Modeling Employer Self-Insurance Decisions after the Affordable Care Act

PubMed Central

Cordova, Amado; Eibner, Christine; Vardavas, Raffaele; Broyles, James; Girosi, Federico

2013-01-01

Objective To present a microsimulation model that addresses the methodological challenge of estimating the firm decision to self-insure. Methodology The model considers the risk that the firm bears when self-insuring and the opportunity to mitigate that risk by purchasing stop-loss insurance. The model makes use of a structural, utility maximization framework to account for numerous aspects of the firm decision, and a multinomial probit to reproduce the elasticity of the firm's demand for health insurance. Findings and Conclusions Our simulations provide three important conclusions. First, they project significant increases in self-insurance rates among small firms--presumably induced by the desire to avoid ACA's rate-banding and risk adjustment regulations—only if generous stop-loss policies become widely available. Second, they show that this increase would be due to this hypothetical adoption of widespread, generous reinsurance by the market and not by passage of the ACA. Third, even with a substantial increase of self-insurance rates among small firms, they project negligible adverse selection in the exchanges, as indicated by our finding that the increase in exchange premium is less than 0.5% when assuming very generous stop-loss policies after implementation of the ACA. PMID:23346976

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

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.

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

Mind the information gap: fertility rate and use of cesarean delivery and tocolytic hospitalizations in Taiwan

PubMed Central

2011-01-01

Background Physician-induced demand (PID) is an important theory to test given the longstanding controversy surrounding it. Empirical health economists have been challenged to find natural experiments to test the theory because PID is tantamount to strong income effects. The data requirements are both a strong exogenous change in income and two types of treatment that are substitutes but have different net revenues. The theory implies that an exogenous fall in income would lead physicians to recoup their income by substituting a more expensive treatment for a less expensive treatment. This study takes advantages of the dramatic decline in the Taiwanese fertility rate to examine whether an exogenous and negative income shock to obstetricians and gynecologists (ob/gyns) affected the use of c-sections, which has a higher reimbursement rate than vaginal delivery under Taiwan's National Health Insurance system during the study period, and tocolytic hospitalizations. Methods The primary data were obtained from the 1996 to 2004 National Health Insurance Research Database in Taiwan. We hypothesized that a negative income shock to ob/gyns would cause them to provide more c-sections and tocolytic hospitalizations to less medically-informed pregnant women. Multinomial probit and probit models were estimated and the marginal effects of the interaction term were conducted to estimate the impacts of ob/gyn to birth ratio and the information gap. Results Our results showed that a decline in fertility did not lead ob/gyns to supply more c-sections to less medically-informed pregnant women, and that during fertility decline ob/gyns may supply more tocolytic hospitalizations to compensate their income loss, regardless of pregnant women's access to health information. Conclusion The exogenous decline in the Taiwanese fertility rate and the use of detailed medical information and demographic attributes of pregnant women allowed us to avoid the endogeneity problem that threatened the validity of prior research. They also provide more accurate estimates of PID. JEL Classification: I10, I19, C23, C25 PMID:22828182

Explaining the demand for pharmaceuticals in Spain: are there differences in drug consumption between foreigners and the Spanish population?

PubMed

Jiménez-Rubio, Dolores; Hernández-Quevedo, Cristina

2010-10-01

The aim of this study is to examine the factors driving the demand for drugs in Spain, focusing on the existence of disparities in pharmaceutical consumption between the Spanish and the foreign population. Our analysis is based on a multilevel multinomial probit model that compares three consumption options (no consumption, prescribed consumption and self-medicated consumption) on the five most consumed drugs in Spain. Data is taken from the adult sample of the 2006 Spanish National Health Survey, including 29,478 individuals over 15 years old. Overall, the findings show a lower consumption of medicines by some immigrants categories relative to Spaniards. In addition, the results indicate that the consumption of medicines is mainly related to variables associated to the specific cost sharing structure in Spain, such as health limitations and retirement status. Other variables found to explain the demand for drugs were: private health insurance, age, sex, alcohol and cigarette consumption and drug class. Further understanding of the reasons for the observed differences in drug consumption on the basis of country of birth would allow the health system to design more effective health policies aimed at ensuring equality of access to health resources to all population groups. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

The Interaction between HIV and Intestinal Helminth Parasites Coinfection with Nutrition among Adults in KwaZulu-Natal, South Africa

PubMed Central

Mabaso, M.; Mamba, T.; Napier, C. E.; Mkhize-Kwitshana, Z. L.

2017-01-01

In South Africa few studies have examined the effects of the overlap of HIV and helminth infections on nutritional status. This cross-sectional study investigated the interaction between HIV and intestinal helminths coinfection with nutritional status among KwaZulu-Natal adults. Participants were recruited from a comprehensive primary health care clinic and stratified based on their HIV, stool parasitology, IgE, and IgG4 results into four groups: the uninfected, HIV infected, helminth infected, and HIV-helminth coinfected groups. The nutritional status was assessed using body mass index, 24-hour food recall, micro-, and macronutrient biochemical markers. Univariate and multivariate multinomial probit regression models were used to assess nutritional factors associated with singly and dually infected groups using the uninfected group as a reference category. Biochemically, the HIV-helminth coinfected group was associated with a significantly higher total protein, higher percentage of transferrin saturation, and significantly lower ferritin. There was no significant association between single or dual infections with HIV and helminths with micro- and macronutrient deficiency; however general obesity and low micronutrient intake patterns, which may indicate a general predisposition to micronutrient and protein-energy deficiency, were observed and may need further investigations. PMID:28421202

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.

Formal and informal care for disabled elderly living in the community: an appraisal of French care composition and costs.

PubMed

Paraponaris, Alain; Davin, Bérengère; Verger, Pierre

2012-06-01

Choices between formal and informal care for disabled elderly people living at home are a key component of the long-term care provision issues faced by an ageing population. This paper aims to identify factors associated with the type of care (informal, formal, mixed or no care at all) received by the French disabled elderly and to assess the care's relative costs. This paper uses data from a French survey on disability; the 3,500 respondents of interest lived at home, were aged 60 and over, had severe disability and needed help with activities of daily living. We use a multinomial probit model to determine factors associated with type of care. We also assess the cost of care with the help of the proxy good method. One-third of disabled elderly people receive no care. Among those who are helped, 55% receive informal, 25% formal, and 20% mixed care. Low socioeconomic status increases difficulties in accessing formal care. The estimated economic value of informal care is 6.6 billion euro [95% CI = 5.9-7.2] and represents about two-thirds of the total cost of care. Public policies should pay more attention to inequalities in access to community care. They also should better support informal care, through respite care or workplace accommodations (working hours rescheduling or reduction for instance) not detrimental for the career of working caregivers.

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

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.

Using Heteroskedastic Ordered Probit Models to Recover Moments of Continuous Test Score Distributions from Coarsened Data

ERIC Educational Resources Information Center

Reardon, Sean F.; Shear, Benjamin R.; Castellano, Katherine E.; Ho, Andrew D.

2017-01-01

Test score distributions of schools or demographic groups are often summarized by frequencies of students scoring in a small number of ordered proficiency categories. We show that heteroskedastic ordered probit (HETOP) models can be used to estimate means and standard deviations of multiple groups' test score distributions from such data. Because…

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...

Factors associated with small-scale agricultural machinery adoption in Bangladesh: Census findings.

PubMed

Mottaleb, Khondoker Abdul; Krupnik, Timothy J; Erenstein, Olaf

2016-08-01

There is strong advocacy for agricultural machinery appropriate for smallholder farmers in South Asia. Such 'scale-appropriate' machinery can increase returns to land and labour, although the still substantial capital investment required can preclude smallholder ownership. Increasing machinery demand has resulted in relatively well-developed markets for rental services for tillage, irrigation, and post-harvest operations. Many smallholders thereby access agricultural machinery that may have otherwise been cost prohibitive to purchase through fee-for-service arrangements, though opportunity for expansion remains. To more effectively facilitate the development and investment in scale-appropriate machinery, there is a need to better understand the factors associated with agricultural machinery purchases and service provision. This paper first reviews Bangladesh's historical policy environment that facilitated the development of agricultural machinery markets. It then uses recent Bangladesh census data from 814,058 farm households to identify variables associated with the adoption of the most common smallholder agricultural machinery - irrigation pumps, threshers, and power tillers (mainly driven by two-wheel tractors). Multinomial probit model results indicate that machinery ownership is positively associated with household assets, credit availability, electrification, and road density. These findings suggest that donors and policy makers should focus not only on short-term projects to boost machinery adoption. Rather, sustained emphasis on improving physical and civil infrastructure and services, as well as assuring credit availability, is also necessary to create an enabling environment in which the adoption of scale-appropriate farm machinery is most likely.

CLUSTERING SOUTH AFRICAN HOUSEHOLDS BASED ON THEIR ASSET STATUS USING LATENT VARIABLE MODELS

PubMed Central

McParland, Damien; Gormley, Isobel Claire; McCormick, Tyler H.; Clark, Samuel J.; Kabudula, Chodziwadziwa Whiteson; Collinson, Mark A.

2014-01-01

The Agincourt Health and Demographic Surveillance System has since 2001 conducted a biannual household asset survey in order to quantify household socio-economic status (SES) in a rural population living in northeast South Africa. The survey contains binary, ordinal and nominal items. In the absence of income or expenditure data, the SES landscape in the study population is explored and described by clustering the households into homogeneous groups based on their asset status. A model-based approach to clustering the Agincourt households, based on latent variable models, is proposed. In the case of modeling binary or ordinal items, item response theory models are employed. For nominal survey items, a factor analysis model, similar in nature to a multinomial probit model, is used. Both model types have an underlying latent variable structure—this similarity is exploited and the models are combined to produce a hybrid model capable of handling mixed data types. Further, a mixture of the hybrid models is considered to provide clustering capabilities within the context of mixed binary, ordinal and nominal response data. The proposed model is termed a mixture of factor analyzers for mixed data (MFA-MD). The MFA-MD model is applied to the survey data to cluster the Agincourt households into homogeneous groups. The model is estimated within the Bayesian paradigm, using a Markov chain Monte Carlo algorithm. Intuitive groupings result, providing insight to the different socio-economic strata within the Agincourt region. PMID:25485026

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

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.

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.

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.

An Empirical Bayes Estimate of Multinomial Probabilities.

DTIC Science & Technology

1982-02-01

multinomial probabilities has been considered from a decision theoretic point of view by Steinhaus (1957), Trybula (1958) and Rutkowska (1977). In a recent...variate Rypergeometric and Multinomial Distributions," Zastosowania Matematyki, 16, 9-21. Steinhaus , H. (1957), "The Problem of Estimation." Annals of

Modeling abundance using multinomial N-mixture models

USGS Publications Warehouse

Royle, Andy

2016-01-01

Multinomial N-mixture models are a generalization of the binomial N-mixture models described in Chapter 6 to allow for more complex and informative sampling protocols beyond simple counts. Many commonly used protocols such as multiple observer sampling, removal sampling, and capture-recapture produce a multivariate count frequency that has a multinomial distribution and for which multinomial N-mixture models can be developed. Such protocols typically result in more precise estimates than binomial mixture models because they provide direct information about parameters of the observation process. We demonstrate the analysis of these models in BUGS using several distinct formulations that afford great flexibility in the types of models that can be developed, and we demonstrate likelihood analysis using the unmarked package. Spatially stratified capture-recapture models are one class of models that fall into the multinomial N-mixture framework, and we discuss analysis of stratified versions of classical models such as model Mb, Mh and other classes of models that are only possible to describe within the multinomial N-mixture framework.

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.

Discrete choice experiments in pharmacy: a review of the literature.

PubMed

Naik-Panvelkar, Pradnya; Armour, Carol; Saini, Bandana

2013-02-01

Discrete choice experiments (DCEs) have been widely used to elicit patient preferences for various healthcare services and interventions. The aim of our study was to conduct an in-depth scoping review of the literature and provide a current overview of the progressive application of DCEs within the field of pharmacy. Electronic databases (MEDLINE, EMBASE, SCOPUS, ECONLIT) were searched (January 1990-August 2011) to identify published English language studies using DCEs within the pharmacy context. Data were abstracted with respect to DCE methodology and application to pharmacy. Our search identified 12 studies. The DCE methodology was utilised to elicit preferences for different aspects of pharmacy products, therapy or services. Preferences were elicited from either patients or pharmacists, with just two studies incorporating the views of both. Most reviewed studies examined preferences for process-related or provider-related aspects with a lesser focus on health outcomes. Monetary attributes were considered to be important by most patients and pharmacists in the studies reviewed. Logit, probit or multinomial logit models were most commonly employed for estimation. Our study showed that the pharmacy profession has adopted the DCE methodology consistent with the general health DCEs although the number of studies is quite limited. Future studies need to examine preferences of both patients and providers for particular products or disease-state management services. Incorporation of health outcome attributes in the design, testing for external validity and the incorporation of DCE results in economic evaluation framework to inform pharmacy policy remain important areas for future research. © 2012 The Authors. IJPP © 2012 Royal Pharmaceutical Society.

Do objective neighbourhood characteristics relate to residents' preferences for certain sports locations? A cross-sectional study using a discrete choice modelling approach.

PubMed

Deelen, Ineke; Jansen, Marijke; Dogterom, Nico J; Kamphuis, Carlijn B M; Ettema, Dick

2017-12-11

The number of sports facilities, sports clubs, or city parks in a residential neighbourhood may affect the likelihood that people participate in sports and their preferences for a certain sports location. This study aimed to assess whether objective physical and socio-spatial neighbourhood characteristics relate to sports participation and preferences for sports locations. Data from Dutch adults (N = 1201) on sports participation, their most-used sports location, and socio-demographic characteristics were collected using an online survey. Objective land-use data and the number of sports facilities were gathered for each participant using a 2000-m buffer around their home locations, whereas socio-spatial neighbourhood characteristics (i.e., density, socio-economic status, and safety) were determined at the neighbourhood level. A discrete choice-modelling framework (multinomial probit model) was used to model the associations between neighbourhood characteristics and sports participation and location. Higher proportions of green space, blue space, and the number of sports facilities were positively associated with sports participation in public space, at sports clubs, and at other sports facilities. Higher degrees of urbanization were negatively associated with sports participation at public spaces, sports clubs, and other sports facilities. Those with more green space, blue space or sports facilities in their residential neighbourhood were more likely to participate in sports, but these factors did not affect their preference for a certain sports location. Longitudinal study designs are necessary to assess causality: do active people choose to live in sports-facilitating neighbourhoods, or do neighbourhood characteristics affect sports participation?

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.

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.

Widen NomoGram for multinomial logistic regression: an application to staging liver fibrosis in chronic hepatitis C patients.

PubMed

Ardoino, Ilaria; Lanzoni, Monica; Marano, Giuseppe; Boracchi, Patrizia; Sagrini, Elisabetta; Gianstefani, Alice; Piscaglia, Fabio; Biganzoli, Elia M

2017-04-01

The interpretation of regression models results can often benefit from the generation of nomograms, 'user friendly' graphical devices especially useful for assisting the decision-making processes. However, in the case of multinomial regression models, whenever categorical responses with more than two classes are involved, nomograms cannot be drawn in the conventional way. Such a difficulty in managing and interpreting the outcome could often result in a limitation of the use of multinomial regression in decision-making support. In the present paper, we illustrate the derivation of a non-conventional nomogram for multinomial regression models, intended to overcome this issue. Although it may appear less straightforward at first sight, the proposed methodology allows an easy interpretation of the results of multinomial regression models and makes them more accessible for clinicians and general practitioners too. Development of prediction model based on multinomial logistic regression and of the pertinent graphical tool is illustrated by means of an example involving the prediction of the extent of liver fibrosis in hepatitis C patients by routinely available markers.

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.

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.

Markov switching multinomial logit model: An application to accident-injury severities.

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2009-07-01

In this study, two-state Markov switching multinomial logit models are proposed for statistical modeling of accident-injury severities. These models assume Markov switching over time between two unobserved states of roadway safety as a means of accounting for potential unobserved heterogeneity. The states are distinct in the sense that in different states accident-severity outcomes are generated by separate multinomial logit processes. To demonstrate the applicability of the approach, two-state Markov switching multinomial logit models are estimated for severity outcomes of accidents occurring on Indiana roads over a four-year time period. Bayesian inference methods and Markov Chain Monte Carlo (MCMC) simulations are used for model estimation. The estimated Markov switching models result in a superior statistical fit relative to the standard (single-state) multinomial logit models for a number of roadway classes and accident types. It is found that the more frequent state of roadway safety is correlated with better weather conditions and that the less frequent state is correlated with adverse weather conditions.

Post-discharge follow-up visits and hospital utilization by Medicare patients, 2007-2010.

PubMed

DeLia, Derek; Tong, Jian; Gaboda, Dorothy; Casalino, Lawrence P

2014-01-01

Document trends in time to post-discharge follow-up visit for Medicare patients with an index admission for heart failure (HF), acute myocardial infarction (AMI), or community-acquired pneumonia (CAP). Determine factors predicting whether the first post-discharge utilization event is a follow-up visit, treat-and-release emergency department (ED) visit, or readmission. Using Medicare claims data from 2007-2010, we plotted annual cumulative incidence functions for the time frame post-discharge to follow-up visit, accounting for competing risks with censoring at 30 days. We used multinomial probit regression to determine factors predicting the probability of first-occurring post-discharge utilization events within 30 days. For each cohort, the cumulative incidence of follow-up visits increased during the study period. For example, in 2010, 54.6% of HF patients had a follow-up visit within 10 days of discharge compared to 47.9% in 2007. Within each cohort, the largest increase in follow-up visits took place between 2008 and 2009. Follow-up visits were less likely for patients who were Black, Hispanic, and enrolled in Medicaid or Medicare Advantage, and they were more likely for patients with greater comorbidities and prior procedures as well as those with private or supplemental Medicare coverage. There were no changes in 30-day readmission rates. Although increases in follow-up visits may have been influenced by the introduction of publicly reported readmission rates in 2009, these increases did not continue in 2010 and were not associated with a change in readmissions. Patients who were Black, Hispanic, and/or enrolled in Medicaid or Medicare Advantage were less likely to have follow-up visits.

Small individual loans and mental health: a randomized controlled trial among South African adults

PubMed Central

Fernald, Lia CH; Hamad, Rita; Karlan, Dean; Ozer, Emily J; Zinman, Jonathan

2008-01-01

Background In the developing world, access to small, individual loans has been variously hailed as a poverty-alleviation tool – in the context of "microcredit" – but has also been criticized as "usury" and harmful to vulnerable borrowers. Prior studies have assessed effects of access to credit on traditional economic outcomes for poor borrowers, but effects on mental health have been largely ignored. Methods Applicants who had previously been rejected (n = 257) for a loan (200% annual percentage rate – APR) from a lender in South Africa were randomly assigned to a "second-look" that encouraged loan officers to approve their applications. This randomized encouragement resulted in 53% of applicants receiving a loan they otherwise would not have received. All subjects were assessed 6–12 months later with questions about demographics, socio-economic status, and two indicators of mental health: the Center for Epidemiologic Studies – Depression Scale (CES-D) and Cohen's Perceived Stress scale. Intent-to-treat analyses were calculated using multinomial probit regressions. Results Randomization into receiving a "second look" for access to credit increased perceived stress in the combined sample of women and men; the findings were stronger among men. Credit access was associated with reduced depressive symptoms in men, but not women. Conclusion Our findings suggest that a mechanism used to reduce the economic stress of extremely poor individuals can have mixed effects on their experiences of psychological stress and depressive symptomatology. Our data support the notion that mental health should be included as a measure of success (or failure) when examining potential tools for poverty alleviation. Further longitudinal research is needed in South Africa and other settings to understand how borrowing at high interest rates affects gender roles and daily life activities. CCT: ISRCTN 10734925 PMID:19087316

Small individual loans and mental health: a randomized controlled trial among South African adults.

PubMed

Fernald, Lia C H; Hamad, Rita; Karlan, Dean; Ozer, Emily J; Zinman, Jonathan

2008-12-16

In the developing world, access to small, individual loans has been variously hailed as a poverty-alleviation tool - in the context of "microcredit" - but has also been criticized as "usury" and harmful to vulnerable borrowers. Prior studies have assessed effects of access to credit on traditional economic outcomes for poor borrowers, but effects on mental health have been largely ignored. Applicants who had previously been rejected (n = 257) for a loan (200% annual percentage rate - APR) from a lender in South Africa were randomly assigned to a "second-look" that encouraged loan officers to approve their applications. This randomized encouragement resulted in 53% of applicants receiving a loan they otherwise would not have received. All subjects were assessed 6-12 months later with questions about demographics, socio-economic status, and two indicators of mental health: the Center for Epidemiologic Studies - Depression Scale (CES-D) and Cohen's Perceived Stress scale. Intent-to-treat analyses were calculated using multinomial probit regressions. Randomization into receiving a "second look" for access to credit increased perceived stress in the combined sample of women and men; the findings were stronger among men. Credit access was associated with reduced depressive symptoms in men, but not women. Our findings suggest that a mechanism used to reduce the economic stress of extremely poor individuals can have mixed effects on their experiences of psychological stress and depressive symptomatology. Our data support the notion that mental health should be included as a measure of success (or failure) when examining potential tools for poverty alleviation. Further longitudinal research is needed in South Africa and other settings to understand how borrowing at high interest rates affects gender roles and daily life activities. CCT: ISRCTN 10734925.

The Impact of Income and Taxation in a Price-Tiered Cigarette Market - findings from the ITC Bangladesh Surveys.

PubMed

Huq, Iftekharul; Nargis, Nigar; Lkhagvasuren, Damba; Hussain, Akm Ghulam; Fong, Geoffrey T

2018-04-25

Taxing tobacco is among the most effective measures of tobacco control. However, in a tiered market structure where multiple tiers of taxes coexist, the anticipated impact of tobacco taxes on consumption is complex. This paper investigates changing smoking behaviour in lieu of changing prices and changing income. The objective of the paper is to evaluate the effectiveness of change in prices (through taxes) and change in income in a price-tiered cigarette market. A panel dataset from the International Tobacco Control Bangladesh surveys is used for analysis. For preliminary analysis transition matrices are developed. Next, probit and multinomial logit regression models are used to identify the effects of changes in prices and changes in income along with other control variables. Transition matrices show significant movement of smokers across price tiers from one wave to another. Regression results show that higher income raises the probability to up-trade and decreases the probability to down-trade. Results also show that higher prices raises the probability to up-trade and reduces the probability to down-trade. Although not significant, there exists a negative relationship between the probability to down-trade and the probability to intend to quit. It is evident from the results that a price-tiered market provides smokers more opportunities to accommodate their smoking behaviour when faced with price and income change. Therefore, tiered structure of the tax system should be replaced with uniform taxes. Moreover, overall cigarette taxes need to be raised to an extent so that it off-sets any positive effects of income growth. © 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.

Multi-disciplinary decision making in general practice.

PubMed

Kirby, Ann; Murphy, Aileen; Bradley, Colin

2018-04-09

Purpose Internationally, healthcare systems are moving towards delivering care in an integrated manner which advocates a multi-disciplinary approach to decision making. Such an approach is formally encouraged in the management of Atrial Fibrillation patients through the European Society of Cardiology guidelines. Since the emergence of new oral anticoagulants switching between oral anticoagulants (OACs) has become prevalent. This case study considers the role of multi-disciplinary decision making, given the complex nature of the agents. The purpose of this paper is to explore Irish General Practitioners' (GPs) experience of switching between all OACs for Arial Fibrillation (AF) patients; prevalence of multi-disciplinary decision making in OAC switching decisions and seeks to determine the GP characteristics that appear to influence the likelihood of multi-disciplinary decision making. Design/methodology/approach A probit model is used to determine the factors influencing multi-disciplinary decision making and a multinomial logit is used to examine the factors influencing who is involved in the multi-disciplinary decisions. Findings Results reveal that while some multi-disciplinary decision-making is occurring (64 per cent), it is not standard practice despite international guidelines on integrated care. Moreover, there is a lack of patient participation in the decision-making process. Female GPs and GPs who have initiated prescriptions for OACs are more likely to engage in multi-disciplinary decision-making surrounding switching OACs amongst AF patients. GPs with training practices were less likely to engage with cardiac consultants and those in urban areas were more likely to engage with other (non-cardiac) consultants. Originality/value For optimal decision making under uncertainty multi-disciplinary decision-making is needed to make a more informed judgement and to improve treatment decisions and reduce the opportunity cost of making the wrong decision.

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.

Effects of supplementary private health insurance on physician visits in Korea.

PubMed

Kang, Sungwook; You, Chang Hoon; Kwon, Young Dae; Oh, Eun-Hwan

2009-12-01

The coverage of social health insurance has remained limited, despite it being compulsory in Korea. Accordingly, Koreans have come to rely upon supplementary private health insurance (PHI) to cover their medical costs. We examined the effects of supplementary PHI on physician visits in Korea. This study used individual data from 11,043 respondents who participated in the Korean Labor and Income Panel Survey in 2001. We conducted a single probit model to identify the relationship between PHI and physician visits, with adjustment for the following covariates: demographic characteristics, socioeconomic status, health status, and health-related behavior. Finally, we performed a bivariate probit model to examine the true effect of PHI on physician visits, with adjustment for the above covariates plus unobservable covariates that might affect not only physician visit, but also the purchase of PHI. We found that about 38% of all respondents had one or more private health plans. Forty-five percent of all respondents visited one or more physicians, and 49% of those who were privately insured had physician visits compared with 42% of the uninsured. The single probit model showed that those with PHI were about 14 percentage points more likely to visit physicians than those who do not have PHI. However, this distinction disappears in the bivariate probit model. This result might have been a consequence of the nature of private health plans in Korea. Private insurance companies pay a fixed amount directly to their enrollees in case of illness/injury, and the individuals are responsible subsequently for purchasing their own healthcare services. This study demonstrated the potential of Korean PHI to address the problem of moral hazard. These results serve as a reference for policy makers when considering how to finance healthcare services, as well as to contain healthcare expenditure.

Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year

USGS Publications Warehouse

Higgs, Megan D.; Link, William; White, Gary C.; Haroldson, Mark A.; Bjornlie, Daniel D.

2013-01-01

Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.

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.

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.

Fuzzy multinomial logistic regression analysis: A multi-objective programming approach

NASA Astrophysics Data System (ADS)

Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan

2017-05-01

Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.

Multinomial mixture model with heterogeneous classification probabilities

USGS Publications Warehouse

Holland, M.D.; Gray, B.R.

2011-01-01

Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.

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.

A Dirichlet-Multinomial Bayes Classifier for Disease Diagnosis with Microbial Compositions.

PubMed

Gao, Xiang; Lin, Huaiying; Dong, Qunfeng

2017-01-01

Dysbiosis of microbial communities is associated with various human diseases, raising the possibility of using microbial compositions as biomarkers for disease diagnosis. We have developed a Bayes classifier by modeling microbial compositions with Dirichlet-multinomial distributions, which are widely used to model multicategorical count data with extra variation. The parameters of the Dirichlet-multinomial distributions are estimated from training microbiome data sets based on maximum likelihood. The posterior probability of a microbiome sample belonging to a disease or healthy category is calculated based on Bayes' theorem, using the likelihood values computed from the estimated Dirichlet-multinomial distribution, as well as a prior probability estimated from the training microbiome data set or previously published information on disease prevalence. When tested on real-world microbiome data sets, our method, called DMBC (for Dirichlet-multinomial Bayes classifier), shows better classification accuracy than the only existing Bayesian microbiome classifier based on a Dirichlet-multinomial mixture model and the popular random forest method. The advantage of DMBC is its built-in automatic feature selection, capable of identifying a subset of microbial taxa with the best classification accuracy between different classes of samples based on cross-validation. This unique ability enables DMBC to maintain and even improve its accuracy at modeling species-level taxa. The R package for DMBC is freely available at https://github.com/qunfengdong/DMBC. IMPORTANCE By incorporating prior information on disease prevalence, Bayes classifiers have the potential to estimate disease probability better than other common machine-learning methods. Thus, it is important to develop Bayes classifiers specifically tailored for microbiome data. Our method shows higher classification accuracy than the only existing Bayesian classifier and the popular random forest method, and thus provides an alternative option for using microbial compositions for disease diagnosis.

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.

