Physical activity in England: who is meeting the recommended level of participation through sports and exercise?

PubMed

Anokye, Nana Kwame; Pokhrel, Subhash; Buxton, Martin; Fox-Rushby, Julia

2013-06-01

Little is known about the correlates of meeting recommended levels of participation in physical activity (PA) and how this understanding informs public health policies on behaviour change. To analyse who meets the recommended level of participation in PA in males and females separately by applying 'process' modelling frameworks (single vs. sequential 2-step process). Using the Health Survey for England 2006, (n = 14 142; ≥ 16 years), gender-specific regression models were estimated using bivariate probit with selectivity correction and single probit models. A 'sequential, 2-step process' modelled participation and meeting the recommended level separately, whereas the 'single process' considered both participation and level together. In females, meeting the recommended level was associated with degree holders [Marginal effect (ME) = 0.013] and age (ME = -0.001), whereas in males, age was a significant correlate (ME = -0.003 to -0.004). The order of importance of correlates was similar across genders, with ethnicity being the most important correlate in both males (ME = -0.060) and females (ME = -0.133). In females, the 'sequential, 2-step process' performed better (ρ = -0.364, P < 0.001) than that in males (ρ = 0.154). The degree to which people undertake the recommended level of PA through vigorous activity varies between males and females, and the process that best predicts such decisions, i.e. whether it is a sequential, 2-step process or a single-step choice, is also different for males and females. Understanding this should help to identify subgroups that are less likely to meet the recommended level of PA (and hence more likely to benefit from any PA promotion intervention).

Children’s Emotional and Behavioral Problems and Their Mothers’ Labor Supply

PubMed Central

Gaskin, Darrell J.; Alexandre, Pierre K.; Burke, Laura S.; Younis, Mustafa

2014-01-01

It has been documented that about 20% of children and adolescents suffer from a diagnosable mental or addictive disorder in the United States. The high prevalence of children’s emotional and behavioral problems (EBP) might have a negative effect on their mothers’ labor market outcomes because children with EBP require additional time for treatment. However, these children may require additional financial resources, which might promote mothers’ labor supply. Previous studies have only considered chronic conditions in analyzing the impact of children’s health on parental work activities. Moreover, most of these studies have not accounted for endogeneity in children’s health. This article estimates the effects of children’s EBP on their mothers’ labor supply by family structure while accounting for endogeneity in children’s health. We used the 1997 and 2002 Child Development Supplements (CDS) to the Panel Study of Income Dynamics (PSID). We used probit and bivariate probit models to estimate mothers’ probability of employment, and tobit and instrumental variable tobit models to estimate the effects of children’s EBP on their mothers’ work hours. Findings show negative effects of children’s EBP on their married mothers’ employment and on their single mothers’ work hours. PMID:25466413

An evaluation of substance misuse treatment providers used by an employee assistance program.

PubMed

Miller, N A

1992-05-01

Structural measures of access, continuity, and quality of substance misuse treatment services were compared in 30 fee-for-service (FFS) facilities and nine health maintenance organizations (HMOs). Probit models related effects of the provider system (FFS or HMO) and the system's structural characteristics to 243 employees' access to and outcomes from treatment. Access was decreased in Independent Practice Association (IPA)/network HMOs and in all facilities which did not employ an addictionologist or provide coordinated treatment services. When bivariate correlations were examined, both use of copayments and imposing limits to the levels of treatment covered were negatively related to access, while a facility's provision of ongoing professional development was positively associated with access. These correlations did not remain significant in the multivariate probits. Receiving treatment in a staff model HMO and facing limits to the levels of treatment covered were negatively associated with attaining sufficient progress, while receiving treatment in a facility which provided ongoing professional development was positively related to progress: these effects did not remain significant in multivariate analyses. Implications for employee assistance program (EAP) staff in their role as case managers and for EAP staff and employers in their shared role as purchasers of treatment are discussed.

Children's emotional and behavioral problems and their mothers' labor supply.

PubMed

Richard, Patrick; Gaskin, Darrell J; Alexandre, Pierre K; Burke, Laura S; Younis, Mustafa

2014-01-01

It has been documented that about 20% of children and adolescents suffer from a diagnosable mental or addictive disorder in the United States. The high prevalence of children's emotional and behavioral problems (EBP) might have a negative effect on their mothers' labor market outcomes because children with EBP require additional time for treatment. However, these children may require additional financial resources, which might promote mothers' labor supply. Previous studies have only considered chronic conditions in analyzing the impact of children's health on parental work activities. Moreover, most of these studies have not accounted for endogeneity in children's health. This article estimates the effects of children's EBP on their mothers' labor supply by family structure while accounting for endogeneity in children's health. We used the 1997 and 2002 Child Development Supplements (CDS) to the Panel Study of Income Dynamics (PSID). We used probit and bivariate probit models to estimate mothers' probability of employment, and tobit and instrumental variable tobit models to estimate the effects of children's EBP on their mothers' work hours. Findings show negative effects of children's EBP on their married mothers' employment and on their single mothers' work hours. © The Author(s) 2014.

A behavioral choice model of the use of car-sharing and ride-sourcing services

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

Dias, Felipe F.; Lavieri, Patrícia S.; Garikapati, Venu M.

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014-2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There aremore » significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.« less

Risk factors associated with the practice of child marriage among Roma girls in Serbia.

PubMed

Hotchkiss, David R; Godha, Deepali; Gage, Anastasia J; Cappa, Claudia

2016-02-01

Relatively little research on the issue of child marriage has been conducted in European countries where the overall prevalence of child marriage is relatively low, but relatively high among marginalized ethnic sub-groups. The purpose of this study is to assess the risk factors associated with the practice of child marriage among females living in Roma settlements in Serbia and among the general population and to explore the inter-relationship between child marriage and school enrollment decisions. The study is based on data from a nationally representative household survey in Serbia conducted in 2010 - and a separate survey of households living in Roma settlements in the same year. For each survey, we estimated a bivariate probit model of risk factors associated with being currently married and currently enrolled in school based on girls 15 to 17 years of age in the nationally representative and Roma settlements samples. The practice of child marriage among the Roma was found to be most common among girls who lived in poorer households, who had less education, and who lived in rural locations. The results of the bivariate probit analysis suggest that, among girls in the general population, decisions about child marriage school attendance are inter-dependent in that common unobserved factors were found to influence both decisions. However, among girls living in Roma settlements, there is only weak evidence of simultaneous decision making. The study finds evidence of the interdependence between marriage and school enrollment decisions among the general population and, to a lesser extent, among the Roma. Further research is needed on child marriage among the Roma and other marginalized sub-groups in Europe, and should be based on panel data, combined with qualitative data, to assess the role of community-level factors and the characteristics of households where girls grow up on child marriage and education decisions.

Substitution of Formal and Informal Home Care Service Use and Nursing Home Service Use: Health Outcomes, Decision-Making Preferences, and Implications for a Public Health Policy.

PubMed

Chen, Chia-Ching; Yamada, Tetsuji; Nakashima, Taeko; Chiu, I-Ming

2017-01-01

The purposes of this study are: (1) to empirically identify decision-making preferences of long-term health-care use, especially informal and formal home care (FHC) service use; (2) to evaluate outcomes vs. costs based on substitutability of informal and FHC service use; and (3) to investigate health outcome disparity based on substitutability. The methods of ordinary least squares, a logit model, and a bivariate probit model are used by controlling for socioeconomic, demographic, and physical/mental health factors to investigate outcomes and costs based substitutability of informal and formal health-care use. The data come from the 2013 Japanese Study of Aging and Retirement (JSTAR), which is designed by Keizai-Sangyo Kenkyu-jo, Hitotsubashi University, and the University of Tokyo. The JSTAR is a globally comparable data survey of the elderly. There exists a complement relationship between the informal home care (IHC) and community-based FHC services, and the elasticity's ranges from 0.18 to 0.22. These are reasonable results, which show that unobservable factors are positively related to IHC and community-based FHC, but negatively related to nursing home (NH) services based on our bivariate probit model. Regarding health-care outcome efficiency issue, the IHC is the best one among three types of elderly care: IHC, community-based FHC, and NH services. Health improvement/outcome of elderly with the IHC is heavier concentrated on IHC services than the elderly care services by community-based FHC and NH care services. Policy makers need to address a diversity of health outcomes and efficiency of services based on providing services to elderly through resource allocation to the different types of long-term care. A provision of partial or full compensation for elderly care at home is recommendable and a viable option to improve their quality of lives.

Internal and external scope in willingness-to-pay estimates for threatened and endangered wildlife

USGS Publications Warehouse

Giraud, K.L.; Loomis, J.B.; Johnson, R.L.

1999-01-01

Economic theory suggests willingness-to-pay (WTP) should be significantly higher for a comprehensive good than for a subset of that good. We tested this using both a split sample design (external scope test) and paired responses (internal scope test) for WTP for several endangered fish and wildlife species in the US. In the paired response case we corrected for correlation of willingness-to-pay responses using a bivariate probit model. Surprisingly, the independent split samples passed the scope test but the paired samples did not. As the results contradict each other, questions of validity for policy implications are raised. However, using either approach, the benefit of maintaining critical habitat for these species exceeds the costs.

Factors affecting Taiwanese smokers' identification of smuggled cigarettes.

PubMed

Hsieh, Chi-Jung; Cheng, Chun-Hao; Lee, Jie-Min

2015-05-01

To analyze whether the perception that smuggled cigarettes are a greater health risk than legal cigarettes affects Taiwanese smokers' intention to distinguish smuggled cigarettes from legal cigarettes. The study used the Recursive Bivariate Probit Model to analyze data from a survey conducted in 2013 of 450 smokers of smuggled cigarettes. The study found that when smokers believe they are more likely to get lung cancer from consuming smuggled cigarettes than they are from consuming legal cigarettes, the probability of the intention to identify smuggled cigarettes increased by 42.46%. The government should strengthen educational policies and programs that teach consumers about the health risks of smoking in general and the even greater health risks of smoking smuggled cigarettes in particular.

Investigation of factors affecting the injury severity of single-vehicle rollover crashes: A random-effects generalized ordered probit model.

PubMed

Anarkooli, Alireza Jafari; Hosseinpour, Mehdi; Kardar, Adele

2017-09-01

Rollover crashes are responsible for a notable number of serious injuries and fatalities; hence, they are of great concern to transportation officials and safety researchers. However, only few published studies have analyzed the factors associated with severity outcomes of rollover crashes. This research has two objectives. The first objective is to investigate the effects of various factors, of which some have been rarely reported in the existing studies, on the injury severities of single-vehicle (SV) rollover crashes based on six-year crash data collected on the Malaysian federal roads. A random-effects generalized ordered probit (REGOP) model is employed in this study to analyze injury severity patterns caused by rollover crashes. The second objective is to examine the performance of the proposed approach, REGOP, for modeling rollover injury severity outcomes. To this end, a mixed logit (MXL) model is also fitted in this study because of its popularity in injury severity modeling. Regarding the effects of the explanatory variables on the injury severity of rollover crashes, the results reveal that factors including dark without supplemental lighting, rainy weather condition, light truck vehicles (e.g., sport utility vehicles, vans), heavy vehicles (e.g., bus, truck), improper overtaking, vehicle age, traffic volume and composition, number of travel lanes, speed limit, undulating terrain, presence of central median, and unsafe roadside conditions are positively associated with more severe SV rollover crashes. On the other hand, unpaved shoulder width, area type, driver occupation, and number of access points are found as the significant variables decreasing the probability of being killed or severely injured (i.e., KSI) in rollover crashes. Land use and side friction are significant and positively associated only with slight injury category. These findings provide valuable insights into the causes and factors affecting the injury severity patterns of rollover crashes, and thus can help develop effective countermeasures to reduce the severity of rollover crashes. The model comparison results show that the REGOP model is found to outperform the MXL model in terms of goodness-of-fit measures, and also is significantly superior to other extensions of ordered probit models, including generalized ordered probit and random-effects ordered probit (REOP) models. As a result, this research introduces REGOP as a promising tool for future research focusing on crash injury severity. Copyright © 2017 Elsevier Ltd. All rights reserved.

The impact of federal bioterrorism funding programs on local health department preparedness activities.

PubMed

Avery, George H; Zabriskie-Timmerman, Jennifer

2009-06-01

Using the 2005 National Association of County and City Health Officers Profile of Local Health Departments data set, bivariate probit and Heckman selection models were used to test the hypothesis that the level of federal funding received for bioterrorism preparedness is related to the preparedness activities undertaken by local health departments. Overall budget, leadership, and crisis experience are found to be the most important determinants of local preparedness activity, but Centers for Disease Control and Prevention preparedness funding plays a mediating role by building capacity through the hiring of one key leadership position, the emergency preparedness coordinator. Additional research is needed to determine the potential impact of these funds on other aspects of the local public health system, such as the scope of services delivered, to determine secondary effects of the program.

Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care.

PubMed

Farbmacher, Helmut; Ihle, Peter; Schubert, Ingrid; Winter, Joachim; Wuppermann, Amelie

2017-10-01

Nonlinear price schedules generally have heterogeneous effects on health-care demand. We develop and apply a finite mixture bivariate probit model to analyze whether there are heterogeneous reactions to the introduction of a nonlinear price schedule in the German statutory health insurance system. In administrative insurance claims data from the largest German health insurance plan, we find that some individuals strongly react to the new price schedule while a second group of individuals does not react. Post-estimation analyses reveal that the group of the individuals who do not react to the reform includes the relatively sick. These results are in line with forward-looking behavior: Individuals who are already sick expect that they will hit the kink in the price schedule and thus are less sensitive to the co-payment. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Acceptability of GM foods among Pakistani consumers.

PubMed

Ali, Akhter; Rahut, Dil Bahadur; Imtiaz, Muhammad

2016-04-02

In Pakistan majority of the consumers do not have information about genetically modified (GM) foods. In developing countries particularly in Pakistan few studies have focused on consumers' acceptability about GM foods. Using comprehensive primary dataset collected from 320 consumers in 2013 from Pakistan, this study analyzes the determinants of consumers' acceptability of GM foods. The data was analyzed by employing the bivariate probit model and censored least absolute deviation (CLAD) models. The empirical results indicated that urban consumers are more aware of GM foods compared to rural consumers. The acceptance of GM foods was more among females' consumers as compared to male consumers. In addition, the older consumers were more willing to accept GM food compared to young consumers. The acceptability of GM foods was also higher among wealthier households. Low price is the key factor leading to the acceptability of GM foods. The acceptability of the GM foods also reduces the risks among Pakistani consumers.

Acceptability of GM foods among Pakistani consumers

PubMed Central

Ali, Akhter; Rahut, Dil Bahadur; Imtiaz, Muhammad

2016-01-01

ABSTRACT In Pakistan majority of the consumers do not have information about genetically modified (GM) foods. In developing countries particularly in Pakistan few studies have focused on consumers' acceptability about GM foods. Using comprehensive primary dataset collected from 320 consumers in 2013 from Pakistan, this study analyzes the determinants of consumers' acceptability of GM foods. The data was analyzed by employing the bivariate probit model and censored least absolute deviation (CLAD) models. The empirical results indicated that urban consumers are more aware of GM foods compared to rural consumers. The acceptance of GM foods was more among females' consumers as compared to male consumers. In addition, the older consumers were more willing to accept GM food compared to young consumers. The acceptability of GM foods was also higher among wealthier households. Low price is the key factor leading to the acceptability of GM foods. The acceptability of the GM foods also reduces the risks among Pakistani consumers. PMID:27494790

Effect of Prior Health-Related Employment on the Registered Nurse Workforce Supply.

PubMed

Yoo, Byung-kwan; Lin, Tzu-chun; Kim, Minchul; Sasaki, Tomoko; Spetz, Joanne

2016-01-01

Registered nurses (RN) who held prior health-related employment in occupations other than licensed practical or vocational nursing (LPN/LVN) are reported to have increased rapidly in the past decades. Researchers examined whether prior health-related employment affects RN workforce supply. A cross-sectional bivariate probit model using the 2008 National Sample Survey of Registered Nurses was esti- mated. Prior health-related employment in relatively lower-wage occupations, such as allied health, clerk, or nursing aide, was positively associated with working s an RN. ~>Prior health-related employ- ment in relatively higher-wage categories, such as a health care manager or LPN/LVN, was positively associated with working full-time as an RN. Policy implications are to promote an expanded career ladder program and a nursing school admission policy that targets non-RN health care workers with an interest in becoming RNs.

Exploring the link between ambulatory care and avoidable hospitalizations at the Veteran Health Administration.

PubMed

Pracht, Etienne E; Bass, Elizabeth

2011-01-01

This paper explores the link between utilization of ambulatory care and the likelihood of rehospitalization for an avoidable reason in veterans served by the Veteran Health Administration (VA). The analysis used administrative data containing healthcare utilization and patient characteristics stored at the national VA data warehouse, the Corporate Franchise Data Center. The study sample consisted of 284 veterans residing in Florida who had been hospitalized at least once for an avoidable reason. A bivariate probit model with instrumental variables was used to estimate the probability of rehospitalization. Veterans who had at least 1 ambulatory care visit per month experienced a significant reduction in the probability of rehospitalization for the same avoidable hospitalization condition. The findings suggest that ambulatory care can serve as an important substitute for more expensive hospitalization for the conditions characterized as avoidable. © 2011 National Association for Healthcare Quality.

Genomic-Enabled Prediction of Ordinal Data with Bayesian Logistic Ordinal Regression.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Burgueño, Juan; Eskridge, Kent

2015-08-18

Most genomic-enabled prediction models developed so far assume that the response variable is continuous and normally distributed. The exception is the probit model, developed for ordered categorical phenotypes. In statistical applications, because of the easy implementation of the Bayesian probit ordinal regression (BPOR) model, Bayesian logistic ordinal regression (BLOR) is implemented rarely in the context of genomic-enabled prediction [sample size (n) is much smaller than the number of parameters (p)]. For this reason, in this paper we propose a BLOR model using the Pólya-Gamma data augmentation approach that produces a Gibbs sampler with similar full conditional distributions of the BPOR model and with the advantage that the BPOR model is a particular case of the BLOR model. We evaluated the proposed model by using simulation and two real data sets. Results indicate that our BLOR model is a good alternative for analyzing ordinal data in the context of genomic-enabled prediction with the probit or logit link. Copyright © 2015 Montesinos-López et al.

Factors Influencing the Incidence of Obesity in Australia: A Generalized Ordered Probit Model.

PubMed

Avsar, Gulay; Ham, Roger; Tannous, W Kathy

2017-02-10

The increasing health costs of and the risks factors associated with obesity are well documented. From this perspective, it is important that the propensity of individuals towards obesity is analyzed. This paper uses longitudinal data from the Household Income and Labour Dynamics in Australia (HILDA) Survey for 2005 to 2010 to model those variables which condition the probability of being obese. The model estimated is a random effects generalized ordered probit, which exploits two sources of heterogeneity; the individual heterogeneity of panel data models and heterogeneity across body mass index (BMI) categories. The latter is associated with non-parallel thresholds in the generalized ordered model, where the thresholds are functions of the conditioning variables, which comprise economic, social, and demographic and lifestyle variables. To control for potential predisposition to obesity, personality traits augment the empirical model. The results support the view that the probability of obesity is significantly determined by the conditioning variables. Particularly, personality is found to be important and these outcomes reinforce other work examining personality and obesity.

Grades as Information

ERIC Educational Resources Information Center

Grant, Darren

2007-01-01

We determine how much observed student performance in microeconomics principles can be attributed, inferentially, to three kinds of student academic "productivity," the instructor, demographics, and unmeasurables. The empirical approach utilizes an ordered probit model that relates student performance in micro to grades in prior…

Firm-Related Training Tracks: A Random Effects Ordered Probit Model

ERIC Educational Resources Information Center

Groot, Wim; van den Brink, Henriette Maassen

2003-01-01

A random effects ordered response model of training is estimated to analyze the existence of training tracks and time varying coefficients in training frequency. Two waves of a Dutch panel survey of workers are used covering the period 1992-1996. The amount of training received by workers increased during the period 1994-1996 compared to…

BIVARIATE MODELLING OF CLUSTERED CONTINUOUS AND ORDERED CATEGORICAL OUTCOMES. (R824757)

EPA Science Inventory

Simultaneous observation of continuous and ordered categorical outcomes for each subject is common in biomedical research but multivariate analysis of the data is complicated by the multiple data types. Here we construct a model for the joint distribution of bivariate continuous ...

The Effect of Free Adult Preventive Care Services on Subsequent Utilization of Inpatient Services in Taiwan.

PubMed

Tian, Wei-Hua

2016-07-01

The objective of this article is to investigate the relationship between the utilization of free adult preventive care services and subsequent utilization of inpatient services among elderly people under the National Health Insurance program in Taiwan. The study used secondary data from the 2005 Taiwan National Health Interview Survey and claim data from the 2006 Taiwan National Health Insurance Research Database for the elderly aged 65 or over. A bivariate probit model was used to avoid the possible endogeneity in individuals' utilization of free adult preventive care and inpatient services. This study finds that, when individuals had utilized the preventive care services in 2005, the probability that they utilized inpatient services in 2006 was significantly reduced by 13.89%. The findings of this study may provide a good reference for policy makers to guide the efficient allocation of medical resources through the continuous promotion of free adult preventive care services under the National Health Insurance program. © Australian Council for Educational Research 2016.

HIV Testing Among Young People Aged 16-24 in South Africa: Impact of Mass Media Communication Programs.

PubMed

Do, Mai; Figueroa, Maria Elena; Lawrence Kincaid, D

2016-09-01

Knowing one's serostatus is critical in the HIV prevention, care and treatment continuum. This study examines the impact of communication programs on HIV testing in South Africa. Data came from 2204 young men and women aged 16-24 who reported to be sexually active in a population based survey. Structural equation modeling was used to test the directions and causal pathways between communication program exposure, HIV testing discussion, and having a test in the last 12 months. Bivariate and multivariate probit regressions provided evidence of exogeneity of communication exposure and the two HIV-related outcomes. One in three sampled individuals had been tested in the last 12 months. Communication program exposure only had an indirect effect on getting tested by encouraging young people to talk about testing. The study suggests that communication programs may create an environment that supports open HIV-related discussions and may have a long-term impact on behavior change.

Implications of Middle School Behavior Problems for High School Graduation and Employment Outcomes of Young Adults: Estimation of a Recursive Model.

PubMed

Karakus, Mustafa C; Salkever, David S; Slade, Eric P; Ialongo, Nicholas; Stuart, Elizabeth

2012-01-01

The potentially serious adverse impacts of behavior problems during adolescence on employment outcomes in adulthood provide a key economic rationale for early intervention programs. However, the extent to which lower educational attainment accounts for the total impact of adolescent behavior problems on later employment remains unclear As an initial step in exploring this issue, we specify and estimate a recursive bivariate probit model that 1) relates middle school behavior problems to high school graduation and 2) models later employment in young adulthood as a function of these behavior problems and of high school graduation. Our model thus allows for both a direct effect of behavior problems on later employment as well as an indirect effect that operates via graduation from high school. Our empirical results, based on analysis of data from the NELS, suggest that the direct effects of externalizing behavior problems on later employment are not significant but that these problems have important indirect effects operating through high school graduation.

Does cyberbullying impact youth suicidal behaviors?

PubMed

Nikolaou, Dimitrios

2017-12-01

Even though several youth fatal suicides have been linked with school victimization, there is lack of evidence on whether cyberbullying victimization causes students to adopt suicidal behaviors. To investigate this issue, I use exogenous state-year variation in cyberbullying laws and information on high school students from the Youth Risk Behavioral Survey within a bivariate probit framework, and complement these estimates with matching techniques. I find that cyberbullying has a strong impact on all suicidal behaviors: it increases suicidal thoughts by 14.5 percentage points and suicide attempts by 8.7 percentage points. Even if the focus is on statewide fatal suicide rates, cyberbullying still leads to significant increases in suicide mortality, with these effects being stronger for men than for women. Since cyberbullying laws have an effect on limiting cyberbullying, investing in cyberbullying-preventing strategies can improve individual health by decreasing suicide attempts, and increase the aggregate health stock by decreasing suicide rates. Copyright © 2017 Elsevier B.V. All rights reserved.

The Effect of Leisure-Time Physical Activity on Obesity, Diabetes, High BP and Heart Disease Among Canadians: Evidence from 2000/2001 to 2005/2006.

PubMed

Sarma, Sisira; Devlin, Rose Anne; Gilliland, Jason; Campbell, M Karen; Zaric, Gregory S

2015-12-01

Although studies have looked at the effect of physical activity on obesity and other health outcomes, the causal nature of this relationship remains unclear. We fill this gap by investigating the impact of leisure-time physical activity (LTPA) and work-related physical activity (WRPA) on obesity and chronic conditions in Canadians aged 18-75 using instrumental variable and recursive bivariate probit approaches. Average local temperatures surrounding the respondents' interview month are used as a novel instrument to help identify the causal relationship between LTPA and health outcomes. We find that an active level of LTPA (i.e., walking ≥1 h/day) reduces the probability of obesity by five percentage points, which increases to 11 percentage points if also combined with some WRPA. WRPA exhibits a negative effect on the probability of obesity and chronic conditions. Copyright © 2014 John Wiley & Sons, Ltd.

Determinants of ambulatory treatment mode for mental illness.

PubMed

Freiman, M P; Zuvekas, S H

2000-07-01

We estimate a reduced-form bivariate probit model to analyse jointly the choice of ambulatory treatment from the specialty mental health sector and/or the use of psychotropic drugs for a nationally representative sample of US household residents. We find significant differences in treatment choice by education, gender, race and ethnicity, while controlling for several aspects of self-reported mental health and treatment attitudes. For example, while women are more likely than men to use the specialty mental health sector and more likely to take psychotropic medications, this difference between men and women is much greater for psychotropic medications. The estimated differences may reflect patient preferences in a manner traditionally assumed when interpreting these coefficients in such equations, but we discuss how they may also reflect biases and misperceptions on the parts of patients and providers. We also discuss how our results relate to some findings and policies in the general health care sector. Copyright 2000 John Wiley & Sons, Ltd.

Price, tax and tobacco product substitution in Zambia.

PubMed

Stoklosa, Michal; Goma, Fastone; Nargis, Nigar; Drope, Jeffrey; Chelwa, Grieve; Chisha, Zunda; Fong, Geoffrey T

2018-03-24

In Zambia, the number of cigarette users is growing, and the lack of strong tax policies is likely an important cause. When adjusted for inflation, levels of tobacco tax have not changed since 2007. Moreover, roll-your-own (RYO) tobacco, a less-costly alternative to factory-made (FM) cigarettes, is highly prevalent. We modelled the probability of FM and RYO cigarette smoking using individual-level data obtained from the 2012 and 2014 waves of the International Tobacco Control (ITC) Zambia Survey. We used two estimation methods: the standard estimation method involving separate random effects probit models and a method involving a system of equations (incorporating bivariate seemingly unrelated random effects probit) to estimate price elasticities of FM and RYO cigarettes and their cross-price elasticities. The estimated price elasticities of smoking prevalence are -0.20 and -0.03 for FM and RYO cigarettes, respectively. FM and RYO are substitutes; that is, when the price of one of the products goes up, some smokers switch to the other product. The effects are stronger for substitution from FM to RYO than vice versa. This study affirms that increasing cigarette tax with corresponding price increases could significantly reduce cigarette use in Zambia. Furthermore, reducing between-product price differences would reduce substitution from FM to RYO. Since RYO use is associated with lower socioeconomic status, efforts to decrease RYO use, including through tax/price approaches and cessation assistance, would decrease health inequalities in Zambian society and reduce the negative economic consequences of tobacco use experienced by the poor. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

How Much Math Do Students Need to Succeed in Business and Economics Statistics? An Ordered Probit Analysis

ERIC Educational Resources Information Center

Green, Jeffrey J.; Stone, Courtenay C.; Zegeye, Abera; Charles, Thomas A.

2009-01-01

Because statistical analysis requires the ability to use mathematics, students typically are required to take one or more prerequisite math courses prior to enrolling in the business statistics course. Despite these math prerequisites, however, many students find it difficult to learn business statistics. In this study, we use an ordered probit…

Tolerance of ciliated protozoan Paramecium bursaria (Protozoa, Ciliophora) to ammonia and nitrites

NASA Astrophysics Data System (ADS)

Xu, Henglong; Song, Weibo; Lu, Lu; Alan, Warren

2005-09-01

The tolerance to ammonia and nitrites in freshwater ciliate Paramecium bursaria was measured in a conventional open system. The ciliate was exposed to different concentrations of ammonia and nitrites for 2h and 12h in order to determine the lethal concentrations. Linear regression analysis revealed that the 2h-LC50 value for ammonia was 95.94 mg/L and for nitrite 27.35 mg/L using probit scale method (with 95% confidence intervals). There was a linear correlation between the mortality probit scale and logarithmic concentration of ammonia which fit by a regression equation y=7.32 x 9.51 ( R 2=0.98; y, mortality probit scale; x, logarithmic concentration of ammonia), by which 2 h-LC50 value for ammonia was found to be 95.50 mg/L. A linear correlation between mortality probit scales and logarithmic concentration of nitrite is also followed the regression equation y=2.86 x+0.89 ( R 2=0.95; y, mortality probit scale; x, logarithmic concentration of nitrite). The regression analysis of toxicity curves showed that the linear correlation between exposed time of ammonia-N LC50 value and ammonia-N LC50 value followed the regression equation y=2 862.85 e -0.08 x ( R 2=0.95; y, duration of exposure to LC50 value; x, LC50 value), and that between exposed time of nitrite-N LC50 value and nitrite-N LC50 value followed the regression equation y=127.15 e -0.13 x ( R 2=0.91; y, exposed time of LC50 value; x, LC50 value). The results demonstrate that the tolerance to ammonia in P. bursaria is considerably higher than that of the larvae or juveniles of some metozoa, e.g. cultured prawns and oysters. In addition, ciliates, as bacterial predators, are likely to play a positive role in maintaining and improving water quality in aquatic environments with high-level ammonium, such as sewage treatment systems.

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

The effect of fatigue driving on injury severity considering the endogeneity.

PubMed

Li, Yanyan; Yamamoto, Toshiyuki; Zhang, Guangnan

2018-02-01

Fatigue driving is one of the most risky driving-related behaviors and represented a significant social and economic cost to the community. Several studies have already examined the relationship between fatigue driving behavior and traffic injury severity from different aspects. However, fatigue driving and injury severity in traffic crash may share some common influential factors. Ignoring the impact of these common factors will lead to endogeneity problem and result in biased parameter estimation. Based on 38,564 crash records during 2006-2011 in Guangdong province, China, we apply a bivariate endogenous binary-ordered probit model to examine the relationship between fatigue driving and injury severity considering endogeneity of fatigue driving. We also explore the difference of influential factors between commercial and non-commercial vehicle drivers. This study identifies several common observed influential factors of fatigue driving propensity and fatal injury propensity and reveals a substantial and significant negative correlation of unobserved factors between them. The influence of fatigue driving on injury severity is significantly underestimated if the endogeneity of fatigue driving on fatal injury propensity is ignored. Factors such as vehicle insurance and road types not only affect fatal injury propensity, but also fatigue driving propensity. The findings in this study can help better understand how those factors affect fatigue driving and injury severity, and contributes to more efficient policy for preventing the harmfulness of fatigue-related crashes. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

The Earnings Impact of Training Duration in a Developing Country. An Ordered Probit Selection Model of Colombia's "Servicio Nacional de Aprendizaje" (SENA).

ERIC Educational Resources Information Center

Jimenez, Emmanuel; Kugler, Bernardo

1987-01-01

Estimates the earnings impact of an extensive inservice training program in the developing world, Colombia's Servicio Nacional de Aprendizaje (SENA), through a comparison of nongraduates' and graduates' earnings profiles. (JOW)

POLO: a user's guide to Probit Or LOgit analysis.

Treesearch

Jacqueline L. Robertson; Robert M. Russell; N.E. Savin

1980-01-01

This user's guide provides detailed instructions for the use of POLO (Probit Or LOgit), a computer program for the analysis of quantal response data such as that obtained from insecticide bioassays by the techniques of probit or logit analysis. Dosage-response lines may be compared for parallelism or...

Reducing fatalities and severe injuries on Florida's high-speed multi-lane arterial corridors : part II, analysis of the crash level data, final report, April 2009

DOT National Transportation Integrated Search

2009-04-28

This report presents the analysis conducted to identify the factors that contribute to severe and fatal crash occurrence on multilane corridors. The authors preliminary investigation using simultaneous ordered probit model provided enough evidence...

Modeling willingness to pay for land conservation easements: treatment of zero and protest bids and application and policy implications

Treesearch

Seong-Hoon Cho; Steven T. Yen; J. Michael Bowker; David H. Newman

2008-01-01

This study compares an ordered probit model and a Tobit model with selection to take into account both true zero and protest zero bids while estimating the willingness to pay (WTP) for conservation easements in Macon County, NC. By comparing the two models, the ordered/Unordered selection issue of the protest responses is analyzed to demonstrate how the treatment of...

A Bayesian Approach for Nonlinear Structural Equation Models with Dichotomous Variables Using Logit and Probit Links

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan; Cai, Jing-Heng

2010-01-01

Analysis of ordered binary and unordered binary data has received considerable attention in social and psychological research. This article introduces a Bayesian approach, which has several nice features in practical applications, for analyzing nonlinear structural equation models with dichotomous data. We demonstrate how to use the software…

Competencies for Young European Higher Education Graduates: Labor Market Mismatches and Their Payoffs

ERIC Educational Resources Information Center

Garcia-Aracil, Adela; Van der Velden, Rolf

2008-01-01

Labor market rewards based on competencies are analyzed using a sample of young European higher education (HE) graduates. Estimates of monetary rewards are obtained from conventional earnings regressions, while estimates total rewards are based on job satisfaction and derived through ordered probit regressions. Results for income show that jobs…

Conjoint analysis of nature tourism values in Bahia, Brazil

Treesearch

Thomas Holmes; Chris Zinkhan; Keith Alger; D. Evan Mercer

1996-01-01

This paper uses conjoint analysis to estimate the value of nature tourism attributes in a threatened forest ecosystem in northeastern Brazil. Computerized interviews were conducted using a paired comparison design. An ordinal interpretation of the rating scale was used and marginal utilities were estimated using ordered probit. The empirical results showed that the...

The Richer, the Happier? An Empirical Investigation in Selected European Countries

ERIC Educational Resources Information Center

Seghieri, Chiara; Desantis, Gustavo; Tanturri, Maria Letizia

2006-01-01

This study analyses the relationship between subjective and objective measures of well-being in selected European countries using the data of the European Community Household Panel (ECHP). In the first part of the paper, we develop a random-effect ordered probit model, separately for each country, relating the subjective measure of income…

The Australian electricity market's pre-dispatch process: Some observations on its efficiency using ordered probit model

NASA Astrophysics Data System (ADS)

Zainudin, Wan Nur Rahini Aznie; Becker, Ralf; Clements, Adam

2015-12-01

Many market participants in Australia Electricity Market had cast doubts on whether the pre-dispatch process in the electricity market is able to give them good and timely quantity and price information. In a study by [11], they observed a significant bias (mainly indicating that the pre-dispatch process tends to underestimate spot price outcomes), a seasonality features of the bias across seasons and/or trading periods and changes in bias across the years in our sample period (1999 to 2007). In a formal setting of an ordered probit model we establish that there are some exogenous variables that are able to explain increased probabilities of over- or under-predictions of the spot price. It transpires that meteorological data, expected pre-dispatch prices and information on past over- and under-predictions contribute significantly to explaining variation in the probabilities for over- and under-predictions. The results allow us to conjecture that some of the bids and re-bids provided by electricity generators are not made in good faith.

Determining the Relationship Between Moral Waivers and Marine Corps Unsuitability Attrition

DTIC Science & Technology

2008-03-01

observed characteristics. However, econometric research indicates that the magnitude of interaction effects estimated via probit or logit models may...1997 to 2005. Multivariate probit models were used to analyze the effects of moral waivers on unsatisfactory service separations. 15. NUMBER OF...files from fiscal years 1997 to 2005. Multivariate probit models were used to analyze the effects of moral waivers on unsatisfactory service

Implications of Middle School Behavior Problems for High School Graduation and Employment Outcomes of Young Adults: Estimation of a Recursive Model

PubMed Central

Karakus, Mustafa C.; Salkever, David S.; Slade, Eric P.; Ialongo, Nicholas; Stuart, Elizabeth

2013-01-01

The potentially serious adverse impacts of behavior problems during adolescence on employment outcomes in adulthood provide a key economic rationale for early intervention programs. However, the extent to which lower educational attainment accounts for the total impact of adolescent behavior problems on later employment remains unclear As an initial step in exploring this issue, we specify and estimate a recursive bivariate probit model that 1) relates middle school behavior problems to high school graduation and 2) models later employment in young adulthood as a function of these behavior problems and of high school graduation. Our model thus allows for both a direct effect of behavior problems on later employment as well as an indirect effect that operates via graduation from high school. Our empirical results, based on analysis of data from the NELS, suggest that the direct effects of externalizing behavior problems on later employment are not significant but that these problems have important indirect effects operating through high school graduation. PMID:23576834

Global Obesity Study on Drivers for Weight Reduction Strategies

PubMed Central

Grebitus, Carola; Hartmann, Monika; Reynolds, Nikolai

2015-01-01

Objective To assess factors determining the reaction of individuals to the threats of overweight and obesity and to examine the interdependencies between weight-reducing strategies. Methods Cross-country survey covering 19 countries and 13,155 interviews. Data were analysed using a bivariate probit model that allows simultaneously analysing two weight-reducing strategies. Results Results show that weight-reducing strategies chosen are not independent from each other. Findings also reveal that different strategies are chosen by different population segments. Women are more likely to change their dietary patterns and less likely to become physically active after surpassing a weight threshold. In addition, the probability of a dietary change in case of overweight differs considerably between countries. The study also reveals that attitudes are an important factor for the strategy choice. Conclusions It is vital for public health policies to understand determinants of citizens’ engagement in weight reduction strategies once a certain threshold is reached. Thus, results can support the design of public health campaigns and programmes that aim to change community or national health behaviour trends taking into account, e.g., national differences. PMID:25765165

Self-injury, suicide ideation, and sexual orientation: differences in causes and correlates among high school students.

PubMed

DeCamp, Whitney; Bakken, Nicholas W

2016-01-01

Research has suggested that sexual minority youth are more likely to experience a number of behavioral and health-related risk factors due to their exposure to negative attitudes and beliefs about sexual minorities. Few studies, however, have examined the prevalence of non-suicidal self-injury (NSSI) among sexual minority youth. With self-cutting and suicidal ideation common in middle and high schools, understanding the antecedents and correlates of such behavior may help identify troubled students and initiate preventative measures. Bivariate probit regression analyses are performed using data from 7,326 high school students collected via the Delaware Youth Risk Behavior Survey. Results indicate that bullying victimization, fighting, substance use, sexual behavior, depression, and unhealthy dieting behaviors were generally associated with NSSI and suicidal ideation. Some effects--including those from sexual activity, substance use, and unhealthy dieting behaviors--significantly differed based on gender and orientation. Risk factors for suicide and NSSI vary by gender and orientation. Both prevention/intervention specialists and researchers should consider the intersection of these risk factors with sexual orientation in their efforts. © 2016 KUMS, All rights reserved.

Changes in the demand for private medical insurance following a shift in tax incentives.

PubMed

Rodríguez, Marisol; Stoyanova, Alexandrina

2008-02-01

The 1998 Spanish reform of the Personal Income Tax eliminated the 15% deduction for private medical expenditures including payments on private health insurance (PHI) policies. To avoid an undesired increase in the demand for publicly funded health care, tax incentives to buy PHI were not completely removed but basically shifted from individual to group employer-paid policies. In a unique fiscal experiment, at the same time that the tax relief for individually purchased policies was abolished, the government provided for tax allowances on policies taken out through employment. Using a bivariate probit model on data from National Health Surveys, we estimate the impact of said reform on the demand for PHI and the changes occurred within it. Our findings indicate that the total probability of buying PHI was not significantly affected by the reform. Indeed, the fall in the demand for individual policies (by 10% between 1997 and 2001) was offset by an increase in the demand for group employer-paid ones. We also briefly discuss the welfare effects on the state budget, the industry and society at large.

Ethnic variations in immigrant poverty exit and female employment: the missing link.

PubMed

Kaida, Lisa

2015-04-01

Despite widespread interest in poverty among recent immigrants and female immigrant employment, research on the link between the two is limited. This study evaluates the effect of recently arrived immigrant women's employment on the exit from family poverty and considers the implications for ethnic differences in poverty exit. It uses the bivariate probit model and the Fairlie decomposition technique to analyze data from the Longitudinal Survey of Immigrants to Canada (LSIC), a nationally representative survey of immigrants arriving in Canada, 2000-2001. Results show that the employment of recently arrived immigrant women makes a notable contribution to lifting families out of poverty. Moreover, the wide ethnic variations in the probability of exit from poverty between European and non-European groups are partially explained by the lower employment rates among non-European women. The results suggest that the equal earner/female breadwinner model applies to low-income recent immigrant families in general, but the male breadwinner model explains the low probability of poverty exit among select non-European groups whose female employment rates are notably low.

Investigating the poverty-obesity paradox in Europe.

PubMed

Salmasi, Luca; Celidoni, Martina

2017-08-01

This paper investigates the effect of income- and wealth-based poverty on the probability of being obese for the elderly in Europe by analysing data drawn from the Survey of Health, Ageing and Retirement (SHARE) and the English Longitudinal Study of Ageing (ELSA). We use early-life economic conditions and regional circumstances as instruments for poverty later in life to account for endogeneity issues. After controlling for a large set of covariates at the individual, household, regional and country level, the results show that poverty significantly increases the probability of being obese and the Body Mass Index (BMI), for men and women. The results show that, accounting for endogeneity with a bivariate probit model, poor individuals are from 10 to 20% points more likely to be obese than non-poor individuals. The effect on BMI ranges from 0.295 points (2.39 kg) to 0.395 points (2.75 kg). These results are robust to a series of checks and suggest that anti-poverty interventions might have positive side effects in terms of reducing food-related health inequalities. Copyright © 2017 Elsevier B.V. All rights reserved.

Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China

PubMed Central

Guo, Yanyong; Zhou, Jibiao; Wu, Yao; Li, Zhibin

2017-01-01

The boom in bike-sharing is receiving growing attention as societies become more aware of the importance of active non-motorized traffic modes. However, the low usage of this transport mode in China raises concerns. The primary objective of this study is to explore factors affecting bike-sharing usage and satisfaction degree of bike-sharing among the bike-sharing user population in China. Data were collected by a questionnaire survey in Ningbo. A bivariate ordered probit (BOP) model was developed to examine simultaneously those factors associated with both bike-sharing usage and satisfaction degree of bike-sharing among users. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results showed that the BOP model can account for commonly shared unobserved characteristics within usage and satisfaction of bike-sharing. The BOP model results showed that the usage of bike-sharing was affected by gender, household bicycle/e-bike ownership, trip model, travel time, bike-sharing stations location, and users’ perception of bike-sharing. The satisfaction degree of bike-sharing was affected by household income, bike-sharing stations location, and users’ perception of bike-sharing. It is also found that bike-sharing usage and satisfaction degree are strongly correlated and positive in direction. The results can enhance our comprehension of the factors that affect usage and satisfaction degree of bike-sharing. Based on the results, some suggestions regarding planning, engineering, and public advocacy were discussed to increase the usage of bike-sharing in Ningbo, China. PMID:28934321

The spatial Probit model-An application to the study of banking crises at the end of the 1990’s

NASA Astrophysics Data System (ADS)

Amaral, Andrea; Abreu, Margarida; Mendes, Victor

2014-12-01

We use a spatial Probit model to study the effect of contagion between banking systems of different countries. Applied to the late 1990s banking crisis in Asia we show that the phenomena of contagion is better seized using a spatial than a traditional Probit model. Unlike the latter, the spatial Probit model allows one to consider the cascade of cross and feedback effects of contagion that result from the outbreak of one initial crisis in one country or system. These contagion effects may result either from business connections between institutions of different countries or from institutional similarities between banking systems.

Cohort profile: The promotion of breastfeeding intervention trial (PROBIT).

PubMed

Patel, Rita; Oken, Emily; Bogdanovich, Natalia; Matush, Lidia; Sevkovskaya, Zinaida; Chalmers, Beverley; Hodnett, Ellen D; Vilchuck, Konstantin; Kramer, Michael S; Martin, Richard M

2014-06-01

The PROmotion of Breastfeeding Intervention Trial (PROBIT) is a multicentre, cluster-randomized controlled trial conducted in the Republic of Belarus, in which the experimental intervention was the promotion of increased breastfeeding duration and exclusivity, modelled on the Baby-friendly hospital initiative. Between June 1996 and December 1997, 17,046 mother-infant pairs were recruited during their postpartum hospital stay from 31 maternity hospitals, of which 16 hospitals and their affiliated polyclinics had been randomly assigned to the arm of PROBIT investigating the promotion of breastfeeding and 15 had been assigned to the control arm, in which breastfeeding practices and policies in effect at the time of randomization was continued. Of the mother-infant pairs originally recruited for the study, 16,492 (96.7%) were followed at regular intervals until the infants were 12 months of age (PROBIT I) for the outcomes of breastfeeding duration and exclusivity; gastrointestinal and respiratory infections; and atopic eczema. Subsequently, 13,889 (81.5%) of the children from these mother-infant pairs were followed-up at age 6.5 years (PROBIT II) for anthropometry, blood pressure (BP), behaviour, dental health, cognitive function, asthma and atopy outcomes, and 13,879 (81.4%) children were followed to the age of 11.5 years (PROBIT III) for anthropometry, body composition, BP, and the measurement of fasted glucose, insulin, adiponectin, insulin-like growth factor-I, and apolipoproteins. The trial registration number for Current Controlled Trials is ISRCTN37687716 and that for ClinicalTrials.gov is NCT01561612. Proposals for collaboration are welcome, and enquires about PROBIT should be made to an executive group of the study steering committee (M.S.K., R.M.M., and E.O.). More information, including information about how to access the trial data, data collection documents, and bibliography, is available at the trial website (http://www.bristol.ac.uk/social-community-medicine/projects/probit/). Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2013; all rights reserved.

What Determines Basic School Attainment in Developing Countries? Evidence from Rural China

ERIC Educational Resources Information Center

Zhao, Meng; Glewwe, Paul

2010-01-01

This paper analyzes recent household survey data from Gansu, a less developed province in Northwest China, to examine school attainment in a poor rural area of China. Censored ordered probit regressions are used to estimate the determinants of years of schooling. Child nutritional status, as measured by height-for-age Z-scores, and household…

The Effect of Response Time on Conjoint Analysis Estimates of Rainforest Protection Values

Treesearch

Thomas Holmes; Keith Alger; Christian Zinkhan; D. Evan Mercer

1998-01-01

This paper reports the first estimutes of willingness to pay (WTP) for rain forest protection in the threatened Atlantic Coastal Forest ecosystem in northeastern Brazil. Conjoint analysis data were collected from Brazilian tourists for recreational bundles with complex prices. An ordered probit model with time-varying parameters and heteroskedastic errors was...

Human Capital Background and the Educational Attainment of Second-Generation Immigrants in France

ERIC Educational Resources Information Center

Dos Santos, Manon Domingues; Wolff, Francois-Charles

2011-01-01

In this paper, we study the impact of parental human capital background on ethnic educational gaps between second-generation immigrants using a large data set conducted in France in 2003. Estimates from censored random effect ordered Probit regressions show that the skills of immigrants explain in the most part, the ethnic educational gap between…

The MDI Method as a Generalization of Logit, Probit and Hendry Analyses in Marketing.

DTIC Science & Technology

1980-04-01

model involves nothing more than fitting a normal distribution function ( Hanushek and Jackson (1977)). For a given value of x, the probit model...preference shifts within the soft drink category. --For applications of probit models relevant for marketing, see Hausman and Wise (1978) and Hanushek and...Marketing Research" JMR XIV, Feb. (1977). Hanushek , E.A., and J.E. Jackson, Statistical Methods for Social Scientists. Academic Press, New York (1977

Investigating the influence of eating habits, body weight and television programme preferences on television viewing time and domestic computer usage.

PubMed

Raptou, Elena; Papastefanou, Georgios; Mattas, Konstadinos

2017-01-01

The present study explored the influence of eating habits, body weight and television programme preference on television viewing time and domestic computer usage, after adjusting for sociodemographic characteristics and home media environment indicators. In addition, potential substitution or complementarity in screen time was investigated. Individual level data were collected via questionnaires that were administered to a random sample of 2,946 Germans. The econometric analysis employed a seemingly unrelated bivariate ordered probit model to conjointly estimate television viewing time and time engaged in domestic computer usage. Television viewing and domestic computer usage represent two independent behaviours in both genders and across all age groups. Dietary habits have a significant impact on television watching with less healthy food choices associated with increasing television viewing time. Body weight is found to be positively correlated with television screen time in both men and women, and overweight individuals have a higher propensity for heavy television viewing. Similar results were obtained for age groups where an increasing body mass index (BMI) in adults over 24 years old is more likely to be positively associated with a higher duration of television watching. With respect to dietary habits of domestic computer users, participants aged over 24 years of both genders seem to adopt more healthy dietary patterns. A downward trend in the BMI of domestic computer users was observed in women and adults aged 25-60 years. On the contrary, young domestic computer users 18-24 years old have a higher body weight than non-users. Television programme preferences also affect television screen time with clear differences to be observed between genders and across different age groups. In order to reduce total screen time, health interventions should target different types of screen viewing audiences separately.

Determinants of tree quality and lumber value in natural uneven-aged southern pine stands

Treesearch

Jeffrey P. Prestemon; Joseph Buongiorno

2000-01-01

An ordered-probit model was developed to predict tree grade from tree- and stand-level variables, some of which could be changed by management. Applied to uneven-aged mixed loblolly (Pinus taeda L.) - shortleaf pine (Pinus echinata Mill.) stands, the model showed that the grade of pine trees was highly correlated with tree diameter...

Income, family characteristics, and physical violence toward children.

PubMed

Berger, Lawrence M

2005-02-01

This paper discusses the ways in which existing microeconomic theories of partner abuse, intra-family bargaining, and distribution of resources within families may contribute to our current understanding of physical child abuse. The empirical implications of this discussion are then tested on data from the 1985 National Family Violence Survey (NFVS) in order to estimate the effects of income, family characteristics, and state characteristics on physical violence toward children. The sample consists of 2,760 families with children from the NFVS. Probit and ordered probit models are used to explore relationships between income, family characteristics, state characteristics, and physical violence toward children among single-parent and two-parent families. In both single-parent and two-parent families, depression, maternal alcohol consumption, and history of family violence affect children's probabilities of being abused. Additionally, income is significantly related to violence toward children in single-parent families. These results reinforce earlier findings that demographic characteristics, maternal depression, maternal alcohol use, and intra-family patterns of violence may largely contribute to child abuse. This research also suggests that income may play a substantially more important role in regard to parental violence in single-parent families than in two-parent families.

Satisfaction and responsiveness with health-care services in Qatar--evidence from a survey.

PubMed

Ali, Faleh Mohamed Hussain; Nikoloski, Zlatko; Reka, Husein

2015-11-01

Satisfaction and responsiveness with health care are some of the main outcome variables of a health system. Although health outcomes have been studied in countries with different levels of economic development, there is limited information on the health provision/satisfaction/responsiveness nexus in countries where rapid transitions from middle to high-income status have occurred. Using a 2012 survey conducted in Qatar (amongst both Qatari and non-Qatari respondents), we analysed satisfaction and responsiveness of health care. The sample consisted of 4083 respondents. We use logit analysis [as well as robustness checks involving ordered logit, ordered probit, ordinary least squares (OLS) and probit analysis] in order to estimate the determinants of satisfaction and responsiveness. Both, satisfaction and responsiveness rates were high. Gender, nationality and, to some extent, income and age were significant sociodemographic determinants of satisfaction, with non-Qataris and females, having higher levels of satisfaction. Cost, previous experience with the same health provider and provision of medical insurance for a particular health provider were the attributes significantly correlated with general satisfaction. The results are consistent when the analysis is applied to the correlates of responsiveness. Sociodemographic factors explain the satisfaction with quality of health care in the state of Qatar (both from the general population point of view and from the patient point of view). Copyright © 2015. Published by Elsevier Ireland Ltd.

Physical work environment: testing an expanded model of job satisfaction in a sample of registered nurses.

PubMed

Djukic, Maja; Kovner, Christine; Budin, Wendy C; Norman, Robert

2010-01-01

The impact of personal, organizational, and economic factors on nurses' job satisfaction have been studied extensively, but few studies exist in which the effects of physical work environment--including perceptions of architectural, interior design, and ambient features on job satisfaction-are examined. The purpose of this study was to examine the effect of perceived physical work environment on job satisfaction, adjusting for multiple personal, organizational, and economic determinants of job satisfaction. A cross-sectional, predictive design and a Web-based survey instrument were used to collect data from staff registered nurses in a large metropolitan hospital. The survey included 34 questions about multiple job satisfaction determinants, including 18 Likert-type measures with established good validity (comparative fit index = .97, Tucker-Lewis index = .98, root mean square error of approximation = .06) and reliability (r ≥ .70). A response rate of 48.5% resulted in a sample of 362, with 80% power to detect a medium effect of perceived physical environment on job satisfaction. On average, nurses had negative perceptions of physical work environment (M = 2.9, SD = 2.2). Although physical environment was related positively to job satisfaction (r =.256, p = .01) in bivariate analysis, in ordered probit regression, no effect of physical work environment on job satisfaction was found. In future studies, this relationship should be examined in larger and more representative samples of nurses. Qualitative methods should be used to explore how negatively perceived physical work environment impacts nurses. Rebuilding of U.S. hospitals, with a planned investment of $200 billion without considering how physical environment contributes to nurse work outcomes, threatens to exacerbate organizational nurse turnover.

Psychiatrists' judgments about antipsychotic benefit and risk outcomes and formulation in schizophrenia treatment.

PubMed

Markowitz, Michael A; Levitan, Bennett S; Mohamed, Ateesha F; Johnson, F R; Bridges, John F P; Alphs, Larry; Citrome, Leslie

2014-09-01

The objectives were to quantify psychiatrists' judgments of the benefits and risks of antipsychotic treatments of patients with schizophrenia and to evaluate how patient adherence history affects these judgments. Weights assigned by respondents to risks, benefits, and alternative drug formulations in the treatment of schizophrenia were assessed via a Web-based survey by using a discrete-choice experiment. Respondents in the United States and the United Kingdom chose among alternative scenarios characterized by various levels of improvement in positive symptoms, negative symptoms, social functioning, weight gain, extrapyramidal symptoms (EPS), hyperprolactinemia, and hyperglycemia and by formulation. The effect of patient adherence history on respondents' judgments was also assessed. Random-parameters logit and bivariate probit models were estimated. The sample included 394 psychiatrists. Improvement in positive symptoms from "no improvement" to "very much improved" was the most preferred outcome over the range of improvements included and was assigned a relative importance score of 10. Other outcomes, in decreasing order of importance, were improvement in negative symptoms from "no improvement" to "very much improved" (5.2; 95% confidence interval [CI]=4.2-6.2), social functioning from "severe problems" to "mild problems" (4.6, CI=3.8-5.4), no hyperglycemia (1.9, CI=1.5-2.4), <15% weight gain (1.5, CI=.9-2.0), no hyperprolactinemia (1.3, CI=.8-1.6), and no EPS (1.1, CI=.7-1.5). As adherence decreased, formulation became more important than modest efficacy changes and injections were preferred to daily pills (p<.05). Psychiatrists favored treatments that primarily improve positive symptoms. Choice of formulation became more important as likely adherence declined.

Health insurance for the poor: impact on catastrophic and out-of-pocket health expenditures in Mexico

PubMed Central

Galárraga, Omar; Salinas-Rodríguez, Aarón; Sesma-Vázquez, Sergio

2009-01-01

The goal of Seguro Popular (SP) in Mexico was to improve the financial protection of the uninsured population against excessive health expenditures. This paper estimates the impact of SP on catastrophic health expenditures (CHE), as well as out-of-pocket (OOP) health expenditures, from two different sources. First, we use the SP Impact Evaluation Survey (2005–2006), and compare the instrumental variables (IV) results with the experimental benchmark. Then, we use the same IV methods with the National Health and Nutrition Survey (ENSANUT 2006). We estimate naïve models, assuming exogeneity, and contrast them with IV models that take advantage of the specific SP implementation mechanisms for identification. The IV models estimated included two-stage least squares (2SLS), bivariate probit, and two-stage residual inclusion (2SRI) models. Instrumental variables estimates resulted in comparable estimates against the “gold standard.” Instrumental variables estimates indicate a reduction of 54% in catastrophic expenditures at the national level. SP beneficiaries also had lower expenditures on outpatient and medicine expenditures. The selection-corrected protective effect is found not only in the limited experimental dataset, but also at the national level. PMID:19756796

Health insurance for the poor: impact on catastrophic and out-of-pocket health expenditures in Mexico.

