in LTCF residents. Each year, 61.7 Campylobacter infections were reported per 100,000 LTCF residents, compared with 97.6 per 100,000 community residents. LTCF residents were at higher risk for S. enterica serotype Typhimurium associated with outbreaks. Rates of foodborne infections (except salmonellosis) were similar to or lower for LTCF residents than for community residents. These findings may indicate that food preparation practices in LTCFs are safer than those used by elderly persons in the community. PMID:22377177

Problems With Using Patient Retention in the Evaluation of Mental Health Providers: Differences in Type of Dropout.

PubMed

Brown, Halley J; Andreason, Hope; Melling, Amy K; Imel, Zac E; Simon, Gregory E

2015-08-01

Retention, or its opposite, dropout, is a common metric of psychotherapy quality, but using it to assess provider performance can be problematic. Differences among providers in numbers of general dropouts, "good" dropouts (patients report positive treatment experiences and outcome), and "bad" dropouts (patients report negative treatment experiences and outcome) were evaluated. Patient records were paired with satisfaction surveys (N=3,054). Binomial mixed-effects models were used to examine differences among providers by dropout type. Thirty-four percent of treatment episodes resulted in dropout. Of these, 14% were bad dropouts and 27% were good dropouts. Providers accounted for approximately 17% of the variance in general dropout and 10% of the variance in both bad dropout and good dropout. The ranking of providers fluctuated by type of dropout. Provider assessments based on patient retention should offer a way to isolate dropout type, given that nonspecific metrics may lead to biased estimates of performance.

Interdependence in Health and Functioning Among Older Spousal Caregivers and Care Recipients.

PubMed

Hoffman, Geoffrey J; Burgard, Sarah; Mendez-Luck, Carolyn A; Gaugler, Joseph E

2018-06-01

Older spousal caregiving relationships involve support that may be affected by the health of either the caregiver or care recipient. We conducted a longitudinal analysis using pooled data from 4,632 community-dwelling spousal care recipients and caregivers aged ⩾50 from the 2002 to 2014 waves of the Health and Retirement Study. We specified logistic and negative binomial regression models using lagged predictor variables to assess the role of partner health status on spousal caregiver and care recipient health care utilization and physical functioning outcomes. Care recipients' odds of hospitalization, odds ratio (OR): 0.83, p<.001, decreased when caregivers had more ADL difficulties. When spouses were in poorer versus better health, care recipients' bed days decreased (4.69 vs. 2.54) while caregivers' bed days increased (0.20 vs. 0.96). Providers should consider the dual needs of caregivers caring for care recipients and their own health care needs, in adopting a family-centered approach to management of older adult long-term care needs.

Deforestation and Malaria in Mâncio Lima County, Brazil

PubMed Central

Gangnon, Ronald; Silveira, Guilherme Abbad; Patz, Jonathan A.

2010-01-01

Malaria is the most prevalent vector-borne disease in the Amazon. We used malaria reports for health districts collected in 2006 by the Programa Nacional de Controle da Malária to determine whether deforestation is associated with malaria incidence in the county (município) of Mâncio Lima, Acre State, Brazil. Cumulative percent deforestation was calculated for the spatial catchment area of each health district by using 60 × 60–meter, resolution-classified imagery. Statistical associations were identified with univariate and multivariate general additive negative binomial models adjusted for spatial effects. Our cross-sectional study shows malaria incidence across health districts in 2006 is positively associated with greater changes in percentage of cumulative deforestation within respective health districts. After adjusting for access to care, health district size, and spatial trends, we show that a 4.3%, or 1 SD, change in deforestation from August 1997 through August 2000 is associated with a 48% increase of malaria incidence. PMID:20587182

The relationship between perceived discrimination and high-risk social ties among illicit drug users in New York City, 2006-2009.

