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Sample records for multinomial probit model

  1. A Multinomial Probit Model with Latent Factors

    DEFF Research Database (Denmark)

    Piatek, Rémi; Gensowski, Miriam

    2017-01-01

    be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...

  2. Parameter Estimation in Probit Model for Multivariate Multinomial Response Using SMLE

    Directory of Open Access Journals (Sweden)

    Jaka Nugraha

    2012-02-01

    Full Text Available In  the  research  field  of  transportation,  market  research and  politics,  often involving  the  response  of  the multinomial multivariate  observations.  In  this  paper, we discused  a  modeling  of  multivariate  multinomial  responses  using  probit  model.  The estimated  parameters  were  calculated  using Maximum  Likelihood  Estimations  (MLE based  on  the  GHK  simulation.  method  known  as Simulated  Maximum  Likelihood Estimations (SMLE. Likelihood function on the Probit model contains probability values that must be resolved by simulation. By using  the GHK simulation algorithm,  the estimator equation has been obtained for the parameters in the model Probit  Keywords : Probit Model, Newton-Raphson Iteration,  GHK simulator, MLE, simulated log-likelihood

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

    Science.gov (United States)

    Zhang, Yongsheng; Wei, Heng; Zheng, Kangning

    2017-01-01

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

  4. Brand Choice Modeling Modeling Toothpaste Brand Choice: An Empirical Comparison of Artificial Neural Networks and Multinomial Probit Model

    Directory of Open Access Journals (Sweden)

    Tolga Kaya

    2010-11-01

    Full Text Available The purpose of this study is to compare the performances of Artificial Neural Networks (ANN and Multinomial Probit (MNP approaches in modeling the choice decision within fast moving consumer goods sector. To do this, based on 2597 toothpaste purchases of a panel sample of 404 households, choice models are built and their performances are compared on the 861 purchases of a test sample of 135 households. Results show that ANN's predictions are better while MNP is useful in providing marketing insight.

  5. Application of Multinomial Probit Model in Analyzing Factors Affecting the Occupation of Graduated Students from the University of Agricultural Applied-Science

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    H. Mohammadi

    2016-03-01

    Full Text Available Introduction:Scientificand practicaltrainingwith an emphasis onoperation andapplication of what is taught and having an empiricalapproachto education isa more suitable approach for creating jobs. Preparation of educational needs of the agricultural sector by scientificand practicaltraining and providingemploymentin agreement with education and skills is one of the most important programs in order to achieve the objectives of comprehensive development of the country. An imbalance seems to exist between the processes and materials in university courses and the skills and abilities needed by the labor market and this is the most importantreason for the failureof the university graduatesin finding employment. This studyhas beendone for understandingthe type of jobof agricultural graduatesof training center of Jihad-e-Keshavarzi in Mashhad and the factor saffecting their employment. Materials and Methods: This study is an applied research and the statistical population is 167 and includes all the students who had earned a Bachelor’s degree who had come to receive their graduation certificates in 2011. The dependent variable is type of job which includes five categories of employment in the public sector related to education, employ men unrelated to the government, employment related tothe privatesector andthe unemployed who were seeking workin the private sector. Independent variables includegender,quotainuniversityadmissions, the level of interestin thefield of study,satisfaction withthe discipline, evaluationand trainingof graduatesofvocational skillsacquired incollegegraduates'assessmentof thework culturein the societyand evaluation oflack ofcapitalas a factor preventingemployment in the academicfield. Information was collected through questionnaires and the multiple probit mode lwas used. Results and discussion: The results ofthe survey showthatjobsof graduates are divided intofour categoriesincluding:Related to the field of study and

  6. The Market for Ph.D. Holders in Greece: Probit and Multinomial Logit Analysis of their Employment Status

    OpenAIRE

    Joan Daouli; Eirini Konstantina Nikolatou

    2015-01-01

    The objective of this paper is to investigate the factors influencing the probability that a Ph.D. holder in Greece will work in the academic sector, as well as the probability of his or her choosing employment in various sectors of industry and occupational categories. Probit/multinomial logit models are employed using the 2001 Census data. The empirical results indicate that being young, married, having a Ph.D. in Natural Sciences and/or in Engineering, granted by a Greek university, increa...

  7. Heterogeneous Impact of the “Seguro Popular” Program on the Utilization of Obstetrical Services in Mexico, 2001–2006: A Multinomial Probit Model with a Discrete Endogenous Variable

    Science.gov (United States)

    Sosa-Rubi, Sandra G.; Galárraga, Omar

    2009-01-01

    Objective We evaluated the impact of Seguro Popular (SP), a program introduced in 2001 in Mexico primarily to finance health care for the poor. We focused on the effect of household enrollment in SP on pregnant women’s access to obstetrical services, an important outcome measure of both maternal and infant health. Data We relied upon data from the cross-sectional 2006 National Health and Nutrition Survey (ENSANUT) in Mexico. We analyzed the responses of 3,890 women who delivered babies during 2001–2006 and whose households lacked employer-based health care coverage. Methods We formulated a multinomial probit model that distinguished between three mutually exclusive sites for delivering a baby: a health unit specifically accredited by SP; a non-SP-accredited clinic run by the Department of Health (Secretaría de Salud, or SSA); and private obstetrical care. Our model accounted for the endogeneity of the household’s binary decision to enroll in the SP program. Results Women in households that participated in the SP program had a much stronger preference for having a baby in a SP-sponsored unit rather than paying out of pocket for a private delivery. At the same time, participation in SP was associated with a stronger preference for delivering in the private sector rather than at a state-run SSA clinic. On balance, the Seguro Popular program reduced pregnant women’s attendance at an SSA clinic much more than it reduced the probability of delivering a baby in the private sector. The quantitative impact of the SP program varied with the woman’s education and health, as well as the assets and location (rural versus urban) of the household. Conclusions The SP program had a robust, significantly positive impact on access to obstetrical services. Our finding that women enrolled in SP switched from non-SP state-run facilities, rather than from out-of-pocket private services, is important for public policy and requires further exploration. PMID:18824268

  8. FORMULASI MODEL PERMUTASI SIKLIS DENGAN OBJEK MULTINOMIAL

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    Sukma Adi Perdana

    2016-10-01

    Full Text Available Penelitian ini bertujuan membangun model matematika untuk menghitung jumlah susunan objek dari permutasi siklis yang memiliki objek multinomial. Model yang dibangun dibatasi untuk permutasi siklis yang memiliki objek multinomial dengan minimal ada satu jenis objek beranggotakan tunggal. Pemodelan dilakukan berdasarkan struktur matematika dari permutasi siklis dan permutasi multinomial. Model permutasi siklis yang memiliki objek multinomial telah dirumuskan.   Pembuktian model telah dilakukan melalui validasi struktur serta validasi hasil yang dilakukan dengan cara membandingkan hasil perhitungan model dan hasil pencacahan. Teorema tentang permutasi siklis dengan objek multinomial juga telah dibangun. Kata kunci:  pemodelan , permutasi siklis, permutasi multinomial This study aims at constructing mathematical model to count the number of arrangement of objects form cyclical permutation that has multinomial objects. The model constructed is limited to cyclical permutation that has multinomial object in which at least one kind of object having single cardinality is contained within. Modelling is undertaken based on mathematical structure of cyclical permutation and multinomial permutation. Cyclical permutation model having multinomial object has been formulated as . The proof of the model has been undertaken by validating structure and validating the outcome which was conducted by comparing counting result of model and counting result manually. The theorem of cyclical permutation with multinomial object has also been developed. Keywords: modelling, cyclical permutation, multinomial permutation

  9. Interpreting and Understanding Logits, Probits, and other Non-Linear Probability Models

    DEFF Research Database (Denmark)

    Breen, Richard; Karlson, Kristian Bernt; Holm, Anders

    2018-01-01

    Methods textbooks in sociology and other social sciences routinely recommend the use of the logit or probit model when an outcome variable is binary, an ordered logit or ordered probit when it is ordinal, and a multinomial logit when it has more than two categories. But these methodological...... guidelines take little or no account of a body of work that, over the past 30 years, has pointed to problematic aspects of these nonlinear probability models and, particularly, to difficulties in interpreting their parameters. In this chapterreview, we draw on that literature to explain the problems, show...

  10. Parameter identification in multinomial processing tree models

    NARCIS (Netherlands)

    Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

    2010-01-01

    Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

  11. Interpreting Results from the Multinomial Logit Model

    DEFF Research Database (Denmark)

    Wulff, Jesper

    2015-01-01

    This article provides guidelines and illustrates practical steps necessary for an analysis of results from the multinomial logit model (MLM). The MLM is a popular model in the strategy literature because it allows researchers to examine strategic choices with multiple outcomes. However, there see...... suitable for both interpretation and communication of results. The pratical steps are illustrated through an application of the MLM to the choice of foreign market entry mode.......This article provides guidelines and illustrates practical steps necessary for an analysis of results from the multinomial logit model (MLM). The MLM is a popular model in the strategy literature because it allows researchers to examine strategic choices with multiple outcomes. However, there seem...... to be systematic issues with regard to how researchers interpret their results when using the MLM. In this study, I present a set of guidelines critical to analyzing and interpreting results from the MLM. The procedure involves intuitive graphical representations of predicted probabilities and marginal effects...

  12. Implicit moral evaluations: A multinomial modeling approach.

    Science.gov (United States)

    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.

  13. Nonparametric Bayesian models through probit stick-breaking processes.

    Science.gov (United States)

    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.

  14. Pricing Mining Concessions Based on Combined Multinomial Pricing Model

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    Chang Xiao

    2017-01-01

    Full Text Available A combined multinomial pricing model is proposed for pricing mining concession in which the annualized volatility of the price of mineral products follows a multinomial distribution. First, a combined multinomial pricing model is proposed which consists of binomial pricing models calculated according to different volatility values. Second, a method is provided to calculate the annualized volatility and the distribution. Third, the value of convenience yields is calculated based on the relationship between the futures price and the spot price. The notion of convenience yields is used to adjust our model as well. Based on an empirical study of a Chinese copper mine concession, we verify that our model is easy to use and better than the model with constant volatility when considering the changing annualized volatility of the price of the mineral product.

  15. Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

    Science.gov (United States)

    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…

  16. Multinomial-exponential reliability function: a software reliability model

    International Nuclear Information System (INIS)

    Saiz de Bustamante, Amalio; Saiz de Bustamante, Barbara

    2003-01-01

    The multinomial-exponential reliability function (MERF) was developed during a detailed study of the software failure/correction processes. Later on MERF was approximated by a much simpler exponential reliability function (EARF), which keeps most of MERF mathematical properties, so the two functions together makes up a single reliability model. The reliability model MERF/EARF considers the software failure process as a non-homogeneous Poisson process (NHPP), and the repair (correction) process, a multinomial distribution. The model supposes that both processes are statistically independent. The paper discusses the model's theoretical basis, its mathematical properties and its application to software reliability. Nevertheless it is foreseen model applications to inspection and maintenance of physical systems. The paper includes a complete numerical example of the model application to a software reliability analysis

  17. Reasons for not buying a car : a probit-selection multinomial logit choice model

    NARCIS (Netherlands)

    Gao, Y.; Rasouli, S.; Timmermans, H.J.P.

    2014-01-01

    Generating and maintaining gradients of cell density and extracellular matrix (ECM) components is a prerequisite for the development of functionality of healthy tissue. Therefore, gaining insights into the drivers of spatial organization of cells and the role of ECM during tissue morphogenesis is

  18. A Probit Model for the State of the Greek GDP Growth

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    Stavros Degiannakis

    2015-08-01

    Full Text Available The paper provides probability estimates of the state of the GDP growth. A regime-switching model defines the probability of the Greek GDP being in boom or recession. Then probit models extract the predictive information of a set of explanatory (economic and financial variables regarding the state of the GDP growth. A contemporaneous, as well as a lagged, relationship between the explanatory variables and the state of the GDP growth is conducted. The mean absolute distance (MAD between the probability of not being in recession and the probability estimated by the probit model is the function that evaluates the performance of the models. The probit model with the industrial production index and the realized volatility as the explanatory variables has the lowest MAD value of 6.43% (7.94% in the contemporaneous (lagged relationship.

  19. The Use of a Probit Model for the Validation of Selection Procedures.

    Science.gov (United States)

    Dagenais, Denyse L.

    1984-01-01

    After a review of the disadvantages of linear models for estimating the probability of academic success from previous school records and admission test results, the use of a probit model is proposed. The model is illustrated with admissions data from the Ecole des Hautes Etudes Commerciales in Montreal. (Author/BW)

  20. Interpreting Marginal Effects in the Multinomial Logit Model

    DEFF Research Database (Denmark)

    Wulff, Jesper

    2014-01-01

    with a substantial increase in the probability of entering a foreign market using a joint venture, while increases in the unpredictability in the host country environment are associated with a lower probability of wholly owned subsidiaries and a higher probability of exporting entries....... that have entered foreign markets. Through the application of a multinomial logit model, careful analysis of the marginal effects is performed through graphical representations, marginal effects at the mean, average marginal effects and elasticities. I show that increasing cultural distance is associated......This paper presents the challenges when researchers interpret results about relationships between variables from discrete choice models with multiple outcomes. The recommended approach is demonstrated by testing predictions from transaction cost theory on a sample of 246 Scandinavian firms...

  1. Evaluating the performance of simple estimators for probit models with two dummy endogenous regressors

    DEFF Research Database (Denmark)

    Holm, Anders; Nielsen, Jacob Arendt

    2013-01-01

    This study considers the small sample performance of approximate but simple two-stage estimators for probit models with two endogenous binary covariates. Monte Carlo simulations showthat all the considered estimators, including the simulated maximum-likelihood (SML) estimation, of the trivariate ...

  2. Another Look at the Method of Y-Standardization in Logit and Probit Models

    DEFF Research Database (Denmark)

    Karlson, Kristian Bernt

    2015-01-01

    This paper takes another look at the derivation of the method of Y-standardization used in sociological analysis involving comparisons of coefficients across logit or probit models. It shows that the method can be derived under less restrictive assumptions than hitherto suggested. Rather than...

  3. Modeling Information Content Via Dirichlet-Multinomial Regression Analysis.

    Science.gov (United States)

    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.

  4. The bivariate probit model of uncomplicated control of tumor: a heuristic exposition of the methodology

    International Nuclear Information System (INIS)

    Herbert, Donald

    1997-01-01

    Purpose: To describe the concept, models, and methods for the construction of estimates of joint probability of uncomplicated control of tumors in radiation oncology. Interpolations using this model can lead to the identification of more efficient treatment regimens for an individual patient. The requirement to find the treatment regimen that will maximize the joint probability of uncomplicated control of tumors suggests a new class of evolutionary experimental designs--Response Surface Methods--for clinical trials in radiation oncology. Methods and Materials: The software developed by Lesaffre and Molenberghs is used to construct bivariate probit models of the joint probability of uncomplicated control of cancer of the oropharynx from a set of 45 patients for each of whom the presence/absence of recurrent tumor (the binary event E-bar 1 /E 1 ) and the presence/absence of necrosis (the binary event E 2 /E-bar 2 ) of the normal tissues of the target volume is recorded, together with the treatment variables dose, time, and fractionation. Results: The bivariate probit model can be used to select a treatment regime that will give a specified probability, say P(S) = 0.60, of uncomplicated control of tumor by interpolation within a set of treatment regimes with known outcomes of recurrence and necrosis. The bivariate probit model can be used to guide a sequence of clinical trials to find the maximum probability of uncomplicated control of tumor for patients in a given prognostic stratum using Response Surface methods by extrapolation from an initial set of treatment regimens. Conclusions: The design of treatments for individual patients and the design of clinical trials might be improved by use of a bivariate probit model and Response Surface Methods

  5. DETERMINANTS OF SOVEREIGN RATING: FACTOR BASED ORDERED PROBIT MODELS FOR PANEL DATA ANALYSIS MODELING FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Dilek Teker

    2013-01-01

    Full Text Available The aim of this research is to compose a new rating methodology and provide credit notches to 23 countries which of 13 are developed and 10 are emerging. There are various literature that explains the determinants of credit ratings. Following the literature, we select 11 variables for our model which of 5 are eliminated by the factor analysis. We use specific dummies to investigate the structural breaks in time and cross section such as pre crises, post crises, BRIC membership, EU membership, OPEC membership, shipbuilder country and platinum reserved country. Then we run an ordered probit model and give credit notches to the countries. We use FITCH ratings as benchmark. Thus, at the end we compare the notches of FITCH with the ones we derive out of our estimated model.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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 maintained 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.

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

    Science.gov (United States)

    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.

  9. A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    ' propensity to engage in various corrective maneuvers in the case of the critical event of vehicle travelling. Five lateral and speed control maneuvers are considered: “braking”, “steering”, “braking & steering”, and “other maneuvers”, in addition to a “no action” option. The analyzed data are retrieved from...... the United States National Automotive Sampling System General Estimates System (GES) crash database for the years 2005-2009. Results show (i) the correlation between crash avoidance maneuvers and crash severity, and (ii) the link between drivers' attributes, risky driving behavior, road characteristics...

  10. A dynamic random effects multinomial logit model of household car ownership

    DEFF Research Database (Denmark)

    Bue Bjørner, Thomas; Leth-Petersen, Søren

    2007-01-01

    Using a large household panel we estimate demand for car ownership by means of a dynamic multinomial model with correlated random effects. Results suggest that the persistence in car ownership observed in the data should be attributed to both true state dependence and to unobserved heterogeneity...... (random effects). It also appears that random effects related to single and multiple car ownership are correlated, suggesting that the IIA assumption employed in simple multinomial models of car ownership is invalid. Relatively small elasticities with respect to income and car costs are estimated...

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

    Directory of Open Access Journals (Sweden)

    Tsair-Fwu Lee

    2015-01-01

    Full Text Available 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, γ50 = 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.

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

    Science.gov (United States)

    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

  13. Multinomial Response Models, for Modeling and Determining Important Factors in Different Contraceptive Methods in Women

    Directory of Open Access Journals (Sweden)

    E Haji Nejad

    2001-06-01

    Full Text Available Difference aspects of multinomial statistical modelings and its classifications has been studied so far. In these type of problems Y is the qualitative random variable with T possible states which are considered as classifications. The goal is prediction of Y based on a random Vector X ? IR^m. Many methods for analyzing these problems were considered. One of the modern and general method of classification is Classification and Regression Trees (CART. Another method is recursive partitioning techniques which has a strange relationship with nonparametric regression. Classical discriminant analysis is a standard method for analyzing these type of data. Flexible discriminant analysis method which is a combination of nonparametric regression and discriminant analysis and classification using spline that includes least square regression and additive cubic splines. Neural network is an advanced statistical method for analyzing these types of data. In this paper properties of multinomial logistics regression were investigated and this method was used for modeling effective factors in selecting contraceptive methods in Ghom province for married women age 15-49. The response variable has a tetranomial distibution. The levels of this variable are: nothing, pills, traditional and a collection of other contraceptive methods. A collection of significant independent variables were: place, age of women, education, history of pregnancy and family size. Menstruation age and age at marriage were not statistically significant.

  14. An Empirical Analysis of Television Commercial Ratings in Alternative Competitive Environments Using Multinomial Logit Model

    Directory of Open Access Journals (Sweden)

    Dilek ALTAŞ

    2013-05-01

    Full Text Available Watching the commercials depends on the choice of the viewer. Most of the television viewing takes place during “Prime-Time” unfortunately; many viewers opt to zap to other channels when commercials start. The television viewers’ demographic characteristics may indicate the likelihood of the zapping frequency. Analysis made by using Multinomial Logit Model indicates how effective the demographic variables are in the watching rate of the first minute of the television commercials.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  18. A metric for cross-sample comparisons using logit and probit

    DEFF Research Database (Denmark)

    Karlson, Kristian Bernt

    relative to an arbitrary scale, which makes the coefficients difficult both to interpret and to compare across groups or samples. Do differences in coefficients reflect true differences or differences in scales? This cross-sample comparison problem raises concerns for comparative research. However, we......* across groups or samples, making it suitable for situations met in real applications in comparative research. Our derivations also extend to the probit and to ordered and multinomial models. The new metric is implemented in the Stata command nlcorr....

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    E Y Arima

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2013-10-01

    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.

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

    Science.gov (United States)

    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).

  5. Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

    Directory of Open Access Journals (Sweden)

    Ibsen Chivatá Cárdenas

    2008-05-01

    Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions

  6. and Multinomial Logistic Regression

    African Journals Online (AJOL)

    This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Snedden, Gregg A.; Steyer, Gregory D.

    2013-01-01

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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%).