Modeling Unconscious Gender Bias in Fame Judgments: Finding the Proper Branch of the Correct (Multinomial) Tree

PubMed

Draine; Greenwald; Banaji

1996-03-01

In the preceding article, Buchner and Wippich used a guessing-corrected, multinomial process-dissociation analysis to test whether a gender bias in fame judgments reported by Banaji and Greenwald (Journal of Personality and Social Psychology, 1995, 68, 181-198) was unconscious. In their two experiments, Buchner and Wippich found no evidence for unconscious mediation of this gender bias. Their conclusion can be questioned by noting that (a) the gender difference in familiarity of previously seen names that Buchner and Wippich modeled was different from the gender difference in criterion for fame judgments reported by Banaji and Greenwald, (b) the assumptions of Buchner and Wippich's multinomial model excluded processes that are plausibly involved in the fame judgment task, and (c) the constructs of Buchner and Wippich's model that corresponded most closely to Banaji and Greenwald's gender-bias interpretation were formulated so as to preclude the possibility of modeling that interpretation. Perhaps a more complex multinomial model can model the Banaji and Greenwald interpretation.

Modeling unconscious gender bias in fame judgments: finding the proper branch of the correct (multinomial) tree.

PubMed

Draine, S C; Greenwald, A G; Banaji, M R

1996-01-01

In the preceding article, Buchner and Wippich used a guessing-corrected, multinomial process-dissociation analysis to test whether a gender bias in fame judgements reported by Banaji and Greenwald (Journal of Personality and Social Psychology, 1995, 68, 181-198) was unconscious. In their two experiments, Buchner and Wippich found no evidence for unconscious mediation of this gender bias. Their conclusion can be questioned by noting that (a) the gender difference in familiarity of previously seen names that Buchner and Wippich modeled was different from the gender difference in criterion for fame judgements reported by Banaji and Greenwald, (b) the assumptions of Buchner and Wippich's multinomial model excluded processes that are plausibly involved in the fame judgement task, and (c) the constructs of Buchner and Wippich's model that corresponded most closely to Banaji and Greenwald's gender-bias interpretation were formulated so as to preclude the possibility of modeling that interpretation. Perhaps a more complex multinomial model can model the Banaji and Greenwald interpretation.

Analysis of multinomial models with unknown index using data augmentation

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, R.M.; Link, W.A.

2007-01-01

Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.

Estimation from incomplete multinomial data. Ph.D. Thesis - Harvard Univ.

NASA Technical Reports Server (NTRS)

Credeur, K. R.

1978-01-01

The vector of multinomial cell probabilities was estimated from incomplete data, incomplete in that it contains partially classified observations. Each such partially classified observation was observed to fall in one of two or more selected categories but was not classified further into a single category. The data were assumed to be incomplete at random. The estimation criterion was minimization of risk for quadratic loss. The estimators were the classical maximum likelihood estimate, the Bayesian posterior mode, and the posterior mean. An approximation was developed for the posterior mean. The Dirichlet, the conjugate prior for the multinomial distribution, was assumed for the prior distribution.

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

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.

Pig Data and Bayesian Inference on Multinomial Probabilities

ERIC Educational Resources Information Center

Kern, John C.

2006-01-01

Bayesian inference on multinomial probabilities is conducted based on data collected from the game Pass the Pigs[R]. Prior information on these probabilities is readily available from the instruction manual, and is easily incorporated in a Dirichlet prior. Posterior analysis of the scoring probabilities quantifies the discrepancy between empirical…

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

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

On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices

PubMed Central

Ye, Xin; Pendyala, Ram M.; Zou, Yajie

2017-01-01

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences. PMID:29073152

On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices.

PubMed

Wang, Ke; Ye, Xin; Pendyala, Ram M; Zou, Yajie

2017-01-01

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences.

A General Family of Limited Information Goodness-of-Fit Statistics for Multinomial Data

ERIC Educational Resources Information Center

Joe, Harry; Maydeu-Olivares, Alberto

2010-01-01

Maydeu-Olivares and Joe (J. Am. Stat. Assoc. 100:1009-1020, "2005"; Psychometrika 71:713-732, "2006") introduced classes of chi-square tests for (sparse) multidimensional multinomial data based on low-order marginal proportions. Our extension provides general conditions under which quadratic forms in linear functions of cell residuals are…

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

ERIC Educational Resources Information Center

Klauer, Karl Christoph

2010-01-01

Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

Institutional Climate and Student Departure: A Multinomial Multilevel Modeling Approach

ERIC Educational Resources Information Center

Yi, Pyong-sik

2008-01-01

This study applied a multinomial HOLM technique to examine the extent to which the institutional climate for diversity influences the different types of college student withdrawal, such as stop out, drop out, and transfer. Based on a reformulation of Tinto's model along with the conceptualization of institutional climate for diversity by Hurtado…

An INAR(1) Negative Multinomial Regression Model for Longitudinal Count Data.

ERIC Educational Resources Information Center

Bockenholt, Ulf

1999-01-01

Discusses a regression model for the analysis of longitudinal count data in a panel study by adapting an integer-valued first-order autoregressive (INAR(1)) Poisson process to represent time-dependent correlation between counts. Derives a new negative multinomial distribution by combining INAR(1) representation with a random effects approach.…

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.

2010-01-01

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…

A Multinomial Model of Event-Based Prospective Memory

ERIC Educational Resources Information Center

Smith, Rebekah E.; Bayen, Ute J.

2004-01-01

Prospective memory is remembering to perform an action in the future. The authors introduce the 1st formal model of event-based prospective memory, namely, a multinomial model that includes 2 separate parameters related to prospective memory processes. The 1st measures preparatory attentional processes, and the 2nd measures retrospective memory…

Risk Score Algorithm for Treatment of Persistent Apical Periodontitis

PubMed Central

Yu, V.S.; Khin, L.W.; Hsu, C.S.; Yee, R.; Messer, H.H.

2014-01-01

Persistent apical periodontitis related to a nonvital tooth that does not resolve following root canal treatment may be compatible with health and may not require further intervention. This research aimed to develop a Deterioration Risk Score (DRS) to differentiate lesions requiring further intervention from lesions likely to be compatible with health. In this cross-sectional study, patient records (2003-2008) were screened for root-filled teeth with periapical radiolucency visible on periapical radiographs taken at treatment and at recruitment at least 4 yr later. The final sample consisted of 228 lesions in 182 patients. Potential demographic and treatment risk factors were screened against 3 categorical outcomes (improved/unchanged/deteriorated), and a multivariate independent multinomial probit regression model was built. A 5-level DRS was constructed by summing values of adjusted regression coefficients in the model, based on predicted probabilities of deterioration. Most lesions (127, 55.7%) had improved over time, while 32 (14.0%) remained unchanged, and 69 (30.3%) had deteriorated. Significant predictors of deterioration were as follows: time since treatment (relative risk [RR]: 1.11, 95% confidence interval [CI]: 1.01-1.22, p = .030, rounded beta value = 1, for every year increase after 4 yr), current pain (RR: 3.79, 95% CI: 1.48-9.70, p = .005, rounded beta value = 13), sinus tract present (RR: 4.13, 95% CI: 1.11-15.29, p = .034, rounded beta value = 14), and lesion size (RR: 7.20, 95% CI: 3.70-14.02, p < .001, rounded beta value = 20). Persistent apical periodontitis with DRS <15 represented very low risk; 15-20, low risk; 21-30, moderate risk; 31-40, high risk; and >40, very high risk. DRS could help the clinician identify persistent apical periodontitis at low risk for deterioration, and it would not require intervention. When validated, this tool could reduce the risk of overtreatment and contribute toward targeted care and better efficiency in the timely management of disease. PMID:25190267

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

NASA Astrophysics Data System (ADS)

Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

2014-12-01

Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

Brief Report: Association of Myositis Autoantibodies, Clinical Features, and Environmental Exposures at Illness Onset With Disease Course in Juvenile Myositis.

PubMed

Habers, G Esther A; Huber, Adam M; Mamyrova, Gulnara; Targoff, Ira N; O'Hanlon, Terrance P; Adams, Sharon; Pandey, Janardan P; Boonacker, Chantal; van Brussel, Marco; Miller, Frederick W; van Royen-Kerkhof, Annet; Rider, Lisa G

2016-03-01

To identify early factors associated with disease course in patients with juvenile idiopathic inflammatory myopathies (IIMs). Univariable and multivariable multinomial logistic regression analyses were performed in a large juvenile IIM registry (n = 365) and included demographic characteristics, early clinical features, serum muscle enzyme levels, myositis autoantibodies, environmental exposures, and immunogenetic polymorphisms. Multivariable associations with chronic or polycyclic courses compared to a monocyclic course included myositis-specific autoantibodies (multinomial odds ratio [OR] 4.2 and 2.8, respectively), myositis-associated autoantibodies (multinomial OR 4.8 and 3.5), and a documented infection within 6 months of illness onset (multinomial OR 2.5 and 4.7). A higher overall clinical symptom score at diagnosis was associated with chronic or monocyclic courses compared to a polycyclic course. Furthermore, severe illness onset was associated with a chronic course compared to monocyclic or polycyclic courses (multinomial OR 2.1 and 2.6, respectively), while anti-p155/140 autoantibodies were associated with chronic or polycyclic courses compared to a monocyclic course (multinomial OR 3.9 and 2.3, respectively). Additional univariable associations of a chronic course compared to a monocyclic course included photosensitivity, V-sign or shawl sign rashes, and cuticular overgrowth (OR 2.2-3.2). The mean ultraviolet index and highest ultraviolet index in the month before diagnosis were associated with a chronic course compared to a polycyclic course in boys (OR 1.5 and 1.3), while residing in the Northwest was less frequently associated with a chronic course (OR 0.2). Our findings indicate that myositis autoantibodies, in particular anti-p155/140, and a number of early clinical features and environmental exposures are associated with a chronic course in patients with juvenile IIM. These findings suggest that early factors, which are associated with poorer outcomes in juvenile IIM, can be identified. © 2016, American College of Rheumatology.

Composite Linear Models | Division of Cancer Prevention

Cancer.gov

By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty

The Source of Adult Age Differences in Event-Based Prospective Memory: A Multinomial Modeling Approach

ERIC Educational Resources Information Center

Smith, Rebekah E.; Bayen, Ute J.

2006-01-01

Event-based prospective memory involves remembering to perform an action in response to a particular future event. Normal younger and older adults performed event-based prospective memory tasks in 2 experiments. The authors applied a formal multinomial processing tree model of prospective memory (Smith & Bayen, 2004) to disentangle age differences…

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.

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.

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

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…

Parameter Estimation for the Dirichlet-Multinomial Distribution Using Supplementary Beta-Binomial Data.

DTIC Science & Technology

1987-07-01

multinomial distribution as a magazine exposure model. J. of Marketing Research . 21, 100-106. Lehmann, E.L. (1983). Theory of Point Estimation. John Wiley and... Marketing Research . 21, 89-99. V I flWflW WflW~WWMWSS tWN ,rw fl rwwrwwr-w~ w-. ~. - - -- .~ 𔃾 4’.) ~a 4’ ., 𔃾. ’-4. .4.: .4~ I .4. ~J3iAf a,’ -a’ 4

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

PubMed

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Arsenic exposure and oral cavity lesions in Bangladesh.

PubMed

Syed, Emdadul H; Melkonian, Stephanie; Poudel, Krishna C; Yasuoka, Junko; Otsuka, Keiko; Ahmed, Alauddin; Islam, Tariqul; Parvez, Faruque; Slavkovich, Vesna; Graziano, Joseph H; Ahsan, Habibul; Jimba, Masamine

2013-01-01

To evaluate the relationship between arsenic exposure and oral cavity lesions among an arsenic-exposed population in Bangladesh. We carried out an analysis utilizing the baseline data of the Health Effects of Arsenic Exposure Longitudinal Study, which is an ongoing population-based cohort study to investigate health outcomes associated with arsenic exposure via drinking water in Araihazar, Bangladesh. We used multinomial regression models to estimate the risk of oral cavity lesions. Participants with high urinary arsenic levels (286.1 to 5000.0 μg/g) were more likely to develop arsenical lesions of the gums (multinomial odds ratio = 2.90; 95% confidence interval, 1.11 to 7.54), and tongue (multinomial odds ratio = 2.79; 95% confidence interval, 1.51 to 5.15), compared with those with urinary arsenic levels of 7.0 to 134.0 μg/g. Higher level of arsenic exposure was positively associated with increased arsenical lesions of the gums and tongue.

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...

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

Physical activity and healthy diet: determinants and implicit relationship.

PubMed

Tavares, Aida Isabel

2014-06-01

People who decide to lose weight by dieting often do so without participating in any associated physical activity. Although some people who participate in sports are unconcerned about their diet, it is generally believed that people who exercise tend to eat a healthy diet and those who do not exercise eat a less healthy diet. There is no clear relationship between the decisions regarding participation in physical activity and eating a healthy diet when choices are taken freely and not influenced by policy factors promoting healthy behaviour. However, these decisions may reveal some common explanatory factors and an implicit link. As such the aim of this study was to identify the common explanatory factors and investigate the existence of an implicit relationship. Econometric estimate - bivariate probit estimation. Using data from the Portuguese National Health Survey, a bivariate probit was undertaken for decisions regarding participation in physical activity and eating a healthy diet. The correlation between the residuals gives information on the implicit relationship between the healthy choices. Common explanatory factors were found between the decisions to eat healthy snacks and participate in physical activity, such as being married. However, holding voluntary private health insurance, smoking, getting older, living alone and unemployment were found to dissuade people from making healthy choices. Positive correlation was found between the residuals of the probit estimations, indicating that other unmeasurable variables have a similar influence on both decisions, such as peer pressure, cultural values, fashion, advertising and risk aversion. Further research is needed to improve understanding of decision making related to participation in physical activity and eating a healthy diet. This will facilitate the design of policies that will make a greater contribution to healthy lifestyles. Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

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.

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)

Assessing characteristics related to the use of seatbelts and cell phones by drivers: application of a bivariate probit model.

PubMed

Russo, Brendan J; Kay, Jonathan J; Savolainen, Peter T; Gates, Timothy J

2014-06-01

The effects of cell phone use and safety belt use have been an important focus of research related to driver safety. Cell phone use has been shown to be a significant source of driver distraction contributing to substantial degradations in driver performance, while safety belts have been demonstrated to play a vital role in mitigating injuries to crash-involved occupants. This study examines the prevalence of cell phone use and safety belt non-use among the driving population through direct observation surveys. A bivariate probit model is developed to simultaneously examine the factors that affect cell phone and safety belt use among motor vehicle drivers. The results show that several factors may influence drivers' decision to use cell phones and safety belts, and that these decisions are correlated. Understanding the factors that affect both cell phone use and safety belt non-use is essential to targeting policy and programs that reduce such behavior. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

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.

Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass

USGS Publications Warehouse

Mollenhauer, Robert; Brewer, Shannon K.

2017-01-01

Failure to account for variable detection across survey conditions constrains progressive stream ecology and can lead to erroneous stream fish management and conservation decisions. In addition to variable detection’s confounding long-term stream fish population trends, reliable abundance estimates across a wide range of survey conditions are fundamental to establishing species–environment relationships. Despite major advancements in accounting for variable detection when surveying animal populations, these approaches remain largely ignored by stream fish scientists, and CPUE remains the most common metric used by researchers and managers. One notable advancement for addressing the challenges of variable detection is the multinomial N-mixture model. Multinomial N-mixture models use a flexible hierarchical framework to model the detection process across sites as a function of covariates; they also accommodate common fisheries survey methods, such as removal and capture–recapture. Effective monitoring of stream-dwelling Smallmouth Bass Micropterus dolomieu populations has long been challenging; therefore, our objective was to examine the use of multinomial N-mixture models to improve the applicability of electrofishing for estimating absolute abundance. We sampled Smallmouth Bass populations by using tow-barge electrofishing across a range of environmental conditions in streams of the Ozark Highlands ecoregion. Using an information-theoretic approach, we identified effort, water clarity, wetted channel width, and water depth as covariates that were related to variable Smallmouth Bass electrofishing detection. Smallmouth Bass abundance estimates derived from our top model consistently agreed with baseline estimates obtained via snorkel surveys. Additionally, confidence intervals from the multinomial N-mixture models were consistently more precise than those of unbiased Petersen capture–recapture estimates due to the dependency among data sets in the hierarchical framework. We demonstrate the application of this contemporary population estimation method to address a longstanding stream fish management issue. We also detail the advantages and trade-offs of hierarchical population estimation methods relative to CPUE and estimation methods that model each site separately.

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.

Genetic parameter estimation of reproductive traits of Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Tan, Jian; Kong, Jie; Cao, Baoxiang; Luo, Kun; Liu, Ning; Meng, Xianhong; Xu, Shengyu; Guo, Zhaojia; Chen, Guoliang; Luan, Sheng

2017-02-01

In this study, the heritability, repeatability, phenotypic correlation, and genetic correlation of the reproductive and growth traits of L. vannamei were investigated and estimated. Eight traits of 385 shrimps from forty-two families, including the number of eggs (EN), number of nauplii (NN), egg diameter (ED), spawning frequency (SF), spawning success (SS), female body weight (BW) and body length (BL) at insemination, and condition factor (K), were measured,. A total of 519 spawning records including multiple spawning and 91 no spawning records were collected. The genetic parameters were estimated using an animal model, a multinomial logit model (for SF), and a sire-dam and probit model (for SS). Because there were repeated records, permanent environmental effects were included in the models. The heritability estimates for BW, BL, EN, NN, ED, SF, SS, and K were 0.49 ± 0.14, 0.51 ± 0.14, 0.12 ± 0.08, 0, 0.01 ± 0.04, 0.06 ± 0.06, 0.18 ± 0.07, and 0.10 ± 0.06, respectively. The genetic correlation was 0.99 ± 0.01 between BW and BL, 0.90 ± 0.19 between BW and EN, 0.22 ± 0.97 between BW and ED, -0.77 ± 1.14 between EN and ED, and -0.27 ± 0.36 between BW and K. The heritability of EN estimated without a covariate was 0.12 ± 0.08, and the genetic correlation was 0.90 ± 0.19 between BW and EN, indicating that improving BW may be used in selection programs to genetically improve the reproductive output of L. vannamei during the breeding. For EN, the data were also analyzed using body weight as a covariate (EN-2). The heritability of EN-2 was 0.03 ± 0.05, indicating that it is difficult to improve the reproductive output by genetic improvement. Furthermore, excessive pursuit of this selection is often at the expense of growth speed. Therefore, the selection of high-performance spawners using BW and SS may be an important strategy to improve nauplii production.

Quality and provider choice: a multinomial logit-least-squares model with selectivity.

PubMed Central

Haas-Wilson, D; Savoca, E

1990-01-01

A Federal Trade Commission survey of contact lens wearers is used to estimate a multinomial logit-least-squares model of the joint determination of provider choice and quality of care in the contact lens industry. The effect of personal and industry characteristics on a consumer's choice among three types of providers--opticians, ophthalmologists, and optometrists--is estimated via multinomial logit. The regression model of the quality of care has two features that distinguish it from previous work in the area. First, it uses an outcome rather than a structural or process measure of quality. Quality is measured as an index of the presence of seven potentially pathological eye conditions caused by poorly fitted lenses. Second, the model controls for possible selection bias that may arise from the fact that the sample observations on quality are generated by consumers' nonrandom choices of providers. The multinomial logit estimates of provider choice indicate that professional regulations limiting the commercial practices of optometrists shift demand for contact lens services away from optometrists toward ophthalmologists. Further, consumers are more likely to have their lenses fitted by opticians in states that require the licensing of opticians. The regression analysis of variations in quality across provider types shows a strong positive selection bias in the estimate of the quality of care received by consumers of ophthalmologists' services. Failure to control for this selection bias results in an overestimate of the quality of care provided by ophthalmologists. PMID:2312308

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)...

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...

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...

Multinomial logistic regression in workers' health

NASA Astrophysics Data System (ADS)

Grilo, Luís M.; Grilo, Helena L.; Gonçalves, Sónia P.; Junça, Ana

2017-11-01

In European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services' organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.

A computer program for estimation from incomplete multinomial data

NASA Technical Reports Server (NTRS)

Credeur, K. R.

1978-01-01

Coding is given for maximum likelihood and Bayesian estimation of the vector p of multinomial cell probabilities from incomplete data. Also included is coding to calculate and approximate elements of the posterior mean and covariance matrices. The program is written in FORTRAN 4 language for the Control Data CYBER 170 series digital computer system with network operating system (NOS) 1.1. The program requires approximately 44000 octal locations of core storage. A typical case requires from 72 seconds to 92 seconds on CYBER 175 depending on the value of the prior parameter.

Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models.

PubMed

Nazem-Zadeh, Mohammad-Reza; Elisevich, Kost V; Schwalb, Jason M; Bagher-Ebadian, Hassan; Mahmoudi, Fariborz; Soltanian-Zadeh, Hamid

2014-12-15

Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment. Copyright © 2014 Elsevier B.V. All rights reserved.

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…

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…

Child Labour and Child Schooling in Rural Ethiopia: Nature and Trade-Off

ERIC Educational Resources Information Center

Haile, Getinet; Haile, Beliyou

2012-01-01

We examine work participation and schooling for children aged 7-15 using survey data from rural Ethiopia. Bivariate probit and age-adjusted educational attainment equations have been estimated. Male children are found to be more likely to attend school than their female counterparts. "Specialization" in child labour is also found, with…

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...

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...

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…

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…

Intimate Partner Violence in Colombia: Who Is at Risk?

ERIC Educational Resources Information Center

Friedemann-Sanchez, Greta; Lovaton, Rodrigo

2012-01-01

The role that domestic violence plays in perpetuating poverty is often overlooked as a development issue. Using data from the 2005 Demographic Health Survey, this paper examines the prevalence of intimate partner violence in Colombia. Employing an intrahousehold bargaining framework and a bivariate probit model, it assesses the prevalence of and…

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.

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

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

NASA Astrophysics Data System (ADS)

Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei

2008-10-01

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

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.

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

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...

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....

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…

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…

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…

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...

Factors Influencing the Likelihood of Overeducation: A Bivariate Probit with Sample Selection Framework

ERIC Educational Resources Information Center

Rubb, Stephen

2014-01-01

Contrary to expectations, the likelihood of overeducation is shown to be inversely related to unemployment rates when not control for selectivity. Furthermore, incidence data show that overeducation is more common among men than women and among Whites than Blacks. At issue is selectivity: employment must be selected for overeducation to occur.…

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…

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

DOE PAGES

Ye, Xin; Garikapati, Venu M.; You, Daehyun; ...

2017-11-08

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

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

Ye, Xin; Garikapati, Venu M.; You, Daehyun

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

A measurement theory of illusory conjunctions.

PubMed

Prinzmetal, William; Ivry, Richard B; Beck, Diane; Shimizu, Naomi

2002-04-01

Illusory conjunctions refer to the incorrect perceptual combination of correctly perceived features, such as color and shape. Research on the phenomenon has been hampered by the lack of a measurement theory that accounts for guessing features, as well as the incorrect combination of correctly perceived features. Recently, several investigators have suggested using multinomial models as a tool for measuring feature integration. The authors examined the adequacy of these models in 2 experiments by testing whether model parameters reflect changes in stimulus factors. In a third experiment, confidence ratings were used as a tool for testing the model. Multinomial models accurately reflected both variations in stimulus factors and observers' trial-by-trial confidence ratings.

Classifying emotion in Twitter using Bayesian network

NASA Astrophysics Data System (ADS)

Surya Asriadie, Muhammad; Syahrul Mubarok, Mohamad; Adiwijaya

2018-03-01

Language is used to express not only facts, but also emotions. Emotions are noticeable from behavior up to the social media statuses written by a person. Analysis of emotions in a text is done in a variety of media such as Twitter. This paper studies classification of emotions on twitter using Bayesian network because of its ability to model uncertainty and relationships between features. The result is two models based on Bayesian network which are Full Bayesian Network (FBN) and Bayesian Network with Mood Indicator (BNM). FBN is a massive Bayesian network where each word is treated as a node. The study shows the method used to train FBN is not very effective to create the best model and performs worse compared to Naive Bayes. F1-score for FBN is 53.71%, while for Naive Bayes is 54.07%. BNM is proposed as an alternative method which is based on the improvement of Multinomial Naive Bayes and has much lower computational complexity compared to FBN. Even though it’s not better compared to FBN, the resulting model successfully improves the performance of Multinomial Naive Bayes. F1-Score for Multinomial Naive Bayes model is 51.49%, while for BNM is 52.14%.

Network-constrained group lasso for high-dimensional multinomial classification with application to cancer subtype prediction.

PubMed

Tian, Xinyu; Wang, Xuefeng; Chen, Jun

2014-01-01

Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases.

Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis

NASA Astrophysics Data System (ADS)

Chang, C. H.; Chan, H. C.; Chen, B. A.

2016-12-01

Classification of effective soil depth is a task of determining the slopeland utilizable limitation in Taiwan. The "Slopeland Conservation and Utilization Act" categorizes the slopeland into agriculture and husbandry land, land suitable for forestry and land for enhanced conservation according to the factors including average slope, effective soil depth, soil erosion and parental rock. However, sit investigation of the effective soil depth requires a cost-effective field work. This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The Wen-Shui Watershed located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. An Error Matrix was then used to assess the model accuracy. The results showed an overall accuracy of 75%. At the end, a map of effective soil depth was produced to help planners and decision makers in determining the slopeland utilizable limitation in the study areas.

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...

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…

Certification of family forests: What influences owners’ awareness and participation?

Treesearch

Selmin F. Creamer; Keith A. Blatner; Brett J. Butler

2012-01-01

In the United States, 35% of the forestland is owned by family forest owners with approximately 0.2% of this land reported to be enrolled in a forest certification system. The current study was conducted to provide insights into factors influencing family forest owners’ decisions to certify their lands. The bivariate probit model with sample selection results suggests...

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…

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…

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.

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

Testing for the Endogenous Nature between Women's Empowerment and Antenatal Health Care Utilization: Evidence from a Cross-Sectional Study in Egypt

PubMed Central

Hussein, Mohamed Ali

2014-01-01

Women's relative lack of decision-making power and their unequal access to employment, finances, education, basic health care, and other resources are considered to be the root causes of their ill-health and that of their children. The main purpose of this paper is to examine the interactive relation between women's empowerment and the use of maternal health care. Two model specifications are tested. One assumes no correlation between empowerment and antenatal care while the second specification allows for correlation. Both the univariate and the recursive bivariate probit models are tested. The data used in this study is EDHS 2008. Factor Analysis Technique is also used to construct some of the explanatory variables such as the availability and quality of health services indicators. The findings show that women's empowerment and receiving regular antenatal care are simultaneously determined and the recursive bivariate probit is a better approximation to the relationship between them. Women's empowerment has significant and positive impact on receiving regular antenatal care. The availability and quality of health services do significantly increase the likelihood of receiving regular antenatal care. PMID:25140310

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.

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

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 simplified conjoint recognition paradigm for the measurement of gist and verbatim memory.

PubMed

Stahl, Christoph; Klauer, Karl Christoph

2008-05-01

The distinction between verbatim and gist memory traces has furthered the understanding of numerous phenomena in various fields, such as false memory research, research on reasoning and decision making, and cognitive development. To measure verbatim and gist memory empirically, an experimental paradigm and multinomial measurement model has been proposed but rarely applied. In the present article, a simplified conjoint recognition paradigm and multinomial model is introduced and validated as a measurement tool for the separate assessment of verbatim and gist memory processes. A Bayesian metacognitive framework is applied to validate guessing processes. Extensions of the model toward incorporating the processes of phantom recollection and erroneous recollection rejection are discussed.

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.

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

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

NASA Astrophysics Data System (ADS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-10-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen

2017-12-01

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.

Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification

USGS Publications Warehouse

Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.

2010-01-01

Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.

Uncovering a Latent Multinomial: Analysis of Mark-Recapture Data with Misidentification

USGS Publications Warehouse

Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.

2009-01-01

Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f=A'x of a latent multinomial variable x with cell probability vector pi= pi(theta). Given that full conditional distributions [theta | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, theta], which is made possible by knowledge of the null space of A'. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

2012-01-01

Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

NASA Astrophysics Data System (ADS)

Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter

2017-05-01

The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.

Multinomial Bayesian learning for modeling classical and nonclassical receptive field properties.

PubMed

Hosoya, Haruo

2012-08-01

We study the interplay of Bayesian inference and natural image learning in a hierarchical vision system, in relation to the response properties of early visual cortex. We particularly focus on a Bayesian network with multinomial variables that can represent discrete feature spaces similar to hypercolumns combining minicolumns, enforce sparsity of activation to learn efficient representations, and explain divisive normalization. We demonstrate that maximal-likelihood learning using sampling-based Bayesian inference gives rise to classical receptive field properties similar to V1 simple cells and V2 cells, while inference performed on the trained network yields nonclassical context-dependent response properties such as cross-orientation suppression and filling in. Comparison with known physiological properties reveals some qualitative and quantitative similarities.