PubMed

Crawford, Natalie D; Ford, Chandra; Galea, Sandro; Latkin, Carl; Jones, Kandice C; Fuller, Crystal M

2013-01-01

Discrimination can influence risk of disease by promoting unhealthy behaviors (e.g., smoking, alcohol use). Whether it influences the formation of high-risk social ties that facilitate HIV transmission is unclear. Using cross-sectional data from a cohort of illicit drug users, this study examined the association between discrimination based on race, drug use and prior incarceration and risky sex and drug ties. Negative binomial regression models were performed. Participants who reported discrimination based on race and drug use had significantly more sex and drug-using ties. But, after accounting for both racial and drug use discrimination, only racial discrimination was associated with increased sex, drug-using, and injecting ties. Drug users who experience discrimination and subsequently develop more sex and drug-using ties, increase their risk of contracting HIV. Future longitudinal studies illuminating the pathways linking discrimination and social network development may guide intervention development and identify drug-using subpopulations at high risk for disease transmission.

Relaxed Poisson cure rate models.

PubMed

Rodrigues, Josemar; Cordeiro, Gauss M; Cancho, Vicente G; Balakrishnan, N

2016-03-01

The purpose of this article is to make the standard promotion cure rate model (Yakovlev and Tsodikov, ) more flexible by assuming that the number of lesions or altered cells after a treatment follows a fractional Poisson distribution (Laskin, ). It is proved that the well-known Mittag-Leffler relaxation function (Berberan-Santos, ) is a simple way to obtain a new cure rate model that is a compromise between the promotion and geometric cure rate models allowing for superdispersion. So, the relaxed cure rate model developed here can be considered as a natural and less restrictive extension of the popular Poisson cure rate model at the cost of an additional parameter, but a competitor to negative-binomial cure rate models (Rodrigues et al., ). Some mathematical properties of a proper relaxed Poisson density are explored. A simulation study and an illustration of the proposed cure rate model from the Bayesian point of view are finally presented. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatio-temporal modelling of dengue fever incidence in Malaysia

NASA Astrophysics Data System (ADS)

Che-Him, Norziha; Ghazali Kamardan, M.; Saifullah Rusiman, Mohd; Sufahani, Suliadi; Mohamad, Mahathir; @ Kamariah Kamaruddin, Nafisah

2018-04-01

Previous studies reported significant relationship between dengue incidence rate (DIR) and both climatic and non-climatic factors. Therefore, this study proposes a generalised additive model (GAM) framework for dengue risk in Malaysia by using both climatic and non-climatic factors. The data used is monthly DIR for 12 states of Malaysia from 2001 to 2009. In this study, we considered an annual trend, seasonal effects, population, population density and lagged DIR, rainfall, temperature, number of rainy days and El Niño-Southern Oscillation (ENSO). The population density is found to be positively related to monthly DIR. There are generally weak relationships between monthly DIR and climate variables. A negative binomial GAM shows that there are statistically significant relationships between DIR with climatic and non-climatic factors. These include mean rainfall and temperature, the number of rainy days, sea surface temperature and the interaction between mean temperature (lag 1 month) and sea surface temperature (lag 6 months). These also apply to DIR (lag 3 months) and population density.

CHANGES IN CONDOM USE OVER TIME AMONG FEMALE SEX WORKERS AND THEIR MALE NONCOMMERCIAL PARTNERS AND CLIENTS

PubMed Central

Tracas, Ashley; Bazzi, Angela Robertson; Artamonova, Irina; Rangel, M. Gudelia; Staines, Hugo; Ulibarri, Monica D.

2017-01-01

Female sex workers (FSWs) often report inconsistent condom use with clients and noncommercial male partners, yet changes in condom use with various partner types during participation in observation studies remains underexplored. This longitudinal study of 214 FSWs and their male, noncommercial partners in the Mexico-U.S. border region, where HIV prevalence among FSWs continues to be high, utilized negative binomial regressions to examine changes in condom use with intimate partners and clients (regular and nonregular) over 24 months. Condom use decreased over time among couples in Ciudad Juarez, but there was no change in condom use among couples in Tijuana. FSWs’ condom use with regular and nonregular clients significantly increased over time, which is consistent with previous research finding behavioral changes when participating in observational studies. Findings suggest the need for continued efforts to promote condom use among FSWs and their noncommercial male partners in addition to clients. PMID:27427926

Forecast of severe fever with thrombocytopenia syndrome incidence with meteorological factors.