PubMed

Galárraga, Omar; Sosa-Rubí, Sandra G; Salinas-Rodríguez, Aarón; Sesma-Vázquez, Sergio

2010-10-01

The goal of Seguro Popular (SP) in Mexico was to improve the financial protection of the uninsured population against excessive health expenditures. This paper estimates the impact of SP on catastrophic health expenditures (CHE), as well as out-of-pocket (OOP) health expenditures, from two different sources. First, we use the SP Impact Evaluation Survey (2005-2006), and compare the instrumental variables (IV) results with the experimental benchmark. Then, we use the same IV methods with the National Health and Nutrition Survey (ENSANUT 2006). We estimate naïve models, assuming exogeneity, and contrast them with IV models that take advantage of the specific SP implementation mechanisms for identification. The IV models estimated included two-stage least squares (2SLS), bivariate probit, and two-stage residual inclusion (2SRI) models. Instrumental variables estimates resulted in comparable estimates against the "gold standard." Instrumental variables estimates indicate a reduction of 54% in catastrophic expenditures at the national level. SP beneficiaries also had lower expenditures on outpatient and medicine expenditures. The selection-corrected protective effect is found not only in the limited experimental dataset, but also at the national level.

Does performance of breast self-exams increase the probability of using mammography: evidence from Malaysia.

PubMed

Dunn, Richard A; Tan, Andrew; Samad, Ismail

2010-01-01

Breast self-examination (BSE) was evaluated to see if it is a significant predictor of mammography. The decisions of females above age 40 in Malaysia to test for breast cancer using BSE and mammography are jointly modeled using a bivariate probit so that unobserved attributes affecting mammography usage are also allowed to affect BSE. Data come from the Malaysia Non-Communicable Disease Surveillance-1, which was collected between September 2005 and February 2006. Having ever performed BSE is positively associated with having ever undergone mammography among Malay (adjusted OR=7.343, CI=2.686, 20.079) and Chinese (adjusted OR=3.466, CI=1.330, 9.031) females after adjusting for household income, education, marital status and residential location. Neither relationship is affected by jointly modelling the decision problem. Although the association is also positive for Indian females when mammography is modelled separately (adjusted OR=5.959, CI=1.546 - 22.970), the relationship is reversed when both decisions are modelled separately. De-emphasizing BSE in Malaysia may reduce mammography screening among a large proportion of the population. Previous work on the issue in developed countries may not apply to nations with limited resources.

The effect of poverty and caregiver education on perceived need and access to health services among children with special health care needs.

PubMed

Porterfield, Shirley L; McBride, Timothy D

2007-02-01

We examined the association between several variables and the use of specialist physician services, developmental therapies, and prescription medications among children with special health care needs (N=38866). We used a bivariate probit model to estimate whether a given child needed specialized services and whether that child accessed those services; we controlled for activity limitations and severity of special needs. Variables included family income, mother's (or other caregiver's) educational level, health insurance coverage, and perceived need for specialized services. We used data from the 2001 National Survey of Children with Special Health Care Needs. Lower-income and less-educated parents were less likely than higher-income and more-educated parents to say their special needs children needed specialized health services. The probability of accessing specialized health services-when needed-increased with both higher family income and insurance coverage. Children with special health care needs have less access to health services because their parents do not recognize the need for those services. An intervention in the form of information at the family level may be an appropriate policy response.

A novel, efficient method for estimating the prevalence of acute malnutrition in resource-constrained and crisis-affected settings: A simulation study.

PubMed

Frison, Severine; Kerac, Marko; Checchi, Francesco; Nicholas, Jennifer

2017-01-01

The assessment of the prevalence of acute malnutrition in children under five is widely used for the detection of emergencies, planning interventions, advocacy, and monitoring and evaluation. This study examined PROBIT Methods which convert parameters (mean and standard deviation (SD)) of a normally distributed variable to a cumulative probability below any cut-off to estimate acute malnutrition in children under five using Middle-Upper Arm Circumference (MUAC). We assessed the performance of: PROBIT Method I, with mean MUAC from the survey sample and MUAC SD from a database of previous surveys; and PROBIT Method II, with mean and SD of MUAC observed in the survey sample. Specifically, we generated sub-samples from 852 survey datasets, simulating 100 surveys for eight sample sizes. Overall the methods were tested on 681 600 simulated surveys. PROBIT methods relying on sample sizes as small as 50 had better performance than the classic method for estimating and classifying the prevalence of acute malnutrition. They had better precision in the estimation of acute malnutrition for all sample sizes and better coverage for smaller sample sizes, while having relatively little bias. They classified situations accurately for a threshold of 5% acute malnutrition. Both PROBIT methods had similar outcomes. PROBIT Methods have a clear advantage in the assessment of acute malnutrition prevalence based on MUAC, compared to the classic method. Their use would require much lower sample sizes, thus enable great time and resource savings and permit timely and/or locally relevant prevalence estimates of acute malnutrition for a swift and well-targeted response.

Probit vs. semi-nonparametric estimation: examining the role of disability on institutional entry for older adults.

PubMed

Sharma, Andy

2017-06-01

The purpose of this study was to showcase an advanced methodological approach to model disability and institutional entry. Both of these are important areas to investigate given the on-going aging of the United States population. By 2020, approximately 15% of the population will be 65 years and older. Many of these older adults will experience disability and require formal care. A probit analysis was employed to determine which disabilities were associated with admission into an institution (i.e. long-term care). Since this framework imposes strong distributional assumptions, misspecification leads to inconsistent estimators. To overcome such a short-coming, this analysis extended the probit framework by employing an advanced semi-nonparamertic maximum likelihood estimation utilizing Hermite polynomial expansions. Specification tests show semi-nonparametric estimation is preferred over probit. In terms of the estimates, semi-nonparametric ratios equal 42 for cognitive difficulty, 64 for independent living, and 111 for self-care disability while probit yields much smaller estimates of 19, 30, and 44, respectively. Public health professionals can use these results to better understand why certain interventions have not shown promise. Equally important, healthcare workers can use this research to evaluate which type of treatment plans may delay institutionalization and improve the quality of life for older adults. Implications for rehabilitation With on-going global aging, understanding the association between disability and institutional entry is important in devising successful rehabilitation interventions. Semi-nonparametric is preferred to probit and shows ambulatory and cognitive impairments present high risk for institutional entry (long-term care). Informal caregiving and home-based care require further examination as forms of rehabilitation/therapy for certain types of disabilities.

Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study.

PubMed

Ghomi, Haniyeh; Bagheri, Morteza; Fu, Liping; Miranda-Moreno, Luis F

2016-11-16

The main objective of this study is to identify the main factors associated with injury severity of vulnerable road users (VRUs) involved in accidents at highway railroad grade crossings (HRGCs) using data mining techniques. This article applies an ordered probit model, association rules, and classification and regression tree (CART) algorithms to the U.S. Federal Railroad Administration's (FRA) HRGC accident database for the period 2007-2013 to identify VRU injury severity factors at HRGCs. The results show that train speed is a key factor influencing injury severity. Further analysis illustrated that the presence of illumination does not reduce the severity of accidents for high-speed trains. In addition, there is a greater propensity toward fatal accidents for elderly road users compared to younger individuals. Interestingly, at night, injury accidents involving female road users are more severe compared to those involving males. The ordered probit model was the primary technique, and CART and association rules act as the supporter and identifier of interactions between variables. All 3 algorithms' results consistently show that the most influential accident factors are train speed, VRU age, and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGCs.

Logit and probit model in toll sensitivity analysis of Solo-Ngawi, Kartasura-Palang Joglo segment based on Willingness to Pay (WTP)

NASA Astrophysics Data System (ADS)

Handayani, Dewi; Cahyaning Putri, Hera; Mahmudah, AMH

2017-12-01

Solo-Ngawi toll road project is part of the mega project of the Trans Java toll road development initiated by the government and is still under construction until now. PT Solo Ngawi Jaya (SNJ) as the Solo-Ngawi toll management company needs to determine the toll fare that is in accordance with the business plan. The determination of appropriate toll rates will affect progress in regional economic sustainability and decrease the traffic congestion. These policy instruments is crucial for achieving environmentally sustainable transport. Therefore, the objective of this research is to find out how the toll fare sensitivity of Solo-Ngawi toll road based on Willingness To Pay (WTP). Primary data was obtained by distributing stated preference questionnaires to four wheeled vehicle users in Kartasura-Palang Joglo artery road segment. Further data obtained will be analysed with logit and probit model. Based on the analysis, it is found that the effect of fare change on the amount of WTP on the binomial logit model is more sensitive than the probit model on the same travel conditions. The range of tariff change against values of WTP on the binomial logit model is 20% greater than the range of values in the probit model . On the other hand, the probability results of the binomial logit model and the binary probit have no significant difference (less than 1%).

Tennis Elbow Diagnosis Using Equivalent Uniform Voltage to Fit the Logistic and the Probit Diseased Probability Models

PubMed Central

Lin, Wei-Chun; Lin, Shu-Yuan; Wu, Li-Fu; Guo, Shih-Sian; Huang, Hsiang-Jui; Chao, Pei-Ju

2015-01-01

To develop the logistic and the probit models to analyse electromyographic (EMG) equivalent uniform voltage- (EUV-) response for the tenderness of tennis elbow. In total, 78 hands from 39 subjects were enrolled. In this study, surface EMG (sEMG) signal is obtained by an innovative device with electrodes over forearm region. The analytical endpoint was defined as Visual Analog Score (VAS) 3+ tenderness of tennis elbow. The logistic and the probit diseased probability (DP) models were established for the VAS score and EMG absolute voltage-time histograms (AVTH). TV50 is the threshold equivalent uniform voltage predicting a 50% risk of disease. Twenty-one out of 78 samples (27%) developed VAS 3+ tenderness of tennis elbow reported by the subject and confirmed by the physician. The fitted DP parameters were TV50 = 153.0 mV (CI: 136.3–169.7 mV), γ 50 = 0.84 (CI: 0.78–0.90) and TV50 = 155.6 mV (CI: 138.9–172.4 mV), m = 0.54 (CI: 0.49–0.59) for logistic and probit models, respectively. When the EUV ≥ 153 mV, the DP of the patient is greater than 50% and vice versa. The logistic and the probit models are valuable tools to predict the DP of VAS 3+ tenderness of tennis elbow. PMID:26380281

The individual tolerance concept is not the sole explanation for the probit dose-effect model

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

Newman, M.C.; McCloskey, J.T.

2000-02-01

Predominant methods for analyzing dose- or concentration-effect data (i.e., probit analysis) are based on the concept of individual tolerance or individual effective dose (IED, the smallest characteristic dose needed to kill an individual). An alternative explanation (stochasticity hypothesis) is that individuals do not have unique tolerances: death results from stochastic processes occurring similarly in all individuals. These opposing hypotheses were tested with two types of experiments. First, time to stupefaction (TTS) was measured for zebra fish (Brachydanio rerio) exposed to benzocaine. The same 40 fish were exposed during five trials to test if the same order for TTS was maintainedmore » among trials. The IED hypothesis was supported with a minor stochastic component being present. Second, eastern mosquitofish (Gambusia holbrooki) were exposed to sublethal or lethal NaCl concentrations until a large portion of the lethally exposed fish died. After sufficient time for recovery, fish sublethally exposed and fish surviving lethal exposure were exposed simultaneously to lethal NaCl concentrations. No statistically significant effect was found of previous exposure on survival time but a large stochastic component to the survival dynamics was obvious. Repetition of this second type of test with pentachlorophenol also provided no support for the IED hypothesis. The authors conclude that neither hypothesis alone was the sole or dominant explanation for the lognormal (probit) model. Determination of the correct explanation (IED or stochastic) or the relative contributions of each is crucial to predicting consequences to populations after repeated or chronic exposures to any particular toxicant.« less

Bayesian multinomial probit modeling of daily windows of susceptibility for maternal PM2.5 exposure and congenital heart defects

EPA Science Inventory

Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregn...

Appropriateness of Probit-9 in development of quarantine treatments for timber and timber commodities

Treesearch

Marcus Schortemeyer; Ken Thomas; Robert A. Haack; Adnan Uzunovic; Kelli Hoover; Jack A. Simpson; Cheryl A. Grgurinovic

2011-01-01

Following the increasing international phasing out of methyl bromide for quarantine purposes, the development of alternative treatments for timber pests becomes imperative. The international accreditation of new quarantine treatments requires verification standards that give confidence in the effectiveness of a treatment. Probit-9 mortality is a standard for treatment...

Experimental and statistical study on fracture boundary of non-irradiated Zircaloy-4 cladding tube under LOCA conditions

NASA Astrophysics Data System (ADS)

Narukawa, Takafumi; Yamaguchi, Akira; Jang, Sunghyon; Amaya, Masaki

2018-02-01

For estimating fracture probability of fuel cladding tube under loss-of-coolant accident conditions of light-water-reactors, laboratory-scale integral thermal shock tests were conducted on non-irradiated Zircaloy-4 cladding tube specimens. Then, the obtained binary data with respect to fracture or non-fracture of the cladding tube specimen were analyzed statistically. A method to obtain the fracture probability curve as a function of equivalent cladding reacted (ECR) was proposed using Bayesian inference for generalized linear models: probit, logit, and log-probit models. Then, model selection was performed in terms of physical characteristics and information criteria, a widely applicable information criterion and a widely applicable Bayesian information criterion. As a result, it was clarified that the log-probit model was the best among the three models to estimate the fracture probability in terms of the degree of prediction accuracy for both next data to be obtained and the true model. Using the log-probit model, it was shown that 20% ECR corresponded to a 5% probability level with a 95% confidence of fracture of the cladding tube specimens.

Numerical analysis of the accuracy of bivariate quantile distributions utilizing copulas compared to the GUM supplement 2 for oil pressure balance uncertainties

NASA Astrophysics Data System (ADS)

Ramnath, Vishal

2017-11-01

In the field of pressure metrology the effective area is Ae = A0 (1 + λP) where A0 is the zero-pressure area and λ is the distortion coefficient and the conventional practise is to construct univariate probability density functions (PDFs) for A0 and λ. As a result analytical generalized non-Gaussian bivariate joint PDFs has not featured prominently in pressure metrology. Recently extended lambda distribution based quantile functions have been successfully utilized for summarizing univariate arbitrary PDF distributions of gas pressure balances. Motivated by this development we investigate the feasibility and utility of extending and applying quantile functions to systems which naturally exhibit bivariate PDFs. Our approach is to utilize the GUM Supplement 1 methodology to solve and generate Monte Carlo based multivariate uncertainty data for an oil based pressure balance laboratory standard that is used to generate known high pressures, and which are in turn cross-floated against another pressure balance transfer standard in order to deduce the transfer standard's respective area. We then numerically analyse the uncertainty data by formulating and constructing an approximate bivariate quantile distribution that directly couples A0 and λ in order to compare and contrast its accuracy to an exact GUM Supplement 2 based uncertainty quantification analysis.

Multiple-Shrinkage Multinomial Probit Models with Applications to Simulating Geographies in Public Use Data.

PubMed

Burgette, Lane F; Reiter, Jerome P

2013-06-01

Multinomial outcomes with many levels can be challenging to model. Information typically accrues slowly with increasing sample size, yet the parameter space expands rapidly with additional covariates. Shrinking all regression parameters towards zero, as often done in models of continuous or binary response variables, is unsatisfactory, since setting parameters equal to zero in multinomial models does not necessarily imply "no effect." We propose an approach to modeling multinomial outcomes with many levels based on a Bayesian multinomial probit (MNP) model and a multiple shrinkage prior distribution for the regression parameters. The prior distribution encourages the MNP regression parameters to shrink toward a number of learned locations, thereby substantially reducing the dimension of the parameter space. Using simulated data, we compare the predictive performance of this model against two other recently-proposed methods for big multinomial models. The results suggest that the fully Bayesian, multiple shrinkage approach can outperform these other methods. We apply the multiple shrinkage MNP to simulating replacement values for areal identifiers, e.g., census tract indicators, in order to protect data confidentiality in public use datasets.

Sexual Risk Behavior in Young Adulthood: Broadening the Scope Beyond Early Sexual Initiation

PubMed Central

Epstein, Marina; Bailey, Jennifer A.; Manhart, Lisa E.; Hill, Karl G.; Hawkins, J. David

2013-01-01

A robust link between early sexual initiation and sexual risk-taking behavior is reported in previous studies. The relationship may not be causal, however, as the effect of common risk factors is often not considered. The current study examined whether early initiation is a key predictor of risky sexual behavior in the 20s and 30s, over and above co-occurring individual and environmental factors. Data were drawn from the Seattle Social Development Project, a longitudinal panel of 808 youth. Early predictors (ages 10–15) and sexual risk-taking (ages 21–24 and 30–33) were assessed prospectively. Early sexual initiation (before age 15) was entered into a series of probit regressions that also included family, neighborhood, peer, and individual risk factors. Although a positive bivariate relation between early sexual initiation and sexual risk-taking was observed at both ages, the link did not persist when co-occurring risk factors were included. Behavioral disinhibition and antisocial peer influences emerged as the strongest predictors of sexual risk over and above early sexual initiation. These results suggest that early sexual initiation must be considered in the context of common antecedents; public health policy aimed at delaying sexual intercourse alone is unlikely to substantially reduce sexual risk behavior in young adulthood. PMID:24423058

Awareness and Adoption of Soil and Water Conservation Technologies in a Developing Country: A Case of Nabajuzi Watershed in Central Uganda

NASA Astrophysics Data System (ADS)

Kagoya, Sarah; Paudel, Krishna P.; Daniel, Nadhomi L.

2018-02-01

Soil and water conservation technologies have been widely available in most parts of Uganda. However, not only has the adoption rate been low but also many farmers seem not to be aware of these technologies. This study aims at identifying the factors that influence awareness and adoption of soil and water conservation technologies in Nabajuzi watershed in central Uganda. A bivariate probit model was used to examine farmers' awareness and adoption of soil and water conservation technologies in the watershed. We use data collected from the interview of 400 households located in the watershed to understand the factors affecting the awareness and adoption of these technologies in the study area. Findings indicate that the likelihood of being aware and adopting the technologies are explained by the age of household head, being a tenant, and number of years of access to farmland. To increase awareness and adoption of technologies in Uganda, policymakers may expedite the process of land titling as farmers may feel secure about landholding and thus adopt these technologies to increase profitability and productivity in the long run. Incentive payments to farmers residing in the vulnerable region to adopt these considered technologies may help to alleviate soil deterioration problems in the affected area.

Association between Clean Indoor Air Laws and Voluntary Smokefree Rules in Homes and Cars

PubMed Central

Cheng, Kai-Wen; Okechukwu, Cassandra A.; McMillen, Robert; Glantz, Stanton A.

2013-01-01

Objectives This study examines the influence that smokefree workplaces, restaurants, and bars on the adoption of smokefree rules in homes and cars and whether the adoptions of home and car smokefree rule are associated. Methods Bivariate probit models were used to jointly estimate the likelihood of living in a smokefree home and having a smokefree car as a function of law coverage and other variables. Household data are from the nationally representative Social Climate Survey of Tobacco Control 2001, 2002, and 2004–2009; clean indoor air law data comes from the American Nonsmokers’ Rights Foundation Tobacco Control Laws Database. Results Both “full coverage” and “partial coverage” smokefree legislations are associated with an increased likelihood of having voluntary home and car smokefree rules compared with “no coverage”. The association between “full coverage” and smokefree rule in homes and cars is 5% and 4%, respectively, and the association between “partial coverage” and smokefree rule in homes and cars is 3% and 4%, respectively. There is a positive association between the adoption of home and car smokefree rules. Conclusions Clean indoor air laws provide the additional benefit of encouraging voluntary adoption of smokefree rules in homes and cars. PMID:24114562

Awareness and Adoption of Soil and Water Conservation Technologies in a Developing Country: A Case of Nabajuzi Watershed in Central Uganda.

PubMed

Kagoya, Sarah; Paudel, Krishna P; Daniel, Nadhomi L

2018-02-01

Soil and water conservation technologies have been widely available in most parts of Uganda. However, not only has the adoption rate been low but also many farmers seem not to be aware of these technologies. This study aims at identifying the factors that influence awareness and adoption of soil and water conservation technologies in Nabajuzi watershed in central Uganda. A bivariate probit model was used to examine farmers' awareness and adoption of soil and water conservation technologies in the watershed. We use data collected from the interview of 400 households located in the watershed to understand the factors affecting the awareness and adoption of these technologies in the study area. Findings indicate that the likelihood of being aware and adopting the technologies are explained by the age of household head, being a tenant, and number of years of access to farmland. To increase awareness and adoption of technologies in Uganda, policymakers may expedite the process of land titling as farmers may feel secure about landholding and thus adopt these technologies to increase profitability and productivity in the long run. Incentive payments to farmers residing in the vulnerable region to adopt these considered technologies may help to alleviate soil deterioration problems in the affected area.

A Cash-back Rebate Program for Healthy Food Purchases in South Africa: Selection and Program Effects in Self-reported Diet Patterns.

PubMed

An, Ruopeng; Sturm, Roland

2017-03-01

A South African insurer launched a rebate program for healthy food purchases for its members, but only available in program-designated supermarkets. To eliminate selection bias in program enrollment, we estimated the impact of subsidies in nudging the population towards a healthier diet using an instrumental variable approach. Data came from a health behavior questionnaire administered among members in the health promotion program. Individual and supermarket addresses were geocoded and differential distances from home to program-designated supermarkets versus competing supermarkets were calculated. Bivariate probit and linear instrumental variable models were performed to control for likely unobserved selection biases, employing differential distances as a predictor of program enrollment. For regular fast-food, processed meat, and salty food consumption, approximately two-thirds of the difference between participants and nonparticipants was attributable to the intervention and one-third to selection effects. For fruit/ vegetable and fried food consumption, merely one-eighth of the difference was selection. The rebate reduced regular consumption of fast food by 15% and foods high in salt/sugar and fried foods by 22%- 26%, and increased fruit/vegetable consumption by 21% (0.66 serving/day). Large population interventions are an essential complement to laboratory experiments, but selection biases require explicit attention in evaluation studies conducted in naturalistic settings.

Does reporting behaviour bias the measurement of social inequalities in self-rated health in Indonesia? An anchoring vignette analysis.

PubMed

Hanandita, Wulung; Tampubolon, Gindo

2016-05-01

Studies on self-rated health outcomes are fraught with problems when individuals' reporting behaviour is systematically biased by demographic, socio-economic, or cultural factors. Analysing the data drawn from the Indonesia Family Life Survey 2007, this paper aims to investigate the extent of differential health reporting behaviour by demographic and socio-economic status among Indonesians aged 40 and older (N = 3735). Interpersonal heterogeneity in reporting style is identified by asking respondents to rate a number of vignettes that describe varying levels of health status in targeted health domains (mobility, pain, cognition, sleep, depression, and breathing) using the same ordinal response scale that is applied to the self-report health question. A compound hierarchical ordered probit model is fitted to obtain health differences by demographic and socio-economic status. The obtained regression coefficients are then compared to the standard ordered probit model. We find that Indonesians with more education tend to rate a given health status in each domain more negatively than their less-educated counterparts. Allowing for such differential reporting behaviour results in relatively stronger positive education effects. There is a need to correct for differential reporting behaviour using vignettes when analysing self-rated health measures in older adults in Indonesia. Unless such an adjustment is made, the salutary effect of education will be underestimated.

Disability weights for infectious diseases in four European countries: comparison between countries and across respondent characteristics

PubMed Central

Maertens de Noordhout, Charline; Devleesschauwer, Brecht; Salomon, Joshua A; Turner, Heather; Cassini, Alessandro; Colzani, Edoardo; Speybroeck, Niko; Polinder, Suzanne; Kretzschmar, Mirjam E; Havelaar, Arie H; Haagsma, Juanita A

2018-01-01

Abstract Background In 2015, new disability weights (DWs) for infectious diseases were constructed based on data from four European countries. In this paper, we evaluated if country, age, sex, disease experience status, income and educational levels have an impact on these DWs. Methods We analyzed paired comparison responses of the European DW study by participants’ characteristics with separate probit regression models. To evaluate the effect of participants’ characteristics, we performed correlation analyses between countries and within country by respondent characteristics and constructed seven probit regression models, including a null model and six models containing participants’ characteristics. We compared these seven models using Akaike Information Criterion (AIC). Results According to AIC, the probit model including country as covariate was the best model. We found a lower correlation of the probit coefficients between countries and income levels (range rs: 0.97–0.99, P < 0.01) than between age groups (range rs: 0.98–0.99, P < 0.01), educational level (range rs: 0.98–0.99, P < 0.01), sex (rs = 0.99, P < 0.01) and disease status (rs = 0.99, P < 0.01). Within country the lowest correlations of the probit coefficients were between low and high income level (range rs = 0.89–0.94, P < 0.01). Conclusions We observed variations in health valuation across countries and within country between income levels. These observations should be further explored in a systematic way, also in non-European countries. We recommend future researches studying the effect of other characteristics of respondents on health assessment. PMID:29020343

Time-dependent dose-response relation for absence of vaginal elasticity after gynecological radiation therapy.

PubMed

Alevronta, Eleftheria; Åvall-Lundqvist, Elisabeth; Al-Abany, Massoud; Nyberg, Tommy; Lind, Helena; Waldenström, Ann-Charlotte; Olsson, Caroline; Dunberger, Gail; Bergmark, Karin; Steineck, Gunnar; Lind, Bengt K

2016-09-01

To investigate the dose-response relation between the dose to the vagina and the patient-reported symptom 'absence of vaginal elasticity' and how time to follow-up influences this relation. The study included 78 long-term gynecological cancer survivors treated between 1991 and 2003 with external beam radiation therapy. Of those, 24 experienced absence of vaginal elasticity. A normal tissue complication model is introduced that takes into account the influence of time to follow-up on the dose-response relation and the patient's age. The best estimates of the dose-response parameters were calculated using Probit, Probit-Relative Seriality (RS) and Probit-time models. Log likelihood (LL) values and the Akaike Information Criterion (AIC) were used to evaluate the model fit. The dose-response parameters for 'absence of vaginal elasticity' according to the Probit and Probit-time models with the 68% Confidence Intervals (CI) were: LL=-39.8, D 50 =49.7 (47.2-52.4) Gy, γ 50 =1.40 (1.12-1.70) and LL=-37.4, D 50 =46.9 (43.5-50.9) Gy, γ 50 =1.81 (1.17-2.51) respectively. The proposed model, which describes the influence of time to follow-up on the dose-response relation, fits our data best. Our data indicate that the steepness of the dose-response curve of the dose to the vagina and the symptom 'absence of vaginal elasticity' increases with time to follow-up, while D 50 decreases. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Seeking alternatives to probit 9 when developing treatments for wood packaging materials under ISPM No. 15

Treesearch

R.A. Haack; A. Uzunovic; K. Hoover; J.A. Cook

2011-01-01

ISPM No. 15 presents guidelines for treating wood packaging material used in international trade. There are currently two approved phytosanitary treatments: heat treatment and methyl bromide fumigation. New treatments are under development, and are needed given that methyl bromide is being phased out. Probit 9 efficacy (100% mortality of at least 93 613 test organisms...

POLO2: a user's guide to multiple Probit Or LOgit analysis

Treesearch

Robert M. Russell; N. E. Savin; Jacqueline L. Robertson

1981-01-01

This guide provides instructions for the use of POLO2, a computer program for multivariate probit or logic analysis of quantal response data. As many as 3000 test subjects may be included in a single analysis. Including the constant term, up to nine explanatory variables may be used. Examples illustrating input, output, and uses of the program's special features...

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors.

PubMed

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-04-16

Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people's quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education, residence in metropolitan areas, and so on). As the results of the Wald test carried out after the estimations did not allow to reject the null hypothesis of endogeneity, a probit model was run too. Overall, women tend to develop depression more frequently than men. There is an inverse effect of education on depressed mood (probability of -24.6% to report a depressed mood due to high school education, as it emerges from the probit model marginal effects), while marital status and the number of family members may act as protective factors (probability to report a depressed mood of -1.0% for each family member). Depression is significantly associated with socio-economic conditions, such as work and income. Living in metropolitan areas is inversely correlated with depression (probability of -4.1% to report a depressed mood estimated through the probit model): this could be explained considering that, in rural areas, people rarely have immediate access to high-quality health services. This study outlines the factors that are more likely to impact on depression, and applies an IVP model to take into account the potential endogeneity of some of the predictors of depressive mood, such as female participation to workforce and health status. A probit model has been estimated too. Depression is associated with a wide range of socio-economic factors, although the strength and direction of the association can differ by gender. Prevention approaches to contrast depressive symptoms might take into consideration the evidence offered by the present study. © 2015 by Kerman University of Medical Sciences.

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors

PubMed Central

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-01-01

Background: Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people’s quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Methods: Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education, residence in metropolitan areas, and so on). As the results of the Wald test carried out after the estimations did not allow to reject the null hypothesis of endogeneity, a probit model was run too. Results: Overall, women tend to develop depression more frequently than men. There is an inverse effect of education on depressed mood (probability of -24.6% to report a depressed mood due to high school education, as it emerges from the probit model marginal effects), while marital status and the number of family members may act as protective factors (probability to report a depressed mood of -1.0% for each family member). Depression is significantly associated with socio-economic conditions, such as work and income. Living in metropolitan areas is inversely correlated with depression (probability of -4.1% to report a depressed mood estimated through the probit model): this could be explained considering that, in rural areas, people rarely have immediate access to high-quality health services. Conclusion: This study outlines the factors that are more likely to impact on depression, and applies an IVP model to take into account the potential endogeneity of some of the predictors of depressive mood, such as female participation to workforce and health status. A probit model has been estimated too. Depression is associated with a wide range of socio-economic factors, although the strength and direction of the association can differ by gender. Prevention approaches to contrast depressive symptoms might take into consideration the evidence offered by the present study. PMID:26340392

Study of Personnel Attrition and Revocation within U.S. Marine Corps Air Traffic Control Specialties

DTIC Science & Technology

2012-03-01

Entrance Processing Stations (MEPS) and recruit depots, to include non-cognitive testing, such as Navy Computer Adaptive Personality Scales ( NCAPS ...Revocation, Selection, MOS, Regression, Probit, dProbit, STATA, Statistics, Marginal Effects, ASVAB, AFQT, Composite Scores, Screening, NCAPS 15. NUMBER...Navy Computer Adaptive Personality Scales ( NCAPS ), during recruitment. It is also recommended that an economic analysis be conducted comparing the

Modeling vehicle operating speed on urban roads in Montreal: a panel mixed ordered probit fractional split model.

PubMed

Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis F

2013-10-01

Vehicle operating speed measured on roadways is a critical component for a host of analysis in the transportation field including transportation safety, traffic flow modeling, roadway geometric design, vehicle emissions modeling, and road user route decisions. The current research effort contributes to the literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model in the literature. The proposed formulation allows us to model the proportion of vehicles traveling in each speed interval for the entire segment of roadway. We extend the model to allow the influence of exogenous variables to vary across the population. Further, we develop a panel mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the speed distribution. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate that the proposed panel mixed ordered probit fractional split model offers promise for modeling such proportional ordinal variables. Copyright © 2013 Elsevier Ltd. All rights reserved.

An analytical study of physical models with inherited temporal and spatial memory

NASA Astrophysics Data System (ADS)

Jaradat, Imad; Alquran, Marwan; Al-Khaled, Kamel

2018-04-01

Du et al. (Sci. Reb. 3, 3431 (2013)) demonstrated that the fractional derivative order can be physically interpreted as a memory index by fitting the test data of memory phenomena. The aim of this work is to study analytically the joint effect of the memory index on time and space coordinates simultaneously. For this purpose, we introduce a novel bivariate fractional power series expansion that is accompanied by twofold fractional derivatives ordering α, β\\in(0,1]. Further, some convergence criteria concerning our expansion are presented and an analog of the well-known bivariate Taylor's formula in the sense of mixed fractional derivatives is obtained. Finally, in order to show the functionality and efficiency of this expansion, we employ the corresponding Taylor's series method to obtain closed-form solutions of various physical models with inherited time and space memory.

A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA.

PubMed

Fong, Duncan K H; Kim, Sunghoon; Chen, Zhe; DeSarbo, Wayne S

2016-03-01

A new Bayesian multinomial probit model is proposed for the analysis of panel choice data. Using a parameter expansion technique, we are able to devise a Markov Chain Monte Carlo algorithm to compute our Bayesian estimates efficiently. We also show that the proposed procedure enables the estimation of individual level coefficients for the single-period multinomial probit model even when the available prior information is vague. We apply our new procedure to consumer purchase data and reanalyze a well-known scanner panel dataset that reveals new substantive insights. In addition, we delineate a number of advantageous features of our proposed procedure over several benchmark models. Finally, through a simulation analysis employing a fractional factorial design, we demonstrate that the results from our proposed model are quite robust with respect to differing factors across various conditions.

Corruption, inequality and population perception of healthcare quality in Europe

PubMed Central

2013-01-01

Background Evaluating the quality of healthcare and patient safety using general population questionnaires is important from research and policy perspective. Using a special wave of the Eurobarometer survey, we analysed the general population’s perception of health care quality and patient safety in a cross-country setting. Methods We used ordered probit, ordinary least squares and probit analysis to estimate the determinants of health care quality, and ordered logit analysis to analyse the likelihood of being harmed by a specific medical procedure. The models used population weights as well as country-clustered standard errors. Results We found robust evidence for the impact of socio-demographic variables on the perception of quality of health care. More specifically, we found a non-linear impact of age on the perception of quality of health care and patient safety, as well as a negative impact of poverty on both perception of quality and patient safety. We also found robust evidence that countries with higher corruption levels were associated with worse perceptions of quality of health care. Finally, we found evidence that income inequality affects patients’ perception vis-à-vis safety, thus feeding into the poverty/health care quality nexus. Conclusions Socio-demographic factors and two macro variables (corruption and income inequality) explain the perception of quality of health care and likelihood of being harmed by adverse events. The results carry significant policy weight and could explain why targeting only the health care sector (without an overall reform of the public sector) could potentially be challenging. PMID:24215401

Exploring motorcyclist injury severity resulting from various crash configurations at T-junctions in the United Kingdom--an application of the ordered probit models.

PubMed

Pai, Chih-Wei; Saleh, Wafaa

2007-03-01

The fact that motorcycle users tend to be more vulnerable to injuries than those using other motorized vehicles may act synergistically with the complexity of conflicting movements between vehicles and motorcycles to increase injury severity in a junction-type accident. A junction-type collision tends to be more severe than a non-junction case due to the fact that some of the injurious crashes such as angle-collision commonly occur. Existing studies have applied several statistical modeling techniques to examine influential factors on the occurrences of different crashes among motorized vehicles but surprisingly very little has empirically explored whether a particular crash type, resulting from a junction-type accident, is more injurious to motorcyclists. This article attempts to investigate whether a particular collision is more deadly to motorcyclists conditioned on crash occurrence at T-junctions in the U.K., while controlling for environment, vehicle, and demographic factors. The statistical modeling technique employed is the ordered probit models using the data extracted from the STATS19 accident injury database (1999-2004). The modeling found determinants of injury severity among motorcyclists at T-junctions in the U.K. For example, an approach-turn/head-on collision is much more injurious to motorcyclists; and, those riding in early morning (i.e., 0000-0659) are more likely to be severely injured. This study offers a guideline for future research, as well as insight into potential prevention strategies that might help moderate motorcyclist injuries.

Corruption, inequality and population perception of healthcare quality in Europe.

PubMed

Nikoloski, Zlatko; Mossialos, Elias

2013-11-11

Evaluating the quality of healthcare and patient safety using general population questionnaires is important from research and policy perspective. Using a special wave of the Eurobarometer survey, we analysed the general population's perception of health care quality and patient safety in a cross-country setting. We used ordered probit, ordinary least squares and probit analysis to estimate the determinants of health care quality, and ordered logit analysis to analyse the likelihood of being harmed by a specific medical procedure. The models used population weights as well as country-clustered standard errors. We found robust evidence for the impact of socio-demographic variables on the perception of quality of health care. More specifically, we found a non-linear impact of age on the perception of quality of health care and patient safety, as well as a negative impact of poverty on both perception of quality and patient safety. We also found robust evidence that countries with higher corruption levels were associated with worse perceptions of quality of health care. Finally, we found evidence that income inequality affects patients' perception vis-à-vis safety, thus feeding into the poverty/health care quality nexus. Socio-demographic factors and two macro variables (corruption and income inequality) explain the perception of quality of health care and likelihood of being harmed by adverse events. The results carry significant policy weight and could explain why targeting only the health care sector (without an overall reform of the public sector) could potentially be challenging.

Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.

PubMed

Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai

2011-01-01

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.

Performance and separation occurrence of binary probit regression estimator using maximum likelihood method and Firths approach under different sample size

NASA Astrophysics Data System (ADS)

Lusiana, Evellin Dewi

2017-12-01

The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.

Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach.

PubMed

Mohammadi, Tayeb; Kheiri, Soleiman; Sedehi, Morteza

2016-01-01

Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.

Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach

PubMed Central

Mohammadi, Tayeb; Sedehi, Morteza

2016-01-01

Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables “number of blood donation” and “number of blood deferral”: as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models. PMID:27703493

A Bivariate Chebyshev Spectral Collocation Quasilinearization Method for Nonlinear Evolution Parabolic Equations

PubMed Central

Motsa, S. S.; Magagula, V. M.; Sibanda, P.

2014-01-01

This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs). The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature. PMID:25254252

A bivariate Chebyshev spectral collocation quasilinearization method for nonlinear evolution parabolic equations.

PubMed

Motsa, S S; Magagula, V M; Sibanda, P

2014-01-01

This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs). The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

Nonparametric Bayesian models through probit stick-breaking processes

PubMed Central

Rodríguez, Abel; Dunson, David B.

2013-01-01

We describe a novel class of Bayesian nonparametric priors based on stick-breaking constructions where the weights of the process are constructed as probit transformations of normal random variables. We show that these priors are extremely flexible, allowing us to generate a great variety of models while preserving computational simplicity. Particular emphasis is placed on the construction of rich temporal and spatial processes, which are applied to two problems in finance and ecology. PMID:24358072

Nonparametric Bayesian models through probit stick-breaking processes.

PubMed

Rodríguez, Abel; Dunson, David B

2011-03-01

We describe a novel class of Bayesian nonparametric priors based on stick-breaking constructions where the weights of the process are constructed as probit transformations of normal random variables. We show that these priors are extremely flexible, allowing us to generate a great variety of models while preserving computational simplicity. Particular emphasis is placed on the construction of rich temporal and spatial processes, which are applied to two problems in finance and ecology.

The Effects of Designated Pollutants on Plants

DTIC Science & Technology

1978-11-01

two marigold . . . . . . . . . . . . . . . . . . . . . . . . . 44 21. Probit analysis of five plant species: petunia , bean, radish, salvia and tomato...Tagetes patula L. French dwarf double goldie Marigold Tagetes erecta L. American,Senator Dirksen Petunia Petunia hybrida Vilm. White cascade Radish...00 s0 too 200 4w0 1000 1 20 3O 060 100 20 00 1000 HCL CONCENTRATION (MG Mŗ ) Figure 21. Probit analysis of five plant species: 16-day- petunia , 25-day

Development and Implementation of a Telecommuting Evaluation Framework, and Modeling the Executive Telecommuting Adoption Process

NASA Astrophysics Data System (ADS)

Vora, V. P.; Mahmassani, H. S.

2002-02-01

This work proposes and implements a comprehensive evaluation framework to document the telecommuter, organizational, and societal impacts of telecommuting through telecommuting programs. Evaluation processes and materials within the outlined framework are also proposed and implemented. As the first component of the evaluation process, the executive survey is administered within a public sector agency. The survey data is examined through exploratory analysis and is compared to a previous survey of private sector executives. The ordinal probit, dynamic probit, and dynamic generalized ordinal probit (DGOP) models of telecommuting adoption are calibrated to identify factors which significantly influence executive adoption preferences and to test the robustness of such factors. The public sector DGOP model of executive willingness to support telecommuting under different program scenarios is compared with an equivalent private sector DGOP model. Through the telecommuting program, a case study of telecommuting travel impacts is performed to further substantiate research.

Women's autonomy and reproductive health care utilisation: empirical evidence from Tajikistan.

PubMed

Kamiya, Yusuke

2011-10-01

Women's autonomy is widely considered to be a key to improving maternal health in developing countries, whereas there is no consistent empirical evidence to support this claim. This paper examines whether or not and how women's autonomy within the household affects the use of reproductive health care, using a household survey data from Tajikistan. Estimation is performed by the bivariate probit model whereby woman's use of health services and the level of women's autonomy are recursively and simultaneously determined. The data is from a sample of women aged 15-49 from the Tajikistan Living Standard Measurement Survey 2007. Women's autonomy as measured by women's decision-making on household financial matters increase the likelihood that a woman receives antenatal and delivery care, whilst it has a negative effect on the probability of attending to four or more antenatal consultations. The hypothesis that women's autonomy and reproductive health care utilisation are independently determined is rejected for most of the estimation specifications, indicating the importance of taking into account the endogenous nature of women's autonomy when assessing its effect on health care use. The empirical results reconfirm the assertion that women's status within the household is closely linked to reproductive health care utilisation in developing countries. Policymakers therefore need not only to implement not only direct health interventions but also to focus on broader social policies which address women's empowerment. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Economic analysis of the intangible impacts of informal care for people with Alzheimer's disease and other mental disorders.

PubMed

Gervès, Chloé; Bellanger, Martine Marie; Ankri, Joël

2013-01-01

Valuation of the intangible impacts of informal care remains a great challenge for economic evaluation, especially in the framework of care recipients with cognitive impairment. Our main objective was to explore the influence of intangible impacts of caring on both informal caregivers' ability to estimate their willingness to pay (WTP) to be replaced and their WTP value. We mapped characteristics that influence ability or inability to estimate WTP by using a multiple correspondence analysis. We ran a bivariate probit model with sample selection to further analyze the caregivers' WTP value conditional on their ability to estimate their WTP. A distinction exists between the opportunity costs of the caring dimension and those of the intangible costs and benefits of caring. Informal caregivers' ability to estimate WTP is negatively influenced by both intangible benefits from caring (P < 0.001) and negative intangible impacts of caring (P < 0.05). Caregivers' WTP value is negatively associated with positive intangible impacts of informal care (P < 0.01). Informal caregivers' WTP and their ability to estimate WTP are both influenced by intangible burden and benefit of caring. These results call into question the relevance of a hypothetical generalized financial compensation system as the optimal way to motivate caregivers to continue providing care. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Measuring the cost-effectiveness of a national health communication program in rural Bangladesh.

PubMed

Hutchinson, Paul; Lance, Peter; Guilkey, David K; Shahjahan, Mohammad; Haque, Shahida

2006-01-01

In this article we examine the cost-effectiveness of the Smiling Sun multichannel media campaign, which was undertaken in Bangladesh from 2001 to 2003 and involved a nationally broadcast television serial drama supported by radio, television, newspaper, and billboard advertisements and local promotion activities. The goal was to encourage the use of a package of family health services at NGO (nongovernmental organization) Service Delivery Program (NSDP) providers. This analysis relates the costs of the Smiling Sun campaign at the national and local level to measures of change in the use of health services, namely, antenatal care and childhood immunizations. Effectiveness is measured using data from cross-sectional surveys conducted in 2001 and 2003 in NSDP catchment areas in rural Bangladesh. The statistical approach, bivariate probit estimation, controls for nonrandom exposure to the program's media messages, advertisements, and signs. Using national-level data, we find that the Smiling Sun campaign was both effective and cost-effective, inducing higher levels of service utilization for only $0.05 per additional antenatal care (ANC) user and only $0.30 and $0.36 for each additional child vaccinated for measles and DPT3, respectively. With respect to local promotion activities, the cost per attributable behavior change was considerably higher--nearly $8 per new ANC user, $37 per new DPT3 vaccination, and $32 per new measles vaccination.

Care-Seeking Patterns and Direct Economic Burden of Injuries in Bangladesh.

PubMed

Alfonso, Natalia Y; Alonge, Olakunle; Hoque, Dewan Md Emdadul; Baset, Kamran Ul; Hyder, Adnan A; Bishai, David

2017-04-29

This study provides a comprehensive review of the care-seeking patterns and direct economic burden of injuries from the victims' perspective in rural Bangladesh using a 2013 household survey covering 1.17 million people. Descriptive statistics and bivariate analyses were used to derive rates and test the association between variables. An analytic model was used to estimate total injury out-of-pocket (OOP) payments and a multivariate probit regression model assessed the relationship between financial distress and injury type. Results show non-fatal injuries occur to 1 in 5 people in our sample per year. With average household size of 4.5 in Bangladesh--every household has an injury every year. Most non-fatally injured patients sought healthcare from drug sellers. Less than half of fatal injuries sought healthcare and half of those with care were hospitalized. Average OOP payments varied significantly (range: $8-$830) by injury type and outcome (fatal vs. non-fatal). Total injury OOP expenditure was $$355,795 and $5000 for non-fatal and fatal injuries, respectively, per 100,000 people. The majority of household heads with injuries reported financial distress. This study can inform injury prevention advocates on disparities in healthcare usage, OOP costs and financial distress. Reallocation of resources to the most at risk populations can accelerate reduction of preventable injuries and prevent injury related catastrophic payments and impoverishment.

Care-Seeking Patterns and Direct Economic Burden of Injuries in Bangladesh

PubMed Central

Alfonso, Yira Natalia; Alonge, Olakunle; Hoque, Dewan Md Emdadul; Ul Baset, Md Kamran; Hyder, Adnan A.; Bishai, David

2017-01-01

This study provides a comprehensive review of the care-seeking patterns and direct economic burden of injuries from the victims’ perspective in rural Bangladesh using a 2013 household survey covering 1.17 million people. Descriptive statistics and bivariate analyses were used to derive rates and test the association between variables. An analytic model was used to estimate total injury out-of-pocket (OOP) payments and a multivariate probit regression model assessed the relationship between financial distress and injury type. Results show non-fatal injuries occur to 1 in 5 people in our sample per year. With average household size of 4.5 in Bangladesh--every household has an injury every year. Most non-fatally injured patients sought healthcare from drug sellers. Less than half of fatal injuries sought healthcare and half of those with care were hospitalized. Average OOP payments varied significantly (range: $8–$830) by injury type and outcome (fatal vs. non-fatal). Total injury OOP expenditure was $355,795 and $5000 for non-fatal and fatal injuries, respectively, per 100,000 people. The majority of household heads with injuries reported financial distress. This study can inform injury prevention advocates on disparities in healthcare usage, OOP costs and financial distress. Reallocation of resources to the most at risk populations can accelerate reduction of preventable injuries and prevent injury related catastrophic payments and impoverishment. PMID:28468240

Association between clean indoor air laws and voluntary smokefree rules in homes and cars.

PubMed

Cheng, Kai-Wen; Okechukwu, Cassandra A; McMillen, Robert; Glantz, Stanton A

2015-03-01

This study examines the influence that smokefree workplaces, restaurants and bars have on the adoption of smokefree rules in homes and cars, and whether there is an association with adopting smokefree rules in homes and cars. Bivariate probit models were used to jointly estimate the likelihood of living in a smokefree home and having a smokefree car as a function of law coverage and other variables. Household data were obtained from the nationally representative Social Climate Survey of Tobacco Control 2001, 2002 and 2004-2009; clean indoor air law data were from the American Nonsmokers' Rights Foundation Tobacco Control Laws Database. 'Full coverage' and 'partial coverage' smokefree legislation is associated with an increased likelihood of having voluntary home and car smokefree rules compared with 'no coverage'. The association between 'full coverage' and smokefree rule in homes and cars is 5% and 4%, respectively, and the association between 'partial coverage' and smokefree rules in homes and cars is 3% and 4%, respectively. There is a positive association between the adoption of smokefree rules in homes and cars. Clean indoor air laws provide the additional benefit of encouraging voluntary adoption of smokefree rules in homes and cars. 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.

The effects of preoperative cardiology consultation prior to elective abdominal aortic aneurysm repair on patient morbidity.

PubMed

Boniakowski, Anna E; Davis, Frank M; Phillips, Amanda R; Robinson, Adina B; Coleman, Dawn M; Henke, Peter K

2017-08-01

Objectives The relationship between preoperative medical consultations and postoperative complications has not been extensively studied. Thus, we investigated the impact of preoperative consultation on postoperative morbidity following elective abdominal aortic aneurysm repair. Methods A retrospective review was conducted on 469 patients (mean age 72 years, 20% female) who underwent elective abdominal aortic aneurysm repair from June 2007 to July 2014. Data elements included detailed medical history, preoperative cardiology consultation, and postoperative complications. Primary outcomes included 30-day morbidity, consult-specific morbidity, and mortality. A bivariate probit regression model accounting for the endogeneity of binary preoperative medical consult and patient variability was estimated with a maximum likelihood function. Results Eighty patients had preoperative medical consults (85% cardiology); thus, our analysis focuses on the effect of cardiac-related preoperative consults. Hyperlipidemia, increased aneurysm size, and increased revised cardiac risk index increased likelihood of referral to cardiology preoperatively. Surgery type (endovascular versus open repair) was not significant in development of postoperative complications when controlling for revised cardiac risk index ( p = 0.295). After controlling for patient comorbidities, there was no difference in postoperative cardiac-related complications between patients who did and did not undergo cardiology consultation preoperatively ( p = 0.386). Conclusions When controlling for patient disease severity using revised cardiac risk index risk stratification, preoperative cardiology consultation is not associated with postoperative cardiac morbidity.

Male factor infertility: a twin study.

PubMed

Cloonan, Yona K; Holt, Victoria L; Goldberg, Jack

2007-05-01

There is a considerable body of literature on the causes of female infertility, but far less is known about male factor infertility. We conducted a classical twin study to estimate the genetic influence on 12-month male factor infertility. The study used the Vietnam Era Twin (VET) Registry, which includes male twin pairs born between 1939 and 1957, and who served in the US military between 1965 and 1975. In 1987, a health survey was mailed to all twins and obtained a 74% response rate. The current analyses comprised 1795 complete pairs in which both twins were married only once. Proband-wise concordance rates, tetrachoric correlations, and a bivariate probit model were used to calculate estimates of familial clustering and heritability for male factor infertility. The proband concordance rate for male factor infertility was 38% [95% CI 32.8, 42.4] in monozygotic (MZ) pairs and 33% [95% CI 28.0, 38.6] in dizygotic (DZ) pairs. The tetrachoric correlations for male infertility were 0.15 in MZ and 0.04 in DZ pairs. This pattern provides evidence of familial clustering, although genetic influence was not evident (P = 0.21). The current study identified that 12-month male factor infertility clustered within families. However, results suggest that factors unique to individual twins may play a more prominent role in male infertility than additive genetic effects or the common environment.

Role of intrinsic search cues in the formation of consumer preferences and choice for pork chops.

PubMed

Verbeke, Wim; De Smet, Stefaan; Vackier, Isabelle; Van Oeckel, Monique J; Warnants, Nathalie; Van Kenhove, Patrick

2005-02-01

This study investigates the role of drip, colour, marbling and fat cover as intrinsic search cues in the formation of pork chop preferences and individual determinants. Data are collected from a sample of 443 pork consumers in Belgium through using repeated selection of chops from randomised photobooks and questionnaires including socio-demographic, attitudinal and behavioural variables. Data analysis includes mixture regression analysis, bivariate descriptive statistics and the estimation of multivariate probit models. Consumers sampled in this study prefer pork chops without fat cover. Preference for fat cover is stronger among male, 35+ aged consumers with lower levels of awareness of the relation between food and health and who like pork for other reasons than taste and nutritional value (all p<0.05). Preference for colour is equally consistent within an individual, though fifty-fifty light-dark, with dark chops being more preferred by 35+ aged consumers (p<0.05). Preferences for marbling and drip are not consistent and not determined by joint socio-demographic, attitudinal and behavioural factors. Preferences for cue levels are not correlated, except a weak relation between preference for dark chops without drip (r=0.116). Preferences are apparently formed by deductions with the use of single cues as key information, mainly based on fat cover or colour, and random choice on marbling and drip.

U.S. Preventive Services Task Force recommendations and cancer screening among female Medicare beneficiaries.

PubMed

Salloum, Ramzi G; Kohler, Racquel E; Jensen, Gail A; Sheridan, Stacey L; Carpenter, William R; Biddle, Andrea K

2014-03-01

Medicare covers several cancer screening tests not currently recommended by the U.S. Preventive Services Task Force (Task Force). In September 2002, the Task Force relaxed the upper age limit of 70 years for breast cancer screening recommendations, and in March 2003 an upper age limit of 65 years was introduced for cervical cancer screening recommendations. We assessed whether mammogram and Pap test utilization among women with Medicare coverage is influenced by changes in the Task Force's recommendations for screening. We identified female Medicare beneficiaries aged 66-80 years and used bivariate probit regression to examine the receipt of breast (mammogram) and cervical (Pap test) cancer screening reflecting changes in the Task Force recommendations. We analyzed 9,760 Medicare Current Beneficiary Survey responses from 2001 to 2007. More than two-thirds reported receiving a mammogram and more than one-third a Pap test in the previous 2 years. Lack of recommendation was given as a reason for not getting screened among the majority (51% for mammogram and 75% for Pap). After controlling for beneficiary-level socioeconomic characteristics and access to care factors, we did not observe a significant change in breast and cervical cancer screening patterns following the changes in Task Force recommendations. Although there is evidence that many Medicare beneficiaries adhere to screening guidelines, some women may be receiving non-recommended screening services covered by Medicare.

Interactions between Private Health and Long-term Care Insurance and the Effects of the Crisis: Evidence for Spain.

PubMed

Jiménez-Martín, Sergi; Labeaga-Azcona, José M; Vilaplana-Prieto, Cristina

2016-11-01

This paper analyzes the reasons for the scarce development of the private long-term care insurance market in Spain, and its relationship with health insurance. We are also interested in the effects the crisis has had both on the evolution of the demand for long-term care insurance and on the existence of regional disparities. We estimate bivariate probit models with endogenous variables using Spanish data from the Survey on Health and Retirement in Europe. Our results confirm that individuals wishing to purchase long-term care insurance are, in a sense, forced to subscribe a health insurance policy. In spite of this restriction in the supply of long-term care insurance contracts, we find its demand has grown in recent years, which we attribute to the budget cuts affecting the implementation of Spain's System of Autonomy and Attention to Dependent People. Regional differences in its implementation, as well as the varying effects the crisis has had across Spanish regions, lead to the existence of a crowding-in effect in the demand for long-term care insurance in those regions where co-payment is based on income and wealth, those that have a lower percentage of public long-term care beneficiaries, or those with a smaller share of cash benefits over total public benefits. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Part-time sick leave as a treatment method for individuals with musculoskeletal disorders.

PubMed

Andrén, Daniela; Svensson, Mikael

2012-09-01

There is increasing evidence that staying active is an important part of a recovery process for individuals on sick leave due to musculoskeletal disorders (MSDs). It has been suggested that using part-time sick-leave rather than full-time sick leave will enhance the possibility of full recovery to the workforce, and several countries actively favor this policy. The aim of this paper is to examine if it is beneficial for individuals on sick leave due to MSDs to be on part-time sick leave compared to full-time sick leave. A sample of 1,170 employees from the RFV-LS (register) database of the Social Insurance Agency of Sweden is used. The effect of being on part-time sick leave compared to full-time sick leave is estimated for the probability of returning to work with full recovery of lost work capacity. A two-stage recursive bivariate probit model is used to deal with the endogeneity problem. The results indicate that employees assigned to part-time sick leave do recover to full work capacity with a higher probability than those assigned to full-time sick leave. The average treatment effect of part-time sick leave is 25 percentage points. Considering that part-time sick leave may also be less expensive than assigning individuals to full-time sick leave, this would imply efficiency improvements from assigning individuals, when possible, to part-time sick leave.

The Consequences of Job Displacement for Health: Moderating Influences of Economic Conditions and Educational Attainment

PubMed Central

Pearlman, Jessica

2015-01-01

This paper will examine the impact of worker displacement on health in the United States from 1975–2004, especially the extent to which the impact of displacement on health varies according to the economic conditions in the year of displacement and the education level of the displaced worker. Findings from ordered probit and fixed effects models suggest that the negative impact of displacement on health is exacerbated by a higher unemployment rate at the time of displacement and for displaced workers with a college degree. PMID:26004481

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

PubMed Central

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

PubMed

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia

NASA Astrophysics Data System (ADS)

Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

2016-08-01

Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

Choice of personal assistance services providers by medicare beneficiaries using a consumer-directed benefit: rural-urban differences.