Disentangling stereotype activation and stereotype application in the stereotype misperception task.

PubMed

Krieglmeyer, Regina; Sherman, Jeffrey W

2012-08-01

When forming impressions about other people, stereotypes about the individual's social group often influence the resulting impression. At least 2 distinguishable processes underlie stereotypic impression formation: stereotype activation and stereotype application. Most previous research has used implicit measures to assess stereotype activation and explicit measures to assess stereotype application, which has several disadvantages. The authors propose a measure of stereotypic impression formation, the stereotype misperception task (SMT), together with a multinomial model that quantitatively disentangles the contributions of stereotype activation and application to responses in the SMT. The validity of the SMT and of the multinomial model was confirmed in 5 studies. The authors hope to advance research on stereotyping by providing a measurement tool that separates multiple processes underlying impression formation.

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…

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...

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.

Estimation of Rank Correlation for Clustered Data

PubMed Central

Rosner, Bernard; Glynn, Robert

2017-01-01

It is well known that the sample correlation coefficient (Rxy) is the maximum likelihood estimator (MLE) of the Pearson correlation (ρxy) for i.i.d. bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the MLE of ρxy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (a) converting ranks of both X and Y to the probit scale, (b) estimating the Pearson correlation between probit scores for X and Y, and (c) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. PMID:28399615

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.

Binge drinking and marijuana use among menthol and non-menthol adolescent smokers: findings from the youth smoking survey.

PubMed

Azagba, Sunday; Sharaf, Mesbah F

2014-03-01

Research has shown that smoking menthol cigarettes induces smoking initiation and hinders cessation efforts especially among youth. The objective of this paper is to examine the association between menthol cigarette smoking and substance use among adolescent students in Canada. A nationally representative cross-sectional sample of 4466 Canadian students in grades 7 to 12 from the 2010-2011 Youth Smoking Survey is analyzed. A bivariate probit model is used jointly to examine the association of menthol smoking status with binge drinking and marijuana use. 32% of the current smokers in grades 7 to 12 smoke mentholated cigarettes, 73% are binge drinkers and 79% use marijuana. Results of the bivariate probit regression analysis, controlling for other covariates, show statistically significant differences in the likelihood of binge drinking and marijuana use between menthol and non-menthol smokers. Menthol cigarette smokers are 6% (ME=0.06, 95% CI=0.03-0.09) more likely to binge drink and 7% (ME=0.07, 95% CI=0.05-0.10) more likely to use marijuana. Smoking menthol cigarettes is associated with a higher likelihood of binge drinking and marijuana use among Canadian adolescents. Banning menthol in cigarettes may be beneficial to public health. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Prospective memory after moderate-to-severe traumatic brain injury: a multinomial modeling approach.

PubMed

Pavawalla, Shital P; Schmitter-Edgecombe, Maureen; Smith, Rebekah E

2012-01-01

Prospective memory (PM), which can be understood as the processes involved in realizing a delayed intention, is consistently found to be impaired after a traumatic brain injury (TBI). Although PM can be empirically dissociated from retrospective memory, it inherently involves both a prospective component (i.e., remembering that an action needs to be carried out) and retrospective components (i.e., remembering what action needs to be executed and when). This study utilized a multinomial processing tree model to disentangle the prospective (that) and retrospective recognition (when) components underlying PM after moderate-to-severe TBI. Seventeen participants with moderate to severe TBI and 17 age- and education-matched control participants completed an event-based PM task that was embedded within an ongoing computer-based color-matching task. The multinomial processing tree modeling approach revealed a significant group difference in the prospective component, indicating that the control participants allocated greater preparatory attentional resources to the PM task compared to the TBI participants. Participants in the TBI group were also found to be significantly more impaired than controls in the when aspect of the retrospective component. These findings indicated that the TBI participants had greater difficulty allocating the necessary preparatory attentional resources to the PM task and greater difficulty discriminating between PM targets and nontargets during task execution, despite demonstrating intact posttest recall and/or recognition of the PM tasks and targets.

Landscape effects on diets of two canids in Northwestern Texas: A multinomial modeling approach

USGS Publications Warehouse

Lemons, P.R.; Sedinger, J.S.; Herzog, M.P.; Gipson, P.S.; Gilliland, R.L.

2010-01-01

Analyses of feces, stomach contents, and regurgitated pellets are common techniques for assessing diets of vertebrates and typically contain more than 1 food item per sampling unit. When analyzed, these individual food items have traditionally been treated as independent, which represents pseudoreplication. When food types are recorded as present or absent, these samples can be treated as multinomial vectors of food items, with each vector representing 1 realization of a possible diet. We suggest such data have a similar structure to capture histories for closed-capture, capturemarkrecapture data. To assess the effects of landscapes and presence of a potential competitor, we used closed-capture models implemented in program MARK into analyze diet data generated from feces of swift foxes (Vulpes velox) and coyotes (Canis latrans) in northwestern Texas. The best models of diet contained season and location for both swift foxes and coyotes, but year accounted for less variation, suggesting that landscape type is an important predictor of diets of both species. Models containing the effect of coyote reduction were not competitive (??QAICc 53.6685), consistent with the hypothesis that presence of coyotes did not influence diet of swift foxes. Our findings suggest that landscape type may have important influences on diets of both species. We believe that multinomial models represent an effective approach to assess hypotheses when diet studies have a data structure similar to ours. ?? 2010 American Society of Mammalogists.

Multinomial model and zero-inflated gamma model to study time spent on leisure time physical activity: an example of ELSA-Brasil.

PubMed

Nobre, Aline Araújo; Carvalho, Marilia Sá; Griep, Rosane Härter; Fonseca, Maria de Jesus Mendes da; Melo, Enirtes Caetano Prates; Santos, Itamar de Souza; Chor, Dora

2017-08-17

To compare two methodological approaches: the multinomial model and the zero-inflated gamma model, evaluating the factors associated with the practice and amount of time spent on leisure time physical activity. Data collected from 14,823 baseline participants in the Longitudinal Study of Adult Health (ELSA-Brasil - Estudo Longitudinal de Saúde do Adulto ) have been analysed. Regular leisure time physical activity has been measured using the leisure time physical activity module of the International Physical Activity Questionnaire. The explanatory variables considered were gender, age, education level, and annual per capita family income. The main advantage of the zero-inflated gamma model over the multinomial model is that it estimates mean time (minutes per week) spent on leisure time physical activity. For example, on average, men spent 28 minutes/week longer on leisure time physical activity than women did. The most sedentary groups were young women with low education level and income. The zero-inflated gamma model, which is rarely used in epidemiological studies, can give more appropriate answers in several situations. In our case, we have obtained important information on the main determinants of the duration of leisure time physical activity. This information can help guide efforts towards the most vulnerable groups since physical inactivity is associated with different diseases and even premature death.

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

Regression Models For Multivariate Count Data

PubMed Central

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2016-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data. PMID:28348500

Regression Models For Multivariate Count Data.

PubMed

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2017-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.

Extending health insurance in Ghana: effects of the National Health Insurance Scheme on maternity care.

PubMed

Brugiavini, Agar; Pace, Noemi

2016-12-01

There is considerable interest in exploring the potential of social health insurance in Africa where a number of countries are currently experimenting with different approaches. Since these schemes have been introduced recently and are continuously evolving, it is important to evaluate their effectiveness in the enhancement of health care utilization and reduction of out-of-pocket expenses for potential policy suggestions. To investigate how the National Health Insurance Schemes (NHIS) in Ghana affects the utilization of maternal health care services and medical out-of-pocket expenses. We used nationally-representative household data from the Ghana Demographic and Health Survey (GDHS). We analyzed the 2014 GDHS focusing on four outcome variables, i.e. antenatal check up, delivery in a health facility, delivery assisted by a trained person and out-of-pocket expenditure. We estimated probit and bivariate probit models to take into account the issue of self selection into the health insurance schemes. The results suggest that, also taking into account the issue of self selection into the health insurance schemes, the NHIS enrollment positively affects the probability of formal antenatal check-ups before delivery, the probability of delivery in an institution and the probability of being assisted during delivery by a trained person. On the contrary, we find that, once the issue of self-selection is taken into account, the NHIS enrollment does not have a significant effect on out-of-pocket expenditure at the extensive margin. Since a greater utilization of health-care services has a strong positive effect on the current and future health status of women and their children, the health-care authorities in Ghana should make every effort to extend this coverage. In particular, since the results of the first step of the bivariate probit regressions suggest that the educational attainment of women is a strong determinant of enrollment, and those with low education and unable to read are less likely to enroll, information on the NHIS should be disseminated in ways that reach those with little or no education. Moreover, the availability of government health facilities in a region is associated with higher likelihood of enrollment in the NHIS. Accordingly, extending geographical access is an important strategy for expanding NHIS membership and improving access to health-care.

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

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.

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.

Modelling the vicious circle between obesity and physical activity in children and adolescents using a bivariate probit model with endogenous regressors.

PubMed

Yeh, C-Y; Chen, L-J; Ku, P-W; Chen, C-M

2015-01-01

The increasing prevalence of obesity in children and adolescents has become one of the most important public health issues around the world. Lack of physical activity is a risk factor for obesity, while being obese could reduce the likelihood of participating in physical activity. Failing to account for the endogeneity between obesity and physical activity would result in biased estimation. This study investigates the relationship between overweight and physical activity by taking endogeneity into consideration. It develops an endogenous bivariate probit model estimated by the maximum likelihood method. The data included 4008 boys and 4197 girls in the 5th-9th grades in Taiwan in 2007-2008. The relationship between overweight and physical activity is significantly negative in the endogenous model, but insignificant in the comparative exogenous model. This endogenous relationship presents a vicious circle in which lower levels of physical activity lead to overweight, while those who are already overweight engage in less physical activity. The results not only reveal the importance of endogenous treatment, but also demonstrate the robust negative relationship between these two factors. An emphasis should be put on overweight and obese children and adolescents in order to break the vicious circle. Promotion of physical activity by appropriate counselling programmes and peer support could be effective in reducing the prevalence of obesity in children and adolescents.

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.

Estimation of rank correlation for clustered data.

PubMed

Rosner, Bernard; Glynn, Robert J

2017-06-30

It is well known that the sample correlation coefficient (R xy ) is the maximum likelihood estimator of the Pearson correlation (ρ xy ) for independent and identically distributed (i.i.d.) bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the maximum likelihood estimator of ρ xy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U_ of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (i) converting ranks of both X and Y to the probit scale, (ii) estimating the Pearson correlation between probit scores for X and Y, and (iii) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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.

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.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Emotionally enhanced memory for negatively arousing words: storage or retrieval advantage?

PubMed

Nadarevic, Lena

2017-12-01

People typically remember emotionally negative words better than neutral words. Two experiments are reported that investigate whether emotionally enhanced memory (EEM) for negatively arousing words is based on a storage or retrieval advantage. Participants studied non-word-word pairs that either involved negatively arousing or neutral target words. Memory for these target words was tested by means of a recognition test and a cued-recall test. Data were analysed with a multinomial model that allows the disentanglement of storage and retrieval processes in the present recognition-then-cued-recall paradigm. In both experiments the multinomial analyses revealed no storage differences between negatively arousing and neutral words but a clear retrieval advantage for negatively arousing words in the cued-recall test. These findings suggest that EEM for negatively arousing words is driven by associative processes.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

Chaibub Neto, Elias

2015-01-01

In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965

An efficient algorithm for accurate computation of the Dirichlet-multinomial log-likelihood function.

PubMed

Yu, Peng; Shaw, Chad A

2014-06-01

The Dirichlet-multinomial (DMN) distribution is a fundamental model for multicategory count data with overdispersion. This distribution has many uses in bioinformatics including applications to metagenomics data, transctriptomics and alternative splicing. The DMN distribution reduces to the multinomial distribution when the overdispersion parameter ψ is 0. Unfortunately, numerical computation of the DMN log-likelihood function by conventional methods results in instability in the neighborhood of [Formula: see text]. An alternative formulation circumvents this instability, but it leads to long runtimes that make it impractical for large count data common in bioinformatics. We have developed a new method for computation of the DMN log-likelihood to solve the instability problem without incurring long runtimes. The new approach is composed of a novel formula and an algorithm to extend its applicability. Our numerical experiments show that this new method both improves the accuracy of log-likelihood evaluation and the runtime by several orders of magnitude, especially in high-count data situations that are common in deep sequencing data. Using real metagenomic data, our method achieves manyfold runtime improvement. Our method increases the feasibility of using the DMN distribution to model many high-throughput problems in bioinformatics. We have included in our work an R package giving access to this method and a vingette applying this approach to metagenomic data. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Factors Associated with Substance Use in Adolescents with Eating Disorders

PubMed Central

Mann, Andrea P; Accurso, Erin C.; Stiles-Shields, Colleen; Capra, Lauren; Labuschagne, Zandre; Karnik, Niranjan S.; Grange, Daniel Le

2014-01-01

Purpose To examine the prevalence and potential risk factors associated with substance use in adolescents with eating disorders (EDs). Methods This cross-sectional study included 290 adolescents, ages 12 –18 years, who presented for an initial ED evaluation at The Eating Disorders Program at The University of Chicago Medicine (UCM) between 2001 and 2012. Several factors, including DSM-5 diagnosis, diagnostic scores, and demographic characteristics were examined. Multinomial logistic regression was used to test associations between several factors and patterns of drug use for alcohol, cannabis, tobacco, and any substance. Results Lifetime prevalence of any substance use was found to be 24.6% in those with anorexia nervosa (AN), 48.7% in bulimia nervosa (BN), and 28.6% in eating disorder not otherwise specified (EDNOS). Regular substance use (monthly, daily, and bingeing behaviors) or a substance use disorder (SUD) was found in 27.9% of all patients. Older age was the only factor associated with regular use of any substance in the final multinomial model. Older age and non-White race was associated with greater alcohol and cannabis use. Although binge-purge frequency and BN diagnosis were associated with regular substance use in bivariate analyses, gender, race and age were more robustly associated with substance use in the final multinomial models. Conclusions Co-morbid substance use in adolescents with EDs is an important issue. Interventions targeting high-risk groups reporting regular substance use or SUDs are needed. PMID:24656448

An investigation on fatality of drivers in vehicle-fixed object accidents on expressways in China: Using multinomial logistic regression model.

PubMed

Peng, Yong; Peng, Shuangling; Wang, Xinghua; Tan, Shiyang

2018-06-01

This study aims to identify the effects of characteristics of vehicle, roadway, driver, and environment on fatality of drivers in vehicle-fixed object accidents on expressways in Changsha-Zhuzhou-Xiangtan district of Hunan province in China by developing multinomial logistic regression models. For this purpose, 121 vehicle-fixed object accidents from 2011-2017 are included in the modeling process. First, descriptive statistical analysis is made to understand the main characteristics of the vehicle-fixed object crashes. Then, 19 explanatory variables are selected, and correlation analysis of each two variables is conducted to choose the variables to be concluded. Finally, five multinomial logistic regression models including different independent variables are compared, and the model with best fitting and prediction capability is chosen as the final model. The results showed that the turning direction in avoiding fixed objects raised the possibility that drivers would die. About 64% of drivers died in the accident were found being ejected out of the car, of which 50% did not use a seatbelt before the fatal accidents. Drivers are likely to die when they encounter bad weather on the expressway. Drivers with less than 10 years of driving experience are more likely to die in these accidents. Fatigue or distracted driving is also a significant factor in fatality of drivers. Findings from this research provide an insight into reducing fatality of drivers in vehicle-fixed object accidents.

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

The Spacetime Between Einstein and Kaluza-Klein: Further Explorations

NASA Astrophysics Data System (ADS)

Vuille, Chris

2017-01-01

Tensor multinomials can be used to create a generalization of Einstein's general relativity that in a mathematical sense falls between Einstein's original theory in four dimensions and the Kaluza-Klein theory in five dimensions. In the extended theory there are only four physical dimensions, but the tensor multinomials are expanded operators that can accommodate other forces of nature. The equivalent Ricci tensor of this geometry yields vacuum general relativity and electromagnetism, as well as a Klein-Gordon-like quantum scalar field. With a generalization of the stress-energy tensor, an exact solution for a plane-symmetric dust can be found where the scalar portion of the field drives early universe inflation, levels off for a period, then causes a later continued universal acceleration, a possible geometric mechanism for the inflaton or dark energy. Some new explorations of the equations, the problems, and possibilities will be presented and discussed.

Identification of nonclassical properties of light with multiplexing layouts

NASA Astrophysics Data System (ADS)

Sperling, J.; Eckstein, A.; Clements, W. R.; Moore, M.; Renema, J. J.; Kolthammer, W. S.; Nam, S. W.; Lita, A.; Gerrits, T.; Walmsley, I. A.; Agarwal, G. S.; Vogel, W.

2017-07-01

In Sperling et al. [Phys. Rev. Lett. 118, 163602 (2017), 10.1103/PhysRevLett.118.163602], we introduced and applied a detector-independent method to uncover nonclassicality. Here, we extend those techniques and give more details on the performed analysis. We derive a general theory of the positive-operator-valued measure that describes multiplexing layouts with arbitrary detectors. From the resulting quantum version of a multinomial statistics, we infer nonclassicality probes based on a matrix of normally ordered moments. We discuss these criteria and apply the theory to our data which are measured with superconducting transition-edge sensors. Our experiment produces heralded multiphoton states from a parametric down-conversion light source. We show that the known notions of sub-Poisson and sub-binomial light can be deduced from our general approach, and we establish the concept of sub-multinomial light, which is shown to outperform the former two concepts of nonclassicality for our data.

The multinomial simulation algorithm for discrete stochastic simulation of reaction-diffusion systems.

PubMed

Lampoudi, Sotiria; Gillespie, Dan T; Petzold, Linda R

2009-03-07

The Inhomogeneous Stochastic Simulation Algorithm (ISSA) is a variant of the stochastic simulation algorithm in which the spatially inhomogeneous volume of the system is divided into homogeneous subvolumes, and the chemical reactions in those subvolumes are augmented by diffusive transfers of molecules between adjacent subvolumes. The ISSA can be prohibitively slow when the system is such that diffusive transfers occur much more frequently than chemical reactions. In this paper we present the Multinomial Simulation Algorithm (MSA), which is designed to, on the one hand, outperform the ISSA when diffusive transfer events outnumber reaction events, and on the other, to handle small reactant populations with greater accuracy than deterministic-stochastic hybrid algorithms. The MSA treats reactions in the usual ISSA fashion, but uses appropriately conditioned binomial random variables for representing the net numbers of molecules diffusing from any given subvolume to a neighbor within a prescribed distance. Simulation results illustrate the benefits of the algorithm.

Verbal Ability and Persistent Offending: A Race-Specific Test of Moffitt's Theory

PubMed Central

Bellair, Paul E.; McNulty, Thomas L.; Piquero, Alex R.

2014-01-01

Theoretical questions linger over the applicability of the verbal ability model to African Americans and the social control theory hypothesis that educational failure mediates the effect of verbal ability on offending patterns. Accordingly, this paper investigates whether verbal ability distinguishes between offending groups within the context of Moffitt's developmental taxonomy. Questions are addressed with longitudinal data spanning childhood through young-adulthood from an ongoing national panel, and multinomial and hierarchical Poisson models (over-dispersed). In multinomial models, low verbal ability predicts membership in a life-course-persistent-oriented group relative to an adolescent-limited-oriented group. Hierarchical models indicate that verbal ability is associated with arrest outcomes among White and African American subjects, with effects consistently operating through educational attainment (high school dropout). The results support Moffitt's hypothesis that verbal deficits distinguish adolescent-limited- and life-course-persistent-oriented groups within race as well as the social control model of verbal ability. PMID:26924885

Identification of nonclassical properties of light with multiplexing layouts

PubMed Central

Sperling, J.; Eckstein, A.; Clements, W. R.; Moore, M.; Renema, J. J.; Kolthammer, W. S.; Nam, S. W.; Lita, A.; Gerrits, T.; Walmsley, I. A.; Agarwal, G. S.; Vogel, W.

2018-01-01

In Sperling et al. [Phys. Rev. Lett. 118, 163602 (2017)], we introduced and applied a detector-independent method to uncover nonclassicality. Here, we extend those techniques and give more details on the performed analysis. We derive a general theory of the positive-operator-valued measure that describes multiplexing layouts with arbitrary detectors. From the resulting quantum version of a multinomial statistics, we infer nonclassicality probes based on a matrix of normally ordered moments. We discuss these criteria and apply the theory to our data which are measured with superconducting transition-edge sensors. Our experiment produces heralded multiphoton states from a parametric down-conversion light source. We show that the known notions of sub-Poisson and sub-binomial light can be deduced from our general approach, and we establish the concept of sub-multinomial light, which is shown to outperform the former two concepts of nonclassicality for our data. PMID:29670949

Grouped gene selection and multi-classification of acute leukemia via new regularized multinomial regression.

PubMed

Li, Juntao; Wang, Yanyan; Jiang, Tao; Xiao, Huimin; Song, Xuekun

2018-05-09

Diagnosing acute leukemia is the necessary prerequisite to treating it. Multi-classification on the gene expression data of acute leukemia is help for diagnosing it which contains B-cell acute lymphoblastic leukemia (BALL), T-cell acute lymphoblastic leukemia (TALL) and acute myeloid leukemia (AML). However, selecting cancer-causing genes is a challenging problem in performing multi-classification. In this paper, weighted gene co-expression networks are employed to divide the genes into groups. Based on the dividing groups, a new regularized multinomial regression with overlapping group lasso penalty (MROGL) has been presented to simultaneously perform multi-classification and select gene groups. By implementing this method on three-class acute leukemia data, the grouped genes which work synergistically are identified, and the overlapped genes shared by different groups are also highlighted. Moreover, MROGL outperforms other five methods on multi-classification accuracy. Copyright © 2017. Published by Elsevier B.V.

MPTinR: analysis of multinomial processing tree models in R.

PubMed

Singmann, Henrik; Kellen, David

2013-06-01

We introduce MPTinR, a software package developed for the analysis of multinomial processing tree (MPT) models. MPT models represent a prominent class of cognitive measurement models for categorical data with applications in a wide variety of fields. MPTinR is the first software for the analysis of MPT models in the statistical programming language R, providing a modeling framework that is more flexible than standalone software packages. MPTinR also introduces important features such as (1) the ability to calculate the Fisher information approximation measure of model complexity for MPT models, (2) the ability to fit models for categorical data outside the MPT model class, such as signal detection models, (3) a function for model selection across a set of nested and nonnested candidate models (using several model selection indices), and (4) multicore fitting. MPTinR is available from the Comprehensive R Archive Network at http://cran.r-project.org/web/packages/MPTinR/ .

The empathy impulse: A multinomial model of intentional and unintentional empathy for pain.

PubMed

Cameron, C Daryl; Spring, Victoria L; Todd, Andrew R

2017-04-01

Empathy for pain is often described as automatic. Here, we used implicit measurement and multinomial modeling to formally quantify unintentional empathy for pain: empathy that occurs despite intentions to the contrary. We developed the pain identification task (PIT), a sequential priming task wherein participants judge the painfulness of target experiences while trying to avoid the influence of prime experiences. Using multinomial modeling, we distinguished 3 component processes underlying PIT performance: empathy toward target stimuli (Intentional Empathy), empathy toward prime stimuli (Unintentional Empathy), and bias to judge target stimuli as painful (Response Bias). In Experiment 1, imposing a fast (vs. slow) response deadline uniquely reduced Intentional Empathy. In Experiment 2, inducing imagine-self (vs. imagine-other) perspective-taking uniquely increased Unintentional Empathy. In Experiment 3, Intentional and Unintentional Empathy were stronger toward targets with typical (vs. atypical) pain outcomes, suggesting that outcome information matters and that effects on the PIT are not reducible to affective priming. Typicality of pain outcomes more weakly affected task performance when target stimuli were merely categorized rather than judged for painfulness, suggesting that effects on the latter are not reducible to semantic priming. In Experiment 4, Unintentional Empathy was stronger for participants who engaged in costly donation to cancer charities, but this parameter was also high for those who donated to an objectively worse but socially more popular charity, suggesting that overly high empathy may facilitate maladaptive altruism. Theoretical and practical applications of our modeling approach for understanding variation in empathy are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Using species spectra to evaluate plant community conservation value along a gradient of anthropogenic disturbance.

PubMed

Marcelino, José A P; Silva, Luís; Garcia, Patricia V; Weber, Everett; Soares, António O

2013-08-01

The aim of this study was to assess the impact of anthropogenic disturbance on the partitioning of plant communities (species spectra) across a landcover gradient of community types, categorizing species on the basis of their biogeographic, ecological, and conservation status. We tested a multinomial model to generate species spectra and monitor changes in plant assemblages as anthropogenic disturbance rise, as well as the usefulness of this method to assess the conservation value of a given community. Herbaceous and arborescent communities were sampled in five Azorean islands. Margins were also sampled to account for edge effects. Different multinomial models were applied to a data set of 348 plant species accounting for differences in parameter estimates among communities and/or islands. Different levels of anthropogenic disturbance produced measurable changes on species spectra. Introduced species proliferated and indigenous species declined, as anthropogenic disturbance and management intensity increased. Species assemblages of relevance other than economic (i.e., native, endemic, threatened species) were enclosed not only in natural habitats, but also in human managed arborescent habitats, which can positively contribute for the preservation of indigenous species outside remnants of natural areas, depending on management strategies. A significant presence of invasive species in margin transects of most community types will contribute to an increase in edge effect that might facilitate invasion. The multinomial model developed in this study was found to be a novel and expedient tool to characterize the species spectra at a given community and its use could be extrapolated for other assemblages or organisms, in order to evaluate and forecast the conservation value of a site.

OPTIMAL DESIGN FOR MULTINOMIAL CHOICE EXPERIMENTS. (R827987)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

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

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.

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.

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.

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.

Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis

ERIC Educational Resources Information Center

Ansari, Asim; Iyengar, Raghuram

2006-01-01

We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…

Estimation of Multinomial Probabilities.

DTIC Science & Technology

1978-11-01

1971) and Alam (1978) have shown that the maximum likelihood estimator is admissible with respect to the quadratic loss. Steinhaus (1957) and Trybula...appear). Johnson, B. Mck. (1971). On admissible estimators for certain fixed sample binomial populations. Ann. Math. Statist. 92, 1579-1587. Steinhaus , H

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

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

Caregiver Burdens and Preventive Dental Care for Children with Autism Spectrum Disorder, Developmental Disability and/or Mental Health Conditions: National Survey of CSHCN, 2009-2010.

PubMed

Wiener, R Constance; Vohra, Rini; Sambamoorthi, Usha; Madhavan, S Suresh

2016-12-01

Objective The purpose of this study is to examine the burdens of caregivers on perception of the need and receipt of preventive dental care for a subset of children with special health care needs-children with Autism Spectrum disorder, developmental disability and/or mental health conditions (CASD/DD/MHC). Methods The authors used the 2009-2010 National Survey of CSHCN. The survey included questions addressing preventive dental care and caregivers' financial, employment, and time-related burdens. The associations of these burdens on perceptions and receipt of preventive dental care use were analyzed with bivariate Chi square analyses and multinomial logistic regressions for CASD/DD/MHC (N = 16,323). Results Overall, 16.3 % of CASD/DD/MHC had an unmet preventive dental care need. There were 40.0 % of caregivers who reported financial burden, 20.3 % who reported employment burden, and 10.8 % who reported time burden. A higher percentage of caregivers with financial burden, employment burden, and time-related burden reported that their CASD/DD/MHC did not receive needed preventive dental care (14.1, 16.5, 17.7 % respectively) compared to caregivers without financial, employment, or time burdens (9.0, 9.6 %, 11.0 % respectively). Caregivers with financial burden (adjusted multinomial odds ratio, 1.38 [95 % CI 1.02, 1.86] and employment burden (adjusted multinomial odds ratio, 1.45 [95 % CI 1.02, 2.06] were more likely to report that their child did not receive preventive dental care despite perceived need compared to caregivers without financial or employment burdens. Conclusions for practice Unmet needs for preventive dental care were associated with employment and financial burdens of the caregivers of CASD/DD/MHC.