PubMed

Sun, Ji-Min; Lu, Liang; Liu, Ke-Ke; Yang, Jun; Wu, Hai-Xia; Liu, Qi-Yong

2018-06-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and some studies reported that SFTS incidence was associated with meteorological factors, while no report on SFTS forecast models was reported up to date. In this study, we constructed and compared three forecast models using autoregressive integrated moving average (ARIMA) model, negative binomial regression model (NBM), and quasi-Poisson generalized additive model (GAM). The dataset from 2011 to 2015 were used for model construction and the dataset in 2016 were used for external validity assessment. All the three models fitted the SFTS cases reasonably well during the training process and forecast process, while the NBM model forecasted better than other two models. Moreover, we demonstrated that temperature and relative humidity played key roles in explaining the temporal dynamics of SFTS occurrence. Our study contributes to better understanding of SFTS dynamics and provides predictive tools for the control and prevention of SFTS. Copyright © 2018 Elsevier B.V. All rights reserved.

[Effects of climate and grazing on the vegetation cover change in Xilinguole League of Inner Mongolia, North China].

PubMed

Wang, Hai-Mei; Li, Zheng-Hai; Wang, Zhen

2013-01-01

Based on the monthly temperature and precipitation data of 15 meteorological stations and the statistical data of livestock density in Xilinguole League in 1981-2007, and by using ArcGIS, this paper analyzed the spatial distribution of the climate aridity and livestock density in the League, and in combining with the ten-day data of the normalized difference vegetation index (NDVI) in 1981-2007, the driving factors of the vegetation cover change in the League were discussed. In the study period, there was a satisfactory linear regression relationship between the climate aridity and the vegetation coverage. The NDVI and the livestock density had a favorable binomial regression relationship. With the increase of NDVI, the livestock density increased first and decreased then. The vegetation coverage had a complex linear relationship with livestock density and climate aridity. The NDVI had a positive correlation with climate aridity, but a negative correlation with livestock density. Compared with livestock density, climate aridity had far greater effects on the NDVI.

The spatial distribution of fixed mutations within genes coding for proteins

NASA Technical Reports Server (NTRS)

Holmquist, R.; Goodman, M.; Conroy, T.; Czelusniak, J.

1983-01-01

An examination has been conducted of the extensive amino acid sequence data now available for five protein families - the alpha crystallin A chain, myoglobin, alpha and beta hemoglobin, and the cytochromes c - with the goal of estimating the true spatial distribution of base substitutions within genes that code for proteins. In every case the commonly used Poisson density failed to even approximate the experimental pattern of base substitution. For the 87 species of beta hemoglobin examined, for example, the probability that the observed results were from a Poisson process was the minuscule 10 to the -44th. Analogous results were obtained for the other functional families. All the data were reasonably, but not perfectly, described by the negative binomial density. In particular, most of the data were described by one of the very simple limiting forms of this density, the geometric density. The implications of this for evolutionary inference are discussed. It is evident that most estimates of total base substitutions between genes are badly in need of revision.

Hope and Hopelessness: The Role of Hope in Buffering the Impact of Hopelessness on Suicidal Ideation.

PubMed

Huen, Jenny M Y; Ip, Brian Y T; Ho, Samuel M Y; Yip, Paul S F

2015-01-01

The present study investigated whether hope and hopelessness are better conceptualized as a single construct of bipolar spectrum or two distinct constructs and whether hope can moderate the relationship between hopelessness and suicidal ideation. Hope, hopelessness, and suicidal ideation were measured in a community sample of 2106 participants through a population-based household survey. Confirmatory factor analyses showed that a measurement model with separate, correlated second-order factors of hope and hopelessness provided a good fit to the data and was significantly better than that of the model collapsing hope and hopelessness into a single second-order factor. Negative binomial regression showed that hope and hopelessness interacted such that the effect of hopelessness on suicidal ideation was lower in individuals with higher hope than individuals with lower hope. Hope and hopelessness are two distinct but correlated constructs. Hope can act as a resilience factor that buffers the impact of hopelessness on suicidal ideation. Inducing hope in people may be a promising avenue for suicide prevention.

Double-edged sword of interdisciplinary knowledge flow from hard sciences to humanities and social sciences: Evidence from China.