PubMed

Meng, Hongdao; Friedman, Bruce; Wamsley, Brenda R; Van Nostrand, Joan F; Eggert, Gerald M

2010-01-01

To examine the impact of an experimental consumer-choice voucher benefit on the selection of independent and agency personal assistance services (PAS) providers among rural and urban Medicare beneficiaries with disabilities. The Medicare Primary and Consumer-Directed Care Demonstration enrolled 1,605 Medicare beneficiaries in 19 counties in New York State, West Virginia, and Ohio. A total of 839 participants were randomly assigned to receive a voucher benefit (up to $250 per month with a 20% copayment) that could be used toward PAS provided by either independent or agency workers. A bivariate probit model was used to estimate the probabilities of choosing either type of PAS provider while controlling for potential confounders. The voucher was associated with a 32.4% (P < .01) increase in the probability of choosing agency providers and a 12.5% (P= .03) increase in the likelihood of choosing independent workers. When the analysis was stratified by rural/urban status, rural voucher recipients had 36.8% higher probability of using independent workers compared to rural controls. Urban voucher recipients had 37.1% higher probability of using agency providers compared to urban controls. This study provided evidence that rural and urban Medicare beneficiaries with disabilities may have very different responses to a consumer-choice PAS voucher program. Offering a consumer-choice voucher option to rural populations holds the potential to significantly improve their access to PAS. © 2010 National Rural Health Association.

Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia.

PubMed

Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

2016-08-01

Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

Impacts of market and organizational characteristics on hospital efficiency and uncompensated care.

PubMed

Hsieh, Hui-Min; Clement, Dolores G; Bazzoli, Gloria J

2010-01-01

Hospitals have confronted a difficult financial environment given many factors, including expansion of managed care, changes in public policy, growing market competition for certain services, and growth in the number of uninsured. Policy makers have expressed concern that hospitals may forgo providing care to the indigent as a means to reduce costs and become more efficient when faced with financial pressures. This article examined the effects of environmental pressures on two dimensions of hospital performance: hospital efficiency and uncompensated care provision. Longitudinal data for the Commonwealth of Virginia from 1998 to 2004 were analyzed. Data Envelopment Analysis and bivariate probit were used to examine the factors associated with efficiency and uncompensated care. The results indicated that a positive relationship between hospital efficiency and uncompensated care provision exists. That is, hospitals that are categorized as efficient are likely to provide more uncompensated care. We also found that hospitals tended to provide more uncompensated care when increased demand for these services occurred in a market. Increases in Medicare or Medicaid patient share reduced the provision of uncompensated care. In relation to hospital efficiency, the results indicated that HMO penetration and Medicaid patient share reduced hospital efficiency. This study found that efficient hospitals tend to provide more uncompensated care over time. The findings also suggest that hospitals alter their efficiency and provision of uncompensated care in response to a number of environmental pressures, but it may depend on the type of pressures or uncertainties encountered.

Concurrent sexual partnerships among female sex workers and their non-commercial male partners in Tijuana and Ciudad Juarez, Mexico.

PubMed

Robertson, Angela Marie; Syvertsen, Jennifer L; Rangel, M Gudelia; Staines, Hugo S; Morris, Martina; Patterson, Thomas L; Ulibarri, Monica D; Strathdee, Steffanie A

2013-06-01

To investigate the prevalence and correlates of concurrent (overlapping) sexual partnerships among female sex workers (FSWs) and their non-commercial male partners in two Mexico-US border cities. A cross-sectional survey of FSWs and their non-commercial male partners was conducted in Tijuana and Ciudad Juárez, Mexico (2010-2011). Eligible FSWs and verified non-commercial partners were aged ≥18 years; FSWs had ever used hard drugs (lifetime) and recently exchanged sex for money, drugs or other goods (past month). Participants underwent baseline questionnaires obtaining dates of sex and condom use with ≤5 other recurring partners, including FSWs' regular clients. These dates were compared with dates of sex with enrolled study partners to determine overlap (ie, 'recurring' concurrency). Bivariate probit regression identified recurring concurrency correlates. Among 428 individuals (214 couples), past-year recurring concurrency prevalence was 16% and was higher among women than their non-commercial male partners (26% vs 6%). In 10 couples (5%), both partners reported recurring concurrency. The majority of couples (64%) always had unprotected sex, and most of the individuals (70%) with recurring concurrency 'sometimes' or 'never' used condoms with their concurrent partners. Recurring concurrency was positively associated with FSWs' income, men's caballerismo (a form of traditional masculinity) and men's belief that their FSW partners had sexually transmitted infections (STIs). Recurring concurrency, representing sustained periods of overlapping partnerships in which unprotected sex was common, should be addressed by couple-based STI prevention interventions.

Understanding Employee Awareness of Health Care Quality Information: How Can Employers Benefit?

PubMed Central

Abraham, Jean; Feldman, Roger; Carlin, Caroline

2004-01-01

Objective To analyze the factors associated with employee awareness of employer-disseminated quality information on providers. Data Sources Primary data were collected in 2002 on a stratified, random sample of 1,365 employees in 16 firms that are members of the Buyers Health Care Action Group (BHCAG) located in the Minneapolis–St. Paul region. An employer survey was also conducted to assess how employers communicated the quality information to employees. Study Design In 2001, BHCAG sponsored two programs for reporting provider quality. We specify employee awareness of the quality information to depend on factors that influence the benefits and costs of search. Factors influencing the benefits include age, sex, provider satisfaction, health status, job tenure, and Twin Cities tenure. Factors influencing search costs include employee income, education, and employer communication strategies. We estimate the model using bivariate probit analysis. Data Collection Employee data were collected by phone survey. Principal Findings Overall, the level of quality information awareness is low. However, employer communication strategies such as distributing booklets to all employees or making them available on request have a large effect on the probability of quality information awareness. Employee education and utilization of providers' services are also positively related to awareness. Conclusions This study is one of the first to investigate employee awareness of provider quality information. Given the direct implications for medical outcomes, one might anticipate higher rates of awareness regarding provider quality, relative to plan quality. However, we do not find empirical evidence to support this assertion. PMID:15533188

Household-Level Determinants of Soil and Water Conservation Adoption Phases: Evidence from North-Western Ethiopian Highlands.

PubMed

Teshome, Akalu; de Graaff, Jan; Kassie, Menale

2016-03-01

Soil and water conservation (SWC) practices have been promoted in the highlands of Ethiopia during the last four decades. However, the level of adoption of SWC practices varies greatly. This paper examines the drivers of different stages of adoption of SWC technologies in the north-western highlands of Ethiopia. This study is based on a detailed farm survey among 298 households in three watersheds. Simple descriptive statistics were applied to analyze the stages of adoption. An ordered probit model was used to analyze the drivers of different stages of adoption of SWC. This model is used to analyze more than two outcomes of an ordinal dependent variable. The results indicate that sampled households are found in different phases of adoption, i.e., dis-adoption/non-adoption (18.5 %), initial adoption (30.5 %), actual adoption (20.1 %), and final adoption (30.9 %). The results of the ordered probit model show that some socio-economic and institutional factors affect the adoption phases of SWC differently. Farm labor, parcel size, ownership of tools, training in SWC, presence of SWC program, social capital (e.g., cooperation with adjacent farm owners), labor sharing scheme, and perception of erosion problem have a significant positive influence on actual and final adoption phases of SWC. In addition, the final adoption phase of SWC is positively associated with tenure security, cultivated land sizes, parcel slope, and perception on SWC profitability. Policy makers should take into consideration factors affecting (continued) adoption of SWC such as profitability, tenure security, social capital, technical support, and resource endowments (e.g., tools and labor) when designing and implementing SWC policies and programs.

Household-Level Determinants of Soil and Water Conservation Adoption Phases: Evidence from North-Western Ethiopian Highlands

NASA Astrophysics Data System (ADS)

Teshome, Akalu; de Graaff, Jan; Kassie, Menale

2016-03-01

Soil and water conservation (SWC) practices have been promoted in the highlands of Ethiopia during the last four decades. However, the level of adoption of SWC practices varies greatly. This paper examines the drivers of different stages of adoption of SWC technologies in the north-western highlands of Ethiopia. This study is based on a detailed farm survey among 298 households in three watersheds. Simple descriptive statistics were applied to analyze the stages of adoption. An ordered probit model was used to analyze the drivers of different stages of adoption of SWC. This model is used to analyze more than two outcomes of an ordinal dependent variable. The results indicate that sampled households are found in different phases of adoption, i.e., dis-adoption/non-adoption (18.5 %), initial adoption (30.5 %), actual adoption (20.1 %), and final adoption (30.9 %). The results of the ordered probit model show that some socio-economic and institutional factors affect the adoption phases of SWC differently. Farm labor, parcel size, ownership of tools, training in SWC, presence of SWC program, social capital (e.g., cooperation with adjacent farm owners), labor sharing scheme, and perception of erosion problem have a significant positive influence on actual and final adoption phases of SWC. In addition, the final adoption phase of SWC is positively associated with tenure security, cultivated land sizes, parcel slope, and perception on SWC profitability. Policy makers should take into consideration factors affecting (continued) adoption of SWC such as profitability, tenure security, social capital, technical support, and resource endowments (e.g., tools and labor) when designing and implementing SWC policies and programs.

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

Carson, K.S.

The presence of overpopulation or unsustainable population growth may place pressure on the food and water supplies of countries in sensitive areas of the world. Severe air or water pollution may place additional pressure on these resources. These pressures may generate both internal and international conflict in these areas as nations struggle to provide for their citizens. Such conflicts may result in United States intervention, either unilaterally, or through the United Nations. Therefore, it is in the interests of the United States to identify potential areas of conflict in order to properly train and allocate forces. The purpose of thismore » research is to forecast the probability of conflict in a nation as a function of it s environmental conditions. Probit, logit and ordered probit models are employed to forecast the probability of a given level of conflict. Data from 95 countries are used to estimate the models. Probability forecasts are generated for these 95 nations. Out-of sample forecasts are generated for an additional 22 nations. These probabilities are then used to rank nations from highest probability of conflict to lowest. The results indicate that the dependence of a nation`s economy on agriculture, the rate of deforestation, and the population density are important variables in forecasting the probability and level of conflict. These results indicate that environmental variables do play a role in generating or exacerbating conflict. It is unclear that the United States military has any direct role in mitigating the environmental conditions that may generate conflict. A more important role for the military is to aid in data gathering to generate better forecasts so that the troops are adequntely prepared when conflicts arises.« less

Two-vehicle injury severity models based on integration of pavement management and traffic engineering factors.

PubMed

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

2013-01-01

The severity of traffic-related injuries has been studied by many researchers in recent decades. However, the evaluation of many factors is still in dispute and, until this point, few studies have taken into account pavement management factors as points of interest. The objective of this article is to evaluate the combined influences of pavement management factors and traditional traffic engineering factors on the injury severity of 2-vehicle crashes. This study examines 2-vehicle rear-end, sideswipe, and angle collisions that occurred on Tennessee state routes from 2004 to 2008. Both the traditional ordered probit (OP) model and Bayesian ordered probit (BOP) model with weak informative prior were fitted for each collision type. The performances of these models were evaluated based on the parameter estimates and deviances. The results indicated that pavement management factors played identical roles in all 3 collision types. Pavement serviceability produces significant positive effects on the severity of injuries. The pavement distress index (PDI), rutting depth (RD), and rutting depth difference between right and left wheels (RD_df) were not significant in any of these 3 collision types. The effects of traffic engineering factors varied across collision types, except that a few were consistently significant in all 3 collision types, such as annual average daily traffic (AADT), rural-urban location, speed limit, peaking hour, and light condition. The findings of this study indicated that improved pavement quality does not necessarily lessen the severity of injuries when a 2-vehicle crash occurs. The effects of traffic engineering factors are not universal but vary by the type of crash. The study also found that the BOP model with a weak informative prior can be used as an alternative but was not superior to the traditional OP model in terms of overall performance.

Wrong-way driving crashes: A random-parameters ordered probit analysis of injury severity.

PubMed

Jalayer, Mohammad; Shabanpour, Ramin; Pour-Rouholamin, Mahdi; Golshani, Nima; Zhou, Huaguo

2018-04-23

In the context of traffic safety, whenever a motorized road user moves against the proper flow of vehicle movement on physically divided highways or access ramps, this is referred to as wrong-way driving (WWD). WWD is notorious for its severity rather than frequency. Based on data from the U.S. National Highway Traffic Safety Administration, an average of 355 deaths occur in the U.S. each year due to WWD. This total translates to 1.34 fatalities per fatal WWD crashes, whereas the same rate for other crash types is 1.10. Given these sobering statistics, WWD crashes, and specifically their severity, must be meticulously analyzed using the appropriate tools to develop sound and effective countermeasures. The objectives of this study were to use a random-parameters ordered probit model to determine the features that best describe WWD crashes and to evaluate the severity of injuries in WWD crashes. This approach takes into account unobserved effects that may be associated with roadway, environmental, vehicle, crash, and driver characteristics. To that end and given the rareness of WWD events, 15 years of crash data from the states of Alabama and Illinois were obtained and compiled. Based on this data, a series of contributing factors including responsible driver characteristics, temporal variables, vehicle characteristics, and crash variables are determined, and their impacts on the severity of injuries are explored. An elasticity analysis was also performed to accurately quantify the effect of significant variables on injury severity outcomes. According to the obtained results, factors such as driver age, driver condition, roadway surface conditions, and lighting conditions significantly contribute to the injury severity of WWD crashes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Measuring public understanding on Tenaga Nasional Berhad (TNB) electricity bills using ordered probit model

NASA Astrophysics Data System (ADS)

Zainudin, WNRA; Ramli, NA

2017-09-01

In 2016, Tenaga Nasional Berhad (TNB) had introduced an upgrade in its Billing and Customer Relationship Management (BCRM) as part of its long-term initiative to provide its customers with greater access to billing information. This includes information on real and suggested power consumption by the customers and further details in their billing charges. This information is useful to help TNB customers to gain better understanding on their electricity usage patterns and items involved in their billing charges. Up to date, there are not many studies done to measure public understanding on current electricity bills and whether this understanding could contribute towards positive impacts. The purpose of this paper is to measure public understanding on current TNB electricity bills and whether their satisfaction towards energy-related services, electricity utility services, and their awareness on the amount of electricity consumed by various appliances and equipment in their home could improve this understanding on the electricity bills. Both qualitative and quantitative research methods are used to achieve these objectives. A total of 160 respondents from local universities in Malaysia participated in a survey used to collect relevant information. Using Ordered Probit model, this paper finds respondents that are highly satisfied with the electricity utility services tend to understand their electricity bills better. The electric utility services include management of electricity bills and the information obtained from utility or non-utility supplier to help consumers manage their energy usage or bills. Based on the results, this paper concludes that the probability to understand the components in the monthly electricity bill increases as respondents are more satisfied with their electric utility services and are more capable to value the energy-related services.

Measuring public acceptance on renewable energy (RE) development in Malaysia using ordered probit model

NASA Astrophysics Data System (ADS)

Zainudin, W. N. R. A.; Ishak, W. W. M.

2017-09-01

In 2009, government of Malaysia has announced a National Renewable Energy Policy and Action Plan as part of their commitment to accelerate the growth in renewable energies (RE). However, an adoption of RE as a main source of energy is still at an early stage due to lack of public awareness and acceptance on RE. Up to date, there are insufficient studies done on the reasons behind this lack of awareness and acceptance. Therefore, this paper is interested to investigate the public acceptance towards development of RE by measuring their willingness to pay slightly more for energy generated from RE sources, denote as willingness level and whether the importance for the electricity to be supplied at absolute lowest possible cost regardless of source and environmental impact, denote as importance level and other socio-economic factors could improve their willingness level. Both qualitative and quantitative research methods are used to achieve the research objectives. A total of 164 respondents from local universities in Malaysia participated in a survey to collect this relevant information. Using Ordered Probit model, the study shows that among the relevant socio-economic factors, age seems to be an important factor to influence the willingness level of the respondents. This paper concludes that younger generation are more willing to pay slightly more for energy generated from RE sources as compared to older generation. One of the possible reason may due to better information access by the younger generation on the RE issues and its positive implication to the world. Finding from this paper is useful to help policy maker in designing RE advocacy programs that would be able to secure public participation. These efforts are important to ensure future success of the RE policy.

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

PubMed

Peñagaricano, F; Urioste, J I; Naya, H; de los Campos, G; Gianola, D

2011-04-01

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep. © 2010 Blackwell Verlag GmbH.

Measuring multiple spike train synchrony.

PubMed

Kreuz, Thomas; Chicharro, Daniel; Andrzejak, Ralph G; Haas, Julie S; Abarbanel, Henry D I

2009-10-15

Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.

Menarcheal age of girls from dysfunctional families.

PubMed

Toromanović, Alma; Tahirović, Husref

2004-07-01

The objective of the present study was to determine median age at menarche and the influence of familial instability on maturation. The sample included 7047 girls between the ages of 9 and 17 years from Tuzla Canton. The girls were divided into two groups. Group A (N=5230) comprised girls who lived in families free of strong traumatic events. Group B (N=1817) included girls whose family dysfunction exposed them to prolonged distress. Probit analysis was performed to estimate mean menarcheal age using the Probit procedure of SAS package. The mean menarcheal age calculated by probit analysis for all the girls studied was 13.07 years. In girls from dysfunctional families a very clear shift toward earlier maturation was observed. The mean age at menarche for group B was 13.0 years, which was significantly lower that that for group A, 13.11 years (t=2.92, P<0.01). The results surveyed here lead to the conclusion that girls from dysfunctional families mature not later but even earlier than girls from normal families. This supports the hypothesis that stressful childhood life events accelerate maturation of girls.

Does Eating Out Make Elderly People Depressed? Empirical Evidence from National Health and Nutrition Survey in Taiwan.

PubMed

Chang, Hung-Hao; Saeliw, Kannika

2017-06-01

This study investigates the association between eating out and depressive symptoms among elderly people. Potential mediators that may link to elderly eating out and depressive symptoms are also discussed. A unique dataset of 1,184 individuals aged 65 and older was drawn from the National Health and Nutrition Survey in 2008 in Taiwan. A bivariate probit model and an instrumental variable probit model were estimated to account for correlated, unmeasured factors that may be associated with both the decision and frequency of eating out and depressive symptoms in the elderly. An additional analysis is conducted to check whether the nutrient intakes and body weights can been seen as mediators that link the association between eating out and depressive symptoms of the elderly. Elderly people who eat out are 38 percent points more likely to have depressive symptoms than their counterparts who do not eat out, after controlling for socio-demographic characteristics and other factors. A positive association between the frequency of eating out and the likelihood of having depressive symptoms of the elderly is also found. It is evident that one addition meal away from home is associated with an increase of the likelihood of being depressed by 3.8 percentage points. With respect to the mediations, we find that nutrient intakes and body weight are likely to serve as mediators for the positive relationship between eating out and depressive symptoms in the elderly. Our results show that elderly who eat out have a higher chance of having depressive symptoms. To prevent depressive symptoms in the elderly, policy makers should be aware of the relationship among psychological status, physical health and nutritional health when assisting the elderly to better manage their food consumption away from home. Our study have some caveats. First, the interpretation of our results on the causality issue calls for caution in that our analysis relies on a cross-sectional survey. Second, other measures to define elderly depression, such as the Center for Epidemiological Studies-Depression (CES-D) score, can be used to check the robustness of our findings. Finally, the availability of food outlets in the local area and family characteristics are possibly associated with food away from home of the elderly. If data permit, the relationship between eating out and elderly depressive symptoms can be better identified after controlling for variables related to food facilities and family characteristics.

Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

PubMed

Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

2015-09-01

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

Modeling hardwood crown radii using circular data analysis

Treesearch

Paul F. Doruska; Hal O. Liechty; Douglas J. Marshall

2003-01-01

Cylindrical data are bivariate data composed of a linear and an angular component. One can use uniform, first-order (one maximum and one minimum) or second-order (two maxima and two minima) models to relate the linear component to the angular component. Crown radii can be treated as cylindrical data when the azimuths at which the radii are measured are also recorded....

Socioeconomic Status and Self-Reported Chronic Diseases Among Argentina's Adult Population: Results Based on Multivariate Probability Models

PubMed Central

Viego, Valentina; Temporelli, Karina

2017-01-01

Background Hypertension, diabetes and hypercholesterolemia are the most frequent and diagnosed chronic diseases in Argentina. They contribute largely to the burden of chronic disease and they are strongly influenced by a small number of risk factors. These risk factors are all modifiable at the population and individual level and offer major prospects for their prevention. We are interested in socioeconomic determinants of prevalence of those 3 specific diseases. Design and methods We estimate 3-equation probit model, combined with 3 separate probit estimations and a probit-based Heckman correction considering possible sample selection bias. Estimations were carried out using secondary self-reported data coming from the 2013 Risk Factor National Survey. Results We find a negative association between socioeconomic status and prevalence of hypertension, cholesterolemia and diabetes; main increases concentrate in the transition from low to high SES in hypertension and diabetes. In cholesterol, the major effect takes place when individual crosses from low to middle SES and then vanishes. Anyway, in Argentina SES exhibit and independent effect on chronic diseases apart from those based on habits and body weight. Conclusions Public strategies to prevent chronic diseases must be specially targeted at women, poorest households and the least educated individuals in order to achieve efficacy. Also, as the probability of having a condition related to excessive blood pressure, high levels of cholesterol or glucose in the blood do not increase proportionally with age, so public campaigns promoting healthy diets, physical activity and medical checkups should be focused on young individuals to facilitate prophylaxis. Significance for public health Latin American countries are going through an epidemiological transition where infectious illnesses are being superseded by chronic diseases which, in turn, are related to lifestyles and socioeconomic factors. Specificities in the relationship between chronic diseases and socioeconomic status have been recorded in high income countries, but has not been sufficiently studied in low and middle income countries. We believe that analysis grounded on large scale datasets, recently available in Argentina, and based on proper statistical tools can provide useful guidance for decision making in public health policies as they highlight where population needs and risks do concentrate. PMID:28785549

Review Of Implementation In Bunut Shoes Assistance Program In Order Of Micro, Small And Medium Enterprises Economic In Asahan Regency

NASA Astrophysics Data System (ADS)

Saleh Malawat, M.; Putra, M. Umar Maya

2018-03-01

This paper studies the implementation of business opportunities that can improve the revenue of Bunut Shoes Micro, Small and Medium Enterprises. Probit model with E Views 6 program was used to see how far the opportunity of variable efforts to improve the revenue such as education, training, capital assistance, technological procurement of them. The data used was the primary data by conducting a survey using questionnaires to members of them with the observation period from 2013 to 2015. The results showed that all variables of implementation did not have a business opportunity correlation to the increase in revenue and Asahan District Governments are asked to create a creative breakthrough in order to achieve optimal business revenue and cooperate with other private institutions related to increase the business income.

Sociodemographic, lifestyle and health determinants of suicidal behaviour in Malaysia.

PubMed

Cheah, Yong Kang; Azahadi, Mohd; Phang, Siew Nooi; Abd Manaf, Noor Hazilah

2018-03-01

Suicide has become a serious matter in both developed and developing countries. The objective of the present study is to examine the factors affecting suicidal behaviour among adults in Malaysia. A nationally representative data which consists of 10,141 respondents is used for analysis. A trivariate probit model is utilised to identify the probability of having suicide ideation, suicide plan and suicide attempt. Results of the regression analysis show that to ensure unbiased estimates, a trivariate probit model should be used instead of three separate probit models. The determining factors of suicidal behaviour are income, age, gender, ethnicity, education, marital status, self-rated health and being diagnosed with diabetes and hypercholesterolemia. The likelihood of adopting suicidal behaviour is lower among higher income earners and older individuals. Being male and married significantly reduce the propensity to engage in suicidal behaviour. Of all the ethnic groups, Indian/others displays the highest likelihood of adopting suicidal behaviour. There is a positive relationship between poor health condition and suicide. Policies targeted at individuals who are likely to adopt suicidal behaviour may be effective in lowering the prevalence of suicide. Copyright © 2018 Elsevier B.V. All rights reserved.

Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling

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

Li Yupeng, E-mail: yupeng@ualberta.ca; Deutsch, Clayton V.

2012-06-15

In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells.more » In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.« less

Concurrent sexual partnerships among female sex workers and their non-commercial male partners in Tijuana and Ciudad Juárez, Mexico

PubMed Central

Robertson, Angela M.; Syvertsen, Jennifer L.; Rangel, M. Gudelia; Staines, Hugo S.; Morris, Martina; Patterson, Thomas L.; Ulibarri, Monica D.; Strathdee, Steffanie A.

2013-01-01

Objectives To investigate the prevalence and correlates of concurrent (overlapping) sexual partnerships among female sex workers (FSWs) and their non-commercial male partners in two Mexico-U.S. border cities. Methods A cross-sectional survey of FSWs and their non-commercial male partners was conducted in Tijuana and Ciudad Juárez, Mexico (2010–2011). Eligible FSWs and verified non-commercial partners were aged ≥18 years; FSWs had ever used hard drugs (lifetime) and recently exchanged sex for money, drugs, or other goods (past month). Participants underwent baseline questionnaires obtaining dates of sex and condom use with ≤5 other recurring partners, including FSWs’ regular clients. These dates were compared to dates of sex with enrolled study partners to determine overlap (i.e., “recurring” concurrency). Bivariate probit regression identified recurring concurrency correlates. Results Among 428 individuals (214 couples), past-year recurring concurrency prevalence was 16% and was higher among women than their non-commercial male partners (26% vs. 6%). In 10 couples (5%), both partners reported recurring concurrency. The majority of couples (64%) always had unprotected sex, and most of the individuals (70%) with recurring concurrency “sometimes” or “never” used condoms with their concurrent partners. Recurring concurrency was positively associated with FSWs’ income, men’s caballerismo (a form of traditional masculinity), and men’s belief that their FSW-partners had STIs. Conclusions Recurring concurrency, representing sustained periods of overlapping partnerships in which unprotected sex was common, should be addressed by couple-based STI prevention interventions. PMID:23172036

Measuring Preferences for a Diabetes Pay-for-Performance for Patient (P4P4P) Program using a Discrete Choice Experiment.

PubMed

Chen, Tsung-Tai; Tung, Tao-Hsin; Hsueh, Ya-Seng Arthur; Tsai, Ming-Han; Liang, Hsiu-Mei; Li, Kay-Lun; Chung, Kuo-Piao; Tang, Chao-Hsiun

2015-07-01

To elicit a patient's willingness to participate in a diabetes pay-for-performance for patient (P4P4P) program using a discrete choice experiment method. The survey was conducted in March 2013. Our sample was drawn from patients with diabetes at five hospitals in Taiwan (International Classification of Diseases, Ninth Revision, Clinical Modification code 250). The sample size was 838 patients. The discrete choice experiment questionnaire included the attributes monthly cash rewards, exercise time, diet control, and program duration. We estimated a bivariate probit model to derive willingness-to-accept levels after accounting for the characteristics (e.g., severity and comorbidity) of patients with diabetes. The preferred program was a 3-year program involving 30 minutes of exercise per day and flexible diet control. Offering an incentive of approximately US $67 in cash per month appears to increase the likelihood that patients with diabetes will participate in the preferred P4P4P program by approximately 50%. Patients with more disadvantageous characteristics (e.g., elderly, low income, greater comorbidity, and severity) could have less to gain from participating in the program and thus require a higher monetary incentive to compensate for the disutility caused by participating in the program's activities. Our result demonstrates that a modest financial incentive could increase the likelihood of program participation after accounting for the attributes of the P4P4P program and patients' characteristics. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Identification of Caries Risk Determinants in Toddlers: Results of the GUSTO birth cohort study

PubMed Central

Un Lam, C.; Khin, L.W.; Kalhan, A.C.; Yee, R.; Lee, Y.S.; Chong, M.F-F.; Kwek, K.; Saw, S.M.; Godfrey, K.; Chong, Y.S.; Hsu, C-Y.

2017-01-01

The aim of the study was to identify risk determinants leading to early childhood caries (ECC) and visible plaque (VP) in toddlers. Data for mother-child pairs participating in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort were collected from pregnancy to toddlerhood. Oral examinations were performed in 543 children during their clinic visit at 24 months to detect ECC and VP. Following logistic regression, ECC and VP were jointly regressed as primary and secondary outcomes, respectively, using bivariate probit model. ECC prevalence was 17.8% at 2 years of age, with 7.3% of children having a VP score >1. ECC was associated with night-time breastfeeding (3 weeks) and biological factors, including Indian ethnicity (lower ECC rate), higher maternal childbearing age and existing health conditions, maternal plasma folate <6 ng/mL, child BMI and plaque index, while VP was associated with psycho-behavioural factors, including frequency of dental visits, brushing frequency, lower parental perceived importance of baby teeth, and weaning onto solids. Interestingly, although higher frequency of dental visits and tooth-brushing were associated with lower plaque accumulation, they were associated with increased ECC risk, suggesting that these established caries-risk factors may be a consequence rather than the cause of ECC. In conclusion, Indian toddlers may be less susceptible to ECC, compared to Chinese and Malay toddlers. The study also highlights a problem-driven utilization pattern of dental services (care sought for treatment) in Singapore, in contrast to the prevention-driven approach (care sought to prevent disease) in Western countries. PMID:28538220

Factors associated with past research participation among low-income persons living with HIV.

PubMed

Slomka, Jacquelyn; Kypriotakis, Georgios; Atkinson, John; Diamond, Pamela M; Williams, Mark L; Vidrine, Damon J; Andrade, Roberto; Arduino, Roberto

2012-08-01

We described influences on past research participation among low-income persons living with HIV (PLWH) and examined whether such influences differed by study type. We analyzed a convenience sample of individuals from a large, urban clinic specializing in treating low-income PLWH. Using a computer-assisted survey, we elicited perceptions of research and participating in research, barriers, benefits, "trigger" influences, and self-efficacy in participating in research. Of 193 participants, we excluded 14 who did not identify any type of study participation, and 17 who identified "other" as study type, resulting in 162 cases for analysis. We compared results among four groups (i.e., 6 comparisons): past medical participants (n=36, 22%), past behavioral participants (n=49, 30%), individuals with no past research participation (n=52, 32%), and persons who had participated in both medical and behavioral studies (n=25, 15%). Data were analyzed using chi-square tests for categorical variables and ANOVA for continuous variables. We employed a multinomial probit (MNP) model to examine the association of multiple factors with the outcome. Confidence in ability to keep appointments, and worry about being a 'guinea pig' showed statistical differences in bivariate analyses. The MNP regression analysis showed differences between and across all 6 comparison groups. Fewer differences were seen across groupings of medical participants, behavioral participants, and those with no past research experience, than in comparisons with the medical-behavioral group. In the MNP regression model 'age' and level of certainty regarding 'keeping yourself from being a guinea pig' showed significant differences between past medical participants and past behavioral participants.

The link between past informal payments and willingness of the Hungarian population to pay formal fees for health care services: results from a contingent valuation study.

PubMed

Baji, Petra; Pavlova, Milena; Gulácsi, László; Farkas, Miklós; Groot, Wim

2014-11-01

We examine the willingness of health care consumers to pay formal fees for health care use and how this willingness to pay is associated with past informal payments. We use data from a survey carried out in Hungary in 2010 among a representative sample of 1,037 respondents. The contingent valuation method is used to elicit the willingness to pay official charges for health care services covered by the social health insurance if certain quality attributes (regarding the health care facility, access to the services and health care personnel) are guaranteed. A bivariate probit model is applied to examine the relationship between willingness to pay and past informal payments. We find that 66% of the respondents are willing to pay formal fees for specialist examinations and 56% are willing to pay for planned hospitalizations if these services are provided with certain quality and access attributes. The act of making past informal payments for health care services is positively associated with the willingness to pay formal charges. The probability that a respondent is willing to pay official charges for health care services is 22% points higher for specialist examinations and 45% points higher for hospitalization if the respondent paid informally during the last 12 months. The introduction of formal fees should be accompanied by adequate service provision to assure acceptance of the fees. Furthermore, our results suggest that the problem of informal patient payments may remain even after the implementation of user fees.

Religious Involvement and the Use of Mental Health Care

PubMed Central

Harris, Katherine M; Edlund, Mark J; Larson, Sharon L

2006-01-01

Objectives To examine the association between religious involvement and mental health care use by adults age 18 or older with mental health problems. Methods We used data from the 2001–2003 National Surveys on Drug Use and Health. We defined two subgroups with moderate (n=49,902) and serious mental or emotional distress (n=14,548). For each subgroup, we estimated a series of bivariate probit models of past year use of outpatient care and prescription medications using indicators of the frequency of religious service attendance and two measures of the strength and influence of religious beliefs as independent variables. Covariates included common Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, disorders symptoms, substance use and related disorders, self-rated health status, and sociodemographic characteristics. Results Among those with moderate distress, we found some evidence of a positive relationship between religious service attendance and outpatient mental health care use and of a negative relationship between the importance of religious beliefs and outpatient use. Among those with serious distress, use of outpatient care and medication was more strongly associated with service attendance and with the importance of religious beliefs. By contrast, we found a negative association between outpatient use and the influence of religious beliefs on decisions. Conclusion The positive relationship between religious service participation and service use for those with serious distress suggests that policy initiatives aimed at increasing the timely and appropriate use of mental health care may be able to build upon structures and referral processes that currently exist in many religious organizations. PMID:16584455

Identification of Caries Risk Determinants in Toddlers: Results of the GUSTO Birth Cohort Study.

PubMed

Un Lam, C; Khin, L W; Kalhan, A C; Yee, R; Lee, Y S; Chong, M F-F; Kwek, K; Saw, S M; Godfrey, K; Chong, Y S; Hsu, C-Y

2017-01-01

The aim of this study was to identify risk determinants leading to early childhood caries (ECC) and visible plaque (VP) in toddlers. Data for mother-child pairs participating in the Growing Up in Singapore towards Healthy Outcomes (GUSTO) birth cohort were collected from pregnancy to toddlerhood. Oral examinations were performed in 543 children during their clinic visit at 24 months to detect ECC and VP. Following logistic regression, ECC and VP were jointly regressed as primary and secondary outcomes, respectively, using the bivariate probit model. The ECC prevalence was 17.8% at 2 years of age, with 7.3% of children having a VP score >1. ECC was associated with nighttime breastfeeding (3 weeks) and biological factors, including Indian ethnicity (lower ECC rate), higher maternal childbearing age and existing health conditions, maternal plasma folate <6 ng/mL, child BMI, and the plaque index, while VP was associated with psychobehavioral factors, including the frequency of dental visits, brushing frequency, lower parental perceived importance of baby teeth, and weaning onto solids. Interestingly, although a higher frequency of dental visits and toothbrushing were associated with lower plaque accumulation, they were associated with increased ECC risk, suggesting that these established caries-risk factors may be a consequence rather than the cause of ECC. In conclusion, Indian toddlers may be less susceptible to ECC, compared to Chinese and Malay toddlers. The study also highlights a problem-driven utilization pattern of dental services (care sought for treatment) in Singapore, in contrast to the prevention-driven approach (care sought to prevent disease) in Western countries. © 2017 S. Karger AG, Basel.

Exploring High-D Spaces with Multiform Matrices and Small Multiples

PubMed Central

MacEachren, Alan; Dai, Xiping; Hardisty, Frank; Guo, Diansheng; Lengerich, Gene

2011-01-01

We introduce an approach to visual analysis of multivariate data that integrates several methods from information visualization, exploratory data analysis (EDA), and geovisualization. The approach leverages the component-based architecture implemented in GeoVISTA Studio to construct a flexible, multiview, tightly (but generically) coordinated, EDA toolkit. This toolkit builds upon traditional ideas behind both small multiples and scatterplot matrices in three fundamental ways. First, we develop a general, MultiForm, Bivariate Matrix and a complementary MultiForm, Bivariate Small Multiple plot in which different bivariate representation forms can be used in combination. We demonstrate the flexibility of this approach with matrices and small multiples that depict multivariate data through combinations of: scatterplots, bivariate maps, and space-filling displays. Second, we apply a measure of conditional entropy to (a) identify variables from a high-dimensional data set that are likely to display interesting relationships and (b) generate a default order of these variables in the matrix or small multiple display. Third, we add conditioning, a kind of dynamic query/filtering in which supplementary (undisplayed) variables are used to constrain the view onto variables that are displayed. Conditioning allows the effects of one or more well understood variables to be removed from the analysis, making relationships among remaining variables easier to explore. We illustrate the individual and combined functionality enabled by this approach through application to analysis of cancer diagnosis and mortality data and their associated covariates and risk factors. PMID:21947129

Lethal Temperature for Pinewood Nematode, Bursaphelenchus xylophilus, in Infested Wood Using Microwave Energy

PubMed Central

Hoover, Kelli; Uzunovic, Adnan; Gething, Brad; Dale, Angela; Leung, Karen; Ostiguy, Nancy; Janowiak, John J.

2010-01-01

To reduce the risks associated with global transport of wood infested with pinewood nematode Bursaphelenchus xylophilus, microwave irradiation was tested at 14 temperatures in replicated wood samples to determine the temperature that would kill 99.9968% of nematodes in a sample of ≥ 100,000 organisms, meeting a level of efficacy of Probit 9. Treatment of these heavily infested wood samples (mean of > 1,000 nematodes/g of sapwood) produced 100% mortality at 56 °C and above, held for 1 min. Because this “brute force” approach to Probit 9 treats individual nematodes as the observational unit regardless of the number of wood samples it takes to treat this number of organisms, we also used a modeling approach. The best fit was to a Probit function, which estimated lethal temperature at 62.2 (95% confidence interval 59.0-70.0) °C. This discrepancy between the observed and predicted temperature to achieve Probit 9 efficacy may have been the result of an inherently limited sample size when predicting the true mean from the total population. The rate of temperature increase in the small wood samples (rise time) did not affect final nematode mortality at 56 °C. In addition, microwave treatment of industrial size, infested wood blocks killed 100% of > 200,000 nematodes at ≥ 56 °C held for 1 min in replicated wood samples. The 3rd-stage juvenile (J3) of the nematode, that is resistant to cold temperatures and desiccation, was abundant in our wood samples and did not show any resistance to microwave treatment. Regression analysis of internal wood temperatures as a function of surface temperature produced a regression equation that could be used with a relatively high degree of accuracy to predict internal wood temperatures, under the conditions of this study. These results provide strong evidence of the ability of microwave treatment to successfully eradicate B. xylophilus in infested wood at or above 56 °C held for 1 min. PMID:22736846

Migration plans of the rural populations of the Third World countries: a probit analysis of micro-level data from Asia, Africa, and Latin America.

PubMed

Mcdevitt, T M; Hawley, A H; Udry, J R; Gadalla, S; Leoprapai, B; Cardona, R

1986-07-01

This study 1) examines the extent to which a given set of microlevel factors has predictive value in different socioeconomic settings and 2) demonstrates the utility of a probit estimation technique in examining plans of rural populations to migrate. Data were collected in 1977-1979 in Thailand, Egypt, and Colombia, 3 countries which differ in culture, extent of urbanization, and proportion of labor force engaged in nonextractive industries. The researchers used identical questionnaires and obtained interviews in 4 rural villages with the "migration shed" of each country's capital city. There were 1088 rural-resident men and women interviewed in Thailand, 1088 in Colombia, and 1376 in Egypt. The researchers gathered information about year-to-year changes in residence, marital status, fertility, housing, employment status, occupation, and industry. While in all 3 countries return moves are relatively frequent, especially among males, the proportions of migrants who have moved 3 or more times do not rise above 10%. The model used portrays the formation of migration intentions of the individual as the outcome of a decision process involving the subjective weighing of perceived differentials in well-being associated with current residence and 1 or more potential destinations, taking into account the direct relocation costs and ability to finance a move. The researchers used dichotomous probit and ordinal probit techniques and 4 variations on the dependant variable to generate some of the results. The only expectancy variable significant in all countries is age. Education is also positively and significantly associated with intentions to move for both sexes in Colombia and Egypt. Marital status is a deterrent to migration plans for males in Colombia and both sexes in Egypt. Previous migration experience fails to show any significant relationship to propensity to move. Conclusions drawn from the data include: 1) the effects of age and economic status appear to increase, both in strength and significance, for males in countries as the likelihood of a move increases; and 2) the effect of the kin and friend contract variable in Colombia appears to be related to its usefulness in explaining th initial consideration of a move rather than the plans that carry a probability or certainty of implementation. The careful measurement of strength of migration intentions and the application of ordinal probit estimation methods to the analysis of prospective migration may contribute to the refinement of our understanding of the process of migration decision making across a range of geographical, cultural, and developmental contexts.

Household income and preschool attendance in china.

PubMed

Gong, Xin; Xu, Di; Han, Wen-Jui

2015-01-01

This article draws upon the literature showing the benefits of high-quality preschools on child well-being to explore the role of household income on preschool attendance for a cohort of 3- to 6-year-olds in China using data from the China Health and Nutrition Survey, 1991-2006. Analyses are conducted separately for rural (N = 1,791) and urban (N = 633) settings. Estimates from a probit model with rich controls suggest a positive association between household income per capita and preschool attendance in both settings. A household fixed-effects model, conducted only on the rural sample, finds results similar to, although smaller than, those from the probit estimates. Policy recommendations are discussed. © 2014 The Authors. Child Development © 2014 Society for Research in Child Development, Inc.

An improved probit method for assessment of domino effect to chemical process equipment caused by overpressure.

PubMed

Mingguang, Zhang; Juncheng, Jiang

2008-10-30

Overpressure is one important cause of domino effect in accidents of chemical process equipments. Damage probability and relative threshold value are two necessary parameters in QRA of this phenomenon. Some simple models had been proposed based on scarce data or oversimplified assumption. Hence, more data about damage to chemical process equipments were gathered and analyzed, a quantitative relationship between damage probability and damage degrees of equipment was built, and reliable probit models were developed associated to specific category of chemical process equipments. Finally, the improvements of present models were evidenced through comparison with other models in literatures, taking into account such parameters: consistency between models and data, depth of quantitativeness in QRA.

Contractual conditions, working conditions and their impact on health and well-being.

PubMed

Robone, Silvana; Jones, Andrew M; Rice, Nigel

2011-10-01

Given changes in the labour market in past decades, it is of interest to evaluate whether and how contractual and working conditions affect health and psychological well-being in society today. We consider the effects of contractual and working conditions on self-assessed health and psychological well-being using twelve waves (1991/1992-2002/2003) of the British Household Panel Survey. For self-assessed health, the dependent variable is categorical, and we estimate non-linear dynamic panel ordered probit models, while for psychological well-being, we estimate a dynamic linear specification. The results show that both contractual and working conditions have an influence on health and psychological well-being and that the impact is different for men and women.

Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.

PubMed

Wali, Behram; Khattak, Asad J; Xu, Jingjing

2018-01-01

The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability models, the study provides evidence that copula based bivariate models can provide more reliable estimates and richer insights. Practical implications of the results are discussed. Published by Elsevier Ltd.

A Spatial Probit Econometric Model of Land Change: The Case of Infrastructure Development in Western Amazonia, Peru

PubMed Central

Arima, E. Y.

2016-01-01

Tropical forests are now at the center stage of climate mitigation policies worldwide given their roles as sources of carbon emissions resulting from deforestation and forest degradation. Although the international community has created mechanisms such as REDD+ to reduce those emissions, developing tropical countries continue to invest in infrastructure development in an effort to spur economic growth. Construction of roads in particular is known to be an important driver of deforestation. This article simulates the impact of road construction on deforestation in Western Amazonia, Peru, and quantifies the amount of carbon emissions associated with projected deforestation. To accomplish this objective, the article adopts a Bayesian probit land change model in which spatial dependencies are defined between regions or groups of pixels instead of between individual pixels, thereby reducing computational requirements. It also compares and contrasts the patterns of deforestation predicted by both spatial and non-spatial probit models. The spatial model replicates complex patterns of deforestation whereas the non-spatial model fails to do so. In terms of policy, both models suggest that road construction will increase deforestation by a modest amount, between 200–300 km2. This translates into aboveground carbon emissions of 1.36 and 1.85 x 106 tons. However, recent introduction of palm oil in the region serves as a cautionary example that the models may be underestimating the impact of roads. PMID:27010739

A Spatial Probit Econometric Model of Land Change: The Case of Infrastructure Development in Western Amazonia, Peru.

PubMed

Arima, E Y

2016-01-01

Tropical forests are now at the center stage of climate mitigation policies worldwide given their roles as sources of carbon emissions resulting from deforestation and forest degradation. Although the international community has created mechanisms such as REDD+ to reduce those emissions, developing tropical countries continue to invest in infrastructure development in an effort to spur economic growth. Construction of roads in particular is known to be an important driver of deforestation. This article simulates the impact of road construction on deforestation in Western Amazonia, Peru, and quantifies the amount of carbon emissions associated with projected deforestation. To accomplish this objective, the article adopts a Bayesian probit land change model in which spatial dependencies are defined between regions or groups of pixels instead of between individual pixels, thereby reducing computational requirements. It also compares and contrasts the patterns of deforestation predicted by both spatial and non-spatial probit models. The spatial model replicates complex patterns of deforestation whereas the non-spatial model fails to do so. In terms of policy, both models suggest that road construction will increase deforestation by a modest amount, between 200-300 km2. This translates into aboveground carbon emissions of 1.36 and 1.85 x 106 tons. However, recent introduction of palm oil in the region serves as a cautionary example that the models may be underestimating the impact of roads.

Differences between husbands and wives in colonoscopy use: Results from a national sample of married couples.

PubMed

Kotwal, Ashwin A; Lauderdale, Diane S; Waite, Linda J; Dale, William

2016-07-01

Marriage is linked to improved colorectal cancer-related health, likely in part through preventive health behaviors, but it is unclear what role spouses play in colorectal cancer screening. We therefore determine whether self-reported colonoscopy rates are correlated within married couples and the characteristics of spouses associated with colonoscopy use in each partner. We use US nationally-representative 2010 data which includes 804 male-female married couples drawn from a total sample of 3137 community-dwelling adults aged 55-90years old. Using a logistic regression model in the full sample (N=3137), we first find married men have higher adjusted colonoscopy rates than unmarried men (61% versus 52%, p=0.023), but women's rates do not differ by marital status. In the couples' sample (N=804 couples), we use a bivariate probit regression model to estimate multiple regression equations for the two spouses simultaneously as a function of individual and spousal covariates, as well as the adjusted correlation within couples. We find that individuals are nearly twice as likely to receive a colonoscopy if their spouse recently has had one (OR=1.94, 95% CI: 1.39, 2.67, p<0.001). Additionally, we find that husbands have higher adjusted colonoscopy rates whose wives are: 1) happier with the marital relationship (65% vs 51%, p=0.020); 2) more highly educated (72% vs 51%, p=0.020), and 3) viewed as more supportive (65% vs 52%, p=0.020). Recognizing the role of marital status, relationship quality, and spousal characteristics on colonoscopy uptake, particularly in men, could help physicians increase guideline adherence. Copyright © 2016. Published by Elsevier Inc.

Cumulative Head Impact Exposure Predicts Later-Life Depression, Apathy, Executive Dysfunction, and Cognitive Impairment in Former High School and College Football Players.

PubMed

Montenigro, Philip H; Alosco, Michael L; Martin, Brett M; Daneshvar, Daniel H; Mez, Jesse; Chaisson, Christine E; Nowinski, Christopher J; Au, Rhoda; McKee, Ann C; Cantu, Robert C; McClean, Michael D; Stern, Robert A; Tripodis, Yorghos

2017-01-15

The term "repetitive head impacts" (RHI) refers to the cumulative exposure to concussive and subconcussive events. Although RHI are believed to increase risk for later-life neurological consequences (including chronic traumatic encephalopathy), quantitative analysis of this relationship has not yet been examined because of the lack of validated tools to quantify lifetime RHI exposure. The objectives of this study were: 1) to develop a metric to quantify cumulative RHI exposure from football, which we term the "cumulative head impact index" (CHII); 2) to use the CHII to examine the association between RHI exposure and long-term clinical outcomes; and 3) to evaluate its predictive properties relative to other exposure metrics (i.e., duration of play, age of first exposure, concussion history). Participants included 93 former high school and collegiate football players who completed objective cognitive and self-reported behavioral/mood tests as part of a larger ongoing longitudinal study. Using established cutoff scores, we transformed continuous outcomes into dichotomous variables (normal vs. impaired). The CHII was computed for each participant and derived from a combination of self-reported athletic history (i.e., number of seasons, position[s], levels played), and impact frequencies reported in helmet accelerometer studies. A bivariate probit, instrumental variable model revealed a threshold dose-response relationship between the CHII and risk for later-life cognitive impairment (p < 0.0001), self-reported executive dysfunction (p < 0.0001), depression (p < 0.0001), apathy (p = 0.0161), and behavioral dysregulation (p < 0.0001). Ultimately, the CHII demonstrated greater predictive validity than other individual exposure metrics.

Cumulative Head Impact Exposure Predicts Later-Life Depression, Apathy, Executive Dysfunction, and Cognitive Impairment in Former High School and College Football Players

PubMed Central

Montenigro, Philip H.; Alosco, Michael L.; Martin, Brett M.; Daneshvar, Daniel H.; Mez, Jesse; Chaisson, Christine E.; Nowinski, Christopher J.; Au, Rhoda; McKee, Ann C.; Cantu, Robert C.; McClean, Michael D.; Tripodis, Yorghos

2017-01-01

Abstract The term “repetitive head impacts” (RHI) refers to the cumulative exposure to concussive and subconcussive events. Although RHI are believed to increase risk for later-life neurological consequences (including chronic traumatic encephalopathy), quantitative analysis of this relationship has not yet been examined because of the lack of validated tools to quantify lifetime RHI exposure. The objectives of this study were: 1) to develop a metric to quantify cumulative RHI exposure from football, which we term the “cumulative head impact index” (CHII); 2) to use the CHII to examine the association between RHI exposure and long-term clinical outcomes; and 3) to evaluate its predictive properties relative to other exposure metrics (i.e., duration of play, age of first exposure, concussion history). Participants included 93 former high school and collegiate football players who completed objective cognitive and self-reported behavioral/mood tests as part of a larger ongoing longitudinal study. Using established cutoff scores, we transformed continuous outcomes into dichotomous variables (normal vs. impaired). The CHII was computed for each participant and derived from a combination of self-reported athletic history (i.e., number of seasons, position[s], levels played), and impact frequencies reported in helmet accelerometer studies. A bivariate probit, instrumental variable model revealed a threshold dose-response relationship between the CHII and risk for later-life cognitive impairment (p < 0.0001), self-reported executive dysfunction (p < 0.0001), depression (p < 0.0001), apathy (p = 0.0161), and behavioral dysregulation (p < 0.0001). Ultimately, the CHII demonstrated greater predictive validity than other individual exposure metrics. PMID:27029716

PROBIT: A Probit Analysis Program for the DRES (Defence Research Establishment Suffield) Computer Facility,

DTIC Science & Technology

1986-07-01

p are are also discussed. When iteration is terminated, we can determine the effective dose at the A percentile level or EDX ; that is the dose at...corresponds to the lower limit, fl.. The fiducial or Fieller limits on x , i.e., the EDX are then f’ = exp If.1 (36) It can be readily shown that g = t2 v-1...4 .4+ 1W (n 0 CL C ~o 0 0 X U) -W CLW W 24W Q X C W C > VW U)w5 z C z 5memo f- G5555t (j) tSS a;C w CO W QZ 1 I- ~ ~ ~ C (. 5r 5W <A * a W Www w V

Bivariate discrete beta Kernel graduation of mortality data.

PubMed

Mazza, Angelo; Punzo, Antonio

2015-07-01

Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

Regression analysis for bivariate gap time with missing first gap time data.

PubMed

Huang, Chia-Hui; Chen, Yi-Hau

2017-01-01

We consider ordered bivariate gap time while data on the first gap time are unobservable. This study is motivated by the HIV infection and AIDS study, where the initial HIV contracting time is unavailable, but the diagnosis times for HIV and AIDS are available. We are interested in studying the risk factors for the gap time between initial HIV contraction and HIV diagnosis, and gap time between HIV and AIDS diagnoses. Besides, the association between the two gap times is also of interest. Accordingly, in the data analysis we are faced with two-fold complexity, namely data on the first gap time is completely missing, and the second gap time is subject to induced informative censoring due to dependence between the two gap times. We propose a modeling framework for regression analysis of bivariate gap time under the complexity of the data. The estimating equations for the covariate effects on, as well as the association between, the two gap times are derived through maximum likelihood and suitable counting processes. Large sample properties of the resulting estimators are developed by martingale theory. Simulations are performed to examine the performance of the proposed analysis procedure. An application of data from the HIV and AIDS study mentioned above is reported for illustration.

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain.

PubMed

Rabbani, Hossein; Sonka, Milan; Abramoff, Michael D

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR.

An Affine Invariant Bivariate Version of the Sign Test.

DTIC Science & Technology

1987-06-01

words: affine invariance, bivariate quantile, bivariate symmetry, model,. generalized median, influence function , permutation test, normal efficiency...calculate a bivariate version of the influence function , and the resulting form is bounded, as is the case for the univartate sign test, and shows the...terms of a blvariate analogue of IHmpel’s (1974) influence function . The latter, though usually defined as a von-Mises derivative of certain

Causal Mediation Analysis of Survival Outcome with Multiple Mediators.

PubMed

Huang, Yen-Tsung; Yang, Hwai-I

2017-05-01

Mediation analyses have been a popular approach to investigate the effect of an exposure on an outcome through a mediator. Mediation models with multiple mediators have been proposed for continuous and dichotomous outcomes. However, development of multimediator models for survival outcomes is still limited. We present methods for multimediator analyses using three survival models: Aalen additive hazard models, Cox proportional hazard models, and semiparametric probit models. Effects through mediators can be characterized by path-specific effects, for which definitions and identifiability assumptions are provided. We derive closed-form expressions for path-specific effects for the three models, which are intuitively interpreted using a causal diagram. Mediation analyses using Cox models under the rare-outcome assumption and Aalen additive hazard models consider effects on log hazard ratio and hazard difference, respectively; analyses using semiparametric probit models consider effects on difference in transformed survival time and survival probability. The three models were applied to a hepatitis study where we investigated effects of hepatitis C on liver cancer incidence mediated through baseline and/or follow-up hepatitis B viral load. The three methods show consistent results on respective effect scales, which suggest an adverse estimated effect of hepatitis C on liver cancer not mediated through hepatitis B, and a protective estimated effect mediated through the baseline (and possibly follow-up) of hepatitis B viral load. Causal mediation analyses of survival outcome with multiple mediators are developed for additive hazard and proportional hazard and probit models with utility demonstrated in a hepatitis study.

Linking hearing impairment, employment and education.

PubMed

Garramiola-Bilbao, I; Rodríguez-Álvarez, A

2016-12-01

To analyse the impact that hearing impairment and other relevant variables have on the education and employment situation of those affected by it in the Principality of Asturias, Spain. To achieve this objective, two discrete choice models (probit) are presented. The first one associates, among other variables, hearing impairment with the individual's employment status and in the second model, an ordered multinomial probit model is used to analyse, among other variables, how the impairment affects the individual's level of studies. Although the levels of statistical significance are low, the model's estimates appear to indicate that hearing impairment in Spain increases the probability of being unemployed by 18.4% (P = 0.09). Additionally, the people suffering from such a disability are, compared with the rest of the population, 10.2% (P = 0.05) more likely to have only completed elementary studies without pursuing any further education. If an individual is able to reach a level of secondary or higher education thus enabling a future incorporation to the work place, a benefit is obviously generated for both the individual as well as society (which has additionally incurred an investment in human capital). In this regard, encouraging the education of hearing-impaired students would profit both the individual (who receives an early integration as a child), which may contribute positively to family and social factors, as well as society who have incurred the investment. Therefore, our result could indicate that programmes created to support individuals with this type of disability represent an increase of welfare both individually and socially. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I

NASA Astrophysics Data System (ADS)

Lee, Sang-Il

This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient, do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task.

[Use of bivariate survival curves for analyzing mortality of heart failure and sudden death in dilated cardiomiopathy].

PubMed

Gregori, Dario; Rosato, Rosalba; Zecchin, Massimo; Di Lenarda, Andrea

2005-01-01

This paper discusses the use of bivariate survival curves estimators within the competing risk framework. Competing risks models are used for the analysis of medical data with more than one cause of death. The case of dilated cardiomiopathy is explored. Bivariate survival curves plot the conjoint mortality processes. The different graphic representation of bivariate survival analysis is the major contribute of this methodology to the competing risks analysis.

Exploratory Analysis of Survey Data for Understanding Adoption of Novel Aerospace Systems

NASA Astrophysics Data System (ADS)

Reddy, Lauren M.