Caregiver Burdens and Preventive Dental Care for Children with Autism Spectrum disorder, developmental disability and/or mental health conditions: National Survey of CSHCN, 2009–10

PubMed Central

Vohra, Rini; Sambamoorthi, Usha; Madhavan, S. Suresh

2016-01-01

Objective The purpose of this study is to examine the burdens of caregivers on one perception of the need and receipt of preventive dental care for a subset of children with special health care needs—children with Autism Spectrum disorder, developmental disability and/or mental health conditions (CASD/DD/MHC). Methods The authors used the 2009–2010 National Survey of CSHCN. The survey included questions addressing preventive dental care and caregivers’ financial, employment, and time-related burdens. The associations of these burdens on perceptions and receipt of preventive dental care use were analyzed with bivariate Chi square analyses and multinomial logistic regressions for CASD/DD/MHC (N=16,323). Results Overall, 16.3% of CASD/DD/MHC had an unmet preventive dental care need. There were 40.0% of caregivers who reported financial burden, 20.3% who reported employment burden, and 10.8% who reported time burden. A higher percentage of caregivers with financial burden, employment burden, and time-related burden reported that their CASD/DD/MHC did not receive needed preventive dental care (14.1 %, 16.5%, 17.7% respectively) compared to caregivers without financial, employment, or time burdens (9.0%, 9.6%, 11.0% respectively). Caregivers with financial burden (adjusted multinomial odds ratio, 1.38 [95%CI: 1.02, 1.86]) and employment burden (adjusted multinomial odds ratio, 1.45 [95%CI: 1.02, 2.06]) were more likely to report that their child did not receive preventive dental care despite perceived need compared to caregivers without financial or employment burdens. Conclusions for practice Unmet needs for preventive dental care were associated with employment and financial burdens of the caregivers of CASD/DD/MHC. PMID:27465058

A Comparison of Methods for Detecting Differential Distractor Functioning

ERIC Educational Resources Information Center

Koon, Sharon

2010-01-01

This study examined the effectiveness of the odds-ratio method (Penfield, 2008) and the multinomial logistic regression method (Kato, Moen, & Thurlow, 2009) for measuring differential distractor functioning (DDF) effects in comparison to the standardized distractor analysis approach (Schmitt & Bleistein, 1987). Students classified as participating…

Use of negative multinomial linear models to investigate environmental effects on community structure.

EPA Science Inventory

A frequent goal in ecology is to understand the relationships between biological communities and their environment. Anderson and McCardle (2001) provided a nonparametric method, known as Permanova, that is often used for this purpose. Permanova represents a significant advance,...

Statistical Development and Application of Cultural Consensus Theory

DTIC Science & Technology

2012-03-31

Bulletin & Review , 17, 275-286. Schmittmann, V.D., Dolan, C.V., Raijmakers, M.E.J., and Batchelder, W.H. (2010). Parameter identification in...Wu, H., Myung, J.I., and Batchelder, W.H. (2010). Minimum description length model selection of multinomial processing tree models. Psychonomic

Predicting The Type Of Pregnancy Using Flexible Discriminate Analysis And Artificial Neural Networks: A Comparison Study

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

Hooman, A.; Mohammadzadeh, M

Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. With regard to the type of pregnancy there are four possible states: wanted, unwanted by wife, unwanted by husband and unwanted by couple. In this paper, we have predicted the type of pregnancy, as well as the factors influencing it using three different models and comparing them. Regarding the type of pregnancy with several levels, we developed a multinomial logistic regression, a neural network and a flexible discrimination based on the data and compared their results using tow statistical indices: Surface under curvemore » (ROC) and kappa coefficient. Based on these tow indices, flexible discrimination proved to be a better fit for prediction on data in comparison to other methods. When the relations among variables are complex, one can use flexible discrimination instead of multinomial logistic regression and neural network to predict the nominal response variables with several levels in order to gain more accurate predictions.« less

Making sense of sparse rating data in collaborative filtering via topographic organization of user preference patterns.

PubMed

Polcicová, Gabriela; Tino, Peter

2004-01-01

We introduce topographic versions of two latent class models (LCM) for collaborative filtering. Latent classes are topologically organized on a square grid. Topographic organization of latent classes makes orientation in rating/preference patterns captured by the latent classes easier and more systematic. The variation in film rating patterns is modelled by multinomial and binomial distributions with varying independence assumptions. In the first stage of topographic LCM construction, self-organizing maps with neural field organized according to the LCM topology are employed. We apply our system to a large collection of user ratings for films. The system can provide useful visualization plots unveiling user preference patterns buried in the data, without loosing potential to be a good recommender model. It appears that multinomial distribution is most adequate if the model is regularized by tight grid topologies. Since we deal with probabilistic models of the data, we can readily use tools from probability and information theories to interpret and visualize information extracted by our system.

A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

Congdon, Peter

2010-02-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.

Compensation of hospital-based physicians.

PubMed Central

Steinwald, B

1983-01-01

This study is concerned with methods of compensating hospital-based physicians (HBPs) in five medical specialties: anesthesiology, pathology, radiology, cardiology, and emergency medicine. Data on 2232 nonfederal, short-term general hospitals came from a mail questionnaire survey conducted in Fall 1979. The data indicate that numerous compensation methods exist but these methods, without much loss of precision, can be reduced to salary, percentage of department revenue, and fee-for-service. When HBPs are compensated by salary or percentage methods, most patient billing is conducted by the hospital. In contrast, most fee-for-service HBPs bill their patients directly. Determinants of HBP compensation methods are investigated via multinomial logit analysis. This analysis indicates that choice of HBP compensation methods are investigated via multinomial logit analysis. This analysis indicates that choice of HBP compensation methods is sensitive to a number of hospital characteristics and attributes of both the hospital and physicians' services markets. The empirical findings are discussed in light of past conceptual and empirical research on physician compensation, and current policy issues in the health services sector. PMID:6841112

Modeling Information Content Via Dirichlet-Multinomial Regression Analysis.

PubMed

Ferrari, Alberto

2017-01-01

Shannon entropy is being increasingly used in biomedical research as an index of complexity and information content in sequences of symbols, e.g. languages, amino acid sequences, DNA methylation patterns and animal vocalizations. Yet, distributional properties of information entropy as a random variable have seldom been the object of study, leading to researchers mainly using linear models or simulation-based analytical approach to assess differences in information content, when entropy is measured repeatedly in different experimental conditions. Here a method to perform inference on entropy in such conditions is proposed. Building on results coming from studies in the field of Bayesian entropy estimation, a symmetric Dirichlet-multinomial regression model, able to deal efficiently with the issue of mean entropy estimation, is formulated. Through a simulation study the model is shown to outperform linear modeling in a vast range of scenarios and to have promising statistical properties. As a practical example, the method is applied to a data set coming from a real experiment on animal communication.

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.

Association Between System Reach and Exposure to Interventions and Characteristics of Mobile Female Sex Workers in Four High HIV Prevalence States in India

PubMed Central

Sharma, Varun; Saggurti, Niranjan; Bharat, Shalini

2015-01-01

Mobility among Female Sex Workers (FSWs) interrupts their demand for, and utilization of, health services under any intervention. Various strategic interventions are meant to provide access to care and reduce the incidence of HIV and other STIs among FSWs. This paper applies a bivariate probit regression analysis to explain the probability of mobile FSWs being reached by the system and being exposed to interventions jointly with a wide variety of characteristics of mobile FSWs in India. The data used are based on a cross-section survey among 5,498 mobile FSWs in 22 districts of four high HIV prevalence states in southern India. A majority of mobile FSWs (59%) were street-based and about 70 percent of them were members of SW organization and nearly half (46%) were highly mobile. The majority of them (90%) had been contacted by outreach workers from any system in the last two years in their current location and 94 percent were exposed to interventions in terms of getting free or subsidized condoms. Bivariate probit analysis revealed that comprehensive interventions are able to reach more vulnerable mobile FSWs effectively, e.g. new entrants, highly mobile, reported STIs, tested for HIV ever and serving a high volume of clients. The results complement the efforts of government and other agencies in response to HIV. However, the results highlight that specific issues related to various subgroups of this highly vulnerable population remain unaddressed calling for tailoring the response to the specific needs of the sub-groups. PMID:25946932

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.

Predictors of Early Termination in a University Counseling Training Clinic

ERIC Educational Resources Information Center

Lampropoulos, Georgios K.; Schneider, Mercedes K.; Spengler, Paul M.

2009-01-01

Despite the existence of counseling dropout research, there are limited predictive data for counseling in training clinics. Potential predictor variables were investigated in this archival study of 380 client files in a university counseling training clinic. Multinomial logistic regression, predictive discriminant analysis, and classification and…

Understanding Civic Identity in College

ERIC Educational Resources Information Center

Weerts, David J.; Cabrera, Alberto F.

2015-01-01

Past literature has examined ways in which college students adopt civic identities. However, little is known about characteristics of students that vary in their expression of these identities. Drawing on data from American College Testing (ACT), this study employs multinomial logistic regression to understand attributes of students who vary in…

Evaluating the Locational Attributes of Education Management Organizations (EMOs)

ERIC Educational Resources Information Center

Gulosino, Charisse; Miron, Gary

2017-01-01

This study uses logistic and multinomial logistic regression models to analyze neighborhood factors affecting EMO (Education Management Organization)-operated schools' locational attributes (using census tracts) in 41 states for the 2014-2015 school year. Our research combines market-based school reform, institutional theory, and resource…

Intergroup Relations and Predictors of Immigrant Experience

ERIC Educational Resources Information Center

Danso, Kofi; Lum, Terry

2013-01-01

Using survey data from 1,036 participants, which included 4 immigrant groups, we examined the factors that influence immigrants' experiences as they interact with nonimmigrant Americans. Logistic and multinomial regression results indicate that non-European immigrants were more likely to report negative experiences with Americans. The odds of…

The Role of Predictor Courses and Teams on Individual Student Success

ERIC Educational Resources Information Center

Baker-Eveleth, Lori Jo; O'Neill, Michele; Sisodiya, Sanjay R.

2014-01-01

Research suggests that diverse environments enhance conscious modes of thought, resulting in greater intellectual engagement and active thinking. Ordinal and multinomial logistic regression results indicate that accounting courses and business law classes are useful predictors of subsequent performance. Odds ratio estimates indicate that students…

Choice-Based Segmentation as an Enrollment Management Tool

ERIC Educational Resources Information Center

Young, Mark R.

2002-01-01

This article presents an approach to enrollment management based on target marketing strategies developed from a choice-based segmentation methodology. Students are classified into "switchable" or "non-switchable" segments based on their probability of selecting specific majors. A modified multinomial logit choice model is used to identify…

Caregivers' Retirement Congruency: A Case for Caregiver Support

ERIC Educational Resources Information Center

Humble, Aine M.; Keefe, Janice M.; Auton, Greg M.

2012-01-01

Using the concept of "retirement congruency" (RC), which takes into account greater variation in retirement decisions (low, moderate, or high RC) than a dichotomous conceptualization (forced versus chosen), multinomial logistic regression was conducted on a sample of caregivers from the 2002 Canadian General Social Survey who were…

The Mixed Effects Trend Vector Model

ERIC Educational Resources Information Center

de Rooij, Mark; Schouteden, Martijn

2012-01-01

Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical…

Race and Unemployment: Labor Market Experiences of Black and White Men, 1968-1988.

ERIC Educational Resources Information Center

Wilson, Franklin D.; And Others

1995-01-01

Estimation of multinomial logistic regression models on a sample of unemployed workers suggested that persistently higher black unemployment is due to differential access to employment opportunities by region, occupational placement, labor market segmentation, and discrimination. The racial gap in unemployment is greatest for college-educated…

Test Design Project: Studies in Test Adequacy. Annual Report.

ERIC Educational Resources Information Center

Wilcox, Rand R.

These studies in test adequacy focus on two problems: procedures for estimating reliability, and techniques for identifying ineffective distractors. Fourteen papers are presented on recent advances in measuring achievement (a response to Molenaar); "an extension of the Dirichlet-multinomial model that allows true score and guessing to be…

Saving for Success: Financial Education and Savings Goal Achievement in Individual Development Accounts

ERIC Educational Resources Information Center

Grinstead, Mary L.; Mauldin, Teresa; Sabia, Joseph J.; Koonce, Joan; Palmer, Lance

2011-01-01

Using microdata from the American Dream Demonstration, the current study examines factors associated with savings and savings goal achievement (indicated by a matched withdrawal) among participants of individual development account (IDA) programs. Multinomial logit results show that hours of participation in financial education programs, higher…

Predicting the Frequency of Senior Center Attendance.

ERIC Educational Resources Information Center

Miner, Sonia; And Others

1993-01-01

Used data from 1984 Supplement on Aging of the National Health Interview Survey to examine frequency of senior center attendance. Estimated multinomial logistic regression model to distinguish between persons who rarely, sometimes, and frequently attend. Found that more frequent users are older. Greater frequency was associated with lower income…

Support vector machines classifiers of physical activities in preschoolers

USDA-ARS?s Scientific Manuscript database

The goal of this study is to develop, test, and compare multinomial logistic regression (MLR) and support vector machines (SVM) in classifying preschool-aged children physical activity data acquired from an accelerometer. In this study, 69 children aged 3-5 years old were asked to participate in a s...

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

ERIC Educational Resources Information Center

Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei

2015-01-01

This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…

An Investigation of the Representativeness Heuristic: The Case of a Multiple Choice Exam

ERIC Educational Resources Information Center

Chernoff, Egan J.; Mamolo, Ami; Zazkis, Rina

2016-01-01

By focusing on a particular alteration of the comparative likelihood task, this study contributes to research on teachers' understanding of probability. Our novel task presented prospective teachers with multinomial, contextualized sequences and asked them to identify which was least likely. Results demonstrate that determinants of…

Bullying and PTSD Symptoms

ERIC Educational Resources Information Center

Idsoe, Thormod; Dyregrov, Atle; Idsoe, Ella Cosmovici

2012-01-01

PTSD symptoms related to school bullying have rarely been investigated, and never in national samples. We used data from a national survey to investigate this among students from grades 8 and 9 (n = 963). The prevalence estimates of exposure to bullying were within the range of earlier research findings. Multinomial logistic regression showed that…

University-Industry Linkages in Developing Countries: Perceived Effect on Innovation

ERIC Educational Resources Information Center

Vaaland, Terje I.; Ishengoma, Esther

2016-01-01

Purpose: The purpose of this paper is to assess the perceptions of both universities and the resource-extractive companies on the influence of university-industry linkages (UILs) on innovation in a developing country. Design/Methodology/Approach: A total of 404 respondents were interviewed. Descriptive analysis and multinomial logistic regression…

Diversity and Educational Benefits: Moving Beyond Self-Reported Questionnaire Data

ERIC Educational Resources Information Center

Herzog, Serge

2007-01-01

Effects of ethnic/racial diversity among students and faculty on cognitive growth of undergraduate students are estimated via a series of hierarchical linear and multinomial logistic regression models. Using objective measures of compositional, curricular, and interactional diversity based on actuarial course enrollment records of over 6,000…

Poverty and Material Hardship in Grandparent-Headed Households

ERIC Educational Resources Information Center

Baker, Lindsey A.; Mutchler, Jan E.

2010-01-01

Using the 2001 Survey of Income and Program Participation, the current study examines poverty and material hardship among children living in 3-generation (n = 486), skipped-generation (n = 238), single-parent (n = 2,076), and 2-parent (n = 6,061) households. Multinomial and logistic regression models indicated that children living in…

Victimization and Health Risk Factors among Weapon-Carrying Youth

ERIC Educational Resources Information Center

Stayton, Catherine; McVeigh, Katharine H.; Olson, E. Carolyn; Perkins, Krystal; Kerker, Bonnie D.

2011-01-01

Objective: To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. Methods: 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Results: Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization.…

In-State Tuition Policies for Undocumented Youth

ERIC Educational Resources Information Center

Vargas, Edward D.

2011-01-01

This article is an investigation into why U.S. states have enacted, banned, or continued with the status quo regarding in-state tuition policies for unauthorized youth. Using data from multiple government and nonprofit sources, a series of multinomial logistic regressions are estimated to explain the determinants of state behavior across the…

Taxes and Bribes in Uganda.

PubMed

Jagger, Pamela; Shively, Gerald

Using data from 433 firms operating along Uganda's charcoal and timber supply chains we investigate patterns of bribe payment and tax collection between supply chain actors and government officials responsible for collecting taxes and fees. We examine the factors associated with the presence and magnitude of bribe and tax payments using a series of bivariate probit and Tobit regression models. We find empirical support for a number of hypotheses related to payments, highlighting the role of queuing, capital-at-risk, favouritism, networks, and role in the supply chain. We also find that taxes crowd-in bribery in the charcoal market.

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 effect of maternal healthcare on the probability of child survival in Azerbaijan.

PubMed

Habibov, Nazim; Fan, Lida

2014-01-01

This study assesses the effects of maternal healthcare on child survival by using nonrandomized data from a cross-sectional survey in Azerbaijan. Using 2SLS and simultaneous equation bivariate probit models, we estimate the effects of delivering in healthcare facility on probability of child survival taking into account self-selection into the treatment. For women who delivered at healthcare facilities, the probability of child survival increases by approximately 18%. Furthermore, if every woman had the opportunity to deliver in healthcare facility, then the probability of child survival in Azerbaijan as a whole would have increased by approximately 16%.

Taxes and Bribes in Uganda

PubMed Central

Jagger, Pamela; Shively, Gerald

2016-01-01

Using data from 433 firms operating along Uganda’s charcoal and timber supply chains we investigate patterns of bribe payment and tax collection between supply chain actors and government officials responsible for collecting taxes and fees. We examine the factors associated with the presence and magnitude of bribe and tax payments using a series of bivariate probit and Tobit regression models. We find empirical support for a number of hypotheses related to payments, highlighting the role of queuing, capital-at-risk, favouritism, networks, and role in the supply chain. We also find that taxes crowd-in bribery in the charcoal market. PMID:27274568

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

Which Kindergarten Children Are at Greatest Risk for Attention-Deficit/Hyperactivity and Conduct Disorder Symptomatology as Adolescents?

ERIC Educational Resources Information Center

Morgan, Paul L.; Li, Hui; Cook, Michael; Farkas, George; Hillemeier, Marianne M.; Lin, Yu-chu

2016-01-01

We sought to identify which kindergarten children are simultaneously at risk of moderate or severe symptomatology in both attention-deficit/hyperactivity disorder (ADHD) and conduct disorder (CD) as adolescents. These risk factor estimates have not been previously available. We conducted multinomial logistic regression analyses of multiinformant…

A Simplified Conjoint Recognition Paradigm for the Measurement of Gist and Verbatim Memory

ERIC Educational Resources Information Center

Stahl, Christoph; Klauer, Karl Christoph

2008-01-01

The distinction between verbatim and gist memory traces has furthered the understanding of numerous phenomena in various fields, such as false memory research, research on reasoning and decision making, and cognitive development. To measure verbatim and gist memory empirically, an experimental paradigm and multinomial measurement model has been…

Foreign Diploma versus Immigrant Background: Determinants of Labour Market Success or Failure?

ERIC Educational Resources Information Center

Storen, Liv Anne; Wiers-Jenssen, Jannecke

2010-01-01

This article compares the labour market situation of graduates with different types of international background. The authors look at four groups of graduates: immigrants and ethnic Norwegians graduated in Norway and immigrants and ethnic Norwegians graduated abroad. By employing multinomial logistic regression analyses the authors find that ethnic…

Motivations and Benefits for Attaining HR Certifications

ERIC Educational Resources Information Center

Lester, Scott W.; Dwyer, Dale J.

2012-01-01

Purpose: The aim of this paper is to examine the motivations and benefits for pursuing or not pursuing the PHR and SPHR. Design/methodology/approach: Using a sample of 1,862 participants, the study used multinomial logistic and hierarchical linear regression to test six hypotheses. Findings: Participants pursuing SPHR were more likely to report…

Latent spatial models and sampling design for landscape genetics

Treesearch

Ephraim M. Hanks; Melvin B. Hooten; Steven T. Knick; Sara J. Oyler-McCance; Jennifer A. Fike; Todd B. Cross; Michael K. Schwartz

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial...

LIA at TREC 2012 Web Track: Unsupervised Search Concepts Identification from General Sources of Information

DTIC Science & Technology

2012-11-01

use in this work the variational approximation algo- rithm implemented and distributed by Pr . Blei1. Each learned multinomial distribution φk is tra...4,111,240 newswire articles collected from four distinct international sources including the New York Times (Graff and Cieri, 2003). The New York Times

Early Family Formation among White, Black, and Mexican American Women

ERIC Educational Resources Information Center

Landale, Nancy S.; Schoen, Robert; Daniels, Kimberly

2010-01-01

Using data from Waves I and III of Add Health, this study examines early family formation among 6,144 White, Black, and Mexican American women. Drawing on cultural and structural perspectives, models of the first and second family transitions (cohabitation, marriage, or childbearing) are estimated using discrete-time multinomial logistic…

Relationship Status, Psychological Orientation, and Sexual Risk Taking in a Heterosexual African American College Sample

ERIC Educational Resources Information Center

Winfield, Evelyn B.; Whaley, Arthur L.

2005-01-01

The present study examined relationship status, psychological orientation toward sexual risk taking, and other characteristics as potential correlates of risky sexual behavior in a sample of 223 heterosexual African American college students. Risky sexual behavior was investigated as a multinomial variable (i.e., abstinence, consistent condom use,…

School Climate: The Controllable and the Uncontrollable

ERIC Educational Resources Information Center

Sulak, Tracey N.

2018-01-01

A positive school climate impacts students by promoting positive relations among students, staff and faculty of the school. The current study used latent class analysis and multinomial regression with R3STEP to analyse patterns of negative behaviours in schools and test the association of these patterns with structural variables like school size,…

Bayesian Network Meta-Analysis for Unordered Categorical Outcomes with Incomplete Data

ERIC Educational Resources Information Center

Schmid, Christopher H.; Trikalinos, Thomas A.; Olkin, Ingram

2014-01-01

We develop a Bayesian multinomial network meta-analysis model for unordered (nominal) categorical outcomes that allows for partially observed data in which exact event counts may not be known for each category. This model properly accounts for correlations of counts in mutually exclusive categories and enables proper comparison and ranking of…

Using Computational Text Classification for Qualitative Research and Evaluation in Extension

ERIC Educational Resources Information Center

Smith, Justin G.; Tissing, Reid

2018-01-01

This article introduces a process for computational text classification that can be used in a variety of qualitative research and evaluation settings. The process leverages supervised machine learning based on an implementation of a multinomial Bayesian classifier. Applied to a community of inquiry framework, the algorithm was used to identify…

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

Ian A. Munn; David Cleaves

1998-01-01

Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...

Racial Threat and White Opposition to Bilingual Education in Texas

ERIC Educational Resources Information Center

Hempel, Lynn M.; Dowling, Julie A.; Boardman, Jason D.; Ellison, Christopher G.

2013-01-01

This study examines local contextual conditions that influence opposition to bilingual education among non-Hispanic Whites, net of individual-level characteristics. Data from the Texas Poll (N = 615) are used in conjunction with U.S. Census data to test five competing hypotheses using binomial and multinomial logistic regression models. Our…

Application of a Multidimensional Nested Logit Model to Multiple-Choice Test Items

ERIC Educational Resources Information Center

Bolt, Daniel M.; Wollack, James A.; Suh, Youngsuk

2012-01-01

Nested logit models have been presented as an alternative to multinomial logistic models for multiple-choice test items (Suh and Bolt in "Psychometrika" 75:454-473, 2010) and possess a mathematical structure that naturally lends itself to evaluating the incremental information provided by attending to distractor selection in scoring. One potential…

Two-Phase Item Selection Procedure for Flexible Content Balancing in CAT

ERIC Educational Resources Information Center

Cheng, Ying; Chang, Hua-Hua; Yi, Qing

2007-01-01

Content balancing is an important issue in the design and implementation of computerized adaptive testing (CAT). Content-balancing techniques that have been applied in fixed content balancing, where the number of items from each content area is fixed, include constrained CAT (CCAT), the modified multinomial model (MMM), modified constrained CAT…

Caste, Class, and Urbanization: The Shaping of Religious Community in Contemporary India

ERIC Educational Resources Information Center

Stroope, Samuel

2012-01-01

Building on the implications of qualitative work from India and urbanism theories, I aim to understand whether religious bonding social capital in contemporary India increases with greater urbanization and whether such increases are moderated by caste or social class position. Results from multinomial logistic regression on 1,417 Hindu respondents…

American Youths' Access to Substance Abuse Treatment: Does Type of Treatment Facility Matter?

ERIC Educational Resources Information Center

Lo, Celia C.; Cheng, Tyrone C.

2013-01-01

Using data from the 2007 National Survey on Drug Use and Health, this study examines whether several social exclusion and psychological factors affect adolescents' receipt of substance abuse treatment. Multinomial logistic regression techniques were used to analyze data. The study asked how the specified factors provide pathways to receipt of…

Primary Factors Related to Multiple Placements for Children in Out-of-Home Care

ERIC Educational Resources Information Center

Eggertsen, Lars

2008-01-01

Using an ecological framework, this study identified which factors related to out-of-home placements significantly influenced multiple placements for children in Utah during 2000, 2001, and 2002. Multinomial logistic regression statistical procedures and a geographical information system (GIS) were used to analyze the data. The final model…

Beyond ROC Curvature: Strength Effects and Response Time Data Support Continuous-Evidence Models of Recognition Memory

ERIC Educational Resources Information Center

Dube, Chad; Starns, Jeffrey J.; Rotello, Caren M.; Ratcliff, Roger

2012-01-01

A classic question in the recognition memory literature is whether retrieval is best described as a continuous-evidence process consistent with signal detection theory (SDT), or a threshold process consistent with many multinomial processing tree (MPT) models. Because receiver operating characteristics (ROCs) based on confidence ratings are…

Leavers, Movers, and Stayers: The Role of Workplace Conditions in Teacher Mobility Decisions

ERIC Educational Resources Information Center

Kukla-Acevedo, Sharon

2009-01-01

The author explored whether 3 workplace conditions were related to teacher mobility decisions. The modeling strategy incorporated a series of binomial and multinomial logistic models to estimate the effects of administrative support, classroom control, and behavioral climate on teachers' decisions to quit teaching or switch schools. The results…

Institutional Discharges and Subsequent Shelter Use among Unaccompanied Adults in New York City

ERIC Educational Resources Information Center

Metraux, Stephen; Byrne, Thomas; Culhane, Dennis P.

2010-01-01

This study empirically examines the link between homelessness and discharges from other institutions. An administrative record match was undertaken to determine rates of discharge from institutional care for 9,247 unaccompanied adult shelter users in New York City. Cluster analysis and multinomial logistic regression analysis was then used to…

Predicting Teacher Value-Added Results in Non-Tested Subjects Based on Confounding Variables: A Multinomial Logistic Regression

ERIC Educational Resources Information Center

Street, Nathan Lee

2017-01-01

Teacher value-added measures (VAM) are designed to provide information regarding teachers' causal impact on the academic growth of students while controlling for exogenous variables. While some researchers contend VAMs successfully and authentically measure teacher causality on learning, others suggest VAMs cannot adequately control for exogenous…

Profiles of Supportive Alumni: Donors, Volunteers, and Those Who "Do It All"

ERIC Educational Resources Information Center

Weerts, David J.; Ronca, Justin M.

2007-01-01

In the competitive marketplace of higher education, college and university alumni are increasingly called on to support their institutions in multiple ways: political advocacy, volunteerism, and charitable giving. Drawing on alumni survey data gathered from a large research extensive university, we employ a multinomial logistic regression model to…

Using Discrete Loss Functions and Weighted Kappa for Classification: An Illustration Based on Bayesian Network Analysis

ERIC Educational Resources Information Center

Zwick, Rebecca; Lenaburg, Lubella

2009-01-01

In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…

Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing

Treesearch

John Hogland; Nedret Billor; Nathaniel Anderson

2013-01-01

Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...

Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use among Students

ERIC Educational Resources Information Center

Merianos, Ashley L.; Rosen, Brittany L.; Montgomery, LaTrice; Barry, Adam E.; Smith, Matthew Lee

2017-01-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data (N=937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime…

Predicting College Success: Achievement, Demographic, and Psychosocial Predictors of First-Semester College Grade Point Average

ERIC Educational Resources Information Center

Saltonstall, Margot

2013-01-01

This study seeks to advance and expand research on college student success. Using multinomial logistic regression analysis, the study investigates the contribution of psychosocial variables above and beyond traditional achievement and demographic measures to predicting first-semester college grade point average (GPA). It also investigates if…

New machine-learning algorithms for prediction of Parkinson's disease

NASA Astrophysics Data System (ADS)

Mandal, Indrajit; Sairam, N.