PubMed

Liu, Meijun; Shi, Dongbo; Li, Jiang

2017-01-01

Humanities and Social Sciences (HSS) increasingly absorb knowledge from Hard Sciences, i.e., Science, Technology, Agriculture and Medicine (STAM), as testified by a growing number of citations. However, whether citing more Hard Sciences brings more citations to HSS remains to be investigated. Based on China's HSS articles indexed by the Web of Science during 1998-2014, this paper estimated two-way fixed effects negative binomial models, with journal effects and year effects. Findings include: (1) An inverse U-shaped curve was observed between the percentage of STAM references to the HSS articles and the number of citations they received; (2) STAM contributed increasing knowledge to China's HSS, while Science and Technology knowledge contributed more citations to HSS articles. It is recommended that research policy should be adjusted to encourage HSS researchers to adequately integrate STAM knowledge when conducting interdisciplinary research, as over-cited STAM knowledge may jeopardize the readability of HSS articles.

Peer influence processes for youth delinquency and depression.

PubMed

Reynolds, Andrew D; Crea, Thomas M

2015-08-01

This study explores the multiple factors that account for peer influence processes of adolescent delinquency and depression using data from Waves I and II of the National Longitudinal Study of Adolescent to Adult Health (Add Health). Random-effects longitudinal negative binomial models were used to predict depression and delinquency, controlling for social connection variables to account for selection bias. Findings suggest peer depression and delinquency are both predictive of youth delinquency, while peer influences of depression are much more modest. Youth who are more connected to parents and communities and who are more popular within their networks are more susceptible to peer influence, while self-regulating youth are less susceptible. We find support for theories of popularity-socialization as well as weak-ties in explaining social network factors that amplify or constrain peer influence. We argue that practitioners working with youth should consider network-informed interventions to improve program efficacy and avoid iatrogenic effects. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Effect of Brazil's conditional cash transfer programme on tuberculosis incidence.

PubMed

Nery, J S; Rodrigues, L C; Rasella, D; Aquino, R; Barreira, D; Torrens, A W; Boccia, D; Penna, G O; Penna, M L F; Barreto, M L; Pereira, S M

2017-07-01

To evaluate the impact of the Brazilian cash transfer programme (Bolsa Família Programme, BFP) on tuberculosis (TB) incidence in Brazil from 2004 to 2012. We studied tuberculosis surveillance data using a combination of an ecological multiple-group and time-trend design covering 2458 Brazilian municipalities. The main independent variable was BFP coverage and the outcome was the TB incidence rate. All study variables were obtained from national databases. We used fixed-effects negative binomial models for panel data adjusted for selected covariates and a variable representing time. After controlling for covariates, TB incidence rates were significantly reduced in municipalities with high BFP coverage compared with those with low and intermediate coverage (in a model with a time variable incidence rate ratio = 0.96, 95%CI 0.93-0.99). This was the first evidence of a statistically significant association between the increase in cash transfer programme coverage and a reduction in TB incidence rate. Our findings provide support for social protection interventions for tackling TB worldwide.

Protecting Construction Worker Health and Safety in Ontario, Canada: Identifying a Union Safety Effect.

PubMed

Amick, Benjamin C; Hogg-Johnson, Sheilah; Latour-Villamil, Desiree; Saunders, Ron

2015-12-01

Do Ontario unionized construction firms have lower workers' compensation claims rates compared with nonunion firms? Building trade and construction trade association lists of union contractors were linked to Workplace Safety and Insurance Board claims data for 2006 to 2012. Data were pooled for 2006 to 2012, and negative binomial regressions conducted with adjustment to estimate a union safety effect. The sample included 5797 unionized and 38,626 nonunion construction firms. Total claims rates were 13% higher (1.13, 1.09 to 1.18) in unionized firms because of higher allowed no-lost-time claim rates (1.28, 1.23 to 1.34), whereas the lost-time claims rate was 14% lower (0.86, 0.82 to 0.91). Unionized construction firms compared with nonunion firms have higher no-lost-time and lower lost-time claims rates. Unionized firms may encourage occupational injury reporting and reduce risks through training and hazard identification and control strategies.