In order to meet the increasing demand for manned and unmanned flight, the air transportation system must constantly evolve. As new technologies or operational procedures are conceived, we must determine their effect on humans in the system. In this research, we introduce a strategy to assess how individuals or organizations would respond to a novel aerospace system. We employ the most appropriate and sophisticated exploratory analysis techniques on the survey data to generate insight and identify significant variables. We employ three different methods for eliciting views from individuals or organizations who are affected by a system: an opinion survey, a stated preference survey, and structured interviews. We conduct an opinion survey of both the general public and stakeholders in the unmanned aircraft industry to assess their knowledge, attitude, and practices regarding unmanned aircraft. We complete a statistical analysis of the multiple-choice questions using multinomial logit and multivariate probit models and conduct qualitative analysis on free-text questions. We next present a stated preference survey of the general public on the use of an unmanned aircraft package delivery service. We complete a statistical analysis of the questions using multinomial logit, ordered probit, linear regression, and negative binomial models. Finally, we discuss structured interviews conducted on stakeholders from ANSPs and airlines operating in the North Atlantic. We describe how these groups may choose to adopt a new technology (space-based ADS-B) or operational procedure (in-trail procedures). We discuss similarities and differences between the stakeholders groups, the benefits and costs of in-trail procedures and space-based ADS-B as reported by the stakeholders, and interdependencies between the groups interviewed. To demonstrate the value of the data we generated, we explore how the findings from the surveys can be used to better characterize uncertainty in the cost-benefit analysis of aerospace systems. We demonstrate how the findings from the opinion and stated preference surveys can be infused into the cost-benefit analysis of an unmanned aircraft delivery system. We also demonstrate how to apply the findings from the interviews to characterize uncertainty in the estimation of the benefits of space-based ADS-B.

Selfie Aging Index: An Index for the Self-assessment of Healthy and Active Aging.

PubMed

Gonçalves, Judite; Gomes, Maria Isabel; Fonseca, Miguel; Teodoro, Tomás; Barros, Pedro Pita; Botelho, Maria-Amália

2017-01-01

Governments across Europe want to promote healthy and active aging, as a matter of both public health and economic sustainability. Designing policies focused on the most vulnerable groups requires information at the individual level. However, a measure of healthy and active aging at the individual level does not yet exist. This paper develops the Selfie Aging Index (SAI), an individual-level index of healthy and active aging. The SAI is developed thinking about a tool that would allow each person to take a selfie of her aging status. Therefore, it is based entirely on self-assessed indicators. This paper also illustrates how the SAI may look like in practice. The SAI is based on the Biopsychosocial Assessment Model (MAB), a tool for the multidimensional assessment of older adults along three domains: biological, psychological, and social. Indicators are selected and their weights determined based on an ordered probit model that relates the MAB indicators to self-assessed health, which proxies healthy and active aging. The ordered probit model predicts the SAI based on the estimated parameters. Finally, predictions are rescaled to the 0-1 interval. Data for the SAI development come from the Study of the Aging Profiles of the Portuguese Population and the Survey of Health, Aging, and Retirement in Europe. The selected indicators are BMI, having difficulties moving around indoors and performing the activities of daily living, feeling depressed, feeling nervous, lacking energy, time awareness score, marital status, having someone to confide in, education, type of job, exercise, and smoking status. The model also determines their weights. Results shed light on various factors that contribute significantly to healthy and active aging. Two examples are mental health and exercise, which deserve more attention from individuals themselves, health-care professionals, and public health policy. The SAI has the potential to put the individual at the center of the healthy and active aging discussion, contribute to patient empowerment, and promote patient-centered care. It can become a useful instrument to monitor healthy and active aging for different actors, including individuals themselves, health-care professionals, and policy makers.

A Bivariate return period for levee failure monitoring

NASA Astrophysics Data System (ADS)

Isola, M.; Caporali, E.

2017-12-01

Levee breaches are strongly linked with the interaction processes among water, soil and structure, thus many are the factors that affect the breach development. One of the main is the hydraulic load, characterized by intensity and duration, i.e. by the flood event hydrograph. On the magnitude of the hydraulic load is based the levee design, generally without considering the fatigue failure due to the load duration. Moreover, many are the cases in which the levee breach are characterized by flood of magnitude lower than the design one. In order to implement the strategies of flood risk management, we built here a procedure based on a multivariate statistical analysis of flood peak and volume together with the analysis of the past levee failure events. Particularly, in order to define the probability of occurrence of the hydraulic load on a levee, a bivariate copula model is used to obtain the bivariate joint distribution of flood peak and volume. Flood peak is the expression of the load magnitude, while the volume is the expression of the stress over time. We consider the annual flood peak and the relative volume. The volume is given by the hydrograph area between the beginning and the end of event. The beginning of the event is identified as an abrupt rise of the discharge by more than 20%. The end is identified as the point from which the receding limb is characterized by the baseflow, using a nonlinear reservoir algorithm as baseflow separation technique. By this, with the aim to define warning thresholds we consider the past levee failure events and the relative bivariate return period (BTr) compared with the estimation of a traditional univariate model. The discharge data of 30 hydrometric stations of Arno River in Tuscany, Italy, in the period 1995-2016 are analysed. The database of levee failure events, considering for each event the location as well as the failure mode, is also created. The events were registered in the period 2000-2014 by EEA-Europe Environment Agency, the Italian Civil Protection and ISPRA (the Italian National Institute for Environmental Protection and Research). Only two levee failures events occurred in the sub-basin of Era River have been detected and analysed. The estimated return period with the univariate model of flood peak is greater than 2 and 5 years while the BTr is greater of 25 and 30 years respectively.

Evaluating Evidence for Conceptually Related Constructs Using Bivariate Correlations

ERIC Educational Resources Information Center

Swank, Jacqueline M.; Mullen, Patrick R.

2017-01-01

The article serves as a guide for researchers in developing evidence of validity using bivariate correlations, specifically construct validity. The authors outline the steps for calculating and interpreting bivariate correlations. Additionally, they provide an illustrative example and discuss the implications.

Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.

PubMed

Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Using bivariate signal analysis to characterize the epileptic focus: The benefit of surrogates

NASA Astrophysics Data System (ADS)

Andrzejak, R. G.; Chicharro, D.; Lehnertz, K.; Mormann, F.

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Extended probit mortality model for zooplankton against transient change of PCO(2).

PubMed

Sato, Toru; Watanabe, Yuji; Toyota, Koji; Ishizaka, Joji

2005-09-01

The direct injection of CO(2) in the deep ocean is a promising way to mitigate global warming. One of the uncertainties in this method, however, is its impact on marine organisms in the near field. Since the concentration of CO(2), which organisms experience in the ocean, changes with time, it is required to develop a biological impact model for the organisms against the unsteady change of CO(2) concentration. In general, the LC(50) concept is widely applied for testing a toxic agent for the acute mortality. Here, we regard the probit-transformed mortality as a linear function not only of the concentration of CO(2) but also of exposure time. A simple mathematical transform of the function gives a damage-accumulation mortality model for zooplankton. In this article, this model was validated by the mortality test of Metamphiascopsis hirsutus against the transient change of CO(2) concentration.

Recommender system based on scarce information mining.

PubMed

Lu, Wei; Chung, Fu-Lai; Lai, Kunfeng; Zhang, Liang

2017-09-01

Guessing what user may like is now a typical interface for video recommendation. Nowadays, the highly popular user generated content sites provide various sources of information such as tags for recommendation tasks. Motivated by a real world online video recommendation problem, this work targets at the long tail phenomena of user behavior and the sparsity of item features. A personalized compound recommendation framework for online video recommendation called Dirichlet mixture probit model for information scarcity (DPIS) is hence proposed. Assuming that each clicking sample is generated from a representation of user preferences, DPIS models the sample level topic proportions as a multinomial item vector, and utilizes topical clustering on the user part for recommendation through a probit classifier. As demonstrated by the real-world application, the proposed DPIS achieves better performance in accuracy, perplexity as well as diversity in coverage than traditional methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Some properties of a 5-parameter bivariate probability distribution

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.; Smith, O. E.

1983-01-01

A five-parameter bivariate gamma distribution having two shape parameters, two location parameters and a correlation parameter was developed. This more general bivariate gamma distribution reduces to the known four-parameter distribution. The five-parameter distribution gives a better fit to the gust data. The statistical properties of this general bivariate gamma distribution and a hypothesis test were investigated. Although these developments have come too late in the Shuttle program to be used directly as design criteria for ascent wind gust loads, the new wind gust model has helped to explain the wind profile conditions which cause large dynamic loads. Other potential applications of the newly developed five-parameter bivariate gamma distribution are in the areas of reliability theory, signal noise, and vibration mechanics.

Bivariate extreme value distributions

NASA Technical Reports Server (NTRS)

Elshamy, M.

1992-01-01

In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given.

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

PubMed Central

Sonka, Milan; Abramoff, Michael D.

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR. PMID:24222760

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.

INLAND DISSOLVED SALT CHEMISTRY: STATISTICAL EVALUATION OF BIVARIATE AND TERNARY DIAGRAM MODELS FOR SURFACE AND SUBSURFACE WATERS

EPA Science Inventory

We compared the use of ternary and bivariate diagrams to distinguish the effects of atmospheric precipitation, rock weathering, and evaporation on inland surface and subsurface water chemistry. The three processes could not be statistically differentiated using bivariate models e...

An Examination of New Paradigms for Spline Approximations.

PubMed

Witzgall, Christoph; Gilsinn, David E; McClain, Marjorie A

2006-01-01

Lavery splines are examined in the univariate and bivariate cases. In both instances relaxation based algorithms for approximate calculation of Lavery splines are proposed. Following previous work Gilsinn, et al. [7] addressing the bivariate case, a rotationally invariant functional is assumed. The version of bivariate splines proposed in this paper also aims at irregularly spaced data and uses Hseih-Clough-Tocher elements based on the triangulated irregular network (TIN) concept. In this paper, the univariate case, however, is investigated in greater detail so as to further the understanding of the bivariate case.

A generalized right truncated bivariate Poisson regression model with applications to health data.

PubMed

Islam, M Ataharul; Chowdhury, Rafiqul I

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.

A generalized right truncated bivariate Poisson regression model with applications to health data

PubMed Central

Islam, M. Ataharul; Chowdhury, Rafiqul I.

2017-01-01

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model. PMID:28586344

Some bivariate distributions for modeling the strength properties of lumber

Treesearch

Richard A. Johnson; James W. Evans; David W. Green

Accurate modeling of the joint stochastic nature of the strength properties of dimension lumber is essential to the determination of reliability-based design safety factors. This report reviews the major techniques for obtaining bivariate distributions and then discusses bivariate distributions whose marginal distributions suggest they might be useful for modeling the...

A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns

NASA Astrophysics Data System (ADS)

Ferdous, Nazneen; Bhat, Chandra R.

2013-01-01

This paper proposes and estimates a spatial panel ordered-response probit model with temporal autoregressive error terms to analyze changes in urban land development intensity levels over time. Such a model structure maintains a close linkage between the land owner's decision (unobserved to the analyst) and the land development intensity level (observed by the analyst) and accommodates spatial interactions between land owners that lead to spatial spillover effects. In addition, the model structure incorporates spatial heterogeneity as well as spatial heteroscedasticity. The resulting model is estimated using a composite marginal likelihood (CML) approach that does not require any simulation machinery and that can be applied to data sets of any size. A simulation exercise indicates that the CML approach recovers the model parameters very well, even in the presence of high spatial and temporal dependence. In addition, the simulation results demonstrate that ignoring spatial dependency and spatial heterogeneity when both are actually present will lead to bias in parameter estimation. A demonstration exercise applies the proposed model to examine urban land development intensity levels using parcel-level data from Austin, Texas.

Bivariate drought frequency analysis using the copula method

NASA Astrophysics Data System (ADS)

Mirabbasi, Rasoul; Fakheri-Fard, Ahmad; Dinpashoh, Yagob

2012-04-01

Droughts are major natural hazards with significant environmental and economic impacts. In this study, two-dimensional copulas were applied to the analysis of the meteorological drought characteristics of the Sharafkhaneh gauge station, located in the northwest of Iran. Two major drought characteristics, duration and severity, as defined by the standardized precipitation index, were abstracted from observed drought events. Since drought duration and severity exhibited a significant correlation and since they were modeled using different distributions, copulas were used to construct the joint distribution function of the drought characteristics. The parameter of copulas was estimated using the method of the Inference Function for Margins. Several copulas were tested in order to determine the best data fit. According to the error analysis and the tail dependence coefficient, the Galambos copula provided the best fit for the observed drought data. Some bivariate probabilistic properties of droughts, based on the derived copula-based joint distribution, were also investigated. These probabilistic properties can provide useful information for water resource planning and management.

Social support network characteristics and sexual risk taking among a racially/ethnically diverse sample of young, urban men who have sex with men.

PubMed

Kapadia, F; Siconolfi, D E; Barton, S; Olivieri, B; Lombardo, L; Halkitis, P N

2013-06-01

Associations between social support network characteristics and sexual risk among racially/ethnically diverse young men who have sex with men (YMSM) were examined using egocentric network data from a prospective cohort study of YMSM (n = 501) recruited in New York City. Bivariate and multivariable logistic regression analyses examined associations between social support network characteristics and sexual risk taking behaviors in Black, Hispanic/Latino, and White YMSM. Bivariate analyses indicated key differences in network size, composition, communication frequency and average relationship duration by race/ethnicity. In multivariable analyses, controlling for individual level sociodemographic, psychosocial and relationship factors, having a sexual partner in one's social support network was associated with unprotected sexual behavior for both Hispanic/Latino (AOR = 3.90) and White YMSM (AOR = 4.93). Further examination of key network characteristics across racial/ethnic groups are warranted in order to better understand the extant mechanisms for provision of HIV prevention programming to racially/ethnically diverse YMSM at risk for HIV.

Risk estimates for CO exposure in man based on behavioral and physiological responses in rodents

NASA Technical Reports Server (NTRS)

Gross, M. K.

1983-01-01

An examination of animal response to CO is studied along with potential models for extrapolating animal test data to humans. The best models for extrapolating data were found to be the Probit and Weibull models.

A new spatial multiple discrete-continuous modeling approach to land use change analysis.

DOT National Transportation Integrated Search

2013-09-01

This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

Modeling rainfall-runoff relationship using multivariate GARCH model

NASA Astrophysics Data System (ADS)

Modarres, R.; Ouarda, T. B. M. J.

2013-08-01

The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

Median infectious dose (ID₅₀) of porcine reproductive and respiratory syndrome virus isolate MN-184 via aerosol exposure.

PubMed

Cutler, Timothy D; Wang, Chong; Hoff, Steven J; Kittawornrat, Apisit; Zimmerman, Jeffrey J

2011-08-05

The median infectious dose (ID(50)) of porcine reproductive and respiratory syndrome (PRRS) virus isolate MN-184 was determined for aerosol exposure. In 7 replicates, 3-week-old pigs (n=58) respired 10l of airborne PRRS virus from a dynamic aerosol toroid (DAT) maintained at -4°C. Thereafter, pigs were housed in isolation and monitored for evidence of infection. Infection occurred at virus concentrations too low to quantify by microinfectivity assays. Therefore, exposure dose was determined using two indirect methods ("calculated" and "theoretical"). "Calculated" virus dose was derived from the concentration of rhodamine B monitored over the exposure sequence. "Theoretical" virus dose was based on the continuous stirred-tank reactor model. The ID(50) estimate was modeled on the proportion of pigs that became infected using the probit and logit link functions for both "calculated" and "theoretical" exposure doses. Based on "calculated" doses, the probit and logit ID(50) estimates were 1 × 10(-0.13)TCID(50) and 1 × 10(-0.14)TCID(50), respectively. Based on "theoretical" doses, the probit and logit ID(50) were 1 × 10(0.26)TCID(50) and 1 × 10(0.24)TCID(50), respectively. For each point estimate, the 95% confidence interval included the other three point estimates. The results indicated that MN-184 was far more infectious than PRRS virus isolate VR-2332, the only other PRRS virus isolate for which ID(50) has been estimated for airborne exposure. Since aerosol ID(50) estimates are available for only these two isolates, it is uncertain whether one or both of these isolates represent the normal range of PRRS virus infectivity by this route. Copyright © 2011 Elsevier B.V. All rights reserved.

On the reliability of self-reported health: evidence from Albanian data.

PubMed

Vaillant, Nicolas; Wolff, François-Charles

2012-06-01

This paper investigates the reliability of self-assessed measures of health using panel data collected in Albania by the World Bank in 2002, 2003 and 2004 through the Living Standard Measurement Study project. As the survey includes questions on a self-assessed measure of health and on more objective health problems, both types of information are combined with a view to understanding how respondents change their answers to the self-reported measures over time. Estimates from random effects ordered Probit models show that differences in self-reported subjective health between individuals are much more marked than those over time, suggesting a strong state dependence in subjective health status. The empirical analysis also reveals respondent consistency, from both a subjective and an objective viewpoint. Self-reported health is much more influenced by permanent shocks than by more transitory illness or injury. Copyright © 2012 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

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

Marital status, childlessness, and social support among older Canadians.

PubMed

Penning, Margaret J; Wu, Zheng

2014-12-01

Despite evidence of increasing diversification of family structures, little is known regarding implications of marital and parental status for access to social support in later life. Using data from Statistics Canada's 2007 General Social Survey, this study assessed the impact of marital and parental status intersections on social support among adults aged 60 and older (n = 11,503). Two-stage probit regression models indicated that among those who were currently married or separated/divorced, childless individuals were more likely to report instrumental (domestic, transportation) and emotional support from people outside the household. Conversely, among never-married or widowed older adults, being childless was associated with reduced domestic support but without differences in other support domains. Findings suggest that marital and parental status intersections are not uniformly positive, neutral, or negative regarding implications for extra-household social support. Future work should address complexities of these relationships in order to better understand rapidly changing family structures.

The relationship between organizational culture and performance in acute hospitals.

PubMed

Jacobs, Rowena; Mannion, Russell; Davies, Huw T O; Harrison, Stephen; Konteh, Fred; Walshe, Kieran

2013-01-01

This paper examines the relationship between senior management team culture and organizational performance in English acute hospitals (NHS Trusts) over three time periods between 2001/2002 and 2007/2008. We use a validated culture rating instrument, the Competing Values Framework, to measure senior management team culture. Organizational performance is assessed using a wide range of routinely collected indicators. We examine the associations between organizational culture and performance using ordered probit and multinomial logit models. We find that organizational culture varies across hospitals and over time, and this variation is at least in part associated in consistent and predictable ways with a variety of organizational characteristics and routine measures of performance. Moreover, hospitals are moving towards more competitive culture archetypes which mirror the current policy context, though with a stronger blend of cultures. The study provides evidence for a relationship between culture and performance in hospital settings. Copyright © 2012 Elsevier Ltd. All rights reserved.

The fatter are happier in Indonesia.

PubMed

Sohn, Kitae

2017-02-01

Although obesity and happiness are known to be negatively related in the developed world, little attention has been paid to this relationship in the developing world. We thus investigated the relationship in Indonesia and attempted to explain the underlying rationale. We considered about 12,000 respondents aged 15+ for each gender obtained from the Indonesian Family Life Survey 2007 by relating a measure of happiness to weight-related measures in ordered probit models. The relationship between obesity and happiness was positive in Indonesia, and this relationship was robust. Our evidence suggests that the contrasting results for the two worlds result from affordability of obesity. That is, while even low socioeconomic status (SES) individuals in the developed world can afford to be obese, only high SES individuals in the developing world can do. Our findings imply that obesity prevention in the developing world requires different measures than those used in the developed world.

UNDERSTANDING THE ASSOCIATION BETWEEN MATERNAL EDUCATION AND USE OF HEALTH SERVICES IN GHANA: EXPLORING THE ROLE OF HEALTH KNOWLEDGE

PubMed Central

GREENAWAY, EMILY SMITH; LEON, JUAN; BAKER, DAVID P.

2013-01-01

Summary This paper examines the role of health knowledge in the association between mothers’ education and use of maternal and child health services in Ghana. The study uses data from a nationally representative sample of female respondents to the 2008 Ghana Demographic and Health Survey. Ordered probit regression models evaluate whether women’s health knowledge helps to explain use of three specific maternal and child health services: antenatal care, giving birth with the supervision of a trained professional and complete child vaccination. The analyses reveal that mothers’ years of formal education are strongly associated with health knowledge; health knowledge helps explain the association between maternal education and use of health services; and, net of a set of stringent demographic and socioeconomic controls, mothers’ health knowledge is a key factor associated with use of health services. PMID:22377424

Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention.

PubMed

Nguyen, Trang Quynh; Webb-Vargas, Yenny; Koning, Ina M; Stuart, Elizabeth A

We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation of risk-difference- and risk-ratio-based effects (RDs, RRs) using the ML, WLSMV and Bayes estimators in Mplus. Across most variations in path-coefficient and mediator-residual-correlation signs and strengths, and confounding situations investigated, the method performs well with all estimators, but favors ML/WLSMV for RDs with continuous mediators, and Bayes for RRs with ordinal mediators. Bayes outperforms WLSMV/ML regardless of mediator type when estimating RRs with small potential outcome probabilities and in two other special cases. An adolescent alcohol prevention study is used for illustration.

Causal networks clarify productivity-richness interrelations, bivariate plots do not

USGS Publications Warehouse

Grace, James B.; Adler, Peter B.; Harpole, W. Stanley; Borer, Elizabeth T.; Seabloom, Eric W.

2014-01-01

We urge ecologists to consider productivity–richness relationships through the lens of causal networks to advance our understanding beyond bivariate analysis. Further, we emphasize that models based on a causal network conceptualization can also provide more meaningful guidance for conservation management than can a bivariate perspective. Measuring only two variables does not permit the evaluation of complex ideas nor resolve debates about underlying mechanisms.

Fisher information for two gamma frailty bivariate Weibull models.

PubMed

Bjarnason, H; Hougaard, P

2000-03-01

The asymptotic properties of frailty models for multivariate survival data are not well understood. To study this aspect, the Fisher information is derived in the standard bivariate gamma frailty model, where the survival distribution is of Weibull form conditional on the frailty. For comparison, the Fisher information is also derived in the bivariate gamma frailty model, where the marginal distribution is of Weibull form.

Statistical modeling of space shuttle environmental data

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.

1983-01-01

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application.

Preventing Unintended Pregnancy and HIV Transmission: Effects of the HIV Treatment Cascade on Contraceptive Use and Choice in Rural KwaZulu-Natal

PubMed Central

Raifman, Julia; Chetty, Terusha; Tanser, Frank; Mutevedzi, Tinofa; Matthews, Philippa; Herbst, Kobus; Pillay, Deenan

2014-01-01

Background: For women living with HIV, contraception using condoms is recommended because it prevents not only unintended pregnancy but also acquisition of other sexually transmitted infections and onward transmission of HIV. Dual-method dual-protection contraception (condoms with other contraceptive methods) is preferable over single-method dual-protection contraception (condoms alone) because of its higher contraceptive effectiveness. We estimate the effect of progression through the HIV treatment cascade on contraceptive use and choice among HIV-infected women in rural South Africa. Methods: We linked population-based surveillance data on contraception collected by the Wellcome Trust Africa Centre for Health and Population Studies to data from the local antiretroviral treatment (ART) program in Hlabisa subdistrict, KwaZulu-Natal. In bivariate probit regression, we estimated the effects of progressing through the cascade on contraceptive choice among HIV-infected sexually active women aged 15–49 years (N = 3169), controlling for a wide range of potential confounders. Findings: Contraception use increased across the cascade from <40% among HIV-infected women who did not know their status to >70% among women who have been on ART for 4–7 years. Holding other factors equal (1) awareness of HIV status, (2) ART initiation, and (3) being on ART for 4–7 years increased the likelihood of single-method/dual-method dual protection by the following percentage points (pp), compared with women who were unaware of their HIV status: (1) 4.6 pp (P = 0.030)/3.5 pp (P = 0.001), (2) 10.3 pp (P = 0.003)/5.2 pp (P = 0.007), and (3) 21.6 pp (P < 0.001)/11.2 pp (P < 0.001). Conclusions: Progression through the HIV treatment cascade significantly increased the likelihood of contraception in general and contraception with condoms in particular. ART programs are likely to contribute to HIV prevention through the behavioral pathway of changing contraception use and choice. PMID:25436821

Preventing unintended pregnancy and HIV transmission: effects of the HIV treatment cascade on contraceptive use and choice in rural KwaZulu-Natal.

PubMed

Raifman, Julia; Chetty, Terusha; Tanser, Frank; Mutevedzi, Tinofa; Matthews, Philippa; Herbst, Kobus; Pillay, Deenan; Bärnighausen, Till

2014-12-01

For women living with HIV, contraception using condoms is recommended because it prevents not only unintended pregnancy but also acquisition of other sexually transmitted infections and onward transmission of HIV. Dual-method dual-protection contraception (condoms with other contraceptive methods) is preferable over single-method dual-protection contraception (condoms alone) because of its higher contraceptive effectiveness. We estimate the effect of progression through the HIV treatment cascade on contraceptive use and choice among HIV-infected women in rural South Africa. We linked population-based surveillance data on contraception collected by the Wellcome Trust Africa Centre for Health and Population Studies to data from the local antiretroviral treatment (ART) program in Hlabisa subdistrict, KwaZulu-Natal. In bivariate probit regression, we estimated the effects of progressing through the cascade on contraceptive choice among HIV-infected sexually active women aged 15-49 years (N = 3169), controlling for a wide range of potential confounders. Contraception use increased across the cascade from <40% among HIV-infected women who did not know their status to >70% among women who have been on ART for 4-7 years. Holding other factors equal (1) awareness of HIV status, (2) ART initiation, and (3) being on ART for 4-7 years increased the likelihood of single-method/dual-method dual protection by the following percentage points (pp), compared with women who were unaware of their HIV status: (1) 4.6 pp (P = 0.030)/3.5 pp (P = 0.001), (2) 10.3 pp (P = 0.003)/5.2 pp (P = 0.007), and (3) 21.6 pp (P < 0.001)/11.2 pp (P < 0.001). Progression through the HIV treatment cascade significantly increased the likelihood of contraception in general and contraception with condoms in particular. ART programs are likely to contribute to HIV prevention through the behavioral pathway of changing contraception use and choice.

Community-directed mass drug administration is undermined by status seeking in friendship networks and inadequate trust in health advice networks.

PubMed

Chami, Goylette F; Kontoleon, Andreas A; Bulte, Erwin; Fenwick, Alan; Kabatereine, Narcis B; Tukahebwa, Edridah M; Dunne, David W

2017-06-01

Over 1.9 billion individuals require preventive chemotherapy through mass drug administration (MDA). Community-directed MDA relies on volunteer community medicine distributors (CMDs) and their achievement of high coverage and compliance. Yet, it is unknown if village social networks influence effective MDA implementation by CMDs. In Mayuge District, Uganda, census-style surveys were conducted for 16,357 individuals from 3,491 households in 17 villages. Praziquantel, albendazole, and ivermectin were administered for one month in community-directed MDA to treat Schistosoma mansoni, hookworm, and lymphatic filariasis. Self-reported treatment outcomes, socioeconomic characteristics, friendship networks, and health advice networks were collected. We investigated systematically missed coverage and noncompliance. Coverage was defined as an eligible person being offered at least one drug by CMDs; compliance included ingesting at least one of the offered drugs. These outcomes were analyzed as a two-stage process using a Heckman selection model. To further assess if MDA through CMDs was working as intended, we examined the probability of accurate drug administration of 1) praziquantel, 2) both albendazole and ivermectin, and 3) all drugs. This analysis was conducted using bivariate Probit regression. Four indicators from each social network were examined: degree, betweenness centrality, closeness centrality, and the presence of a direct connection to CMDs. All models accounted for nested household and village standard errors. CMDs were more likely to offer medicines, and to accurately administer the drugs as trained by the national control programme, to individuals with high friendship degree (many connections) and high friendship closeness centrality (households that were only a short number of steps away from all other households in the network). Though high (88.59%), additional compliance was associated with directly trusting CMDs for health advice. Effective treatment provision requires addressing CMD biases towards influential, well-embedded individuals in friendship networks and utilizing health advice networks to increase village trust in CMDs. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Informal cash payments for birth in Hungary: Are women paying to secure a known provider, respect, or quality of care?

PubMed

Baji, Petra; Rubashkin, Nicholas; Szebik, Imre; Stoll, Kathrin; Vedam, Saraswathi

2017-09-01

In Central and Eastern Europe, many women make informal cash payments to ensure continuity of provider, i.e., to have a "chosen" doctor who provided their prenatal care, be present for birth. High rates of obstetric interventions and disrespectful maternity care are also common to the region. No previous study has examined the associations among informal payments, intervention rates, and quality of maternity care. We distributed an online cross-sectional survey in 2014 to a nationally representative sample of Hungarian internet-using women (N = 600) who had given birth in the last 5 years. The survey included items related to socio-demographics, type of provider, obstetric interventions, and experiences of care. Women reported if they paid informally, and how much. We built a two-part model, where a bivariate probit model was used to estimate conditional probabilities of women paying informally, and a GLM model to explore the amount of payments. We calculated marginal effects of the covariates (provider choice, interventions, respectful care). Many more women (79%) with a chosen doctor paid informally (191 euros on average) compared to 17% of women without a chosen doctor (86 euros). Based on regression analysis, the chosen doctor's presence at birth was the principal determinant of payment. Intervention and procedure rates were significantly higher for women with a chosen doctor versus without (cesareans 45% vs. 33%; inductions 32% vs. 19%; episiotomy 75% vs. 62%; epidural 13% vs. 5%), but had no direct effect on payments. Half of the sample (42% with a chosen doctor, 62% without) reported some form of disrespectful care, but this did not reduce payments. Despite reporting disrespect and higher rates of interventions, women rewarded the presence of a chosen doctor with informal payments. They may be unaware of evidence-based standards, and trust that their chosen doctor provided high quality maternity care. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of Statistical Methods for Modeling Historical Resource Production and Forecasting

NASA Astrophysics Data System (ADS)

Nanzad, Bolorchimeg

This master's thesis project consists of two parts. Part I of the project compares modeling of historical resource production and forecasting of future production trends using the logit/probit transform advocated by Rutledge (2011) with conventional Hubbert curve fitting, using global coal production as a case study. The conventional Hubbert/Gaussian method fits a curve to historical production data whereas a logit/probit transform uses a linear fit to a subset of transformed production data. Within the errors and limitations inherent in this type of statistical modeling, these methods provide comparable results. That is, despite that apparent goodness-of-fit achievable using the Logit/Probit methodology, neither approach provides a significant advantage over the other in either explaining the observed data or in making future projections. For mature production regions, those that have already substantially passed peak production, results obtained by either method are closely comparable and reasonable, and estimates of ultimately recoverable resources obtained by either method are consistent with geologically estimated reserves. In contrast, for immature regions, estimates of ultimately recoverable resources generated by either of these alternative methods are unstable and thus, need to be used with caution. Although the logit/probit transform generates high quality-of-fit correspondence with historical production data, this approach provides no new information compared to conventional Gaussian or Hubbert-type models and may have the effect of masking the noise and/or instability in the data and the derived fits. In particular, production forecasts for immature or marginally mature production systems based on either method need to be regarded with considerable caution. Part II of the project investigates the utility of a novel alternative method for multicyclic Hubbert modeling tentatively termed "cycle-jumping" wherein overlap of multiple cycles is limited. The model is designed in a way that each cycle is described by the same three parameters as conventional multicyclic Hubbert model and every two cycles are connected with a transition width. Transition width indicates the shift from one cycle to the next and is described as weighted coaddition of neighboring two cycles. It is determined by three parameters: transition year, transition width, and gamma parameter for weighting. The cycle-jumping method provides superior model compared to the conventional multicyclic Hubbert model and reflects historical production behavior more reasonably and practically, by better modeling of the effects of technological transitions and socioeconomic factors that affect historical resource production behavior by explicitly considering the form of the transitions between production cycles.

Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Treesearch

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

A Note on the Heterogeneous Choice Model

ERIC Educational Resources Information Center

Rohwer, Goetz

2015-01-01

The heterogeneous choice model (HCM) has been proposed as an extension of the standard logit and probit models, which allows taking into account different error variances of explanatory variables. In this note, I show that in an important special case, this model is just another way to specify an interaction effect.

Statistical considerations in the analysis of data from replicated bioassays

USDA-ARS?s Scientific Manuscript database

Multiple-dose bioassay is generally the preferred method for characterizing virulence of insect pathogens. Linear regression of probit mortality on log dose enables estimation of LD50/LC50 and slope, the latter having substantial effect on LD90/95s (doses of considerable interest in pest management)...

Using Neural Networks to Predict MBA Student Success

ERIC Educational Resources Information Center

Naik, Bijayananda; Ragothaman, Srinivasan

2004-01-01

Predicting MBA student performance for admission decisions is crucial for educational institutions. This paper evaluates the ability of three different models--neural networks, logit, and probit to predict MBA student performance in graduate programs. The neural network technique was used to classify applicants into successful and marginal student…

USE OF WEIBULL FUNCTION FOR NON-LINEAR ANALYSIS OF EFFECTS OF LOW LEVELS OF SIMULATED HERBICIDE DRIFT ON PLANTS

EPA Science Inventory

We compared two regression models, which are based on the Weibull and probit functions, for the analysis of pesticide toxicity data from laboratory studies on Illinois crop and native plant species. Both mathematical models are continuous, differentiable, strictly positive, and...

Social support network characteristics and sexual risk taking among a racially/ethnically diverse sample of young, urban men who have sex with men

PubMed Central

Kapadia, F; Siconolfi, DE; Barton, S; Olivieri, B; Lombardo, L; Halkitis, PN

2013-01-01

Associations between social support network characteristics and sexual risk among racially/ethnically diverse young men who have sex with men (YMSM) were examined using egocentric network data from a prospective cohort study of YMSM (n=501) recruited in New York City. Bivariate and multivariable logistic regression analyses examined associations between social support network characteristics and sexual risk taking behaviors in Black, Hispanic/Latino, and White YMSM. Bivariate analyses indicated key differences in network size, composition, communication frequency and average relationship duration by race/ethnicity. In multivariable analyses, controlling for individual level sociodemographic, psychosocial and relationship factors, having a sexual partner in one’s social support network was associated with unprotected sexual behavior for both Hispanic/Latino (AOR=3.90) and White YMSM (AOR=4.93). Further examination of key network characteristics across racial/ethnic groups are warranted in order to better understand the extant mechanisms for provision of HIV prevention programming to racially/ethnically diverse YMSM at risk for HIV. PMID:23553346

Neural Systems with Numerically Matched Input-Output Statistic: Isotonic Bivariate Statistical Modeling

PubMed Central

Fiori, Simone

2007-01-01

Bivariate statistical modeling from incomplete data is a useful statistical tool that allows to discover the model underlying two data sets when the data in the two sets do not correspond in size nor in ordering. Such situation may occur when the sizes of the two data sets do not match (i.e., there are “holes” in the data) or when the data sets have been acquired independently. Also, statistical modeling is useful when the amount of available data is enough to show relevant statistical features of the phenomenon underlying the data. We propose to tackle the problem of statistical modeling via a neural (nonlinear) system that is able to match its input-output statistic to the statistic of the available data sets. A key point of the new implementation proposed here is that it is based on look-up-table (LUT) neural systems, which guarantee a computationally advantageous way of implementing neural systems. A number of numerical experiments, performed on both synthetic and real-world data sets, illustrate the features of the proposed modeling procedure. PMID:18566641

A User’s Guide to BISAM (BIvariate SAMple): The Bivariate Data Modeling Program.

DTIC Science & Technology

1983-08-01

method for the null case specified and is then used to form the bivariate density-quantile function as described in section 4. If D(U) in stage...employed assigns average ranks for tied observations. Other methods for assigning ranks to tied observations are often employed but are not attempted...34 €.. . . . .. . .. . . . ,.. . ,•. . . ... *.., .. , - . . . . - - . . .. - -. .. observations will weaken the results obtained since underlying continuous distributions are assumed. One should avoid such situations if possible. Two methods

Bivariate versus multivariate smart spectrophotometric calibration methods for the simultaneous determination of a quaternary mixture of mosapride, pantoprazole and their degradation products.

PubMed

Hegazy, M A; Yehia, A M; Moustafa, A A

2013-05-01

The ability of bivariate and multivariate spectrophotometric methods was demonstrated in the resolution of a quaternary mixture of mosapride, pantoprazole and their degradation products. The bivariate calibrations include bivariate spectrophotometric method (BSM) and H-point standard addition method (HPSAM), which were able to determine the two drugs, simultaneously, but not in the presence of their degradation products, the results showed that simultaneous determinations could be performed in the concentration ranges of 5.0-50.0 microg/ml for mosapride and 10.0-40.0 microg/ml for pantoprazole by bivariate spectrophotometric method and in the concentration ranges of 5.0-45.0 microg/ml for both drugs by H-point standard addition method. Moreover, the applied multivariate calibration methods were able for the determination of mosapride, pantoprazole and their degradation products using concentration residuals augmented classical least squares (CRACLS) and partial least squares (PLS). The proposed multivariate methods were applied to 17 synthetic samples in the concentration ranges of 3.0-12.0 microg/ml mosapride, 8.0-32.0 microg/ml pantoprazole, 1.5-6.0 microg/ml mosapride degradation products and 2.0-8.0 microg/ml pantoprazole degradation products. The proposed bivariate and multivariate calibration methods were successfully applied to the determination of mosapride and pantoprazole in their pharmaceutical preparations.

Development and applicability of Hospital Survey on Patient Safety Culture (HSOPS) in Japan.

PubMed

Ito, Shinya; Seto, Kanako; Kigawa, Mika; Fujita, Shigeru; Hasegawa, Toshihiko; Hasegawa, Tomonori

2011-02-07

Patient safety culture at healthcare organizations plays an important role in guaranteeing, improving and promoting overall patient safety. Although several conceptual frameworks have been proposed in the past, no standard measurement tool has yet been developed for Japan. In order to examine possibilities to introduce the Hospital Survey on Patient Safety Culture (HSOPS) in Japan, the authors of this study translated the HSOPS into Japanese, and evaluated its factor structure, internal consistency, and construct validity. Healthcare workers (n = 6,395) from 13 acute care general hospitals in Japan participated in this survey. Confirmatory factor analysis indicated that the Japanese HSOPS' 12-factor model was selected as the most pertinent, and showed a sufficiently high standard partial regression coefficient. The internal reliability of the subscale scores was 0.46-0.88. The construct validity of each safety culture sub-dimension was confirmed by polychoric correlation, and by an ordered probit analysis. The results of the present study indicate that the factor structures of the Japanese and the American HSOPS are almost identical, and that the Japanese HSOPS has acceptable levels of internal reliability and construct validity. This shows that the HSOPS can be introduced in Japan.

Innovation and motivation in public health professionals.

PubMed

García-Goñi, Manuel; Maroto, Andrés; Rubalcaba, Luis

2007-12-01

Innovations in public health services promote increases in the health status of the population. Therefore, it is a major concern for health policy makers to understand the drivers of innovation processes. This paper focuses on the differences in behaviour of managers and front-line employees in the pro-innovative provision of public health services. We utilize a survey conducted on front-line employees and managers in public health institutions across six European countries. The survey covers topics related to satisfaction, or attitude towards innovation or their institution. We undertake principal components analysis and analysis of variance, and estimate a multinomial ordered probit model to analyse the existence of different behaviour in managers and front-line employees with respect to innovation. Perception of innovation is different for managers and front-line employees in public health institutions. While front-line employees' attitude depends mostly on the overall performance of the institution, managers feel more involved and motivated, and their behaviour depends more on individual and organisational innovative profiles. It becomes crucial to make both managers and front-line employees at public health institutions feel participative and motivated in order to maximise the benefits of technical or organisational innovative process in the health services provision.

Injury severity analysis of commercially-licensed drivers in single-vehicle crashes: Accounting for unobserved heterogeneity and age group differences.

PubMed

Osman, Mohamed; Mishra, Sabyasachee; Paleti, Rajesh

2018-05-18

This study analyzes the injury severity of commercially-licensed drivers involved in single-vehicle crashes. Considering the discrete ordinal nature of injury severity data, the ordered response modeling framework was adopted. The moderating effect of driver's age on all other factors was examined by segmenting the parameters by driver's age group. Additional effects of the different drivers' age groups are taken into consideration through interaction terms. Unobserved heterogeneity of the different covariates was investigated using the Mixed Generalized Ordered Response Probit (MGORP) model. The empirical analysis was conducted using four years of the Highway Safety Information System (HSIS) data that included 6247 commercially-licensed drivers involved in single-vehicle crashes in the state of Minnesota. The MGORP model elasticity effects indicate that key factors that increase the likelihood of severe crashes for commercially-licensed drivers across all age groups include: lack of seatbelt usage, collision with a fixed object, speeding, vehicle age of 11 years or more, wind, night time, weekday, and female drivers. Also, the effects of several covariates were found to vary across different age groups. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bivariate categorical data analysis using normal linear conditional multinomial probability model.

PubMed

Sun, Bingrui; Sutradhar, Brajendra

2015-02-10

Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.

A Bivariate Mixed Distribution with a Heavy-tailed Component and its Application to Single-site Daily Rainfall Simulation

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

Li, Chao ..; Singh, Vijay P.; Mishra, Ashok K.

2013-02-06

This paper presents an improved brivariate mixed distribution, which is capable of modeling the dependence of daily rainfall from two distinct sources (e.g., rainfall from two stations, two consecutive days, or two instruments such as satellite and rain gauge). The distribution couples an existing framework for building a bivariate mixed distribution, the theory of copulae and a hybrid marginal distribution. Contributions of the improved distribution are twofold. One is the appropriate selection of the bivariate dependence structure from a wider admissible choice (10 candidate copula families). The other is the introduction of a marginal distribution capable of better representing lowmore » to moderate values as well as extremes of daily rainfall. Among several applications of the improved distribution, particularly presented here is its utility for single-site daily rainfall simulation. Rather than simulating rainfall occurrences and amounts separately, the developed generator unifies the two processes by generalizing daily rainfall as a Markov process with autocorrelation described by the improved bivariate mixed distribution. The generator is first tested on a sample station in Texas. Results reveal that the simulated and observed sequences are in good agreement with respect to essential characteristics. Then, extensive simulation experiments are carried out to compare the developed generator with three other alternative models: the conventional two-state Markov chain generator, the transition probability matrix model and the semi-parametric Markov chain model with kernel density estimation for rainfall amounts. Analyses establish that overall the developed generator is capable of reproducing characteristics of historical extreme rainfall events and is apt at extrapolating rare values beyond the upper range of available observed data. Moreover, it automatically captures the persistence of rainfall amounts on consecutive wet days in a relatively natural and easy way. Another interesting observation is that the recognized ‘overdispersion’ problem in daily rainfall simulation ascribes more to the loss of rainfall extremes than the under-representation of first-order persistence. The developed generator appears to be a sound option for daily rainfall simulation, especially in particular hydrologic planning situations when rare rainfall events are of great importance.« less

Do firstborn children have an increased risk of ADHD?

PubMed

Marín, Adela Masana; Seco, Fernando Lopez; Serrano, Susana Martí; García, Silvia Acosta; Gaviria Gómez, Ana Milena; Ney, Inti

2014-10-01

Although previous reports have found no birth-order influence on ADHD risk, the authors hypothesize that being the firstborn is a risk factor for developing ADHD. They selected all of the currently treated ADHD outpatients (n = 748) from our database. Families with adopted sons, nonnuclear families, and families with only one child and with sons (affected or unaffected) younger than 6 or older than 18 years were excluded. A total of 181 families with 213 ADHD sons met the inclusion criteria. We used all siblings without a clinical diagnosis of ADHD and who had no contact with our service as our unaffected controls (n = 173). The bivariate analysis showed that ADHD was associated with birth order and that firstborn children had nearly twice the ADHD risk of children with other birth orders. birth order can be an ADHD risk factor in clinical samples. © 2012 SAGE Publications.

Bivariate tensor product [Formula: see text]-analogue of Kantorovich-type Bernstein-Stancu-Schurer operators.

PubMed

Cai, Qing-Bo; Xu, Xiao-Wei; Zhou, Guorong

2017-01-01

In this paper, we construct a bivariate tensor product generalization of Kantorovich-type Bernstein-Stancu-Schurer operators based on the concept of [Formula: see text]-integers. We obtain moments and central moments of these operators, give the rate of convergence by using the complete modulus of continuity for the bivariate case and estimate a convergence theorem for the Lipschitz continuous functions. We also give some graphs and numerical examples to illustrate the convergence properties of these operators to certain functions.

Factors Affecting Smoking Tendency and Smoking Intensity

ERIC Educational Resources Information Center

David, Nissim Ben; Zion, Uri Ben

2009-01-01

Purpose: The purpose of this paper is to measure the relative effect of relevant explanatory variable on smoking tendency and smoking intensity. Design/methodology/approach: Using survey data collected by the Israeli Bureau of Statistics in 2003-2004, a probit procedure is estimated for analyzing factors that affect the probability of being a…

Bayesian Analysis of Multilevel Probit Models for Data with Friendship Dependencies

ERIC Educational Resources Information Center

Koskinen, Johan; Stenberg, Sten-Ake

2012-01-01

When studying educational aspirations of adolescents, it is unrealistic to assume that the aspirations of pupils are independent of those of their friends. Considerable attention has also been given to the study of peer influence in the educational and behavioral literature. Typically, in empirical studies, the friendship networks have either been…

Bioassay of the Nucleopolyhedrosis Virus of Neodiprion sertifer (Hymenoptera: Diprionidae)

Treesearch

M.A. Mohamed; J.D. Podgwaite

1982-01-01

Linear regression analysis of probit mortality versus several concentrations of nucleopolyhedrosis virus of Neodiprion sertifer resulted in the equation Y = 2.170 + 0.872X. An LC50 was calculated at 1758 PIB/ml. Also, the incubation time of the virus was dependent on its concentration. Most insect viruses possess the potential...

A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories

ERIC Educational Resources Information Center

Duvvuri, Sri Devi; Gruca, Thomas S.

2010-01-01

Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…

Calcium spiking activity and baseline calcium levels in ROS 17/2.8 cells exposed to extremely low frequency electromagnetic fields (ELF EMF).

PubMed

Shahidain, R; Mullins, R D; Sisken, J E

2001-02-01

To determine whether extremely low frequency electromagnetic fields can alter average free cytosolic calcium ion concentrations [Ca2+]i and transient increases in [Ca2+]i in populations of ROS 17/2.8 cells. Cells loaded with the calcium-selective luminescent photoprotein, aequorin, were placed in the bottom of a sample chamber, which was inserted into the gap of a previously described air gap reactor system where they were exposed either to sinusoidal magnetic fields at a variety of frequencies and flux densities or to sham conditions. Real-time recordings of photon counts due to aequorin luminescence were obtained and data were analysed with the use of probit plots. Probit plots of data obtained from cells exposed to the various magnetic fields were virtually superimposable over the data obtained for the same cultures during pre- and post-exposure sham or no-field periods. These experiments provided no evidence for any effects of ELF EMF, either positive or negative, on either average [Ca2+]i or on transient increases in [Ca2+]i.

Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention

PubMed Central

Nguyen, Trang Quynh; Webb-Vargas, Yenny; Koning, Ina M.; Stuart, Elizabeth A.

2016-01-01

We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation of risk-difference- and risk-ratio-based effects (RDs, RRs) using the ML, WLSMV and Bayes estimators in Mplus. Across most variations in path-coefficient and mediator-residual-correlation signs and strengths, and confounding situations investigated, the method performs well with all estimators, but favors ML/WLSMV for RDs with continuous mediators, and Bayes for RRs with ordinal mediators. Bayes outperforms WLSMV/ML regardless of mediator type when estimating RRs with small potential outcome probabilities and in two other special cases. An adolescent alcohol prevention study is used for illustration. PMID:27158217

A Method for Approximating the Bivariate Normal Correlation Coefficient.

ERIC Educational Resources Information Center

Kirk, David B.

Improvements of the Gaussian quadrature in conjunction with the Newton-Raphson iteration technique (TM 000 789) are discussed as effective methods of calculating the bivariate normal correlation coefficient. (CK)

The episodic random utility model unifies time trade-off and discrete choice approaches in health state valuation

PubMed Central

Craig, Benjamin M; Busschbach, Jan JV

2009-01-01

Background To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation. Methods First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common instant RUM. For the interpretation of time trade-off (TTO) responses, we show that the episodic model implies a coefficient estimator, and the instant model implies a mean slope estimator. Secondly, we demonstrate these estimators and the differences between the estimates for 42 health states using TTO responses from the seminal Measurement and Valuation in Health (MVH) study conducted in the United Kingdom. Mean slopes are estimates with and without Dolan's transformation of worse-than-death (WTD) responses. Finally, we demonstrate an exploded probit estimator, an extension of the coefficient estimator for discrete choice data that accommodates both TTO and rank responses. Results By construction, mean slopes are less than or equal to coefficients, because slopes are fractions and, therefore, magnify downward errors in WTD responses. The Dolan transformation of WTD responses causes mean slopes to increase in similarity to coefficient estimates, yet they are not equivalent (i.e., absolute mean difference = 0.179). Unlike mean slopes, coefficient estimates demonstrate strong concordance with rank-based predictions (Lin's rho = 0.91). Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results. Conclusion The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses. In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single estimator. PMID:19144115

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.

National Human Trafficking Initiatives: Dimensions of Policy Diffusion1

PubMed Central

Yoo, Eun-hye; Boyle, Elizabeth Heger

2014-01-01

The implementation of criminal law involves formal law enforcement, education and public outreach aimed at preventing criminal activity, and providing services for victims. Historically, quantitative research on global trends has tended to focus on a single policy dimension, potentially masking the unique factors that affect the diffusion of each policy dimension independently. Using an ordered-probit model to analyze new human trafficking policy data on national prosecution, prevention, and victim-protection efforts, we find that global ties and domestic interest groups matter more in areas where international law is less defined. While prosecution, officially mandated by the Trafficking Protocol, was relatively impervious to global ties and domestic interest groups, both trafficking prevention and victim protection were associated with these factors. Our findings also suggest that fear of repercussions is not a major driver of state actions to combat trafficking—neither ratification of the Trafficking Protocol nor levels of United States aid were associated with greater implementation of anti-trafficking measures. PMID:26538806

Does social insurance enrollment improve citizen assessment of local government performance? Evidence from China.

PubMed

Huang, Xian; Gao, Qin

2018-02-01

Although many studies claim that social policies are "carrots" that authoritarian leaders use to garner public support, the assumption that social benefits can boost public support of government has been rarely tested empirically, especially at the local levels. This article investigates the effects of social insurance enrollment on citizens' assessment of local government performance using data from the 2010 China Family Panel Study. We use propensity score matching to reduce selection bias and ordered probit regressions with fixed effects to examine these possible effects. We find that social insurance enrollment had a significant positive effect on rural citizens' assessment of government performance, but this effect did not exist for their urban and migrant peers. This discrepancy could be largely due to the groups' different expectations for government redistribution and their distinct experiences of China's social welfare reform. We conclude that the Chinese authoritarian government has achieved partial success in its attempt to use social policies to maintain popular support. Published by Elsevier Inc.

When Do Older Adults Become “Disabled”? Social and Health Antecedents of Perceived Disability in a Panel Study of the Oldest Old*

PubMed Central

KELLEY-MOORE, JESSICA A.; SCHUMACHER, JOHN G.; KAHANA, EVA; KAHANA, BOAZ

2007-01-01

Disability carries negative social meaning, and little is known about when (or if), in the process of health decline, persons identify themselves as “disabled” We examine the social and health criteria that older adults use to subjectively rate their own disability status. Using a panel study of older adults (ages 72+), we estimate ordered probit and growth curve models of perceived disability over time. Total prevalent morbidity, functional limitations, and cognitive impairment are predictors of perceived disability. Cessation of driving and receipt of home health care also influence older adults’ perceptions of their own disability. A dense social network slowed the rate of labeling oneself disabled, while health anxiety accelerated the process over time, independent of health status. When considering perceived disability, the oldest old use multidimensional criteria capturing function, recent changes in health status and social networks, and anxiety about their health. PMID:16821507

National Human Trafficking Initiatives: Dimensions of Policy Diffusion.

PubMed

Yoo, Eun-Hye; Boyle, Elizabeth Heger

2015-01-01

The implementation of criminal law involves formal law enforcement, education and public outreach aimed at preventing criminal activity, and providing services for victims. Historically, quantitative research on global trends has tended to focus on a single policy dimension, potentially masking the unique factors that affect the diffusion of each policy dimension independently. Using an ordered-probit model to analyze new human trafficking policy data on national prosecution, prevention, and victim-protection efforts, we find that global ties and domestic interest groups matter more in areas where international law is less defined. While prosecution, officially mandated by the Trafficking Protocol, was relatively impervious to global ties and domestic interest groups, both trafficking prevention and victim protection were associated with these factors. Our findings also suggest that fear of repercussions is not a major driver of state actions to combat trafficking-neither ratification of the Trafficking Protocol nor levels of United States aid were associated with greater implementation of anti-trafficking measures.

Using Survey Data to Determine a Numeric Criterion for Nutrient Pollution

NASA Astrophysics Data System (ADS)

Jakus, Paul M.; Nelson, Nanette; Ostermiller, Jeffrey

2017-12-01

We present a scientific replication of a benthic algae nuisance threshold study originally conducted in Montana, but we do so using a different sampling methodology in a different state. Respondents are asked to rate eight photographs that depict varying algae conditions. Our initial results show that Utah resident preferences for benthic algae levels are quite similar to those of Montana residents, thus replicating the Montana study. For the full Utah sample, though, Cronbach's α indicated poor internal consistency in rating the photographs, so a "monotonicity rule" was used to identify respondents providing monotonic preferences with respect to chlorophyll a densities. Simple graphical analyses are combined with ordered probit analysis to determine the maximum desirable density of chlorophyll a (Chl a). Our analysis indicates that Chl a levels in excess of 150 mg Chl a/m2 are undesirable, but the regression model suggests that those with strictly monotonic preferences were far more likely favor a more stringent standard.

Identifying and Validating Selection Tools for Predicting Officer Performance and Retention

DTIC Science & Technology

2017-05-01

Performance composite. Findings: Simple bivariate correlations indicated that the RBI Fitness Motivation scale was the strongest predictor of...Scored Job Knowledge Tests (JKTs) ............................................................ 14 Self-Report: Career History Survey (CHS...36 Bivariate Correlations

Optimum runway orientation relative to crosswinds

NASA Technical Reports Server (NTRS)

Falls, L. W.; Brown, S. C.

1972-01-01

Specific magnitudes of crosswinds may exist that could be constraints to the success of an aircraft mission such as the landing of the proposed space shuttle. A method is required to determine the orientation or azimuth of the proposed runway which will minimize the probability of certain critical crosswinds. Two procedures for obtaining the optimum runway orientation relative to minimizing a specified crosswind speed are described and illustrated with examples. The empirical procedure requires only hand calculations on an ordinary wind rose. The theoretical method utilizes wind statistics computed after the bivariate normal elliptical distribution is applied to a data sample of component winds. This method requires only the assumption that the wind components are bivariate normally distributed. This assumption seems to be reasonable. Studies are currently in progress for testing wind components for bivariate normality for various stations. The close agreement between the theoretical and empirical results for the example chosen substantiates the bivariate normal assumption.

Scientific Productivity and Academic Promotion: A Study on French and Italian Physicists. NBER Working Paper No. 16341

ERIC Educational Resources Information Center

Lissoni, Francesco; Mairesse, Jacques; Montobbio, Fabio; Pezzoni, Michele

2010-01-01

The paper examines the determinants of scientific productivity (number of articles and journals' impact factor) for a panel of about 3600 French and Italian academic physicists active in 2004-05. Endogeneity problems concerning promotion and productivity are addressed by specifying a generalized Tobit model, in which a selection probit equation…

The effect of trends in forest and ownership characteristics on recreational use of private forests

Treesearch

Donald F. Dennis

1992-01-01

Probit analysis was used to estimate correlations between recreational use of private woodland and forest, owner, and surrounding community characteristics. Land held by more highly educated owners or those reared in large cities was more likely to be used for recreation, while the opposite was true for land held by older owners.

Factors Influencing Recreational Use of Private Woodland

Treesearch

Donald F. Dennis; Donald F. Dennis

1990-01-01

Probit analysis was used to estimate relationships between the probability that forest land was used for recreation and characteristics of the forest, owner, and surrounding community. Land held by owners with more formal education or those reared in large cities was more likely to be used for recreation while the opposite was true for land held by older owners....

Estimation of Item Parameters and the GEM Algorithm.

ERIC Educational Resources Information Center

Tsutakawa, Robert K.

The models and procedures discussed in this paper are related to those presented in Bock and Aitkin (1981), where they considered the 2-parameter probit model and approximated a normally distributed prior distribution of abilities by a finite and discrete distribution. One purpose of this paper is to clarify the nature of the general EM (GEM)…

Site occupancy of brown-headed nuthatches varies with habitat restoration and range-limit context

Treesearch

Richard A. Stanton; Frank R. Thompson; Dylan C. Kesler

2015-01-01

Knowledge about species’ responses to habitat restoration can inform subsequent management and reintroduction planning. We used repeated call-response surveys to study brown-headed nuthatch (Sitta pusilla) patch occupancy at the current limits of its apparently expanding range in an area with active habitat restoration. We fit a probit occupancy...