2014-03-01

This article presents an enhanced prediction accuracy of diagnosis of Parkinson's disease (PD) to prevent the delay and misdiagnosis of patients using the proposed robust inference system. New machine-learning methods are proposed and performance comparisons are based on specificity, sensitivity, accuracy and other measurable parameters. The robust methods of treating Parkinson's disease (PD) includes sparse multinomial logistic regression, rotation forest ensemble with support vector machines and principal components analysis, artificial neural networks, boosting methods. A new ensemble method comprising of the Bayesian network optimised by Tabu search algorithm as classifier and Haar wavelets as projection filter is used for relevant feature selection and ranking. The highest accuracy obtained by linear logistic regression and sparse multinomial logistic regression is 100% and sensitivity, specificity of 0.983 and 0.996, respectively. All the experiments are conducted over 95% and 99% confidence levels and establish the results with corrected t-tests. This work shows a high degree of advancement in software reliability and quality of the computer-aided diagnosis system and experimentally shows best results with supportive statistical inference.

A panel multinomial logit analysis of elderly living arrangements: evidence from Aging In Manitoba longitudinal data, Canada.

PubMed

Sarma, Sisira; Simpson, Wayne

2007-12-01

Utilizing a unique longitudinal survey linked with home care use data, this paper analyzes the determinants of elderly living arrangements in Manitoba, Canada using a random effects multinomial logit model that accounts for unobserved individual heterogeneity. Because current home ownership is potentially endogenous in a living arrangements choice model, we use prior home ownership as an instrument. We also use prior home care use as an instrument for home care and use a random coefficient framework to account for unobserved health status. After controlling for relevant socio-demographic factors and accounting for unobserved individual heterogeneity, we find that home care and home ownership reduce the probability of living in a nursing home. Consistent with previous studies, we find that age is a strong predictor of nursing home entry. We also find that married people, those who have lived longer in the same community, and those who are healthy are more likely to live independently and less likely to be institutionalized or to cohabit with individuals other than their spouse.

Profiles of internalizing and externalizing symptoms associated with bullying victimization.

PubMed

Eastman, Meridith; Foshee, Vangie; Ennett, Susan; Sotres-Alvarez, Daniela; Reyes, H Luz McNaughton; Faris, Robert; North, Kari

2018-06-01

This study identified profiles of internalizing (anxiety and depression) and externalizing (delinquency and violence against peers) symptoms among bullying victims and examined associations between bullying victimization characteristics and profile membership. The sample consisted of 1196 bullying victims in grades 8-10 (M age  = 14.4, SD = 1.01) who participated in The Context Study in three North Carolina counties in Fall 2003. Five profiles were identified using latent profile analysis: an asymptomatic profile and four profiles capturing combinations of internalizing and externalizing symptoms. Associations between bullying characteristics and membership in symptom profiles were tested using multinomial logistic regression. More frequent victimization increased odds of membership in the two high internalizing profiles compared to the asymptomatic profile. Across all multinomial logistic regression models, when the high internalizing, high externalizing profile was the reference category, adolescents who received any type of bullying (direct, indirect, or dual) were more likely to be in this category than any others. Copyright © 2018 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Prevalence of and risk factors for depressive symptoms among people living with HIV/AIDS receiving antiretroviral treatment in Wuhan, China: a short report.

PubMed

Rong, Hu; Nianhua, Xie; Jun, Xu; Lianguo, Ruan; Si, Wu; Sheng, Wei; Heng, Guo; Xia, Wang

2017-12-01

We aimed to explore the prevalence of and risk factors for depressive symptoms (DS) among people living with HIV/AIDS (PLWHA) receiving antiretroviral treatment (ART) in Wuhan, Hubei, China. A cross-sectional study evaluating adult PLWHA receiving ART in nine designated clinical hospitals was conducted from October to December 2015. The validated Beck Depression Inventory (BDI) was used to assess DS in eligible participants. Socio-demographical, epidemiological and clinical data were directly extracted from the case reporting database of the China HIV/AIDS Information Network. Multinomial regression analysis was used to explore the risk factors for DS. 394 participants were finally included in all analyses. 40.3% were found to have DS with 13.7% having mild DS and 26.6% having moderate to severe DS. The results of multinomial regression analysis suggested that being married or living with a partner, recent experience of ART-related side effects, and/or history of HCV infection were positively associated with mild DS, while increasing age was positively associated with moderate to severe DS.

A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US

PubMed Central

Congdon, Peter

2010-01-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk. PMID:20616977

Body mass index and employment status: A new look.

PubMed

Kinge, Jonas Minet

2016-09-01

Earlier literature has usually modelled the impact of obesity on employment status as a binary choice (employed, yes/no). I provide new evidence on the impact of obesity on employment status by treating the dependent variable as a as a multinomial choice variable. Using data from a representative English survey, with measured height and weight on parents and children, I define employment status as one of four: working; looking for paid work; permanently not working due to disability; and, looking after home or family. I use a multinomial logit model controlling for a set of covariates. I also run instrumental variable models, instrumenting for Body Mass Index (BMI) based on genetic variation in weight. I find that BMI and obesity significantly increase the probability of "not working due to disability". The results for the other employment outcomes are less clear. My findings also indicate that BMI affects employment through its effect on health. Factors other than health may be less important in explaining the impact of BMI/obesity on employment. Copyright © 2016 Elsevier B.V. All rights reserved.

The perception of the relationship between environment and health according to data from Italian Behavioural Risk Factor Surveillance System (PASSI).

PubMed

Sampaolo, Letizia; Tommaso, Giulia; Gherardi, Bianca; Carrozzi, Giuliano; Freni Sterrantino, Anna; Ottone, Marta; Goldoni, Carlo Alberto; Bertozzi, Nicoletta; Scaringi, Meri; Bolognesi, Lara; Masocco, Maria; Salmaso, Stefania; Lauriola, Paolo

2017-01-01

"OBJECTIVES: to identify groups of people in relation to the perception of environmental risk and to assess the main characteristics using data collected in the environmental module of the surveillance network Italian Behavioral Risk Factor Surveillance System (PASSI). perceptive profiles were identified using a latent class analysis; later they were included as outcome in multinomial logistic regression models to assess the association between environmental risk perception and demographic, health, socio-economic and behavioural variables. the latent class analysis allowed to split the sample in "worried", "indifferent", and "positive" people. The multinomial logistic regression model showed that the "worried" profile typically includes people of Italian nationality, living in highly urbanized areas, with a high level of education, and with economic difficulties; they pay special attention to their own health and fitness, but they have a negative perception of their own psychophysical state. the application of advanced statistical analysis enable to appraise PASSI data in order to characterize the perception of environmental risk, making the planning of interventions related to risk communication possible. ".

Socio-economic determinants of severe and moderate stunting among under-five children of rural Bangladesh.

PubMed

Mostafa, Kamal S M

2011-04-01

Malnutrition among under-five children is a chronic problem in developing countries. This study explores the socio-economic determinants of severe and moderate stunting among under-five children of rural Bangladesh. The study used data from the 2007 Bangladesh Demographic and Health Survey. Cross-sectional and multinomial logistic regression analyses were used to assess the effect of the socio-demographic variables on moderate and severe stunting over normal among the children. Findings revealed that over two-fifths of the children were stunted, of which 26.3% were moderately stunted and 15.1% were severely stunted. The multivariate multinomial logistic regression analysis yielded significantly increased risk of severe stunting (OR=2.53, 95% CI=1.34-4.79) and moderate stunting (OR=2.37, 95% CI=1.47-3.83) over normal among children with a thinner mother. Region, father's education, toilet facilities, child's age, birth order of children and wealth index were also important determinants of children's nutritional status. Development and poverty alleviation programmes should focus on the disadvantaged rural segments of people to improve their nutritional status.

Towards dropout training for convolutional neural networks.

PubMed

Wu, Haibing; Gu, Xiaodong

2015-11-01

Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this insight, we advocate employing our proposed probabilistic weighted pooling, instead of commonly used max-pooling, to act as model averaging at test time. Empirical evidence validates the superiority of probabilistic weighted pooling. We also empirically show that the effect of convolutional dropout is not trivial, despite the dramatically reduced possibility of over-fitting due to the convolutional architecture. Elaborately designing dropout training simultaneously in max-pooling and fully-connected layers, we achieve state-of-the-art performance on MNIST, and very competitive results on CIFAR-10 and CIFAR-100, relative to other approaches without data augmentation. Finally, we compare max-pooling dropout and stochastic pooling, both of which introduce stochasticity based on multinomial distributions at pooling stage. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling pedestrian shopping behavior using principles of bounded rationality: model comparison and validation

NASA Astrophysics Data System (ADS)

Zhu, Wei; Timmermans, Harry

2011-06-01

Models of geographical choice behavior have been dominantly based on rational choice models, which assume that decision makers are utility-maximizers. Rational choice models may be less appropriate as behavioral models when modeling decisions in complex environments in which decision makers may simplify the decision problem using heuristics. Pedestrian behavior in shopping streets is an example. We therefore propose a modeling framework for pedestrian shopping behavior incorporating principles of bounded rationality. We extend three classical heuristic rules (conjunctive, disjunctive and lexicographic rule) by introducing threshold heterogeneity. The proposed models are implemented using data on pedestrian behavior in Wang Fujing Street, the city center of Beijing, China. The models are estimated and compared with multinomial logit models and mixed logit models. Results show that the heuristic models are the best for all the decisions that are modeled. Validation tests are carried out through multi-agent simulation by comparing simulated spatio-temporal agent behavior with the observed pedestrian behavior. The predictions of heuristic models are slightly better than those of the multinomial logit models.

A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

PubMed

Bersabé, Rosa; Rivas, Teresa

2010-05-01

The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.

A general class of multinomial mixture models for anuran calling survey data

USGS Publications Warehouse

Royle, J. Andrew; Link, W.A.

2005-01-01

We propose a general framework for modeling anuran abundance using data collected from commonly used calling surveys. The data generated from calling surveys are indices of calling intensity (vocalization of males) that do not have a precise link to actual population size and are sensitive to factors that influence anuran behavior. We formulate a model for calling-index data in terms of the maximum potential calling index that could be observed at a site (the 'latent abundance class'), given its underlying breeding population, and we focus attention on estimating the distribution of this latent abundance class. A critical consideration in estimating the latent structure is imperfect detection, which causes the observed abundance index to be less than or equal to the latent abundance class. We specify a multinomial sampling model for the observed abundance index that is conditional on the latent abundance class. Estimation of the latent abundance class distribution is based on the marginal likelihood of the index data, having integrated over the latent class distribution. We apply the proposed modeling framework to data collected as part of the North American Amphibian Monitoring Program (NAAMP).

Modeling health survey data with excessive zero and K responses.

PubMed

Lin, Ting Hsiang; Tsai, Min-Hsiao

2013-04-30

Zero-inflated Poisson regression is a popular tool used to analyze data with excessive zeros. Although much work has already been performed to fit zero-inflated data, most models heavily depend on special features of the individual data. To be specific, this means that there is a sizable group of respondents who endorse the same answers making the data have peaks. In this paper, we propose a new model with the flexibility to model excessive counts other than zero, and the model is a mixture of multinomial logistic and Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts, including zeros, K (where K is a positive integer) and all other values. The Poisson regression component models the counts that are assumed to follow a Poisson distribution. Two examples are provided to illustrate our models when the data have counts containing many ones and sixes. As a result, the zero-inflated and K-inflated models exhibit a better fit than the zero-inflated Poisson and standard Poisson regressions. Copyright © 2012 John Wiley & Sons, Ltd.

The Effect of Stochastic Perturbation of Fuel Distribution on the Criticality of a One Speed Reactor and the Development of Multi-Material Multinomial Line Statistics

NASA Technical Reports Server (NTRS)

Jahshan, S. N.; Singleterry, R. C.

2001-01-01

The effect of random fuel redistribution on the eigenvalue of a one-speed reactor is investigated. An ensemble of such reactors that are identical to a homogeneous reference critical reactor except for the fissile isotope density distribution is constructed such that it meets a set of well-posed redistribution requirements. The average eigenvalue, , is evaluated when the total fissile loading per ensemble element, or realization, is conserved. The perturbation is proven to increase the reactor criticality on average when it is uniformly distributed. The various causes of the change in reactivity, and their relative effects are identified and ranked. From this, a path towards identifying the causes. and relative effects of reactivity fluctuations for the energy dependent problem is pointed to. The perturbation method of using multinomial distributions for representing the perturbed reactor is developed. This method has some advantages that can be of use in other stochastic problems. Finally, some of the features of this perturbation problem are related to other techniques that have been used for addressing similar problems.

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.

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.

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.

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.

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

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.

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.

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.

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.

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).

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.

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.

Dietary Fiber Intake Is Inversely Associated with Periodontal Disease among US Adults.

PubMed

Nielsen, Samara Joy; Trak-Fellermeier, Maria Angelica; Joshipura, Kaumudi; Dye, Bruce A

2016-12-01

Approximately 47% of adults in the United States have periodontal disease. Dietary guidelines recommend a diet providing adequate fiber. Healthier dietary habits, particularly an increased fiber intake, may contribute to periodontal disease prevention. Our objective was to evaluate the relation of dietary fiber intake and its sources with periodontal disease in the US adult population (≥30 y of age). Data from 6052 adults participating in NHANES 2009-2012 were used. Periodontal disease was defined (according to the CDC/American Academy of Periodontology) as severe, moderate, mild, and none. Intake was assessed by 24-h dietary recalls. The relation between periodontal disease and dietary fiber, whole-grain, and fruit and vegetable intakes were evaluated by using multivariate models, adjusting for sociodemographic characteristics and dentition status. In the multivariate logistic model, the lowest quartile of dietary fiber was associated with moderate-severe periodontitis (compared with mild-none) compared with the highest dietary fiber intake quartile (OR: 1.30; 95% CI: 1.00, 1.69). In the multivariate multinomial logistic model, intake in the lowest quartile of dietary fiber was associated with higher severity of periodontitis than dietary fiber intake in the highest quartile (OR: 1.27; 95% CI: 1.00, 1.62). In the adjusted logistic model, whole-grain intake was not associated with moderate-severe periodontitis. However, in the adjusted multinomial logistic model, adults consuming whole grains in the lowest quartile were more likely to have more severe periodontal disease than were adults consuming whole grains in the highest quartile (OR: 1.32; 95% CI: 1.08, 1.62). In fully adjusted logistic and multinomial logistic models, fruit and vegetable intake was not significantly associated with periodontitis. We found an inverse relation between dietary fiber intake and periodontal disease among US adults ≥30 y old. Periodontal disease was associated with low whole-grain intake but not with low fruit and vegetable intake. © 2016 American Society for Nutrition.

"The empathy impulse: A multinomial model of intentional and unintentional empathy for pain": Correction.

PubMed

2018-04-01

Reports an error in "The empathy impulse: A multinomial model of intentional and unintentional empathy for pain" by C. Daryl Cameron, Victoria L. Spring and Andrew R. Todd ( Emotion , 2017[Apr], Vol 17[3], 395-411). In this article, there was an error in the calculation of some of the effect sizes. The w effect size was manually computed incorrectly. The incorrect number of total observations was used, which affected the final effect size estimates. This computing error does not change any of the results or interpretations about model fit based on the G² statistic, or about significant differences across conditions in process parameters. Therefore, it does not change any of the hypothesis tests or conclusions. The w statistics for overall model fit should be .02 instead of .04 in Study 1, .01 instead of .02 in Study 2, .01 instead of .03 for the OIT in Study 3 (model fit for the PIT remains the same: .00), and .02 instead of .03 in Study 4. The corrected tables can be seen here: http://osf.io/qebku at the Open Science Framework site for the article. (The following abstract of the original article appeared in record 2017-01641-001.) Empathy for pain is often described as automatic. Here, we used implicit measurement and multinomial modeling to formally quantify unintentional empathy for pain: empathy that occurs despite intentions to the contrary. We developed the pain identification task (PIT), a sequential priming task wherein participants judge the painfulness of target experiences while trying to avoid the influence of prime experiences. Using multinomial modeling, we distinguished 3 component processes underlying PIT performance: empathy toward target stimuli (Intentional Empathy), empathy toward prime stimuli (Unintentional Empathy), and bias to judge target stimuli as painful (Response Bias). In Experiment 1, imposing a fast (vs. slow) response deadline uniquely reduced Intentional Empathy. In Experiment 2, inducing imagine-self (vs. imagine-other) perspective-taking uniquely increased Unintentional Empathy. In Experiment 3, Intentional and Unintentional Empathy were stronger toward targets with typical (vs. atypical) pain outcomes, suggesting that outcome information matters and that effects on the PIT are not reducible to affective priming. Typicality of pain outcomes more weakly affected task performance when target stimuli were merely categorized rather than judged for painfulness, suggesting that effects on the latter are not reducible to semantic priming. In Experiment 4, Unintentional Empathy was stronger for participants who engaged in costly donation to cancer charities, but this parameter was also high for those who donated to an objectively worse but socially more popular charity, suggesting that overly high empathy may facilitate maladaptive altruism. Theoretical and practical applications of our modeling approach for understanding variation in empathy are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.

How Effective Are Severe Disciplinary Policies? School Policies and Offending from Adolescence into Young Adulthood

ERIC Educational Resources Information Center

Matjasko, Jennifer L.

2011-01-01

Based on the stage environment and the person environment fit perspectives, the current study examined the relation between school disciplinary policies and offending from adolescence into young adulthood. Using Waves I and III of the National Longitudinal Study of Adolescent Health (a.k.a., Add Health), hierarchical multinomial logistic…

Primary and Secondary Socialization Impacts on Support for Same-Sex Marriage after Legalization in the Netherlands

ERIC Educational Resources Information Center

Lubbers, Marcel; Jaspers, Eva; Ultee, Wout

2009-01-01

Two years after the legalization of same-sex marriages in the Netherlands, 65% of the Dutch population largely or completely disagrees with the statement "gay marriage should be abolished." This article shows, by way of multinomial logistic regression analysis of survey data, which socializing agents influence one's attitude toward…

Large Sample Confidence Limits for Goodman and Kruskal's Proportional Prediction Measure TAU-b

ERIC Educational Resources Information Center

Berry, Kenneth J.; Mielke, Paul W.

1976-01-01

A Fortran Extended program which computes Goodman and Kruskal's Tau-b, its asymmetrical counterpart, Tau-a, and three sets of confidence limits for each coefficient under full multinomial and proportional stratified sampling is presented. A correction of an error in the calculation of the large sample standard error of Tau-b is discussed.…

The Association between Electronic Bullying and School Absenteeism among High School Students in the United States

ERIC Educational Resources Information Center

Grinshteyn, Erin; Yang, Y. T.

2017-01-01

Background: We examined the relationship between exposure to electronic bullying and absenteeism as a result of being afraid. Methods: This multivariate, multinomial regression analysis of the 2013 Youth Risk Behavior Survey data assessed the association between experiencing electronic bullying in the past year and how often students were absent…

Perpetration of Intimate Partner Aggression by Men and Women in the Philippines: Prevalence and Associated Factors

ERIC Educational Resources Information Center

Ansara, Donna L.; Hindin, Michelle J.

2009-01-01

This study uses data from the 2002 Cebu Longitudinal Health and Nutrition Survey to examine the prevalence of and factors associated with intimate partner violence perpetration by husbands and wives in Cebu, Philippines. Multinomial logistic regression was used to identify the factors associated with wife-only, husband-only, and reciprocal…

Using Multidimensional Rasch Analysis to Validate the Chinese Version of the Motivated Strategies for Learning Questionnaire (MSLQ-CV)

ERIC Educational Resources Information Center

Lee, John Chi-Kin; Zhang, Zhonghua; Yin, Hongbiao

2010-01-01

This article used the multidimensional random coefficients multinomial logit model to examine the construct validity and detect the substantial differential item functioning (DIF) of the Chinese version of motivated strategies for learning questionnaire (MSLQ-CV). A total of 1,354 Hong Kong junior high school students were administered the…

Persistent Nonmedical Use of Prescription Stimulants among College Students: Possible Association with ADHD Symptoms

ERIC Educational Resources Information Center

Arria, Amelia M.; Garnier-Dykstra, Laura M.; Caldeira, Kimberly M.; Vincent, Kathryn B.; O'Grady, Kevin E.; Wish, Eric D.

2011-01-01

Objective: To investigate the possible association between untreated ADHD symptoms (as measured by the Adult ADHD Self-Report Scale) and persistent nonmedical use of prescription stimulants. Method: Multinomial regression modeling was used to compare ADHD symptoms among three groups of college students enrolled in a longitudinal study over 4…

Random Walks on a Simple Cubic Lattice, the Multinomial Theorem, and Configurational Properties of Polymers

ERIC Educational Resources Information Center

Hladky, Paul W.

2007-01-01

Random-climb models enable undergraduate chemistry students to visualize polymer molecules, quantify their configurational properties, and relate molecular structure to a variety of physical properties. The model could serve as an introduction to more elaborate models of polymer molecules and could help in learning topics such as lattice models of…

A Multinomial Model for Identifying Significant Pure-Tone Threshold Shifts

ERIC Educational Resources Information Center

Schlauch, Robert S.; Carney, Edward

2007-01-01

Purpose: Significant threshold differences on retest for pure-tone audiometry are often evaluated by application of ad hoc rules, such as a shift in a pure-tone average or in 2 adjacent frequencies that exceeds a predefined amount. Rules that are so derived do not consider the probability of observing a particular audiogram. Methods: A general…

How Framing Statistical Statements Affects Subjective Veracity: Validation and Application of a Multinomial Model for Judgments of Truth

ERIC Educational Resources Information Center

Hilbig, Benjamin E.

2012-01-01

Extending the well-established negativity bias in human cognition to truth judgments, it was recently shown that negatively framed statistical statements are more likely to be considered true than formally equivalent statements framed positively. However, the underlying processes responsible for this effect are insufficiently understood.…

A Multilevel Study of Students' Motivations of Studying Accounting: Implications for Employers

ERIC Educational Resources Information Center

Law, Philip; Yuen, Desmond

2012-01-01

Purpose: The purpose of this study is to examine the influence of factors affecting students' choice of accounting as a study major in Hong Kong. Design/methodology/approach: Multinomial logistic regression and Hierarchical Generalized Linear Modeling (HGLM) are used to analyze the survey data for the level one and level two data, which is the…

The Dirichlet-Multinomial Model for Multivariate Randomized Response Data and Small Samples

ERIC Educational Resources Information Center

Avetisyan, Marianna; Fox, Jean-Paul

2012-01-01

In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The beta-binomial model for binary RR data will be generalized…

Implementing Sympson-Hetter Item-Exposure Control in a Shadow-Test Approach to Constrained Adaptive Testing

ERIC Educational Resources Information Center

Veldkamp, Bernard P.; van der Linden, Wim J.

2008-01-01

In most operational computerized adaptive testing (CAT) programs, the Sympson-Hetter (SH) method is used to control the exposure of the items. Several modifications and improvements of the original method have been proposed. The Stocking and Lewis (1998) version of the method uses a multinomial experiment to select items. For severely constrained…

Belonging to and Exclusion from the Peer Group in Schools: Influences on Adolescents' Moral Choices

ERIC Educational Resources Information Center

Feigenberg, Luba Falk; King, Melissa Steel; Barr, Dennis J.; Selman, Robert L.

2008-01-01

This paper reports on a mixed methods study of adolescents' responses to case material about social exclusion. First, a qualitative coding method is presented that describes the way adolescents choose and justify strategies to negotiate such situations. The responses were then analysed quantitatively using chi square tests and multinomial logistic…

Behavioral and Emotional Strengths among Youth in Systems of Care and the Effect of Race/Ethnicity

ERIC Educational Resources Information Center

Barksdale, Crystal L.; Azur, Melissa; Daniels, Amy M.

2010-01-01

Behavioral and emotional strengths are important to consider when understanding youth mental health and treatment. This study examined the association between youth strengths and functional impairment and whether this association is modified by race/ethnicity. Multinomial logistic regression models were used to estimate the effects of strengths on…

Religiosity Profiles of American Youth in Relation to Substance Use, Violence, and Delinquency

ERIC Educational Resources Information Center

Salas-Wright, Christopher P.; Vaughn, Michael G.; Hodge, David R.; Perron, Brian E.

2012-01-01

Relatively little is known in terms of the relationship between religiosity profiles and adolescents' involvement in substance use, violence, and delinquency. Using a diverse sample of 17,705 (49 % female) adolescents from the 2008 National Survey on Drug Use and Health, latent profile analysis and multinomial regression are employed to examine…

Testing an Online English Course: Lessons Learned from an Analysis of Postcourse Proficiency Change Scores

ERIC Educational Resources Information Center

Jee, Rebecca Y.

2015-01-01

Voxy, an English-language-learning company, has developed a custom, in-house proficiency exam, the Voxy Proficiency Assessment (VPA), which is given to all learners at the beginning and end of their courses. Using Multinomial Logistic Regression (MLR), the impact of covariates, such as total learning activities completed and total number of…

Using multinomial logistic regression analysis to understand anglers willingness to substitute other fishing locations

Treesearch

Woo-Yong Hyun; Robert B. Ditton

2007-01-01

The concept of recreation substitutability has been a continuing research topic for outdoor recreation researchers. This study explores the relationships among variables regarding the willingness to substitute one location for another location. The objectives of the study are 1) to ascertain and predict the extent to which saltwater anglers were willing to substitute...

School Exits in the Milwaukee Parental Choice Program: Evidence of a Marketplace?

ERIC Educational Resources Information Center

Ford, Michael

2011-01-01

This article examines whether the large number of school exits from the Milwaukee school voucher program is evidence of a marketplace. Two logistic regression and multinomial logistic regression models tested the relation between the inability to draw large numbers of voucher students and the ability for a private school to remain viable. Data on…

So Close, yet So Far Away: Early vs. Late Dropouts

ERIC Educational Resources Information Center

Ma, Yanli; Cragg, Kristina M.

2013-01-01

While some students drop out early in their academic career, others drop out close to completion. What similarities and differences exist between these early and late dropouts? Using a sample 3,520 first-time, full-time (FTFT) students seeking a bachelor's degree at a state university, this study employs multinomial logistic regression to model…

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.

2007-01-01

Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…

A Multinomial Logit Model of Attrition that Distinguishes between Stopout and Dropout Behavior

ERIC Educational Resources Information Center

Stratton, Leslie S.; O'Toole, Dennis M.; Wetzel, James N.

2004-01-01

College attrition rates are of substantial concern to policy makers and economists interested in educational attainment and earnings opportunities. This is not surprising since nationwide, almost one-third of all first-time college students fail to return for their sophomore year. There exists a substantial body of literature seeking to model this…

High School Predictors of College Persistence: The Significance of Engagement and Teacher Interaction

ERIC Educational Resources Information Center

Sciarra, Daniel T.; Seirup, Holly J.; Sposato, Elizabeth

2016-01-01

This study investigated factors from high school that might predict college persistence. The sample consisted of 7,271 participants in three waves of data collection (2002, 2004 and 2006) who participated in the Educational Longitudinal Study (ELS; U.S. Department of Education, 2008). A multinomial logistic regression mode was employed to…

Application of binomial and multinomial probability statistics to the sampling design process of a global grain tracing and recall system

USDA-ARS?s Scientific Manuscript database

Small, coded, pill-sized tracers embedded in grain are proposed as a method for grain traceability. A sampling process for a grain traceability system was designed and investigated by applying probability statistics using a science-based sampling approach to collect an adequate number of tracers fo...

A Multinomial Logit Approach to Estimating Regional Inventories by Product Class

Treesearch

Lawrence Teeter; Xiaoping Zhou

1998-01-01

Current timber inventory projections generally lack information on inventory by product classes. Most models available for inventory projection and linked to supply analyses are limited to projecting aggregate softwood and hardwood. The objective of this research is to develop a methodology to distribute the volume on each FIA survey plot to product classes and...

Generalized Partial Least Squares Approach for Nominal Multinomial Logit Regression Models with a Functional Covariate

ERIC Educational Resources Information Center

Albaqshi, Amani Mohammed H.