  12. PROBIT MODEL ANALYSIS OF SMALLHOLDER’S FARMERS DECISION TO USE AGROCHEMICAL INPUTS IN GWAGWALADA AND KUJE AREA COUNCILS OF FEDERAL CAPITAL TERRITORY, ABUJA, NIGERIA

    Directory of Open Access Journals (Sweden)

    Omotayo Olugbenga Alabi

    2014-01-01

    Full Text Available This study examined Probit model analysis of smallholder’s farmers decision to use agrochemical inputs in Gwagwalada and Kuje Area Councils of Federal Capital Territory, Abuja, Nigeria. Primary data were used for this study. Data were obtained using structured questionnaire. The questionnaires were administered to sixty smallholder’s farmers sampled using a two-stage sampling technique. Data obtained were analyzed using descriptive statistics and Probit model. Eight estimators, age; farm-size; education–level; extension services; access to credit; off-farm income; experiences in farming; in the Probit model were found statistically significant. Results show that the probability of using agrochemical inputs increases with age; farm-size; family-size; education-level; extension services; experiences in farming but decreases where they have off-farm income and access to credits. Mc Fadden Pseudo-R 2 gives 0.6866 and Probit model correctly classified 93%. This study concluded that capacity of agricultural extension agents needs to be improved in the study area to educate farmers to invest in agrochemicals and improved agricultural technologies. Also, Government needs to improve on good road networks and appropriate policies to regulate standard, use, safety needs and environment of use of agrochemicals in the study area.

  13. The Effect of Task Duration on Event-Based Prospective Memory: A Multinomial Modeling Approach

    Directory of Open Access Journals (Sweden)

    Hongxia Zhang

    2017-11-01

    Full Text Available Remembering to perform an action when a specific event occurs is referred to as Event-Based Prospective Memory (EBPM. This study investigated how EBPM performance is affected by task duration by having university students (n = 223 perform an EBPM task that was embedded within an ongoing computer-based color-matching task. For this experiment, we separated the overall task’s duration into the filler task duration and the ongoing task duration. The filler task duration is the length of time between the intention and the beginning of the ongoing task, and the ongoing task duration is the length of time between the beginning of the ongoing task and the appearance of the first Prospective Memory (PM cue. The filler task duration and ongoing task duration were further divided into three levels: 3, 6, and 9 min. Two factors were then orthogonally manipulated between-subjects using a multinomial processing tree model to separate the effects of different task durations on the two EBPM components. A mediation model was then created to verify whether task duration influences EBPM via self-reminding or discrimination. The results reveal three points. (1 Lengthening the duration of ongoing tasks had a negative effect on EBPM performance while lengthening the duration of the filler task had no significant effect on it. (2 As the filler task was lengthened, both the prospective and retrospective components show a decreasing and then increasing trend. Also, when the ongoing task duration was lengthened, the prospective component decreased while the retrospective component significantly increased. (3 The mediating effect of discrimination between the task duration and EBPM performance was significant. We concluded that different task durations influence EBPM performance through different components with discrimination being the mediator between task duration and EBPM performance.

  14. Modeling Unobserved Consideration Sets for Household Panel Data

    NARCIS (Netherlands)

    J.E.M. van Nierop; R. Paap (Richard); B. Bronnenberg; Ph.H.B.F. Franses (Philip Hans)

    2000-01-01

    textabstractWe propose a new method to model consumers' consideration and choice processes. We develop a parsimonious probit type model for consideration and a multinomial probit model for choice, given consideration. Unlike earlier models of consideration ours is not prone to the curse of

  15. Exploring the Factors that Impact on Transit Use through an Ordered Probit Model: the Case of Metro of Madrid

    Energy Technology Data Exchange (ETDEWEB)

    Eboli, L.; Forciniti, C.; Mazzulla, G.; Calvo, F.

    2016-07-01

    The configuration of urban areas is the result of a cyclic relationship between land use and transportation system: the changes in transportation system arrangements influence the localisation of residence and economic activities, as well as the changes in land use affect transportation system characteristics. In this context, by operating on land use, travel demand can be shift from the individual transportation modes to transit systems. In the literature, many conceptual models were proposed to describe the complex relationship between land use and travel behaviour. In addition to spatial variation, the study of travel demand shows the categorical variation of variables. This work aims to analyse the influence of the categorical variation of variables impacting on transit use. An ordered probit model is proposed for evaluating how transit use depends on variables related to socio-economic characteristics of population, territorial features, accessibility, and transportation system. The study case is Madrid metro network (Spain). The results show a strong influence of characteristics of population and land use variables on daily trips made using metro system and highlighted the aspects that mainly impact on the choice to travel by metro, providing useful suggestions for shifting people from individual transportation mode to transit systems. (Author)

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  18. The Effect of Supplemental Instruction on Retention: A Bivariate Probit Model

    Science.gov (United States)

    Bowles, Tyler J.; Jones, Jason

    2004-01-01

    Single equation regression models have been used to test the effect of Supplemental Instruction (SI) on student retention. These models, however, fail to account for the two salient features of SI attendance and retention: (1) both SI attendance and retention are categorical variables, and (2) are jointly determined endogenous variables. Adopting…

  19. Multinomial logistic models explaining income changes of migrants to high-amenity counties.

    Science.gov (United States)

    Von Reichert, C; Rudzitis, G

    1992-01-01

    "A survey of residents of and migrants to 15 fast-growing wilderness counties [in the United States] showed that only 25 percent of the migrants increased their income, while almost 50 percent accepted income losses upon their moves to high-amenity counties. Concomitantly, amenities and quality of life were more important factors in the migration decision than was employment, for instance. We focused on migrants in the labor force and employed multinomial logistic regression to identify the impact of migrants' characteristics, their satisfaction/dissatisfaction with previous location (push), and the importance of destination features (pull) on income change." excerpt

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

    Energy Technology Data Exchange (ETDEWEB)

    Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam [Pusat Pengajian Sains Matematik, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia amirul@unisel.edu.my, zalila@cs.usm.my, norlida@usm.my, adam@usm.my (Malaysia)

    2015-10-22

    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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  4. A probit- log- skew-normal mixture model for repeated measures data with excess zeros, with application to a cohort study of paediatric respiratory symptoms

    Directory of Open Access Journals (Sweden)

    Johnston Neil W

    2010-06-01

    Full Text Available Abstract Background A zero-inflated continuous outcome is characterized by occurrence of "excess" zeros that more than a single distribution can explain, with the positive observations forming a skewed distribution. Mixture models are employed for regression analysis of zero-inflated data. Moreover, for repeated measures zero-inflated data the clustering structure should also be modeled for an adequate analysis. Methods Diary of Asthma and Viral Infections Study (DAVIS was a one year (2004 cohort study conducted at McMaster University to monitor viral infection and respiratory symptoms in children aged 5-11 years with and without asthma. Respiratory symptoms were recorded daily using either an Internet or paper-based diary. Changes in symptoms were assessed by study staff and led to collection of nasal fluid specimens for virological testing. The study objectives included investigating the response of respiratory symptoms to respiratory viral infection in children with and without asthma over a one year period. Due to sparse data daily respiratory symptom scores were aggregated into weekly average scores. More than 70% of the weekly average scores were zero, with the positive scores forming a skewed distribution. We propose a random effects probit/log-skew-normal mixture model to analyze the DAVIS data. The model parameters were estimated using a maximum marginal likelihood approach. A simulation study was conducted to assess the performance of the proposed mixture model if the underlying distribution of the positive response is different from log-skew normal. Results Viral infection status was highly significant in both probit and log-skew normal model components respectively. The probability of being symptom free was much lower for the week a child was viral positive relative to the week she/he was viral negative. The severity of the symptoms was also greater for the week a child was viral positive. The probability of being symptom free was

  5. Modeling a Multinomial Logit Model of Intercity Travel Mode Choice Behavior for All Trips in Libya

    OpenAIRE

    Manssour A. Abdulsalam Bin Miskeen; Ahmed Mohamed Alhodairi; Riza Atiq Abdullah Bin O. K. Rahmat

    2013-01-01

    In the planning point of view, it is essential to have mode choice, due to the massive amount of incurred in transportation systems. The intercity travellers in Libya have distinct features, as against travellers from other countries, which includes cultural and socioeconomic factors. Consequently, the goal of this study is to recognize the behavior of intercity travel using disaggregate models, for projecting the demand of nation-level intercity travel in Libya. Multinom...

  6. Recreation Value of Water to Wetlands in the San Joaquin Valley: Linked Multinomial Logit and Count Data Trip Frequency Models

    Science.gov (United States)

    Creel, Michael; Loomis, John

    1992-10-01

    The recreational benefits from providing increased quantities of water to wildlife and fisheries habitats is estimated using linked multinomial logit site selection models and count data trip frequency models. The study encompasses waterfowl hunting, fishing and wildlife viewing at 14 recreational resources in the San Joaquin Valley, including the National Wildlife Refuges, the State Wildlife Management Areas, and six river destinations. The economic benefits of increasing water supplies to wildlife refuges were also examined by using the estimated models to predict changing patterns of site selection and overall participation due to increases in water allocations. Estimates of the dollar value per acre foot of water are calculated for increases in water to refuges. The resulting model is a flexible and useful tool for estimating the economic benefits of alternative water allocation policies for wildlife habitat and rivers.

  7. Effectiveness of enforcement levels of speed limit and drink driving laws and associated factors – Exploratory empirical analysis using a bivariate ordered probit model

    Directory of Open Access Journals (Sweden)

    Behram Wali

    2017-06-01

    Full Text Available The contemporary traffic safety research comprises little information on quantifying the simultaneous association between drink driving and speeding among fatally injured drivers. Potential correlation between driver's drink driving and speeding behavior poses a substantial methodological concern which needs investigation. This study therefore focused on investigating the simultaneous impact of socioeconomic factors, fatalities, vehicle ownership, health services and highway agency road safety policies on enforcement levels of speed limit and drink driving laws. The effectiveness of enforcement levels of speed limit and drink driving laws has been investigated through development of bivariate ordered probit model using data extricated from WHO's global status report on road safety in 2013. The consistent and intuitive parameter estimates along with statistically significant correlation between response outcomes validates the statistical supremacy of bivariate ordered probit model. The results revealed that fatalities per thousand registered vehicles, hospital beds per hundred thousand population and road safety policies are associated with a likely medium or high effectiveness of enforcement levels of speed limit and drink driving laws, respectively. Also, the model encapsulates the effect of several other agency related variables and socio-economic status on the response outcomes. Marginal effects are reported for analyzing the impact of such factors on intermediate categories of response outcomes. The results of this study are expected to provide necessary insights to elemental enforcement programs. Also, marginal effects of explanatory variables may provide useful directions for formulating effective policy countermeasures for overcoming driver's speeding and drink driving behavior.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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…

  11. Determination of the Factors Influencing Store Preference in Erzurum by a Multinomial Logit Model

    Directory of Open Access Journals (Sweden)

    Hüseyin ÖZER

    2008-12-01

    Full Text Available The main objective of this study is to determine factors influencing store preference of the store costumers in Erzurum in terms of some characteristics of the store and its product and costumers’ demographic characteristics (sex, age, marital status, level of education and their income level. In order to carry out this objective, Pearson chi-square test is applied to determine whether there is a relationship between the store preference and customer, stores, and some characteristics of products and a multinominal logit model is fitted by stepwise regression method to the cross-section data compiled from a questionnaire applied to 384 store costumers in the center of Erzurum province. According to the model estimation and test results, the variables of marital status (married, education (primary and cheapness (unimportant for Migros; education (middle for Özmar and marital status (married for the other stores are determined as statistically significant at the level of 5 percent

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Aline Araújo Nobre

    2017-08-01

    Full Text Available ABSTRACT OBJECTIVE 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. METHODS 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. RESULTS 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 CONCLUSIONS 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.

  16. Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

    Directory of Open Access Journals (Sweden)

    Yanyong Guo

    2017-01-01

    Full Text Available The primary objective of this study is to evaluate factors affecting e-bike involved crash and license plate use in China. E-bike crashes data were collected from police database and completed through a telephone interview. Noncrash samples were collected by a questionnaire survey. A bivariate probit (BP model was developed to simultaneously examine the significant factors associated with e-bike involved crash and e-bike license plate and to account for the correlations between them. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results show that several contributory factors, including gender, age, education level, driver license, car in household, experiences in using e-bike, law compliance, and aggressive driving behaviors, are found to have significant impacts on both e-bike involved crash and license plate use. Moreover, type of e-bike, frequency of using e-bike, impulse behavior, degree of riding experience, and risk perception scale are found to be associated with e-bike involved crash. It is also found that e-bike involved crash and e-bike license plate use are strongly correlated and are negative in direction. The result enhanced our comprehension of the factors related to e-bike involved crash and e-bike license plate use.

  17. Predicting Lung Radiotherapy-Induced Pneumonitis Using a Model Combining Parametric Lyman Probit With Nonparametric Decision Trees

    International Nuclear Information System (INIS)

    Das, Shiva K.; Zhou Sumin; Zhang, Junan; Yin, F.-F.; Dewhirst, Mark W.; Marks, Lawrence B.

    2007-01-01

    Purpose: To develop and test a model to predict for lung radiation-induced Grade 2+ pneumonitis. Methods and Materials: The model was built from a database of 234 lung cancer patients treated with radiotherapy (RT), of whom 43 were diagnosed with pneumonitis. The model augmented the predictive capability of the parametric dose-based Lyman normal tissue complication probability (LNTCP) metric by combining it with weighted nonparametric decision trees that use dose and nondose inputs. The decision trees were sequentially added to the model using a 'boosting' process that enhances the accuracy of prediction. The model's predictive capability was estimated by 10-fold cross-validation. To facilitate dissemination, the cross-validation result was used to extract a simplified approximation to the complicated model architecture created by boosting. Application of the simplified model is demonstrated in two example cases. Results: The area under the model receiver operating characteristics curve for cross-validation was 0.72, a significant improvement over the LNTCP area of 0.63 (p = 0.005). The simplified model used the following variables to output a measure of injury: LNTCP, gender, histologic type, chemotherapy schedule, and treatment schedule. For a given patient RT plan, injury prediction was highest for the combination of pre-RT chemotherapy, once-daily treatment, female gender and lowest for the combination of no pre-RT chemotherapy and nonsquamous cell histologic type. Application of the simplified model to the example cases revealed that injury prediction for a given treatment plan can range from very low to very high, depending on the settings of the nondose variables. Conclusions: Radiation pneumonitis prediction was significantly enhanced by decision trees that added the influence of nondose factors to the LNTCP formulation

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-04-01

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

  20. Reproductive risk factors assessment for anaemia among pregnant women in India using a multinomial logistic regression model.

    Science.gov (United States)

    Perumal, Vanamail

    2014-07-01

    To assess reproductive risk factors for anaemia among pregnant women in urban and rural areas of India. The International Institute of Population Sciences, India, carried out third National Family Health Survey in 2005-2006 to estimate a key indicator from a sample of ever-married women in the reproductive age group 15-49 years. Data on various dimensions were collected using a structured questionnaire, and anaemia was measured using a portable HemoCue instrument. Anaemia prevalence among pregnant women was compared between rural and urban areas using chi-square test and odds ratio. Multinomial logistic regression analysis was used to determine risk factors. Anaemia prevalence was assessed among 3355 pregnant women from rural areas and 1962 pregnant women from urban areas. Moderate-to-severe anaemia in rural areas (32.4%) is significantly more common than in urban areas (27.3%) with an excess risk of 30%. Gestational age specific prevalence of anaemia significantly increases in rural areas after 6 months. Pregnancy duration is a significant risk factor in both urban and rural areas. In rural areas, increasing age at marriage and mass media exposure are significant protective factors of anaemia. However, more births in the last five years, alcohol consumption and smoking habits are significant risk factors. In rural areas, various reproductive factors and lifestyle characteristics constitute significant risk factors for moderate-to-severe anaemia. Therefore, intensive health education on reproductive practices and the impact of lifestyle characteristics are warranted to reduce anaemia prevalence. © 2014 John Wiley & Sons Ltd.

  1. Survival analysis with covariates in combination with multinomial analysis to parametrize time to event for multi-state models

    NARCIS (Netherlands)

    Feenstra, T.L.; Postmus, D.; Quik, E.H.; Langendijk, H.; Krabbe, P.F.M.

    Objectives: Recent ISPOR Good practice guidelines as well as literature encourage to use a single distribution rather than the latent failure approach to model time to event for patient level simulation models with multiple competing outcomes. Aim was to apply the preferred method of a single

  2. Survival analysis with covariates in combination with multinomial analysis to parametrize time to event for multi-state models

    NARCIS (Netherlands)

    Feenstra, T.L.; Postmus, D.; Quik, E.H.; Langendijk, H.; Krabbe, P.F.M.

    2013-01-01

    Objectives: Recent ISPOR Good practice guidelines as well as literature encourage to use a single distribution rather than the latent failure approach to model time to event for patient level simulation models with multiple competing outcomes. Aim was to apply the preferred method of a single

  3. Prevalence and Predictors of Pre-Diabetes and Diabetes among Adults 18 Years or Older in Florida: A Multinomial Logistic Modeling Approach.

    Directory of Open Access Journals (Sweden)

    Ifechukwude Obiamaka Okwechime

    Full Text Available Individuals with pre-diabetes and diabetes have increased risks of developing macro-vascular complications including heart disease and stroke; which are the leading causes of death globally. The objective of this study was to estimate the prevalence of pre-diabetes and diabetes, and to investigate their predictors among adults ≥18 years in Florida.Data covering the time period January-December 2013, were obtained from Florida's Behavioral Risk Factor Surveillance System (BRFSS. Survey design of the study was declared using SVYSET statement of STATA 13.1. Descriptive analyses were performed to estimate the prevalence of pre-diabetes and diabetes. Predictors of pre-diabetes and diabetes were investigated using multinomial logistic regression model. Model goodness-of-fit was evaluated using both the multinomial goodness-of-fit test proposed by Fagerland, Hosmer, and Bofin, as well as, the Hosmer-Lemeshow's goodness of fit test.There were approximately 2,983 (7.3% and 5,189 (12.1% adults in Florida diagnosed with pre-diabetes and diabetes, respectively. Over half of the study respondents were white, married and over the age of 45 years while 36.4% reported being physically inactive, overweight (36.4% or obese (26.4%, hypertensive (34.6%, hypercholesteremic (40.3%, and 26% were arthritic. Based on the final multivariable multinomial model, only being overweight (Relative Risk Ratio [RRR] = 1.85, 95% Confidence Interval [95% CI] = 1.41, 2.42, obese (RRR = 3.41, 95% CI = 2.61, 4.45, hypertensive (RRR = 1.69, 95% CI = 1.33, 2.15, hypercholesterolemic (RRR = 1.94, 95% CI = 1.55, 2.43, and arthritic (RRR = 1.24, 95% CI = 1.00, 1.55 had significant associations with pre-diabetes. However, more predictors had significant associations with diabetes and the strengths of associations tended to be higher than for the association with pre-diabetes. For instance, the relative risk ratios for the association between diabetes and being overweight (RRR = 2.00, 95

  4. The Application of Multinomial Logistic Regression Models for the Assessment of Parameters of Oocytes and Embryos Quality in Predicting Pregnancy and Miscarriage

    Directory of Open Access Journals (Sweden)

    Milewska Anna Justyna

    2017-09-01

    Full Text Available Infertility is a huge problem nowadays, not only from the medical but also from the social point of view. A key step to improve treatment outcomes is the possibility of effective prediction of treatment result. In a situation when a phenomenon with more than 2 states needs to be explained, e.g. pregnancy, miscarriage, non-pregnancy, the use of multinomial logistic regression is a good solution. The aim of this paper is to select those features that have a significant impact on achieving clinical pregnancy as well as those that determine the occurrence of spontaneous miscarriage (non-pregnancy was set as the reference category. Two multi-factor models were obtained, used in predicting infertility treatment outcomes. One of the models enabled to conclude that the number of follicles and the percentage of retrieved mature oocytes have a significant impact when prediction of treatment outcome is made on the basis of information about oocytes. The other model, built on the basis of information about embryos, showed the significance of the number of fertilized oocytes, the percentage of at least 7-cell embryos on day 3, the percentage of blasts on day 5, and the day of transfer.

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

    Science.gov (United States)

    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

  6. Naive Bayesian classifiers for multinomial features: a theoretical analysis

    CSIR Research Space (South Africa)

    Van Dyk, E

    2007-11-01

    Full Text Available The authors investigate the use of naive Bayesian classifiers for multinomial feature spaces and derive error estimates for these classifiers. The error analysis is done by developing a mathematical model to estimate the probability density...

  7. Expert Elicitation of Multinomial Probabilities for Decision-Analytic Modeling: An Application to Rates of Disease Progression in Undiagnosed and Untreated Melanoma.