Religious Background and Educational Attainment: The Effects of Buddhism, Islam, and Judaism

ERIC Educational Resources Information Center

Sander, William

2010-01-01

The effects of Buddhism, Islam, and Judaism on educational attainment in the United States are examined. OLS estimates of educational attainment and Probit estimates of college attainment are undertaken. It is shown that Islam and Judaism have similar positive effects on attainment relative to Protestants and Catholics. The effect of Buddhism is…

Does Alcohol Use during High School Affect Educational Attainment?: Evidence from the National Education Longitudinal Study

ERIC Educational Resources Information Center

Chatterji, Pinka

2006-01-01

This paper uses data from the National Education Longitudinal Study to estimate the association between high school alcohol use and educational attainment measured around age 26. Initially, the effect of alcohol use on educational attainment is estimated using baseline probit models, which ignore the possibility that unmeasured determinants of…

An alternate property tax program requiring a forest management plan and scheduled harvesting

Treesearch

D.F. Dennis; P.E. Sendak

1991-01-01

Vermont's Use Value Appraisal property tax program, designed to address problems such as tax inequity and forced development caused by taxing agricultural and forest land based on speculative values, requires a forest management plan and scheduled harvests. A probit analysis of enrollment provides evidence of the program's success in attracting large parcels...

The Effect of Overskilling Dynamics on Wages

ERIC Educational Resources Information Center

Mavromaras, Kostas; Mahuteau, Stephane; Sloane, Peter; Wei, Zhang

2013-01-01

We use a random-effects dynamic probit model to estimate the effect of overskilling dynamics on wages. We find that overskilling mismatch is common and more likely among those who have been overskilled in the past. It is also highly persistent, in a manner that is inversely related to educational level. Yet, the wages of university graduates are…

Linking harvest choices to timber supply

Treesearch

Jeffrey P. Prestemon; David N. Wear

2000-01-01

Aggregate timber supply by ownership was investigated for a small region by applying stand-level harvest choice models to a representative sample of stands and then aggregating to regional totals using the area-frame of the forest survey. Timber harvest choices were estimated as probit models for three ownership categories in coastal plain southern pine stands of North...

Persistence in the Determination of Work-Related Training Participation: Evidence from the BHPS, 1991-1997

ERIC Educational Resources Information Center

Sousounis, Panos; Bladen-Hovell, Robin

2010-01-01

In this paper we investigate the role of workers' training history in determining current training-incidence. The analysis is conducted on an unbalanced sample comprising information on approximately 5000 employees from the first seven waves of the BHPS. Training participation is modelled as a dynamic random effects probit model where the effects…

The Impact of School Socioeconomic Status on Student-Generated Teacher Ratings

ERIC Educational Resources Information Center

Agnew, Steve

2011-01-01

This paper uses ordinary least squares, logit and probit regressions, along with chi-square analysis applied to nationwide data from the New Zealand ratemyteacher website to establish if there is any correlation between student ratings of their teachers and the socioeconomic status of the school the students attend. The results show that students…

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 threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

Predictive spectroscopy and chemical imaging based on novel optical systems

NASA Astrophysics Data System (ADS)

Nelson, Matthew Paul

1998-10-01

This thesis describes two futuristic optical systems designed to surpass contemporary spectroscopic methods for predictive spectroscopy and chemical imaging. These systems are advantageous to current techniques in a number of ways including lower cost, enhanced portability, shorter analysis time, and improved S/N. First, a novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated. A regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. Second, a novel optical system is described which takes a single-shot approach to chemical imaging with high spectroscopic resolution using a dimension-reduction fiber-optic array. Images are focused onto a two- dimensional matrix of optical fibers which are drawn into a linear distal array with specific ordering. The distal end is imaged with a spectrograph equipped with an ICCD camera for spectral analysis. Software is used to extract the spatial/spectral information contained in the ICCD images and deconvolute them into wave length-specific reconstructed images or position-specific spectra which span a multi-wavelength space. This thesis includes a description of the fabrication of two dimension-reduction arrays as well as an evaluation of the system for spatial and spectral resolution, throughput, image brightness, resolving power, depth of focus, and channel cross-talk. PCA is performed on the images by treating rows of the ICCD images as spectra and plotting the scores of each PC as a function of reconstruction position. In addition, iterative target transformation factor analysis (ITTFA) is performed on the spectroscopic images to generate ``true'' chemical maps of samples. Univariate zero-order images, univariate first-order spectroscopic images, bivariate first-order spectroscopic images, and multivariate first-order spectroscopic images of the temporal development of laser-induced plumes are presented and interpreted. Reconstructed chemical images generated using bivariate and trivariate wavelength techniques, bimodal and trimodal PCA methods, and bimodal and trimodal ITTFA approaches are also included.

Bivariate sub-Gaussian model for stock index returns

NASA Astrophysics Data System (ADS)

Jabłońska-Sabuka, Matylda; Teuerle, Marek; Wyłomańska, Agnieszka

2017-11-01

Financial time series are commonly modeled with methods assuming data normality. However, the real distribution can be nontrivial, also not having an explicitly formulated probability density function. In this work we introduce novel parameter estimation and high-powered distribution testing methods which do not rely on closed form densities, but use the characteristic functions for comparison. The approach applied to a pair of stock index returns demonstrates that such a bivariate vector can be a sample coming from a bivariate sub-Gaussian distribution. The methods presented here can be applied to any nontrivially distributed financial data, among others.

Bayesian Estimation of Panel Data Fractional Response Models with Endogeneity: An Application to Standardized Test Rates

ERIC Educational Resources Information Center

Kessler, Lawrence M.

2013-01-01

In this paper I propose Bayesian estimation of a nonlinear panel data model with a fractional dependent variable (bounded between 0 and 1). Specifically, I estimate a panel data fractional probit model which takes into account the bounded nature of the fractional response variable. I outline estimation under the assumption of strict exogeneity as…

The Predicaments of Non-Residential Students in Ghanaian Institutions of Higher Education: A Micro-Level Empirical Evidence

ERIC Educational Resources Information Center

Addai, Isaac

2015-01-01

This paper in the field of capacity building and students' affairs used the external survey assessment techniques of the probit model to examine the predicaments of non-resident students of the College of Technology Education, University of Education, Winneba. Considering the very limited residential facilities and the growing demand for tertiary…

Socio-Economic Factors Affecting Adoption of Modern Information and Communication Technology by Farmers in India: Analysis Using Multivariate Probit Model

ERIC Educational Resources Information Center

Mittal, Surabhi; Mehar, Mamta

2016-01-01

Purpose: The paper analyzes factors that affect the likelihood of adoption of different agriculture-related information sources by farmers. Design/Methodology/Approach: The paper links the theoretical understanding of the existing multiple sources of information that farmers use, with the empirical model to analyze the factors that affect the…

Joint Analysis of Preschool Attendance and School Performance in the Short and Long-Run

ERIC Educational Resources Information Center

Aguilar, Renato; Tansini, Ruben

2012-01-01

This paper aims at explaining the academic performance of a sample of children starting their first year at public schools in Montevideo, Uruguay, during 1999. We are mainly interested in the effect of pre-school education on the children's academic results. Previous probit and OLS estimations suggested that pre-school education has a positive…

Visual Determination of Industrial Color-Difference Tolerances Using Probit Analysis

DTIC Science & Technology

1991-06-01

determine the median tolerance values of 45 color-difference vectors in CIELAB color space using surface mode viewing of paint samples. Nine different...8 4. Distribution Design for Color Centers in CIELAB Color Space ............................. 13 5. CIE Recommended Color Centers...compared to a near neutral anchor color- difference stimulus. The experiment concentrated on nine color centers systematically distributed in CIELAB color

An Analysis of the Social Impact of the Stipend Program for Secondary School Girls of Khyber Pakhtunkhwa

ERIC Educational Resources Information Center

Ahmed, Vaqar; Zeshan, Muhammad

2014-01-01

The present study carries out an impact analysis of a conditional cash transfer (CCT) program for secondary-school girls in seven districts of Khyber Pakhtunkhwa province in Pakistan, including Battagram, Bonair, Hangu, Kohistan, Shangla, Tank, and Upper Dir. In 2012 we collected household-level primary data and used a probit model for…

Who Is Overeducated and Why? Probit and Dynamic Mixed Multinomial Logit Analyses of Vertical Mismatch in East and West Germany

ERIC Educational Resources Information Center

Boll, Christina; Leppin, Julian Sebastian; Schömann, Klaus

2016-01-01

Overeducation potentially signals a productivity loss. With Socio-Economic Panel data from 1984 to 2011 we identify drivers of educational mismatch for East and West medium and highly educated Germans. Addressing measurement error, state dependence and unobserved heterogeneity, we run dynamic mixed multinomial logit models for three different…

A constrained multinomial Probit route choice model in the metro network: Formulation, estimation and application

PubMed Central

Zhang, Yongsheng; Wei, Heng; Zheng, Kangning

2017-01-01

Considering that metro network expansion brings us with more alternative routes, it is attractive to integrate the impacts of routes set and the interdependency among alternative routes on route choice probability into route choice modeling. Therefore, the formulation, estimation and application of a constrained multinomial probit (CMNP) route choice model in the metro network are carried out in this paper. The utility function is formulated as three components: the compensatory component is a function of influencing factors; the non-compensatory component measures the impacts of routes set on utility; following a multivariate normal distribution, the covariance of error component is structured into three parts, representing the correlation among routes, the transfer variance of route, and the unobserved variance respectively. Considering multidimensional integrals of the multivariate normal probability density function, the CMNP model is rewritten as Hierarchical Bayes formula and M-H sampling algorithm based Monte Carlo Markov Chain approach is constructed to estimate all parameters. Based on Guangzhou Metro data, reliable estimation results are gained. Furthermore, the proposed CMNP model also shows a good forecasting performance for the route choice probabilities calculation and a good application performance for transfer flow volume prediction. PMID:28591188

Gasto catastrófico en salud en México y sus factores determinantes, 2002-2014.

PubMed

Rodríguez-Aguilar, Román; Rivera-Peña, Gustavo

2017-01-01

To assess the financial protection of public health insurance by analyzing the percentage of households with catastrophic health expenditure (HCHE) in Mexico and its relationship with poverty status, size of locality, federal entity, insurance status and items of health spending. Mexican National Survey of Income and Expenditures 2002-2014 was used to estimate the percentage of HCHE. Through a probit model, factors associated with the occurrence of catastrophic spending are identified. Analysis was performed using Stata-SE 12. In 2014 there were 2.08% of HCHE (1.82-2.34%; N = 657,474). The estimated probit model correctly classified 98.2% of HCHE (Pr (D) ≥ 0.5). Factors affecting the catastrophic expenditures were affiliation, presence of chronic disease, hospitalization expenditure, rural condition and that the household is below the food poverty line. The percentage of HCHE decreased in recent years, improving financial protection in health. This decline seems to have stalled, keeping inequities in access to health services, especially in rural population without affiliation to any health institution, below the food poverty line and suffering from chronic diseases. Copyright: © 2017 SecretarÍa de Salud

Nonlinear spline wavefront reconstruction through moment-based Shack-Hartmann sensor measurements.

PubMed

Viegers, M; Brunner, E; Soloviev, O; de Visser, C C; Verhaegen, M

2017-05-15

We propose a spline-based aberration reconstruction method through moment measurements (SABRE-M). The method uses first and second moment information from the focal spots of the SH sensor to reconstruct the wavefront with bivariate simplex B-spline basis functions. The proposed method, since it provides higher order local wavefront estimates with quadratic and cubic basis functions can provide the same accuracy for SH arrays with a reduced number of subapertures and, correspondingly, larger lenses which can be beneficial for application in low light conditions. In numerical experiments the performance of SABRE-M is compared to that of the first moment method SABRE for aberrations of different spatial orders and for different sizes of the SH array. The results show that SABRE-M is superior to SABRE, in particular for the higher order aberrations and that SABRE-M can give equal performance as SABRE on a SH grid of halved sampling.

A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.

PubMed

Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea

2017-11-01

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

CI2 for creating and comparing confidence-intervals for time-series bivariate plots.

PubMed

Mullineaux, David R

2017-02-01

Currently no method exists for calculating and comparing the confidence-intervals (CI) for the time-series of a bivariate plot. The study's aim was to develop 'CI2' as a method to calculate the CI on time-series bivariate plots, and to identify if the CI between two bivariate time-series overlap. The test data were the knee and ankle angles from 10 healthy participants running on a motorised standard-treadmill and non-motorised curved-treadmill. For a recommended 10+ trials, CI2 involved calculating 95% confidence-ellipses at each time-point, then taking as the CI the points on the ellipses that were perpendicular to the direction vector between the means of two adjacent time-points. Consecutive pairs of CI created convex quadrilaterals, and any overlap of these quadrilaterals at the same time or ±1 frame as a time-lag calculated using cross-correlations, indicated where the two time-series differed. CI2 showed no group differences between left and right legs on both treadmills, but the same legs between treadmills for all participants showed differences of less knee extension on the curved-treadmill before heel-strike. To improve and standardise the use of CI2 it is recommended to remove outlier time-series, use 95% confidence-ellipses, and scale the ellipse by the fixed Chi-square value as opposed to the sample-size dependent F-value. For practical use, and to aid in standardisation or future development of CI2, Matlab code is provided. CI2 provides an effective method to quantify the CI of bivariate plots, and to explore the differences in CI between two bivariate time-series. Copyright © 2016 Elsevier B.V. All rights reserved.

Bivariate at-site frequency analysis of simulated flood peak-volume data using copulas

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Viglione, Alberto; Szolgay, Ján.; Blöschl, Günter; Bacigál, Tomáå.¡

2010-05-01

In frequency analysis of joint hydro-climatological extremes (flood peaks and volumes, low flows and durations, etc.), usually, bivariate distribution functions are fitted to the observed data in order to estimate the probability of their occurrence. Bivariate models, however, have a number of limitations; therefore, in the recent past, dependence models based on copulas have gained increased attention to represent the joint probabilities of hydrological characteristics. Regardless of whether standard or copula based bivariate frequency analysis is carried out, one is generally interested in the extremes corresponding to low probabilities of the fitted joint cumulative distribution functions (CDFs). However, usually there is not enough flood data in the right tail of the empirical CDFs to derive reliable statistical inferences on the behaviour of the extremes. Therefore, different techniques are used to extend the amount of information for the statistical inference, i.e., temporal extension methods that allow for making use of historical data or spatial extension methods such as regional approaches. In this study, a different approach was adopted which uses simulated flood data by rainfall-runoff modelling, to increase the amount of data in the right tail of the CDFs. In order to generate artificial runoff data (i.e. to simulate flood records of lengths of approximately 106 years), a two-step procedure was used. (i) First, the stochastic rainfall generator proposed by Sivapalan et al. (2005) was modified for our purpose. This model is based on the assumption of discrete rainfall events whose arrival times, durations, mean rainfall intensity and the within-storm intensity patterns are all random, and can be described by specified distributions. The mean storm rainfall intensity is disaggregated further to hourly intensity patterns. (ii) Secondly, the simulated rainfall data entered a semi-distributed conceptual rainfall-runoff model that consisted of a snow routine, a soil moisture routine and a flow routing routine (Parajka et al., 2007). The applicability of the proposed method was demonstrated on selected sites in Slovakia and Austria. The pairs of simulated flood volumes and flood peaks were analysed in terms of their dependence structure and different families of copulas (Archimedean, extreme value, Gumbel-Hougaard, etc.) were fitted to the observed and simulated data. The question to what extent measured data can be used to find the right copula was discussed. The study is supported by the Austrian Academy of Sciences and the Austrian-Slovak Co-operation in Science and Education "Aktion". Parajka, J., Merz, R., Blöschl, G., 2007: Uncertainty and multiple objective calibration in regional water balance modeling - Case study in 320 Austrian catchments. Hydrological Processes, 21, 435-446. Sivapalan, M., Blöschl, G., Merz, R., Gutknecht, D., 2005: Linking flood frequency to long-term water balance: incorporating effects of seasonality. Water Resources Research, 41, W06012, doi:10.1029/2004WR003439.

An intensive monitoring campaign of PAHs for assessing the impact of a steel plant.

PubMed

Di Gilio, A; Ventrella, G; Giungato, P; Tutino, M; Giua, R; Assennato, G; de Gennaro, G

2017-02-01

This study provided a useful approach for assessing the impact of industrial sources on surrounding, especially in a sensitive industrial area as Taranto (South of Italy). Taranto is one of the most industrialized Italian towns, where several emission sources operate simultaneously in proximity to the urban settlement. An intensive monitoring campaign of PAHs was carried out from January 28th to July 30th, 2011, in seven sites located in residential settlement around the industrial area and in the city center. The collected data were integrated with the information about wind direction and speed by means bivariate polarplot in order to characterize and localize the industrial sources. High BaP concentrations were detected especially when Benzene to Toluene ratio (B/T ratio) values excedeed 1 and all receptor sites were downwind to the steel plant. Moreover, in order to discriminate among PAH sources and quantify their contributions, a source apportionment analysis of the collected data was provided by means Principal component Analysis (PCA) and Positive Matrix Factorization (PMF) methods. Finally, the processing of PMF5.0 output by bivariate polar plot, confirmed the impact of steel plant on both industrial sites downwind the steel plant and the city center. B[a]P apportionment was quite similar for industrial and urban sites: the traffic source contributed only 11% and 24% to B[a]P measured at two sites, respectively. Therefore, the proximity of Taranto downtown to industrial pole makes negligible all other source contributions to PAH concentrations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Univariate and Bivariate Loglinear Models for Discrete Test Score Distributions.

ERIC Educational Resources Information Center

Holland, Paul W.; Thayer, Dorothy T.

2000-01-01

Applied the theory of exponential families of distributions to the problem of fitting the univariate histograms and discrete bivariate frequency distributions that often arise in the analysis of test scores. Considers efficient computation of the maximum likelihood estimates of the parameters using Newton's Method and computationally efficient…

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Using fixed-parameter and random-parameter ordered regression models to identify significant factors that affect the severity of drivers' injuries in vehicle-train collisions.

PubMed

Dabbour, Essam; Easa, Said; Haider, Murtaza

2017-10-01

This study attempts to identify significant factors that affect the severity of drivers' injuries when colliding with trains at railroad-grade crossings by analyzing the individual-specific heterogeneity related to those factors over a period of 15 years. Both fixed-parameter and random-parameter ordered regression models were used to analyze records of all vehicle-train collisions that occurred in the United States from January 1, 2001 to December 31, 2015. For fixed-parameter ordered models, both probit and negative log-log link functions were used. The latter function accounts for the fact that lower injury severity levels are more probable than higher ones. Separate models were developed for heavy and light-duty vehicles. Higher train and vehicle speeds, female, and young drivers (below the age of 21 years) were found to be consistently associated with higher severity of drivers' injuries for both heavy and light-duty vehicles. Furthermore, favorable weather, light-duty trucks (including pickup trucks, panel trucks, mini-vans, vans, and sports-utility vehicles), and senior drivers (above the age of 65 years) were found be consistently associated with higher severity of drivers' injuries for light-duty vehicles only. All other factors (e.g. air temperature, the type of warning devices, darkness conditions, and highway pavement type) were found to be temporally unstable, which may explain the conflicting findings of previous studies related to those factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Role of Education Pathways in the Relationship between Job Mismatch, Wages and Job Satisfaction: A Panel Estimation Approach

ERIC Educational Resources Information Center

Mavromaras, Kostas; Sloane, Peter; Wei, Zhang

2012-01-01

This paper examines the outcome of over-skilling and over-education on wages and job satisfaction of full-time employees in Australia between 2001 and 2008. We employ a random effects probit model with Mundlak corrections. We find differences by type of mismatch, education pathway, and gender. We categorise reported mismatches as genuine…

'Whatever She May Study, She Can't Escape from Washing Dishes': Gender Inequity in Secondary Education--Evidence from a Longitudinal Study in India

ERIC Educational Resources Information Center

Singh, Renu; Mukherjee, Protap

2018-01-01

Using unique panel data from Young Lives study conducted in undivided Andhra Pradesh, India, this mixed-method paper analyses gender differentials in completion of secondary education. Results show biased secondary school completion rates in favor of boys. Probit regression results highlight certain variables such as mothers' education, wealth,…

Filter Paper Blood Spot Enzyme Linked Immunoassay for Adiponectin and Application in the Evaluation of Determinants of Child Insulin Sensitivity

PubMed Central

Martin, Richard M.; Patel, Rita; Oken, Emily; Thompson, Jennifer; Zinovik, Alexander; Kramer, Michael S.; Vilchuck, Konstantin; Bogdanovich, Natalia; Sergeichick, Natalia; Foo, Ying; Gusina, Nina

2013-01-01

Background Adiponectin is an adipocyte-derived hormone that acts as a marker of insulin sensitivity. Bloodspot sampling by fingerstick onto filter paper may increase the feasibility of large-scale studies of the determinants of insulin sensitivity. We first describe the validation of an enzyme-linked immunoassay (ELISA) for quantifying adiponectin from dried blood spots and then demonstrate its application in a large trial (PROBIT). Methods We quantified adiponectin from 3-mm diameter discs (≈3 µL of blood) punched from dried blood spots obtained from: i) whole blood standards (validation); and ii) PROBIT trial samples (application) in which paediatricians collected blood spots from 13,879 children aged 11.5 years from 31 sites across Belarus. We examined the distribution of bloodspot adiponectin by demographic and anthropometric factors, fasting insulin and glucose. Results In the validation study, mean intra-assay coefficients of variation (n = 162) were 15%, 13% and 10% for ‘low’ (6.78 µg/ml), ‘medium’ (18.18 µg/ml) and 'high’ (33.13 µg/ml) internal quality control (IQC) samples, respectively; the respective inter-assay values (n = 40) were 23%, 21% and 14%. The correlation coefficient between 50 paired whole bloodspot versus plasma samples, collected simultaneously, was 0.87 (95% CI: 0.78 to 0.93). Recovery of known quantities of adiponectin (between 4.5 to 36 µg/ml) was 100.3–133%. Bloodspot adiponectin was stable for at least 30 months at −80°C. In PROBIT, we successfully quantified fasting adiponectin from dried blood spots in 13,329 of 13,879 (96%) children. Mean adiponectin (standard deviation) concentrations were 17.34 µg/ml (7.54) in boys and 18.41 µg/ml (7.92) in girls and were inversely associated with body mass index, fat mass, triceps and subscapular skin-fold thickness, waist circumference, height and fasting glucose. Conclusions Bloodspot ELISA is suitable for measuring adiponectin in very small volumes of blood collected on filter paper and can be applied to large-scale studies. PMID:23936498

Mechanism-based model for tumor drug resistance.

PubMed

Kuczek, T; Chan, T C

1992-01-01

The development of tumor resistance to cytotoxic agents has important implications in the treatment of cancer. If supported by experimental data, mathematical models of resistance can provide useful information on the underlying mechanisms and aid in the design of therapeutic regimens. We report on the development of a model of tumor-growth kinetics based on the assumption that the rates of cell growth in a tumor are normally distributed. We further assumed that the growth rate of each cell is proportional to its rate of total pyrimidine synthesis (de novo plus salvage). Using an ovarian carcinoma cell line (2008) and resistant variants selected for chronic exposure to a pyrimidine antimetabolite, N-phosphonacetyl-L-aspartate (PALA), we derived a simple and specific analytical form describing the growth curves generated in 72 h growth assays. The model assumes that the rate of de novo pyrimidine synthesis, denoted alpha, is shifted down by an amount proportional to the log10 PALA concentration and that cells whose rate of pyrimidine synthesis falls below a critical level, denoted alpha 0, can no longer grow. This is described by the equation: Probability (growth) = probability (alpha 0 less than alpha-constant x log10 [PALA]). This model predicts that when growth curves are plotted on probit paper, they will produce straight lines. This prediction is in agreement with the data we obtained for the 2008 cells. Another prediction of this model is that the same probit plots for the resistant variants should shift to the right in a parallel fashion. Probit plots of the dose-response data obtained for each resistant 2008 line following chronic exposure to PALA again confirmed this prediction. Correlation of the rightward shift of dose responses to uridine transport (r = 0.99) also suggests that salvage metabolism plays a key role in tumor-cell resistance to PALA. Furthermore, the slope of the regression lines enables the detection of synergy such as that observed between dipyridamole and PALA. Although the rate-normal model was used to study the rate of salvage metabolism in PALA resistance in the present study, it may be widely applicable to modeling of other resistance mechanisms such as gene amplification of target enzymes.

Bivariate normal, conditional and rectangular probabilities: A computer program with applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.; Ashwworth, G. R.; Winter, W. R.

1980-01-01

Some results for the bivariate normal distribution analysis are presented. Computer programs for conditional normal probabilities, marginal probabilities, as well as joint probabilities for rectangular regions are given: routines for computing fractile points and distribution functions are also presented. Some examples from a closed circuit television experiment are included.

Contributions to the Underlying Bivariate Normal Method for Factor Analyzing Ordinal Data

ERIC Educational Resources Information Center

Xi, Nuo; Browne, Michael W.

2014-01-01

A promising "underlying bivariate normal" approach was proposed by Jöreskog and Moustaki for use in the factor analysis of ordinal data. This was a limited information approach that involved the maximization of a composite likelihood function. Its advantage over full-information maximum likelihood was that very much less computation was…

The Effects of Selection Strategies for Bivariate Loglinear Smoothing Models on NEAT Equating Functions

ERIC Educational Resources Information Center

Moses, Tim; Holland, Paul W.

2010-01-01

In this study, eight statistical strategies were evaluated for selecting the parameterizations of loglinear models for smoothing the bivariate test score distributions used in nonequivalent groups with anchor test (NEAT) equating. Four of the strategies were based on significance tests of chi-square statistics (Likelihood Ratio, Pearson,…

Simultaneous determination of Nifuroxazide and Drotaverine hydrochloride in pharmaceutical preparations by bivariate and multivariate spectral analysis

NASA Astrophysics Data System (ADS)

Metwally, Fadia H.

2008-02-01

The quantitative predictive abilities of the new and simple bivariate spectrophotometric method are compared with the results obtained by the use of multivariate calibration methods [the classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS)], using the information contained in the absorption spectra of the appropriate solutions. Mixtures of the two drugs Nifuroxazide (NIF) and Drotaverine hydrochloride (DRO) were resolved by application of the bivariate method. The different chemometric approaches were applied also with previous optimization of the calibration matrix, as they are useful in simultaneous inclusion of many spectral wavelengths. The results found by application of the bivariate, CLS, PCR and PLS methods for the simultaneous determinations of mixtures of both components containing 2-12 μg ml -1 of NIF and 2-8 μg ml -1 of DRO are reported. Both approaches were satisfactorily applied to the simultaneous determination of NIF and DRO in pure form and in pharmaceutical formulation. The results were in accordance with those given by the EVA Pharma reference spectrophotometric method.

Meta-analysis of diagnostic test data: a bivariate Bayesian modeling approach.

PubMed

Verde, Pablo E

2010-12-30

In the last decades, the amount of published results on clinical diagnostic tests has expanded very rapidly. The counterpart to this development has been the formal evaluation and synthesis of diagnostic results. However, published results present substantial heterogeneity and they can be regarded as so far removed from the classical domain of meta-analysis, that they can provide a rather severe test of classical statistical methods. Recently, bivariate random effects meta-analytic methods, which model the pairs of sensitivities and specificities, have been presented from the classical point of view. In this work a bivariate Bayesian modeling approach is presented. This approach substantially extends the scope of classical bivariate methods by allowing the structural distribution of the random effects to depend on multiple sources of variability. Meta-analysis is summarized by the predictive posterior distributions for sensitivity and specificity. This new approach allows, also, to perform substantial model checking, model diagnostic and model selection. Statistical computations are implemented in the public domain statistical software (WinBUGS and R) and illustrated with real data examples. Copyright © 2010 John Wiley & Sons, Ltd.

Mixture models in diagnostic meta-analyses--clustering summary receiver operating characteristic curves accounted for heterogeneity and correlation.

PubMed

Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario

2015-01-01

Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.

Time-dependent summary receiver operating characteristics for meta-analysis of prognostic studies.

PubMed

Hattori, Satoshi; Zhou, Xiao-Hua

2016-11-20

Prognostic studies are widely conducted to examine whether biomarkers are associated with patient's prognoses and play important roles in medical decisions. Because findings from one prognostic study may be very limited, meta-analyses may be useful to obtain sound evidence. However, prognostic studies are often analyzed by relying on a study-specific cut-off value, which can lead to difficulty in applying the standard meta-analysis techniques. In this paper, we propose two methods to estimate a time-dependent version of the summary receiver operating characteristics curve for meta-analyses of prognostic studies with a right-censored time-to-event outcome. We introduce a bivariate normal model for the pair of time-dependent sensitivity and specificity and propose a method to form inferences based on summary statistics reported in published papers. This method provides a valid inference asymptotically. In addition, we consider a bivariate binomial model. To draw inferences from this bivariate binomial model, we introduce a multiple imputation method. The multiple imputation is found to be approximately proper multiple imputation, and thus the standard Rubin's variance formula is justified from a Bayesian view point. Our simulation study and application to a real dataset revealed that both methods work well with a moderate or large number of studies and the bivariate binomial model coupled with the multiple imputation outperforms the bivariate normal model with a small number of studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Bivariate genome-wide association analyses identified genetic pleiotropic effects for bone mineral density and alcohol drinking in Caucasians

PubMed Central

Lu, Shan; Zhao, Lan-Juan; Chen, Xiang-Ding; Papasian, Christopher J.; Wu, Ke-Hao; Tan, Li-Jun; Wang, Zhuo-Er; Pei, Yu-Fang; Tian, Qing

2018-01-01

Several studies indicated bone mineral density (BMD) and alcohol intake might share common genetic factors. The study aimed to explore potential SNPs/genes related to both phenotypes in US Caucasians at the genome-wide level. A bivariate genome-wide association study (GWAS) was performed in 2069 unrelated participants. Regular drinking was graded as 1, 2, 3, 4, 5, or 6, representing drinking alcohol never, less than once, once or twice, three to six times, seven to ten times, or more than ten times per week respectively. Hip, spine, and whole body BMDs were measured. The bivariate GWAS was conducted on the basis of a bivariate linear regression model. Sex-stratified association analyses were performed in the male and female subgroups. In males, the most significant association signal was detected in SNP rs685395 in DYNC2H1 with bivariate spine BMD and alcohol drinking (P = 1.94 × 10−8). SNP rs685395 and five other SNPs, rs657752, rs614902, rs682851, rs626330, and rs689295, located in the same haplotype block in DYNC2H1 were the top ten most significant SNPs in the bivariate GWAS in males. Additionally, two SNPs in GRIK4 in males and three SNPs in OPRM1 in females were suggestively associated with BMDs (of the hip, spine, and whole body) and alcohol drinking. Nine SNPs in IL1RN were only suggestively associated with female whole body BMD and alcohol drinking. Our study indicated that DYNC2H1 may contribute to the genetic mechanisms of both spine BMD and alcohol drinking in male Caucasians. Moreover, our study suggested potential pleiotropic roles of OPRM1 and IL1RN in females and GRIK4 in males underlying variation of both BMD and alcohol drinking. PMID:28012008

A bivariate model for analyzing recurrent multi-type automobile failures

NASA Astrophysics Data System (ADS)

Sunethra, A. A.; Sooriyarachchi, M. R.

2017-09-01

The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by the bivariate model. The proposed model can be used to determine the time and type of failure that would occur in the automobiles considered here.

Gram-Negative Bacterial Wound Infections

DTIC Science & Technology

2014-05-01

shows an effect with increasing concentration, however survival analysis does not show a significant difference between treatment groups and controls ...with 3 dead larvae in the 25 mM group compared to a single dead larva in the control group (Fig. 7). Probit analysis estimates the lethal...statistically differ- ent from that of the control group . The levels (CFU/g) of bacteria in lung tissue correlated with the survival curves. The median

Potential for hypobaric storage as a phytosanitary treatment: Mortality of Rhagoletis pomonella (Diptera: Tephritidae) in apples and effects on fruit quality

USDA-ARS?s Scientific Manuscript database

The efficacy of low-oxygen atmospheres using low pressure, referred to as hypobaric conditions, to kill egg and 3rd instar Rhagoletis pomonella (Walsh) in apples was investigated. Infested apples were exposed to 3.33 and 6.67 kPa in glass jars at 25 and 30°C for 3-120 h. Probit analyses and lethal-d...

"You Pay Your Share, We'll Pay Our Share": The College Cost Burden and the Role of Race, Income, and College Assets

ERIC Educational Resources Information Center

Elliott, William; Friedline, Terri

2013-01-01

Changes in financial aid policies raise questions about students being asked to pay too much for college and whether parents' college savings for their children helps reduce the burden on students to pay for college. Using trivariate probit analysis with predicted probabilities, in this exploratory study we find recent changes in the financial aid…

Pricing behaviour of pharmacies after market deregulation for OTC drugs: the case of Germany.

PubMed

Stargardt, Tom; Schreyögg, Jonas; Busse, Reinhard

2007-11-01

To examine the price reactions of German pharmacies to changes made to OTC drug regulations in 2004. Prior to these changes, regulations guaranteed identical prices in all German pharmacies. Two years after market deregulation, 256 pharmacies were surveyed to determine the retail prices of five selected OTC drugs. A probit regression model was used to identify factors that increased the likelihood of price changes. In addition, 409 pharmacy consumers were interviewed to gather information on their knowledge of the regulatory changes and to better explain consumer behaviour. Data was collected on a total of 1215 prices. Two years after deregulation, 23.1% of the participating pharmacies had modified the price of at least one of the five OTCs included in our study. However, in total, only 7.5% of the prices differed from their pre-deregulation level. The probit model showed that population density and the geographic concentration of pharmacies were significantly associated with price changes. Interestingly, the association with the geographic concentration of pharmacies was negative. The consumer survey revealed that 47.1% of those interviewed were aware of the deregulation. Our findings indicate that, two years after deregulation, very few pharmacies had made use of individual pricing strategies; price competition between pharmacies in Germany is thus taking place only a very small scale.

Job tenure and self-reported workplace discrimination for cancer survivors 2 years after diagnosis: does employment legislation matter?

PubMed

Paraponaris, Alain; Teyssier, Luis Sagaon; Ventelou, Bruno

2010-12-01

To assess the risk of leaving employment for cancer survivors 2 years after diagnosis and the role of workplace discrimination in this risk. A representative sample of 4270 French individuals older than 17 and younger than 58 years when diagnosed with cancer in 2002 were interviewed 2 years later. Their occupational status was analyzed with the help of Probit and IV-Probit models. Overall, 66% of the cancer survivors who were working at the time of diagnosis were still employed 2 years later. Age, education level, income at diagnosis, work contract, professional status, affective support, relative prognosis at diagnosis, tumor site and treatment have contrasting impacts upon the probability of job loss across gender. Even after having controlled for these variables, self-reported workplace discrimination increases the probability of job loss by 15%. Despite protective labor law and favorable health insurance arrangements, French cancer survivors continue to experience problems to stay in or to return to the labor force. Measures targeting only the employment protection of cancer survivors do not seem to be sufficient to end prior social inequalities in job attainment. Intervention for specific populations particularly exposed to job-loss risks would also be needed. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

PubMed

Tang, Yongqiang

2018-04-30

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods. Copyright © 2018 John Wiley & Sons, Ltd.

A flexible model for multivariate interval-censored survival times with complex correlation structure.

PubMed

Falcaro, Milena; Pickles, Andrew

2007-02-10

We focus on the analysis of multivariate survival times with highly structured interdependency and subject to interval censoring. Such data are common in developmental genetics and genetic epidemiology. We propose a flexible mixed probit model that deals naturally with complex but uninformative censoring. The recorded ages of onset are treated as possibly censored ordinal outcomes with the interval censoring mechanism seen as arising from a coarsened measurement of a continuous variable observed as falling between subject-specific thresholds. This bypasses the requirement for the failure times to be observed as falling into non-overlapping intervals. The assumption of a normal age-of-onset distribution of the standard probit model is relaxed by embedding within it a multivariate Box-Cox transformation whose parameters are jointly estimated with the other parameters of the model. Complex decompositions of the underlying multivariate normal covariance matrix of the transformed ages of onset become possible. The new methodology is here applied to a multivariate study of the ages of first use of tobacco and first consumption of alcohol without parental permission in twins. The proposed model allows estimation of the genetic and environmental effects that are shared by both of these risk behaviours as well as those that are specific. 2006 John Wiley & Sons, Ltd.

Study on the Rationality and Validity of Probit Models of Domino Effect to Chemical Process Equipment caused by Overpressure

NASA Astrophysics Data System (ADS)

Sun, Dongliang; Huang, Guangtuan; Jiang, Juncheng; Zhang, Mingguang; Wang, Zhirong

2013-04-01

Overpressure is one important cause of domino effect in accidents of chemical process equipments. Some models considering propagation probability and threshold values of the domino effect caused by overpressure have been proposed in previous study. In order to prove the rationality and validity of the models reported in the reference, two boundary values of three damage degrees reported were considered as random variables respectively in the interval [0, 100%]. Based on the overpressure data for damage to the equipment and the damage state, and the calculation method reported in the references, the mean square errors of the four categories of damage probability models of overpressure were calculated with random boundary values, and then a relationship of mean square error vs. the two boundary value was obtained, the minimum of mean square error was obtained, compared with the result of the present work, mean square error decreases by about 3%. Therefore, the error was in the acceptable range of engineering applications, the models reported can be considered reasonable and valid.

Difference in rural and urban driver-injury severities in highway-rail grade crossing accidents.

PubMed

Hao, Wei; Kamga, Camille

2017-06-01

Based on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive research, analysis results showed that there were substantial differences between rural and urban areas at highway-rail grade crossings. However, there is no published study specific on driver's injury severity at highway-rail grade crossings classified by area types. Using an ordered probit modelling approach, the study explores the determinants of driver-injury severity at rural highway-rail grade crossings compared with urban highway-rail grade crossings. The analysis found that motor vehicle driver's injury level at rural highway-rail grade crossing is extremely higher than urban area. Compared to collisions at urban area, collisions happened at rural area tend to result in more severe injuries. These crashes were more prevalent if vehicle drivers are driving at a high speed or the oncoming trains are high-speed. Moreover, highway-rail grade crossing accidents were more likely to occur at rural area without pavement and lighting.

Motor vehicle driver injury severity study under various traffic control at highway-rail grade crossings in the United States.

PubMed

Hao, Wei; Daniel, Janice

2014-12-01

Based on the Federal Railway Administration (FRA) database, approximately 62% of the collisions at highway-rail crossings occurred at locations with active controls (gate and flashing lights), followed by passive controls (cross bucks and stop signs) with approximately 28% of accidents. The study applied an ordered probit model to explore the determinants of driver injury severity under various control measures at highway-rail grade crossing in the United States. The analysis found that schedule factor (peak hour), visibility, motor vehicle speed, train speed, driver's age, area type, traffic volume and highway pavement impact driver injury severity at both active and passive highway-rail crossings. For both active and passive control highway-rail grade crossings, speed control for both trains and vehicles will significantly reduce driver injury severity. However, the level of influence by vehicle speed and train speed at passive control is higher compared with active control. Paving highways at highway-rail grade crossings will also help to reduce driver injury severity at highway-rail crossing accidents. Published by Elsevier Ltd.

Structural Zeros and Their Implications with Log-Linear Bivariate Presmoothing under the Internal-Anchor Design

ERIC Educational Resources Information Center

Kim, Hyung Jin; Brennan, Robert L.; Lee, Won-Chan

2017-01-01

In equating, when common items are internal and scoring is conducted in terms of the number of correct items, some pairs of total scores ("X") and common-item scores ("V") can never be observed in a bivariate distribution of "X" and "V"; these pairs are called "structural zeros." This simulation…

Creating Realistic Data Sets with Specified Properties via Simulation

ERIC Educational Resources Information Center

Goldman, Robert N.; McKenzie, John D. Jr.

2009-01-01

We explain how to simulate both univariate and bivariate raw data sets having specified values for common summary statistics. The first example illustrates how to "construct" a data set having prescribed values for the mean and the standard deviation--for a one-sample t test with a specified outcome. The second shows how to create a bivariate data…

Multi scale habitat relationships of Martes americana in northern Idaho, U.S.A.

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; David O. Wallin; Jim Hayden

2012-01-01

We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in...

Statistical power of intervention analyses: simulation and empirical application to treated lumber prices

Treesearch

Jeffrey P. Prestemon

2009-01-01

Timber product markets are subject to large shocks deriving from natural disturbances and policy shifts. Statistical modeling of shocks is often done to assess their economic importance. In this article, I simulate the statistical power of univariate and bivariate methods of shock detection using time series intervention models. Simulations show that bivariate methods...

Bivariate copula in fitting rainfall data

NASA Astrophysics Data System (ADS)

Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

2014-07-01

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).

Vector wind profile gust model

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1981-01-01

To enable development of a vector wind gust model suitable for orbital flight test operations and trade studies, hypotheses concerning the distributions of gust component variables were verified. Methods for verification of hypotheses that observed gust variables, including gust component magnitude, gust length, u range, and L range, are gamma distributed and presented. Observed gust modulus has been drawn from a bivariate gamma distribution that can be approximated with a Weibull distribution. Zonal and meridional gust components are bivariate gamma distributed. An analytical method for testing for bivariate gamma distributed variables is presented. Two distributions for gust modulus are described and the results of extensive hypothesis testing of one of the distributions are presented. The validity of the gamma distribution for representation of gust component variables is established.

The effect of crash characteristics on cyclist injuries: An analysis of Virginia automobile-bicycle crash data.

PubMed

Robartes, Erin; Chen, T Donna

2017-07-01

This paper examines bicyclist, automobile driver, vehicle, environmental, and roadway characteristics that influence cyclist injury severity in order to determine which factors should be addressed to mitigate the worst bicyclist injuries. An ordered probit model is used to examine single bicycle-single vehicle crashes from Virginia police crash report data from 2010 to 2014. Five injury severity levels are considered: fatalities, severe injuries, minor or possible injuries, no apparent injuries, and no injury. The results of this study most notably found automobile driver intoxication to increase the probability of a cyclist fatality six fold and double the risk of a severe injury, while bicyclist intoxication increases the probability of a fatality by 36.7% and doubles the probability of severe injury. Additionally, bicycle and automobile speeds, obscured automobile driver vision, specific vehicle body types (SUV, truck, and van), vertical roadway grades and horizontal curves elevate the probability of more severe bicyclist injuries. Model results encourage consideration of methods to reduce the impact of biking and driving while intoxicated such as analysis of bicycling under the influence laws, education of drunk driving impacts on bicyclists, and separation of vehicles and bicycles on the road. Additionally, the results encourage consideration of methods to improve visibility of bicyclists and expectation of their presence on the road. Copyright © 2017 Elsevier Ltd. All rights reserved.

The influence of institutional pressures on hospital electronic health record presence.

PubMed

Fareed, Naleef; Bazzoli, Gloria J; Farnsworth Mick, Stephen S; Harless, David W

2015-05-01

Electronic health records (EHR) are a promising form of health information technology that could help US hospitals improve on their quality of care and costs. During the study period explored (2005-2009), high expectations for EHR diffused across institutional stakeholders in the healthcare environment, which may have pressured hospitals to have EHR capabilities even in the presence of weak technical rationale for the technology. Using an extensive set of organizational theory-specific predictors, this study explored whether five factors - cause, constituents, content, context, and control - that reflect the nature of institutional pressures for EHR capabilities motivated hospitals to comply with these pressures. Using information from several national data bases, an ordered probit regression model was estimated. The resulting predicted probabilities of EHR capabilities from the empirical model's estimates were used to test the study's five hypotheses, of which three were supported. When the underlying cause, dependence on constituents, or influence of control were high and potential countervailing forces were low, hospitals were more likely to employ strategic responses that were compliant with the institutional pressures for EHR capabilities. In light of these pressures, hospitals may have acquiesced, by having comprehensive EHR capabilities, or compromised, by having intermediate EHR capabilities, in order to maintain legitimacy in their environment. The study underscores the importance of our assessment for theory and policy development, and provides suggestions for future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Malnutrition, menarche, and marriage in rural Bangladesh.

PubMed

Chowdhury, A K; Huffman, S L; Curlin, G T

1977-01-01

In order to assess the impact of nutritional status on the onset of menarche and the association between age at menarche and age at marriage, a survey of 1155 girls, ages 10 through 20, was conducted in a rural area of Bangladesh in March 1976. In order to obtain an estimated mean of age of menarche, probit analysis was used. The mean age of menarche using this technique is estimated at 15.65 for Muslims and 15.91 for Hindus. It was learned that in recent years the age of menarche has increased in a rural area. This increase seems to be associated with malnutrition caused by the war, postwar inflation, floods and famines during the 1971-75 period. When age is controlled for, the prominent effect of weight on menstrual status is evident. 98% of the girls whose weights were 88 pounds or greater had reached menarche compared to only 1% of those weighing less than 66 pounds. Body weight appears to be 1 of the most important factors for the determination of onset of menarche. There exists a seasonality of onset of menarche with a peak in winter. Age of marriage among this rural population has increased and may be associated with the increasing age of menarche. Since both age of menarche and age of marriage have increased, fertility among females age 15-19 may be expected to decrease in the future if this pattern continues.

Hydrologic risk analysis in the Yangtze River basin through coupling Gaussian mixtures into copulas

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, W. W.; Huang, G. H.; Li, Y. P.; Huang, K.; Li, Z.

2016-02-01

In this study, a bivariate hydrologic risk framework is proposed through coupling Gaussian mixtures into copulas, leading to a coupled GMM-copula method. In the coupled GMM-Copula method, the marginal distributions of flood peak, volume and duration are quantified through Gaussian mixture models and the joint probability distributions of flood peak-volume, peak-duration and volume-duration are established through copulas. The bivariate hydrologic risk is then derived based on the joint return period of flood variable pairs. The proposed method is applied to the risk analysis for the Yichang station on the main stream of the Yangtze River, China. The results indicate that (i) the bivariate risk for flood peak-volume would keep constant for the flood volume less than 1.0 × 105 m3/s day, but present a significant decreasing trend for the flood volume larger than 1.7 × 105 m3/s day; and (ii) the bivariate risk for flood peak-duration would not change significantly for the flood duration less than 8 days, and then decrease significantly as duration value become larger. The probability density functions (pdfs) of the flood volume and duration conditional on flood peak can also be generated through the fitted copulas. The results indicate that the conditional pdfs of flood volume and duration follow bimodal distributions, with the occurrence frequency of the first vertex decreasing and the latter one increasing as the increase of flood peak. The obtained conclusions from the bivariate hydrologic analysis can provide decision support for flood control and mitigation.

Shared genetic factors underlie migraine and depression

PubMed Central

Yang, Yuanhao; Zhao, Huiying; Heath, Andrew C; Madden, Pamela AF; Martin, Nicholas G; Nyholt, Dale R

2017-01-01

Migraine frequently co-occurs with depression. Using a large sample of Australian twin pairs, we aimed to characterise the extent to which shared genetic factors underlie these two disorders. Migraine was classified using three diagnostic measures, including self-reported migraine, the ID migraine™ screening tool, or migraine without aura (MO) and migraine with aura (MA) based on International Headache Society (IHS) diagnostic criteria. Major depressive disorder (MDD) and minor depressive disorder (MiDD) were classified using the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. Univariate and bivariate twin models, with and without sex-limitation, were constructed to estimate the univariate and bivariate variance components and genetic correlation for migraine and depression. The univariate heritability of broad migraine (self-reported, ID migraine or IHS MO/MA) and broad depression (MiDD or MDD) was estimated at 56% (95% confidence interval [CI]: 53–60%) and 42% (95% CI: 37–46%), respectively. A significant additive genetic correlation (rG=0.36, 95% CI: 0.29–0.43) and bivariate heritability (h2=5.5%, 95% CI: 3.6–7.8%) was observed between broad migraine and depression using the bivariate Cholesky model. Notably, both the bivariate h2 (13.3%, 95% CI: 7.0–24.5%) and rG (0.51, 95% CI: 0.37–0.69) estimates significantly increased when analysing the more narrow clinically-accepted diagnoses of IHS MO/MA and MDD. Our results indicate that for both broad and narrow definitions, the observed comorbidity between migraine and depression can be explained almost entirely by shared underlying genetically determined disease mechanisms. PMID:27302564

A survey of variable selection methods in two Chinese epidemiology journals

PubMed Central

2010-01-01

Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252

Family leave after childbirth and the mental health of new mothers.

PubMed

Chatterji, Pinka; Markowitz, Sara

2012-06-01

Recent studies indicate that short maternity leave, and, more generally, full-time maternal employment during the first year of life, detract from children's health, cognitive development, and behavioral outcomes. Much less is known, however, about how early parental employment affects the mental and physical health of the mothers themselves. The purpose of this paper is to examine the association between short family leave length (less than 12 weeks of total leave after childbirth, less than 8 weeks of paid leave) and mental and physical health outcomes among new mothers. Data come from the Early Childhood Longitudinal Study--Birth Cohort (ECLS-B), a nationally representative sample of 14,000 children born in 2001 and followed until kindergarten entry. We focus on a sample of ECLS-B mothers from the first wave of the survey who had worked during pregnancy and who had returned to work by the time of the first follow-up interview, which was conducted about 9 months after childbirth. When examining the effects of paternal leave, we further restrict this sample to mothers who were married at the time of the first follow-up interview. The maternal health outcomes of interest are measures of depression and overall health status. We use standard OLS and ordered probit models, as well as two-stage least squares and two-stage residual inclusion methods which address the potential endogeneity of family leave with respect to maternal health. Our findings from the OLS and ordered probit models indicate that, for mothers who worked prior to childbirth and who return to work in the first year, having less than 12 weeks of maternal leave and having less than 8 weeks of paid maternal leave are both associated with increases in depressive symptoms, and having less than 8 weeks of paid leave is associated with a reduction in overall health status. Findings from models that address the potential endogeneity of maternal leave generally support these results, and suggest that longer leave may improve the health of new mothers. Our findings suggest that longer leave after childbirth may benefit families. However, one potential drawback of using cross-sectional variation in state policies and community characteristics for identification is that these measures may be correlated with other unmeasured factors that directly influence family leave and maternal health. The mother's mental and physical health can be an important route through which infants are affected by parents' employment decisions. Our findings suggest that post-partum health services that target mothers' mental and physical health, and its effects on infants, may be useful. Our findings suggest that policies that support longer family leave may benefit maternal mental health. Future research should examine how workplace and public policies related to maternal employment can be used to improve families' health outcomes.

Properties of the Bivariate Delayed Poisson Process

DTIC Science & Technology

1974-07-01

and Lewis (1972) in their Berkeley Symposium paper and here their analysis of the bivariate Poisson processes (without Poisson noise) is carried... Poisson processes . They cannot, however, be independent Poisson processes because their events are associated in pairs by the displace- ment centres...process because its marginal processes for events of each type are themselves (univariate) Poisson processes . Cox and Lewis (1972) assumed a

Sexual Harassment Retaliation Climate DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

exploratory factor analysis, and bivariate correlations (sample 1) 2) To determine the factor structure of the remaining (final) questions via...statistics, reliability analysis, exploratory factor analysis, and bivariate correlations of the prospective Sexual Harassment Retaliation Climate...reported by the survey requester). For information regarding the composition of sample, refer to Table 1. Table 1. Sample 1 Demographics n

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers

PubMed Central

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-01-01

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait. PMID:16451570

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers.

PubMed

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-12-30

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait.

Identifying the Source of Misfit in Item Response Theory Models.

PubMed

Liu, Yang; Maydeu-Olivares, Alberto

2014-01-01

When an item response theory model fails to fit adequately, the items for which the model provides a good fit and those for which it does not must be determined. To this end, we compare the performance of several fit statistics for item pairs with known asymptotic distributions under maximum likelihood estimation of the item parameters: (a) a mean and variance adjustment to bivariate Pearson's X(2), (b) a bivariate subtable analog to Reiser's (1996) overall goodness-of-fit test, (c) a z statistic for the bivariate residual cross product, and (d) Maydeu-Olivares and Joe's (2006) M2 statistic applied to bivariate subtables. The unadjusted Pearson's X(2) with heuristically determined degrees of freedom is also included in the comparison. For binary and ordinal data, our simulation results suggest that the z statistic has the best Type I error and power behavior among all the statistics under investigation when the observed information matrix is used in its computation. However, if one has to use the cross-product information, the mean and variance adjusted X(2) is recommended. We illustrate the use of pairwise fit statistics in 2 real-data examples and discuss possible extensions of the current research in various directions.

An Analysis of the Effects of Military Service on Retirees’ Civilian Earnings

DTIC Science & Technology

1993-12-01

labor market following separation from the service. Thus. military retirees receive two incomes over a lengthy period of their lives, the military pension...labor market experience. Within this model. Probit analysis Was emprio~cd to correct for expected selecti\\I1!% bilas. The sampie employed in this...have a more direct correlation with the civilian lob market . The third phase examined occupational transfer effects. A dummy transfer variable was

Lessons Learned from the Protección en Construcción Community Research Partnership.

PubMed

Martinez, Linda Sprague; Ndulue, Uchenna J; Brunette, Maria J

2012-01-01

PenC seeks to build community-university-labor partnership in order to design, implement and evaluate an intervention aimed at preventing falls and silica exposure among Latino construction workers. This study evaluated the PenC partnership process. Semi-structured partner interviews and surveys were used. Thematic, univariate and bivariate analyses were conducted; results were presented back to partners who then provided data context. Although all partners report increased capacity including new connections and knowledge, resident researchers, here promotores, are much more likely to share information with their neighbors and other local residents. Engaging residents can lead to deeper community penetration.

Lessons Learned from the Protección en Construcción Community Research Partnership

PubMed Central

Martinez, Linda Sprague; Ndulue, Uchenna J.; Brunette, Maria J.

2015-01-01

PenC seeks to build community-university-labor partnership in order to design, implement and evaluate an intervention aimed at preventing falls and silica exposure among Latino construction workers. This study evaluated the PenC partnership process. Semi-structured partner interviews and surveys were used. Thematic, univariate and bivariate analyses were conducted; results were presented back to partners who then provided data context. Although all partners report increased capacity including new connections and knowledge, resident researchers, here promotores, are much more likely to share information with their neighbors and other local residents. Engaging residents can lead to deeper community penetration. PMID:26005517

Identifying hidden common causes from bivariate time series: a method using recurrence plots.

PubMed

Hirata, Yoshito; Aihara, Kazuyuki

2010-01-01

We propose a method for inferring the existence of hidden common causes from observations of bivariate time series. We detect related time series by excessive simultaneous recurrences in the corresponding recurrence plots. We also use a noncoverage property of a recurrence plot by the other to deny the existence of a directional coupling. We apply the proposed method to real wind data.

Covariate analysis of bivariate survival data

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

Bennett, L.E.

1992-01-01

The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methodsmore » have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.« less

Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study.

PubMed

Arya, Rector; Lehman, Donna; Hunt, Kelly J; Schneider, Jennifer; Almasy, Laura; Blangero, John; Stern, Michael P; Duggirala, Ravindranath

2003-12-31

Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits. We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 (LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage (LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely. We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

Social and economic costs and health-related quality of life in stroke survivors in the Canary Islands, Spain

PubMed Central

2012-01-01

Background Cost-of-illness analysis is the main method of providing an overall vision of the economic impact of a disease. Such studies have been used to set priorities for healthcare policies and inform resource allocation. The aim of this study was to determine the economic burden and health-related quality of life (HRQOL) in the first, second and third years after surviving a stroke in the Canary Islands, Spain. Methods Cross-sectional, retrospective study of 448 patients with stroke based on ICD 9 discharge codes, who received outpatient care at five hospitals. The study was approved by the Research Ethics Committee of Nuestra Señora de la Candelaria University Hospital. Data on demographic characteristics, health resource utilization, informal care, labor productivity losses and HRQOL were collected from the hospital admissions databases and questionnaires completed by stroke patients or their caregivers. Labor productivity losses were calculated from physical units and converted into monetary units with a human capital-based method. HRQOL was measured with the EuroQol EQ-5D questionnaire. Healthcare costs, productivity losses and informal care costs were analyzed with log-normal, probit and ordered probit multivariate models. Results The average cost for each stroke survivor was €17 618 in the first, €14 453 in the second and €12 924 in the third year after the stroke; the reference year for unit prices was 2004. The largest expenditures in the first year were informal care and hospitalizations; in the second and third years the main costs were for informal care, productivity losses and medication. Mean EQ-5D index scores for stroke survivors were 0.50 for the first, 0.47 for the second and 0.46 for the third year, and mean EQ-5D visual analog scale scores were 56, 52 and 55, respectively. Conclusions The main strengths of this study lie in our bottom-up-approach to costing, and in the evaluation of stroke survivors from a broad perspective (societal costs) in the first, second and third years after surviving the stroke. This type of analysis is rare in the Spanish context. We conclude that stroke incurs considerable societal costs among survivors to three years and there is substantial deterioration in HRQOL. PMID:22970797

Testing independence of bivariate interval-censored data using modified Kendall's tau statistic.