2017-01-01

Functional Data Analysis (FDA) has attracted substantial attention for the last two decades. Within FDA, classifying curves into two or more categories is consistently of interest to scientists, but multi-class prediction within FDA is challenged in that most classification tools have been limited to binary response applications. The functional…

False Memory for Orthographically versus Semantically Similar Words in Adolescents with Dyslexia: A Fuzzy-Trace Theory Perspective

ERIC Educational Resources Information Center

Obidzinski, Michal; Nieznanski, Marek

2017-01-01

The presented research was conducted in order to investigate the connections between developmental dyslexia and the functioning of verbatim and gist memory traces--assumed in the fuzzy-trace theory. The participants were 71 high school students (33 with dyslexia and 38 without learning difficulties). The modified procedure and multinomial model of…

Emergency Department Use by Nursing Home Residents: Effect of Severity of Cognitive Impairment

ERIC Educational Resources Information Center

Stephens, Caroline E.; Newcomer, Robert; Blegen, Mary; Miller, Bruce; Harrington, Charlene

2012-01-01

Purpose: To examine the 1-year prevalence and risk of emergency department (ED) use and ambulatory care-sensitive (ACS) ED use by nursing home (NH) residents with different levels of severity of cognitive impairment (CI). Design and Methods: We used multinomial logistic regression to estimate the effect of CI severity on the odds of any ED visit…

Comparative Evaluation of Two Methods to Estimate Natural Gas Production in Texas

EIA Publications

2003-01-01

This report describes an evaluation conducted by the Energy Information Administration (EIA) in August 2003 of two methods that estimate natural gas production in Texas. The first method (parametric method) was used by EIA from February through August 2003 and the second method (multinomial method) replaced it starting in September 2003, based on the results of this evaluation.

An Exploration of Teacher Attrition and Mobility in High Poverty Racially Segregated Schools

ERIC Educational Resources Information Center

Djonko-Moore, Cara M.

2016-01-01

The purpose of this study was to examine the mobility (movement to a new school) and attrition (quitting teaching) patterns of teachers in high poverty, racially segregated (HPRS) schools in the US. Using 2007-9 survey data from the National Center for Education Statistics, a multi-level multinomial logistic regression was performed to examine the…

The analysis of the pilot's cognitive and decision processes

NASA Technical Reports Server (NTRS)

Curry, R. E.

1975-01-01

Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

A Process View on Implementing an Antibullying Curriculum: How Teachers Differ and What Explains the Variation

ERIC Educational Resources Information Center

Haataja, Anne; Ahtola, Annarilla; Poskiparta, Elisa; Salmivalli, Christina

2015-01-01

The present study provides a person-centered view on teachers' adherence to the KiVa antibullying curriculum over a school year. Factor mixture modeling was used to examine how teachers (N = 282) differed in their implementation profiles and multinomial logistic regression was used to identify factors related to these profiles. On the basis of…

Emotional Reactions to Stress among Adolescent Boys and Girls: An Examination of the Mediating Mechanisms Proposed by General Strain Theory

ERIC Educational Resources Information Center

Sigfusdottir, Inga-Dora; Silver, Eric

2009-01-01

This study examines the effects of negative life events on anger and depressed mood among a sample of 7,758 Icelandic adolescents, measured as part of the National Survey of Icelandic Adolescents (Thorlindsson, Sigfusdottir, Bernburg, & Halldorsson, 1998). Using multiple linear regression and multinomial logit regression, we find that (a)…

A Typology of Work-Family Arrangements among Dual-Earner Couples in Norway

ERIC Educational Resources Information Center

Kitterod, Ragni Hege; Lappegard, Trude

2012-01-01

A symmetrical family model of two workers or caregivers is a political goal in many western European countries. We explore how common this family type is in Norway, a country with high gender-equality ambitions, by using a multinomial latent class model to develop a typology of dual-earner couples with children based on the partners' allocations…

The Effects of Secondary Special Education Preparation in Reading: Research to Inform State Policy in a New Era

ERIC Educational Resources Information Center

Knackstedt, Kimberly M.; Leko, Melinda M.; Siuty, Molly Baustien

2018-01-01

In this study, the authors present findings from a survey of 577 secondary special educators in a large Midwestern state regarding their reading pre-service and in-service teacher preparation and its effect on teachers' sense of preparedness for teaching reading to adolescents with disabilities. Six models were fitted using multinomial logistic…

Multinomial-Regression Modeling of the Environmental Attitudes of Higher Education Students Based on the Revised New Ecological Paradigm Scale

ERIC Educational Resources Information Center

Jowett, Tim; Harraway, John; Lovelock, Brent; Skeaff, Sheila; Slooten, Liz; Strack, Mick; Shephard, Kerry

2014-01-01

Higher education is increasingly interested in its impact on the sustainability attributes of its students, so we wanted to explore how our students' environmental concern changed during their higher education experiences. We used the Revised New Ecological Paradigm Scale (NEP) with 505 students and developed and tested a multinomial…

The Effect of Participating in Indiana's Twenty-First Century Scholars Program on College Enrollments

ERIC Educational Resources Information Center

Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S.

2015-01-01

Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…

Limited-Information Goodness-of-Fit Testing of Diagnostic Classification Item Response Theory Models. CRESST Report 840

ERIC Educational Resources Information Center

Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen

2014-01-01

It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2]?? and the likelihood ratio statistic…

How School Choice Is Framed by Parental Preferences and Family Characteristics: A Study of Western Area, Sierra Leone

ERIC Educational Resources Information Center

Dixon, Pauline; Humble, Steve

2017-01-01

This research set out to investigate how, in a post-conflict area, parental preferences and household characteristics affect school choice for their children. A multinomial logit is used to model the relationship between education preferences and the selection of schools for 954 households in Freetown and neighboring districts, Western Area,…

The Design and Analysis of Salmonid Tagging Studies in the Columbia Basin; Volume XII; A Multinomial Model for Estimating Ocean Survival from Salmonid Coded Wire-Tag Data.

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

Ryding, Kristen E.; Skalski, John R.

1999-06-01

The purpose of this report is to illustrate the development of a stochastic model using coded wire-tag (CWT) release and age-at-return data, in order to regress first year ocean survival probabilities against coastal ocean conditions and climate covariates.

Latent profile analysis of regression-based norms demonstrates relationship of compounding MS symptom burden and negative work events.

PubMed

Frndak, Seth E; Smerbeck, Audrey M; Irwin, Lauren N; Drake, Allison S; Kordovski, Victoria M; Kunker, Katrina A; Khan, Anjum L; Benedict, Ralph H B

2016-10-01

We endeavored to clarify how distinct co-occurring symptoms relate to the presence of negative work events in employed multiple sclerosis (MS) patients. Latent profile analysis (LPA) was utilized to elucidate common disability patterns by isolating patient subpopulations. Samples of 272 employed MS patients and 209 healthy controls (HC) were administered neuroperformance tests of ambulation, hand dexterity, processing speed, and memory. Regression-based norms were created from the HC sample. LPA identified latent profiles using the regression-based z-scores. Finally, multinomial logistic regression tested for negative work event differences among the latent profiles. Four profiles were identified via LPA: a common profile (55%) characterized by slightly below average performance in all domains, a broadly low-performing profile (18%), a poor motor abilities profile with average cognition (17%), and a generally high-functioning profile (9%). Multinomial regression analysis revealed that the uniformly low-performing profile demonstrated a higher likelihood of reported negative work events. Employed MS patients with co-occurring motor, memory and processing speed impairments were most likely to report a negative work event, classifying them as uniquely at risk for job loss.

Sex-related perceptions associated with sexual activity status among Japanese adolescents who heavily use text messaging.

PubMed

Kawamura, Yoko

2012-01-01

This study examines the relationship between sex-related perceptions and engagement in sexual intercourse among adolescents in Japan who were heavy users of text massaging. Using the data from the 6th National Survey on Youth Sexual Behavior of 548 high school students who heavily use text messaging, multinomial logistic regression analyses on variables constructing sexual norms and gender-role attitudes were conducted to assess the relationship with sexual activity status as the first step. A backward stepwise elimination method of multinomial logistic regression was used as the second step at which variables for each set of two factors were tested, and as the third step at which variables of two factors were simultaneously tested. The study results showed that perceptions were related to engagement in sexual intercourse among adolescents who heavily used text messaging. In particular, those who perceived that sex is an act to be engaged in at an earlier stage of a relationship and that men have a stronger sex drive tended to be sexually active or have experienced sexual intercourse. These findings could be utilized to design more effective sexual health education messages for Japanese adolescents who are at an elevated risk.

Factors associated with happiness in the elderly persons living in the community.

PubMed

Luchesi, Bruna Moretti; de Oliveira, Nathalia Alves; de Morais, Daiene; de Paula Pessoa, Rebeca Mendes; Pavarini, Sofia Cristina I; Chagas, Marcos Hortes N

2018-01-01

The aim of the present study was to evaluate factors associated with happiness in a sample of Brazilian older adults. A study was conducted with 263 elderly people in the area of coverage of a family health unit located in the state of São Paulo, Brazil. The Subjective Happiness Scale was used to measure happiness, the final score of which determined one of three outcomes: not happy, intermediate, and happy. Disability, sociodemographic characteristics, and psychological, cognitive, and physical factors were considered for the multinomial logistic regression analysis. Statistically significant differences were found among the three groups regarding satisfaction with life, disability, social phobia, anxiety, depression, and frailty (p≤0.05). In the multinomial regression analysis, being "not happy" was significantly associated with satisfaction with life (RRR: 0.53), depression (RRR: 1.46), social phobia (RRR: 1.24), and age (RRR: 1.06). The present findings indicate that psychological factors and age influence the levels of happiness in older adults living in the community. Furthermore, better screening, diagnosis, and treatment of mental health disorders could increase the feeling of happiness among older adults. Copyright © 2017 Elsevier B.V. All rights reserved.

An econometric analysis of changes in arable land utilization using multinomial logit model in Pinggu district, Beijing, China.

PubMed

Xu, Yueqing; McNamara, Paul; Wu, Yanfang; Dong, Yue

2013-10-15

Arable land in China has been decreasing as a result of rapid population growth and economic development as well as urban expansion, especially in developed regions around cities where quality farmland quickly disappears. This paper analyzed changes in arable land utilization during 1993-2008 in the Pinggu district, Beijing, China, developed a multinomial logit (MNL) model to determine spatial driving factors influencing arable land-use change, and simulated arable land transition probabilities. Land-use maps, as well as social-economic and geographical data were used in the study. The results indicated that arable land decreased significantly between 1993 and 2008. Lost arable land shifted into orchard, forestland, settlement, and transportation land. Significant differences existed for arable land transitions among different landform areas. Slope, elevation, population density, urbanization rate, distance to settlements, and distance to roadways were strong drivers influencing arable land transition to other uses. The MNL model was proved effective for predicting transition probabilities in land use from arable land to other land-use types, thus can be used for scenario analysis to develop land-use policies and land-management measures in this metropolitan area. Copyright © 2013 Elsevier Ltd. All rights reserved.

Redintegration and the benefits of long-term knowledge in verbal short-term memory: an evaluation of Schweickert's (1993) multinomial processing tree model.

PubMed

Thorn, Annabel S C; Gathercole, Susan E; Frankish, Clive R

2005-03-01

The impact of four long-term knowledge variables on serial recall accuracy was investigated. Serial recall was tested for high and low frequency words and high and low phonotactic frequency nonwords in 2 groups: monolingual English speakers and French-English bilinguals. For both groups the recall advantage for words over nonwords reflected more fully correct recalls with fewer recall attempts that consisted of fragments of the target memory items (one or two of the three target phonemes recalled correctly); completely incorrect recalls were equivalent for the 2 list types. However, word frequency (for both groups), nonword phonotactic frequency (for the monolingual group), and language familiarity all influenced the proportions of completely incorrect recalls that were made. These results are not consistent with the view that long-term knowledge influences on immediate recall accuracy can be exclusively attributed to a redintegration process of the type specified in multinomial processing tree model of immediate recall. The finding of a differential influence on completely incorrect recalls of these four long-term knowledge variables suggests instead that the beneficial effects of long-term knowledge on short-term recall accuracy are mediated by more than one mechanism.

Model-based Clustering of Categorical Time Series with Multinomial Logit Classification

NASA Astrophysics Data System (ADS)

Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Winter-Ebmer, Rudolf; Weber, Andrea

2010-09-01

A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance-based clustering methods cannot easily be extended to time series data, where an appropriate distance-measure is rather difficult to define, particularly for discrete-valued time series. Markov chain clustering, proposed by Pamminger and Frühwirth-Schnatter [6], is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This model-based clustering method is based on finite mixtures of first-order time-homogeneous Markov chain models. In order to further explain group membership we present an extension to the approach of Pamminger and Frühwirth-Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model. The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov chain Monte Carlo (MCMC) sampling scheme representing a (full) Gibbs-type sampler which involves only draws from standard distributions. Finally, an application to a panel of Austrian wage mobility data is presented which leads to an interesting segmentation of the Austrian labour market.

Perception of tourists regarding the smoke-free policy at Suvarnabhumi International Airport, Bangkok, Thailand.

PubMed

Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon

2013-08-30

This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment.

Evaluating the Relationship between Productivity and Quality in Emergency Departments

PubMed Central

Bastian, Nathaniel D.; Riordan, John P.

2017-01-01

Background In the United States, emergency departments (EDs) are constantly pressured to improve operational efficiency and quality in order to gain financial benefits and maintain a positive reputation. Objectives The first objective is to evaluate how efficiently EDs transform their input resources into quality outputs. The second objective is to investigate the relationship between the efficiency and quality performance of EDs and the factors affecting this relationship. Methods Using two data sources, we develop a data envelopment analysis (DEA) model to evaluate the relative efficiency of EDs. Based on the DEA result, we performed multinomial logistic regression to investigate the relationship between ED efficiency and quality performance. Results The DEA results indicated that the main source of inefficiencies was working hours of technicians. The multinomial logistic regression result indicated that the number of electrocardiograms and X-ray procedures conducted in the ED and the length of stay were significantly associated with the trade-offs between relative efficiency and quality. Structural ED characteristics did not influence the relationship between efficiency and quality. Conclusions Depending on the structural and operational characteristics of EDs, different factors can affect the relationship between efficiency and quality. PMID:29065673

Evaluation of the laboratory mouse model for screening topical mosquito repellents.

PubMed

Rutledge, L C; Gupta, R K; Wirtz, R A; Buescher, M D

1994-12-01

Eight commercial repellents were tested against Aedes aegypti 0 and 4 h after application in serial dilution to volunteers and laboratory mice. Results were analyzed by multiple regression of percentage of biting (probit scale) on dose (logarithmic scale) and time. Empirical correction terms for conversion of values obtained in tests on mice to values expected in tests on human volunteers were calculated from data obtained on 4 repellents and evaluated with data obtained on 4 others. Corrected values from tests on mice did not differ significantly from values obtained in tests on volunteers. Test materials used in the study were dimethyl phthalate, butopyronoxyl, butoxy polypropylene glycol, MGK Repellent 11, deet, ethyl hexanediol, Citronyl, and dibutyl phthalate.

Canadian Eskimo permanent tooth emergence timing.

PubMed

Mayhall, J T; Belier, P L; Mayhall, M F

1978-08-01

To identify the times of emergence of the permanent teeth of Canadian Eskimos (Inuit), 368 children and adolescents were examined. The presence or absence of all permanent teeth except the third molars was recorded and these data subjected to probit analysis. Female emergence times were advanced over males. Generally, the Inuit of both sexes showed statistically significant earlier emergence times than Montreal children, except for the incisors. The present results do not support hypotheses indicating that premature extraction of the deciduous teeth advances the emergence of their succedaneous counterparts. There is some indication the controls of deciduous tooth emergence continue to play some part in emergence of the permanent dentition, especially the first permanent teeth that emerge.

The relationship between happiness and health: evidence from Italy.

PubMed

Sabatini, Fabio

2014-08-01

We test the relationship between happiness and self-rated health in Italy. The analysis relies on a unique dataset collected through the administration of a questionnaire to a representative sample (n = 817) of the population of the Italian Province of Trento in March 2011. Based on probit regressions and instrumental variables estimates, we find that happiness is strongly correlated with perceived good health, after controlling for a number of relevant socio-economic phenomena. Health inequalities based on income, work status and education are relatively contained with respect to the rest of Italy. As expected, this scales down the role of social relationships. Copyright © 2014 Elsevier Ltd. All rights reserved.

Health insurance and use of alternative medicine in Mexico

PubMed Central

van Gameren, Edwin

2014-01-01

Objectives I analyze the effect of coverage by health insurance on the use of alternative medicine such as folk healers and homeopaths, in particular if it complements or substitutes conventional services. Methods Panel data from the Mexican Health and Aging Study (MHAS) is used to estimate bivariate probit models in order to explain the use of alternative medicine while allowing the determinant of interest, access to health insurance, to be an endogenous factor. Results The findings indicate that households with insurance coverage less often use alternative medicine, and that the effect is much stronger among poor than among rich households. Conclusions Poor households substitute away from traditional medicine towards conventional medicine. PMID:20546965

A Pilot Test of Indicator Species to Assess Uniqueness of Oak-Dominated Ecoregions in Central Tennessee

Treesearch

W. Henry McNab; David L. Loftis; Callie J. Schweitzer; Raymond Sheffield

2004-01-01

We used tree indicator species occurring on 438 plots in the Plateau counties of Tennessee to test the uniqueness of four conterminous ecoregions. Multinomial logistic regression indicated that the presence of 14 tree species allowed classification of sample plots according to ecoregion with an average overall accuracy of 75 percent (range 45 to 94 percent). Additional...

Brief Report: Sexual Orientation in Individuals with Autistic Traits--Population Based Study of 47,000 Adults in Stockholm County

ERIC Educational Resources Information Center

Rudolph, Christiane E. S.; Lundin, Andreas; Åhs, Jill W.; Dalman, Christina; Kosidou, Kyriaki

2018-01-01

We examined the association between autistic traits and sexual orientation in a general adult population (N = 47,356). Autistic traits were measured with the ten items Autistic Quotient questionnaire using a cut-off score of = 6. Sexual orientation was assessed by self-report. Multinomial logistic regression was used to estimate odds ratios (ORs)…

Redintegration and the Benefits of Long-Term Knowledge in Verbal Short-Term Memory: An Evaluation of Schweickert's (1993) Multinomial Processing Tree Model

ERIC Educational Resources Information Center

Thorn, Annabel S. C.; Gathercole, Susan E.; Frankish, Clive R.

2005-01-01

The impact of four long-term knowledge variables on serial recall accuracy was investigated. Serial recall was tested for high and low frequency words and high and low phonotactic frequency nonwords in 2 groups: monolingual English speakers and French-English bilinguals. For both groups the recall advantage for words over nonwords reflected more…

Mind-Mindedness as a Multidimensional Construct: Appropriate and Nonattuned Mind-Related Comments Independently Predict Infant-Mother Attachment in a Socially Diverse Sample

ERIC Educational Resources Information Center

Meins, Elizabeth; Fernyhough, Charles; de Rosnay, Marc; Arnott, Bronia; Leekam, Susan R.; Turner, Michelle

2012-01-01

In a socially diverse sample of 206 infant-mother pairs, we investigated predictors of infants' attachment security at 15 months, with a particular emphasis on mothers' tendency to comment appropriately or in a non-attuned manner on their 8-month-olds' internal states (so-called mind-mindedness). Multinomial logistic regression analyses showed…

Determinants of Intent to Transfer among Black Male Community College Students: A Multinomial, Multi-Level Investigation of Student Engagement

ERIC Educational Resources Information Center

Wood, J. Luke; Palmer, Robert T.

2016-01-01

Background/Context: Transfer is a core function of community colleges; this is a critical point given that these institutions serve as the primary pathway into postsecondary education for Black men. However, too few Black men identify transfer as a primary goal and/or eventually transfer to a 4-year college or university.…

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

ERIC Educational Resources Information Center

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

Disability weights from a household survey in a low socio-economic setting: how does it compare to the global burden of disease 2010 study?

PubMed

Neethling, Ian; Jelsma, Jennifer; Ramma, Lebogang; Schneider, Helen; Bradshaw, Debbie

2016-01-01

The global burden of disease (GBD) 2010 study used a universal set of disability weights to estimate disability adjusted life years (DALYs) by country. However, it is not clear whether these weights can be applied universally in calculating DALYs to inform local decision-making. This study derived disability weights for a resource-constrained community in Cape Town, South Africa, and interrogated whether the GBD 2010 disability weights necessarily represent the preferences of economically disadvantaged communities. A household survey was conducted in Lavender Hill, Cape Town, to assess the health state preferences of the general public. The responses from a paired comparison valuation method were assessed using a probit regression. The probit coefficients were anchored onto the 0 to 1 disability weight scale by running a lowess regression on the GBD 2010 disability weights and interpolating the coefficients between the upper and lower limit of the smoothed disability weights. Heroin and opioid dependence had the highest disability weight of 0.630, whereas intellectual disability had the lowest (0.040). Untreated injuries ranked higher than severe mental disorders. There were some counterintuitive results, such as moderate (15th) and severe vision impairment (16th) ranking higher than blindness (20th). A moderate correlation between the disability weights of the local study and those of the GBD 2010 study was observed (R(2)=0.440, p<0.05). This indicates that there was a relationship, although some conditions, such as untreated fracture of the radius or ulna, showed large variability in disability weights (0.488 in local study and 0.043 in GBD 2010). Respondents seemed to value physical mobility higher than cognitive functioning, which is in contrast to the GBD 2010 study. This study shows that not all health state preferences are universal. Studies estimating DALYs need to derive local disability weights using methods that are less cognitively demanding for respondents.

[Investigation on prevalence of soil-transmitted nematode infections and influencing factors for children in southwest areas of China].

PubMed

Wang, Xiao-Bing; Wang, Guo-Fei; Zhang, Lin-Xiu; Luo, Ren-Fu; Tian, Hong-Chun; Tang, Li-Na; Wang, Ju-Jun; Medina, Alexis; Wise, Paul; Rozelle, Scott

2012-06-01

To understand the infection status and main risk factors of soil-transmitted nematodes in southwest China so as to provide the evidence for making the control programs for soil-transmitted nematodiasis. The prevalence of soil-transmitted nematode infections was determined by Kato-Katz technique and influencing factors were surveyed by using a standardized questionnaire, and in part of the children, the examination of Enterobius vermicularis eggs was performed by using the cellophane swab method. The relationship between soil-transmitted nematode infections and influencing factors was analyzed by the multiple probit estimated method. A total of 1 707 children were examined, with a soil-transmitted nematode infection rate of 22.2%, the crowd infection rates ofAscaris lumbricoides, hookworm, and Trichuris trichiura were 16.0%, 3.8% and 6.6% respectively and 495 children were examined on Enterobius vermicularis eggs, with the infection rate of 5.1%. The results of probit estimated analysis suggested that the effects of 4 factors on soil-transmitted nematode infections were significant (all P values were less than 0.05), namely the number of sib, educational level of mother, drinking unboiled water and raising livestock and poultry. Among the factors above, the educational level of mother could reduce the probability of infection (ME = -0.074), while the number of sib, drinking unboiled water and raising livestock and poultry could increase the probability of the infections (with ME of 0.028, -0.112 and 0.080, respectively). Soil-transmitted nematode infection rates are still in a high level for children in southwest poor areas of China, with Ascaris lumbricoides as a priority. The changes of children's bad health habits, raising livestock and poultry habits, and implementing the health education about parasitic diseases in mothers would be of great significance for the prevention and control of soil-transmitted nematodiasis.

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.

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.

Dose-volume effects in pathologic lymph nodes in locally advanced cervical cancer.

PubMed

Bacorro, Warren; Dumas, Isabelle; Escande, Alexandre; Gouy, Sebastien; Bentivegna, Enrica; Morice, Philippe; Haie-Meder, Christine; Chargari, Cyrus

2018-03-01

In cervical cancer patients, dose-volume relationships have been demonstrated for tumor and organs-at-risk, but not for pathologic nodes. The nodal control probability (NCP) according to dose/volume parameters was investigated. Patients with node-positive cervical cancer treated curatively with external beam radiotherapy (EBRT) and image-guided brachytherapy (IGABT) were identified. Nodal doses during EBRT, IGABT and boost were converted to 2-Gy equivalent (α/β = 10 Gy) and summed. Pathologic nodes were followed individually from diagnosis to relapse. Statistical analyses comprised log-rank tests (univariate analyses), Cox proportional model (factors with p ≤ 0.1 in univariate) and Probit analyses. A total of 108 patients with 254 unresected pathological nodes were identified. The mean nodal volume at diagnosis was 3.4 ± 5.8 cm 3 . The mean total nodal EQD2 doses were 55.3 ± 5.6 Gy. Concurrent chemotherapy was given in 96%. With a median follow-up of 33.5 months, 20 patients (18.5%) experienced relapse in nodes considered pathologic at diagnosis. Overall nodal recurrence rate was 9.1% (23/254). On univariate analyses, nodal volume (threshold: 3 cm 3 , p < .0001) and lymph node dose (≥57.5 Gy α/β10 , p = .039) were significant for nodal control. The use of simultaneous boost was borderline for significance (p = .07). On multivariate analysis, volume (HR = 8.2, 4.0-16.6, p < .0001) and dose (HR = 2, 1.05-3.9, p = .034) remained independent factors. Probit analysis combining dose and volume showed significant relationships with NCP, with increasing gap between the curves with higher nodal volumes. A nodal dose-volume effect on NCP is demonstrated for the first time, with increasing NCP benefit of additional doses to higher-volume nodes. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed Central

2018-01-01

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

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

PubMed

Oyekale, Abayomi Samuel

2018-02-13

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

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.

Predictors of Place of Death for Seniors in Ontario: A Population-Based Cohort Analysis

ERIC Educational Resources Information Center

Motiwala, Sanober S.; Croxford, Ruth; Guerriere, Denise N.; Coyte, Peter C.

2006-01-01

Place of death was determined for all 58,689 seniors (age greater than or equal to 66 years) in Ontario who died during fiscal year 2001/2002. The relationship of place of death to medical and socio-demographic characteristics was examined using a multinomial logit model. Half (49.2 %) of these individuals died in hospital, 30.5 per cent died in a…

Factors influencing spatial pattern in tropical forest clearance and stand age: Implications for carbon storage and species diversity.

Treesearch

E. H. Helmer; Thomas J. Brandeis; Ariel E. Lugo; Todd Kennaway

2008-01-01

Little is known about the tropical forests that undergo clearing as urban/built-up and other developed lands spread. This study uses remote sensing-based maps of Puerto Rico, multinomial logit models and forest inventory data to explain patterns of forest age and the age of forests cleared for land development and assess their implications for forest carbon storage and...

Modeling the Distribution of Fingerprint Characteristics. Revision 1.

DTIC Science & Technology

1980-09-19

the details of the print. The ridge-line details are termed Galton characteristics since Sir Francis Galton was among the first to study them...U.S.A. CONTENTS Abstract 1. Introduction 2. Background Information on Fingerprints 2.1. Types 2.2. Ridge counts 2.3. The Galton details 3. Data...The Multinomial Markov Model 7. The Poisson Markov Model 8. The Infinitely Divisible Model Acknowledgements References Appendices A The Galton

Modeling of orthotropic plate fracture under impact load using various strength criteria

NASA Astrophysics Data System (ADS)

Radchenko, Andrey; Krivosheina, Marina; Kobenko, Sergei; Radchenko, Pavel; Grebenyuk, Grigory

2017-01-01

The paper presents the comparative analysis of various tensor multinomial criteria of strength for modeling of orthotropic organic plastic plate fracture under impact load. Ashkenazi, Hoffman and Wu strength criteria were used. They allowed fracture modeling of orthotropic materials with various compressive and tensile strength properties. The modeling of organic plastic fracture was performed numerically within the impact velocity range of 700-1500 m/s.

Masquerade Detection Using a Taxonomy-Based Multinomial Modeling Approach in UNIX Systems

DTIC Science & Technology

2008-08-25

primarily the modeling of statistical features , such as the frequency of events, the duration of events, the co- occurrence of multiple events...are identified, we can extract features representing such behavior while auditing the user’s behavior. Figure1: Taxonomy of Linux and Unix...achieved when the features are extracted just from simple commands. Method Hit Rate False Positive Rate ocSVM using simple cmds (freq.-based

Three faces of entropy for complex systems: Information, thermodynamics, and the maximum entropy principle

NASA Astrophysics Data System (ADS)

Thurner, Stefan; Corominas-Murtra, Bernat; Hanel, Rudolf

2017-09-01

There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynamic quantity of physical systems (Clausius, Boltzmann, Gibbs), entropy as a measure for information production of ergodic sources (Shannon), and entropy as a means for statistical inference on multinomial processes (Jaynes maximum entropy principle). Even though these notions represent fundamentally different concepts, the functional form of the entropy for thermodynamic systems in equilibrium, for ergodic sources in information theory, and for independent sampling processes in statistical systems, is degenerate, H (p ) =-∑ipilogpi . For many complex systems, which are typically history-dependent, nonergodic, and nonmultinomial, this is no longer the case. Here we show that for such processes, the three entropy concepts lead to different functional forms of entropy, which we will refer to as SEXT for extensive entropy, SIT for the source information rate in information theory, and SMEP for the entropy functional that appears in the so-called maximum entropy principle, which characterizes the most likely observable distribution functions of a system. We explicitly compute these three entropy functionals for three concrete examples: for Pólya urn processes, which are simple self-reinforcing processes, for sample-space-reducing (SSR) processes, which are simple history dependent processes that are associated with power-law statistics, and finally for multinomial mixture processes.