    Science.gov (United States)

    Wilson, Edward C F; Usher-Smith, Juliet A; Emery, Jon; Corrie, Pippa G; Walter, Fiona M

    2018-06-01

    Expert elicitation is required to inform decision making when relevant "better quality" data either do not exist or cannot be collected. An example of this is to inform decisions as to whether to screen for melanoma. A key input is the counterfactual, in this case the natural history of melanoma in patients who are undiagnosed and hence untreated. To elicit expert opinion on the probability of disease progression in patients with melanoma that is undetected and hence untreated. A bespoke webinar-based expert elicitation protocol was administered to 14 participants in the United Kingdom, Australia, and New Zealand, comprising 12 multinomial questions on the probability of progression from one disease stage to another in the absence of treatment. A modified Connor-Mosimann distribution was fitted to individual responses to each question. Individual responses were pooled using a Monte-Carlo simulation approach. Participants were asked to provide feedback on the process. A pooled modified Connor-Mosimann distribution was successfully derived from participants' responses. Feedback from participants was generally positive, with 86% willing to take part in such an exercise again. Nevertheless, only 57% of participants felt that this was a valid approach to determine the risk of disease progression. Qualitative feedback reflected some understanding of the need to rely on expert elicitation in the absence of "hard" data. We successfully elicited and pooled the beliefs of experts in melanoma regarding the probability of disease progression in a format suitable for inclusion in a decision-analytic model. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  8. Comparison of multinomial and binomial proportion methods for analysis of multinomial count data.

    Science.gov (United States)

    Galyean, M L; Wester, D B

    2010-10-01

    Simulation methods were used to generate 1,000 experiments, each with 3 treatments and 10 experimental units/treatment, in completely randomized (CRD) and randomized complete block designs. Data were counts in 3 ordered or 4 nominal categories from multinomial distributions. For the 3-category analyses, category probabilities were 0.6, 0.3, and 0.1, respectively, for 2 of the treatments, and 0.5, 0.35, and 0.15 for the third treatment. In the 4-category analysis (CRD only), probabilities were 0.3, 0.3, 0.2, and 0.2 for treatments 1 and 2 vs. 0.4, 0.4, 0.1, and 0.1 for treatment 3. The 3-category data were analyzed with generalized linear mixed models as an ordered multinomial distribution with a cumulative logit link or by regrouping the data (e.g., counts in 1 category/sum of counts in all categories), followed by analysis of single categories as binomial proportions. Similarly, the 4-category data were analyzed as a nominal multinomial distribution with a glogit link or by grouping data as binomial proportions. For the 3-category CRD analyses, empirically determined type I error rates based on pair-wise comparisons (F- and Wald chi(2) tests) did not differ between multinomial and individual binomial category analyses with 10 (P = 0.38 to 0.60) or 50 (P = 0.19 to 0.67) sampling units/experimental unit. When analyzed as binomial proportions, power estimates varied among categories, with analysis of the category with the greatest counts yielding power similar to the multinomial analysis. Agreement between methods (percentage of experiments with the same results for the overall test for treatment effects) varied considerably among categories analyzed and sampling unit scenarios for the 3-category CRD analyses. Power (F-test) was 24.3, 49.1, 66.9, 83.5, 86.8, and 99.7% for 10, 20, 30, 40, 50, and 100 sampling units/experimental unit for the 3-category multinomial CRD analyses. Results with randomized complete block design simulations were similar to those with the CRD

  9. Multinomial logistic regression in workers' health

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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…

  11. PENERAPAN REGRESI PROBIT BIVARIAT UNTUK MENDUGA FAKTOR-FAKTOR YANG MEMENGARUHI KELULUSAN MAHASISWA (Studi Kasus: Mahasiswa Fakultas MIPA Unversitas Udayana

    Directory of Open Access Journals (Sweden)

    NI GUSTI KETUT TRISNA PRADNYANTARI

    2015-06-01

    Full Text Available The aim of this research to estimate the factors that affect students graduation using bivariate probit regression. Bivariate probit regression is a statistical method that involves two response variables which are qualitative and the independent variables are qualitative, quantitative, or a combination of both. In bivariate probit regression model, the result obtained is the probability of the response variable. The result of this research are the factors that affect significantly for students graduation based on study period are majors, sex, and duration of the thesis, while the factors that significantly for students graduation based on GPA are the entry system, duration of the thesis and the number of parents’ dependents.

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

    Science.gov (United States)

    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…

  13. The intermediate endpoint effect in logistic and probit regression

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  15. Exploring Driver Injury Severity at Intersection: An Ordered Probit Analysis

    Directory of Open Access Journals (Sweden)

    Yaping Zhang

    2015-02-01

    Full Text Available It is well known that intersections are the most hazardous locations; however, only little is known about driver injury severity in intersection crashes. Hence, the main goal of this study was to further examine the different factors contributing to driver injury severity involved in fatal crashes at intersections. Data used for the present analysis was from the US DOT-Fatality Analysis Reporting System (FARS crash database from the year 2011. An ordered probit model was employed to fit the fatal crash data and analyze the factors impacting each injury severity level. The analysis results displayed that driver injury severity is significantly affected by many factors. They include driver age and gender, driver ethnicity, vehicle type and age (years of use, crash type, driving drunk, speeding, violating stop sign, cognitively distracted driving, and seat belt usage. These findings from the current study are beneficial to form a solid basis for adopting corresponding measures to effectively drop injury severity suffering from intersection crash. More insights into the effects of risk factors on driver injury severity could be acquired using more advanced statistical models.

  16. 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.

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  19. The Finite and Moving Order Multinomial Universal Portfolio

    International Nuclear Information System (INIS)

    Tan, Choon Peng; Pang, Sook Theng

    2013-01-01

    An upper bound for the ratio of wealths of the best constant -rebalanced portfolio to that of the multinomial universal portfolio is derived. The finite- order multinomial universal portfolios can reduce the implementation time and computer-memory requirements for computation. The improved performance of the finite-order portfolios on some selected local stock-price data sets is observed.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    OpenAIRE

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

    2008-01-01

    Because statistical analysis requires both familiarity with and 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, students find it extremely difficult to learn business statistics. In this study, we use an ordered probit model to examine the effect of alternative prerequisite math course sequences on the grade performance of 1,684 busines...

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

    Science.gov (United States)

    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.

  4. A Comparison of Alternative Specifications of the College Attendance Equation with an Extension to two-stage Selectivity-Correction Models.

    Science.gov (United States)

    Hilmer, Michael J.

    2001-01-01

    Estimates a college-attendance equation for a common set of students (from the High School and Beyond Survey) using three popular econometric specifications: the multinomial logit, the ordered probit, and the bivariate probit. Estimated marginal effects do not differ significantly across the three specifications. Choice of specification may not…

  5. Health Care Facility Choice and User Fee Abolition: Regression Discontinuity in a Multinomial Choice Setting

    OpenAIRE

    Steven F. Koch; Jeffrey S. Racine

    2013-01-01

    We apply parametric and nonparametric regression discontinuity methodology within a multinomial choice setting to examine the impact of public health care user fee abolition on health facility choice using data from South Africa. The nonparametric model is found to outperform the parametric model both in- and out-of-sample, while also delivering more plausible estimates of the impact of user fee abolition (i.e. the 'treatment effect'). In the parametric framework, treatment effects were relat...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  8. Influencing Factors of Currency Risk of Deposit Banks in Turkey by Using Probit Method

    Directory of Open Access Journals (Sweden)

    Serhat Yüksel

    2016-12-01

    Full Text Available In this paper, we aimed to analyze the factors that affect currency risk of the banks. Within this scope, annual data of 23 deposit banks for the periods between 2005 and 2015 was evaluated. In addition to this situation, panel probit model was used in order to achieve this objective. Regarding the subject of the currency risk, this model was firstly used in this study. According to the results of the analysis, it was determined that 3 independent variables affect the currency risk of deposit banks in Turkey. Firstly, it was identified that there is a positive relationship between total assets and currency risk. This situation explains that when the size of the banks increases, they tend to take more currency risk. In addition to this variable, it was also defined that there is a direct relationship between economic growth and currency risk of the banks. This result refers that in case of an increment in the market stability; banks think that the market is safer and they increase their currency risk. Moreover, it was also concluded that there is a negative relationship between interest rate and currency risk of the banks. This aspect shows that when interest rate decreases, it will lower uncertainty in the market. Thus, banks would take higher currency risk in such markets.

  9. The Role of Wealth and Health in Insurance Choice: Bivariate Probit Analysis in China

    Directory of Open Access Journals (Sweden)

    Yiding Yue

    2014-01-01

    Full Text Available This paper captures the correlation between the choices of health insurance and pension insurance using the bivariate probit model and then studies the effect of wealth and health on insurance choice. Our empirical evidence shows that people who participate in a health care program are more likely to participate in a pension plan at the same time, while wealth and health have different effects on the choices of the health care program and the pension program. Generally, the higher an individual’s wealth level is, the more likelihood he will participate in a health care program; but wealth has no effect on the participation of pension. Health status has opposite effects on choices of health care programs and pension plans; the poorer an individual’s health is, the more likely he is to participate in health care programs, while the better health he enjoys, the more likely he is to participate in pension plans. When the investigation scope narrows down to commercial insurance, there is only a significant effect of health status on commercial health insurance. The commercial insurance choice and the insurance choice of the agricultural population are more complicated.

  10. Comparison of Weibull and Probit Analysis in Toxicity Testing of ...

    African Journals Online (AJOL)

    HP

    Keywords: Hunteria umbellata, Weibull model, Acute toxicity, Median lethal dose (LD50). Received: 7 November ... (PBPK) models [14,15], and (v) biologically-. Based Models: Moolgavkar-Venzon-Kundson. (MVK) model [16] and Ellwein and Cohen model [17]. ... Nigeria, Ibadan, where a sample with number. FHI107618 ...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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...

  14. Default probabilities, CDS premiums and downgrades : A probit-MIDAS analysis

    NARCIS (Netherlands)

    Freitag, L.

    2014-01-01

    This paper examines the relationship between sovereign credit default swaps (CDS) and sovereign rating changes of European countries. To this aim, a new estimator is introduced which merges mixed data sampling (MIDAS) with probit regression. Simulations show that the estimator has good properties in

  15. Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis

    Science.gov (United States)

    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.

  16. Identifying the Factors Influence Turkish Deposit Banks to Join Corporate Social Responsibility Activities by Using Panel Probit Method

    Directory of Open Access Journals (Sweden)

    Serhat Yuksel

    2017-02-01

    Full Text Available This study aims to determine the influencing factors of the banks to join corporate social responsibility activities. Within this scope, annual data of 23 deposit banks in Turkey for the periods between 2005 and 2015 was taken into the consideration. In addition to this situation, panel probit model was used in the analysis so as to achieve this objective. According to the results of the analysis, it was determined that there is a negative relationship between CSR activities and nonperforming loans ratio. This situation shows that banks do not prefer to make social responsibility activities in case of higher financial losses. In addition to this situation, it was also identified that there is a positive relationship between return on asset and corporate social responsibility activities of the banks. In other words, it can be understood that Turkish deposit banks, which have higher profitability, joint more CSR activities in comparison with others.

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

    Science.gov (United States)

    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.

  18. Ordered Probit Analysis of Consumers’ Preferences for Milk and Meat Quality Attributes in the Emerging Cities of Southern India

    Directory of Open Access Journals (Sweden)

    S. PRIYADHARSINI

    2017-09-01

    Full Text Available In order to assess consumer preferences for milk and meat quality attributes, a study was carried out in two Second-Tier cities of Tamil Nadu. Personal interviews were done to collect the data from 160 respondents chosen through a multistage sampling procedure in each of the two cities selected for this study. Ordered Probit model fitted for the attributes of milk showed that: family size had a significant positive preference towards texture, low fat and low price of milk, educated consumers paid greater attention to taste, safety, flavour, packaging and low fat attributes of milk and low income consumers paid less importance on most of the attributes of milk. Ordered Probit model for meat revealed that as the family size increased, the consumers were likely to give more importance to ageing and tenderness and less importance to leanness of meat. Male consumers paid greater attention to colour and females were none concerned with tenderness, cooking quality and price. As the education level increased, the consumers became more and more quality and price conscious. Households having children paid more importance to tenderness and taste attributes of meat, whereas the household having aged people opted for colour, taste, tenderness, cooking quality, leanness and price attributes. Low income consumers paid less importance to quality attributes and the respondents performing more physical activity paid lesser attention towards leanness and more importance to price of the meat. This suggests the need for enhancing the production of quality livestock products, together by developing a well-organized distribution system.

  19. Analysis of the liquidity risk in credit unions: a logit multinomial approach

    Directory of Open Access Journals (Sweden)

    Rosiane Maria Lima Gonçalves

    2008-10-01

    Full Text Available Liquidity risk in financial institutions is associated to balance between working capital and financial demands. Other factors that affect credit union liquidity are an unanticipated increase of withdrawals without an offsetting amount of new deposits, and the lack of ability in promoting the product geographical diversification. The objective of this study is to analyze Minas Gerais state credit union liquidity risk and its factor determinants. Financial ratios and the multinomial logit model are used. The cooperatives were classified in five categories of liquidity risk: very low, low, medium, high and very high. The empirical results indicate that high levels of liquidity are related to smaller values of the outsourcing capital use, immobilization of the turnover capital, and provision ratios. So, they are associated to larger values of the deposit total/credit operations, and asset growth ratios.

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

    Science.gov (United States)

    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

  1. An Instrumental Variable Probit (IVP Analysis on Depressed Mood in Korea: The Impact of Gender Differences and Other Socio-Economic Factors

    Directory of Open Access Journals (Sweden)

    Lara Gitto

    2015-08-01

    -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 socioeconomic 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.

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

    Science.gov (United States)

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

    2015-04-16

    , 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.

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

    Science.gov (United States)

    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.

  4. Is the probit 9 security level appropriate for disinfestation using gamma-radiation

    International Nuclear Information System (INIS)

    Ohta, A.T.; Kaneshiro, K.Y.; Kurihara, J.S.; Kanegawa, K.M.; Nagamine, L.R.

    1985-01-01

    The probit 9 concept requires that a given treatment result in 99.9968 percent mortality in an estimated population of 100,000 individuals. The USDA-Hawaiian Fruit Fly Investigations Laboratory has determined that 0.26 kGy is the minimum absorbed dose of gamma-radiation required to prevent adult emergence of the three species of fruit flies in Hawaii: the Mediterranean fruit fly, Ceratitis capitata; the Oriental fruit fly, Dacus dorsalis; and the melon fly, Dacus cucurbitae. However, at dosages higher than 0.26 kGy, the authors observed relatively high rates of egg hatch (10-30 percent). In addition, when eggs are treated at 0.26 kGy, those larvae that do hatch may develop into third instar larvae, and their feeing may decrease the marketability of the fruits. Furthermore, there is some uncertainty as to whether or not importing countries would accept fruits with any living larvae in the shipment. For these reasons, the authors tried to determine the minimum absorbed dosages required to obtain mortality in mature eggs and larvae of the medfly. Results of the research showed that although high egg and larval mortality was observed at dosages of 0.50 to 0.60 kGy in nearly all of the fruit types and varieties studied, 100 percent mortality of mature eggs and larvae was not attained at these dosages. Nevertheless, the authors think that an increase in the minimum absorbed dose higher than that determined using the probit 9 concept (i.e., 0.26 kGy) should be considered because they were able to ascertain that, at dosages from 0.40 to 0.60 kGy, not only is egg hatch greatly reduced but the larvae hatching from these eggs developed only to the late first or early second larval instar stages

  5. Work Intensity of Households: Multinomial Logit Analysis and Correspondence Analysis for Slovak Republic

    Directory of Open Access Journals (Sweden)

    Erik Šoltés

    2018-03-01

    Full Text Available Exclusion from the labour market is a serious social problem that is also addressed by the Europe 2020 strategy. While in the past the attention of statisticians and sociologists in the fight against poverty and social exclusion has concentrated mainly on income poverty and material deprivation, in recent times many studies and analyses are much more focused on work intensity as well. Households that use their work potential to less than 20%, have a very low work intensity, and members of such households are included into the population of people who are at risk of poverty or social exclusion. Moreover, the low use of labour potential of households significantly increases the risk of income poverty and the threat of material deprivation. This article provides an analysis of work intensity levels of Slovak households depending on the factors that are monitored by the EU-SILC 2015. The impact of relevant factors is quantified by correspondence analysis and by multinomial logistic regression model.

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

    Directory of Open Access Journals (Sweden)

    Barbara Reis-Santos

    2013-09-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  8. A public perspective on the adoption of microgeneration technologies in New Zealand: A multivariate probit approach

    International Nuclear Information System (INIS)

    Baskaran, Ramesh; Managi, Shunsuke; Bendig, Mirko

    2013-01-01

    The growing demand for electricity in New Zealand has led to the construction of new hydro-dams or power stations that have had environmental, social and cultural effects. These effects may drive increases in electricity prices, as such prices reflect the cost of running existing power stations as well as building new ones. This study uses Canterbury and Central Otago as case studies because both regions face similar issues in building new hydro-dams and ever-increasing electricity prices that will eventually prompt households to buy power at higher prices. One way for households to respond to these price changes is to generate their own electricity through microgeneration technologies (MGT). The objective of this study is to investigate public perception and preferences regarding MGT and to analyze the factors that influence people’s decision to adopt such new technologies in New Zealand. The study uses a multivariate probit approach to examine households’ willingness to adopt any one MGT system or a combination of the MGT systems. Our findings provide valuable information for policy makers and marketers who wish to promote effective microgeneration technologies. - Highlights: ► We examine New Zealand households’ awareness level for microgeneration technologies (MGT) and empirically explore the factors that determine people’s willingness to adopt for MGT. ► The households are interested and willing to adopt the MGT systems. ► Noticeable heterogeneity exists between groups of households in adopting the MGT. ► No significant regional difference exists in promoting solar hot water policies. ► Public and private sectors incentives are important in promoting the MGT

  9. Multinomial Logistic Regression & Bootstrapping for Bayesian Estimation of Vertical Facies Prediction in Heterogeneous Sandstone Reservoirs

    Science.gov (United States)

    Al-Mudhafar, W. J.

    2013-12-01

    Precisely prediction of rock facies leads to adequate reservoir characterization by improving the porosity-permeability relationships to estimate the properties in non-cored intervals. It also helps to accurately identify the spatial facies distribution to perform an accurate reservoir model for optimal future reservoir performance. In this paper, the facies estimation has been done through Multinomial logistic regression (MLR) with respect to the well logs and core data in a well in upper sandstone formation of South Rumaila oil field. The entire independent variables are gamma rays, formation density, water saturation, shale volume, log porosity, core porosity, and core permeability. Firstly, Robust Sequential Imputation Algorithm has been considered to impute the missing data. This algorithm starts from a complete subset of the dataset and estimates sequentially the missing values in an incomplete observation by minimizing the determinant of the covariance of the augmented data matrix. Then, the observation is added to the complete data matrix and the algorithm continues with the next observation with missing values. The MLR has been chosen to estimate the maximum likelihood and minimize the standard error for the nonlinear relationships between facies & core and log data. The MLR is used to predict the probabilities of the different possible facies given each independent variable by constructing a linear predictor function having a set of weights that are linearly combined with the independent variables by using a dot product. Beta distribution of facies has been considered as prior knowledge and the resulted predicted probability (posterior) has been estimated from MLR based on Baye's theorem that represents the relationship between predicted probability (posterior) with the conditional probability and the prior knowledge. To assess the statistical accuracy of the model, the bootstrap should be carried out to estimate extra-sample prediction error by randomly

  10. Endogeneity and Heterogeneity in a Probit Demand Model: Estimation Using Aggregate Data

    OpenAIRE

    Pradeep K. Chintagunta

    2001-01-01

    Two issues that have become increasingly important while estimating the parameters of aggregate demand functions to study firm behavior are the of marketing activities (typically, price) and across consumers in the market under consideration. Ignoring these issues in the estimation of the demand function parameters can lead to biased and inconsistent estimates for the effects of marketing activities. Endogeneity and heterogeneity have achieved prominence in large measure because of the increa...

  11. Bayesian Analysis of Multilevel Probit Models for Data with Friendship Dependencies

    Science.gov (United States)

    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…

  12. 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

    Directory of Open Access Journals (Sweden)

    Varga Csaba

    2012-10-01

    Full Text Available Abstract 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.

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

    Science.gov (United States)

    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.

  14. Retrieving unobserved consideration sets from household panel data

    NARCIS (Netherlands)

    J.E.M. van Nierop; R. Paap (Richard); B. Bronnenberg; Ph.H.B.F. Franses (Philip Hans); M. Wedel (Michel)

    2005-01-01

    textabstractWe propose a new model to describe consideration, consisting of a multivariate probit model component for consideration and a multinomial probit model component for choice, given consideration. The approach allows one to analyze stated consideration set data, revealed consideration set

  15. The consumer’s choice among television displays: A multinomial logit approach

    Directory of Open Access Journals (Sweden)

    Carlos Giovanni González Espitia

    2013-07-01

    Full Text Available The consumer’s choice over a bundle of products depends on observable and unobservable characteristics of goods and consumers. This choice is made in order to maximize utility subject to a budget constraint. At the same time, firms make product differentiation decisions to maximize profit. Quality is a form of differentiation. An example of this occurs in the TV market, where several displays are developed. Our objective is to determine the probability for a consumer of choosing a type of display from among five kinds: standard tube, LCD, plasma, projection and LED. Using a multinomial logit approach, we find that electronic appliances like DVDs and audio systems, as well as socioeconomic status, increase the probability of choosing a high-tech television display. Our empirical approximation contributes to further understanding rational consumer behavior through the theory of utility maximization and highlights the importance of studying market structure and analyzing changes in welfare and efficiency.