PubMed

Kim, Yuneung; Lim, Johan; Park, DoHwan

2015-11-01

In this paper, we study a nonparametric procedure to test independence of bivariate interval censored data; for both current status data (case 1 interval-censored data) and case 2 interval-censored data. To do it, we propose a score-based modification of the Kendall's tau statistic for bivariate interval-censored data. Our modification defines the Kendall's tau statistic with expected numbers of concordant and disconcordant pairs of data. The performance of the modified approach is illustrated by simulation studies and application to the AIDS study. We compare our method to alternative approaches such as the two-stage estimation method by Sun et al. (Scandinavian Journal of Statistics, 2006) and the multiple imputation method by Betensky and Finkelstein (Statistics in Medicine, 1999b). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Health Insurance: The Trade-Off Between Risk Pooling and Moral Hazard.

DTIC Science & Technology

1989-12-01

bias comes about because we suppress the intercept term in estimating VFor the power, the test is against 1, - 1. With this transform, the risk...dealing with the same utility function. As one test of whether families behave in the way economic theory suggests, we have also fitted a probit model of...nonparametric alternative to test our results’ sensitivity to the assumption of a normal error in both the theoretical and empirical models of the

A Framework for the Analysis of the Reserve Officer Augmentation Process in the United States Marine Corps

DTIC Science & Technology

1987-12-01

occupation group, category (i.e., strength, loss, etc.), years of commissioned service (YCS), grade, occupation, source of commission, education, sex ...OF MCORP OUTPUT OCCUPATION GROUP: All CAT: Strength YCS: 01 - 09 GRADE: All Unrestricted Officers OCCUPATION: All SOURCE: All EDUCATION: All SEX : All...source of commission, sex , MOS, GCT, and other pertinent variables such as the performance index. A Probit or Logit model could be utilized. The variables

Probabilistic Model for Laser Damage to the Human Retina

DTIC Science & Technology

2012-03-01

the beam. Power density may be measured in radiant exposure, J cm2 , or by irradiance , W cm2 . In the experimental database used in this study and...to quan- tify a binary response, either lethal or non-lethal, within a population such as insects or rats. In directed energy research, probit...value of the normalized Arrhenius damage integral. In a one-dimensional simulation, the source term is determined as a spatially averaged irradiance (W

Demand for Health Insurance by Military Retirees

DTIC Science & Technology

2015-05-01

Plans,” The Journal of Health Economics 16, No. 2 (1997): 231–247 and Bruce A. Strombom, Thomas C. Buchmueller, and Paul J. Feldstein, “Switching Costs...Initiative: Volume 3. Health Care Utilization and Costs,” R -4244/3-HA (Santa Monica, CA: RAND Corporation, 1993). 10 probit regression model for TRICARE...Solomon (1998) Stanford University employees, panel data, 1994–95 HMO vs. PPO and FFS Logit -0.29 Fixed-Effects Logit -0.97 Barringer and Mitchell

Legacy Status as a Signal in College Admissions

DTIC Science & Technology

2006-01-01

but no equivalent procedure for probit. 24 Hausman and McFadden (1984). This test is performed using the suest command in Stata to verify that...312. Attiyeh, Gregory and Richard Attiyeh. "Testing for Bias in Graduate School Admissions." The Journal of Human Resources. Vol. 32, No. 3 ( Summer ...John. "The Effects of Public Policies on the Demand for Higher Education." The Journal of Human Resources. Vol. 12, No. 3 ( Summer 1977), 285-307

Reanalysis of the start of the UK 1967 to 1968 foot-and-mouth disease epidemic to calculate airborne transmission probabilities.

PubMed

Sanson, R L; Gloster, J; Burgin, L

2011-09-24

The aims of this study were to statistically reassess the likelihood that windborne spread of foot-and-mouth disease (FMD) virus (FMDV) occurred at the start of the UK 1967 to 1968 FMD epidemic at Oswestry, Shropshire, and to derive dose-response probability of infection curves for farms exposed to airborne FMDV. To enable this, data on all farms present in 1967 in the parishes near Oswestry were assembled. Cases were infected premises whose date of appearance of first clinical signs was within 14 days of the depopulation of the index farm. Logistic regression was used to evaluate the association between infection status and distance and direction from the index farm. The UK Met Office's NAME atmospheric dispersion model (ADM) was used to generate plumes for each day that FMDV was excreted from the index farm based on actual historical weather records from October 1967. Daily airborne FMDV exposure rates for all farms in the study area were calculated using a geographical information system. Probit analyses were used to calculate dose-response probability of infection curves to FMDV, using relative exposure rates on case and control farms. Both the logistic regression and probit analyses gave strong statistical support to the hypothesis that airborne spread occurred. There was some evidence that incubation period was inversely proportional to the exposure rate.

Bayesian multinomial probit modeling of daily windows of ...

EPA Pesticide Factsheets

Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregnancy for 12 individual types of CHDs with respect to maternal PM2.5 exposure. We apply the model to a dataset of mothers from the National Birth Defect Prevention Study where daily PM2.5 exposures from weeks 2-8 of pregnancy are assigned (specific to each location and pregnancy date) using predictions from the downscaler pollution model. Results are compared to an aggregated exposure model which defines exposure as the average value over pregnancy weeks 2-8. Increased PM2.5 exposure during pregnancy days 53 and 50-51 for pulmonary valve stenosis and tetralogy of Fallot, respectively, are associated with an increased probability of development of each CHD. The largest estimated effect is seen for atrioventricular septal defects on pregnancy day 14. The aggregated exposure model fails to identify any significant windows of susceptibility during pregnancy weeks 2-8 for the considered CHDs. Considering daily PM2.5 exposures in a new modeling framework revealed positive associations for defects that the standard aggregated exposure model was unable to identify. Disclaimer: The views expressed in this manuscript are those of the authors and do not necessarily represent the views or policie

Anti-Fungal activity of essential oil from Baeckea frutescens L against Pleuratus ostreatus

NASA Astrophysics Data System (ADS)

Jemi, Renhart; Barus, Ade Irma; Nuwa, Sarinah, Luhan, Gimson

2017-11-01

Ujung Atap is an herb that have distinctive odor on its leaves. The plant's essential oil contains bioactive compounds but has not been investigated its anti-fungal activity against Pleurotus ostreatus. Essential oil from Ujung Atap leaves is one environmentally friendly natural preservative. This study consisted of distillation Ujung Atap leaves with boiled method, determining the number of acid, essential oil ester, and anti-fungal activity against Pleurotus ostreatus. Analysis of the data to calculate anti-fungal activity used probit analysis method to determine the IC50. Results for the distillation of leaves Ujung Atap produce essential oil yield of 0.071% and the average yield of the acid number and the ester of essential oils Ujung Atap leaves are 5.24 and 12.15. Anti-fungal activity Pleurotus ostreatus at a concentration of 1000 µg/mL, 100 µg/mL, 75 µg/mL, 50 µg/mL and 100 µg/mL BA defunct or fungi was declared dead, while at a concentration of 25 µg/mL, 10 µg/mL and 5 µg/mL still occur inhibitory processes. Results obtained probit analysis method IC50 of 35.48 mg/mL; means the essential oil of Ujung Atap leaf can inhibit fungal growth by 50 percent to 35.48 µg/mL concentration.

Are Lowered Socioeconomic Circumstances Causally Related to Tooth Loss? A Natural Experiment Involving the 2011 Great East Japan Earthquake.

PubMed

Matsuyama, Yusuke; Aida, Jun; Tsuboya, Toru; Hikichi, Hiroyuki; Kondo, Katsunori; Kawachi, Ichiro; Osaka, Ken

2017-07-01

Oral health status is correlated with socioeconomic status. However, the causal nature of the relationship is not established. Here we describe a natural experiment involving deteriorating socioeconomic circumstances following exposure to the 2011 Great East Japan Earthquake and Tsunami. We investigated the relationship between subjective economic deterioration and housing damage due to the disaster and tooth loss in a cohort of community-dwelling residents (n = 3,039), from whom we obtained information about socioeconomic status and health status in 2010 (i.e., predating the disaster). A follow-up survey was performed in 2013 (postdisaster), and 82.1% of the 4,380 eligible survivors responded. We estimated the impact of subjective economic deterioration and housing damage due to the disaster on tooth loss by fitting an instrumental variable probit model. Subjective economic deterioration and housing damage due to the disaster were significantly associated with 8.1% and 1.7% increases in the probability of tooth loss (probit coefficients were 0.469 (95% confidence interval: 0.065, 0.872) and 0.103 (95% confidence interval: 0.011, 0.196), respectively). In this natural experiment, we confirmed the causal relationship between deteriorating socioeconomic circumstances and tooth loss. © The Author 2017. 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.

An assessment of two-step linear regression and a multifactor probit analysis as alternatives to acute to chronic ratios in the estimation of chronic response from acute toxicity data to derive water quality guidelines.

PubMed

Slaughter, Andrew R; Palmer, Carolyn G; Muller, Wilhelmine J

2007-04-01

In aquatic ecotoxicology, acute to chronic ratios (ACRs) are often used to predict chronic responses from available acute data to derive water quality guidelines, despite many problems associated with this method. This paper explores the comparative protectiveness and accuracy of predicted guideline values derived from the ACR, linear regression analysis (LRA), and multifactor probit analysis (MPA) extrapolation methods applied to acute toxicity data for aquatic macroinvertebrates. Although the authors of the LRA and MPA methods advocate the use of extrapolated lethal effects in the 0.01% to 10% lethal concentration (LC0.01-LC10) range to predict safe chronic exposure levels to toxicants, the use of an extrapolated LC50 value divided by a safety factor of 5 was in addition explored here because of higher statistical confidence surrounding the LC50 value. The LRA LC50/5 method was found to compare most favorably with available experimental chronic toxicity data and was therefore most likely to be sufficiently protective, although further validation with the use of additional species is needed. Values derived by the ACR method were the least protective. It is suggested that there is an argument for the replacement of ACRs in developing water quality guidelines by the LRA LC50/5 method.

Aquaculture in artificially developed wetlands in urban areas: an application of the bivariate relationship between soil and surface water in landscape ecology.

PubMed

Paul, Abhijit

2011-01-01

Wetlands show a strong bivariate relationship between soil and surface water. Artificially developed wetlands help to build landscape ecology and make built environments sustainable. The bheries, wetlands of eastern Calcutta (India), utilize the city sewage to develop urban aquaculture that supports the local fish industries and opens a new frontier in sustainable environmental planning research.

Idealized models of the joint probability distribution of wind speeds

NASA Astrophysics Data System (ADS)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

Nonparametric analysis of bivariate gap time with competing risks.

PubMed

Huang, Chiung-Yu; Wang, Chenguang; Wang, Mei-Cheng

2016-09-01

This article considers nonparametric methods for studying recurrent disease and death with competing risks. We first point out that comparisons based on the well-known cumulative incidence function can be confounded by different prevalence rates of the competing events, and that comparisons of the conditional distribution of the survival time given the failure event type are more relevant for investigating the prognosis of different patterns of recurrence disease. We then propose nonparametric estimators for the conditional cumulative incidence function as well as the conditional bivariate cumulative incidence function for the bivariate gap times, that is, the time to disease recurrence and the residual lifetime after recurrence. To quantify the association between the two gap times in the competing risks setting, a modified Kendall's tau statistic is proposed. The proposed estimators for the conditional bivariate cumulative incidence distribution and the association measure account for the induced dependent censoring for the second gap time. Uniform consistency and weak convergence of the proposed estimators are established. Hypothesis testing procedures for two-sample comparisons are discussed. Numerical simulation studies with practical sample sizes are conducted to evaluate the performance of the proposed nonparametric estimators and tests. An application to data from a pancreatic cancer study is presented to illustrate the methods developed in this article. © 2016, The International Biometric Society.

Galaxy And Mass Assembly (GAMA): bivariate functions of Hα star-forming galaxies

NASA Astrophysics Data System (ADS)

Gunawardhana, M. L. P.; Hopkins, A. M.; Taylor, E. N.; Bland-Hawthorn, J.; Norberg, P.; Baldry, I. K.; Loveday, J.; Owers, M. S.; Wilkins, S. M.; Colless, M.; Brown, M. J. I.; Driver, S. P.; Alpaslan, M.; Brough, S.; Cluver, M.; Croom, S.; Kelvin, L.; Lara-López, M. A.; Liske, J.; López-Sánchez, A. R.; Robotham, A. S. G.

2015-02-01

We present bivariate luminosity and stellar mass functions of Hα star-forming galaxies drawn from the Galaxy And Mass Assembly (GAMA) survey. While optically deep spectroscopic observations of GAMA over a wide sky area enable the detection of a large number of 0.001 < SFRHα (M⊙ yr-1) < 100 galaxies, the requirement for an Hα detection in targets selected from an r-band magnitude-limited survey leads to an incompleteness due to missing optically faint star-forming galaxies. Using z < 0.1 bivariate distributions as a reference we model the higher-z distributions, thereby approximating a correction for the missing optically faint star-forming galaxies to the local star formation rate (SFR) and M densities. Furthermore, we obtain the r-band luminosity functions (LFs) and stellar mass functions of Hα star-forming galaxies from the bivariate LFs. As our sample is selected on the basis of detected Hα emission, a direct tracer of ongoing star formation, this sample represents a true star-forming galaxy sample, and is drawn from both photometrically classified blue and red subpopulations, though mostly from the blue population. On average 20-30 per cent of red galaxies at all stellar masses are star forming, implying that these galaxies may be dusty star-forming systems.

Bivariate- distribution for transition matrix elements in Breit-Wigner to Gaussian domains of interacting particle systems.

PubMed

Kota, V K B; Chavda, N D; Sahu, R

2006-04-01

Interacting many-particle systems with a mean-field one-body part plus a chaos generating random two-body interaction having strength lambda exhibit Poisson to Gaussian orthogonal ensemble and Breit-Wigner (BW) to Gaussian transitions in level fluctuations and strength functions with transition points marked by lambda = lambda c and lambda = lambda F, respectively; lambda F > lambda c. For these systems a theory for the matrix elements of one-body transition operators is available, as valid in the Gaussian domain, with lambda > lambda F, in terms of orbital occupation numbers, level densities, and an integral involving a bivariate Gaussian in the initial and final energies. Here we show that, using a bivariate-t distribution, the theory extends below from the Gaussian regime to the BW regime up to lambda = lambda c. This is well tested in numerical calculations for 6 spinless fermions in 12 single-particle states.

Smoothing of the bivariate LOD score for non-normal quantitative traits.

PubMed

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Global assessment of predictability of water availability: A bivariate probabilistic Budyko analysis

NASA Astrophysics Data System (ADS)

Wang, Weiguang; Fu, Jianyu

2018-02-01

Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang's equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.

Relation between lowered colloid osmotic pressure, respiratory failure, and death.

PubMed

Tonnesen, A S; Gabel, J C; McLeavey, C A

1977-01-01

Plasma colloid osmotic pressure was measured each day in 84 intensive care unit patients. Probit analysis demonstrated a direct relationship between colloid osmotic pressure (COP) and survival. The COP associated with a 50% survival rate was 15.0 torr. COP was higher in survivors than in nonsurvivors without respiratory failure and in patients who recovered from respiratory failure. We conclude that lowered COP is associated with an elevated mortality rate. However, the relationship to death is not explained by the relationship to respiratory failure.

Guidelines for Acute Toxicological Tests

DTIC Science & Technology

1979-11-01

with a group of individuals being exposed is independence (usually assured by randoruiza- tion) of the respondent. In the case of acute studies on plants...reasonable choice. If estimates of the EC50 are available and if the purpose of the pro- posed study is to check the median response rate Finney on page...appropriate test. Figure 2 shois the probit equation and the results on scale 1/X. In the transformed scale, EC50 = 59.83 with bounds of 54.53 and 63.92

An in vitro Corneal Model with a Laser Damage Threshold at 2 Micrometers That is Similar to That in the Rabbit

DTIC Science & Technology

2007-11-01

Proceedings 3. DATES COVERED (From - To) June 2007- November 2007 4. TITLE AND SUBTITLE An In Vitro Corneal Model with a Laser Damage Threshold at 2...2-µm wavelength output of a thulium fiber laser with 4 mm beam diameter for 0.25 seconds in a thermally controlled environment and then assayed for...data in the literature. 15. SUBJECT TERMS corneal organotypic culture, laser , threshold, thermography, Probit 16. SECURITY CLASSIFICATION OF

Disruption of the Putative Vascular Leak Peptide Sequence in the Stabilized Ricin Vaccine Candidate RTA1-33/44-198

DTIC Science & Technology

2013-01-29

Time- dependence of calculated LD50. The data shown in Panel A were submitted to probit analysis to determine the LD50 of ricin at every 0.5-day...degenerate neutrophils and necrotic debris evident; (C) Only a limited region of the epithelium lining a bronchus remains viable (arrowheads); the...quantitative analysis of the dose dependent protective effects of the immunizations. All vaccine doses (2.5, 10 or 40 μg immunogen) resulted in significant

Reporting heterogeneity in self-assessed health among elderly Europeans.

PubMed

Pfarr, Christian; Schmid, Andreas; Schneider, Udo

2012-10-05

Self-assessed health (SAH) is a frequently used measure of individuals' health status. It is also prone to reporting heterogeneity. To control for reporting heterogeneity objective measures of true health need to be included in an analysis. The topic becomes even more complex for cross-country comparisons, as many key variables tend to vary strongly across countries, influenced by cultural and institutional differences. This study aims at exploring the key drivers for reporting heterogeneity in SAH in an international context. To this end, country specific effects are accounted for and the objective health measure is concretized, distinguishing effects of mental and physical health conditions. We use panel data from the SHARE-project which provides a rich dataset on the elderly European population. To obtain distinct indicators for physical and mental health conditions two indices are constructed. Finally, to identify potential reporting heterogeneity in SAH a generalized ordered probit model is estimated. We find evidence that in addition to health behaviour, health care utilization, mental and physical health condition as well as country characteristics affect reporting behaviour. We conclude that observed and unobserved heterogeneity play an important role when analysing SAH and have to be taken into account.

Willingness to use mobile application for smartphone for improving road safety.

PubMed

Cardamone, Angelo Stephen; Eboli, Laura; Forciniti, Carmen; Mazzulla, Gabriella

2016-01-01

In the last few years mobile devices have reached a large amount of consumers in both developed and high-growth world economies. In 2013, 97% of the Italian population owns a mobile phone, and 62% owns a smartphone. Application software for mobile devices is largely proposed to consumers, and several mobile applications were oriented toward the improvement of road safety and road accident risk reduction. In this paper, we describe the results of a survey oriented to preventively investigate on the willingness to receive and/or to give information about road condition by means of mobile devices. Road users were informed about the characteristics of a mobile application, and then they were invited to complete a questionnaire. Experimental data were used for capturing road user attitudes toward the use of the smartphone to improve road safety, and to establish the preferences for the different features of the proposed mobile application. To this end, we choose to use the ordered probit model methodology. We demonstrate that the adopted methodology accounts for the differential impacts of the willingness to receive and/or to give information about road conditions on the overall willingness to receive and/or to give information through an application software for mobile devices.

Choice Set Size and Decision-Making: The Case of Medicare Part D Prescription Drug Plans

PubMed Central

Bundorf, M. Kate; Szrek, Helena

2013-01-01

Background The impact of choice on consumer decision-making is controversial in U.S. health policy. Objective Our objective was to determine how choice set size influences decision-making among Medicare beneficiaries choosing prescription drug plans. Methods We randomly assigned members of an internet-enabled panel age 65 and over to sets of prescription drug plans of varying sizes (2, 5, 10, and 16) and asked them to choose a plan. Respondents answered questions about the plan they chose, the choice set, and the decision process. We used ordered probit models to estimate the effect of choice set size on the study outcomes. Results Both the benefits of choice, measured by whether the chosen plan is close to the ideal plan, and the costs, measured by whether the respondent found decision-making difficult, increased with choice set size. Choice set size was not associated with the probability of enrolling in any plan. Conclusions Medicare beneficiaries face a tension between not wanting to choose from too many options and feeling happier with an outcome when they have more alternatives. Interventions that reduce cognitive costs when choice sets are large may make this program more attractive to beneficiaries. PMID:20228281

Factors affecting nurses' decision to get the flu vaccine.

PubMed

Shahrabani, Shosh; Benzion, Uri; Yom Din, Gregory

2009-05-01

The objective of this study was to identify factors that influence the decision whether or not to get the influenza (flu) vaccine among nurses in Israel by using the health belief model (HBM). A questionnaire distributed among 299 nurses in Israel in winter 2005/2006 included (1) socio-demographic information; (2) variables based on the HBM, including susceptibility, seriousness, benefits, barriers and cues to action; and (3) knowledge about influenza and the vaccine, and health motivation. A probit model was used to analyze the data. In Israel, the significant HBM categories affecting nurses' decision to get a flu shot are the perceived benefits from vaccination and cues to action. In addition, nurses who are vaccinated have higher levels of (1) knowledge regarding the vaccine and influenza, (2) perceived seriousness of the illness, (3) perceived susceptibility, and (4) health motivation than do those who do not get the vaccine. Immunization of healthcare workers may reduce the risk of flu outbreaks in all types of healthcare facilities and reduce morbidity and mortality among high-risk patients. In order to increase vaccination rates among nurses, efforts should be made to educate them regarding the benefits of vaccination and the potential health consequences of influenza for their patients, and themselves.

Inference for the Bivariate and Multivariate Hidden Truncated Pareto(type II) and Pareto(type IV) Distribution and Some Measures of Divergence Related to Incompatibility of Probability Distribution

ERIC Educational Resources Information Center

Ghosh, Indranil

2011-01-01

Consider a discrete bivariate random variable (X, Y) with possible values x[subscript 1], x[subscript 2],..., x[subscript I] for X and y[subscript 1], y[subscript 2],..., y[subscript J] for Y. Further suppose that the corresponding families of conditional distributions, for X given values of Y and of Y for given values of X are available. We…

New MYC IHC Classifier Integrating Quantitative Architecture Parameters to Predict MYC Gene Translocation in Diffuse Large B-Cell Lymphoma

PubMed Central

Dong, Wei-Feng; Canil, Sarah; Lai, Raymond; Morel, Didier; Swanson, Paul E.; Izevbaye, Iyare

2018-01-01

A new automated MYC IHC classifier based on bivariate logistic regression is presented. The predictor relies on image analysis developed with the open-source ImageJ platform. From a histologic section immunostained for MYC protein, 2 dimensionless quantitative variables are extracted: (a) relative distance between nuclei positive for MYC IHC based on euclidean minimum spanning tree graph and (b) coefficient of variation of the MYC IHC stain intensity among MYC IHC-positive nuclei. Distance between positive nuclei is suggested to inversely correlate MYC gene rearrangement status, whereas coefficient of variation is suggested to inversely correlate physiological regulation of MYC protein expression. The bivariate classifier was compared with 2 other MYC IHC classifiers (based on percentage of MYC IHC positive nuclei), all tested on 113 lymphomas including mostly diffuse large B-cell lymphomas with known MYC fluorescent in situ hybridization (FISH) status. The bivariate classifier strongly outperformed the “percentage of MYC IHC-positive nuclei” methods to predict MYC+ FISH status with 100% sensitivity (95% confidence interval, 94-100) associated with 80% specificity. The test is rapidly performed and might at a minimum provide primary IHC screening for MYC gene rearrangement status in diffuse large B-cell lymphomas. Furthermore, as this bivariate classifier actually predicts “permanent overexpressed MYC protein status,” it might identify nontranslocation-related chromosomal anomalies missed by FISH. PMID:27093450

Gender differences in the diagnostic accuracy of SPECT myocardial perfusion imaging: a bivariate meta-analysis.

PubMed

Iskandar, Aline; Limone, Brendan; Parker, Matthew W; Perugini, Andrew; Kim, Hyejin; Jones, Charles; Calamari, Brian; Coleman, Craig I; Heller, Gary V

2013-02-01

It remains controversial whether the diagnostic accuracy of single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI) is different in men as compared to women. We performed a meta-analysis to investigate gender differences of SPECT MPI for the diagnosis of CAD (≥50% stenosis). Two investigators independently performed a systematic review of the MEDLINE and EMBASE databases from inception through January 2012 for English-language studies determining the diagnostic accuracy of SPECT MPI. We included prospective studies that compared SPECT MPI with conventional coronary angiography which provided sufficient data to calculate gender-specific true and false positives and negatives. Data from studies evaluating <20 patients of one gender were excluded. Bivariate meta-analysis was used to create summary receiver operating curves. Twenty-six studies met inclusion criteria, representing 1,148 women and 1,142 men. Bivariate meta-analysis yielded a mean sensitivity and specificity of 84.2% (95% confidence interval [CI] 78.7%-88.6%) and 78.7% (CI 70.0%-85.3%) for SPECT MPI in women and 89.1% (CI 84.0%-92.7%) and 71.2% (CI 60.8%-79.8%) for SPECT MPI in men. There was no significant difference in the sensitivity (P = .15) or specificity (P = .23) between male and female subjects. In a bivariate meta-analysis of the available literature, the diagnostic accuracy of SPECT MPI is similar for both men and women.

Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males

PubMed Central

Liu, Yao-Zhong; Pei, Yu-Fang; Liu, Jian-Feng; Yang, Fang; Guo, Yan; Zhang, Lei; Liu, Xiao-Gang; Yan, Han; Wang, Liang; Zhang, Yin-Ping; Levy, Shawn; Recker, Robert R.; Deng, Hong-Wen

2009-01-01

Background Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically. Principal Findings To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10−7 and 1.47×10−6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat. Conclusions Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis. PMID:19714249

The impact of diabetes on employment and work productivity.

PubMed

Tunceli, Kaan; Bradley, Cathy J; Nerenz, David; Williams, L Keoki; Pladevall, Manel; Elston Lafata, Jennifer

2005-11-01

The purpose of this study was to longitudinally examine the effect of diabetes on labor market outcomes. Using secondary data from the first two waves (1992 and 1994) of the Health and Retirement Study, we identified 7,055 employed respondents (51-61 years of age), 490 of whom reported having diabetes in wave 1. We estimated the effect of diabetes in wave 1 on the probability of working in wave 2 using probit regression. For those working in wave 2, we modeled the relationships between diabetic status in wave 1 and the change in hours worked and work-loss days using ordinary least-squares regressions and modeled the presence of health-related work limitations using probit regression. All models control for health status and job characteristics and are estimated separately by sex. Among individuals with diabetes, the absolute probability of working was 4.4 percentage points less for women and 7.1 percentage points less for men relative to that of their counterparts without diabetes. Change in weekly hours worked was not statistically significantly associated with diabetes. Women with diabetes had 2 more work-loss days per year compared with women without diabetes. Compared with individuals without diabetes, men and women with diabetes were 5.4 and 6 percentage points (absolute increase), respectively, more likely to have work limitations. This article provides evidence that diabetes affects patients, employers, and society not only by reducing employment but also by contributing to work loss and health-related work limitations for those who remain employed.

Web based health surveys: Using a Two Step Heckman model to examine their potential for population health analysis.

PubMed

Morrissey, Karyn; Kinderman, Peter; Pontin, Eleanor; Tai, Sara; Schwannauer, Mathias

2016-08-01

In June 2011 the BBC Lab UK carried out a web-based survey on the causes of mental distress. The 'Stress Test' was launched on 'All in the Mind' a BBC Radio 4 programme and the test's URL was publicised on radio and TV broadcasts, and made available via BBC web pages and social media. Given the large amount of data created, over 32,800 participants, with corresponding diagnosis, demographic and socioeconomic characteristics; the dataset are potentially an important source of data for population based research on depression and anxiety. However, as respondents self-selected to participate in the online survey, the survey may comprise a non-random sample. It may be only individuals that listen to BBC Radio 4 and/or use their website that participated in the survey. In this instance using the Stress Test data for wider population based research may create sample selection bias. Focusing on the depression component of the Stress Test, this paper presents an easy-to-use method, the Two Step Probit Selection Model, to detect and statistically correct selection bias in the Stress Test. Using a Two Step Probit Selection Model; this paper did not find a statistically significant selection on unobserved factors for participants of the Stress Test. That is, survey participants who accessed and completed an online survey are not systematically different from non-participants on the variables of substantive interest. Copyright © 2016 Elsevier Ltd. All rights reserved.

The H-ARS Dose Response Relationship (DRR): Validation and Variables.

PubMed

Plett, P Artur; Sampson, Carol H; Chua, Hui Lin; Jackson, William; Vemula, Sasidhar; Sellamuthu, Rajendran; Fisher, Alexa; Feng, Hailin; Wu, Tong; MacVittie, Thomas J; Orschell, Christie M

2015-11-01

Manipulations of lethally-irradiated animals, such as for administration of pharmaceuticals, blood sampling, or other laboratory procedures, have the potential to induce stress effects that may negatively affect morbidity and mortality. To investigate this in a murine model of the hematopoietic acute radiation syndrome, 20 individual survival efficacy studies were grouped based on the severity of the administration (Admn) schedules of their medical countermeasure (MCM) into Admn 1 (no injections), Admn 2 (1-3 injections), or Admn 3 (29 injections or 6-9 oral gavages). Radiation doses ranged from LD30/30 to LD95/30. Thirty-day survival of vehicle controls in each group was used to construct radiation dose lethality response relationship (DRR) probit plots, which were compared statistically to the original DRR from which all LDXX/30 for the studies were obtained. The slope of the Admn 3 probit was found to be significantly steeper (5.190) than that of the original DRR (2.842) or Admn 2 (2.009), which were not significantly different. The LD50/30 for Admn 3 (8.43 Gy) was less than that of the original DRR (8.53 Gy, p < 0.050), whereas the LD50/30 of other groups were similar. Kaplan-Meier survival curves showed significantly worse survival of Admn 3 mice compared to the three other groups (p = 0.007). Taken together, these results show that stressful administration schedules of MCM can negatively impact survival and that dosing regimens should be considered when constructing DRR to use in survival studies.

Effectiveness of conservation easements in agricultural regions.

PubMed

Braza, Mark

2017-08-01

Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity-score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions. © 2017 Society for Conservation Biology.

[Suicide risk and suicide attempt in North Pas de Calais Region. Lessons from the survey Mental Health in General Population].

PubMed

Danel, T; Vilain, J; Roelandt, J L; Salleron, J; Vaiva, G; Amariei, A; Amarie, A; Plancke, L; Plance, L; Duhamel, A

2010-01-01

The Santé Mentale en Population Générale Survey (Mental Health in General Population Survey (MHGP)) is a multicentre international research and action project initiated by the World Health Organisation Collaboration Centre for research and training in mental health. Its aims are to assess the prevalence of the major mental health disorders in the general adult population and from this to record perceptions associated with "mental illness", "madness" and "depression" together with different means of assistance and specialist or lay care. In this work we present the analysis of data on risks of suicide and past history of suicide attempts in the Nord pas de Calais region. We present the qualitative features of these phenomena and correlations with socio-economic, cultural and psychopathological factors, which are discussed in terms of both protective and vulnerability factors. Risk of suicide is present in 15% of the Nord pas de Calais population and is divided into 10.44% slight risk, 2.37% moderate risk and 2.2% high risk. A comparison with data from the MHGP survey in other regions reveals the high risk of suicide in the NPDC region. A risk of suicide is present is 13% of the population in other SMPG survey regions, broken down into 9.1% low risk, 2.1% medium risk and 1.7% high risk. Compared to the 2.2% high risk figure for NPDC, the population in this category is 21% larger. In terms of risk and protective factors, a bivariate analysis of socio-economic and cultural factors confirms the classical risk factors of sex, marital, occupational and educational status and income. The odds-ratio for these socio-economic and cultural factors can be calculated from logistic regression and the protective factors ranked in decreasing order from religion (Muslim versus other religions), martial status (marked versus separated), age (over 58 years old), occupational status (working or retired versus unemployed), income (more than 1300 euros versus less than 840 euros), sex (men versus women) and immigration. For mental illness, the bivariate analysis confirms that the risk of suicide is significantly higher regardless of the mental disorder in question. Logistic regression categorises the mental illnesses as risk factors in the following order: depression, psychotic disorders, anxiety, alcohol abuse disorders, other drugs and insomnia. Suicide attempts have been made by 9.7% of the study population. This figure should be compared with the 8% of the study population in other regions in the survey and represents 29% more attempts. For the risk and protective factors the results of the bivariate analysis of socio-economic on cultural and psychopathological factors are superimposeable on those found for risk of suicide. The ranking of protective factors obtained from logistic regression places age in first position followed in decreasing order by religion, martial status, income, employment status and finally sex and immigration. The same ranking of mental illnesses by logistic regression places depression as the greatest risk factor followed by anxiety, psychotic disorders, alcohol abuse disorders, drugs and insomnia. Copyright 2010 L’Encéphale. Published by Elsevier Masson SAS.. All rights reserved.

Genetic parameters of legendre polynomials for first parity lactation curves.

PubMed

Pool, M H; Janss, L L; Meuwissen, T H

2000-11-01

Variance components of the covariance function coefficients in a random regression test-day model were estimated by Legendre polynomials up to a fifth order for first-parity records of Dutch dairy cows using Gibbs sampling. Two Legendre polynomials of equal order were used to model the random part of the lactation curve, one for the genetic component and one for permanent environment. Test-day records from cows registered between 1990 to 1996 and collected by regular milk recording were available. For the data set, 23,700 complete lactations were selected from 475 herds sired by 262 sires. Because the application of a random regression model is limited by computing capacity, we investigated the minimum order needed to fit the variance structure in the data sufficiently. Predictions of genetic and permanent environmental variance structures were compared with bivariate estimates on 30-d intervals. A third-order or higher polynomial modeled the shape of variance curves over DIM with sufficient accuracy for the genetic and permanent environment part. Also, the genetic correlation structure was fitted with sufficient accuracy by a third-order polynomial, but, for the permanent environmental component, a fourth order was needed. Because equal orders are suggested in the literature, a fourth-order Legendre polynomial is recommended in this study. However, a rank of three for the genetic covariance matrix and of four for permanent environment allows a simpler covariance function with a reduced number of parameters based on the eigenvalues and eigenvectors.

Modeling of chemical inhibition from amyloid protein aggregation kinetics.

PubMed

Vázquez, José Antonio

2014-02-27

The process of amyloid proteins aggregation causes several human neuropathologies. In some cases, e.g. fibrillar deposits of insulin, the problems are generated in the processes of production and purification of protein and in the pump devices or injectable preparations for diabetics. Experimental kinetics and adequate modelling of chemical inhibition from amyloid aggregation are of practical importance in order to study the viable processing, formulation and storage as well as to predict and optimize the best conditions to reduce the effect of protein nucleation. In this manuscript, experimental data of insulin, Aβ42 amyloid protein and apomyoglobin fibrillation from recent bibliography were selected to evaluate the capability of a bivariate sigmoid equation to model them. The mathematical functions (logistic combined with Weibull equation) were used in reparameterized form and the effect of inhibitor concentrations on kinetic parameters from logistic equation were perfectly defined and explained. The surfaces of data were accurately described by proposed model and the presented analysis characterized the inhibitory influence on the protein aggregation by several chemicals. Discrimination between true and apparent inhibitors was also confirmed by the bivariate equation. EGCG for insulin (working at pH = 7.4/T = 37°C) and taiwaniaflavone for Aβ42 were the compounds studied that shown the greatest inhibition capacity. An accurate, simple and effective model to investigate the inhibition of chemicals on amyloid protein aggregation has been developed. The equation could be useful for the clear quantification of inhibitor potential of chemicals and rigorous comparison among them.

“I’LL DIE WITH THE HAMMER IN MY HAND”: JOHN HENRYISM AS A PREDICTOR OF HAPPINESS

PubMed Central

Angner, Erik; Hullett, Sandral; Allison, Jeroan

2011-01-01

This paper examines the association between John Henryism – a behavioral predisposition to cope actively with psychosocial environmental stressors – and happiness. On the basis of previous research on aspiration and goal regulation, we predicted that John Henryism would be negatively associated with happiness when controlling for demographic factors and attainment in various domains of life. We tested the prediction in a sample of hypertensive participants (n=758) drawn from an inner-city, mainly African-American, safety-net hospital in Jefferson County, Alabama. Bivariate analysis revealed no association between John Henryism and attainment in six domains of life: marriage, children, education, employment, income, and health. However, a significant negative association between John Henryism and happiness was found both in bivariate analysis (Spearman’s ρ= −0.335; p<.001) and when controlling for demographic factors and attainment using ordinal logistic regression analysis. There was a significant interaction effect between John Henryism and gender: being male was positively associated with happiness among participants with low John Henryism, but negatively associated with happiness among participants with high John Henryism. While further study would be required in order to establish the extent to which these findings can be generalized as well as their causal underpinnings, the results indicate that John Henryism is negatively associated with happiness, especially among men, and underscore the limitations of using self-reported measures of happiness as proxies for well-being for purposes of public policy. PMID:21666864

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

PubMed Central

Maadooliat, Mehdi; Huang, Jianhua Z.

2013-01-01

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence–structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu.edu/∼madoliat/LagSVD) that can be used to produce informative animations. PMID:22926831

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

NASA Astrophysics Data System (ADS)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Mental health literacy in an educational elite -- an online survey among university students.

PubMed

Lauber, Christoph; Ajdacic-Gross, Vladeta; Fritschi, Nadja; Stulz, Niklaus; Rössler, Wulf

2005-05-09

Mental health literacy is a prerequisite for early recognition and intervention in mental disorders. The aims of this paper are to determine whether a sample of university students recognise different symptoms of depression and schizophrenia and to reveal factors influencing correct recognition. Bivariate and correspondence analyses of the results from an online survey among university students (n = 225). Most participants recognised the specific symptoms of depression. The symptoms of schizophrenia were acknowledged to a lower extent. Delusions of control and hallucinations of taste were not identified as symptoms of schizophrenia. Repeated revival of a trauma for depression and split personality for schizophrenia were frequently mistaken as symptoms of the respective disorders. Bivariate analyses demonstrated that previous interest in and a side job related to mental disorders, as well as previous personal treatment experience had a positive influence on symptom recognition. The correspondence analysis showed that male students of natural science, economics and philosophy are illiterate in recognising the symptoms depression and schizophrenia. Among the educational elite, a wide variability in mental health literacy was found. Therefore, it's important for public mental health interventions to focus on the different recognition rates in depression and schizophrenia. Possibilities for contact must be arranged according to interest and activity (e.g., at work). In order to improve mental health literacy, finally, education and/or internship should be integrated in high school or apprenticeship curricula. Special emphasis must be given towards the effects of gender and stereotypes held about mental illnesses.

A Statistical Tool for Examining Heat Waves and Other Extreme Phenomena Arising from Multiple Factors

NASA Astrophysics Data System (ADS)

Cooley, D. S.; Castillo, F.; Thibaud, E.

2017-12-01

A 2015 heatwave in Pakistan is blamed for over a thousand deaths. This event consisted of several days of very high temperatures and unusually high humidity for this region. However, none of these days exceeded the threshold for "extreme danger" in terms of the heat index. The heat index is a univariate function of both temperature and humidity which is universally applied at all locations regardless of local climate. Understanding extremes which arise from multiple factors is challenging. In this paper we will present a tool for examining bivariate extreme behavior. The tool, developed in the statistical software R, draws isolines of equal exceedance probability. These isolines can be understood as bivariate "return levels". The tool is based on a dependence framework specific for extremes, is semiparametric, and is able to extrapolate isolines beyond the range of the data. We illustrate this tool using the Pakistan heat wave data and other bivariate data.

Using Item Response Theory to Develop Measures of Acquisitive and Protective Self-Monitoring From the Original Self-Monitoring Scale.

PubMed

Wilmot, Michael P; Kostal, Jack W; Stillwell, David; Kosinski, Michal

2017-07-01

For the past 40 years, the conventional univariate model of self-monitoring has reigned as the dominant interpretative paradigm in the literature. However, recent findings associated with an alternative bivariate model challenge the conventional paradigm. In this study, item response theory is used to develop measures of the bivariate model of acquisitive and protective self-monitoring using original Self-Monitoring Scale (SMS) items, and data from two large, nonstudent samples ( Ns = 13,563 and 709). Results indicate that the new acquisitive (six-item) and protective (seven-item) self-monitoring scales are reliable, unbiased in terms of gender and age, and demonstrate theoretically consistent relations to measures of personality traits and cognitive ability. Additionally, by virtue of using original SMS items, previously collected responses can be reanalyzed in accordance with the alternative bivariate model. Recommendations for the reanalysis of archival SMS data, as well as directions for future research, are provided.

Does Child Maltreatment Predict Adult Crime? Reexamining the Question in a Prospective Study of Gender Differences, Education, and Marital Status.

PubMed

Jung, Hyunzee; Herrenkohl, Todd I; Klika, J Bart; Lee, Jungeun Olivia; Brown, Eric C

2015-08-01

Bivariate analyses of adult crime and child maltreatment showed that individuals who had been maltreated as children, according to child welfare reports, subsequently committed more crime than others who had not been maltreated. Analyses of crimes by category-property, person, and society-provided further evidence of a link between child maltreatment and crime at the bivariate level. Tests of gender differences showed that crime generally is more prevalent among males, although females with a history of maltreatment were more likely than those in a no-maltreatment (comparison) group to report having had some prior involvement in crime. Surprisingly, multivariate analyses controlling for childhood socioeconomic status, gender, minority racial status, marital status, and education level showed that, with one exception (crimes against society), the significant association between child maltreatment and crime observed in bivariate tests was not maintained. Implications for future research are discussed. © The Author(s) 2014.

Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas.

PubMed

Hoyer, A; Kuss, O

2015-05-20

In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples. Copyright © 2015 John Wiley & Sons, Ltd.

On non-parametric maximum likelihood estimation of the bivariate survivor function.

PubMed

Prentice, R L

The likelihood function for the bivariate survivor function F, under independent censorship, is maximized to obtain a non-parametric maximum likelihood estimator &Fcirc;. &Fcirc; may or may not be unique depending on the configuration of singly- and doubly-censored pairs. The likelihood function can be maximized by placing all mass on the grid formed by the uncensored failure times, or half lines beyond the failure time grid, or in the upper right quadrant beyond the grid. By accumulating the mass along lines (or regions) where the likelihood is flat, one obtains a partially maximized likelihood as a function of parameters that can be uniquely estimated. The score equations corresponding to these point mass parameters are derived, using a Lagrange multiplier technique to ensure unit total mass, and a modified Newton procedure is used to calculate the parameter estimates in some limited simulation studies. Some considerations for the further development of non-parametric bivariate survivor function estimators are briefly described.

On the level of skill in predicting maximum sunspot number - A comparative study of single variate and bivariate precursor techniques

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

1990-01-01

The level of skill in predicting the size of the sunspot cycle is investigated for the two types of precursor techniques, single variate and bivariate fits, both applied to cycle 22. The present level of growth in solar activity is compared to the mean level of growth (cycles 10-21) and to the predictions based on the precursor techniques. It is shown that, for cycle 22, both single variate methods (based on geomagnetic data) and bivariate methods suggest a maximum amplitude smaller than that observed for cycle 19, and possibly for cycle 21. Compared to the mean cycle, cycle 22 is presently behaving as if it were a +2.6 sigma cycle (maximum amplitude of about 225), which means that either it will be the first cycle not to be reliably predicted by the combined precursor techniques or its deviation relative to the mean cycle will substantially decrease over the next 18 months.

An Agent-Based Modeling Approach to Integrate Tsunami Science, Human Behavior, and Unplanned Network Disruptions for Nearfield Tsunami Evacuation

NASA Astrophysics Data System (ADS)

Cox, D. T.; Wang, H.; Cramer, L.; Mostafizi, A.; Park, H.

2016-12-01

A 2015 heatwave in Pakistan is blamed for over a thousand deaths. This event consisted of several days of very high temperatures and unusually high humidity for this region. However, none of these days exceeded the threshold for "extreme danger" in terms of the heat index. The heat index is a univariate function of both temperature and humidity which is universally applied at all locations regardless of local climate. Understanding extremes which arise from multiple factors is challenging. In this paper we will present a tool for examining bivariate extreme behavior. The tool, developed in the statistical software R, draws isolines of equal exceedance probability. These isolines can be understood as bivariate "return levels". The tool is based on a dependence framework specific for extremes, is semiparametric, and is able to extrapolate isolines beyond the range of the data. We illustrate this tool using the Pakistan heat wave data and other bivariate data.

Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

NASA Astrophysics Data System (ADS)

Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.

2014-12-01

We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q<0 and greater than GHE when q>0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus.

PubMed

Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L; Kreiner, Eskil; Chesi, Alessandra; Zemel, Babette S; Bønnelykke, Klaus; Boer, Cindy G; Ahluwalia, Tarunveer S; Bisgaard, Hans; Evangelou, Evangelos; Heppe, Denise H M; Bonewald, Lynda F; Gorski, Jeffrey P; Ghanbari, Mohsen; Demissie, Serkalem; Duque, Gustavo; Maurano, Matthew T; Kiel, Douglas P; Hsu, Yi-Hsiang; C J van der Eerden, Bram; Ackert-Bicknell, Cheryl; Reppe, Sjur; Gautvik, Kaare M; Raastad, Truls; Karasik, David; van de Peppel, Jeroen; Jaddoe, Vincent W V; Uitterlinden, André G; Tobias, Jonathan H; Grant, Struan F A; Bagos, Pantelis G; Evans, David M; Rivadeneira, Fernando

2017-07-25

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34-52%) for TBLH-BMD, and 39% (95% CI: 30-48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29-56%). We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total body lean mass and bone mass density in children, and show genetic loci with pleiotropic effects on both traits.

The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

PubMed

Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

2018-05-01

Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.

Detection of phase synchronization from the data: Application to physiology

NASA Astrophysics Data System (ADS)

Rosenblum, Michael G.; Pikovsky, Arkady S.; Schäfer, Carsten; Tass, Peter; Kurths, Jürgen

2000-02-01

Synchronization of coupled oscillating systems means appearance of certain relations between their phases and frequencies. Here we use this concept in order to address the inverse problem and to reveal interaction between systems from experimental data. We discuss how the phases and frequencies can be estimated from time series and present the techniques for detection and quantification of synchronization. We apply our approach to multichannel magnetoencephalography data and records of muscle activity of a Parkinsonian patient, and also use it to analyze the cardiorespiratory interaction in humans. By means of these examples we demonstrate that our method is effective for the analysis of systems interrelation from noisy nonstationary bivariate data and provides other information than traditional correlation (spectral) techniques.

Health insurance coverage among disabled Medicare enrollees

PubMed Central

Rubin, Jeffrey I.; Wilcox-Gök, Virginia

1991-01-01

In this article, we use the Survey of Income and Program Participation to identify patterns of non-Medicare insurance coverage among disabled Medicare enrollees. Compared with the aged, the disabled are less likely to have private insurance coverage and more likely to have Medicaid. Probit analysis of the determinants of private insurance for disabled Medicare enrollees shows that income, education, marital status, sex, and having an employed family member are positively related to the likelihood of having private health insurance, whereas age and the probability of Medicaid enrollment are negatively related to this likelihood. PMID:10170806

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.

An algorithm for surface smoothing with rational splines

NASA Technical Reports Server (NTRS)

Schiess, James R.

1987-01-01

Discussed is an algorithm for smoothing surfaces with spline functions containing tension parameters. The bivariate spline functions used are tensor products of univariate rational-spline functions. A distinct tension parameter corresponds to each rectangular strip defined by a pair of consecutive spline knots along either axis. Equations are derived for writing the bivariate rational spline in terms of functions and derivatives at the knots. Estimates of these values are obtained via weighted least squares subject to continuity constraints at the knots. The algorithm is illustrated on a set of terrain elevation data.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Seasonal differences in the subjective assessment of outdoor thermal conditions and the impact of analysis techniques on the obtained results

NASA Astrophysics Data System (ADS)

Kántor, Noémi; Kovács, Attila; Takács, Ágnes

2016-11-01

Wide research attention has been paid in the last two decades to the thermal comfort conditions of different outdoor and semi-outdoor urban spaces. Field studies were conducted in a wide range of geographical regions in order to investigate the relationship between the thermal sensation of people and thermal comfort indices. Researchers found that the original threshold values of these indices did not describe precisely the actual thermal sensation patterns of subjects, and they reported neutral temperatures that vary among nations and with time of the year. For that reason, thresholds of some objective indices were rescaled and new thermal comfort categories were defined. This research investigates the outdoor thermal perception patterns of Hungarians regarding the Physiologically Equivalent Temperature ( PET) index, based on more than 5800 questionnaires. The surveys were conducted in the city of Szeged on 78 days in spring, summer, and autumn. Various, frequently applied analysis approaches (simple descriptive technique, regression analysis, and probit models) were adopted to reveal seasonal differences in the thermal assessment of people. Thermal sensitivity and neutral temperatures were found to be significantly different, especially between summer and the two transient seasons. Challenges of international comparison are also emphasized, since the results prove that neutral temperatures obtained through different analysis techniques may be considerably different. The outcomes of this study underline the importance of the development of standard measurement and analysis methodologies in order to make future studies comprehensible, hereby facilitating the broadening of the common scientific knowledge about outdoor thermal comfort.

Comparative Toxicities and Synergism of Apple Orchard Pesticides to Apis mellifera (L.) and Osmia cornifrons (Radoszkowski)

PubMed Central

Biddinger, David J.; Robertson, Jacqueline L.; Mullin, Chris; Frazier, James; Ashcraft, Sara A.; Rajotte, Edwin G.; Joshi, Neelendra K.; Vaughn, Mace

2013-01-01

The topical toxicities of five commercial grade pesticides commonly sprayed in apple orchards were estimated on adult worker honey bees, Apis mellifera (L.) (Hymenoptera: Apidae) and Japanese orchard bees, Osmia cornifrons (Radoszkowski) (Hymenoptera: Megachilidae). The pesticides were acetamiprid (Assail 30SG), λ-cyhalothrin (Warrior II), dimethoate (Dimethoate 4EC), phosmet (Imidan 70W), and imidacloprid (Provado 1.6F). At least 5 doses of each chemical, diluted in distilled water, were applied to freshly-eclosed adult bees. Mortality was assessed after 48 hr. Dose-mortality regressions were analyzed by probit analysis to test the hypotheses of parallelism and equality by likelihood ratio tests. For A. mellifera, the decreasing order of toxicity at LD50 was imidacloprid, λ-cyhalothrin, dimethoate, phosmet, and acetamiprid. For O. cornifrons, the decreasing order of toxicity at LD50 was dimethoate, λ-cyhalothrin, imidacloprid, acetamiprid, and phosmet. Interaction of imidacloprid or acetamiprid with the fungicide fenbuconazole (Indar 2F) was also tested in a 1∶1 proportion for each species. Estimates of response parameters for each mixture component applied to each species were compared with dose-response data for each mixture in statistical tests of the hypothesis of independent joint action. For each mixture, the interaction of fenbuconazole (a material non-toxic to both species) was significant and positive along the entire line for the pesticide. Our results clearly show that responses of A. mellifera cannot be extrapolated to responses of O.cornifrons, and that synergism of neonicotinoid insecticides and fungicides occurs using formulated product in mixtures as they are commonly applied in apple orchards. PMID:24039783

Comparative toxicities and synergism of apple orchard pesticides to Apis mellifera (L.) and Osmia cornifrons (Radoszkowski).

PubMed

Biddinger, David J; Robertson, Jacqueline L; Mullin, Chris; Frazier, James; Ashcraft, Sara A; Rajotte, Edwin G; Joshi, Neelendra K; Vaughn, Mace

2013-01-01

The topical toxicities of five commercial grade pesticides commonly sprayed in apple orchards were estimated on adult worker honey bees, Apis mellifera (L.) (Hymenoptera: Apidae) and Japanese orchard bees, Osmia cornifrons (Radoszkowski) (Hymenoptera: Megachilidae). The pesticides were acetamiprid (Assail 30SG), λ-cyhalothrin (Warrior II), dimethoate (Dimethoate 4EC), phosmet (Imidan 70W), and imidacloprid (Provado 1.6F). At least 5 doses of each chemical, diluted in distilled water, were applied to freshly-eclosed adult bees. Mortality was assessed after 48 hr. Dose-mortality regressions were analyzed by probit analysis to test the hypotheses of parallelism and equality by likelihood ratio tests. For A. mellifera, the decreasing order of toxicity at LD₅₀ was imidacloprid, λ-cyhalothrin, dimethoate, phosmet, and acetamiprid. For O. cornifrons, the decreasing order of toxicity at LD₅₀ was dimethoate, λ-cyhalothrin, imidacloprid, acetamiprid, and phosmet. Interaction of imidacloprid or acetamiprid with the fungicide fenbuconazole (Indar 2F) was also tested in a 1∶1 proportion for each species. Estimates of response parameters for each mixture component applied to each species were compared with dose-response data for each mixture in statistical tests of the hypothesis of independent joint action. For each mixture, the interaction of fenbuconazole (a material non-toxic to both species) was significant and positive along the entire line for the pesticide. Our results clearly show that responses of A. mellifera cannot be extrapolated to responses of O.cornifrons, and that synergism of neonicotinoid insecticides and fungicides occurs using formulated product in mixtures as they are commonly applied in apple orchards.

The patient’s anxiety before seeing a doctor and her/his hospital choice behavior in China

PubMed Central

2012-01-01

Background The patient’s anxiety before seeing a doctor may influence her/his hospital choice behavior through various ways. In order to explore why high level hospitals were overused by patients and why low level hospitals were not fully used by patients in China, this study was set up to test whether and to what extent the patient’s anxiety before seeing a doctor influenced her/his hospital choice behavior in China. Methods This study commissioned a large-scale 2009–2010 national resident household survey (N=4,853) in China, and in this survey the Self-Rating Anxiety Scale (SAS) was employed to help patients assess their anxiety before seeing a doctor. Specified ordered probit models were established to analyze the survey dataset. Results When the patient had high level of anxiety before seeing a doctor, her/his level of anxiety could not only predict that she/he was more likely to choose the high level hospital, but also accurately predict which level of hospital she/he would choose; when the patient had low level of anxiety before seeing a doctor, her/his level of anxiety could only predict that she/he was more likely to choose the low level hospital, but it couldn’t clearly predict which level of hospital she/he would choose. Conclusion The patient with high level of anxiety had the strong consistent bias when she/he chose a hospital (she/he always preferred the high level hospital), while the patient with low level of anxiety didn’t have such consistent bias. PMID:23270526

Child support and mixed-status families an analysis using the Fragile Families and Child Wellbeing Study.

PubMed

Xu, Lanlan; Pirog, Maureen A; Vargas, Edward D

2016-11-01

A large body of literature documents the importance of child support for children's wellbeing, though little is known about the child support behaviors of mixed-status families, a large and rapidly growing population in the United States. In this paper, we use data from the Fragile Families and Child Wellbeing Study to investigate the impact of citizenship status on formal and informal child support transfers among a nationally representative sample of parents who have citizen children. Probit regression models and propensity score matching (PSM) estimators show that mixed-status families are significantly less likely to have child support orders and child support receipt compared to their citizen counterparts. We found that mothers' knowledge of the child support system increases the probability of establishing paternity. However, cultural differences in knowledge of and perception about the U.S. child support system between mixed-status families and citizen families do not have an impact on the probability of getting a child support order, child support receipt, or in-kind child support. Rather, institutional factors such as collaborations between welfare agencies and child support enforcement agencies as well as state child support enforcement efforts have a significant impact on formal child support outcomes. The results are robust against different model specifications, measure constructions, and use of datasets. These findings have important policy implications for policy makers and researchers interested in reducing child poverty in complex family structures and underscore the need to revisit child support policies for mixed-status families. Copyright © 2016 Elsevier Inc. All rights reserved.

[Comparison of simple pooling and bivariate model used in meta-analyses of diagnostic test accuracy published in Chinese journals].

PubMed

Huang, Yuan-sheng; Yang, Zhi-rong; Zhan, Si-yan

2015-06-18

To investigate the use of simple pooling and bivariate model in meta-analyses of diagnostic test accuracy (DTA) published in Chinese journals (January to November, 2014), compare the differences of results from these two models, and explore the impact of between-study variability of sensitivity and specificity on the differences. DTA meta-analyses were searched through Chinese Biomedical Literature Database (January to November, 2014). Details in models and data for fourfold table were extracted. Descriptive analysis was conducted to investigate the prevalence of the use of simple pooling method and bivariate model in the included literature. Data were re-analyzed with the two models respectively. Differences in the results were examined by Wilcoxon signed rank test. How the results differences were affected by between-study variability of sensitivity and specificity, expressed by I2, was explored. The 55 systematic reviews, containing 58 DTA meta-analyses, were included and 25 DTA meta-analyses were eligible for re-analysis. Simple pooling was used in 50 (90.9%) systematic reviews and bivariate model in 1 (1.8%). The remaining 4 (7.3%) articles used other models pooling sensitivity and specificity or pooled neither of them. Of the reviews simply pooling sensitivity and specificity, 41(82.0%) were at the risk of wrongly using Meta-disc software. The differences in medians of sensitivity and specificity between two models were both 0.011 (P<0.001, P=0.031 respectively). Greater differences could be found as I2 of sensitivity or specificity became larger, especially when I2>75%. Most DTA meta-analyses published in Chinese journals(January to November, 2014) combine the sensitivity and specificity by simple pooling. Meta-disc software can pool the sensitivity and specificity only through fixed-effect model, but a high proportion of authors think it can implement random-effect model. Simple pooling tends to underestimate the results compared with bivariate model. The greater the between-study variance is, the more likely the simple pooling has larger deviation. It is necessary to increase the knowledge level of statistical methods and software for meta-analyses of DTA data.

Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies.

PubMed

Calus, M P L; de Haas, Y; Veerkamp, R F

2013-10-01

Genomic selection holds the promise to be particularly beneficial for traits that are difficult or expensive to measure, such that access to phenotypes on large daughter groups of bulls is limited. Instead, cow reference populations can be generated, potentially supplemented with existing information from the same or (highly) correlated traits available on bull reference populations. The objective of this study, therefore, was to develop a model to perform genomic predictions and genome-wide association studies based on a combined cow and bull reference data set, with the accuracy of the phenotypes differing between the cow and bull genomic selection reference populations. The developed bivariate Bayesian stochastic search variable selection model allowed for an unbalanced design by imputing residuals in the residual updating scheme for all missing records. The performance of this model is demonstrated on a real data example, where the analyzed trait, being milk fat or protein yield, was either measured only on a cow or a bull reference population, or recorded on both. Our results were that the developed bivariate Bayesian stochastic search variable selection model was able to analyze 2 traits, even though animals had measurements on only 1 of 2 traits. The Bayesian stochastic search variable selection model yielded consistently higher accuracy for fat yield compared with a model without variable selection, both for the univariate and bivariate analyses, whereas the accuracy of both models was very similar for protein yield. The bivariate model identified several additional quantitative trait loci peaks compared with the single-trait models on either trait. In addition, the bivariate models showed a marginal increase in accuracy of genomic predictions for the cow traits (0.01-0.05), although a greater increase in accuracy is expected as the size of the bull population increases. Our results emphasize that the chosen value of priors in Bayesian genomic prediction models are especially important in small data sets. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Flood risk analysis for flood control and sediment transportation: a case study in the catchments of the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Wang, Y.; Chang, J.; Guo, A.

2017-12-01

Traditional flood risk analysis focuses on the probability of flood events exceeding the design flood of downstream hydraulic structures while neglecting the influence of sedimentation in river channels on flood control systems. Given this focus, a univariate and copula-based bivariate hydrological risk framework focusing on flood control and sediment transport is proposed in the current work. Additionally, the conditional probabilities of occurrence of different flood events under various extreme precipitation scenarios are estimated by exploiting the copula model. Moreover, a Monte Carlo-based algorithm is used to evaluate the uncertainties of univariate and bivariate hydrological risk. Two catchments located on the Loess plateau are selected as study regions: the upper catchments of the Xianyang and Huaxian stations (denoted as UCX and UCH, respectively). The results indicate that (1) 2-day and 3-day consecutive rainfall are highly correlated with the annual maximum flood discharge (AMF) in UCX and UCH, respectively; and (2) univariate and bivariate return periods, risk and reliability for the purposes of flood control and sediment transport are successfully estimated. Sedimentation triggers higher risks of damaging the safety of local flood control systems compared with the AMF, exceeding the design flood of downstream hydraulic structures in the UCX and UCH. Most importantly, there was considerable sampling uncertainty in the univariate and bivariate hydrologic risk analysis, which would greatly challenge measures of future flood mitigation. The proposed hydrological risk framework offers a promising technical reference for flood risk analysis in sandy regions worldwide.

Predicting the Size of Sunspot Cycle 24 on the Basis of Single- and Bi-Variate Geomagnetic Precursor Methods

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2009-01-01

Examined are single- and bi-variate geomagnetic precursors for predicting the maximum amplitude (RM) of a sunspot cycle several years in advance. The best single-variate fit is one based on the average of the ap index 36 mo prior to cycle minimum occurrence (E(Rm)), having a coefficient of correlation (r) equal to 0.97 and a standard error of estimate (se) equal to 9.3. Presuming cycle 24 not to be a statistical outlier and its minimum in March 2008, the fit suggests cycle 24 s RM to be about 69 +/- 20 (the 90% prediction interval). The weighted mean prediction of 11 statistically important single-variate fits is 116 +/- 34. The best bi-variate fit is one based on the maximum and minimum values of the 12-mma of the ap index; i.e., APM# and APm*, where # means the value post-E(RM) for the preceding cycle and * means the value in the vicinity of cycle minimum, having r = 0.98 and se = 8.2. It predicts cycle 24 s RM to be about 92 +/- 27. The weighted mean prediction of 22 statistically important bi-variate fits is 112 32. Thus, cycle 24's RM is expected to lie somewhere within the range of about 82 to 144. Also examined are the late-cycle 23 behaviors of geomagnetic indices and solar wind velocity in comparison to the mean behaviors of cycles 2023 and the geomagnetic indices of cycle 14 (RM = 64.2), the weakest sunspot cycle of the modern era.

Probabilistic modelling of drought events in China via 2-dimensional joint copula

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Javed, Tehseen; Yao, Ning

2018-04-01

Probabilistic modelling of drought events is a significant aspect of water resources management and planning. In this study, popularly applied and several relatively new bivariate Archimedean copulas were employed to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013. Drought duration (Dd), severity (Ds), and peak (Dp), as indicated by Standardized Precipitation Evapotranspiration Index (SPEI), were extracted according to the run theory and fitted with suitable marginal distributions. The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas. Drought probabilities and return periods were analysed based on appropriate bivariate copula in sub-region I-VII and entire mainland China. The goodness-of-fit tests as indicated by the CFM showed that copula NN19 in sub-regions III, IV, V, VI and mainland China, NN20 in sub-region I and NN13 in sub-region VII are the best for modeling drought variables. Bivariate drought probability across mainland China is relatively high, and the highest drought probabilities are found mainly in the Northwestern and Southwestern China. Besides, the result also showed that different sub-regions might suffer varying drought risks. The drought risks as observed in Sub-region III, VI and VII, are significantly greater than other sub-regions. Higher probability of droughts of longer durations in the sub-regions also corresponds to shorter return periods with greater drought severity. These results may imply tremendous challenges for the water resources management in different sub-regions, particularly the Northwestern and Southwestern China.

Bayesian inference in an item response theory model with a generalized student t link function

NASA Astrophysics Data System (ADS)

Azevedo, Caio L. N.; Migon, Helio S.

2012-10-01

In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

Timing of Puberty in Overweight Versus Obese Boys.

PubMed

Lee, Joyce M; Wasserman, Richard; Kaciroti, Niko; Gebremariam, Achamyeleh; Steffes, Jennifer; Dowshen, Steven; Harris, Donna; Serwint, Janet; Abney, Dianna; Smitherman, Lynn; Reiter, Edward; Herman-Giddens, Marcia E

2016-02-01

Studies of the relationship of weight status with timing of puberty in boys have been mixed. This study examined whether overweight and obesity are associated with differences in the timing of puberty in US boys. We reanalyzed recent community-based pubertal data from the American Academy of Pediatrics' Pediatric Research in Office Settings study in which trained clinicians assessed boys 6 to 16 years for height, weight, Tanner stages, testicular volume (TV), and other pubertal variables. We classified children based on BMI as normal weight, overweight, or obese and compared median age at a given Tanner stage or greater by weight class using probit and ordinal probit models and a Bayesian approach. Half of boys (49.9%, n = 1931) were white, 25.8% (n = 1000) were African American, and 24.3% (n = 941) were Hispanic. For genital development in white and African American boys across a variety of Tanner stages, we found earlier puberty in overweight compared with normal weight boys, and later puberty in obese compared with overweight, but no significant differences for Hispanics. For TV (≥3 mL or ≥4 mL), our findings support earlier puberty for overweight compared with normal weight white boys. In a large, racially diverse, community-based sample of US boys, we found evidence of earlier puberty for overweight compared with normal or obese, and later puberty for obese boys compared with normal and overweight boys. Additional studies are needed to understand the possible relationships among race/ethnicity, gender, BMI, and the timing of pubertal development. Copyright © 2016 by the American Academy of Pediatrics.

Multilevel Effects of Wealth on Women's Contraceptive Use in Mozambique

PubMed Central

Dias, José G.; de Oliveira, Isabel Tiago

2015-01-01

Objective This paper analyzes the impact of wealth on the use of contraception in Mozambique unmixing the contextual effects due to community wealth from the individual effects associated with the women's situation within the community of residence. Methods Data from the 2011 Mozambican Demographic and Health Survey on women who are married or living together are analyzed for the entire country and also for the rural and urban areas separately. We used single level and multilevel probit regression models. Findings A single level probit regression reveals that region, religion, age, previous fertility, education, and wealth impact contraceptive behavior. The multilevel analysis shows that average community wealth and the women’s relative socioeconomic position within the community have significant positive effects on the use of modern contraceptives. The multilevel framework proved to be necessary in rural settings but not relevant in urban areas. Moreover, the contextual effects due to community wealth are greater in rural than in urban areas and this feature is associated with the higher socioeconomic heterogeneity within the richest communities. Conclusion This analysis highlights the need for the studies on contraceptive behavior to specifically address the individual and contextual effects arising from the poverty-wealth dimension in rural and urban areas separately. The inclusion in a particular community of residence is not relevant in urban areas, but it is an important feature in rural areas. Although the women's individual position within the community of residence has a similar effect on contraceptive adoption in rural and urban settings, the impact of community wealth is greater in rural areas and smaller in urban areas. PMID:25786228

Effects of the 2008 Global Economic Crisis on National Health Indicators: Results from the Korean National Health and Nutrition Examination Survey

PubMed Central

Shin, Jung-Hyun; Lee, Gyeongsil; Kim, Jun-Suk; Oh, Hyung-Seok; Lee, Keun-Seung; Hur, Yong

2015-01-01

Background The relationship between economics and health has been of great interest throughout the years. The accumulated data is not sufficient enough to carry out long-term studies from the viewpoint of morbidity, although Korea National Health and Nutrition Examination Survey (KNHANES) was carried out yearly since 1998 in Korea. Thus, we investigated the effect of the 2008 global economic crisis on health indicators of Korea. Methods Health indicators were selected by paired t-test based on 2007 and 2009 KNHANES data. Age, gender, body mass index (BMI), smoking, drinking, exercise, education, income, working status, and stress were used as confounding factors, which were analyzed with logistic and probit analyses. Validation was done by comparing gross domestic product (GDP) growth rates and probit analyses results of 2007-2012 KNHANES data. Results Among several health indicators, the prevalence of hypertension and stress perception was higher after the economic crisis. Factors related with higher hypertension prevalence include older age, male gender, higher BMI, no current tobacco use, recent drinking, lower education levels, and stress perception. Factors related with more stress perception were younger age, female gender, current smoking, lower education levels, and lower income. GDP growth rates, a macroeconomic indicator, are inversely associated with hypertension prevalence with a one-year lag, and also inversely associated with stress perception without time lag. Conclusion The economic crisis increased the prevalence of hypertension and stress perception. In the case of GDP growth rate change, hypertension was an inversely lagging indicator and stress perception was an inversely-related coincident indicator. PMID:26217479

Validity of using ad hoc methods to analyze secondary traits in case-control association studies.

PubMed

Yung, Godwin; Lin, Xihong

2016-12-01

Case-control association studies often collect from their subjects information on secondary phenotypes. Reusing the data and studying the association between genes and secondary phenotypes provide an attractive and cost-effective approach that can lead to discovery of new genetic associations. A number of approaches have been proposed, including simple and computationally efficient ad hoc methods that ignore ascertainment or stratify on case-control status. Justification for these approaches relies on the assumption of no covariates and the correct specification of the primary disease model as a logistic model. Both might not be true in practice, for example, in the presence of population stratification or the primary disease model following a probit model. In this paper, we investigate the validity of ad hoc methods in the presence of covariates and possible disease model misspecification. We show that in taking an ad hoc approach, it may be desirable to include covariates that affect the primary disease in the secondary phenotype model, even though these covariates are not necessarily associated with the secondary phenotype. We also show that when the disease is rare, ad hoc methods can lead to severely biased estimation and inference if the true disease model follows a probit model instead of a logistic model. Our results are justified theoretically and via simulations. Applied to real data analysis of genetic associations with cigarette smoking, ad hoc methods collectively identified as highly significant (P<10-5) single nucleotide polymorphisms from over 10 genes, genes that were identified in previous studies of smoking cessation. © 2016 WILEY PERIODICALS, INC.

Retinal injury thresholds for 532, 578, and 630 nm lasers in connection to photodynamic therapy for choroidal neovascularization.

PubMed

Chen, Hongxia; Yang, Zaifu; Zou, Xianbiao; Wang, Jiarui; Zhu, Jianguo; Gu, Ying

2014-01-01

The purpose of this study was to explore the retinal injury thresholds in rabbits and evaluate the influence of retinal pigmentation on threshold irradiance at laser wavelengths of 532, 578, and 630 nm which might be involved in hypocrellin B (HB) and hematoporphyrin monomethyl ether (HMME) photodynamic therapy (PDT) for choroidal neovascularization (CNV). The eyes of pigmented and non-pigmented rabbits were exposed to 532, 578, and 630 nm lasers coupled to a slit lamp biological microscope. The exposure duration was 100 seconds and the retinal spot size was 2 mm throughout the experiment. The minimum visible lesions were detected by funduscopy at 1 and 24 hours post exposure. Bliss probit analysis was performed to determine the ED50 thresholds, fiducial limits and probit slope. In pigmented rabbits, the 24-hour retinal threshold irradiances at 532, 578, and 630 nm were 1,003, 1,475, and 1,720 mW/cm(2) , respectively. In non-pigmented rabbits, the 24-hour threshold irradiances were 1,657, 1,865, and 15,360 mW/cm(2) , respectively. The ED50 for 24-hour observation differed very little from the ED50 for 1-hour observation. The non-pigmented rabbits required a ninefold increase in threshold irradiance at 630 nm comparing to the pigmented rabbits. This study will contribute to the knowledge base for the limits of laser irradiance in application of HB or HMME PDT for CNV. © 2013 Wiley Periodicals, Inc.

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

Takahashi, Ryo, E-mail: inter.takahashi@gmail.com; Todo, Yasuyuki, E-mail: yastodo@k.u-tokyo.ac.jp

In recent years, shade coffee certification programs have attracted increasing attention from forest conservation and development organizations. The certification programs could be expected to promote forest conservation by providing a premium price to shade coffee producers. However, little is known about the significance of the conservation efforts generated by certification programs. In particular, the relationship between the impact of the certification and producer characteristics has yet to be examined. The purpose of this study, which was conducted in Ethiopia, was to examine the impact of a shade coffee certification program on forest conservation and its relationship with the socioeconomic characteristicsmore » of the producers. Remote sensing data of 2005 and 2010 was used to gauge the changes in forest area. Employing a probit model, we found that a forest coffee area being certified increased the probability of forest conservation by 19.3 percentage points relative to forest coffee areas lacking certification. We also found that although economically poor producers tended to engage in forest clearing, the forest coffee certification program had a significant impact on these producers. This result suggests that the certification program significantly affects the behaviors of economically poor producers and motivates these producers to conserve the forest. -- Highlights: • We employed the probit mode to evaluate the impact of the shade coffee certification on forest conservation in Ethiopia. • We estimated how the impact of the certification varied among producers with different characteristics. • The certification increased the probability of conserving forest by 19.3 percentage points. • Certification program motivated the economically poor producers to conserve the forest.« less

Genetic contribution to patent ductus arteriosus in the premature newborn.

PubMed

Bhandari, Vineet; Zhou, Gongfu; Bizzarro, Matthew J; Buhimschi, Catalin; Hussain, Naveed; Gruen, Jeffrey R; Zhang, Heping

2009-02-01

The most common congenital heart disease in the newborn population, patent ductus arteriosus, accounts for significant morbidity in preterm newborns. In addition to prematurity and environmental factors, we hypothesized that genetic factors play a significant role in this condition. The objective of this study was to quantify the contribution of genetic factors to the variance in liability for patent ductus arteriosus in premature newborns. A retrospective study (1991-2006) from 2 centers was performed by using zygosity data from premature twins born at < or =36 weeks' gestational age and surviving beyond 36 weeks' postmenstrual age. Patent ductus arteriosus was diagnosed by echocardiography at each center. Mixed-effects logistic regression was used to assess the effect of specific covariates. Latent variable probit modeling was then performed to estimate the heritability of patent ductus arteriosus, and mixed-effects probit modeling was used to quantify the genetic component. We obtained data from 333 dizygotic twin pairs and 99 monozygotic twin pairs from 2 centers (Yale University and University of Connecticut). Data on chorioamnionitis, antenatal steroids, gestational age, body weight, gender, respiratory distress syndrome, patent ductus arteriosus, necrotizing enterocolitis, oxygen supplementation, and bronchopulmonary dysplasia were comparable between monozygotic and dizygotic twins. We found that gestational age, respiratory distress syndrome, and institution were significant covariates for patent ductus arteriosus. After controlling for specific covariates, genetic factors or the shared environment accounted for 76.1% of the variance in liability for patent ductus arteriosus. Preterm patent ductus arteriosus is highly familial (contributed to by genetic and environmental factors), with the effect being mainly environmental, after controlling for known confounders.

Effects of the 2008 Global Economic Crisis on National Health Indicators: Results from the Korean National Health and Nutrition Examination Survey.

PubMed

Shin, Jung-Hyun; Lee, Gyeongsil; Kim, Jun-Suk; Oh, Hyung-Seok; Lee, Keun-Seung; Hur, Yong; Cho, Be-Long

2015-07-01

The relationship between economics and health has been of great interest throughout the years. The accumulated data is not sufficient enough to carry out long-term studies from the viewpoint of morbidity, although Korea National Health and Nutrition Examination Survey (KNHANES) was carried out yearly since 1998 in Korea. Thus, we investigated the effect of the 2008 global economic crisis on health indicators of Korea. Health indicators were selected by paired t-test based on 2007 and 2009 KNHANES data. Age, gender, body mass index (BMI), smoking, drinking, exercise, education, income, working status, and stress were used as confounding factors, which were analyzed with logistic and probit analyses. Validation was done by comparing gross domestic product (GDP) growth rates and probit analyses results of 2007-2012 KNHANES data. Among several health indicators, the prevalence of hypertension and stress perception was higher after the economic crisis. Factors related with higher hypertension prevalence include older age, male gender, higher BMI, no current tobacco use, recent drinking, lower education levels, and stress perception. Factors related with more stress perception were younger age, female gender, current smoking, lower education levels, and lower income. GDP growth rates, a macroeconomic indicator, are inversely associated with hypertension prevalence with a one-year lag, and also inversely associated with stress perception without time lag. The economic crisis increased the prevalence of hypertension and stress perception. In the case of GDP growth rate change, hypertension was an inversely lagging indicator and stress perception was an inversely-related coincident indicator.

Genome-wide meta-analysis identifies novel gender specific loci associated with thyroid antibodies level in Croatians.

PubMed

Matana, Antonela; Popović, Marijana; Boutin, Thibaud; Torlak, Vesela; Brdar, Dubravka; Gunjača, Ivana; Kolčić, Ivana; Boraska Perica, Vesna; Punda, Ante; Polašek, Ozren; Hayward, Caroline; Barbalić, Maja; Zemunik, Tatijana

2018-04-18

Autoimmune thyroid diseases (AITD) are multifactorial endocrine diseases most frequently accompanied by Tg and TPO autoantibodies. Both antibodies have a higher prevalence in females and act under a strong genetic influence. To identify novel variants underlying thyroid antibody levels, we performed GWAS meta-analysis on the plasma levels of TgAb and TPOAb in three Croatian cohorts, as well as gender specific GWAS and a bivariate analysis. No significant association was detected with the level of TgAb and TPOAb in the meta-analysis of GWAS or bivariate results for all individuals. The bivariate analysis in females only revealed a genome-wide significant association for the locus near GRIN3A (rs4457391, P = 7.76 × 10 -9 ). The same locus had borderline association with TPOAb levels in females (rs1935377, P = 8.58 × 10 -8 ). In conclusion, we identified a novel gender specific locus associated with TgAb and TPOAb levels. Our findings provide a novel insight into genetic and gender differences associated with thyroid antibodies. Copyright © 2018 Elsevier Inc. All rights reserved.

Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models

PubMed Central

Liu, Ziyue; Cappola, Anne R.; Crofford, Leslie J.; Guo, Wensheng

2013-01-01

The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudinal hormone profiles is a challenging task. In this paper, we propose a bivariate hierarchical state space model, in which each hormone profile is modeled by a hierarchical state space model, with both population-average and subject-specific components. The bivariate model is constructed by concatenating the univariate models based on the hypothesized relationship. Because of the flexible framework of state space form, the resultant models not only can handle complex individual profiles, but also can incorporate complex relationships between two hormones, including both concurrent and feedback relationship. Estimation and inference are based on marginal likelihood and posterior means and variances. Computationally efficient Kalman filtering and smoothing algorithms are used for implementation. Application of the proposed method to a study of chronic fatigue syndrome and fibromyalgia reveals that the relationships between adrenocorticotropic hormone and cortisol in the patient group are weaker than in healthy controls. PMID:24729646

Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models.

PubMed

Liu, Ziyue; Cappola, Anne R; Crofford, Leslie J; Guo, Wensheng

2014-01-01

The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudinal hormone profiles is a challenging task. In this paper, we propose a bivariate hierarchical state space model, in which each hormone profile is modeled by a hierarchical state space model, with both population-average and subject-specific components. The bivariate model is constructed by concatenating the univariate models based on the hypothesized relationship. Because of the flexible framework of state space form, the resultant models not only can handle complex individual profiles, but also can incorporate complex relationships between two hormones, including both concurrent and feedback relationship. Estimation and inference are based on marginal likelihood and posterior means and variances. Computationally efficient Kalman filtering and smoothing algorithms are used for implementation. Application of the proposed method to a study of chronic fatigue syndrome and fibromyalgia reveals that the relationships between adrenocorticotropic hormone and cortisol in the patient group are weaker than in healthy controls.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors.

PubMed

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A

2015-11-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors

PubMed Central

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A.

2015-01-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional. PMID:26644943

Bivariate random-effects meta-analysis models for diagnostic test accuracy studies using arcsine-based transformations.

PubMed

Negeri, Zelalem F; Shaikh, Mateen; Beyene, Joseph

2018-05-11

Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation. We compared the performance of the proposed methods with the standard method through simulations using several performance measures. The simulation results showed that our proposed methods performed better than the standard LMM in terms of bias, root mean square error, and coverage probability in most of the scenarios, even when data were generated assuming the standard LMM. We also illustrated the methods using two real data sets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effects of Medical Insurance on the Health Status and Life Satisfaction of the Elderly

PubMed Central

GU, Liubao; FENG, Huihui; JIN, Jian

2017-01-01

Background: Population aging has become increasingly serious in China. The demand for medical insurance of the elderly is increasing, and their health status and life satisfaction are becoming significant issues. This study investigates the effects of medical insurance on the health status and life satisfaction of the elderly. Methods: The national baseline survey data of the China Health and Retirement Longitudinal Survey in 2013 were adopted. The Ordered Probit Model was established. The effects of the medical insurance for urban employees, medical insurance for urban residents, and new rural cooperative medical insurance on the health status and life satisfaction of the elderly were investigated. Results: Medical insurance could facilitate the improvement of the health status and life satisfaction of the elderly. Accordingly, the health status and life satisfaction of the elderly who have medical insurance for urban residents improved significantly. The regression coefficients were 0.348 and 0.307. The corresponding regression coefficients of the medical insurance for urban employees were 0.189 and 0.236. The regression coefficients of the new rural cooperative medical insurance were 0.170 and 0.188. Conclusion: Medical insurance can significantly improve the health status and life satisfaction of the elderly. This development is of immense significance for the formulation of equal medical security. PMID:29026784

Enhanced Reverse Transcription-PCR Assay for Detection of Norovirus Genogroup I

PubMed Central

Dreier, Jens; Störmer, Melanie; Mäde, Dietrich; Burkhardt, Sabine; Kleesiek, Knut

2006-01-01

We have developed a one-tube reverse transcription (RT)-PCR method using the real-time TaqMan PCR system for the detection of norovirus genogroup I (NV GGI). By introduction of a novel probe based on locked nucleic acid technology, we enhanced the sensitivity of the assay compared to those of conventional TaqMan probes. The sensitivity of the NV GGI RT-PCR was determined by probit analysis with defined RNA standards and quantified norovirus isolates to 711 copies/ml (95% detection limit). In order to detect PCR inhibition, we included a heterologous internal control (IC) system based on phage MS2. This internally controlled RT-PCR was tested on different real-time PCR platforms, LightCycler, Rotorgene, Mastercycler EP realplex, and ABI Prism. Compared to the assay without an IC, the duplex RT-PCR exhibited no reduction in sensitivity in clinical samples. In combination with an established NV GGII real-time RT-PCR, we used the novel assay in a routine assay for diagnosis of clinical and food-borne norovirus infection. We applied this novel assay to analyze outbreaks of nonbacterial acute gastroenteritis. Norovirus of GGI was detected in these outbreaks. Sequence and similarity plot analysis of open reading frame 1 (ORF1) and ORF2 showed two genotypes, GGI/2 and GGI/4, in semiclosed communities. PMID:16891482

Analysis of the injury severity of crashes by considering different lighting conditions on two-lane rural roads.

PubMed

Jafari Anarkooli, A; Hadji Hosseinlou, M

2016-02-01

Many studies have examined different factors contributing to the injury severity of crashes; however, relatively few studies have focused on the crashes by considering the specific effects of lighting conditions. This research investigates lighting condition differences in the injury severity of crashes using 3-year (2009-2011) crash data of two-lane rural roads of the state of Washington. Separate ordered-probit models were developed to predict the effects of a set of factors expected to influence injury severity in three lighting conditions; daylight, dark, and dark with street lights. A series of likelihood ratio tests were conducted to determine if these lighting condition models were justified. The modeling results suggest that injury severity in specific lighting conditions are associated with contributing factors in different ways, and that such differences cannot be uncovered by focusing merely on one aggregate model. Key differences include crash location, speed limit, shoulder width, driver action, and three collision types (head-on, rear-end, and right-side impact collisions). This paper highlights the importance of deploying street lights at and near intersections (or access points) on two-lane rural roads because injury severity highly increases when crashes occur at these points in dark conditions. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Bayesian Analysis of High Dimensional Classification

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Subhadeep; Liang, Faming

2009-12-01

Modern data mining and bioinformatics have presented an important playground for statistical learning techniques, where the number of input variables is possibly much larger than the sample size of the training data. In supervised learning, logistic regression or probit regression can be used to model a binary output and form perceptron classification rules based on Bayesian inference. In these cases , there is a lot of interest in searching for sparse model in High Dimensional regression(/classification) setup. we first discuss two common challenges for analyzing high dimensional data. The first one is the curse of dimensionality. The complexity of many existing algorithms scale exponentially with the dimensionality of the space and by virtue of that algorithms soon become computationally intractable and therefore inapplicable in many real applications. secondly, multicollinearities among the predictors which severely slowdown the algorithm. In order to make Bayesian analysis operational in high dimension we propose a novel 'Hierarchical stochastic approximation monte carlo algorithm' (HSAMC), which overcomes the curse of dimensionality, multicollinearity of predictors in high dimension and also it possesses the self-adjusting mechanism to avoid the local minima separated by high energy barriers. Models and methods are illustrated by simulation inspired from from the feild of genomics. Numerical results indicate that HSAMC can work as a general model selection sampler in high dimensional complex model space.

Exploring the covariates of sport participation for health: an analysis of males and females in England.

PubMed

Downward, Paul; Rasciute, Simona

2015-01-01

Increasing sport participation has been identified as a key vehicle for achieving World Health Organisation guidelines for health-enhancing physical activity (HEPA). A policy challenge is to promote this changed behaviour. Making use of the Active People Survey, a zero-inflated ordered probit model is used to identify the covariates of sport participation for males and females with respect to the related decisions to either participate in sport or not, and to participate at either lower or higher than desired intensity. To inform current policy emphases, the Active Places Survey is also used to examine the causal impact of facility provision on these behaviours. Results indicate that females are more likely to adopt less intensive activity even with time available. Families could place most constraints on females, but also reduce the intensity of male participation. Education has a greater association with higher intensity female activity. The largest effects are identified for sport club membership and facility satisfaction. Both of these affect male intensity of activity most. The main policy challenges facing sport in contributing to HEPA are shown to involve retaining male intensity of participation when ageing and encouraging greater female intensity of participation, with more appropriate matching of facilities.

Determinants of body weight status in Malaysia: an ethnic comparison.

PubMed

Tan, Andrew K G; Yen, Steven T; Feisul, Mustapha I

2012-04-01

To investigate the roles of sociodemographic and health lifestyle factors in affecting body mass index (BMI) across ethnic groups in Malaysia. Data are obtained from 2,436 observations from the Malaysia Non-Communicable Disease Surveillance-1. The multi-ethnic sample is segmented into Malay, Chinese, and Indian/other ethnicities. Ordered probit analysis is conducted and marginal effects of sociodemographic and health lifestyle variables on BMI calculated. Malays between 41 and 58 years are more likely to be overweight or obese than their 31-40 years counterparts, while the opposite is true among Chinese. Retirees of Chinese and Indian/other ethnicities are less likely to be obese and more likely to have normal BMI than those between 31 and 40 years. Primary educated Chinese are more likely to be overweight or obese, while tertiary-educated Malays are less likely to suffer from similar weight issues as compared to those with only junior high school education. Affluent Malays and Chinese are more likely to be overweight than their low-middle income cohorts. Family illness history is likely to cause overweightness or obesity, irrespective of ethnicity. Malay cigarette smokers have lower overweight and obesity probabilities than non-cigarette smokers. There exists a need for flexible policies to address cross-ethnic differences in the sociodemographic and health-lifestyle covariates of BMI.

Do increases in cigarette prices lead to increases in sales of cigarettes with high tar and nicotine yields?

PubMed

Farrelly, Matthew C; Loomis, Brett R; Mann, Nathan H

2007-10-01

We used scanner data on cigarette prices and sales collected from supermarkets across the United States from 1994 to 2004 to test the hypothesis that cigarette prices are positively correlated with sales of cigarettes with higher tar and nicotine content. During this period the average inflation-adjusted price for menthol cigarettes increased 55.8%. Price elasticities from multivariate regression models suggest that this price increase led to an increase of 1.73% in sales-weighted average tar yields and a 1.28% increase in sales-weighted average nicotine yields for menthol cigarettes. The 50.5% price increase of nonmenthol varieties over the same period yielded an estimated increase of 1% in tar per cigarette but no statistically significant increase in nicotine yields. An ordered probit model of the impact of cigarette prices on cigarette strength (ultra-light, light, full flavor, unfiltered) offers an explanation: As cigarette prices increase, the probability that stronger cigarette types will be sold increases. This effect is larger for menthol than for nonmenthol cigarettes. Our results are consistent with earlier population-based cross-sectional and longitudinal studies showing that higher cigarette prices and taxes are associated with increasing consumption of higher-yield cigarettes by smokers.

Types of gambling and levels of harm: A UK study to assess severity of presentation in a treatment-seeking population

PubMed Central

Ronzitti, Silvia; Soldini, Emiliano; Lutri, Vittorio; Smith, Neil; Clerici, Massimo; Bowden-Jones, Henrietta

2016-01-01

Background and aim Previous international research emphasized that some forms of gambling are more “addictive” than others. More recently, research has shown that we should shift our attention from the type of gambling activity to the level of involvement in a number of different gambling activities. The aim of our study was to verify whether a higher Problem Gambling Severity Index (PGSI) score was associated with particular gambling activities and evaluate the impact of involvement on gambling behavior. Methods A total of 736 treatment-seeking individuals with gambling disorder were assessed at the National Problem Gambling Clinic in London. First, the independent two-sample t-test and the Mann–Whitney test were used to verify if the PGSI score changed significantly according to the gambling activity at a bivariate level. Second, we conducted a cluster analysis and finally, we fitted a linear regression model in order to verify if some variables are useful to predict gambling addiction severity. Results The PGSI score was significantly higher for lower stakes gaming machine gamblers (1% significance level) and for fixed-odds betting terminal (FOBT) gamblers (5% significance level) at a bivariate level. Moreover, such finding was confirmed by cluster and linear regression analyses. Conclusions The results of this study indicated that gambling addiction severity was related to gambling involvement and, for a given level of gambling involvement, gambling addiction severity may vary according to gambling type, with a particularly significant increase for FOBT and gaming machine gambling. PMID:27677350

[Socio-demographic Characterization of Psychosexual Development and Crime in Men Convicted of Sexual Crimes Imprisoned in the Manizales Penitentiary Center].

PubMed

Rivera, Adriana Arcila; Ramírez, Mauricio Castaño; Montoya, Dulcinea Osorio; Quiroz, Germán

2013-03-01

This article introduces the socio-demographic characteristics of psychosexual development and sexual crimes in men deprived of liberty for such crimes who are doing time in a Manizales prison (Colombia) in 2011. It also describes the differences between abusers of individuals under 12 years of age or who are 12 years old, and abusers of individuals over that age. This is a descriptive, retrospective study performed by simple random sampling. It consisted of semi-structured interviews in which socio-demographic characteristics, psychosexual development, characteristics of crime, and prevalence of mental disorders were analyzed in a sample of 80 inmates convicted of sexual offenses at the Medium-security Pentientiary center in the city of Manizales. Univariate and bivariate analysis were performed using the χ(2) test and the logistic regression analysis with variables showing statistical significance in the bivariate analysis. It was found that convicted sex offenders belong to lower socioeconomic levels, have low educational levels, and did not receive any sexual education. Such findings become more relevant when the crimes in questions are committed against 12-year-olders or children under this age. The lack of sexual education, low educational levels and lower socioeconomic levels are associated factors in the case of sexual offenses. It is important for society (particularly health-care institutions) to find additional measures for the criminalization of such behaviors in order to achieve a better control of the problem. Copyright © 2013 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Types of gambling and levels of harm: A UK study to assess severity of presentation in a treatment-seeking population.

PubMed

Ronzitti, Silvia; Soldini, Emiliano; Lutri, Vittorio; Smith, Neil; Clerici, Massimo; Bowden-Jones, Henrietta

2016-09-01

Background and aim Previous international research emphasized that some forms of gambling are more "addictive" than others. More recently, research has shown that we should shift our attention from the type of gambling activity to the level of involvement in a number of different gambling activities. The aim of our study was to verify whether a higher Problem Gambling Severity Index (PGSI) score was associated with particular gambling activities and evaluate the impact of involvement on gambling behavior. Methods A total of 736 treatment-seeking individuals with gambling disorder were assessed at the National Problem Gambling Clinic in London. First, the independent two-sample t-test and the Mann-Whitney test were used to verify if the PGSI score changed significantly according to the gambling activity at a bivariate level. Second, we conducted a cluster analysis and finally, we fitted a linear regression model in order to verify if some variables are useful to predict gambling addiction severity. Results The PGSI score was significantly higher for lower stakes gaming machine gamblers (1% significance level) and for fixed-odds betting terminal (FOBT) gamblers (5% significance level) at a bivariate level. Moreover, such finding was confirmed by cluster and linear regression analyses. Conclusions The results of this study indicated that gambling addiction severity was related to gambling involvement and, for a given level of gambling involvement, gambling addiction severity may vary according to gambling type, with a particularly significant increase for FOBT and gaming machine gambling.

Predictors of medication nonadherence differ among black and white patients with heart failure.

PubMed

Dickson, Victoria Vaughan; Knafl, George J; Riegel, Barbara

2015-08-01

Heart failure (HF) is a global public health problem, and outcomes remain poor, especially among ethnic minority populations. Medication adherence can improve heart failure outcomes but is notoriously low. The purpose of this secondary analysis of data from a prospective cohort comparison study of adults with heart failure was to explore differences in predictors of medication nonadherence by racial group (Black vs. White) in 212 adults with heart failure. Adaptive modeling analytic methods were used to model HF patient medication nonadherence separately for Black (31.7%) and White (68.3%) participants in order to investigate differences between these two racial groups. Of the 63 Black participants, 33.3% had low medication adherence, compared to 27.5% of the 149 White participants. Among Blacks, 16 risk factors were related to adherence in bivariate analyses; four of these (more comorbidities, lower serum sodium, higher systolic blood pressure, and use of fewer activities compensating for forgetfulness) jointly predicted nonadherence. In the multiple risk factor model, the number of risk factors in Black patients ranged from 0 to 4, and 76.2% had at least one risk factor. The estimated odds ratio for medication nonadherence was increased 9.34 times with each additional risk factor. Among White participants, five risk factors were related to adherence in bivariate analyses; one of these (older age) explained the individual effects of the other four. Because Blacks with HF have different and more risk factors than Whites for low medication adherence, interventions are needed that address unique risk factors among Black patients with HF. © 2015 Wiley Periodicals, Inc.

How much do workers' health examinations add to health and safety at the workplace? Occupational preventive usefulness of routine health examinations.

PubMed

Rodríguez-Jareño, Maria Cruz; Molinero, Emilia; de Montserrat, Jaume; Vallès, Antoni; Aymerich, Marta

2015-01-01

Despite no evidence in favour, routine workers' health examinations, mostly pre-employment and periodic, are extensively performed worldwide with important allocation of resources. In Spain they are performed within a theoretical job-specific health surveillance system. Our objective was to ascertain their occupational preventive usefulness from the perspective of occupational health professionals. Cross sectional study. Online survey addressed to all physicians and nurses members of the Catalan Society of Safety and Occupational Medicine (n=539) in 2011. Univariate and bivariate analyses of prevalence and prevalence differences of answers. Response rate 53% (n=285). According to more than 70% of respondents the health surveillance system isn't cost-effective, doesn't meet the goal of early detection of health damage related to work, and doesn't contribute to improve the occupational risk prevention system. Further deficiencies were identified regarding specificity and scientific basis for health examinations, quality of collective health surveillance and referral of suspected cases to mutual insurance companies for diagnosis and treatment. Bivariate analysis showed a significantly more negative opinion for several items amongst physicians (versus nurses) and amongst professionals working in external prevention services (versus internal services). This study raises serious concerns about how health examinations are performed within our workers' health surveillance system, which should be reviewed to ensure the fulfilment of its occupational preventive objective. Our results might encourage other countries with similar practices to assess them in order to assure their fitness for purpose. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

Socioeconomic Status and Health: A New Approach to the Measurement of Bivariate Inequality.

PubMed

Erreygers, Guido; Kessels, Roselinde

2017-06-23

We suggest an alternative way to construct a family of indices of socioeconomic inequality of health. Our indices belong to the broad category of linear indices. In contrast to rank-dependent indices, which are defined in terms of the ranks of the socioeconomic variable and the levels of the health variable, our indices are based on the levels of both the socioeconomic and the health variable. We also indicate how the indices can be modified in order to introduce sensitivity to inequality in the socioeconomic distribution and to inequality in the health distribution. As an empirical illustration, we make a comparative study of the relation between income and well-being in 16 European countries using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 4.

Measuring willingness to pay to improve municipal water in southeast Anatolia, Turkey

NASA Astrophysics Data System (ADS)

Bilgic, Abdulbaki

2010-12-01

Increasing demands for water and quality concerns have highlighted the importance of accounting for household perceptions before local municipalities rehabilitate existing water infrastructures and bring them into compliance. We compared different willingness-to-pay (WTP) estimates using household surveys in the southern Anatolian region of Turkey. Our study is the first of its kind in Turkey. Biases resulting from sample selection and the endogeneity of explanatory variables were corrected. When compared to a univariate probit model, correction of these biases was shown to result in statistically significant findings through moderate reductions in mean WTP.

The optimal dose of dexmedetomidine added to an sufentanil-based analgesic regimen for postoperative pain control in spine surgery

PubMed Central

Dong, Chun-Shan; Lu, Yao; Zhang, Jun; Sun, Peng; Yu, Jun-Ma; Wu, Chao; Lu, Qiang

2016-01-01

Abstract Postoperative spinal patients remain a challenge for provision of postoperative analgesia. Patient-controlled intravenous analgesia (PCIA) is a major method in reducing the severe pain after the surgery in our institution, but some adverse effects prevent the use of adequate dosage opioids. This study was determined using the probit analysis to investigate the optimal dose of dexmedetomidine (DEX) infusion for postoperative analgesia combined with sufentanil (SUF) in spine surgery. The dose of DEX needed to produce satisfactory analgesia conditions following combination of 3.0 μg/kg SUF in PCIA pump, which was diluted to 250 mL with a 4 mL/h as background infusion. Patients were recruited with age 35 to 65 years. The satisfactory criteria of postoperative analgesia were determined with a average satisfaction level of pain control, sedation, self-satisfaction, and adverse effects, among others. The dose of DEX was determined using the modified Dixon's up-and-down method (0.5 μg/kg as a step size). The first patient was test at 3.0 μg/kg DEX. The patient was assessed at 6, 12, 36 hours, and termination of PCIA following the continuous infusion of DEX-SUF mixture in PCIA after surgery. Twenty-five patients were enrolled by predetermined criteria. The optimal dose of DEX required for satisfactory analgesic was 4.33 (SD, 0.38) μg/kg combined with 3.0 μg/kg SUF via a PCIA volume of 250 mL by background infusion of 4 mL/h. Using probit analysis, the ED50 of DEX was 4.12 μg/kg (95% confidence limits 3.74–4.52 μg/kg) for satisfactory postoperative analgesic in spine surgery, the ED95 of DEX was 4.85 μg/kg (95% confidence limits 4.48–7.13 μg/kg). There was no report of somnolence or respiratory depression, relevant bradycardia or hypotension, or over sedation in this study. The optimal dose of DEX was 4.33 (0.38) μg/kg−1 combined with 3.0 μg/kg−1 SUF diluted to 250 mL with a background infusion of 4 mL/h for satisfactory analgesic after spine surgery. From probit analysis, ED50 and ED95 of DEX were 4.12 μg/kg (95% confidence limits 3.74–4.52 μg/kg) and 4.85 μg.kg−1 (95% confidence limits 4.48–7.13 μg/kg), respectively. PMID:27684802

Constructing a bivariate distribution function with given marginals and correlation: application to the galaxy luminosity function

NASA Astrophysics Data System (ADS)

Takeuchi, Tsutomu T.

2010-08-01

We provide an analytic method to construct a bivariate distribution function (DF) with given marginal distributions and correlation coefficient. We introduce a convenient mathematical tool, called a copula, to connect two DFs with any prescribed dependence structure. If the correlation of two variables is weak (Pearson's correlation coefficient |ρ| < 1/3), the Farlie-Gumbel-Morgenstern (FGM) copula provides an intuitive and natural way to construct such a bivariate DF. When the linear correlation is stronger, the FGM copula cannot work anymore. In this case, we propose using a Gaussian copula, which connects two given marginals and is directly related to the linear correlation coefficient between two variables. Using the copulas, we construct the bivariate luminosity function (BLF) and discuss its statistical properties. We focus especially on the far-infrared-far-ulatraviolet (FUV-FIR) BLF, since these two wavelength regions are related to star-formation (SF) activity. Though both the FUV and FIR are related to SF activity, the univariate LFs have a very different functional form: the former is well described by the Schechter function whilst the latter has a much more extended power-law-like luminous end. We construct the FUV-FIR BLFs using the FGM and Gaussian copulas with different strengths of correlation, and examine their statistical properties. We then discuss some further possible applications of the BLF: the problem of a multiband flux-limited sample selection, the construction of the star-formation rate (SFR) function, and the construction of the stellar mass of galaxies (M*)-specific SFR (SFR/M*) relation. The copulas turn out to be a very useful tool to investigate all these issues, especially for including complicated selection effects.

Flood risk analysis for flood control and sediment transportation in sandy regions: A case study in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Guo, Aijun; Chang, Jianxia; Wang, Yimin; Huang, Qiang; Zhou, Shuai

2018-05-01

Traditional flood risk analysis focuses on the probability of flood events exceeding the design flood of downstream hydraulic structures while neglecting the influence of sedimentation in river channels on regional flood control systems. This work advances traditional flood risk analysis by proposing a univariate and copula-based bivariate hydrological risk framework which incorporates both flood control and sediment transport. In developing the framework, the conditional probabilities of different flood events under various extreme precipitation scenarios are estimated by exploiting the copula-based model. Moreover, a Monte Carlo-based algorithm is designed to quantify the sampling uncertainty associated with univariate and bivariate hydrological risk analyses. Two catchments located on the Loess plateau are selected as study regions: the upper catchments of the Xianyang and Huaxian stations (denoted as UCX and UCH, respectively). The univariate and bivariate return periods, risk and reliability in the context of uncertainty for the purposes of flood control and sediment transport are assessed for the study regions. The results indicate that sedimentation triggers higher risks of damaging the safety of local flood control systems compared with the event that AMF exceeds the design flood of downstream hydraulic structures in the UCX and UCH. Moreover, there is considerable sampling uncertainty affecting the univariate and bivariate hydrologic risk evaluation, which greatly challenges measures of future flood mitigation. In addition, results also confirm that the developed framework can estimate conditional probabilities associated with different flood events under various extreme precipitation scenarios aiming for flood control and sediment transport. The proposed hydrological risk framework offers a promising technical reference for flood risk analysis in sandy regions worldwide.

Modeling continuous covariates with a "spike" at zero: Bivariate approaches.

PubMed

Jenkner, Carolin; Lorenz, Eva; Becher, Heiko; Sauerbrei, Willi

2016-07-01

In epidemiology and clinical research, predictors often take value zero for a large amount of observations while the distribution of the remaining observations is continuous. These predictors are called variables with a spike at zero. Examples include smoking or alcohol consumption. Recently, an extension of the fractional polynomial (FP) procedure, a technique for modeling nonlinear relationships, was proposed to deal with such situations. To indicate whether or not a value is zero, a binary variable is added to the model. In a two stage procedure, called FP-spike, the necessity of the binary variable and/or the continuous FP function for the positive part are assessed for a suitable fit. In univariate analyses, the FP-spike procedure usually leads to functional relationships that are easy to interpret. This paper introduces four approaches for dealing with two variables with a spike at zero (SAZ). The methods depend on the bivariate distribution of zero and nonzero values. Bi-Sep is the simplest of the four bivariate approaches. It uses the univariate FP-spike procedure separately for the two SAZ variables. In Bi-D3, Bi-D1, and Bi-Sub, proportions of zeros in both variables are considered simultaneously in the binary indicators. Therefore, these strategies can account for correlated variables. The methods can be used for arbitrary distributions of the covariates. For illustration and comparison of results, data from a case-control study on laryngeal cancer, with smoking and alcohol intake as two SAZ variables, is considered. In addition, a possible extension to three or more SAZ variables is outlined. A combination of log-linear models for the analysis of the correlation in combination with the bivariate approaches is proposed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A tutorial on Bayesian bivariate meta-analysis of mixed binary-continuous outcomes with missing treatment effects.

PubMed

Gajic-Veljanoski, Olga; Cheung, Angela M; Bayoumi, Ahmed M; Tomlinson, George

2016-05-30

Bivariate random-effects meta-analysis (BVMA) is a method of data synthesis that accounts for treatment effects measured on two outcomes. BVMA gives more precise estimates of the population mean and predicted values than two univariate random-effects meta-analyses (UVMAs). BVMA also addresses bias from incomplete reporting of outcomes. A few tutorials have covered technical details of BVMA of categorical or continuous outcomes. Limited guidance is available on how to analyze datasets that include trials with mixed continuous-binary outcomes where treatment effects on one outcome or the other are not reported. Given the advantages of Bayesian BVMA for handling missing outcomes, we present a tutorial for Bayesian BVMA of incompletely reported treatment effects on mixed bivariate outcomes. This step-by-step approach can serve as a model for our intended audience, the methodologist familiar with Bayesian meta-analysis, looking for practical advice on fitting bivariate models. To facilitate application of the proposed methods, we include our WinBUGS code. As an example, we use aggregate-level data from published trials to demonstrate the estimation of the effects of vitamin K and bisphosphonates on two correlated bone outcomes, fracture, and bone mineral density. We present datasets where reporting of the pairs of treatment effects on both outcomes was 'partially' complete (i.e., pairs completely reported in some trials), and we outline steps for modeling the incompletely reported data. To assess what is gained from the additional work required by BVMA, we compare the resulting estimates to those from separate UVMAs. We discuss methodological findings and make four recommendations. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Emergency physicians' attitudes and preferences regarding computed tomography, radiation exposure, and imaging decision support.

PubMed

Griffey, Richard T; Jeffe, Donna B; Bailey, Thomas

2014-07-01

Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians' (EPs') preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. A 42-item, Web-based survey of EPs was developed and used to measure EPs' attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach's alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient's cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients' cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients' cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs' greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP's decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. © 2014 by the Society for Academic Emergency Medicine.

Emergency Physicians’ Attitudes and Preferences Regarding Computed Tomography, Radiation Exposure, and Imaging Decision Support

PubMed Central

Griffey, Richard T.; Jeffe, Donna B.; Bailey, Thomas

2014-01-01

Objectives Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians’ (EPs’) preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. Methods A 42-item, Web-based survey of EPs was developed and used to measure EPs’ attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach’s alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Results Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient’s cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients’ cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients’ cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs’ greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP’s decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Conclusions Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. PMID:25125272

Psychosocial and contextual correlates of opioid overdose risk among drug users in St. Petersburg, Russia.

PubMed

Grau, Lauretta E; Green, Traci C; Torban, Mikhail; Blinnikova, Ksenia; Krupitsky, Evgeny; Ilyuk, Ruslan; Kozlov, Andrei P; Heimer, Robert

2009-07-24

Opioid overdose in Russia is a problem that has grown more severe as heroin abuse expanded over the past decade, yet few studies have explored it in detail. In order to gain a clearer understanding of the situation, 60 drug users, both in and out of drug treatment in St. Petersburg, were interviewed concerning their overdose experience and knowledge about overdose recognition and prevention. Using a semi-structured interview, we sought to identify and describe local attitudes, knowledge and experience (both self-sustained and witnessed) of opioid overdose. Bi-variate and multiple logistic regressions were performed in order to identify the relationship between overdose experience and sociodemographic factors, risk behaviors, and clinical psychiatric measures. We found that having experienced or witnessed an opioid overdose within the previous year was common, overdose knowledge was generally high, but nearly half the participants reported low self-efficacy for effectively intervening in an overdose situation. In bivariate analyses, self-reported family problems (i.e., perceived problematic family interactions) were positively associated with both experiencing (t56 = 2.49; p < 0.05) and with witnessing a greater number of overdoses in the previous year (rhos = 0.31; p < 0.05). Having previously overdosed [Adjusted Risk Ratio (ARR) 1.7, 95% Confidence Interval (CI) 1.1-2.6] and higher SCL-90-R somatization scores (ARR 1.2, 95% CI 0.96 - 1.5) were independently associated in multivariable analyses with self-sustained overdose experience in the past year. Greater perceived likelihood of experiencing a future overdose and concern about medical problems were independently associated with witnessing a higher number of overdoses within the previous year. Over two thirds of the participants expressed interest in receiving training in overdose prevention and response. Opioid overdose experience is very common among drug users in St. Petersburg, Russia, and interest in receiving training for overdose recognition and prevention was high. Future research should target the development of effective overdose recognition and prevention interventions, especially ones that include naloxone distribution and involve drug users' families.

Psychosocial and contextual correlates of opioid overdose risk among drug users in St. Petersburg, Russia

PubMed Central

Grau, Lauretta E; Green, Traci C; Torban, Mikhail; Blinnikova, Ksenia; Krupitsky, Evgeny; Ilyuk, Ruslan; Kozlov, Andrei P; Heimer, Robert

2009-01-01

Background Opioid overdose in Russia is a problem that has grown more severe as heroin abuse expanded over the past decade, yet few studies have explored it in detail. In order to gain a clearer understanding of the situation, 60 drug users, both in and out of drug treatment in St. Petersburg, were interviewed concerning their overdose experience and knowledge about overdose recognition and prevention. Methods Using a semi-structured interview, we sought to identify and describe local attitudes, knowledge and experience (both self-sustained and witnessed) of opioid overdose. Bi-variate and multiple logistic regressions were performed in order to identify the relationship between overdose experience and sociodemographic factors, risk behaviors, and clinical psychiatric measures. Results We found that having experienced or witnessed an opioid overdose within the previous year was common, overdose knowledge was generally high, but nearly half the participants reported low self-efficacy for effectively intervening in an overdose situation. In bivariate analyses, self-reported family problems (i.e., perceived problematic family interactions) were positively associated with both experiencing (t56 = 2.49; p < 0.05) and with witnessing a greater number of overdoses in the previous year (rhos = 0.31; p < 0.05). Having previously overdosed [Adjusted Risk Ratio (ARR) 1.7, 95% Confidence Interval (CI) 1.1–2.6] and higher SCL-90-R somatization scores (ARR 1.2, 95% CI 0.96 – 1.5) were independently associated in multivariable analyses with self-sustained overdose experience in the past year. Greater perceived likelihood of experiencing a future overdose and concern about medical problems were independently associated with witnessing a higher number of overdoses within the previous year. Over two thirds of the participants expressed interest in receiving training in overdose prevention and response. Conclusion Opioid overdose experience is very common among drug users in St. Petersburg, Russia, and interest in receiving training for overdose recognition and prevention was high. Future research should target the development of effective overdose recognition and prevention interventions, especially ones that include naloxone distribution and involve drug users' families. PMID:19630963

[Metabolic syndrome in workers of a second level hospital].

PubMed

Mathiew-Quirós, Alvaro; Salinas-Martínez, Ana María; Hernández-Herrera, Ricardo Jorge; Gallardo-Vela, José Alberto

2014-01-01

People with metabolic syndrome (20-25 % of the world population) are three times more likely to suffer a heart attack or stroke and twice as likely to die from this cause. The objective of this study was to assess the prevalence of metabolic syndrome in workers of a second level hospital. This was a cross-sectional study with 160 healthcare workers in Monterrey, México. Sociodemographic, anthropometric and biochemical data were obtained to assess the prevalence of metabolic syndrome. Bivariate and multiple logistic regression analysis were carried out in order to assess the relationship between metabolic syndrome and sociodemographic and occupational variables. The prevalence of metabolic syndrome among workers was 38.1 %. Nurses were more affected with 32.8 %. Overweight and obesity were prevalent in 78 %. In the logistic regression there was a significant association between metabolic syndrome and not having partner (OR 3.98, 95 % CI [1.54-10.25]) and obesity (OR 4.69, 95 % CI [1.73-12.73]). The prevalence of metabolic syndrome and obesity is alarming. Appropriate and prompt actions must be taken in order to reduce the risk of cardiovascular disease in this population.

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

Spectrum-based estimators of the bivariate Hurst exponent

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav

2014-12-01

We discuss two alternate spectrum-based estimators of the bivariate Hurst exponent in the power-law cross-correlations setting, the cross-periodogram and local X -Whittle estimators, as generalizations of their univariate counterparts. As the spectrum-based estimators are dependent on a part of the spectrum taken into consideration during estimation, a simulation study showing performance of the estimators under varying bandwidth parameter as well as correlation between processes and their specification is provided as well. These estimators are less biased than the already existent averaged periodogram estimator, which, however, has slightly lower variance. The spectrum-based estimators can serve as a good complement to the popular time domain estimators.

Bivariate spline solution of time dependent nonlinear PDE for a population density over irregular domains.

PubMed

Gutierrez, Juan B; Lai, Ming-Jun; Slavov, George

2015-12-01

We study a time dependent partial differential equation (PDE) which arises from classic models in ecology involving logistic growth with Allee effect by introducing a discrete weak solution. Existence, uniqueness and stability of the discrete weak solutions are discussed. We use bivariate splines to approximate the discrete weak solution of the nonlinear PDE. A computational algorithm is designed to solve this PDE. A convergence analysis of the algorithm is presented. We present some simulations of population development over some irregular domains. Finally, we discuss applications in epidemiology and other ecological problems. Copyright © 2015 Elsevier Inc. All rights reserved.

Computational approach to Thornley's problem by bivariate operational calculus

NASA Astrophysics Data System (ADS)

Bazhlekova, E.; Dimovski, I.

2012-10-01

Thornley's problem is an initial-boundary value problem with a nonlocal boundary condition for linear onedimensional reaction-diffusion equation, used as a mathematical model of spiral phyllotaxis in botany. Applying a bivariate operational calculus we find explicit representation of the solution, containing two convolution products of special solutions and the arbitrary initial and boundary functions. We use a non-classical convolution with respect to the space variable, extending in this way the classical Duhamel principle. The special solutions involved are represented in the form of fast convergent series. Numerical examples are considered to show the application of the present technique and to analyze the character of the solution.