Measuring Response Styles Across the Big Five: A Multiscale Extension of an Approach Using Multinomial Processing Trees.

PubMed

Khorramdel, Lale; von Davier, Matthias

2014-01-01

This study shows how to address the problem of trait-unrelated response styles (RS) in rating scales using multidimensional item response theory. The aim is to test and correct data for RS in order to provide fair assessments of personality. Expanding on an approach presented by Böckenholt (2012), observed rating data are decomposed into multiple response processes based on a multinomial processing tree. The data come from a questionnaire consisting of 50 items of the International Personality Item Pool measuring the Big Five dimensions administered to 2,026 U.S. students with a 5-point rating scale. It is shown that this approach can be used to test if RS exist in the data and that RS can be differentiated from trait-related responses. Although the extreme RS appear to be unidimensional after exclusion of only 1 item, a unidimensional measure for the midpoint RS is obtained only after exclusion of 10 items. Both RS measurements show high cross-scale correlations and item response theory-based (marginal) reliabilities. Cultural differences could be found in giving extreme responses. Moreover, it is shown how to score rating data to correct for RS after being proved to exist in the data.

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

PubMed

Kéry, Marc

2018-02-01

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

Patient choice modelling: how do patients choose their hospitals?

PubMed

Smith, Honora; Currie, Christine; Chaiwuttisak, Pornpimol; Kyprianou, Andreas

2018-06-01

As an aid to predicting future hospital admissions, we compare use of the Multinomial Logit and the Utility Maximising Nested Logit models to describe how patients choose their hospitals. The models are fitted to real data from Derbyshire, United Kingdom, which lists the postcodes of more than 200,000 admissions to six different local hospitals. Both elective and emergency admissions are analysed for this mixed urban/rural area. For characteristics that may affect a patient's choice of hospital, we consider the distance of the patient from the hospital, the number of beds at the hospital and the number of car parking spaces available at the hospital, as well as several statistics publicly available on National Health Service (NHS) websites: an average waiting time, the patient survey score for ward cleanliness, the patient safety score and the inpatient survey score for overall care. The Multinomial Logit model is successfully fitted to the data. Results obtained with the Utility Maximising Nested Logit model show that nesting according to city or town may be invalid for these data; in other words, the choice of hospital does not appear to be preceded by choice of city. In all of the analysis carried out, distance appears to be one of the main influences on a patient's choice of hospital rather than statistics available on the Internet.

Classification of vegetation types in military region

NASA Astrophysics Data System (ADS)

Gonçalves, Miguel; Silva, Jose Silvestre; Bioucas-Dias, Jose

2015-10-01

In decision-making process regarding planning and execution of military operations, the terrain is a determining factor. Aerial photographs are a source of vital information for the success of an operation in hostile region, namely when the cartographic information behind enemy lines is scarce or non-existent. The objective of present work is the development of a tool capable of processing aerial photos. The methodology implemented starts with feature extraction, followed by the application of an automatic selector of features. The next step, using the k-fold cross validation technique, estimates the input parameters for the following classifiers: Sparse Multinomial Logist Regression (SMLR), K Nearest Neighbor (KNN), Linear Classifier using Principal Component Expansion on the Joint Data (PCLDC) and Multi-Class Support Vector Machine (MSVM). These classifiers were used in two different studies with distinct objectives: discrimination of vegetation's density and identification of vegetation's main components. It was found that the best classifier on the first approach is the Sparse Logistic Multinomial Regression (SMLR). On the second approach, the implemented methodology applied to high resolution images showed that the better performance was achieved by KNN classifier and PCLDC. Comparing the two approaches there is a multiscale issue, in which for different resolutions, the best solution to the problem requires different classifiers and the extraction of different features.

The molecular epidemiology of HIV-1 in the Comunidad Valenciana (Spain): analysis of transmission clusters.

PubMed

Patiño-Galindo, Juan Ángel; Torres-Puente, Manoli; Bracho, María Alma; Alastrué, Ignacio; Juan, Amparo; Navarro, David; Galindo, María José; Ocete, Dolores; Ortega, Enrique; Gimeno, Concepción; Belda, Josefina; Domínguez, Victoria; Moreno, Rosario; González-Candelas, Fernando

2017-09-14

HIV infections are still a very serious concern for public heath worldwide. We have applied molecular evolution methods to study the HIV-1 epidemics in the Comunidad Valenciana (CV, Spain) from a public health surveillance perspective. For this, we analysed 1804 HIV-1 sequences comprising protease and reverse transcriptase (PR/RT) coding regions, sampled between 2004 and 2014. These sequences were subtyped and subjected to phylogenetic analyses in order to detect transmission clusters. In addition, univariate and multinomial comparisons were performed to detect epidemiological differences between HIV-1 subtypes, and risk groups. The HIV epidemic in the CV is dominated by subtype B infections among local men who have sex with men (MSM). 270 transmission clusters were identified (>57% of the dataset), 12 of which included ≥10 patients; 11 of subtype B (9 affecting MSMs) and one (n = 21) of CRF14, affecting predominately intravenous drug users (IDUs). Dated phylogenies revealed these large clusters to have originated from the mid-80s to the early 00 s. Subtype B is more likely to form transmission clusters than non-B variants and MSMs to cluster than other risk groups. Multinomial analyses revealed an association between non-B variants, which are not established in the local population yet, and different foreign groups.

Source and destination memory in face-to-face interaction: A multinomial modeling approach.

PubMed

Fischer, Nele M; Schult, Janette C; Steffens, Melanie C

2015-06-01

Arguing that people are often in doubt concerning to whom they have presented what information, Gopie and MacLeod (2009) introduced a new memory component, destination memory: remembering the destination of output information (i.e., "Who did you tell this to?"). They investigated source (i.e., "Who told you that?") versus destination memory in computer-based imagined interactions. The present study investigated destination memory in real interaction situations. In 2 experiments with mixed-gender (N = 53) versus same-gender (N = 89) groups, source and destination memory were manipulated by creating a setup similar to speed dating. In dyads, participants completed phrase fragments with personal information, taking turns. At recognition, participants decided whether fragments were new or old and, if old, whether they were listened to or spoken and which depicted person was the source or the destination of the information. A multinomial model was used for analyses. Source memory significantly exceeded destination memory, whereas information itself was better remembered in the destination than in the source condition. These findings corroborate the trade-off hypothesis: Context is better remembered in input than in output events, but information itself is better remembered in output than in input events. We discuss the implications of these findings for real-world conversation situations. (c) 2015 APA, all rights reserved).

Implicit moral evaluations: A multinomial modeling approach.

PubMed

Cameron, C Daryl; Payne, B Keith; Sinnott-Armstrong, Walter; Scheffer, Julian A; Inzlicht, Michael

2017-01-01

Implicit moral evaluations-i.e., immediate, unintentional assessments of the wrongness of actions or persons-play a central role in supporting moral behavior in everyday life. Yet little research has employed methods that rigorously measure individual differences in implicit moral evaluations. In five experiments, we develop a new sequential priming measure-the Moral Categorization Task-and a multinomial model that decomposes judgment on this task into multiple component processes. These include implicit moral evaluations of moral transgression primes (Unintentional Judgment), accurate moral judgments about target actions (Intentional Judgment), and a directional tendency to judge actions as morally wrong (Response Bias). Speeded response deadlines reduced Intentional Judgment but not Unintentional Judgment (Experiment 1). Unintentional Judgment was stronger toward moral transgression primes than non-moral negative primes (Experiments 2-4). Intentional Judgment was associated with increased error-related negativity, a neurophysiological indicator of behavioral control (Experiment 4). Finally, people who voted for an anti-gay marriage amendment had stronger Unintentional Judgment toward gay marriage primes (Experiment 5). Across Experiments 1-4, implicit moral evaluations converged with moral personality: Unintentional Judgment about wrong primes, but not negative primes, was negatively associated with psychopathic tendencies and positively associated with moral identity and guilt proneness. Theoretical and practical applications of formal modeling for moral psychology are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

An Optimization-Based Framework for the Transformation of Incomplete Biological Knowledge into a Probabilistic Structure and Its Application to the Utilization of Gene/Protein Signaling Pathways in Discrete Phenotype Classification.

PubMed

Esfahani, Mohammad Shahrokh; Dougherty, Edward R

2015-01-01

Phenotype classification via genomic data is hampered by small sample sizes that negatively impact classifier design. Utilization of prior biological knowledge in conjunction with training data can improve both classifier design and error estimation via the construction of the optimal Bayesian classifier. In the genomic setting, gene/protein signaling pathways provide a key source of biological knowledge. Although these pathways are neither complete, nor regulatory, with no timing associated with them, they are capable of constraining the set of possible models representing the underlying interaction between molecules. The aim of this paper is to provide a framework and the mathematical tools to transform signaling pathways to prior probabilities governing uncertainty classes of feature-label distributions used in classifier design. Structural motifs extracted from the signaling pathways are mapped to a set of constraints on a prior probability on a Multinomial distribution. Being the conjugate prior for the Multinomial distribution, we propose optimization paradigms to estimate the parameters of a Dirichlet distribution in the Bayesian setting. The performance of the proposed methods is tested on two widely studied pathways: mammalian cell cycle and a p53 pathway model.

The outcome of tuberculosis treatment in subjects with chronic kidney disease in Brazil: a multinomial analysis*

PubMed Central

Reis-Santos, Barbara; Gomes, Teresa; Horta, Bernardo Lessa; Maciel, Ethel Leonor Noia

2013-01-01

OBJECTIVE: To analyze the association between clinical/epidemiological characteristics and outcomes of tuberculosis treatment in patients with concomitant tuberculosis and chronic kidney disease (CKD) in Brazil. METHODS: We used the Brazilian Ministry of Health National Case Registry Database to identify patients with tuberculosis and CKD, treated between 2007 and 2011. The tuberculosis treatment outcomes were compared with epidemiological and clinical characteristics of the subjects using a hierarchical multinomial logistic regression model, in which cure was the reference outcome. RESULTS: The prevalence of CKD among patients with tuberculosis was 0.4% (95% CI: 0.37-0.42%). The sample comprised 1,077 subjects. The outcomes were cure, in 58%; treatment abandonment, in 7%; death from tuberculosis, in 13%; and death from other causes, in 22%. The characteristics that differentiated the ORs for treatment abandonment or death were age; alcoholism; AIDS; previous noncompliance with treatment; transfer to another facility; suspected tuberculosis on chest X-ray; positive results in the first smear microscopy; and indications for/use of directly observed treatment, short-course strategy. CONCLUSIONS: Our data indicate the importance of sociodemographic characteristics for the diagnosis of tuberculosis in patients with CKD and underscore the need for tuberculosis control strategies targeting patients with chronic noncommunicable diseases, such as CKD. PMID:24310632

Registered dietitian's personal beliefs and characteristics predict their teaching or intention to teach fresh vegetable food safety.

PubMed

Casagrande, Gina; LeJeune, Jeffery; Belury, Martha A; Medeiros, Lydia C

2011-04-01

The Theory of Planned Behavior was used to determine if dietitians personal characteristics and beliefs about fresh vegetable food safety predict whether they currently teach, intend to teach, or neither currently teach nor intend to teach food safety information to their clients. Dietitians who participated in direct client education responded to this web-based survey (n=327). The survey evaluated three independent belief variables: Subjective Norm, Attitudes, and Perceived Behavioral Control. Spearman rho correlations were completed to determine variables that correlated best with current teaching behavior. Multinomial logistical regression was conducted to determine if the belief variables significantly predicted dietitians teaching behavior. Binary logistic regression was used to determine which independent variable was the better predictor of whether dietitians currently taught. Controlling for age, income, education, and gender, the multinomial logistical regression was significant. Perceived behavioral control was the best predictor of whether a dietitian currently taught fresh vegetable food safety. Factors affecting whether dietitians currently taught were confidence in fresh vegetable food safety knowledge, being socially influenced, and a positive attitude toward the teaching behavior. These results validate the importance of teaching food safety effectively and may be used to create more informed food safety curriculum for dietitians. Copyright © 2011 Elsevier Ltd. All rights reserved.

Knowledge and perception on tuberculosis transmission in Tanzania: Multinomial logistic regression analysis of secondary data.

PubMed

Ismail, Abbas; Josephat, Peter

2014-01-01

Tuberculosis (TB) is one of the most important public health problems in Tanzania and was declared as a national public health emergency in 2006. Community and individual knowledge and perceptions are critical factors in the control of the disease. The objective of this study was to analyze the knowledge and perception on the transmission of TB in Tanzania. Multinomial Logistic Regression analysis was considered in order to quantify the impact of knowledge and perception on TB. The data used was adopted as secondary data from larger national survey 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey. The findings across groups revealed that knowledge on TB transmission increased with an increase in age and level of education. People in rural areas had less knowledge regarding tuberculosis transmission compared to urban areas [OR = 0.7]. People with the access to radio [OR = 1.7] were more knowledgeable on tuberculosis transmission compared to those who did not have access to radio. People who did not have telephone [OR = 0.6] were less knowledgeable on tuberculosis route of transmission compared to those who had telephone. The findings showed that socio-demographic factors such as age, education, place of residence and owning telephone or radio varied systematically with knowledge on tuberculosis transmission.

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

PubMed

Dai, Huanping; Micheyl, Christophe

2012-11-01

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

Perception of Tourists Regarding the Smoke-Free Policy at Suvarnabhumi International Airport, Bangkok, Thailand

PubMed Central

Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon

2013-01-01

This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment. PMID:23999549

Who Works Among Older Black and White, Well-Functioning Adults in the Health, Aging, and Body Composition Study?

PubMed Central

Rooks, Ronica N.; Simonsick, Eleanor M.; Schulz, Richard; Rubin, Susan; Harris, Tamara

2017-01-01

Objective: The aim of this study is to examine social, economic, and health factors related to paid work in well-functioning older adults and if and how these factors vary by race. Method: We used sex-stratified logistic and multinomial logistic regression to examine cross-sectional data in the Health, Aging, and Body Composition cohort study. The sample included 3,075 community-dwelling Black (42%) and White adults aged 70 to 79 at baseline. Results: Multinomial logistic regression analyses show Black men were more likely to work full-time, and Black women were more likely to work part-time. Men with ≥US$50,000 family income were more likely to work full-time. Men with better physical functioning were more likely to work full- and part-time. Women with ≥US$50,000 family income and fewer chronic diseases were more likely to work full-time. Women who were overweight and had fewer chronic diseases were more likely to work part-time. Discussion: Results suggest that well-functioning, older Black adults were more likely to work than their White counterparts, and working relates to better health and higher income, providing support for a productive or successful aging perspective. PMID:28894767

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.

Comparing the reliability of related populations with the probability of agreement

DOE PAGES

Stevens, Nathaniel T.; Anderson-Cook, Christine M.

2016-07-26

Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regressionmore » model. Note that supplementary materials including code, datasets, and added discussion are available online.« less

Investigation of acute toxicity of fenitrothion on peppered corydoras (Corydoras paleatus) (Jenyns, 1842).

PubMed

Sarikaya, Rabia; Selvi, Mahmut; Erkoç, Figen

2004-08-01

Fenitrothion, as an organophosphothionate insecticide, is a contact insecticide and selective acaricide, also used as a vector control agent for malaria in public health programs. A 96 h LC50 value of fenitrothion, a potential toxic pollutant contaminating aquatic ecosystems, was determined on the adult peppered corydoras (Corydoras paleatus). The experiments were repeated three times. The static test method of acute toxicity test was used. Water temperature was regulated at 23 +/- 1 degrees C. In addition, behavioral changes at each fenitrothion concentration were observed for the individual fish. Data obtained from acute toxicity tests were evaluated using the Probit Analysis Statistical Method. The 96 h LC50 value for peppered corydoras was estimated as 3.51 mg/l.

Comparing the reliability of related populations with the probability of agreement

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

Stevens, Nathaniel T.; Anderson-Cook, Christine M.

Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regressionmore » model. Note that supplementary materials including code, datasets, and added discussion are available online.« less

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.

Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images

PubMed Central

Zhou, Mingyuan; Chen, Haojun; Paisley, John; Ren, Lu; Li, Lingbo; Xing, Zhengming; Dunson, David; Sapiro, Guillermo; Carin, Lawrence

2013-01-01

Nonparametric Bayesian methods are considered for recovery of imagery based upon compressive, incomplete, and/or noisy measurements. A truncated beta-Bernoulli process is employed to infer an appropriate dictionary for the data under test and also for image recovery. In the context of compressive sensing, significant improvements in image recovery are manifested using learned dictionaries, relative to using standard orthonormal image expansions. The compressive-measurement projections are also optimized for the learned dictionary. Additionally, we consider simpler (incomplete) measurements, defined by measuring a subset of image pixels, uniformly selected at random. Spatial interrelationships within imagery are exploited through use of the Dirichlet and probit stick-breaking processes. Several example results are presented, with comparisons to other methods in the literature. PMID:21693421

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.

Firewood, smoke and respiratory diseases in developing countries—The neglected role of outdoor cooking

PubMed Central

2017-01-01

Smoke from cooking in the kitchen is one of the world’s leading causes of premature child death, claiming the lives of 500,000 children under five annually. This study analyses the role of outdoor cooking and the prevalence of respiratory diseases among children under five years by means of probit regressions using information from 41 surveys conducted in 30 developing countries from Asia, Africa and Latin America. I find that outdoor cooking reduces respiratory diseases among young children aged 0-4 by around 9 percent, an effect that reaches 13 percent among children aged 0-1. The results suggest that simple behavioral interventions, such as promoting outdoor cooking, can have a substantial impact on health hazards. PMID:28658290

Economic analysis of the potential impact of climate change on recreational trout fishing in the Southern Appalachian Mountains: An appication of a nested multinomial logti model

Treesearch

Soeun Ahn; Joseph E. de Steiguer; Raymond B. Palmquist; Thomas P. Holmes

2000-01-01

Global warming due to the enhanced greenhouse effect through human activities has become a major public policy issue in recent years. The present study focuses on the potential economic impact of climate change on recreational trout fishing in the Southern Appalachian Mountains of North Carolina. Significant reductions in trout habitat and/or populations are...

Generalizing the Iterative Proportional Fitting Procedure.

DTIC Science & Technology

1980-04-01

Csiszar gives conditions under which P (R) exists (it is always unique) and develops a geometry of I-divergence by using an analogue of Pythagoras ...8217 Theorem . As our goal is to study maximum likelihood estimation in contingency tables, we turn briefly to the problem of estimating a multinomial...envoke a result of Csiszir (due originally to Kullback (1959)), giving the form of the density of the I-projection. Csiszar’s Theorem 3.1, which we

Spatial distribution of the risk of dengue fever in southeast Brazil, 2006-2007

PubMed Central

2011-01-01

Background Many factors have been associated with circulation of the dengue fever virus and vector, although the dynamics of transmission are not yet fully understood. The aim of this work is to estimate the spatial distribution of the risk of dengue fever in an area of continuous dengue occurrence. Methods This is a spatial population-based case-control study that analyzed 538 cases and 727 controls in one district of the municipality of Campinas, São Paulo, Brazil, from 2006-2007, considering socio-demographic, ecological, case severity, and household infestation variables. Information was collected by in-home interviews and inspection of living conditions in and around the homes studied. Cases were classified as mild or severe according to clinical data, and they were compared with controls through a multinomial logistic model. A generalized additive model was used in order to include space in a non-parametric fashion with cubic smoothing splines. Results Variables associated with increased incidence of all dengue cases in the multiple binomial regression model were: higher larval density (odds ratio (OR) = 2.3 (95%CI: 2.0-2.7)), reports of mosquito bites during the day (OR = 1.8 (95%CI: 1.4-2.4)), the practice of water storage at home (OR = 2.5 (95%CI: 1.4, 4.3)), low frequency of garbage collection (OR = 2.6 (95%CI: 1.6-4.5)) and lack of basic sanitation (OR = 2.9 (95%CI: 1.8-4.9)). Staying at home during the day was protective against the disease (OR = 0.5 (95%CI: 0.3-0.6)). When cases were analyzed by categories (mild and severe) in the multinomial model, age and number of breeding sites more than 10 were significant only for the occurrence of severe cases (OR = 0.97, (95%CI: 0.96-0.99) and OR = 2.1 (95%CI: 1.2-3.5), respectively. Spatial distribution of risks of mild and severe dengue fever differed from each other in the 2006/2007 epidemic, in the study area. Conclusions Age and presence of more than 10 breeding sites were significant only for severe cases. Other predictors of mild and severe cases were similar in the multiple models. The analyses of multinomial models and spatial distribution maps of dengue fever probabilities suggest an area-specific epidemic with varying clinical and demographic characteristics. PMID:21599980

Predicting Prostate Cancer Progression At Time of Diagnosis

DTIC Science & Technology

2016-09-01

greater or less than 50% pattern 4—is again arbitrary and may not capture biology adequately [see an unrelated paper we published during the study period...predictor of major upgrading (p=0.02 and p=0.18, respectively). On multinomial analysis, which we feel best reflects the spectrum of biology we are...predictive of outcomes, and that unique insights into tumor biology may be gleaned by analysis of both types of biomarkers. Task 6 As noted

Cognitive overload? An exploration of the potential impact of cognitive functioning in discrete choice experiments with older people in health care.

PubMed

Milte, Rachel; Ratcliffe, Julie; Chen, Gang; Lancsar, Emily; Miller, Michelle; Crotty, Maria

2014-07-01

This exploratory study sought to investigate the effect of cognitive functioning on the consistency of individual responses to a discrete choice experiment (DCE) study conducted exclusively with older people. A DCE to investigate preferences for multidisciplinary rehabilitation was administered to a consenting sample of older patients (aged 65 years and older) after surgery to repair a fractured hip (N = 84). Conditional logit, mixed logit, heteroscedastic conditional logit, and generalized multinomial logit regression models were used to analyze the DCE data and to explore the relationship between the level of cognitive functioning (specifically the absence or presence of mild cognitive impairment as assessed by the Mini-Mental State Examination) and preference and scale heterogeneity. Both the heteroscedastic conditional logit and generalized multinomial logit models indicated that the presence of mild cognitive impairment did not have a significant effect on the consistency of responses to the DCE. This study provides important preliminary evidence relating to the effect of mild cognitive impairment on DCE responses for older people. It is important that further research be conducted in larger samples and more diverse populations to further substantiate the findings from this exploratory study and to assess the practicality and validity of the DCE approach with populations of older people. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Clinicians' adherence to clinical practice guidelines for cardiac function monitoring during antipsychotic treatment: a retrospective report on 434 patients with severe mental illness.

PubMed

Manchia, Mirko; Firinu, Giorgio; Carpiniello, Bernardo; Pinna, Federica

2017-03-31

Severe mental illness (SMI) has considerable excess morbidity and mortality, a proportion of which is explained by cardiovascular diseases, caused in part by antipsychotic (AP) induced QT-related arrhythmias and sudden death by Torsade de Point (TdP). The implementation of evidence-based recommendations for cardiac function monitoring might reduce the incidence of these AP-related adverse events. To investigate clinicians' adherence to cardiac function monitoring before and after starting AP, we performed a retrospective assessment of 434 AP-treated SMI patients longitudinally followed-up for 5 years at an academic community mental health center. We classified antipsychotics according to their risk of inducing QT-related arrhythmias and TdP (Center for Research on Therapeutics, University of Arizona). We used univariate tests and multinomial or binary logistic regression model for data analysis. Univariate and multinomial regression analysis showed that psychiatrists were more likely to perform pre-treatment electrocardiogram (ECG) and electrolyte testing with AP carrying higher cardiovascular risk, but not on the basis of AP pharmacological class. Univariate and binomial regression analysis showed that cardiac function parameters (ECG and electrolyte balance) were more frequently monitored during treatment with second generation AP than with first generation AP. Our data show the presence of weaknesses in the cardiac function monitoring of AP-treated SMI patients, and might guide future interventions to tackle them.

Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes.

PubMed

Wu, Qiong; Zhang, Guohui; Ci, Yusheng; Wu, Lina; Tarefder, Rafiqul A; Alcántara, Adélamar Dely

2016-05-18

Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle-infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities. Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality. The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups. The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.

Minimal intervention dentistry for early childhood caries and child dental anxiety: a randomized controlled trial.

PubMed

Arrow, P; Klobas, E

2017-06-01

To compare changes in child dental anxiety after treatment for early childhood caries (ECC) using two treatment approaches. Children with ECC were randomized to test (atraumatic restorative treatment (ART)-based approach) or control (standard care approach) groups. Children aged 3 years or older completed a dental anxiety scale at baseline and follow up. Changes in child dental anxiety from baseline to follow up were tested using the chi-squared statistic, Wilcoxon rank sum test, McNemar's test and multinomial logistic regression. Two hundred and fifty-four children were randomized (N = 127 test, N = 127 control). At baseline, 193 children completed the dental anxiety scale, 211 at follow up and 170 completed the scale on both occasions. Children who were anxious at baseline (11%) were no longer anxious at follow up, and 11% non-anxious children became anxious. Multinomial logistic regression found each increment in the number of visits increased the odds of worsening dental anxiety (odds ratio (OR), 2.2; P < 0.05), whereas each increment in the number of treatments lowered the odds of worsening anxiety (OR, 0.50; P = 0.05). The ART-based approach to managing ECC resulted in similar levels of dental anxiety to the standard treatment approach and provides a valuable alternative approach to the management of ECC in a primary dental care setting. © 2016 Australian Dental Association.

Predictive occurrence models for coastal wetland plant communities: Delineating hydrologic response surfaces with multinomial logistic regression

NASA Astrophysics Data System (ADS)

Snedden, Gregg A.; Steyer, Gregory D.

2013-02-01

Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007-Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.

Knowledge about tuberculosis transmission among ever-married women in Bangladesh.

PubMed

Khandoker, A; Khan, M M H; Krämer, A; Mori, M

2011-03-01

To identify the level of knowledge about TB transmission among ever-married women aged 15-49 years (n = 10 996) in Bangladesh, one of the highest tuberculosis (TB) burden countries. We analysed data from the Bangladesh Demographic and Health Survey conducted in 2007. Covariate factors included age, district, urban/rural residence, marital status, education, husband's education and access to the media (television, radio, newspaper/magazine). Bivariate and multinomial logistic regression analyses were performed to find the correlates of correct knowledge of TB transmission. Knowledge about TB transmission was correctly reported by approximately 7.0% of women, and was significantly associated with education, district and access to media using multinomial logistic regression. The likelihood of correct knowledge was 3.5 times (OR 3.5, 95%CI 2.5-4.9) higher among women with ≥11 years of education than among women with no/primary education. A significantly higher OR for correct knowledge of TB transmission (OR 1.5, 95%CI 1.2-1.9) was found among women who watched television almost every day compared to women who watched less than once a week. Correct knowledge about TB transmission was very low among married women in Bangladesh. Factors such as education and access to media, especially television, could play an important role in improving knowledge about TB transmission among women in Bangladesh.

Multinomial logistic regression analysis for differentiating 3 treatment outcome trajectory groups for headache-associated disability.

PubMed

Lewis, Kristin Nicole; Heckman, Bernadette Davantes; Himawan, Lina

2011-08-01

Growth mixture modeling (GMM) identified latent groups based on treatment outcome trajectories of headache disability measures in patients in headache subspecialty treatment clinics. Using a longitudinal design, 219 patients in headache subspecialty clinics in 4 large cities throughout Ohio provided data on their headache disability at pretreatment and 3 follow-up assessments. GMM identified 3 treatment outcome trajectory groups: (1) patients who initiated treatment with elevated disability levels and who reported statistically significant reductions in headache disability (high-disability improvers; 11%); (2) patients who initiated treatment with elevated disability but who reported no reductions in disability (high-disability nonimprovers; 34%); and (3) patients who initiated treatment with moderate disability and who reported statistically significant reductions in headache disability (moderate-disability improvers; 55%). Based on the final multinomial logistic regression model, a dichotomized treatment appointment attendance variable was a statistically significant predictor for differentiating high-disability improvers from high-disability nonimprovers. Three-fourths of patients who initiated treatment with elevated disability levels did not report reductions in disability after 5 months of treatment with new preventive pharmacotherapies. Preventive headache agents may be most efficacious for patients with moderate levels of disability and for patients with high disability levels who attend all treatment appointments. Copyright © 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Physical victimization, gender identity and suicide risk among transgender men and women.