  16. Anàlisi cluster multinomial bayesià..Aplicació a dades electorals

    OpenAIRE

    Montón Domingo, Maria

    2009-01-01

    En aquest treball fi de màster se li vol donar una altra visió a les dades de resultats electorals, en concret, les del Parlament de Catalunya. Així doncs, l'eina d'anàlisi que s'utilitza és l'anàlisi clúster multinomial bayesià i les unitats d'estudi són les zones de recerca petita de la ciutat de Barcelona. D'aquesta manera es determina com s'agrupen les diferents zones de recerca petita de Barcelona des del punt de vista de les seves votacions i quina relació hi ha entre els partits en fun...

  17. Testing independence between two Poisson-generated multinomial variables in case-series and cohort studies.

    Science.gov (United States)

    Hocine, Mounia; Guillemot, Didier; Tubert-Bitter, Pascale; Moreau, Thierry

    2005-12-30

    In case-series or cohort studies, we propose a test of independence between the occurrences of two types of recurrent events (such as two repeated infections) related to an intermittent exposure (such as an antibiotic treatment). The test relies upon an extension of a recent method for analysing case-series data, in the presence of one type of recurrent event. The test statistic is derived from a bivariate Poisson generated-multinomial distribution. Simulations for checking the validity of the test concerning the type I error and the power properties are presented. The test is illustrated using data from a cohort on antibiotics bacterial resistance in schoolchildren. Copyright 2005 John Wiley & Sons, Ltd.

  18. DETERMINATION OF FACTORS AFFECTING LENGTH OF STAY WITH MULTINOMIAL LOGISTIC REGRESSION IN TURKEY

    Directory of Open Access Journals (Sweden)

    Öğr. Gör. Rukiye NUMAN TEKİN

    2016-08-01

    Full Text Available Length of stay (LOS has important implications in various aspects of health services, can vary according to a wide range of factors. It is noticed that LOS has been neglected mostly in both theoratical studies and practice of health care management in Turkey. The main purpose of this study is to identify factors related to LOS in Turkey. A retrospective analysis of 2.255.836 patients hospitalized to private, university, foundation university and other (municipality, association and foreigners/minority hospitals hospitals which have an agreement with Social Security Institution (SSI in Turkey, from January 1, 2010, until the December 31, 2010, was examined. Patient’s data were taken from MEDULA (National Electronic Invoice System and SPSS 18.0 was used to perform statistical analysis. In this study t-test, one way anova and multinomial logistic regression are used to determine variables that may affect to LOS. The average LOS of patients was 3,93 days (SD = 5,882. LOS showed a statistically significant difference according to all independent variables used in the study (age, gender, disease class, type of hospitalization, presence of comorbidity, type and number of surgery, season of hospitalization, hospital ownership/bed capacity/ geographical region/residential area/type of service. According to the results of the multinomial lojistic regression analysis, LOS was negatively affected in terms of gender, presence of comorbidity, geographical region of hospital and was positively affected in terms of age, season of hospitalization, hospital bed capacity/ ownership/type of service/residential area.

  19. Identifying response styles: A latent-class bilinear multinomial logit model

    NARCIS (Netherlands)

    van Rosmalen, J.; van Herk, H.; Groenen, P.J.F.

    2010-01-01

    Respondents can vary strongly in the way they use rating scales. Specifically, respondents can exhibit a variety of response styles, which threatens the validity of the responses. The purpose of this article Is to investigate how response style and content of the items affect rating scale responses.

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

    Science.gov (United States)

    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,...

  1. The Dirichet-Multinomial model for multivariate randomized response data and small samples

    NARCIS (Netherlands)

    Avetisyan, Marianna; Fox, Gerardus J.A.

    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

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

    Science.gov (United States)

    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…

  3. Mixed multinomial logit model for out-of-home leisure activity choice

    NARCIS (Netherlands)

    Grigolon, A.B.; Kemperman, A.D.A.M.; Timmermans, H.J.P.

    2013-01-01

    This paper documents the design and results of a study on the factors influencing the choice of out-of-home leisure activities. Influencing factors seem related to socio-demographic characteristics, personal preferences, characteristics of the built environment and other aspects of the activities

  4. PREMIM and EMIM: tools for estimation of maternal, imprinting and interaction effects using multinomial modelling

    Directory of Open Access Journals (Sweden)

    Howey Richard

    2012-06-01

    Full Text Available Abstract Background Here we present two new computer tools, PREMIM and EMIM, for the estimation of parental and child genetic effects, based on genotype data from a variety of different child-parent configurations. PREMIM allows the extraction of child-parent genotype data from standard-format pedigree data files, while EMIM uses the extracted genotype data to perform subsequent statistical analysis. The use of genotype data from the parents as well as from the child in question allows the estimation of complex genetic effects such as maternal genotype effects, maternal-foetal interactions and parent-of-origin (imprinting effects. These effects are estimated by EMIM, incorporating chosen assumptions such as Hardy-Weinberg equilibrium or exchangeability of parental matings as required. Results In application to simulated data, we show that the inference provided by EMIM is essentially equivalent to that provided by alternative (competing software packages such as MENDEL and LEM. However, PREMIM and EMIM (used in combination considerably outperform MENDEL and LEM in terms of speed and ease of execution. Conclusions Together, EMIM and PREMIM provide easy-to-use command-line tools for the analysis of pedigree data, giving unbiased estimates of parental and child genotype relative risks.

  5. A Multinomial Model of Fertility Choice and Offspring Sex-Ratios in India

    OpenAIRE

    Rubiana Chamarbagwala; Martin Ranger

    2007-01-01

    Fertility decline in developing countries may have unexpected demographic consequences. Although lower fertility improves nutrition, health, and human capital investments for surviving children, little is known about the relationship between fertility outcomes and female-male offspring sex-ratios. Particularly in countries with a cultural preference for sons, like India and China, fertility decline may deteriorate the already imbalanced sex-ratios. We use the fertility histories of over 90,00...

  6. INCLUSION OF THE LATENT PERSONALITY VARIABLE IN MULTINOMIAL LOGIT MODELS USING THE 16PF PSYCHOMETRIC TEST

    Directory of Open Access Journals (Sweden)

    JORGE E. CÓRDOBA MAQUILÓN

    2012-01-01

    Full Text Available Los modelos de demanda de viajes utilizan principalmente los atributos modales y las características socioeconómicas como variables explicativas. También se ha establecido que las actitudes y percepciones influyen en el comportamiento de los usuarios. Sin embargo, las variables psicológicas del individuo condicionan la conducta del usuario. En este estudio se incluyó la variable latente personalidad, en la estimación del modelo híbrido de elección discreta, el cual constituye una buena alternativa para incorporar los efectos de los factores subjetivos. La variable latente personalidad se evaluó con la prueba psicométrica 16PF de validez internacional. El artículo analiza los resultados de la aplicación de este modelo a una población de empleados y docentes universitarios, y también propone un camino para la utilización de pruebas psicométricas en los modelos híbridos de elección discreta. Nuestros resultados muestran que los modelos híbridos que incluyen variables latentes psicológicas son superiores a los modelos tradicionales que ignoran los efectos de la conducta de los usuarios.

  7. Identifying Unknown Response Styles: A Latent-Class Bilinear Multinomial Logit Model

    NARCIS (Netherlands)

    J.M. van Rosmalen (Joost); H. van Herk (Hester); P.J.F. Groenen (Patrick)

    2007-01-01

    textabstractRespondents can vary significantly in the way they use rating scales. Specifically, respondents can exhibit varying degrees of response style, which threatens the validity of the responses. The purpose of this article is to investigate to what extent rating scale responses show response

  8. COMPARACION DE 13 INTERVALOS DE CONFIANZA PARA LOS PARAMETROS DE LA DISTRIBUCION MULTINOMIAL

    Directory of Open Access Journals (Sweden)

    Difariney González-Gómez

    2015-07-01

    Full Text Available La distribución multinomial es fundamental para la descripción de fenómenos en los que pueden ocurrir k > 2 eventos excluyentes, cada uno con probabilidad π = (π1, π2, . . . , πk. Algunos ejemplos de esta distribución incluyen la calidad de un producto o encuestas de selección múltiple. Un problema de gran interés en inferencia estadística es la construcción de intervalos de confianza los parámetros para π. En este trabajo se comparan, a través de un estudio de simulación, 13 metodologías para la construcción de intervalos de confianza para dicha distribución. Utilizando como criterios de comparación el nivel de confianza nominal, la longitud del intervalo y una combinación de estos, se encuentra que los intervalos de confianza basados en el Teorema del Límite Central no presentan el mejor desempeño. Finalmente se recomiendan los métodos basados en la distribución F (Leemis, 1996, seguido del método de verosimilitud relativa (Kalbfleish, 1985 y Quesenberry & Hurst (1964.

  9. The multivariate Dirichlet-multinomial distribution and its application in forensic genetics to adjust for subpopulation effects using the θ-correction

    DEFF Research Database (Denmark)

    Tvedebrink, Torben; Eriksen, Poul Svante; Morling, Niels

    2015-01-01

    In this paper, we discuss the construction of a multivariate generalisation of the Dirichlet-multinomial distribution. An example from forensic genetics in the statistical analysis of DNA mixtures motivates the study of this multivariate extension. In forensic genetics, adjustment of the match...... probabilities due to remote ancestry in the population is often done using the so-called θ-correction. This correction increases the probability of observing multiple copies of rare alleles in a subpopulation and thereby reduces the weight of the evidence for rare genotypes. A recent publication by Cowell et al....... (2015) showed elegantly how to use Bayesian networks for efficient computations of likelihood ratios in a forensic genetic context. However, their underlying population genetic model assumed independence of alleles, which is not realistic in real populations. We demonstrate how the so-called θ...

  10. A Capacity-Restraint Transit Assignment Model When a Predetermination Method Indicates the Invalidity of Time Independence

    Directory of Open Access Journals (Sweden)

    Haoyang Ding

    2015-01-01

    Full Text Available The statistical independence of time of every two adjacent bus links plays a crucial role in deciding the feasibility of using many mathematical models to analyze urban transit networks. Traditional research generally ignores the time independence that acts as the ground of their models. Assumption is usually made that time independence of every two adjacent links is sound. This is, however, actually groundless and probably causes problematic conclusions reached by corresponding models. Many transit assignment models such as multinomial probit-based models lose their effects when the time independence is not valid. In this paper, a simple method to predetermine the time independence is proposed. Based on the predetermination method, a modified capacity-restraint transit assignment method aimed at engineering practice is put forward and tested through a small contrived network and a case study in Nanjing city, China, respectively. It is found that the slope of regression equation between the mean and standard deviation of normal distribution acts as the indicator of time independence at the same time. Besides, our modified assignment method performs better than the traditional one with more reasonable results while keeping the property of simplicity well.

  11. Modeling Word Burstiness Using the Dirichlet Distribution

    DEFF Research Database (Denmark)

    Madsen, Rasmus Elsborg; Kauchak, David; Elkan, Charles

    2005-01-01

    Multinomial distributions are often used to model text documents. However, they do not capture well the phenomenon that words in a document tend to appear in bursts: if a word appears once, it is more likely to appear again. In this paper, we propose the Dirichlet compound multinomial model (DCM......) as an alternative to the multinomial. The DCM model has one additional degree of freedom, which allows it to capture burstiness. We show experimentally that the DCM is substantially better than the multinomial at modeling text data, measured by perplexity. We also show using three standard document collections...

  12. Bivariate Probit Models for Analysing how “Knowledge” Affects Innovation and Performance in Small and Medium Sized Firms

    OpenAIRE

    FARACE, Salvatore; MAZZOTTA, Fernanda

    2011-01-01

    This paper examines the determinants of innovation and its effects on small- and medium-sized firms We use the data from the OPIS databank, which provides a survey on a representative sample of firms from a province of the Southern Italy. We want to study whether small and medium sized firms can have a competitive advantage using their innovative capabilities, regardless of their sectoral and size limits. The main factor influencing the likelihood of innovation is knowledge, which is acquired...

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

    Science.gov (United States)

    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...

  14. Composite Linear Models | Division of Cancer Prevention

    Science.gov (United States)

    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

  15. A Multinomial Logit Approach to Estimating Regional Inventories by Product Class

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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?

  19. Modelling Stochastic Route Choice Behaviours with a Closed-Form Mixed Logit Model

    Directory of Open Access Journals (Sweden)

    Xinjun Lai

    2015-01-01

    Full Text Available A closed-form mixed Logit approach is proposed to model the stochastic route choice behaviours. It combines both the advantages of Probit and Logit to provide a flexible form in alternatives correlation and a tractable form in expression; besides, the heterogeneity in alternative variance can also be addressed. Paths are compared by pairs where the superiority of the binary Probit can be fully used. The Probit-based aggregation is also used for a nested Logit structure. Case studies on both numerical and empirical examples demonstrate that the new method is valid and practical. This paper thus provides an operational solution to incorporate the normal distribution in route choice with an analytical expression.

  20. Integration of Fishers' Perception on the Environment

    African Journals Online (AJOL)

    Keywords: Climate change, Green Economy, multinomial probit model, small- scale fisheries ... adoption of new preferences regarding environmental management and how these .... food security and poverty eradication in ... The challenges for SIDS are to integrate these ..... are thus facing unprecedented threats from.

  1. Bayes factor covariance testing in item response models

    NARCIS (Netherlands)

    Fox, J.P.; Mulder, J.; Sinharay, Sandip

    2017-01-01

    Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning

  2. Bayes Factor Covariance Testing in Item Response Models

    NARCIS (Netherlands)

    Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

    2017-01-01

    Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning

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

    Science.gov (United States)

    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)

  4. Comparison on models for genetic evaluation of non-return rate and success in first insemination of the Danish Holstein cow

    DEFF Research Database (Denmark)

    Sun, C; Su, G

    2010-01-01

    The aim of is study was to compare a linear Gaussian model with logit model and probit model for genetic evaluation of non-return rate within 56 d after first-insemination (NRR56) and success in first insemination (SFI). The whole dataset used in the analysis contained 471,742 records from...... the EBV of proven bulls, obtained from the whole dataset and from a reduced dataset which only contains the first-crop daughters of sires; 2) χ2 statistic for the expected and observed frequency in a cross validation. Heritabilities estimated using linear, probit and logit models were 0.011, 0.014 and 0....... Model validation showed that there was no difference between probit model and logit model, but the two models were better than linear model in stability and predictive ability for genetic evaluation of NRR56 and SFI. However, based on the whole dataset, the correlations between EBV estimated using...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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…

  7. Bayesian mixture models for assessment of gene differential behaviour and prediction of pCR through the integration of copy number and gene expression data.

    Directory of Open Access Journals (Sweden)

    Filippo Trentini

    Full Text Available We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian mixture models that define latent Gaussian probit scores for the DNA and RNA, and integrate between the two platforms via a regression of the RNA probit scores on the DNA probit scores. Such a regression conveniently allows us to include additional sample specific covariates such as biological conditions and clinical outcomes. The two developed methods are aimed respectively to make inference on differential behaviour of genes in patients showing different subtypes of breast cancer and to predict the pathological complete response (pCR of patients borrowing strength across the genomic platforms. Posterior inference is carried out via MCMC simulations. We demonstrate the proposed methodology using a published data set consisting of 121 breast cancer patients.

  8. Sequential and Simultaneous Logit: A Nested Model.

    NARCIS (Netherlands)

    van Ophem, J.C.M.; Schram, A.J.H.C.

    1997-01-01

    A nested model is presented which has both the sequential and the multinomial logit model as special cases. This model provides a simple test to investigate the validity of these specifications. Some theoretical properties of the model are discussed. In the analysis a distribution function is

  9. 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

    Science.gov (United States)

    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...

  10. A comparison of generalized multinomial logit, random parameters logit, wtp-space and latent class models to studying consumers' preferences for animal welfare

    OpenAIRE

    Kallas, Zein; Borrisser-Pairó,, Francesc; Martínez, Beatriz; Vieira, Ceferina; Panella-Riera, Nuria; Olivar, Maria Angels; Gil Roig, José María

    2016-01-01

    The European societies are requiring that animals to be raised as closely as possible to their natural conditions. The growing concerns about animal welfare is resulting in continuous modifications of regulations and policies that led to ban of a number of intensive farming methods. The European authorities consider the pig welfare as a priority issue. They are studying to ban surgical pig castration by 2018, which may seriously affect markets and consumers due to boar tainted-meat. This stud...

  11. Dealing with selection bias in educational transition models

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads Meier

    2011-01-01

    This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational tr...... account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models.......This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational...... transitions to be correlated across transitions. We use simulated and real data to illustrate how the BPSM improves on the traditional Mare model in terms of correcting for selection bias and providing credible estimates of the effect of family background on educational success. We conclude that models which...

  12. Discrete choice models for commuting interactions

    DEFF Research Database (Denmark)

    Rouwendal, Jan; Mulalic, Ismir; Levkovich, Or

    An emerging quantitative spatial economics literature models commuting interactions by a gravity equation that is mathematically equivalent to a multinomial logit model. This model is widely viewed as restrictive because of the independence of irrelevant alternatives (IIA) property that links sub...

  13. Ordering the Preference Hierarchies for Internal Finance, Bank Loans, Bond and Share Issues

    OpenAIRE

    Leo de Haan; Jeroen Hinloopen

    2002-01-01

    We estimate the incremental financing decision for a sample of some 150Dutch companies for the years 1984 through 1997, thereby distinguishinginternal finance and three types of external finance: bank borrowing, bondissues and share issues. First, we estimate a multinomial logit model whichconfirms several predictions of both the static trade-off theory and thepecking-order theory as to the determinants of financing choices. Next, weuse ordered probit models to determine which financing hiera...

  14. Remarques concernant la probité scientifique

    Directory of Open Access Journals (Sweden)

    Roxana Iordache

    2015-08-01

    Full Text Available On constate, ces derniers temps, que certains jeunes enseignants expérimentent le plagiat sur des théories déjà publiées et généralement acceptées par les milieux scientifiques. D'autres enseignants faussent le contenu d'idées d'un travail, ou de l'autre, dans l'espoir d'augmenter leurs propres mérites. C' est avec stupeur que nous découvrons dans les Actes du IXe Colloque de linguistique Latine (Madrid, 1998, vol. 1, les pages de Mme Mirka Maraldi (Université de Bologne, intitulées «Concessive ut: parataxis, hypotaxis and correlation» (pages 487- 500. Mme M. Maraldi critique à la page 493 du volume supra mentionné notre étude sur le ut concessif du Jatin, en oubliant complètement d 'indiquer dans le texte et dans les notes de cette page, ainsi que de toutes les autres pages, le litre de notre étude, le lieu de parution et la page (ou les pages de nos soi-disant erreurs. On critique plusieurs fois «Jordache's analysis» - un syntagme vague, en fait! Précisons en mȇme temps que Mme M. Maraldi mentionne avec beaucoup de souci, à chaque page, les données des autres articles (Iieu d'apparition, page etc., etc, quoique, pour la plupart, il s'agisse de travaux peu importants pour le sujet en discussion.

  15. Remarques concernant la probité scientifique

    Directory of Open Access Journals (Sweden)

    Roxana Iordache

    2000-12-01

    Full Text Available On constate, ces derniers temps, que certains jeunes enseignants expérimentent le plagiat sur des théories déjà publiées et généralement acceptées par les milieux scientifiques. D'autres enseignants faussent le contenu d'idees d'un travail, ou de l'autre, dans l'espoir d'augmenter leurs propres mérites.

  16. The differentiated impacts of organizational innovation practices on technological innovation persistence

    OpenAIRE

    Le Bas , Christian; Mothe , Caroline; Nguyen-Thi , Thuc Uyen

    2015-01-01

    International audience; Purpose – The purpose of this paper is to test the major determinants of technological (product and process) innovation persistence and provides evidence of the significant role of organizational innovation. Design/methodology/approach – Data came from two waves of the Luxembourg Community Innovation Survey (CIS): CIS2006 for 2004-2006 and CIS2008 for 2006-2008. The longitudinal data set resulted in a final sample of 287 firms. A multinomial probit model estimates the ...

  17. Unter welchen Umständen würden deutsche Landwirte gentechnisch veränderten Raps anbauen? Ein Discrete-Choice-Experiment

    OpenAIRE

    Breustedt, Gunnar; Muller-Scheessel, Jorg; Meyer-Schatz, Henrika Marie

    2007-01-01

    We examine the factors affecting the willingness of German farmers to adopt genetically modified (GM) oilseed rape after the pending commercial release of GM varieties. The analysis is based mainly on a web-based Discrete Choice Experiment with 217 oilseed rape growers in Germany. The determinants of adoption were estimated with the use of a multinomial probit model. Results indicate a significant impact of economic determinants on the adoption willingness: the difference in gross margins bet...