A Semiparametric Approach to Simultaneous Covariance Estimation for Bivariate Sparse Longitudinal Data

PubMed Central

Das, Kiranmoy; Daniels, Michael J.

2014-01-01

Summary Estimation of the covariance structure for irregular sparse longitudinal data has been studied by many authors in recent years but typically using fully parametric specifications. In addition, when data are collected from several groups over time, it is known that assuming the same or completely different covariance matrices over groups can lead to loss of efficiency and/or bias. Nonparametric approaches have been proposed for estimating the covariance matrix for regular univariate longitudinal data by sharing information across the groups under study. For the irregular case, with longitudinal measurements that are bivariate or multivariate, modeling becomes more difficult. In this article, to model bivariate sparse longitudinal data from several groups, we propose a flexible covariance structure via a novel matrix stick-breaking process for the residual covariance structure and a Dirichlet process mixture of normals for the random effects. Simulation studies are performed to investigate the effectiveness of the proposed approach over more traditional approaches. We also analyze a subset of Framingham Heart Study data to examine how the blood pressure trajectories and covariance structures differ for the patients from different BMI groups (high, medium and low) at baseline. PMID:24400941

Cost-offsets of prescription drug expenditures: data analysis via a copula-based bivariate dynamic hurdle model.

PubMed

Deb, Partha; Trivedi, Pravin K; Zimmer, David M

2014-10-01

In this paper, we estimate a copula-based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost-offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply the proposed methodology to data from the Medical Expenditure Panel Survey, which have the following features: (i) the observed bivariate outcomes are a mixture of zeros and continuously measured positives; (ii) both the zero and positive outcomes show state dependence and inter-temporal interdependence; and (iii) the zeros and the positives display contemporaneous association. The point mass at zero is accommodated using a hurdle or a two-part approach. The copula-based approach to generating joint distributions is appealing because the contemporaneous association involves asymmetric dependence. The paper studies samples categorized by four health conditions: arthritis, diabetes, heart disease, and mental illness. There is evidence of greater than dollar-for-dollar cost-offsets of expenditures on prescribed drugs for relatively low levels of spending on drugs and less than dollar-for-dollar cost-offsets at higher levels of drug expenditures. Copyright © 2013 John Wiley & Sons, Ltd.

Vector wind and vector wind shear models 0 to 27 km altitude for Cape Kennedy, Florida, and Vandenberg AFB, California

NASA Technical Reports Server (NTRS)

Smith, O. E.

1976-01-01

The techniques are presented to derive several statistical wind models. The techniques are from the properties of the multivariate normal probability function. Assuming that the winds can be considered as bivariate normally distributed, then (1) the wind components and conditional wind components are univariate normally distributed, (2) the wind speed is Rayleigh distributed, (3) the conditional distribution of wind speed given a wind direction is Rayleigh distributed, and (4) the frequency of wind direction can be derived. All of these distributions are derived from the 5-sample parameter of wind for the bivariate normal distribution. By further assuming that the winds at two altitudes are quadravariate normally distributed, then the vector wind shear is bivariate normally distributed and the modulus of the vector wind shear is Rayleigh distributed. The conditional probability of wind component shears given a wind component is normally distributed. Examples of these and other properties of the multivariate normal probability distribution function as applied to Cape Kennedy, Florida, and Vandenberg AFB, California, wind data samples are given. A technique to develop a synthetic vector wind profile model of interest to aerospace vehicle applications is presented.

Nonlinear cancer response at ultralow dose: a 40800-animal ED(001) tumor and biomarker study.

PubMed

Bailey, George S; Reddy, Ashok P; Pereira, Clifford B; Harttig, Ulrich; Baird, William; Spitsbergen, Jan M; Hendricks, Jerry D; Orner, Gayle A; Williams, David E; Swenberg, James A

2009-07-01

Assessment of human cancer risk from animal carcinogen studies is severely limited by inadequate experimental data at environmentally relevant exposures and by procedures requiring modeled extrapolations many orders of magnitude below observable data. We used rainbow trout, an animal model well-suited to ultralow-dose carcinogenesis research, to explore dose-response down to a targeted 10 excess liver tumors per 10000 animals (ED(001)). A total of 40800 trout were fed 0-225 ppm dibenzo[a,l]pyrene (DBP) for 4 weeks, sampled for biomarker analyses, and returned to control diet for 9 months prior to gross and histologic examination. Suspect tumors were confirmed by pathology, and resulting incidences were modeled and compared to the default EPA LED(10) linear extrapolation method. The study provided observed incidence data down to two above-background liver tumors per 10000 animals at the lowest dose (that is, an unmodeled ED(0002) measurement). Among nine statistical models explored, three were determined to fit the liver data well-linear probit, quadratic logit, and Ryzin-Rai. None of these fitted models is compatible with the LED(10) default assumption, and all fell increasingly below the default extrapolation with decreasing DBP dose. Low-dose tumor response was also not predictable from hepatic DBP-DNA adduct biomarkers, which accumulated as a power function of dose (adducts = 100 x DBP(1.31)). Two-order extrapolations below the modeled tumor data predicted DBP doses producing one excess cancer per million individuals (ED(10)(-6)) that were 500-1500-fold higher than that predicted by the five-order LED(10) extrapolation. These results are considered specific to the animal model, carcinogen, and protocol used. They provide the first experimental estimation in any model of the degree of conservatism that may exist for the EPA default linear assumption for a genotoxic carcinogen.

An Analysis of Some Observations of Thermal Comfort in an Equatorial Climate

PubMed Central

Webb, C. G.

1959-01-01

The analysis is introduced by a brief account of the development of work on thermal comfort. The observations, which are fully described in relation to the interior climates which were experienced, were made in Singapore in 1949-50. The climate of Singapore is typical of the equator, being warm, damp and windless; and the annual variation is almost negligible. Buildings are unheated, of an open type, and shaded from the sun and sky. A multiple regression equation has been derived, giving the thermal effect on a number of subjects of variations in the air temperature, the water vapour pressure, and the air velocity within the ranges experienced. The implications of the equation are discussed, and a climatic index is derived from it which is similar in definition to the widely used “effective temperature” scale, but shows a better correlation with thermal sensation. The new index is named the Singapore index. At a further stage the thermal sensation scale is simplified for the purpose of probit analysis. The probit regressions of discomfort due to warmth and cold are separately given in relation to the new index, and are combined to yield a thermal comfort graph from which the optimum is obtained and explored. A comfort chart for the rapid assessment of these humid climates is supplied, and an alternative form of the index equation is given which is more suitable for rapid calculation. It appears desirable in an equatorial climate to attempt to minimize discomfort by allowing to some extent for individual thermal requirements, and the benefits of a suitable climatic spread within a room are described. PMID:13843256

Targeting smooth emergence: the effect site concentration of remifentanil for preventing cough during emergence during propofol-remifentanil anaesthesia for thyroid surgery.

PubMed

Lee, B; Lee, J-R; Na, S

2009-06-01

The administration of short-acting opioids can be a reliable and safe method to prevent coughing during emergence from anaesthesia but the proper dose or effect site concentration of remifentanil for this purpose has not been reported. We therefore investigated the effect site concentration (Ce) of remifentanil for preventing cough during emergence from anaesthesia with propofol-remifentanil target-controlled infusion. Twenty-three ASA I-II grade female patients, aged 23-66 yr undergoing elective thyroidectomy were enrolled in this study. EC(50) and EC(95) of remifentanil for preventing cough were determined using Dixon's up-and-down method and probit analysis. Propofol effect site concentration at extubation, mean arterial pressure, and heart rate (HR) were compared in patients with smooth emergence and without smooth emergence. Three out of 11 patients with remifentanil Ce of 1.5 ng ml(-1) and all seven patients with Ce of 2.0 ng ml(-1) did not cough during emergence; the EC(50) of remifentanil that suppressed coughing was 1.46 ng ml(-1) by Dixon's up-and-down method, and EC(95) was 2.14 ng ml(-1) by probit analysis. Effect site concentration of propofol at awakening was similar in patients with a smooth emergence and those without smooth emergence, but HR and arterial pressure were higher in those who coughed during emergence. Clinically significant hypoventilation was not seen in any patient. We found that the EC(95) of effect site concentration of remifentanil to suppress coughing at emergence from anaesthesia was 2.14 ng ml(-1). Maintaining an established Ce of remifentanil is a reliable method of abolishing cough and thereby targeting smooth emergence from anaesthesia.

Dimensions of antenatal care service and the alacrity of mothers towards institutional delivery in South and South East Asia.

PubMed

Dixit, Priyanka; Khan, Junaid; Dwivedi, Laxmi Kant; Gupta, Amrita

2017-01-01

A number of studies have assessed the effectiveness of antenatal care (ANC) on uptake of institutional delivery care. However, none address the issue of association between the different components of ANC i.e. ANC component which is independent of health care delivery systems (timing and number of ANC visits), ANC components which depends on health care delivery systems (specific ANC procedures that women receive) with institutional delivery. Data for the study has been taken from the DHS conducted in the six selected South and South-East Asian countries during 1998-2013. The two dimensions of ANC are the key predictors. The outcome variable is a binary variable, where zero '0' denotes a home delivery and one '1' denotes an institutional delivery. In addition to probit estimation biprobit estimation method has been used to correct for the possible endogeneity. Analysis suggests that both the factors show a positive effect on institutional delivery but the level of associations are different. Probit estimation for each country suggests that the association is higher for the factor- which depends on health care delivery systems than the other factor. After correction of endogeneity through biprobit estimation we get the true associations for both the dimensions and it confirms that the ANC components which depends on health care delivery systems is more associated with the utilization of institutional delivery than the other factor. The content of care may fulfill the women's need and expectations while visiting for ANC care. The study suggests that the quality of antenatal care must be improved which depends on health care delivery systems to motivates the women to utilize the institutional delivery.

Dimensions of antenatal care service and the alacrity of mothers towards institutional delivery in South and South East Asia

PubMed Central

Dixit, Priyanka; Khan, Junaid; Dwivedi, Laxmi Kant; Gupta, Amrita

2017-01-01

Background A number of studies have assessed the effectiveness of antenatal care (ANC) on uptake of institutional delivery care. However, none address the issue of association between the different components of ANC i.e. ANC component which is independent of health care delivery systems (timing and number of ANC visits), ANC components which depends on health care delivery systems (specific ANC procedures that women receive) with institutional delivery. Methods Data for the study has been taken from the DHS conducted in the six selected South and South-East Asian countries during 1998–2013. The two dimensions of ANC are the key predictors. The outcome variable is a binary variable, where zero '0' denotes a home delivery and one '1' denotes an institutional delivery. In addition to probit estimation biprobit estimation method has been used to correct for the possible endogeneity. Findings Analysis suggests that both the factors show a positive effect on institutional delivery but the level of associations are different. Probit estimation for each country suggests that the association is higher for the factor- which depends on health care delivery systems than the other factor. After correction of endogeneity through biprobit estimation we get the true associations for both the dimensions and it confirms that the ANC components which depends on health care delivery systems is more associated with the utilization of institutional delivery than the other factor. Conclusions The content of care may fulfill the women’s need and expectations while visiting for ANC care. The study suggests that the quality of antenatal care must be improved which depends on health care delivery systems to motivates the women to utilize the institutional delivery. PMID:28742809

Detection of warfare agents in liquid foods using the brine shrimp lethality assay.

PubMed

Lumor, Stephen E; Diez-Gonzalez, Francisco; Labuza, Theodore P

2011-01-01

The brine shrimp lethality assay (BSLA) was used for rapid and non-specific detection of biological and chemical warfare agents at concentrations considerably below that which will cause harm to humans. Warfare agents detected include T-2 toxin, trimethylsilyl cyanide, and commercially available pesticides such as dichlorvos, diazinon, dursban, malathion, and parathion. The assay was performed by introducing 50 μL of milk or orange juice contaminated with each analyte into vials containing 10 freshly hatched brine shrimp nauplii in seawater. This was incubated at 28 °C for 24 h, after which mortality was determined. Mortality was converted to probits and the LC(50) was determined for each analyte by plotting probits of mortality against analyte concentration (log(10)). Our findings were the following: (1) the lethal effects of toxins dissolved in milk were observed, with T-2 toxin being the most lethal and malathion being the least, (2) except for parathion, the dosage (based on LC(50)) of analyte in a cup of milk (200 mL) consumed by a 6-y-old (20 kg) was less than the respective published rat LD(50) values, and (3) the BSLA was only suitable for detecting toxins dissolved in orange juice if incubation time was reduced to 6 h. Our results support the application of the BSLA for routine, rapid, and non-specific prescreening of liquid foods for possible sabotage by an employee or an intentional bioterrorist act. Practical Application: The findings of this study strongly indicate that the brine shrimp lethality assay can be adapted for nonspecific detection of warfare agents or toxins in food at any point during food production and distribution.

Determinants of adaptation choices to climate change by sheep and goat farmers in Northern Ethiopia: the case of Southern and Central Tigray, Ethiopia.

PubMed

Feleke, Fikeremaryam Birara; Berhe, Melaku; Gebru, Getachew; Hoag, Dana

2016-01-01

The livestock sector serves as a foremost source of revenue for rural people, particularly in many developing countries. Among the livestock species, sheep and goats are the main source of livelihood for rural people in Ethiopia; they can quickly multiply, resilient and are easily convertible to cash to meet financial needs of the rural producers. The multiple contributions of sheep and goat and other livestock to rural farmers are however being challenged by climate change and variability. Farmers are responding to the impacts of climate change by adopting different mechanisms, where choices are largely dependent on many factors. This study, therefore, aims to analyze the determinants of choices of adaptation practices to climate change that causes scarcity of feed, heat stress, shortage of water and pasture on sheep and goat production. The study used 318 sample households drawn from potential livestock producing districts representing 3 agro-ecological settings. Data was analyzed using simple descriptive statistical tools, a multivariate probit model and Ordinary Least Squares (OLS). Most of the respondents (98.6 %) noted that climate is changing. Respondents' perception is that climate change is expressed through increased temperature (88 %) and decline in rainfall (73 %) over the last 10 years. The most commonly used adaptation strategy was marketing during forage shock (96.5 %), followed by home feeding (89.6 %). The estimation from the multivariate probit model showed that access to information, farming experience, number of households in one village, distance to main market, income of household, and agro-ecological settings influenced farmers' adaptation choices to climate change. Furthermore, OLS revealed that the adaptation strategies had positive influence on the household income.

Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

PubMed

Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

2016-05-01

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

Texture analysis of apparent diffusion coefficient maps for treatment response assessment in prostate cancer bone metastases-A pilot study.

PubMed

Reischauer, Carolin; Patzwahl, René; Koh, Dow-Mu; Froehlich, Johannes M; Gutzeit, Andreas

2018-04-01

To evaluate whole-lesion volumetric texture analysis of apparent diffusion coefficient (ADC) maps for assessing treatment response in prostate cancer bone metastases. Texture analysis is performed in 12 treatment-naïve patients with 34 metastases before treatment and at one, two, and three months after the initiation of androgen deprivation therapy. Four first-order and 19 second-order statistical texture features are computed on the ADC maps in each lesion at every time point. Repeatability, inter-patient variability, and changes in the feature values under therapy are investigated. Spearman rank's correlation coefficients are calculated across time to demonstrate the relationship between the texture features and the serum prostate specific antigen (PSA) levels. With few exceptions, the texture features exhibited moderate to high precision. At the same time, Friedman's tests revealed that all first-order and second-order statistical texture features changed significantly in response to therapy. Thereby, the majority of texture features showed significant changes in their values at all post-treatment time points relative to baseline. Bivariate analysis detected significant correlations between the great majority of texture features and the serum PSA levels. Thereby, three first-order and six second-order statistical features showed strong correlations with the serum PSA levels across time. The findings in the present work indicate that whole-tumor volumetric texture analysis may be utilized for response assessment in prostate cancer bone metastases. The approach may be used as a complementary measure for treatment monitoring in conjunction with averaged ADC values. Copyright © 2018 Elsevier B.V. All rights reserved.

Impact of human resource management practices on nursing home performance.

PubMed

Rondeau, K V; Wagar, T H

2001-08-01

Management scholars and practitioners alike have become increasingly interested in learning more about the ability of certain 'progressive' or 'high-performance' human resource management (HRM) practices to enhance organizational effectiveness. There is growing evidence to suggest that the contribution of various HRM practices to impact firm performance may be synergistic in effect yet contingent on a number of contextual factors, including workplace climate. A contingency theory perspective suggests that in order to be effective, HMR policies and practices must be consistent with other aspects of the organization, including its environment. This paper reports on empirical findings from research that examines the relationship between HRM practices, workplace climate and perceptions of organizational performance, in a large sample of Canadian nursing homes. Data from 283 nursing homes were collected by means of a mail survey that included questions on HRM practices, programmes, and policies, on human resource aspects of workplace climate, as well as a variety of indicators that include employee, customer/resident and facility measures of organizational performance. Results derived from ordered probit analysis suggest that nursing homes in our sample which had implemented more 'progressive' HRM practices and which reported a workplace climate that strongly values employee participation, empowerment and accountability tended to be perceived to generally perform better on a number of valued organizational outcomes. Nursing homes in our sample that performed best overall were found to be more likely to not only have implemented more of these HRM practices, but also to report having a workplace climate that reflects the seminal value that it places on its human resources. This finding is consistent with the conclusion that simply introducing HRM practices or programmes, in the absence of an appropriately supportive workplace climate, will be insufficient to attain optimal organizational performance.

Comparing the performance of English mental health providers in achieving patient outcomes.

PubMed

Moran, Valerie; Jacobs, Rowena

2015-09-01

Evidence on provider payment systems that incorporate patient outcomes is limited for mental health care. In England, funding for mental health care services is changing to a prospective payment system with a future objective of linking some part of provider payment to outcomes. This research examines performance of mental health providers offering hospital and community services, in order to investigate if some are delivering better outcomes. Outcomes are measured using the Health of the Nation Outcome Scales (HoNOS) - a clinician-rated routine outcome measure (CROM) mandated for national use. We use data from the Mental Health Minimum Data Set (MHMDS) - a dataset on specialist mental health care with national coverage - for the years 2011/12 and 2012/13 with a final estimation sample of 305,960 observations with follow-up HoNOS scores. A hierarchical ordered probit model is used and outcomes are risk adjusted with independent variables reflecting demographic, need, severity and social indicators. A hierarchical linear model is also estimated with the follow-up total HoNOS score as the dependent variable and the baseline total HoNOS score included as a risk-adjuster. Provider performance is captured by a random effect that is quantified using Empirical Bayes methods. We find that worse outcomes are associated with severity and better outcomes with older age and social support. After adjusting outcomes for various risk factors, variations in performance are still evident across providers. This suggests that if the intention to link some element of provider payment to outcomes becomes a reality, some providers may gain financially whilst others may lose. The paper contributes to the limited literature on risk adjustment of outcomes and performance assessment of providers in mental health in the context of prospective activity-based payment systems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Anchoring Vignettes in EQ-5D-5L Questionnaire: Validation of a New Instrument.

PubMed

Azzolina, Danila; Minto, Clara; Boschetto, Stefania; Martinato, Matteo; Bauce, Barbara; Iliceto, Sabino; Gregori, Dario

2017-01-01

Health Related Quality of Life (HRQoL) is an indicator of patient's physical, psychological and social life. HRQoL is influenced by experience, beliefs, perceptions and expectations, and measures subjective perspective of the patient himself. EQ-5D-5L and SF-12 questionnaires are validated instruments useful to measure HRQoL, increasingly administered in electronic formats. The main purpose is to evaluate the feasibility of anchoring vignettes for the EQ-5D-5L questionnaire, with the aim to improve intergroup comparability of responses among different subjects. A comparison with SF-12 questionnaire is carried out. This is a cross-sectional study conducted at the ambulatories of cardiology of the University Hospital of Padova, in Italy. Thirty-eight subjects with a diagnosis of cardiovascular disease or at risk of cardiovascular disease were enrolled. A factorial analysis has been performed to assess the convergent validity of EQ-5D-5L questionnaire compared to Sf-12. Moreover, a compound Hierarchical Ordered Probit (Chopit) model has been estimated to evaluate if the questionnaire form affects the subjective evaluation process in order to compare EQ-5D-5L with and without vignettes. Correlation and factor analysis demonstrate that EQ_5D questionnaire is coherent with SF-12 in paper format. Chopit model estimation shows that questionnaire format does not affect the subjective question interpretation. Moreover, in a parametric model including vignettes, education attainment, disease severity, and gender are predictors of HRQoL status. The EQ-5D including vignettes in electronic format seems to be a valid tool to measure HRQoL as compared to EQ-5D without vignettes in paper format and to SF-12 questionnaire.

Socioeconomic Status and Health: A New Approach to the Measurement of Bivariate Inequality

PubMed Central

Kessels, Roselinde

2017-01-01

We suggest an alternative way to construct a family of indices of socioeconomic inequality of health. Our indices belong to the broad category of linear indices. In contrast to rank-dependent indices, which are defined in terms of the ranks of the socioeconomic variable and the levels of the health variable, our indices are based on the levels of both the socioeconomic and the health variable. We also indicate how the indices can be modified in order to introduce sensitivity to inequality in the socioeconomic distribution and to inequality in the health distribution. As an empirical illustration, we make a comparative study of the relation between income and well-being in 16 European countries using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 4. PMID:28644405

Risk factor assessment to anticipate performance in the National Developmental Screening Test in children from a disadvantaged area.

PubMed

Montes, Alejandro; Pazos, Gustavo

2016-02-01

Identifying children at risk of failing the National Developmental Screening Test by combining prevalences of children suspected of having inapparent developmental disorders (IDDs) and associated risk factors (RFs) would allow to save resources. 1. To estimate the prevalence of children suspected of having IDDs. 2. To identify associated RFs. 3. To assess three methods developed based on observed RFs and propose a pre-screening procedure. The National Developmental Screening Test was administered to 60 randomly selected children aged between 2 and 4 years old from a socioeconomically disadvantaged area from Puerto Madryn. Twenty-four biological and socioenvironmental outcome measures were assessed in order to identify potential RFs using bivariate and multivariate analyses. The likelihood of failing the screening test was estimated as follows: 1. a multivariate logistic regression model was developed; 2. a relationship was established between the number of RFs present in each child and the percentage of children who failed the test; 3. these two methods were combined. The prevalence of children suspected of having IDDs was 55.0% (95% confidence interval: 42.4%-67.6%). Six RFs were initially identified using the bivariate approach. Three of them (maternal education, number of health checkups and Z scores for height-for-age, and maternal age) were included in the logistic regression model, which has a greater explanatory power. The third method included in the assessment showed greater sensitivity and specificity (85% and 79%, respectively). The estimated prevalence of children suspected of having IDDs was four times higher than the national standards. Seven RFs were identified. Combining the analysis of risk factor accumulation and a multivariate model provides a firm basis for developing a sensitive, specific and practical pre-screening procedure for socioeconomically disadvantaged areas. Sociedad Argentina de Pediatría.

Statistical Association Criteria in Forensic Psychiatry–A criminological evaluation of casuistry

PubMed Central

Gheorghiu, V; Buda, O; Popescu, I; Trandafir, MS

2011-01-01

Purpose. Identification of potential shared primary psychoprophylaxis and crime prevention is measured by analyzing the rate of commitments for patients–subjects to forensic examination. Material and method. The statistic trial is a retrospective, document–based study. The statistical lot consists of 770 initial examination reports performed and completed during the whole year 2007, primarily analyzed in order to summarize the data within the National Institute of Forensic Medicine, Bucharest, Romania (INML), with one of the group variables being ‘particularities of the psychiatric patient history’, containing the items ‘forensic onset’, ‘commitments within the last year prior to the examination’ and ‘absence of commitments within the last year prior to the examination’. The method used was the Kendall bivariate correlation. For this study, the authors separately analyze only the two items regarding commitments by other correlation alternatives and by modern, elaborate statistical analyses, i.e. recording of the standard case study variables, Kendall bivariate correlation, cross tabulation, factor analysis and hierarchical cluster analysis. Results. The results are varied, from theoretically presumed clinical nosography (such as schizophrenia or manic depression), to non–presumed (conduct disorders) or unexpected behavioral acts, and therefore difficult to interpret. Conclusions. One took into consideration the features of the batch as well as the results of the previous standard correlation of the whole statistical lot. The authors emphasize the role of medical security measures that are actually applied in the therapeutic management in general and in risk and second offence management in particular, as well as the role of forensic psychiatric examinations in the detection of certain aspects related to the monitoring of mental patients. PMID:21505571

A view on coupled cluster perturbation theory using a bivariational Lagrangian formulation.

PubMed

Kristensen, Kasper; Eriksen, Janus J; Matthews, Devin A; Olsen, Jeppe; Jørgensen, Poul

2016-02-14

We consider two distinct coupled cluster (CC) perturbation series that both expand the difference between the energies of the CCSD (CC with single and double excitations) and CCSDT (CC with single, double, and triple excitations) models in orders of the Møller-Plesset fluctuation potential. We initially introduce the E-CCSD(T-n) series, in which the CCSD amplitude equations are satisfied at the expansion point, and compare it to the recently developed CCSD(T-n) series [J. J. Eriksen et al., J. Chem. Phys. 140, 064108 (2014)], in which not only the CCSD amplitude, but also the CCSD multiplier equations are satisfied at the expansion point. The computational scaling is similar for the two series, and both are term-wise size extensive with a formal convergence towards the CCSDT target energy. However, the two series are different, and the CCSD(T-n) series is found to exhibit a more rapid convergence up through the series, which we trace back to the fact that more information at the expansion point is utilized than for the E-CCSD(T-n) series. The present analysis can be generalized to any perturbation expansion representing the difference between a parent CC model and a higher-level target CC model. In general, we demonstrate that, whenever the parent parameters depend upon the perturbation operator, a perturbation expansion of the CC energy (where only parent amplitudes are used) differs from a perturbation expansion of the CC Lagrangian (where both parent amplitudes and parent multipliers are used). For the latter case, the bivariational Lagrangian formulation becomes more than a convenient mathematical tool, since it facilitates a different and faster convergent perturbation series than the simpler energy-based expansion.

Why are our children wasting: Determinants of wasting among under 5s in Ghana.

PubMed

Darteh, Eugene Kofuor Maafo; Acquah, Evelyn; Darteh, Florie

2017-09-01

Wasting is one of the indicators of malnutrition known to contribute to the deaths occurring from childhood malnutrition. It is the measure of body mass in relation to body length used to explain recent nutritional status. This paper examines the determinants of wasting among under 5s in Ghana. Data were drawn from the 2014 Ghana Demographic and Health Survey children's records file to examine the determinants of wasting among children. A total of 2720 children under 5 years with valid anthropometric data were used. Data on wasting were collected by measuring the weight and height of all children under 5 years of age. Bi-variate and multi-variate statistics are used to examine the determinants of wasting. The bi-variate analysis showed significant differences ( p < 0.001) in the prevalence of wasting among under 5s according to age of the child, region, and wealth status. On the other hand, the multi-variate analysis revealed that the odds of wasting were lower among children aged 24-35 months (Odds ratio (OR) = 0.37; p < 0.001), those from households of the middle wealth quintile (OR = 0.49, p < 0.05) and with health insurance (OR = 0.70; p < 0.10). Programmes and policies aimed at ensuring the survival of children during the first 24 months of life should be strengthened to reduce the risk of wasting among under 5s. Also, efforts should be made by the relevant government agencies and other stakeholders to strengthen the socio-economic status of mothers to enable them to provide adequate nutrition and improve access to health insurance for their children in order to reduce the incidence of wasting among these children.

Corticospinal excitability as a predictor of functional gains at the affected upper limb following robotic training in chronic stroke survivors.

PubMed

Milot, Marie-Hélène; Spencer, Steven J; Chan, Vicky; Allington, James P; Klein, Julius; Chou, Cathy; Pearson-Fuhrhop, Kristin; Bobrow, James E; Reinkensmeyer, David J; Cramer, Steven C

2014-01-01

Robotic training can help improve function of a paretic limb following a stroke, but individuals respond differently to the training. A predictor of functional gains might improve the ability to select those individuals more likely to benefit from robot-based therapy. Studies evaluating predictors of functional improvement after a robotic training are scarce. One study has found that white matter tract integrity predicts functional gains following a robotic training of the hand and wrist. Objective. To determine the predictive ability of behavioral and brain measures in order to improve selection of individuals for robotic training. Twenty subjects with chronic stroke participated in an 8-week course of robotic exoskeletal training for the arm. Before training, a clinical evaluation, functional magnetic resonance imaging (fMRI), diffusion tensor imaging, and transcranial magnetic stimulation (TMS) were each measured as predictors. Final functional gain was defined as change in the Box and Block Test (BBT). Measures significant in bivariate analysis were fed into a multivariate linear regression model. Training was associated with an average gain of 6 ± 5 blocks on the BBT (P < .0001). Bivariate analysis revealed that lower baseline motor-evoked potential (MEP) amplitude on TMS, and lower laterality M1 index on fMRI each significantly correlated with greater BBT change. In the multivariate linear regression analysis, baseline MEP magnitude was the only measure that remained significant. Subjects with lower baseline MEP magnitude benefited the most from robotic training of the affected arm. These subjects might have reserve remaining for the training to boost corticospinal excitability, translating into functional gains. © The Author(s) 2014.

Evaluation of larvicidal activity and brine shrimp toxicity of rhizome extracts of Zingiber zerumbet (L.) Smith.

PubMed

Bücker, Augusto; Falcão-Bücker, Nádia Cristina; Nunez, Cecília Veronica; Pinheiro, Carlos Cleomir de Souza; Tadei, Wanderli Pedro

2013-01-01

In this study, we used dichloromethane (DCM) and methanol (MeOH) extracts of the Zingiber zerumbet rhizome to evaluate brine shrimp lethality and larvicidal activity on Aedes aegypti and Anopheles nuneztovari mosquitoes. Bioassays were performed by exposing third-instar larvae of each mosquito species to the DCM or MeOH extracts. Probit analysis with DCM and MeOH extracts demonstrated efficient larvicidal activity against A. aegypti and A. nuneztovari larvae. The DCM and MeOH extracts showed higher activity against A. nuneztovari larvae than against A. aegypti larvae, suggesting that the extracts have species-specific activity.

The bivariate regression model and its application

NASA Astrophysics Data System (ADS)

Pratikno, B.; Sulistia, L.; Saniyah

2018-03-01

The paper studied a bivariate regression model (BRM) and its application. The maximum power and minimum size are used to choose the eligible tests using non-sample prior information (NSPI). In the simulation study on real data, we used Wilk’s lamda to determine the best model of the BRM. The result showed that the power of the pre-test-test (PTT) on the NSPI is a significant choice of the tests among unrestricted test (UT) and restricted test (RT), and the best model of the BRM is Y (1) = ‑894 + 46X and Y (2) = 78 + 0.2X with significant Wilk’s lamda 0.88 < 0.90 (Wilk’s table).

Modelling world gold prices and USD foreign exchange relationship using multivariate GARCH model

NASA Astrophysics Data System (ADS)

Ping, Pung Yean; Ahmad, Maizah Hura Binti

2014-12-01

World gold price is a popular investment commodity. The series have often been modeled using univariate models. The objective of this paper is to show that there is a co-movement between gold price and USD foreign exchange rate. Using the effect of the USD foreign exchange rate on the gold price, a model that can be used to forecast future gold prices is developed. For this purpose, the current paper proposes a multivariate GARCH (Bivariate GARCH) model. Using daily prices of both series from 01.01.2000 to 05.05.2014, a causal relation between the two series understudied are found and a bivariate GARCH model is produced.

'In general, how do you feel today?'--self-rated health in the context of aging in India.

PubMed

Hirve, Siddhivinayak

2014-01-01

This thesis is centered on self-rated health (SRH) as an outcome measure, as a predictor, and as a marker. The thesis uses primary data from the WHO Study on global AGEing and adult health (SAGE) implemented in India in 2007. The structural equation modeling approach is employed to understand the pathways through which the social environment, disability, disease, and sociodemographic characteristics influence SRH among older adults aged 50 years and above. Cox proportional hazard model is used to explore the role of SRH as a predictor for mortality and the role of disability in modifying this effect. The hierarchical ordered probit modeling approach, which combines information from anchoring vignettes with SRH, was used to address the long overlooked methodological concern of interpersonal incomparability. Finally, multilevel model-based small area estimation techniques were used to demonstrate the use of large national surveys and census information to derive precise SRH prevalence estimates at the district and sub-district level. The thesis advocates the use of such a simple measure to identify vulnerable communities for targeted health interventions, to plan and prioritize resource allocation, and to evaluate health interventions in resource-scarce settings. The thesis provides the basis and impetus to generate and integrate similar and harmonized adult health and aging data platforms within demographic surveillance systems in different regions of India and elsewhere.

[What factors help to explain satisfaction with Primary Health care in Spain?].

PubMed

Arrazola-Vacas, M; de Hevia-Payá, J; Rodríguez-Esteban, L

2015-01-01

To find out the factors that determine satisfaction with public primary health care in Spain. The work has considered a wide group of potential determining factors of that satisfaction, which are organised into 3 blocks of variables: Those related to the perceived quality in the care received, socioeconomic, and those relative to the state of health. The micro data of the Barómetro Sanitario (BS) of 2013, which are representative at a national level, were employed. After a prior first descriptive analysis, 2 multivariate models were estimated: One in which satisfaction is considered as being of a cardinal nature (regression model), and another in which it is contemplated as being of an ordinal nature (ordered probit model). There were practically no differences between the results obtained with one or other of the multivariate models. Not all the variables considered were statistically significant. Of the 3 blocks of variables studied, the one related to the perceived quality in the care received in the health centre exerts the greatest relevance in the explanation of satisfaction. The results obtained show that, by means of the management of the variables related to the perception of quality of care in health centres, public administrators and health professionals may have a highly favourable influence on the levels of satisfaction of primary health care patients. Copyright © 2015 SECA. Published by Elsevier Espana. All rights reserved.

Socio-economic disparities in health system responsiveness in India.

PubMed

Malhotra, Chetna; Do, Young Kyung

2013-03-01

To assess the magnitude of socio-economic disparities in health system responsiveness in India after correcting for potential reporting heterogeneity by socio-economic characteristics (education and wealth). Data from Wave 1 of the Study on Global Ageing and Adult Health (2007-2008) involving six Indian states were used. Seven health system responsiveness domains were considered for a respondent's last visit to an outpatient service in 12 months: prompt attention, dignity, clarity of information, autonomy, confidentiality, choice and quality of basic amenities. Hierarchical ordered probit models (correcting for reporting heterogeneity through anchoring vignettes) were used to assess the association of socio-economic characteristics with the seven responsiveness domains, controlling for age, gender and area of residence. Stratified analysis was also conducted among users of public and private health facilities. Our statistical models accounting for reporting heterogeneity revealed socio-economic disparities in all health system responsiveness domains. Estimates suggested that individuals from the lowest wealth group, for example, were less likely than individuals from the highest wealth group to report 'very good' on the dignity domain by 8% points (10% vs 18%). Stratified analysis showed that such disparities existed among users of both public and private health facilities. Socio-economic disparities exist in health system responsiveness in India, irrespective of the type of health facility used. Policy efforts to monitor and improve these disparities are required at the health system level.

Injury severity analysis in taxi-pedestrian crashes: An application of reconstructed crash data using a vehicle black box.

PubMed

Chung, Younshik

2018-02-01

In-vehicle recording devices have enabled recent changes in methodological paradigms for traffic safety research. Such devices include event data recorders (EDRs), vehicle black boxes (VBBs), and various sensors used in naturalistic driving studies (NDSs). These technologies may help improve the validity of models used to assess impacts on traffic safety. The objective of this study is to analyze the injury severity in taxi-pedestrian crashes using the accurate crash data from VBBs, such as the time-to-collision (TTC), speed, angle, and region of the crash. VBB data from a two-year period (2010-2011) were collected from taxis operating in Incheon, South Korea. An ordered probit model was then applied to analyze the injury severity in crashes. Five variables were found to have a greater effect on injury severity: crash speed, crashes in no-median sections, crashes where the secondary impact object of pedestrians was the crash vehicle, crashes where the third impact object of pedestrians was another moving vehicle, and crashes where the third impact region of pedestrians was their head. However, injuries were less severe in crashes where the first impact region on the pedestrian was their leg, crashes with the car moving in a straight line, and crashes involving junior high school students. Copyright © 2017 Elsevier Ltd. All rights reserved.

The effect of age and gender on motor vehicle driver injury severity at highway-rail grade crossings in the United States.

PubMed

Hao, Wei; Kamga, Camille; Daniel, Janice

2015-12-01

Based on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive database of highway-rail grade crossing accidents in the United States from 2002 to 2011, estimation results showed that there were substantial differences across age/gender groups for driver's injury severity. The study applied an ordered probit model to explore the determinants of driver injury severity for motor vehicle drivers at highway-rail grade crossings. The analysis found that there are important behavioral and physical differences between male and female drivers given a highway-rail grade crossing accident happened. Older drivers have higher fatality probabilities when driving in open space under passive control especially during bad weather condition. Younger male drivers are found to be more likely to have severe injuries at rush hour with high vehicle speed passing unpaved highway-rail grade crossings under passive control. Synthesizing these results led to the conclusion that the primary problem with young is risk-taking and lack of vehicle handling skills. The strength of older drivers lies in their aversion to risk, but physical degradation issues which result in longer reaction/perception times and degradation in vision and hearing often counterbalance this attribute. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

The effect of physician supply on health status: Canadian evidence.

PubMed

Piérard, Emmanuelle

2014-10-01

We estimate the relationship between per capita supply of physicians, both general practitioners and specialists, and health status of Canadians. We use data from the Canadian National Population Health Survey and the Canadian Institute for Health Information. Two measures of quality of life, self-assessed health status and the Health Utility Index, are explored. Random effects ordered probits are used to model self-assessed health status, and quantile regressions are used for the Health Utility Index. A higher supply of general practitioners is correlated with better health outcomes as measured by both measures of health status, albeit for different age groups, and it is correlated with a higher HUI for some individuals who report having a chronic condition. A higher supply of specialists is correlated with worse health outcomes for the HUI for some individuals. It is possible that a higher supply of general practitioners increases the likelihood of diagnosing and treating health conditions in a timely manner and that this in turn affects health status. Specialists, due to the nature of their expertise could affect negatively health, both through the use of riskier procedures and due to their clientele being in relatively worse health. Based on our findings, we therefore would recommend maintaining a robust supply and distribution of GPs across Canada. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Truck crash severity in New York city: An investigation of the spatial and the time of day effects.

PubMed

Zou, Wei; Wang, Xiaokun; Zhang, Dapeng

2017-02-01

This paper investigates the differences between single-vehicle and multi-vehicle truck crashes in New York City. The random parameter models take into account the time of day effect, the heterogeneous truck weight effect and other influencing factors such as crash characteristics, driver and vehicle characteristics, built environment factors and traffic volume attributes. Based on the results from the co-location quotient analysis, a spatial generalized ordered probit model is further developed to investigate the potential spatial dependency among single-vehicle truck crashes. The sample is drawn from the state maintained incident data, the publicly available Smart Location Data, and the BEST Practices Model (BPM) data from 2008 to 2012. The result shows that there exists a substantial difference between factors influencing single-vehicle and multi-vehicle truck crash severity. It also suggests that heterogeneity does exist in the truck weight, and it behaves differently in single-vehicle and multi-vehicle truck crashes. Furthermore, individual truck crashes are proved to be spatially dependent events for both single and multi-vehicle crashes. Last but not least, significant time of day effects were found for PM and night time slots, crashes that occurred in the afternoons and at nights were less severe in single-vehicle crashes, but more severe in multi-vehicle crashes. Copyright © 2016. Published by Elsevier Ltd.

Crime and subjective well-being in the countries of the former Soviet Union.

PubMed

Stickley, Andrew; Koyanagi, Ai; Roberts, Bayard; Goryakin, Yevgeniy; McKee, Martin

2015-10-03

Criminal victimisation and subjective well-being have both been linked to health outcomes, although as yet, comparatively little is known about the relationship between these two phenomena. In this study we used data from nine countries of the former Soviet Union (fSU) to examine the association between different types of crime and subjective well-being. Data were obtained from 18,000 individuals aged 18 and above collected during the Health in Times of Transition (HITT) survey in 2010/11 in Armenia, Azerbaijan, Belarus, Georgia, Moldova, Kazakhstan, Kyrgyzstan, Russia and Ukraine. Information was obtained on respondents' experience of crime (violence and theft) and self-reported affective (happiness) and cognitive (life satisfaction) well-being. Ordered probit and ordinary least squares (OLS) regression analyses were undertaken to examine the associations between these variables. In pooled country analyses, experiencing violence was associated with significantly lower happiness and life satisfaction. Theft victimisation was associated with significantly reduced life satisfaction but not happiness. Among the individual countries, there was a more pronounced association between violent victimisation and reduced happiness in Kazakhstan and Moldova. The finding that criminal victimisation is linked to lower levels of subjective well-being highlights the importance of reducing crime in the fSU, and also of having effective support services in place for victims of crime to reduce its detrimental effects on health and well-being.

Should I Text or Call Here? A Situation-Based Analysis of Drivers' Perceived Likelihood of Engaging in Mobile Phone Multitasking.

PubMed

Oviedo-Trespalacios, Oscar; Haque, Md Mazharul; King, Mark; Washington, Simon

2018-05-29

This study investigated how situational characteristics typically encountered in the transport system influence drivers' perceived likelihood of engaging in mobile phone multitasking. The impacts of mobile phone tasks, perceived environmental complexity/risk, and drivers' individual differences were evaluated as relevant individual predictors within the behavioral adaptation framework. An innovative questionnaire, which includes randomized textual and visual scenarios, was administered to collect data from a sample of 447 drivers in South East Queensland-Australia (66% females; n = 296). The likelihood of engaging in a mobile phone task across various scenarios was modeled by a random parameters ordered probit model. Results indicated that drivers who are female, are frequent users of phones for texting/answering calls, have less favorable attitudes towards safety, and are highly disinhibited were more likely to report stronger intentions of engaging in mobile phone multitasking. However, more years with a valid driving license, self-efficacy toward self-regulation in demanding traffic conditions and police enforcement, texting tasks, and demanding traffic conditions were negatively related to self-reported likelihood of mobile phone multitasking. The unobserved heterogeneity warned of riskier groups among female drivers and participants who need a lot of convincing to believe that multitasking while driving is dangerous. This research concludes that behavioral adaptation theory is a robust framework explaining self-regulation of distracted drivers. © 2018 Society for Risk Analysis.

Symmetric co-movement between Malaysia and Japan stock markets

NASA Astrophysics Data System (ADS)

Razak, Ruzanna Ab; Ismail, Noriszura

2017-04-01

The copula approach is a flexible tool known to capture linear, nonlinear, symmetric and asymmetric dependence between two or more random variables. It is often used as a co-movement measure between stock market returns. The information obtained from copulas such as the level of association of financial market during normal and bullish and bearish markets phases are useful for investment strategies and risk management. However, the study of co-movement between Malaysia and Japan markets are limited, especially using copulas. Hence, we aim to investigate the dependence structure between Malaysia and Japan capital markets for the period spanning from 2000 to 2012. In this study, we showed that the bivariate normal distribution is not suitable as the bivariate distribution or to present the dependence between Malaysia and Japan markets. Instead, Gaussian or normal copula was found a good fit to represent the dependence. From our findings, it can be concluded that simple distribution fitting such as bivariate normal distribution does not suit financial time series data, whose characteristics are often leptokurtic. The nature of the data is treated by ARMA-GARCH with heavy tail distributions and these can be associated with copula functions. Regarding the dependence structure between Malaysia and Japan markets, the findings suggest that both markets co-move concurrently during normal periods.

Bivariate mass-size relation as a function of morphology as determined by Galaxy Zoo 2 crowdsourced visual classifications

NASA Astrophysics Data System (ADS)

Beck, Melanie; Scarlata, Claudia; Fortson, Lucy; Willett, Kyle; Galloway, Melanie

2016-01-01

It is well known that the mass-size distribution evolves as a function of cosmic time and that this evolution is different between passive and star-forming galaxy populations. However, the devil is in the details and the precise evolution is still a matter of debate since this requires careful comparison between similar galaxy populations over cosmic time while simultaneously taking into account changes in image resolution, rest-frame wavelength, and surface brightness dimming in addition to properly selecting representative morphological samples.Here we present the first step in an ambitious undertaking to calculate the bivariate mass-size distribution as a function of time and morphology. We begin with a large sample (~3 x 105) of SDSS galaxies at z ~ 0.1. Morphologies for this sample have been determined by Galaxy Zoo crowdsourced visual classifications and we split the sample not only by disk- and bulge-dominated galaxies but also in finer morphology bins such as bulge strength. Bivariate distribution functions are the only way to properly account for biases and selection effects. In particular, we quantify the mass-size distribution with a version of the parametric Maximum Likelihood estimator which has been modified to account for measurement errors as well as upper limits on galaxy sizes.

Dissecting the Complexities of the Relationship Between Police Officer-Civilian Race/Ethnicity Dyads and Less-Than-Lethal Use of Force.

PubMed

Jetelina, Katelyn K; Jennings, Wesley G; Bishopp, Stephen A; Piquero, Alex R; Reingle Gonzalez, Jennifer M

2017-07-01

To examine how sublethal use-of-force patterns vary across officer-civilian race/ethnicity while accounting for officer-, civilian-, and situational-level factors. We extracted cross-sectional data from 5630 use-of-force reports from the Dallas Police Department in 2014 and 2015. We categorized each officer-civilian interaction into race/ethnicity dyads. We used multilevel, mixed logistic regression models to evaluate the relationship between race/ethnicity dyads and the types of use of force. Forty-eight percent of use-of-force interactions occurred between a White officer and a non-White civilian (White-non-White). In bivariate models, the odds of hard-empty hand control and intermediate weapon use were significantly higher among White-Black dyads compared with White-White dyads. The bivariate odds of intermediate weapon use were also significantly higher among Black-Black, Hispanic-White, Black-Hispanic, and Hispanic-Black dyads compared with White-White dyads. However, after we controlled for individual and situational factors, the relationship between race/ethnicity dyad and hard-empty hand control was no longer significant. Although we observed significant bivariate relationships between race/ethnicity dyads and use of force, these relationships largely dissipated after we controlled for other factors.

Recurrent major depression and right hippocampal volume: A bivariate linkage and association study.

PubMed

Mathias, Samuel R; Knowles, Emma E M; Kent, Jack W; McKay, D Reese; Curran, Joanne E; de Almeida, Marcio A A; Dyer, Thomas D; Göring, Harald H H; Olvera, Rene L; Duggirala, Ravi; Fox, Peter T; Almasy, Laura; Blangero, John; Glahn, David C

2016-01-01

Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk. © 2015 Wiley Periodicals, Inc.

Operator identities involving the bivariate Rogers-Szegö polynomials and their applications to the multiple q-series identities

NASA Astrophysics Data System (ADS)

Zhang, Zhizheng; Wang, Tianze

2008-07-01

In this paper, we first give several operator identities involving the bivariate Rogers-Szegö polynomials. By applying the technique of parameter augmentation to the multiple q-binomial theorems given by Milne [S.C. Milne, Balanced summation theorems for U(n) basic hypergeometric series, AdvE Math. 131 (1997) 93-187], we obtain several new multiple q-series identities involving the bivariate Rogers-Szegö polynomials. These include multiple extensions of Mehler's formula and Rogers's formula. Our U(n+1) generalizations are quite natural as they are also a direct and immediate consequence of their (often classical) known one-variable cases and Milne's fundamental theorem for An or U(n+1) basic hypergeometric series in Theorem 1E49 of [S.C. Milne, An elementary proof of the Macdonald identities for , Adv. Math. 57 (1985) 34-70], as rewritten in Lemma 7.3 on p. 163 of [S.C. Milne, Balanced summation theorems for U(n) basic hypergeometric series, Adv. Math. 131 (1997) 93-187] or Corollary 4.4 on pp. 768-769 of [S.C. Milne, M. Schlosser, A new An extension of Ramanujan's summation with applications to multilateral An series, Rocky Mountain J. Math. 32 (2002) 759-792].

An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ

NASA Astrophysics Data System (ADS)

Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin

2013-04-01

The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.

Bivariate Heritability of Total and Regional Brain Volumes: the Framingham Study

PubMed Central

DeStefano, Anita L.; Seshadri, Sudha; Beiser, Alexa; Atwood, Larry D.; Massaro, Joe M.; Au, Rhoda; Wolf, Philip A.; DeCarli, Charles

2009-01-01

Heritability and genetic and environmental correlations of total and regional brain volumes were estimated from a large, generally healthy, community-based sample, to determine if there are common elements to the genetic influence of brain volumes and white matter hyperintensity volume. There were 1538 Framingham Heart Study participants with brain volume measures from quantitative magnetic resonance imaging (MRI) who were free of stroke and other neurological disorders that might influence brain volumes and who were members of families with at least two Framingham Heart Study participants. Heritability was estimated using variance component methodology and adjusting for the components of the Framingham stroke risk profile. Genetic and environmental correlations between traits were obtained from bivariate analysis. Heritability estimates ranging from 0.46 to 0.60, were observed for total brain, white matter hyperintensity, hippocampal, temporal lobe, and lateral ventricular volumes. Moderate, yet significant, heritability was observed for the other measures. Bivariate analyses demonstrated that relationships between brain volume measures, except for white matter hyperintensity, reflected both moderate to strong shared genetic and shared environmental influences. This study confirms strong genetic effects on brain and white matter hyperintensity volumes. These data extend current knowledge by showing that these two different types of MRI measures do not share underlying genetic or environmental influences. PMID:19812462

Random matrix theory for transition strengths: Applications and open questions

NASA Astrophysics Data System (ADS)

Kota, V. K. B.

2017-12-01

Embedded random matrix ensembles are generic models for describing statistical properties of finite isolated interacting quantum many-particle systems. A finite quantum system, induced by a transition operator, makes transitions from its states to the states of the same system or to those of another system. Examples are electromagnetic transitions (then the initial and final systems are same), nuclear beta and double beta decay (then the initial and final systems are different) and so on. Using embedded ensembles (EE), there are efforts to derive a good statistical theory for transition strengths. With m fermions (or bosons) in N mean-field single particle levels and interacting via two-body forces, we have with GOE embedding, the so called EGOE(1+2). Now, the transition strength density (transition strength multiplied by the density of states at the initial and final energies) is a convolution of the density generated by the mean-field one-body part with a bivariate spreading function due to the two-body interaction. Using the embedding U(N) algebra, it is established, for a variety of transition operators, that the spreading function, for sufficiently strong interactions, is close to a bivariate Gaussian. Also, as the interaction strength increases, the spreading function exhibits a transition from bivariate Breit-Wigner to bivariate Gaussian form. In appropriate limits, this EE theory reduces to the polynomial theory of Draayer, French and Wong on one hand and to the theory due to Flambaum and Izrailev for one-body transition operators on the other. Using spin-cutoff factors for projecting angular momentum, the theory is applied to nuclear matrix elements for neutrinoless double beta decay (NDBD). In this paper we will describe: (i) various developments in the EE theory for transition strengths; (ii) results for nuclear matrix elements for 130Te and 136Xe NDBD; (iii) important open questions in the current form of the EE theory.

Bioelectrical impedance vector distribution in the first year of life.

PubMed

Savino, Francesco; Grasso, Giulia; Cresi, Francesco; Oggero, Roberto; Silvestro, Leandra

2003-06-01

We assessed the bioelectrical impedance vector distribution in a sample of healthy infants in the first year of life, which is not available in literature. The study was conducted as a cross-sectional study in 153 healthy Caucasian infants (90 male and 63 female) younger than 1 y, born at full term, adequate for gestational age, free from chronic diseases or growth problems, and not feverish. Z scores for weight, length, cranial circumference, and body mass index for the study population were within the range of +/-1.5 standard deviations according to the Euro-Growth Study references. Concurrent anthropometrics (weight, length, and cranial circumference), body mass index, and bioelectrical impedance (resistance and reactance) measurements were made by the same operator. Whole-body (hand to foot) tetrapolar measurements were performed with a single-frequency (50 kHz), phase-sensitive impedance analyzer. The study population was subdivided into three classes of age for statistical analysis: 0 to 3.99 mo, 4 to 7.99 mo, and 8 to 11.99 mo. Using the bivariate normal distribution of resistance and reactance components standardized by the infant's length, the bivariate 95% confidence limits for the mean impedance vector separated by sex and age groups were calculated and plotted. Further, the bivariate 95%, 75%, and 50% tolerance intervals for individual vector measurements in the first year of life were plotted. Resistance and reactance values often fluctuated during the first year of life, particularly as raw measurements (without normalization by subject's length). However, 95% confidence ellipses of mean vectors from the three age groups overlapped each other, as did confidence ellipses by sex for each age class, indicating no significant vector migration during the first year of life. We obtained an estimate of mean impedance vector in a sample of healthy infants in the first year of life and calculated the bivariate values for an individual vector (95%, 75%, and 50% tolerance ellipses).

[Bioimpedance vector analysis for body composition in Mexican population].

PubMed

Espinosa-Cuevas, Maria de los Angeles; Rivas-Rodríguez, Lucía; González-Medina, Enna Cristal; Atilano-Carsi, Ximena; Miranda-Alatriste, Paola; Correa-Rotter, Ricardo

2007-01-01

To construct bivariate tolerance ellipses from impedance values normalized for height, which can be used in Mexican population for the assessment of body composition and compare them with others made in different populations. Body composition was assessed by bioelectrical impedance analysis (BIA) in 439 subjects (204 men and 235 women), 18 to 82 years old, with a BMI between 18-31, using an impedanciometer Quadscan 4000. Resistance, reactance and phase angle were used to calculate bioelectrical impedance vectors and construct bivariate tolerance ellipses. Mean age in men was 47.1 +/- 16 years and 42.4 +/- 13 for women, mean weight (73.4 + 9 vs. 60.1 + 8 kg) and height (1.68 vs. 1.55 m) were significant greater in men than in women (p < 0.002). Women in comparison with men, had greater values of impedance (622.96 +/- 66.16 S2 vs. 523.59 +/- 56.56 D) and resistance (618.96 +/- 66.10 Q 61.97 vs. 521.73 +/- 61.97 2), as well as of resistance and reactance standardized by height (398.24 +/-46.30 S2/m vs. 308.66 +/- 38.44) (44.32 +/- 7.14 i/m vs. 39.75 +/-6.29) respectively, with a significant difference in all of them (p < 0.0001). Similarly, the reactance was greater in females, nevertheless this difference did not reach statistical significance (68.96 +/- 11.17 vs. 67.18 +/- 10.3; p = 0.0861). The phase angle was greater in men than in women, with a statistically significant difference (7.330 +/- 0.88 vs. 6.360 +/- 0.97; p < 0.0001). Bivariate tolerance ellipses (50%, 75% and 95%) derived from Mexican subjects showed a significant upward deviation (p < 0.05) from previously published references from Mexican American and Italian populations. New ellipses of tolerance were therefore constructed for the Mexican population. Bioimpedance vectors in Mexican subjects are significantly different from the existing ones, supporting the need of population specific bivariate tolerance ellipses for the evaluation of body composition.

Assessing the genetic overlap between BMI and cognitive function

PubMed Central

Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J

2016-01-01

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function. PMID:26857597

Basic cardiovascular variability signals: mutual directed interactions explored in the information domain.

PubMed

Javorka, Michal; Krohova, Jana; Czippelova, Barbora; Turianikova, Zuzana; Lazarova, Zuzana; Javorka, Kamil; Faes, Luca

2017-05-01

The study of short-term cardiovascular interactions is classically performed through the bivariate analysis of the interactions between the beat-to-beat variability of heart period (RR interval from the ECG) and systolic blood pressure (SBP). Recent progress in the development of multivariate time series analysis methods is making it possible to explore how directed interactions between two signals change in the context of networks including other coupled signals. Exploiting these advances, the present study aims at assessing directional cardiovascular interactions among the basic variability signals of RR, SBP and diastolic blood pressure (DBP), using an approach which allows direct comparison between bivariate and multivariate coupling measures. To this end, we compute information-theoretic measures of the strength and delay of causal interactions between RR, SBP and DBP using both bivariate and trivariate (conditioned) formulations in a group of healthy subjects in a resting state and during stress conditions induced by head-up tilt (HUT) and mental arithmetics (MA). We find that bivariate measures better quantify the overall (direct  +  indirect) information transferred between variables, while trivariate measures better reflect the existence and delay of directed interactions. The main physiological results are: (i) the detection during supine rest of strong interactions along the pathway RR  →  DBP  →  SBP, reflecting marked Windkessel and/or Frank-Starling effects; (ii) the finding of relatively weak baroreflex effects SBP  →  RR at rest; (iii) the invariance of cardiovascular interactions during MA, and the emergence of stronger and faster SBP  →  RR interactions, as well as of weaker RR  →  DBP interactions, during HUT. These findings support the importance of investigating cardiovascular interactions from a network perspective, and suggest the usefulness of directed information measures to assess physiological mechanisms and track their changes across different physiological states.