PubMed

Barboza, Gia Elise; Dominguez, Silvia; Chance, Elena

2016-12-01

We investigated whether being attacked physically due to one's gender identity or expression was associated with suicide risk among trans men and women living in Virginia. The sample consisted of 350 transgender men and women who participated in the Virginia Transgender Health Initiative Survey (THIS). Multivariate multinomial logistic regression was used to explore the competing outcomes associated with suicidal risk. Thirty-seven percent of trans men and women experienced at least one physical attack since the age of 13. On average, individuals experienced 3.97 (SD = 2.86) physical attacks; among these about half were attributed to one's gender identity or expression (mean = 2.08, SD = 1.96). In the multivariate multinomial regression, compared to those with no risk, being physically attacked increased the odds of both attempting and contemplating suicide regardless of gender attribution. Nevertheless, the relative impact of physical victimization on suicidal behavior was higher among those who were targeted on the basis of their gender identity or expression. Finally, no significant association was found between multiple measures of institutional discrimination and suicide risk once discriminatory and non-discriminatory physical victimization was taken into account. Trans men and women experience high levels of physical abuse and face multiple forms of discrimination. They are also at an increased risk for suicidal tendencies. Interventions that help transindividuals cope with discrimination and physical victimization simultaneously may be more effective in saving lives.

Toxicity of certain new compounds to insecticide-resistant houseflies*

PubMed Central

Georghiou, G. P.; Metcalf, R. L.; von Zboray, E. P.

1965-01-01

Houseflies in poultry ranches in certain areas of California are now resistant to most insecticides licensed for use in these establishments, and this resistance problem appears likely to spread to other areas in the future. The authors have therefore studied the contact and oral toxicity of 19 new compounds that have shown interesting properties against resistant flies. These compounds were selected from among several hundred submitted by various laboratories for evaluation under a co-operative programme sponsored by the World Health Organization. Five compounds were found to be as toxic to three insecticide-resistant strains as to a susceptible strain, and showed strikingly steep log-dosage/probit mortality lines against the resistant strains. The authors suggest that these compounds be further studied for fly control in field trials. PMID:5294994

Credit risk evaluation based on social media.

PubMed

Yang, Yang; Gu, Jing; Zhou, Zongfang

2016-07-01

Social media has been playing an increasingly important role in the sharing of individuals' opinions on many financial issues, including credit risk in investment decisions. This paper analyzes whether these opinions, which are transmitted through social media, can accurately predict enterprises' future credit risk. We consider financial statements oriented evaluation results based on logit and probit approaches as the benchmarks. We then conduct textual analysis to retrieve both posts and their corresponding commentaries published on two of the most popular social media platforms for financial investors in China. Professional advice from financial analysts is also investigated in this paper. We surprisingly find that the opinions extracted from both posts and commentaries surpass opinions of analysts in terms of credit risk prediction. Copyright © 2015 Elsevier Inc. All rights reserved.

Dose-time relationships for post-irradiation cutaneous telangiectasia

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

Cohen, L.; Ubaldi, S.E.

1977-01-01

Seventy-five patients who had received electron beam radiation a year or more previously were studied. The irradiated skin portals were photographed and late reactions graded in terms of the number and severity of telangiectatic lesions observed. The skin dose, number of fractions, overall treatment time and irradiated volume were recorded in each case. A Strandqvist-type iso-effect line was derived for this response. A multi-probit search program also was used to derive best-fitting cell population kinetic parameters for the same data. From these parameters a comprehensive iso-effect table could be computed for a wide range of treatment schedules including daily treatmentmore » as well as fractionation at shorter and longer intervals; this provided a useful set of normal tissue tolerance limits for late effects.« less

optBINS: Optimal Binning for histograms

NASA Astrophysics Data System (ADS)

Knuth, Kevin H.

2018-03-01

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

Asymptotic Normality Through Factorial Cumulants and Partition Identities

PubMed Central

Bobecka, Konstancja; Hitczenko, Paweł; López-Blázquez, Fernando; Rempała, Grzegorz; Wesołowski, Jacek

2013-01-01

In the paper we develop an approach to asymptotic normality through factorial cumulants. Factorial cumulants arise in the same manner from factorial moments as do (ordinary) cumulants from (ordinary) moments. Another tool we exploit is a new identity for ‘moments’ of partitions of numbers. The general limiting result is then used to (re-)derive asymptotic normality for several models including classical discrete distributions, occupancy problems in some generalized allocation schemes and two models related to negative multinomial distribution. PMID:24591773

Poverty and childhood undernutrition in developing countries: a multi-national cohort study.

PubMed

Petrou, Stavros; Kupek, Emil

2010-10-01

The importance of reducing childhood undernutrition has been enshrined in the United Nations' Millennium Development Goals. This study explores the relationship between alternative indicators of poverty and childhood undernutrition in developing countries within the context of a multi-national cohort study (Young Lives). Approximately 2000 children in each of four countries - Ethiopia, India (Andhra Pradesh), Peru and Vietnam - had their heights measured and were weighed when they were aged between 6 and 17 months (survey one) and again between 4.5 and 5.5 years (survey two). The anthropometric outcomes of stunted, underweight and wasted were calculated using World Health Organization 2006 reference standards. Maximum-likelihood probit estimation was employed to model the relationship within each country and survey between alternative measures of living standards (principally a wealth index developed using principal components analysis) and each anthropometric outcome. An extensive set of covariates was incorporated into the models to remove as much individual heterogeneity as possible. The fully adjusted models revealed a negative and statistically significant coefficient on wealth for all outcomes in all countries, with the exception of the outcome of wasted in India (Andhra Pradesh) and Vietnam (survey one) and the outcome of underweight in Vietnam (surveys one and two). In survey one, the partial effects of wealth on the probabilities of stunting, being underweight and wasting was to reduce them by between 1.4 and 5.1 percentage points, 1.0 and 6.4 percentage points, and 0.3 and 4.5 percentage points, respectively, with each unit (10%) increase in wealth. The partial effects of wealth on the probabilities of anthropometric outcomes were larger in the survey two models. In both surveys, children residing in the lowest wealth quintile households had significantly increased probabilities of being stunted in all four study countries and of being underweight in Ethiopia, India (Andhra Pradesh) and Peru in comparison to children residing in the highest wealth quintile households. Random effects probit models confirmed the statistical significance of increased wealth in reducing the probability of being stunted and underweight across all four study countries. We conclude that, although multi-faceted, childhood undernutrition in developing countries is strongly rooted in poverty.

Achieving universal health coverage through voluntary insurance: what can we learn from the experience of Lao PDR?

PubMed Central

2013-01-01

Background The Government of Lao Peoples’ Democratic Republic (Lao PDR) has embarked on a path to achieve universal health coverage (UHC) through implementation of four risk-protection schemes. One of these schemes is community-based health insurance (CBHI) – a voluntary scheme that targets roughly half the population. However, after 12 years of implementation, coverage through CBHI remains very low. Increasing coverage of the scheme would require expansion to households in both villages where CBHI is currently operating, and new geographic areas. In this study we explore the prospects of both types of expansion by examining household and district level data. Methods Using a household survey based on a case-comparison design of 3000 households, we examine the determinants of enrolment at the household level in areas where the scheme is currently operating. We model the determinants of enrolment using a probit model and predicted probabilities. Findings from focus group discussions are used to explain the quantitative findings. To examine the prospects for geographic scale-up, we use secondary data to compare characteristics of districts with and without insurance, using a combination of univariate and multivariate analyses. The multivariate analysis is a probit model, which models the factors associated with roll-out of CBHI to the districts. Results The household findings show that enrolment is concentrated among the better off and that adverse selection is present in the scheme. The district level findings show that to date, the scheme has been implemented in the most affluent areas, in closest proximity to the district hospitals, and in areas where quality of care is relatively good. Conclusions The household-level findings indicate that the scheme suffers from poor risk-pooling, which threatens financial sustainability. The district-level findings call into question whether or not the Government of Laos can successfully expand to more remote, less affluent districts, with lower population density. We discuss the policy implications of the findings and specifically address whether CBHI can serve as a foundation for a national scheme, while exploring alternative approaches to reaching the informal sector in Laos and other countries attempting to achieve UHC. PMID:24344925

Natural gas projects in the developing world: An empirical evaluation of merits, obstacles, and risks

NASA Astrophysics Data System (ADS)

Mor, Amit

Significant amounts of natural gas have been discovered in developing countries throughout the years during the course of oil exploration. The vast majority of these resources have not been utilized. Some developing countries may benefit from a carefully planned utilization of their indigenous resources, which can either be exported or used domestically to substitute imported or exportable fuels or feedstock. Governments, potential private sector investors, and financiers have been searching for strategies to promote natural gas schemes, some of which have been in the pipeline for more than two decades. The purpose of this thesis is to identify the crucial factors determining the success or failure of launching natural gas projects in the developing world. The methodology used to evaluate these questions included: (1) establishing a representative sample of natural gas projects in developing countries that were either implemented or failed to materialize during the 1980-1995 period, (2) utilizing a Probit limited dependent variable econometric model in which the explained variable is project success or failure, and (3) choosing representing indicators to reflect the assumed factors affecting project success. The study identified two conditions for project success: (1) the economic viability of the project and (2) securing financing for the investment. The factors that explain the ability or inability of the sponsors to secure financing were: (1) the volume of investment that represented the large capital costs of gas transportation, distribution, and storage, (2) the level of foreign exchange constraint in the host country, and (3) the level of development of the country. The conditions for private sector participation in natural gas projects in developing countries were identified in the study by a Probit model in which the explained variable was private sector participation. The results showed that a critical condition for private sector participation is the financial profitability of a project. Other factors that explained private sector participation and the ability of the private-sector sponsor to secure financing for a project were: (1) the political risk associated with the project, (2) the foreign exchange constraint associated with the project, and (3) whether the project was domestic or export-oriented.

Tumor dose-volume response in image-guided adaptive brachytherapy for cervical cancer: A meta-regression analysis.

PubMed

Mazeron, Renaud; Castelnau-Marchand, Pauline; Escande, Alexandre; Rivin Del Campo, Eleonor; Maroun, Pierre; Lefkopoulos, Dimitri; Chargari, Cyrus; Haie-Meder, Christine

2016-01-01

Image-guided adaptive brachytherapy is a high precision technique that allows dose escalation and adaptation to tumor response. Two monocentric studies reported continuous dose-volume response relationships, however, burdened by large confidence intervals. The aim was to refine these estimations by performing a meta-regression analysis based on published series. Eligibility was limited to series reporting dosimetric parameters according to the Groupe Européen de Curiethérapie-European SocieTy for Radiation Oncology recommendations. The local control rates reported at 2-3 years were confronted to the mean D90 clinical target volume (CTV) in 2-Gy equivalent using the probit model. The impact of each series on the relationships was pondered according to the number of patients reported. An exhaustive literature search retrieved 13 series reporting on 1299 patients. D90 high-risk CTV ranged from 70.9 to 93.1 Gy. The probit model showed a significant correlation between the D90 and the probability of achieving local control (p < 0.0001). The D90 associated to a 90% probability of achieving local control was 81.4 Gy (78.3-83.8 Gy). The planning aim of 90 Gy corresponded to a 95.0% probability (92.8-96.3%). For the intermediate-risk CTV, less data were available, with 873 patients from eight institutions. Reported mean D90 intermediate-risk CTV ranged from 61.7 to 69.1 Gy. A significant dose-volume effect was observed (p = 0.009). The D90 of 60 Gy was associated to a 79.4% (60.2-86.0%) local control probability. Based on published data from a high number of patients, significant dose-volume effect relationships were confirmed and refined between the D90 of both CTV and the probability of achieving local control. Further studies based on individual data are required to develop nomograms including nondosimetric prognostic criteria. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

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.

Preventing land loss in coastal Louisiana: estimates of WTP and WTA.

PubMed

Petrolia, Daniel R; Kim, Tae-Goun

2011-03-01

A dichotomous-choice contingent-valuation survey was conducted in the State of Louisiana (USA) to estimate compensating surplus (CS) and equivalent surplus (ES) welfare measures for the prevention of future coastal wetland losses in Louisiana. Valuations were elicited using both willingness to pay (WTP) and willingness to accept compensation (WTA) payment vehicles. Mean CS (WTP) estimates based on a probit model using a Box-Cox specification on income was $825 per household annually, and mean ES (WTA) was estimated at $4444 per household annually. Regression results indicate that the major factors influencing support for land-loss prevention were income (positive, WTP model only), perceived hurricane protection benefits (positive), environmental and recreation protection (positive), distrust of government (negative), age (positive, WTA model only), and race (positive for whites). Copyright © 2010 Elsevier Ltd. All rights reserved.

Spatial Dependence and Determinants of Dairy Farmers' Adoption of Best Management Practices for Water Protection in New Zealand

NASA Astrophysics Data System (ADS)

Yang, Wei; Sharp, Basil

2017-04-01

This paper analyses spatial dependence and determinants of the New Zealand dairy farmers' adoption of best management practices to protect water quality. A Bayesian spatial durbin probit model is used to survey data collected from farmers in the Waikato region of New Zealand. The results show that farmers located near each other exhibit similar choice behaviour, indicating the importance of farmer interactions in adoption decisions. The results also address that information acquisition is the most important determinant of farmers' adoption of best management practices. Financial problems are considered a significant barrier to adopting best management practices. Overall, the existence of distance decay effect and spatial dependence in farmers' adoption decisions highlights the importance of accounting for spatial effects in farmers' decision-making, which emerges as crucial to the formulation of sustainable agriculture policy.

Is there evidence for dual causation between malaria and socioeconomic status? Findings from rural Tanzania.

PubMed

Somi, Masha F; Butler, James R G; Vahid, Farshid; Njau, Joseph; Kachur, S Patrick; Abdulla, Salim

2007-12-01

Malaria's relationship with socioeconomic status at the macroeconomic level has been established. This is the first study to explore this relationship at the microeconomic (household) level and estimate the direction of association. Malaria prevalence was measured by parasitemia, and household socioeconomic status was measured using an asset based index. Results from an instrumental variable probit model suggest that socioeconomic status is negatively associated with malaria parasitemia. Other variables that are significantly associated with parasitemia include age of the individual, use of a mosquito net on the night before interview, the number of people living in the household, whether the household was residing at their farm home at the time of interview, household wall construction, and the region of residence. Matching estimators indicate that malaria parasitemia is associated with reduced household socioeconomic status.

Toxicity of bromate to striped bass ichthyoplankton (Morone saxatilis) and juvenile spot (Leiostomus xanthurus).

PubMed

Richardson, L B; Burton, D T; Rhoderick, J C

1981-10-01

Striped bass (Morone saxatillis) eggs (12 h after fertilization) and larvae (4 d after hatching) and juvenile spot (Leiostomus xanthurus) were exposed to a series of bromate concentrations for 4, 10, and 10 d, respectively, using static replacement bioassay techniques. Three-dimensional mortality response surfaces were constructed by computerized probit regression techniques. Newly hatched striped bass prolarvae were most sensitive to bromate and had a 96-h LC50 of 30.8 mg/l (as BrO3-). Four-day-old striped bass larvae were less sensitive, with 2- to 10-d LC50s ranging from 605.0 to 92.6 mg/l BrO3-, respectively. Juvenile spot were least sensitive, with 1- to 10-d LC50s ranging from 698.0 to 278.6 mg/l BrO3-, respectively.

Spatial Dependence and Determinants of Dairy Farmers' Adoption of Best Management Practices for Water Protection in New Zealand.

PubMed

Yang, Wei; Sharp, Basil

2017-04-01

This paper analyses spatial dependence and determinants of the New Zealand dairy farmers' adoption of best management practices to protect water quality. A Bayesian spatial durbin probit model is used to survey data collected from farmers in the Waikato region of New Zealand. The results show that farmers located near each other exhibit similar choice behaviour, indicating the importance of farmer interactions in adoption decisions. The results also address that information acquisition is the most important determinant of farmers' adoption of best management practices. Financial problems are considered a significant barrier to adopting best management practices. Overall, the existence of distance decay effect and spatial dependence in farmers' adoption decisions highlights the importance of accounting for spatial effects in farmers' decision-making, which emerges as crucial to the formulation of sustainable agriculture policy.

Who gets a second chance? An investigation of Ohio's blended juvenile sentence.

PubMed

Cheesman, Fred L; Waters, Nicole L; Hurst, Hunter

2010-01-01

Factors differentiating blended sentencing cases (Serious Youthful Offenders or SYOs) from conventional juvenile cases and cases transferred to the adult criminal court in Ohio were investigated using a two-stage probit. Conventional juvenile cases differed from cases selected for non-conventional processing (i.e., SYO or transfer) according to offense seriousness, number of prior Ohio Department of Youth Services placements, age and gender. Controlling for probability of selection for nonconventional processing, transfers differed from SYOs according to age, gender, and race. Minorities were significantly more likely than Whites to be transfers rather than SYOs, suggesting possible bias in the decision-making process. Objective risk and needs assessments should be used to identify the most suitable candidates for blended sentences and adult transfer and enhanced services should be provided to juvenile offenders given blended sentences.

Toxicity of Bacillus sphaericus strain 2362 on Mansonia spp. larvae.

PubMed

Petcharat, J

1991-09-01

The efficiency of Bacillus sphaericus strain 2362 (Vectolex) as larvicide against Mansonia spp. was studied. Bioassay studies showed that the toxicity of B. sphaericus on both age groups (I-II instar and III-IV instar) of Mansonia spp. larvae occurred within 24 hours. Probit analysis revealed that LC100 (one hundred per cent lethal concentration) for both age groups of M. boneae were higher than those of M. dives. Small scale field trials were done at Kreng Village, Cha-uat District, Nakhon Si Thammarat Province, one of the most serious filarial infected areas. It was indicated that 100% kill of Mansonia spp. larvae in the field occurred within 9 days after the larvicide application. When a dose of 5 times of LC100 value was used, 100% control was achieved up to about one month.

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.

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.

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.

Sensitivity to friction for primary explosives.

PubMed

Matyáš, Robert; Šelešovský, Jakub; Musil, Tomáš

2012-04-30

The sensitivity to friction for a selection of primary explosives has been studied using a small BAM friction apparatus. The probit analysis was used for the construction of a sensitivity curve for each primary explosive tested. Two groups of primary explosives were chosen for measurement (a) the most commonly used industrially produced primary explosives (e.g. lead azide, tetrazene, dinol, lead styphnate) and (b) the most produced improvised primary explosives (e.g. triacetone triperoxide, hexamethylenetriperoxide diamine, mercury fulminate, acetylides of heavy metals). A knowledge of friction sensitivity is very important for determining manipulation safety for primary explosives. All the primary explosives tested were carefully characterised (synthesis procedure, shape and size of crystals). The sensitivity curves obtained represent a unique set of data, which cannot be found anywhere else in the available literature. Copyright © 2012 Elsevier B.V. All rights reserved.

Enrollment Management in Medical School Admissions: A Novel Evidence-Based Approach at One Institution.

PubMed

Burkhardt, John C; DesJardins, Stephen L; Teener, Carol A; Gay, Steven E; Santen, Sally A

2016-11-01

In higher education, enrollment management has been developed to accurately predict the likelihood of enrollment of admitted students. This allows evidence to dictate numbers of interviews scheduled, offers of admission, and financial aid package distribution. The applicability of enrollment management techniques for use in medical education was tested through creation of a predictive enrollment model at the University of Michigan Medical School (U-M). U-M and American Medical College Application Service data (2006-2014) were combined to create a database including applicant demographics, academic application scores, institutional financial aid offer, and choice of school attended. Binomial logistic regression and multinomial logistic regression models were estimated in order to study factors related to enrollment at the local institution versus elsewhere and to groupings of competing peer institutions. A predictive analytic "dashboard" was created for practical use. Both models were significant at P < .001 and had similar predictive performance. In the binomial model female, underrepresented minority students, grade point average, Medical College Admission Test score, admissions committee desirability score, and most individual financial aid offers were significant (P < .05). The significant covariates were similar in the multinomial model (excluding female) and provided separate likelihoods of students enrolling at different institutional types. An enrollment-management-based approach would allow medical schools to better manage the number of students they admit and target recruitment efforts to improve their likelihood of success. It also performs a key institutional research function for understanding failed recruitment of highly desirable candidates.

Monitoring stress and recovery: new insights for the prevention of injuries and illnesses in elite youth soccer players.

PubMed

Brink, Michel S; Visscher, Chris; Arends, Suzanne; Zwerver, Johannes; Post, Wendy J; Lemmink, Koen Apm

2010-09-01

Elite youth soccer players have a relatively high risk for injuries and illnesses due to increased physical and psychosocial stress. The aim of this study is to investigate how measures to monitor stress and recovery, and its analysis, provide useful information for the prevention of injuries and illnesses in elite youth soccer players. 53 elite soccer players between 15 and 18 years of age participated in this study. To determine physical stress, soccer players registered training and match duration and session rating of perceived exertion for two competitive seasons by means of daily training logs. The Dutch version of the Recovery Stress Questionnaire for athletes (RESTQ-Sport) was administered monthly to assess the psychosocial stress-recovery state of players. The medical staff collected injury and illness data using the standardised Fédération Internationale de Football Association registration system. ORs and 95% CIs were calculated for injuries and illnesses using multinomial regression analyses. The independent measures were stress and recovery. During the study period, 320 injuries and 82 illnesses occurred. Multinomial regression demonstrated that physical stress was related to both injury and illness (range OR 1.01 to 2.59). Psychosocial stress and recovery were related the occurrence of illness (range OR 0.56 to 2.27). Injuries are related to physical stress. Physical stress and psychosocial stress and recovery are important in relation to illness. Individual monitoring of stress and recovery may provide useful information to prevent soccer players from injuries and illnesses.

Multinomial modeling and an evaluation of common data-mining algorithms for identifying signals of disproportionate reporting in pharmacovigilance databases.

PubMed

Johnson, Kjell; Guo, Cen; Gosink, Mark; Wang, Vicky; Hauben, Manfred

2012-12-01

A principal objective of pharmacovigilance is to detect adverse drug reactions that are unknown or novel in terms of their clinical severity or frequency. One method is through inspection of spontaneous reporting system databases, which consist of millions of reports of patients experiencing adverse effects while taking one or more drugs. For such large databases, there is an increasing need for quantitative and automated screening tools to assist drug safety professionals in identifying drug-event combinations (DECs) worthy of further investigation. Existing algorithms can effectively identify problematic DECs when the frequencies are high. However these algorithms perform differently for low-frequency DECs. In this work, we provide a method based on the multinomial distribution that identifies signals of disproportionate reporting, especially for low-frequency combinations. In addition, we comprehensively compare the performance of commonly used algorithms with the new approach. Simulation results demonstrate the advantages of the proposed method, and analysis of the Adverse Event Reporting System data shows that the proposed method can help detect interesting signals. Furthermore, we suggest that these methods be used to identify DECs that occur significantly less frequently than expected, thus identifying potential alternative indications for these drugs. We provide an empirical example that demonstrates the importance of exploring underexpected DECs. Code to implement the proposed method is available in R on request from the corresponding authors. kjell@arboranalytics.com or Mark.M.Gosink@Pfizer.com Supplementary data are available at Bioinformatics online.

Public funding of pharmaceuticals in The Netherlands: investigating the effect of evidence, process and context on CVZ decision-making.

PubMed

Cerri, Karin H; Knapp, Martin; Fernandez, Jose-Luis

2014-09-01

The College Voor Zorgverzekeringen (CVZ) provides guidance to the Dutch healthcare system on funding and use of new pharmaceutical technologies. This study examined the impact of evidence, process and context factors on CVZ decisions in 2004-2009. A data set of CVZ decisions pertaining to pharmaceutical technologies was created, including 29 variables extracted from published information. A three-category outcome variable was used, defined as the decision to 'recommend', 'restrict' or 'not recommend' a technology. Technologies included in list 1A/1B or on the expensive drug list were considered recommended; those included in list 2 or for which patient co-payment is required were considered restricted; technologies not included on any reimbursement list were classified as 'not recommended'. Using multinomial logistic regression, the relative contribution of explanatory variables on CVZ decisions was assessed. In all, 244 technology appraisals (256 technologies) were analysed, with 51%, of technologies recommended, 33% restricted and 16% not recommended by CVZ for funding. The multinomial model showed significant associations (p ≤ 0.10) between CVZ outcome and several variables, including: (1) use of an active comparator and demonstration of statistical superiority of the primary endpoint in clinical trials, (2) pharmaceutical budget impact associated with introduction of the technology, (3) therapeutic indication and (4) prevalence of the target population. Results confirm the value of a comprehensive and multivariate approach to understanding CVZ decision-making.

Dental health services utilization and associated factors in children 6 to 12 years old in a low-income country.

PubMed

Medina-Solis, Carlo Eduardo; Maupomé, Gerardo; del Socorro, Herrera Miriam; Pérez-Núñez, Ricardo; Avila-Burgos, Leticia; Lamadrid-Figueroa, Hector

2008-01-01

To determine the factors associated with the dental health services utilization among children ages 6 to 12 in León, Nicaragua. A cross-sectional study was carried out in 1,400 schoolchildren. Using a questionnaire, we determined information related to utilization and independent variables in the previous year. Oral health needs were established by means of a dental examination. To identify the independent variables associated with dental health services utilization, two types of multivariate regression models were used, according to the measurement scale of the outcome variable: a) frequency of utilization as (0) none, (1) one, and (2) two or more, analyzed with the ordered logistic regression and b) the type of service utilized as (0) none, (1) preventive services, (2) curative services, and (3) both services, analyzed with the multinomial logistic regression. The proportion of children who received at least one dental service in the 12 months prior to the study was 27.7 percent. The variables associated with utilization in the two models were older age, female sex, more frequent toothbrushing, positive attitude of the mother toward the child's oral health, higher socioeconomic level, and higher oral health needs. Various predisposing, enabling, and oral health needs variables were associated with higher dental health services utilization. As in prior reports elsewhere, these results from Nicaragua confirmed that utilization inequalities exist between socioeconomic groups. The multinomial logistic regression model evidenced the association of different variables depending on the type of service used.

Circulating Prolactin Associates With Diabetes and Impaired Glucose Regulation

PubMed Central

Wang, Tiange; Lu, Jieli; Xu, Yu; Li, Mian; Sun, Jichao; Zhang, Jie; Xu, Baihui; Xu, Min; Chen, Yuhong; Bi, Yufang; Wang, Weiqing; Ning, Guang

2013-01-01

OBJECTIVE Prolactin is a major stimulus for the β-cell adaptation during gestation and guards postpartum women against gestational diabetes. Most studies of the role of prolactin on glucose metabolism have been conducted in humans and animals during pregnancy. However, little is known concerning the association between circulating prolactin and glucose metabolism outside pregnancy in epidemiological studies. We aimed to determine whether the variation of circulating prolactin concentration associates with diabetes and impaired glucose regulation (IGR) in a cross-sectional study. RESEARCH DESIGN AND METHODS We recruited 2,377 participants (1,034 men and 1,343 postmenopausal women) without hyperprolactinemia, aged 40 years and older, in Shanghai, China. Diabetes and IGR were determined by an oral glucose tolerance test. Multinomial logit analyses were performed to evaluate the relationship of prolactin with diabetes and IGR. RESULTS Prolactin levels decreased from normal glucose regulation to IGR to diabetes. Multinomial logit analyses, adjusted for potential confounding factors, showed that high circulating prolactin was associated with lower prevalence of diabetes and IGR. The adjusted odds ratios (95% CI) for IGR and diabetes for the highest compared with the lowest quartile of prolactin were 0.54 (95% CI 0.33–0.89) and 0.38 (0.24–0.59) in men and 0.54 (0.36–0.81) and 0.47 (0.32–0.70) in women. CONCLUSIONS High circulating prolactin associates with lower prevalence of diabetes and IGR in the current study. Further studies are warranted to confirm this association. PMID:23340889