  18. Vocational and General Education of Girls and Boys in Tunisia: The Effects of Income and Parental Education

    OpenAIRE

    Mohamed Siala; Nehed Ben Ammar

    2014-01-01

    Throughout Tunisia, basic education is compulsory. Children are required to enroll for at least 9 years from age 6. This paper examines gender differences in education choice of upper basic education of youths aged 15–24 in Tunisia. To investigate the factors that influence an individual’s choice between vocational education, general education (secondary and high education) and leaving school, the paper estimates a multinomial probit model of education choice. We focus on the i...

  19. Total, Direct, and Indirect Effects in Logit Models

    DEFF Research Database (Denmark)

    Karlson, Kristian Bernt; Holm, Anders; Breen, Richard

    It has long been believed that the decomposition of the total effect of one variable on another into direct and indirect effects, while feasible in linear models, is not possible in non-linear probability models such as the logit and probit. In this paper we present a new and simple method...... average partial effects, as defined by Wooldridge (2002). We present the method graphically and illustrate it using the National Educational Longitudinal Study of 1988...

  20. Poisson versus threshold models for genetic analysis of clinical mastitis in US Holsteins.

    Science.gov (United States)

    Vazquez, A I; Weigel, K A; Gianola, D; Bates, D M; Perez-Cabal, M A; Rosa, G J M; Chang, Y M

    2009-10-01

    Typically, clinical mastitis is coded as the presence or absence of disease in a given lactation, and records are analyzed with either linear models or binary threshold models. Because the presence of mastitis may include cows with multiple episodes, there is a loss of information when counts are treated as binary responses. Poisson models are appropriated for random variables measured as the number of events, and although these models are used extensively in studying the epidemiology of mastitis, they have rarely been used for studying the genetic aspects of mastitis. Ordinal threshold models are pertinent for ordered categorical responses; although one can hypothesize that the number of clinical mastitis episodes per animal reflects a continuous underlying increase in mastitis susceptibility, these models have rarely been used in genetic analysis of mastitis. The objective of this study was to compare probit, Poisson, and ordinal threshold models for the genetic evaluation of US Holstein sires for clinical mastitis. Mastitis was measured as a binary trait or as the number of mastitis cases. Data from 44,908 first-parity cows recorded in on-farm herd management software were gathered, edited, and processed for the present study. The cows were daughters of 1,861 sires, distributed over 94 herds. Predictive ability was assessed via a 5-fold cross-validation using 2 loss functions: mean squared error of prediction (MSEP) as the end point and a cost difference function. The heritability estimates were 0.061 for mastitis measured as a binary trait in the probit model and 0.085 and 0.132 for the number of mastitis cases in the ordinal threshold and Poisson models, respectively; because of scale differences, only the probit and ordinal threshold models are directly comparable. Among healthy animals, MSEP was smallest for the probit model, and the cost function was smallest for the ordinal threshold model. Among diseased animals, MSEP and the cost function were smallest

  1. Regression Models For Multivariate Count Data.

    Science.gov (United States)

    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.

  2. Maternal and anaesthesia-related risk factors and incidence of spinal anaesthesia-induced hypotension in elective caesarean section: A multinomial logistic regression.

    Science.gov (United States)

    Fakherpour, Atousa; Ghaem, Haleh; Fattahi, Zeinabsadat; Zaree, Samaneh

    2018-01-01

    Although spinal anaesthesia (SA) is nowadays the preferred anaesthesia technique for caesarean section (CS), it is associated with considerable haemodynamic effects, such as maternal hypotension. This study aimed to evaluate a wide range of variables (related to parturient and anaesthesia techniques) associated with the incidence of different degrees of SA-induced hypotension during elective CS. This prospective study was conducted on 511 mother-infant pairs, in which the mother underwent elective CS under SA. The data were collected through preset proforma containing three parts related to the parturient, anaesthetic techniques and a table for recording maternal blood pressure. It was hypothesized that some maternal (such as age) and anaesthesia-related risk factors (such as block height) were associated with occurance of SA-induced hypotension during elective CS. The incidence of mild, moderate and severe hypotension was 20%, 35% and 40%, respectively. Eventually, ten risk factors were found to be associated with hypotension, including age >35 years, body mass index ≥25 kg/m 2 , 11-20 kg weight gain, gravidity ≥4, history of hypotension, baseline systolic blood pressure (SBP) 100 beats/min in maternal modelling, fluid preloading ≥1000 ml, adding sufentanil to bupivacaine and sensory block height >T 4 in anaesthesia-related modelling ( P < 0.05). Age, body mass index, weight gain, gravidity, history of hypotension, baseline SBP and heart rate, fluid preloading, adding sufentanil to bupivacaine and sensory block hieght were the main risk factors identified in the study for SA-induced hypotension during CS.

  3. Maternal and anaesthesia-related risk factors and incidence of spinal anaesthesia-induced hypotension in elective caesarean section: A multinomial logistic regression

    Directory of Open Access Journals (Sweden)

    Atousa Fakherpour

    2018-01-01

    Full Text Available Background and Aims: Although spinal anaesthesia (SA is nowadays the preferred anaesthesia technique for caesarean section (CS, it is associated with considerable haemodynamic effects, such as maternal hypotension. This study aimed to evaluate a wide range of variables (related to parturient and anaesthesia techniques associated with the incidence of different degrees of SA-induced hypotension during elective CS. Methods: This prospective study was conducted on 511 mother–infant pairs, in which the mother underwent elective CS under SA. The data were collected through preset proforma containing three parts related to the parturient, anaesthetic techniques and a table for recording maternal blood pressure. It was hypothesized that some maternal (such as age and anaesthesia-related risk factors (such as block height were associated with occurance of SA-induced hypotension during elective CS. Results: The incidence of mild, moderate and severe hypotension was 20%, 35% and 40%, respectively. Eventually, ten risk factors were found to be associated with hypotension, including age >35 years, body mass index ≥25 kg/m2, 11–20 kg weight gain, gravidity ≥4, history of hypotension, baseline systolic blood pressure (SBP 100 beats/min in maternal modelling, fluid preloading ≥1000 ml, adding sufentanil to bupivacaine and sensory block height >T4in anaesthesia-related modelling (P < 0.05. Conclusion: Age, body mass index, weight gain, gravidity, history of hypotension, baseline SBP and heart rate, fluid preloading, adding sufentanil to bupivacaine and sensory block hieght were the main risk factors identified in the study for SA-induced hypotension during CS.

  4. Modelling the monetary policy reaction function of the Colombian Central Bank

    OpenAIRE

    Otero, Jesus; Ramírez, Manuel

    2008-01-01

    This paper proposes a simple Ordered Probit model to analyse the monetary policy reaction function of the Colombian Central Bank. There is evidence that the reaction function is asymmetric, in the sense that the Bank increases the Bank rate when the gap between observed inflation and the inflation target (lagged once) is positive, but it does not reduce the Bank rate when the gap is negative. This behaviour suggests that the Bank is more interested in fulfilling the announced inflation target...

  5. Multinomial malware classification based on call graphs

    OpenAIRE

    Østbye, Morten Oscar

    2017-01-01

    Ever since the computer was invented, people have found ways to evolve interaction or simplify tasks with computational resources, this for both good and bad. For the known lifespan of the digital age, malicious software (malware) has been a constant threat to computer systems. Malware has been the cause of enormous damage related to both governmental and private sectors, but also for individuals. Malware has evolved to target different systems and environments and therefore there exists a va...

  6. Choice experiments versus revealed choice models : a before-after study of consumer spatial shopping behavior

    NARCIS (Netherlands)

    Timmermans, H.J.P.; Borgers, A.W.J.; Waerden, van der P.J.H.J.

    1992-01-01

    The purpose of this article is to compare a set of multinomial logit models derived from revealed choice data and a decompositional choice model derived from experimental data in terms of predictive success in the context of consumer spatial shopping behavior. Data on consumer shopping choice

  7. TAFV Alternative Fuels and Vehicles Choice Model Documentation; TOPICAL

    International Nuclear Information System (INIS)

    Greene, D.L.

    2001-01-01

    A model for predicting choice of alternative fuel and among alternative vehicle technologies for light-duty motor vehicles is derived. The nested multinomial logit (NML) mathematical framework is used. Calibration of the model is based on information in the existing literature and deduction based on assuming a small number of key parameters, such as the value of time and discount rates. A spreadsheet model has been developed for calibration and preliminary testing of the model

  8. Recommender system based on scarce information mining.

    Science.gov (United States)

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

    2017-09-01

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

  9. Text document classification based on mixture models

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana; Malík, Antonín

    2004-01-01

    Roč. 40, č. 3 (2004), s. 293-304 ISSN 0023-5954 R&D Projects: GA AV ČR IAA2075302; GA ČR GA102/03/0049; GA AV ČR KSK1019101 Institutional research plan: CEZ:AV0Z1075907 Keywords : text classification * text categorization * multinomial mixture model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.224, year: 2004

  10. A comparison of dose-response models for death from hematological depression

    International Nuclear Information System (INIS)

    Morris, M.D.; Jones, T.D.

    1987-01-01

    Many radiation-induced lethality experiments that have been published for various mammalian species have been compiled into a database suitable to study interspecific variability of radiosensitivity, dose-rate dependence of sensitivity, dose-response behavior within each experiment, etc. The data compiled were restricted to continuous and nearly continuous exposures to photon radiations having source energies above 100 keV. Also, photon source energy, exposure geometry, and body weight considerations were used to select studies where the dose to hematopoietic marrow was nearly uniform, i.e., < +- 20%. The data base reflects 13 mammalian test species ranging from mouse to cattle. Some 211 studies were compiled but only 105 were documented in adequate detail to be useful in development and evaluation of dose-response models of interest to practical human exposures. Of the 105 studies, 70 were for various rodent species, and 35 were for nonrodent groups ranging from standard laboratory primates (body weight ∼5 kg) to cattle (body weight 375 kg). This paper considers seven different dose-response models which are tested for validity against those 105 studies. The dose-response models included: a right-skewed extreme value, a left-skewed extreme value model, log-logistic, log-probit, logistic, probit, and Weibull models. In general, the log transformed models did not improve model performance and the extreme value models did not seem consistent with the preponderance of the data. Overall, the probit and the logistic models seemed preferable over the Weibull model. 30 refs., 8 tabs

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

    Science.gov (United States)

    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…

  12. —: A Multicategory Brand Equity Model and Its Application at Allstate

    OpenAIRE

    Venkatesh Shankar; Pablo Azar; Matthew Fuller

    2008-01-01

    We develop a robust model for estimating, tracking, and managing brand equity for multicategory brands based on customer survey and financial measures. This model has two components: (1) offering value (computed from discounted cash flow analysis) and (2) relative brand importance (computed from brand choice models such as multinomial logit, heteroscedastic extreme value, and mixed logit). We apply this model to estimate the brand equity of Allstate—a leading insurance company—and its leading...

  13. The Development of Dynamic Brand Equity Chase Model and Its Application to Digital Industry Based on Scanner Data

    OpenAIRE

    Nam Yongsik; Kwak Youngsik

    2009-01-01

    The purpose of this research is to develop a comprehensive modeling for measuring dynamics of brand power. We define brand power as brand specific coefficients to yield the sales volume for each period. The modeling consists of multinomial log it model for eachproduct category, the brand-specific coefficients, mixture modeling and fuzzy clustering algorithm. We apply our modeling to TV scanner data in Tianjin China. The results show 5 brands have 12 to 23 times change on their brand power in ...

  14. Correlations and Non-Linear Probability Models

    DEFF Research Database (Denmark)

    Breen, Richard; Holm, Anders; Karlson, Kristian Bernt

    2014-01-01

    the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under......Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models....

  15. Evaluation of Statistical Methods for Modeling Historical Resource Production and Forecasting

    Science.gov (United States)

    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

  16. QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles

    OpenAIRE

    Nyberg, Henri

    2010-01-01

    In the empirical finance literature findings on the risk return tradeoff in excess stock market returns are ambiguous. In this study, we develop a new QR-GARCH-M model combining a probit model for a binary business cycle indicator and a regime switching GARCH-in-mean model for excess stock market return with the business cycle indicator defining the regime. Estimation results show that there is statistically significant variation in the U.S. excess stock returns over the business cycle. Howev...

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

    Science.gov (United States)

    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.

  18. Estimation of the Thurstonian model for the 2-AC protocol

    DEFF Research Database (Denmark)

    Christensen, Rune Haubo Bojesen; Lee, Hye-Seong; Brockhoff, Per B.

    2012-01-01

    . This relationship makes it possible to extract estimates and standard errors of δ and τ from general statistical software, and furthermore, it makes it possible to combine standard regression modelling with the Thurstonian model for the 2-AC protocol. A model for replicated 2-AC data is proposed using cumulative......The 2-AC protocol is a 2-AFC protocol with a “no-difference” option and is technically identical to the paired preference test with a “no-preference” option. The Thurstonian model for the 2-AC protocol is parameterized by δ and a decision parameter τ, the estimates of which can be obtained...... by fairly simple well-known methods. In this paper we describe how standard errors of the parameters can be obtained and how exact power computations can be performed. We also show how the Thurstonian model for the 2-AC protocol is closely related to a statistical model known as a cumulative probit model...

  19. Modeling the Choice of Telecommuting Frequency in California: An Exploratory Analysis

    OpenAIRE

    Mannering, Jill S.; Mokhtarian, Patricia L.

    1995-01-01

    This study explores the individual's choice of telecommuting frequency as a function of demographic, travel, work and attitudinal factors. To do this, multinomial logit models are estimated using data collected in a recent survey of employees from three public agencies in California. Separate models are estimated, one for data collected from the Franchise Tax Board in Sacramento, one for data from the Public Utilities Commission in San Francisco, and one for data collected from employees of t...

  20. Latent spatial models and sampling design for landscape genetics

    Science.gov (United States)

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

    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 random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  1. A model for predicting Inactivity in the European Banking Sector

    Directory of Open Access Journals (Sweden)

    Themistokles Lazarides

    2015-08-01

    Full Text Available Purpose – The paper will addresses the issue of inactivity and will try to detect its causes using econometric models. The Banking sector of Europe has been under transformation or restructuring for almost half a century. Design/methodology/approach – Probit models and descriptive statistics have been used to create a system that predicts inactivity. The data was collected from Bankscope. Findings – The results of the econometric models show that from the six groups of indicators, four have been found to be statistically important (performance, size, ownership, corporate governance. These findings are consistent with the theory. Research limitations/implications – The limitation is that Bankscope does not provide any longitudinal data regarding ownership, management structure and there are some many missing values before 2007 for some of the financial ratios and data. Originality/value – The paper's value and innovation is that it has given a systemic approach to find indicators of inactivity.

  2. Bayesian inference in an item response theory model with a generalized student t link function

    Science.gov (United States)

    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.

  3. Modelling and Forecasting Stock Price Movements with Serially Dependent Determinants

    Directory of Open Access Journals (Sweden)

    Rasika Yatigammana

    2018-05-01

    Full Text Available The direction of price movements are analysed under an ordered probit framework, recognising the importance of accounting for discreteness in price changes. By extending the work of Hausman et al. (1972 and Yang and Parwada (2012,This paper focuses on improving the forecast performance of the model while infusing a more practical perspective by enhancing flexibility. This is achieved by extending the existing framework to generate short term multi period ahead forecasts for better decision making, whilst considering the serial dependence structure. This approach enhances the flexibility and adaptability of the model to future price changes, particularly targeting risk minimisation. Empirical evidence is provided, based on seven stocks listed on the Australian Securities Exchange (ASX. The prediction success varies between 78 and 91 per cent for in-sample and out-of-sample forecasts for both the short term and long term.

  4. Differential Topic Models.

    Science.gov (United States)

    Chen, Changyou; Buntine, Wray; Ding, Nan; Xie, Lexing; Du, Lan

    2015-02-01

    In applications we may want to compare different document collections: they could have shared content but also different and unique aspects in particular collections. This task has been called comparative text mining or cross-collection modeling. We present a differential topic model for this application that models both topic differences and similarities. For this we use hierarchical Bayesian nonparametric models. Moreover, we found it was important to properly model power-law phenomena in topic-word distributions and thus we used the full Pitman-Yor process rather than just a Dirichlet process. Furthermore, we propose the transformed Pitman-Yor process (TPYP) to incorporate prior knowledge such as vocabulary variations in different collections into the model. To deal with the non-conjugate issue between model prior and likelihood in the TPYP, we thus propose an efficient sampling algorithm using a data augmentation technique based on the multinomial theorem. Experimental results show the model discovers interesting aspects of different collections. We also show the proposed MCMC based algorithm achieves a dramatically reduced test perplexity compared to some existing topic models. Finally, we show our model outperforms the state-of-the-art for document classification/ideology prediction on a number of text collections.

  5. Web based health surveys: Using a Two Step Heckman model to examine their potential for population health analysis.

    Science.gov (United States)

    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.

  6. Mathematical Modeling for Risk Averse Firm Facing Loss Averse Customer’s Stochastic Uncertainty

    Directory of Open Access Journals (Sweden)

    Seungbeom Kim

    2017-01-01

    Full Text Available To optimize the firm’s profit during a finite planning horizon, a dynamic programming model is used to make joint pricing and inventory replenishment decision assuming that customers are loss averse and the firm is risk averse. We model the loss averse customer’s demand using the multinomial choice model. In this choice model, we consider the acquisition and transition utilities widely used by a mental accounting theory which also incorporate the reference price and actual price. Then, we show that there is an optimal inventory policy which is base-stock policy depending on the accumulated wealth in each period.

  7. The Cognitive Processes Underlying Event-Based Prospective Memory In School Age Children and Young Adults: A Formal Model-Based Study

    OpenAIRE

    Smith, Rebekah E.; Bayen, Ute Johanna; Martin, Claudia

    2010-01-01

    Fifty 7-year-olds (29 female), 53 10-year-olds (29 female), and 36 young adults (19 female), performed a computerized event-based prospective memory task. All three groups differed significantly in prospective memory performance with adults showing the best performance and 7-year-olds the poorest performance. We used a formal multinomial process tree model of event-based prospective memory to decompose age differences in cognitive processes that jointly contribute to prospective memory perfor...

  8. Forecasting Macedonian Business Cycle Turning Points Using Qual Var Model

    Directory of Open Access Journals (Sweden)

    Petrovska Magdalena

    2016-09-01

    Full Text Available This paper aims at assessing the usefulness of leading indicators in business cycle research and forecast. Initially we test the predictive power of the economic sentiment indicator (ESI within a static probit model as a leading indicator, commonly perceived to be able to provide a reliable summary of the current economic conditions. We further proceed analyzing how well an extended set of indicators performs in forecasting turning points of the Macedonian business cycle by employing the Qual VAR approach of Dueker (2005. In continuation, we evaluate the quality of the selected indicators in pseudo-out-of-sample context. The results show that the use of survey-based indicators as a complement to macroeconomic data work satisfactory well in capturing the business cycle developments in Macedonia.

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

    Science.gov (United States)

    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.

  10. Joint models for noise annoyance and willingness to pay for road noise reduction

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Bue Bjørner, Thomas

    2006-01-01

    Recent contingent valuation (CV) studies of the willingness to pay (WTP) for road noise reduction have used stated annoyance as an independent variable. We argue that this may be inappropriate due to potential endogeneity bias. Instead, an alternative model is proposed that treats both WTP...... and annoyance as endogenous variables in a simultaneous equation model as a combination of a linear regression with an ordered probit with correlated error terms and possibly common parameters. Thus, information on stated annoyance is utilised to estimate WTP with increased efficiency. Application of the model...... to a dataset from Copenhagen indicates a potential for improving the precision of the estimate of WTP for noise reduction with CV data....

  11. Longitudinal beta-binomial modeling using GEE for overdispersed binomial data.

    Science.gov (United States)

    Wu, Hongqian; Zhang, Ying; Long, Jeffrey D

    2017-03-15

    Longitudinal binomial data are frequently generated from multiple questionnaires and assessments in various scientific settings for which the binomial data are often overdispersed. The standard generalized linear mixed effects model may result in severe underestimation of standard errors of estimated regression parameters in such cases and hence potentially bias the statistical inference. In this paper, we propose a longitudinal beta-binomial model for overdispersed binomial data and estimate the regression parameters under a probit model using the generalized estimating equation method. A hybrid algorithm of the Fisher scoring and the method of moments is implemented for computing the method. Extensive simulation studies are conducted to justify the validity of the proposed method. Finally, the proposed method is applied to analyze functional impairment in subjects who are at risk of Huntington disease from a multisite observational study of prodromal Huntington disease. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Statistical modelling for social researchers principles and practice

    CERN Document Server

    Tarling, Roger

    2008-01-01

    This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-l...

  13. Patient choice modelling: how do patients choose their hospitals?

    Science.gov (United States)

    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.

  14. A constrained rasch model of trace redintegration in serial recall.

    Science.gov (United States)

    Roodenrys, Steven; Miller, Leonie M

    2008-04-01

    The notion that verbal short-term memory tasks, such as serial recall, make use of information in long-term as well as in short-term memory is instantiated in many models of these tasks. Such models incorporate a process in which degraded traces retrieved from a short-term store are reconstructed, or redintegrated (Schweickert, 1993), through the use of information in long-term memory. This article presents a conceptual and mathematical model of this process based on a class of item-response theory models. It is demonstrated that this model provides a better fit to three sets of data than does the multinomial processing tree model of redintegration (Schweickert, 1993) and that a number of conceptual accounts of serial recall can be related to the parameters of the model.

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

    Science.gov (United States)

    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.

  16. Nonparametric Bayes Modeling of Multivariate Categorical Data.

    Science.gov (United States)

    Dunson, David B; Xing, Chuanhua

    2012-01-01

    Modeling of multivariate unordered categorical (nominal) data is a challenging problem, particularly in high dimensions and cases in which one wishes to avoid strong assumptions about the dependence structure. Commonly used approaches rely on the incorporation of latent Gaussian random variables or parametric latent class models. The goal of this article is to develop a nonparametric Bayes approach, which defines a prior with full support on the space of distributions for multiple unordered categorical variables. This support condition ensures that we are not restricting the dependence structure a priori. We show this can be accomplished through a Dirichlet process mixture of product multinomial distributions, which is also a convenient form for posterior computation. Methods for nonparametric testing of violations of independence are proposed, and the methods are applied to model positional dependence within transcription factor binding motifs.

  17. Attitudinal travel demand model for non-work trips of homogeneously constrained segments of a population

    Energy Technology Data Exchange (ETDEWEB)

    Recker, W.W.; Stevens, R.F.

    1977-06-01

    Market-segmentation techniques are used to capture effects of opportunity and availability constraints on urban residents' choice of mode for trips for major grocery shopping and for visiting friends and acquaintances. Attitudinal multinomial logit choice models are estimated for each market segment. Explanatory variables are individual's beliefs about attributes of four modal alternatives: bus, car, taxi and walking. Factor analysis is employed to identify latent dimensions of perception of the modal alternatives and to eliminate problems of multicollinearity in model estimation.

  18. Modeling the Joint Labor-Commute Engagement Decisions of San Francisco Bay Area Residents

    OpenAIRE

    Ory, David T.; Mokhtarian, Patricia L.

    2005-01-01

    Using socio-demographic, personality, and attitudinal data from 1,680 residents of the San Francisco Bay Area, we develop and estimate binary, multinomial, and nested logit models of the choice to work or not, whether or not to work at home, and whether to commute all of the time or some of the time (either by only working part time, or by working a compressed work week, or by telecommuting some of the time). To our knowledge, these are the first models of all these choices simultaneously. Th...

  19. ABrox-A user-friendly Python module for approximate Bayesian computation with a focus on model comparison.

    Science.gov (United States)

    Mertens, Ulf Kai; Voss, Andreas; Radev, Stefan

    2018-01-01

    We give an overview of the basic principles of approximate Bayesian computation (ABC), a class of stochastic methods that enable flexible and likelihood-free model comparison and parameter estimation. Our new open-source software called ABrox is used to illustrate ABC for model comparison on two prominent statistical tests, the two-sample t-test and the Levene-Test. We further highlight the flexibility of ABC compared to classical Bayesian hypothesis testing by computing an approximate Bayes factor for two multinomial processing tree models. Last but not least, throughout the paper, we introduce ABrox using the accompanied graphical user interface.

  20. Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China

    OpenAIRE

    Hong Chen; Zuo-xian Gan; Yu-ting He

    2015-01-01

    Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all great...

  1. Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

    Science.gov (United States)

    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.

  2. The relationship between organizational culture and performance in acute hospitals.

    Science.gov (United States)

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

    2013-01-01

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

  3. Intercity Travel Demand Analysis Model

    Directory of Open Access Journals (Sweden)

    Ming Lu

    2014-01-01

    Full Text Available It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model of main mode choice and access mode choice. At last, an integrated multilevel nested logit model structure system was built. The model system includes trip generation, destination choice, and mode-route choice based on multinomial logit model, and it achieved linkage and feedback of each part through logsum variable. This model was applied in Shenzhen intercity railway passenger demand forecast in 2010 as a case study. As a result, the forecast results were consistent with the actuality. The model's correctness and feasibility were verified.

  4. Workshop on Model Uncertainty and its Statistical Implications

    CERN Document Server

    1988-01-01

    In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.

  5. Rigorously testing multialternative decision field theory against random utility models.

    Science.gov (United States)

    Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg

    2014-06-01

    Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  6. Modelling

    CERN Document Server

    Spädtke, P

    2013-01-01

    Modeling of technical machines became a standard technique since computer became powerful enough to handle the amount of data relevant to the specific system. Simulation of an existing physical device requires the knowledge of all relevant quantities. Electric fields given by the surrounding boundary as well as magnetic fields caused by coils or permanent magnets have to be known. Internal sources for both fields are sometimes taken into account, such as space charge forces or the internal magnetic field of a moving bunch of charged particles. Used solver routines are briefly described and some bench-marking is shown to estimate necessary computing times for different problems. Different types of charged particle sources will be shown together with a suitable model to describe the physical model. Electron guns are covered as well as different ion sources (volume ion sources, laser ion sources, Penning ion sources, electron resonance ion sources, and H$^-$-sources) together with some remarks on beam transport.

  7. Modelling female fertility traits in beef cattle using linear and non-linear models.

    Science.gov (United States)

    Naya, H; Peñagaricano, F; Urioste, J I

    2017-06-01

    Female fertility traits are key components of the profitability of beef cattle production. However, these traits are difficult and expensive to measure, particularly under extensive pastoral conditions, and consequently, fertility records are in general scarce and somehow incomplete. Moreover, fertility traits are usually dominated by the effects of herd-year environment, and it is generally assumed that relatively small margins are kept for genetic improvement. New ways of modelling genetic variation in these traits are needed. Inspired in the methodological developments made by Prof. Daniel Gianola and co-workers, we assayed linear (Gaussian), Poisson, probit (threshold), censored Poisson and censored Gaussian models to three different kinds of endpoints, namely calving success (CS), number of days from first calving (CD) and number of failed oestrus (FE). For models involving FE and CS, non-linear models overperformed their linear counterparts. For models derived from CD, linear versions displayed better adjustment than the non-linear counterparts. Non-linear models showed consistently higher estimates of heritability and repeatability in all cases (h 2  linear models; h 2  > 0.23 and r > 0.24, for non-linear models). While additive and permanent environment effects showed highly favourable correlations between all models (>0.789), consistency in selecting the 10% best sires showed important differences, mainly amongst the considered endpoints (FE, CS and CD). In consequence, endpoints should be considered as modelling different underlying genetic effects, with linear models more appropriate to describe CD and non-linear models better for FE and CS. © 2017 Blackwell Verlag GmbH.

  8. mixtools: An R Package for Analyzing Mixture Models

    Directory of Open Access Journals (Sweden)

    Tatiana Benaglia

    2009-10-01

    Full Text Available The mixtools package for R provides a set of functions for analyzing a variety of finite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reflect some recent research in finite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide range of different mixture-of-regression contexts, in multinomial mixtures such as those arising from discretizing continuous multivariate data, in nonparametric situations where the multivariate component densities are completely unspecified, and in semiparametric situations such as a univariate location mixture of symmetric but otherwise unspecified densities. Many of the algorithms of the mixtools package are EM algorithms or are based on EM-like ideas, so this article includes an overview of EM algorithms for finite mixture models.

  9. Don’t Work, Work at Home, or Commute? Discrete Choice Models of the Decision for San Francisco Bay Area Residents

    OpenAIRE

    Ory, D T; Mokhtarian, Patricia L

    2005-01-01

    Using socio-demographic, personality, and attitudinal data from 1,680 residents of the San Francisco Bay Area, we develop and estimate binary, multinomial, and nested logit models of the choice to work or not, whether or not to work at home, and whether to commute all of the time or some of the time (either by only working part time, or by working a compressed work week, or by telecommuting some of the time). To our knowledge, these are the first models of all these choices simultaneously. Th...

  10. Single toxin dose-response models revisited

    Energy Technology Data Exchange (ETDEWEB)

    Demidenko, Eugene, E-mail: eugened@dartmouth.edu [Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH03756 (United States); Glaholt, SP, E-mail: sglaholt@indiana.edu [Indiana University, School of Public & Environmental Affairs, Bloomington, IN47405 (United States); Department of Biological Sciences, Dartmouth College, Hanover, NH03755 (United States); Kyker-Snowman, E, E-mail: ek2002@wildcats.unh.edu [Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH03824 (United States); Shaw, JR, E-mail: joeshaw@indiana.edu [Indiana University, School of Public & Environmental Affairs, Bloomington, IN47405 (United States); Chen, CY, E-mail: Celia.Y.Chen@dartmouth.edu [Department of Biological Sciences, Dartmouth College, Hanover, NH03755 (United States)

    2017-01-01

    The goal of this paper is to offer a rigorous analysis of the sigmoid shape single toxin dose-response relationship. The toxin efficacy function is introduced and four special points, including maximum toxin efficacy and inflection points, on the dose-response curve are defined. The special points define three phases of the toxin effect on mortality: (1) toxin concentrations smaller than the first inflection point or (2) larger then the second inflection point imply low mortality rate, and (3) concentrations between the first and the second inflection points imply high mortality rate. Probabilistic interpretation and mathematical analysis for each of the four models, Hill, logit, probit, and Weibull is provided. Two general model extensions are introduced: (1) the multi-target hit model that accounts for the existence of several vital receptors affected by the toxin, and (2) model with a nonzero mortality at zero concentration to account for natural mortality. Special attention is given to statistical estimation in the framework of the generalized linear model with the binomial dependent variable as the mortality count in each experiment, contrary to the widespread nonlinear regression treating the mortality rate as continuous variable. The models are illustrated using standard EPA Daphnia acute (48 h) toxicity tests with mortality as a function of NiCl or CuSO{sub 4} toxin. - Highlights: • The paper offers a rigorous study of a sigmoid dose-response relationship. • The concentration with highest mortality rate is rigorously defined. • A table with four special points for five morality curves is presented. • Two new sigmoid dose-response models have been introduced. • The generalized linear model is advocated for estimation of sigmoid dose-response relationship.

  11. Insights from computational modeling in inflammation and acute rejection in limb transplantation.

    Directory of Open Access Journals (Sweden)

    Dolores Wolfram

    Full Text Available Acute skin rejection in vascularized composite allotransplantation (VCA is the major obstacle for wider adoption in clinical practice. This study utilized computational modeling to identify biomarkers for diagnosis and targets for treatment of skin rejection. Protein levels of 14 inflammatory mediators in skin and muscle biopsies from syngeneic grafts [n = 10], allogeneic transplants without immunosuppression [n = 10] and allografts treated with tacrolimus [n = 10] were assessed by multiplexed analysis technology. Hierarchical Clustering Analysis, Principal Component Analysis, Random Forest Classification and Multinomial Logistic Regression models were used to segregate experimental groups. Based on Random Forest Classification, Multinomial Logistic Regression and Hierarchical Clustering Analysis models, IL-4, TNF-α and IL-12p70 were the best predictors of skin rejection and identified rejection well in advance of histopathological alterations. TNF-α and IL-12p70 were the best predictors of muscle rejection and also preceded histopathological alterations. Principal Component Analysis identified IL-1α, IL-18, IL-1β, and IL-4 as principal drivers of transplant rejection. Thus, inflammatory patterns associated with rejection are specific for the individual tissue and may be superior for early detection and targeted treatment of rejection.

  12. Bayes Factor Covariance Testing in Item Response Models.

    Science.gov (United States)

    Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

    2017-12-01

    Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

  13. Modelling parking behaviour considering heterogeneity

    Energy Technology Data Exchange (ETDEWEB)

    San Martin, G.A.; Ibeas Portilla, A.; Alonso Oreña, B.; Olio, L. del

    2016-07-01

    Most of motorized trips in cities of middle and small size are made in public transport and mainly in private vehicle, this has caused a saturation in parking systems of the cities, causing important problems to society, one of the most important problems is high occupancy of public space by parking systems. Thus, is required the estimation of models that reproduce users’ behaviour when they are choosing for parking in cities, to carry out transport policies to improve transport efficiency and parking systems in the cities. The aim of this paper is the specification and estimation of models that simulate users’ behaviour when they are choosing among alternatives of parking that there are in the city: free on street parking, paid on street parking, paid on underground parking and Park and Ride (now there isn´t). For this purpose, is proposed a multinomial logit model that consider systematic and random variations in tastes. Data of users’ behaviour from the different alternatives of parking have been obtained with a stated preference surveys campaign which have been done in May 2015 in the principal parking zones of the city of Santander. In this paper, we provide a number of improvements to previously developed methodologies because of we consider much more realism to create the scenarios stated preference survey, obtaining better adjustments. (Author)

  14. Spatial occupancy models for large data sets

    Science.gov (United States)

    Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

    2013-01-01

    Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

  15. Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

    Science.gov (United States)

    Seaman, Shaun R; Hughes, Rachael A

    2018-06-01

    Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

  16. A Simulation-Based Dynamic Stochastic Route Choice Model for Evacuation

    Directory of Open Access Journals (Sweden)

    Xing Zhao

    2012-01-01

    Full Text Available This paper establishes a dynamic stochastic route choice model for evacuation to simulate the propagation process of traffic flow and estimate the stochastic route choice under evacuation situations. The model contains a lane-group-based cell transmission model (CTM which sets different traffic capacities for links with different turning movements to flow out in an evacuation situation, an actual impedance model which is to obtain the impedance of each route in time units at each time interval and a stochastic route choice model according to the probit-based stochastic user equilibrium. In this model, vehicles loading at each origin at each time interval are assumed to choose an evacuation route under determinate road network, signal design, and OD demand. As a case study, the proposed model is validated on the network nearby Nanjing Olympic Center after the opening ceremony of the 10th National Games of the People's Republic of China. The traffic volumes and clearing time at five exit points of the evacuation zone are calculated by the model to compare with survey data. The results show that this model can appropriately simulate the dynamic route choice and evolution process of the traffic flow on the network in an evacuation situation.

  17. Analysis of transtheoretical model of health behavioral changes in a nutrition intervention study--a continuous time Markov chain model with Bayesian approach.

    Science.gov (United States)

    Ma, Junsheng; Chan, Wenyaw; Tsai, Chu-Lin; Xiong, Momiao; Tilley, Barbara C

    2015-11-30

    Continuous time Markov chain (CTMC) models are often used to study the progression of chronic diseases in medical research but rarely applied to studies of the process of behavioral change. In studies of interventions to modify behaviors, a widely used psychosocial model is based on the transtheoretical model that often has more than three states (representing stages of change) and conceptually permits all possible instantaneous transitions. Very little attention is given to the study of the relationships between a CTMC model and associated covariates under the framework of transtheoretical model. We developed a Bayesian approach to evaluate the covariate effects on a CTMC model through a log-linear regression link. A simulation study of this approach showed that model parameters were accurately and precisely estimated. We analyzed an existing data set on stages of change in dietary intake from the Next Step Trial using the proposed method and the generalized multinomial logit model. We found that the generalized multinomial logit model was not suitable for these data because it ignores the unbalanced data structure and temporal correlation between successive measurements. Our analysis not only confirms that the nutrition intervention was effective but also provides information on how the intervention affected the transitions among the stages of change. We found that, compared with the control group, subjects in the intervention group, on average, spent substantively less time in the precontemplation stage and were more/less likely to move from an unhealthy/healthy state to a healthy/unhealthy state. Copyright © 2015 John Wiley & Sons, Ltd.

  18. PUBLIC APPROVAL OF PLANT AND ANIMAL BIOTECHNOLOGY IN KOREA: AN ORDERED PROBIT ANALYSIS

    OpenAIRE

    Hallman, William K.; Onyango, Benjamin M.; Govindasamy, Ramu; Jang, Ho-Min; Puduri, Venkata S.

    2004-01-01

    This study analyzes predictors of Korean public acceptance of the use of biotechnology to create genetically modified food products. Results indicate that the consumers with above average knowledge of specific outcomes of genetic modification were more likely than those with inaccurate or no knowledge to approve use of plant or animal genetic modification for the creation of new food products. Young South Koreans consumers (ages 20 to 29 years old) were more likely than old consumers (ages 50...

  19. Clinical implications of alternative TCP models for nonuniform dose distributions

    International Nuclear Information System (INIS)

    Deasy, J. O.

    1995-01-01

    Several tumor control probability (TCP) models for nonuniform dose distributions were compared, including: (a) a logistic/inter-patient-heterogeneity model, (b) a probit/inter-patient-heterogeneity model, (c) a Poisson/radioresistant-strain/identical-patients model, (d) a Poisson/inter-patient-heterogeneity model and (e) a Poisson/intra-tumor- and inter-patient-heterogeneity model. The models were analyzed in terms of the probability of controlling a single tumor voxel (the voxel control probability, or VCP), as a function of voxel volume and dose. Alternatively, the VCP surface can be thought of as the effect of a small cold spot. The models based on the Poisson equation which include inter-patient heterogeneity ((d) and (e)) have VCP surfaces (VCP as a function of dose and volume) which have a threshold 'waterfall' shape: below the waterfall (in dose), VCP is nearly zero. The threshold dose decreases with decreasing voxel volume. However, models (a), (b), and (c) all show a high probability of controlling a voxel (VCP>50%) with very low dose (e.g., 1 Gy) if the voxel is small (smaller than about 10 -3 of the tumor volume). Model (c) does not have the waterfall shape at low volumes due to the assumption of patient uniformity and a neglect of the effect of the clonogens which are more radiosensitive (and more numerous). Models (a) and (b) deviate from the waterfall shape at low volumes due to numerical differences between the functions used and the Poisson function. Hence, the Possion models which include inter-patient heterogeneities ((d) and (e)) are more sensitive to the effects of small cold spots than the other models considered

  20. Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

    Science.gov (United States)

    Lorenz, Alyson; Dhingra, Radhika; Chang, Howard H; Bisanzio, Donal; Liu, Yang; Remais, Justin V

    2014-01-01

    Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. Three models based on measures of vegetation, habitat patch characteristics, and herbaceous landcover emerged as effective predictors of observed disease and vector distribution. An ensemble model containing these three models improved precision and predictive ability over individual models. A priori assessment of qualitative model characteristics effectively identified models that subsequently emerged as better predictors in quantitative analysis. Both a methodology for quantitative model comparison and a checklist for qualitative assessment of candidate models for extrapolation are provided; both tools aim to improve collaboration between those producing models and those interested in applying them to new areas and research questions.

  1. Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

    Directory of Open Access Journals (Sweden)

    Alyson Lorenz

    Full Text Available Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. Three models based on measures of vegetation, habitat patch characteristics, and herbaceous landcover emerged as effective predictors of observed disease and vector distribution. An ensemble model containing these three models improved precision and predictive ability over individual models. A priori assessment of qualitative model characteristics effectively identified models that subsequently emerged as better predictors in quantitative analysis. Both a methodology for quantitative model comparison and a checklist for qualitative assessment of candidate models for extrapolation are provided; both tools aim to improve collaboration between those producing models and those interested in applying them to new areas and research questions.

  2. An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions

    Energy Technology Data Exchange (ETDEWEB)

    Oña, J. de; Oña, R. de; Eboli, L.; Forciniti, C.; Mazzulla, G.

    2016-07-01

    Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future. (Author)

  3. Modeling the Perceptions and Preferences of Pedestrians on Crossing Facilities

    Directory of Open Access Journals (Sweden)

    Hongwei Guo

    2014-01-01

    Full Text Available Pedestrian’s street-crossing behaviour has a significant effect on traffic performance and safety. The crossing behaviour is determined by human factors and environmental factors. Aiming at examining the pedestrian perceptions toward crossing facilities and preferences for crossing locations, an observational study of pedestrian crossing behaviour at urban street is conducted. The perceptions and preferences of pedestrians are collected using stated preference technique. A specific questionnaire is designed to conduct the stated preference survey. A multinomial logit model is proposed to describe the perceptions and preferences of pedestrians on crossing facilities and locations. The sensitivity analysis is performed to discuss the influence of various factors on crossing behaviour. Then the relationship between crossing locations and crossing distances is analyzed by a new proposed method. With the theoretical analysis, the engineering solutions considering pedestrian behaviour are suggested. The results are helpful to design human-centered crossing facilities in urban traffic.

  4. A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

    Science.gov (United States)

    Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

    2018-04-19

    Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model

  5. A Heckman selection model for the safety analysis of signalized intersections.

    Directory of Open Access Journals (Sweden)

    Xuecai Xu

    Full Text Available The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously.This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI, respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years.The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels.A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections.

  6. The design and analysis of salmonid tagging studies in the Columbia basin. Volume 8: A new model for estimating survival probabilities and residualization from a release-recapture study of fall chinook salmon (Oncorhynchus tschawytscha) smolts in the Snake River

    International Nuclear Information System (INIS)

    Lowther, A.B.; Skalski, J.

    1997-09-01

    Standard release-recapture analysis using Cormack-Jolly-Seber (CJS) models to estimate survival probabilities between hydroelectric facilities for Snake river fall chinook salmon (Oncorhynchus tschawytscha) ignore the possibility of individual fish residualizing and completing their migration in the year following tagging. These models do not utilize available capture history data from this second year and, thus, produce negatively biased estimates of survival probabilities. A new multinomial likelihood model was developed that results in biologically relevant, unbiased estimates of survival probabilities using the full two years of capture history data. This model was applied to 1995 Snake River fall chinook hatchery releases to estimate the true survival probability from one of three upstream release points (Asotin, Billy Creek, and Pittsburgh Landing) to Lower Granite Dam. In the data analyzed here, residualization is not a common physiological response and thus the use of CJS models did not result in appreciably different results than the true survival probability obtained using the new multinomial likelihood model

  7. Effects of ignoring baseline on modeling transitions from intact cognition to dementia.

    Science.gov (United States)

    Yu, Lei; Tyas, Suzanne L; Snowdon, David A; Kryscio, Richard J

    2009-07-01

    This paper evaluates the effect of ignoring baseline when modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. Transitions among states are modeled by a discrete-time Markov chain having three transient (intact cognition, MCI, and GI) and two competing absorbing states (death and dementia). Transition probabilities depend on two covariates, age and the presence/absence of an apolipoprotein E-epsilon4 allele, through a multinomial logistic model with shared random effects. Results are illustrated with an application to the Nun Study, a cohort of 678 participants 75+ years of age at baseline and followed longitudinally with up to ten cognitive assessments per nun.

  8. EXTENDING THE DEEP PACKET INSPECTION MODEL TO THE GCC/MENA REGION

    Directory of Open Access Journals (Sweden)

    Alfred H. Miller

    2013-12-01

    Full Text Available This study seeks to explore extending the technology acceptance model (DPAM from a 2011 quantitative study—Modeling Intention to Use Deep Packet Inspection Technology in the United Arab Emirates, to the cyber security practitioner community of the Gulf Cooperation Council (GCC and greater Middle East North Africa (MENA Region. Analysis of regression between independent variable model factors of computer self efficacy, attitude toward ICT, perceived usefulness of ecommerce, intention to use ecommerce, societal trust and Internet filtration toward the dependent variable intention to use deep packet inspection, to determine parsimony, using confirmatory factor analysis (CFA, multinomial regression to assess correlation of independent and dependent variables, and assessment of the cross-suitability of DPAM across the MENA/GCC states through a MANOVA assessment. A qualitative component of the instrument enables collection of data about specific hardware and software deployed for deep packet inspection and cyber security systems.

  9. Modeling marrow damage from response data: Morphallaxis from radiation biology to benzene toxicity

    Energy Technology Data Exchange (ETDEWEB)

    Jones, T.D.; Morris, M.D.; Hasan, J.S.

    1995-12-01

    Consensus principles from radiation biology were used to describe a generic set of nonlinear, first-order differential equations for modeling of toxicity-induced compensatory cell kinetics in terms of sublethal injury, repair, direct killing, killing of cells with unrepaired sublethal injury, and repopulation. This cellular model was linked to a probit model of hematopoietic mortality that describes death from infection and/or hemorrhage between {approximately} 5 and 30 days. Mortality data from 27 experiments with 851 doseresponse groups, in which doses were protracted by rate and/or fractionation, were used to simultaneously estimate all rate constants by maximum-likelihood methods. Data used represented 18,940 test animals distributed according to: (mice, 12,827); (rats, 2,925); (sheep, 1,676); (swine, 829); (dogs, 479); and (burros, 204). Although a long-term, repopulating hematopoietic stem cell is ancestral to all lineages needed to restore normal homeostasis, the dose-response data from the protracted irradiations indicate clearly that the particular lineage that is ``critical`` to hematopoietic recovery does not resemble stem-like cells with regard to radiosensitivity and repopulation rates. Instead, the weakest link in the chain of hematopoiesis was found to have an intrinsic radioresistance equal to or greater than stromal cells and to repopulate at the same rates. Model validation has been achieved by predicting the LD{sub 50} and/or fractional group mortality in 38 protracted-dose experiments (rats and mice) that were not used in the fitting of model coefficients.

  10. Modeling marrow damage from response data: Morphallaxis from radiation biology to benzene toxicity

    International Nuclear Information System (INIS)

    Jones, T.D.; Morris, M.D.; Hasan, J.S.

    1995-01-01

    Consensus principles from radiation biology were used to describe a generic set of nonlinear, first-order differential equations for modeling of toxicity-induced compensatory cell kinetics in terms of sublethal injury, repair, direct killing, killing of cells with unrepaired sublethal injury, and repopulation. This cellular model was linked to a probit model of hematopoietic mortality that describes death from infection and/or hemorrhage between ∼ 5 and 30 days. Mortality data from 27 experiments with 851 doseresponse groups, in which doses were protracted by rate and/or fractionation, were used to simultaneously estimate all rate constants by maximum-likelihood methods. Data used represented 18,940 test animals distributed according to: (mice, 12,827); (rats, 2,925); (sheep, 1,676); (swine, 829); (dogs, 479); and (burros, 204). Although a long-term, repopulating hematopoietic stem cell is ancestral to all lineages needed to restore normal homeostasis, the dose-response data from the protracted irradiations indicate clearly that the particular lineage that is ''critical'' to hematopoietic recovery does not resemble stem-like cells with regard to radiosensitivity and repopulation rates. Instead, the weakest link in the chain of hematopoiesis was found to have an intrinsic radioresistance equal to or greater than stromal cells and to repopulate at the same rates. Model validation has been achieved by predicting the LD 50 and/or fractional group mortality in 38 protracted-dose experiments (rats and mice) that were not used in the fitting of model coefficients

  11. Modeling the Cumulative Effects of Social Exposures on Health: Moving beyond Disease-Specific Models

    Directory of Open Access Journals (Sweden)

    Heather L. White

    2013-03-01

    Full Text Available The traditional explanatory models used in epidemiology are “disease specific”, identifying risk factors for specific health conditions. Yet social exposures lead to a generalized, cumulative health impact which may not be specific to one illness. Disease-specific models may therefore misestimate social factors’ effects on health. Using data from the Canadian Community Health Survey and Canada 2001 Census we construct and compare “disease-specific” and “generalized health impact” (GHI models to gauge the negative health effects of one social exposure: socioeconomic position (SEP. We use logistic and multinomial multilevel modeling with neighbourhood-level material deprivation, individual-level education and household income to compare and contrast the two approaches. In disease-specific models, the social determinants under study were each associated with the health conditions of interest. However, larger effect sizes were apparent when outcomes were modeled as compound health problems (0, 1, 2, or 3+ conditions using the GHI approach. To more accurately estimate social exposures’ impacts on population health, researchers should consider a GHI framework.

  12. A real-time crash prediction model for the ramp vicinities of urban expressways

    Directory of Open Access Journals (Sweden)

    Moinul Hossain

    2013-07-01

    Full Text Available Ramp vicinities are arguably the known black-spots on urban expressways. There, while maintaining high speed, drivers need to respond to several complex events such as maneuvering, reading road signs, route planning and maintaining safe distance from other maneuvering vehicles simultaneously which demand higher level of cognitive response to ensure safety. Therefore, any additional discomfort caused by traffic dynamics may induce driving error resulting in a crash. This manuscript presents a methodology for identifying these dynamically forming hazardous traffic conditions near the ramp vicinities with high resolution real-time traffic flow data. It separates the ramp vicinities into four zones – upstream and downstream of entrance and exit ramps, and builds four separate real-time crash prediction models. Around two year (December 2007 to October 2009 crash data as well as their matching traffic sensor data from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited have been utilized for this research. Random multinomial logit, a forest of multinomial logit models, has been used to identify the most important variables. Finally, a real-time modeling method, Bayesian belief net (BBN, has been employed to build the four models using ramp flow, flow and congestion index in the upstream and flow and speed in the downstream of the ramp location as variables. The newly proposed models could predict 50%, 42%, 43% and 55% of the future crashes with around 10% false alarm for the downstream of entrance, downstream of exit, upstream of entrance and upstream of exit ramps respectively. The models can be utilized in combination with various traffic smoothing measures such as ramp metering, variable speed limit, warning messages through variable message signs, etc. to enhance safety near the ramp vicinities.

  13. Modeling Fuel Choice among Households in Northern Cameroon

    Directory of Open Access Journals (Sweden)

    Jean Hugues Nlom

    2015-07-01

    Full Text Available The present study aims to explore economic and socio-demographic factors that influence a household’s probability to switch from firewood to cleaner fuels (kerosene and LPG in northern Cameroon. The paper employs an ordered probit model to construct cooking patterns and fuel choices. Three main cooking sources are considered: firewood, kerosene, and liquefied petroleum gas. Utilized data are derived from a national survey conducted in 2004 by the Cameroonian National Institute of Statistics. The study analyzes the data related to the Sudano-Sahelian agro-ecological zone, which is one of the most affected by land degradation and decertification. While results indicate that there is a potential for a transition from traditional to cleaner fuels in the studied region, this transition is still in its earlier stage. The research demonstrates that firewood and kerosene prices, age of household heads, educational level of household heads and willingness to have a gas cylinder, as well as type of dwelling have a statistically significant impact on fuel-switching decisions.

  14. Immigrants' language skills: the immigrant experience in a longitudinal survey

    OpenAIRE

    Barry CHISWICK; Yew LEE; Paul W. MILLER

    2003-01-01

    This paper is concerned with the determinants of English language proficiency among immigrants. It presents a model based on economic incentives, exposure, and efficiency in language acquisition, which it tests using the Longitudinal Survey of Immigrants to Australia. Probit and bivariate probit analyses are employed. The hypotheses are supported by the data. The bivariate probit analysis across waves indicates a "regression to the mean" in the unobserved components of English language profic...

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

    Energy Technology Data Exchange (ETDEWEB)

    Dias, Felipe F.; Lavieri, Patrícia S.; Garikapati, Venu M.; Astroza, Sebastian; Pendyala, Ram M.; Bhat, Chandra R.

    2017-07-26

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

  16. Job Motivation and Self-Confidence for Learning and Development as Predictors of Support for Change

    OpenAIRE

    Vithessonthi, Chaiporn; Schwaninger, Markus

    2008-01-01

    For the most part, studies on change management have attempted to determine the factors that influence employee resistance to change. The focus of the present study is to test whether job motivation and self-confidence for learning and development influence employee support for downsizing. Data were gathered from a sample of 86 teachers at one private school in Bangkok, Thailand. The analysis was carried out using multinomial ordered probit regression. The results suggest that the level of jo...

  17. Modelling Preference Heterogeneity for Theatre Tickets

    DEFF Research Database (Denmark)

    Baldin, Andrea; Bille, Trine

    This paper analyzes the behavioural choice for theatre tickets using a rich dataset for 2010-2013 from the sale system of the Royal Danish National Theatre. A consumer who decides to attend a theater production faces multiple sources of price variation that depends on: socio-economic characterist......This paper analyzes the behavioural choice for theatre tickets using a rich dataset for 2010-2013 from the sale system of the Royal Danish National Theatre. A consumer who decides to attend a theater production faces multiple sources of price variation that depends on: socio......-economic characteristics, quality of the seat, day of the performance and timing of purchase. Except for the first case, factors of price differentiation involves a choice by the consumer among different ticket alternatives. Two modelling approaches, namely multinomial logit (with socio-demographic characteristics......) and latent class are proposed in order to model ticket purchase behaviour. These models allow us explicitly to take into account consumers' preference heterogeneity with respect to the attributes associated to each ticket alternative In addition, the distribution of the willingness-to-pay (WTP) of choice...

  18. Calculating the Probability of Returning a Loan with Binary Probability Models

    Directory of Open Access Journals (Sweden)

    Julian Vasilev

    2014-12-01

    Full Text Available The purpose of this article is to give a new approach in calculating the probability of returning a loan. A lot of factors affect the value of the probability. In this article by using statistical and econometric models some influencing factors are proved. The main approach is concerned with applying probit and logit models in loan management institutions. A new aspect of the credit risk analysis is given. Calculating the probability of returning a loan is a difficult task. We assume that specific data fields concerning the contract (month of signing, year of signing, given sum and data fields concerning the borrower of the loan (month of birth, year of birth (age, gender, region, where he/she lives may be independent variables in a binary logistics model with a dependent variable “the probability of returning a loan”. It is proved that the month of signing a contract, the year of signing a contract, the gender and the age of the loan owner do not affect the probability of returning a loan. It is proved that the probability of returning a loan depends on the sum of contract, the remoteness of the loan owner and the month of birth. The probability of returning a loan increases with the increase of the given sum, decreases with the proximity of the customer, increases for people born in the beginning of the year and decreases for people born at the end of the year.

  19. Modeling Stochastic Route Choice Behaviors with Equivalent Impedance

    Directory of Open Access Journals (Sweden)

    Jun Li

    2015-01-01

    Full Text Available A Logit-based route choice model is proposed to address the overlapping and scaling problems in the traditional multinomial Logit model. The nonoverlapping links are defined as a subnetwork, and its equivalent impedance is explicitly calculated in order to simply network analyzing. The overlapping links are repeatedly merged into subnetworks with Logit-based equivalent travel costs. The choice set at each intersection comprises only the virtual equivalent route without overlapping. In order to capture heterogeneity in perception errors of different sizes of networks, different scale parameters are assigned to subnetworks and they are linked to the topological relationships to avoid estimation burden. The proposed model provides an alternative method to model the stochastic route choice behaviors without the overlapping and scaling problems, and it still maintains the simple and closed-form expression from the MNL model. A link-based loading algorithm based on Dial’s algorithm is proposed to obviate route enumeration and it is suitable to be applied on large-scale networks. Finally a comparison between the proposed model and other route choice models is given by numerical examples.

  20. Clustering disaggregated load profiles using a Dirichlet process mixture model

    International Nuclear Information System (INIS)

    Granell, Ramon; Axon, Colin J.; Wallom, David C.H.

    2015-01-01

    Highlights: • We show that the Dirichlet process mixture model is scaleable. • Our model does not require the number of clusters as an input. • Our model creates clusters only by the features of the demand profiles. • We have used both residential and commercial data sets. - Abstract: The increasing availability of substantial quantities of power-use data in both the residential and commercial sectors raises the possibility of mining the data to the advantage of both consumers and network operations. We present a Bayesian non-parametric model to cluster load profiles from households and business premises. Evaluators show that our model performs as well as other popular clustering methods, but unlike most other methods it does not require the number of clusters to be predetermined by the user. We used the so-called ‘Chinese restaurant process’ method to solve the model, making use of the Dirichlet-multinomial distribution. The number of clusters grew logarithmically with the quantity of data, making the technique suitable for scaling to large data sets. We were able to show that the model could distinguish features such as the nationality, household size, and type of dwelling between the cluster memberships

  1. Modelos de predição para sobrevivência de plantas de Eucalyptus grandis Prediction models of Eucalyptus grandis plant survival

    Directory of Open Access Journals (Sweden)

    Telde Natel Custódio

    2009-01-01

    Full Text Available Objetivou-se com este trabalho comparar modelos de predição de plantas sobreviventes de Eucalyptus grandis. Utilizaram-se os seguintes modelos: modelo linear misto com os dados transformados, utilizando-se as transformações angular e BOX-COX; modelo linear generalizado misto com distribuição binomial e funções de ligação logística, probit e complemento log-log; modelo linear generalizado misto com distribuição Poisson e função de ligação logarítmica. Os dados são provenientes de um experimento em blocos ao acaso, para avaliação de progênies maternas de Eucalyptus grandis, aos 5 anos de idade, em que a variável resposta são plantas sobreviventes. Para comparação dos efeitos entre os modelos foram estimadas as correlações de Spearman e aplicado o teste de permutação de Fisher. Foi possível concluir que, o modelo linear generalizado misto com distribuição Poisson e função de ligação logarítmica se ajustou mal aos dados e que as estimativas para os efeitos fixos e predição para os efeitos aleatórios, não se diferenciaram entre os demais modelos estudados.The objective of this work was to compare models for prediction of the survival of plants of Eucalyptus grandis. The following models were used: linear mixed model with the transformed data, by utilizing the angular transformations and BOX-COX; generalized linear mixed model with binomial distribution and logistic functions, probit and complement log-log links; generalized linear mixed model with Poisson distribution and logarithmic link function. The data came from a randomized block experiment for evaluation of Eucalyptus grandis maternal progenies at five years old, in which the variable response are surviving plants. For comparison of the effects among the models the correlations of Spearman were estimated and the test of permutation of Fisher was applied. It was possible to conclude that: the generalized linear mixed model with Poisson distribution and

  2. Patterns and correlates of solid waste disposal practices in Dar es ...

    African Journals Online (AJOL)

    USER

    collection. Key words: Solid waste, garbage, waste disposal, waste management, Multinomial Logit model. INTRODUCTION. Urbanization introduces society to a new, modern way of ..... Multinomial logistic estimation. .... The trend of using.

  3. An integrated model to simulate sown area changes for major crops at a global scale

    Institute of Scientific and Technical Information of China (English)

    SHIBASAKI; Ryosuke

    2008-01-01

    Dynamics of land use systems have attracted much attention from scientists around the world due to their ecological and socio-economic implications. An integrated model to dynamically simulate future changes in sown areas of four major crops (rice, maize, wheat and soybean) on a global scale is pre- sented. To do so, a crop choice model was developed on the basis of Multinomial Logit (Logit) model to model land users’ decisions on crop choices among a set of available alternatives with using a crop utility function. A GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted to simulate the crop yields under a given geophysical environment and farming management conditions, while the International Food Policy and Agricultural Simulation (IFPSIM) model was utilized to estimate crop price in the international market. The crop choice model was linked with the GIS-based EPIC model and the IFPSIM model through data exchange. This integrated model was then validated against the FAO statistical data in 2001-2003 and the Moderate Resolution Imaging Spectroradiometer (MODIS) global land cover product in 2001. Both validation approaches indicated reliability of the model for ad- dressing the dynamics in agricultural land use and its capability for long-term scenario analysis. Finally, the model application was designed to run over a time period of 30 a, taking the year 2000 as baseline. The model outcomes can help understand and explain the causes, locations and consequences of land use changes, and provide support for land use planning and policy making.

  4. Comparative analysis of informal borrowing behaviour between ...

    African Journals Online (AJOL)

    Tools of analyses were descriptive statistics of mean and percentages and probit model, The result of the Probit model on the variables influencing borrowing behaviour of male-headed households indicated that the coefficients of household size, farm size, purpose of borrowing, loan duration, interest rate and collateral ...

  5. A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

    Science.gov (United States)

    Karabatsos, George

    2017-02-01

    Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected

  6. Development of discrete choice model considering internal reference points and their effects in travel mode choice context

    Science.gov (United States)

    Sarif; Kurauchi, Shinya; Yoshii, Toshio

    2017-06-01

    In the conventional travel behavior models such as logit and probit, decision makers are assumed to conduct the absolute evaluations on the attributes of the choice alternatives. On the other hand, many researchers in cognitive psychology and marketing science have been suggesting that the perceptions of attributes are characterized by the benchmark called “reference points” and the relative evaluations based on them are often employed in various choice situations. Therefore, this study developed a travel behavior model based on the mental accounting theory in which the internal reference points are explicitly considered. A questionnaire survey about the shopping trip to the CBD in Matsuyama city was conducted, and then the roles of reference points in travel mode choice contexts were investigated. The result showed that the goodness-of-fit of the developed model was higher than that of the conventional model, indicating that the internal reference points might play the major roles in the choice of travel mode. Also shown was that the respondents seem to utilize various reference points: some tend to adopt the lowest fuel price they have experienced, others employ fare price they feel in perceptions of the travel cost.

  7. Investigating the adaptive model of thermal comfort for naturally ventilated school buildings in Taiwan

    Science.gov (United States)

    Hwang, Ruey-Lung; Lin, Tzu-Ping; Chen, Chen-Peng; Kuo, Nai-Jung

    2009-03-01

    Divergence in the acceptability to people in different regions of naturally ventilated thermal environments raises a concern over the extent to which the ASHRAE Standard 55 may be applied as a universal criterion of thermal comfort. In this study, the ASHRAE 55 adaptive model of thermal comfort was investigated for its applicability to a hot and humid climate through a long-term field survey performed in central Taiwan among local students attending 14 elementary and high schools during September to January. Adaptive behaviors, thermal neutrality, and thermal comfort zones are explored. A probit analysis of thermal acceptability responses from students was performed in place of the conventional linear regression of thermal sensation votes against operative temperature to investigate the limits of comfort zones for 90% and 80% acceptability; the corresponding comfort zones were found to occur at 20.1-28.4°C and 17.6-30.0°C, respectively. In comparison with the yearly comfort zones recommended by the adaptive model for naturally ventilated spaces in the ASHRAE Standard 55, those observed in this study differ in the lower limit for 80% acceptability, with the observed level being 1.7°C lower than the ASHRAE-recommended value. These findings can be generalized to the population of school children, thus providing information that can supplement ASHRAE Standard 55 in evaluating the thermal performance of naturally ventilated school buildings, particularly in hot-humid areas such as Taiwan.

  8. Environmental Sound Perception: Metadescription and Modeling Based on Independent Primary Studies

    Directory of Open Access Journals (Sweden)

    Stephen McAdams

    2010-01-01

    Full Text Available The aim of the study is to transpose and extend to a set of environmental sounds the notion of sound descriptors usually used for musical sounds. Four separate primary studies dealing with interior car sounds, air-conditioning units, car horns, and closing car doors are considered collectively. The corpus formed by these initial stimuli is submitted to new experimental studies and analyses, both for revealing metacategories and for defining more precisely the limits of each of the resulting categories. In a second step, the new structure is modeled: common and specific dimensions within each category are derived from the initial results and new investigations of audio features are performed. Furthermore, an automatic classifier based on two audio descriptors and a multinomial logistic regression procedure is implemented and validated with the corpus.

  9. Cumulative t-link threshold models for the genetic analysis of calving ease scores

    Directory of Open Access Journals (Sweden)

    Tempelman Robert J

    2003-09-01

    Full Text Available Abstract In this study, a hierarchical threshold mixed model based on a cumulative t-link specification for the analysis of ordinal data or more, specifically, calving ease scores, was developed. The validation of this model and the Markov chain Monte Carlo (MCMC algorithm was carried out on simulated data from normally and t4 (i.e. a t-distribution with four degrees of freedom distributed populations using the deviance information criterion (DIC and a pseudo Bayes factor (PBF measure to validate recently proposed model choice criteria. The simulation study indicated that although inference on the degrees of freedom parameter is possible, MCMC mixing was problematic. Nevertheless, the DIC and PBF were validated to be satisfactory measures of model fit to data. A sire and maternal grandsire cumulative t-link model was applied to a calving ease dataset from 8847 Italian Piemontese first parity dams. The cumulative t-link model was shown to lead to posterior means of direct and maternal heritabilities (0.40 ± 0.06, 0.11 ± 0.04 and a direct maternal genetic correlation (-0.58 ± 0.15 that were not different from the corresponding posterior means of the heritabilities (0.42 ± 0.07, 0.14 ± 0.04 and the genetic correlation (-0.55 ± 0.14 inferred under the conventional cumulative probit link threshold model. Furthermore, the correlation (> 0.99 between posterior means of sire progeny merit from the two models suggested no meaningful rerankings. Nevertheless, the cumulative t-link model was decisively chosen as the better fitting model for this calving ease data using DIC and PBF.

  10. A disaggregate model to predict the intercity travel demand

    Energy Technology Data Exchange (ETDEWEB)

    Damodaran, S.

    1988-01-01

    This study was directed towards developing disaggregate models to predict the intercity travel demand in Canada. A conceptual framework for the intercity travel behavior was proposed; under this framework, a nested multinomial model structure that combined mode choice and trip generation was developed. The CTS (Canadian Travel Survey) data base was used for testing the structure and to determine the viability of using this data base for intercity travel-demand prediction. Mode-choice and trip-generation models were calibrated for four modes (auto, bus, rail and air) for both business and non-business trips. The models were linked through the inclusive value variable, also referred to as the long sum of the denominator in the literature. Results of the study indicated that the structure used in this study could be applied for intercity travel-demand modeling. However, some limitations of the data base were identified. It is believed that, with some modifications, the CTS data could be used for predicting intercity travel demand. Future research can identify the factors affecting intercity travel behavior, which will facilitate collection of useful data for intercity travel prediction and policy analysis.

  11. Measuring political sentiment on Twitter: factor-optimal design for multinomial inverse regression

    OpenAIRE

    Taddy, Matt

    2012-01-01

    This article presents a short case study in text analysis: the scoring of Twitter posts for positive, negative, or neutral sentiment directed towards particular US politicians. The study requires selection of a sub-sample of representative posts for sentiment scoring, a common and costly aspect of sentiment mining. As a general contribution, our application is preceded by a proposed algorithm for maximizing sampling efficiency. In particular, we outline and illustrate greedy selection of docu...

  12. Analysis of Functional Data with Focus on Multinomial Regression and Multilevel Data

    DEFF Research Database (Denmark)

    Mousavi, Seyed Nourollah

    Functional data analysis (FDA) is a fast growing area in statistical research with increasingly diverse range of application from economics, medicine, agriculture, chemometrics, etc. Functional regression is an area of FDA which has received the most attention both in aspects of application...... and methodological development. Our main Functional data analysis (FDA) is a fast growing area in statistical research with increasingly diverse range of application from economics, medicine, agriculture, chemometrics, etc. Functional regression is an area of FDA which has received the most attention both in aspects...

  13. Wage mobility in Europe. A comparative analysis using restricted multinomial logit regression

    NARCIS (Netherlands)

    Pavlopoulos, D.; Muffels, R.; Vermunt, J.K.

    2010-01-01

    In this paper, we investigate cross-country differences in wage mobility in Europe using the European Community Household Panel. The paper is particularly focused on examining the impact of economic conditions, welfare state regimes and employment regulation on wage mobility. We apply a log-linear

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

    Science.gov (United States)

    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...

  15. Think twice before you book? Modelling the choice of public vs private dentist in a choice experiment.

    Science.gov (United States)

    Kiiskinen, Urpo; Suominen-Taipale, Anna Liisa; Cairns, John

    2010-06-01

    This study concerns the choice of primary dental service provider by consumers. If the health service delivery system allows individuals to choose between public-care providers or if complementary private services are available, it is typically assumed that utilisation is a three-stage decision process. The patient first makes a decision to seek care, and then chooses the service provider. The final stage, involving decisions over the amount and form of treatment, is not considered here. The paper reports a discrete choice experiment (DCE) designed to evaluate attributes affecting individuals' choice of dental-care provider. The feasibility of the DCE approach in modelling consumers' choice in the context of non-acute need for dental care is assessed. The aim is to test whether a separate two-stage logit, a multinomial logit, or a nested logit best fits the choice process of consumers. A nested logit model of indirect utility functions is estimated and inclusive value (IV) constraints are tested for modelling implications. The results show that non-trading behaviour has an impact on the choice of appropriate modelling technique, but is to some extent dependent on the choice of scenarios offered. It is concluded that for traders multinomial logit is appropriate, whereas for non-traders and on average the nested logit is the method supported by the analyses. The consistent finding in all subgroup analyses is that the traditional two-stage decision process is found to be implausible in the context of consumer's choice of dental-care provider.

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

    Science.gov (United States)

    Ma, Ke-Zong M; Norton, Edward C; Lee, Shoou-Yih D

    2011-12-12

    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. 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. 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. 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

  17. ADOPT: A Historically Validated Light Duty Vehicle Consumer Choice Model

    Energy Technology Data Exchange (ETDEWEB)

    Brooker, A.; Gonder, J.; Lopp, S.; Ward, J.

    2015-05-04

    The Automotive Deployment Option Projection Tool (ADOPT) is a light-duty vehicle consumer choice and stock model supported by the U.S. Department of Energy’s Vehicle Technologies Office. It estimates technology improvement impacts on U.S. light-duty vehicles sales, petroleum use, and greenhouse gas emissions. ADOPT uses techniques from the multinomial logit method and the mixed logit method estimate sales. Specifically, it estimates sales based on the weighted value of key attributes including vehicle price, fuel cost, acceleration, range and usable volume. The average importance of several attributes changes nonlinearly across its range and changes with income. For several attributes, a distribution of importance around the average value is used to represent consumer heterogeneity. The majority of existing vehicle makes, models, and trims are included to fully represent the market. The Corporate Average Fuel Economy regulations are enforced. The sales feed into the ADOPT stock model. It captures key aspects for summing petroleum use and greenhouse gas emissions This includes capturing the change in vehicle miles traveled by vehicle age, the creation of new model options based on the success of existing vehicles, new vehicle option introduction rate limits, and survival rates by vehicle age. ADOPT has been extensively validated with historical sales data. It matches in key dimensions including sales by fuel economy, acceleration, price, vehicle size class, and powertrain across multiple years. A graphical user interface provides easy and efficient use. It manages the inputs, simulation, and results.

  18. Landslide susceptibility mapping in Mawat area, Kurdistan Region, NE Iraq: a comparison of different statistical models

    Science.gov (United States)

    Othman, A. A.; Gloaguen, R.; Andreani, L.; Rahnama, M.

    2015-03-01

    During the last decades, expansion of settlements into areas prone to landslides in Iraq has increased the importance of accurate hazard assessment. Susceptibility mapping provides information about hazardous locations and thus helps to potentially prevent infrastructure damage due to mass wasting. The aim of this study is to evaluate and compare frequency ratio (FR), weight of evidence (WOE), logistic regression (LR) and probit regression (PR) approaches in combination with new geomorphological indices to determine the landslide susceptibility index (LSI). We tested these four methods in Mawat area, Kurdistan Region, NE Iraq, where landslides occur frequently. For this purpose, we evaluated 16 geomorphological, geological and environmental predicting factors mainly derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite. The available reference inventory includes 351 landslides representing a cumulative surface of 3.127 km2. This reference inventory was mapped from QuickBird data by manual delineation and partly verified by field survey. The areas under curve (AUC) of the receiver operating characteristic (ROC), and relative landslide density (R index) show that all models perform similarly and that focus should be put on the careful selection of proxies. The results indicate that the lithology and the slope aspects play major roles for landslide occurrences. Furthermore, this paper demonstrates that using hypsometric integral as a prediction factor instead of slope curvature gives better results and increases the accuracy of the LSI.

  19. Econometric modelling of risk adverse behaviours of entrepreneurs in the provision of house fittings in China

    Directory of Open Access Journals (Sweden)

    Rita Yi Man Li

    2012-03-01

    Full Text Available Entrepreneurs have always born the risk of running their business. They reap a profit in return for their risk taking and work. Housing developers are no different. In many countries, such as Australia, the United Kingdom and the United States, they interpret the tastes of the buyers and provide the dwellings they develop with basic fittings such as floor and wall coverings, bathroom fittings and kitchen cupboards. In mainland China, however, in most of the developments, units or houses are sold without floor or wall coverings, kitchen  or bathroom fittings. What is the motive behind this choice? This paper analyses the factors affecting housing developers’ decisions to provide fittings based on 1701 housing developments in Hangzhou, Chongqing and Hangzhou using a Probit model. The results show that developers build a higher proportion of bare units in mainland China when: 1 there is shortage of housing; 2 land costs are high so that the comparative costs of providing fittings become relatively low.

  20. Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

    Directory of Open Access Journals (Sweden)

    Dirk Temme

    2008-12-01

    Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

  1. Cultural consensus modeling to measure transactional sex in Swaziland: Scale building and validation.

    Science.gov (United States)

    Fielding-Miller, Rebecca; Dunkle, Kristin L; Cooper, Hannah L F; Windle, Michael; Hadley, Craig

    2016-01-01

    Transactional sex is associated with increased risk of HIV and gender based violence in southern Africa and around the world. However the typical quantitative operationalization, "the exchange of gifts or money for sex," can be at odds with a wide array of relationship types and motivations described in qualitative explorations. To build on the strengths of both qualitative and quantitative research streams, we used cultural consensus models to identify distinct models of transactional sex in Swaziland. The process allowed us to build and validate emic scales of transactional sex, while identifying key informants for qualitative interviews within each model to contextualize women's experiences and risk perceptions. We used logistic and multinomial logistic regression models to measure associations with condom use and social status outcomes. Fieldwork was conducted between November 2013 and December 2014 in the Hhohho and Manzini regions. We identified three distinct models of transactional sex in Swaziland based on 124 Swazi women's emic valuation of what they hoped to receive in exchange for sex with their partners. In a clinic-based survey (n = 406), consensus model scales were more sensitive to condom use than the etic definition. Model consonance had distinct effects on social status for the three different models. Transactional sex is better measured as an emic spectrum of expectations within a relationship, rather than an etic binary relationship type. Cultural consensus models allowed us to blend qualitative and quantitative approaches to create an emicly valid quantitative scale grounded in qualitative context. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Airport choice model in multiple airport regions

    Directory of Open Access Journals (Sweden)

    Claudia Muñoz

    2017-02-01

    Full Text Available Purpose: This study aims to analyze travel choices made by air transportation users in multi airport regions because it is a crucial component when planning passenger redistribution policies. The purpose of this study is to find a utility function which makes it possible to know the variables that influence users’ choice of the airports on routes to the main cities in the Colombian territory. Design/methodology/approach: This research generates a Multinomial Logit Model (MNL, which is based on the theory of maximizing utility, and it is based on the data obtained on revealed and stated preference surveys applied to users who reside in the metropolitan area of Aburrá Valley (Colombia. This zone is the only one in the Colombian territory which has two neighboring airports for domestic flights. The airports included in the modeling process were Enrique Olaya Herrera (EOH Airport and José María Córdova (JMC Airport. Several structure models were tested, and the MNL proved to be the most significant revealing the common variables that affect passenger airport choice include the airfare, the price to travel the airport, and the time to get to the airport. Findings and Originality/value: The airport choice model which was calibrated corresponds to a valid powerful tool used to calculate the probability of each analyzed airport of being chosen for domestic flights in the Colombian territory. This is done bearing in mind specific characteristic of each of the attributes contained in the utility function. In addition, these probabilities will be used to calculate future market shares of the two airports considered in this study, and this will be done generating a support tool for airport and airline marketing policies.

  3. An imprecise Dirichlet model for Bayesian analysis of failure data including right-censored observations

    International Nuclear Information System (INIS)

    Coolen, F.P.A.

    1997-01-01

    This paper is intended to make researchers in reliability theory aware of a recently introduced Bayesian model with imprecise prior distributions for statistical inference on failure data, that can also be considered as a robust Bayesian model. The model consists of a multinomial distribution with Dirichlet priors, making the approach basically nonparametric. New results for the model are presented, related to right-censored observations, where estimation based on this model is closely related to the product-limit estimator, which is an important statistical method to deal with reliability or survival data including right-censored observations. As for the product-limit estimator, the model considered in this paper aims at not using any information other than that provided by observed data, but our model fits into the robust Bayesian context which has the advantage that all inferences can be based on probabilities or expectations, or bounds for probabilities or expectations. The model uses a finite partition of the time-axis, and as such it is also related to life-tables

  4. An optimal hierarchical decision model for a regional logistics network with environmental impact consideration.

    Science.gov (United States)

    Zhang, Dezhi; Li, Shuangyan; Qin, Jin

    2014-01-01

    This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

  5. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Directory of Open Access Journals (Sweden)

    Dezhi Zhang

    2014-01-01

    Full Text Available This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users’ demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators’ service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

  6. Maximum likelihood estimation of semiparametric mixture component models for competing risks data.

    Science.gov (United States)

    Choi, Sangbum; Huang, Xuelin

    2014-09-01

    In the analysis of competing risks data, the cumulative incidence function is a useful quantity to characterize the crude risk of failure from a specific event type. In this article, we consider an efficient semiparametric analysis of mixture component models on cumulative incidence functions. Under the proposed mixture model, latency survival regressions given the event type are performed through a class of semiparametric models that encompasses the proportional hazards model and the proportional odds model, allowing for time-dependent covariates. The marginal proportions of the occurrences of cause-specific events are assessed by a multinomial logistic model. Our mixture modeling approach is advantageous in that it makes a joint estimation of model parameters associated with all competing risks under consideration, satisfying the constraint that the cumulative probability of failing from any cause adds up to one given any covariates. We develop a novel maximum likelihood scheme based on semiparametric regression analysis that facilitates efficient and reliable estimation. Statistical inferences can be conveniently made from the inverse of the observed information matrix. We establish the consistency and asymptotic normality of the proposed estimators. We validate small sample properties with simulations and demonstrate the methodology with a data set from a study of follicular lymphoma. © 2014, The International Biometric Society.

  7. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Science.gov (United States)

    Zhang, Dezhi; Li, Shuangyan

    2014-01-01

    This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209

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

    Science.gov (United States)

    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…

  9. An anatomic risk model to screen post endovascular aneurysm repair patients for aneurysm sac enlargement.

    Science.gov (United States)

    Png, Chien Yi M; Tadros, Rami O; Beckerman, William E; Han, Daniel K; Tardiff, Melissa L; Torres, Marielle R; Marin, Michael L; Faries, Peter L

    2017-09-01

    Follow-up computed tomography angiography (CTA) scans add considerable postimplantation costs to endovascular aneurysm repairs (EVARs) of abdominal aortic aneurysms (AAAs). By building a risk model, we hope to identify patients at low risk for aneurysm sac enlargement to minimize unnecessary CTAs. 895 consecutive patients who underwent EVAR for AAA were reviewed, of which 556 met inclusion criteria. A Probit model was created for aneurysm sac enlargement, with preoperative aneurysm morphology, patient demographics, and operative details as variables. Our final model included 287 patients and had a sensitivity of 100%, a specificity of 68.9%, and an accuracy of 70.4%. Ninety-nine (35%) of patients were assigned to the high-risk group, whereas 188 (65%) of patients were assigned to the low-risk group. Notably, regarding anatomic variables, our model reported that age, pulmonary comorbidities, aortic neck diameter, iliac artery length, and aneurysms were independent predictors of post-EVAR sac enlargement. With the exception of age, all statistically significant variables were qualitatively supported by prior literature. With regards to secondary outcomes, the high-risk group had significantly higher proportions of AAA-related deaths (5.1% versus 1.1%, P = 0.037) and Type 1 endoleaks (9.1% versus 3.2%, P = 0.033). Our model is a decent predictor of patients at low risk for post AAA EVAR aneurysm sac enlargement and associated complications. With additional validation and refinement, it could be applied to practices to cut down on the overall need for postimplantation CTA. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Generalized outcome-based strategy classification: comparing deterministic and probabilistic choice models.

    Science.gov (United States)

    Hilbig, Benjamin E; Moshagen, Morten

    2014-12-01

    Model comparisons are a vital tool for disentangling which of several strategies a decision maker may have used--that is, which cognitive processes may have governed observable choice behavior. However, previous methodological approaches have been limited to models (i.e., decision strategies) with deterministic choice rules. As such, psychologically plausible choice models--such as evidence-accumulation and connectionist models--that entail probabilistic choice predictions could not be considered appropriately. To overcome this limitation, we propose a generalization of Bröder and Schiffer's (Journal of Behavioral Decision Making, 19, 361-380, 2003) choice-based classification method, relying on (1) parametric order constraints in the multinomial processing tree framework to implement probabilistic models and (2) minimum description length for model comparison. The advantages of the generalized approach are demonstrated through recovery simulations and an experiment. In explaining previous methods and our generalization, we maintain a nontechnical focus--so as to provide a practical guide for comparing both deterministic and probabilistic choice models.

  11. Street Choice Logit Model for Visitors in Shopping Districts

    Directory of Open Access Journals (Sweden)

    Ko Kawada

    2014-07-01

    Full Text Available In this study, we propose two models for predicting people’s activity. The first model is the pedestrian distribution prediction (or postdiction model by multiple regression analysis using space syntax indices of urban fabric and people distribution data obtained from a field survey. The second model is a street choice model for visitors using multinomial logit model. We performed a questionnaire survey on the field to investigate the strolling routes of 46 visitors and obtained a total of 1211 street choices in their routes. We proposed a utility function, sum of weighted space syntax indices, and other indices, and estimated the parameters for weights on the basis of maximum likelihood. These models consider both street networks, distance from destination, direction of the street choice and other spatial compositions (numbers of pedestrians, cars, shops, and elevation. The first model explains the characteristics of the street where many people tend to walk or stay. The second model explains the mechanism underlying the street choice of visitors and clarifies the differences in the weights of street choice parameters among the various attributes, such as gender, existence of destinations, number of people, etc. For all the attributes considered, the influences of DISTANCE and DIRECTION are strong. On the other hand, the influences of Int.V, SHOPS, CARS, ELEVATION, and WIDTH are different for each attribute. People with defined destinations tend to choose streets that “have more shops, and are wider and lower”. In contrast, people with undefined destinations tend to choose streets of high Int.V. The choice of males is affected by Int.V, SHOPS, WIDTH (positive and CARS (negative. Females prefer streets that have many shops, and couples tend to choose downhill streets. The behavior of individual persons is affected by all variables. The behavior of people visiting in groups is affected by SHOP and WIDTH (positive.

  12. Street Choice Logit Model for Visitors in Shopping Districts

    Science.gov (United States)

    Kawada, Ko; Yamada, Takashi; Kishimoto, Tatsuya

    2014-01-01

    In this study, we propose two models for predicting people’s activity. The first model is the pedestrian distribution prediction (or postdiction) model by multiple regression analysis using space syntax indices of urban fabric and people distribution data obtained from a field survey. The second model is a street choice model for visitors using multinomial logit model. We performed a questionnaire survey on the field to investigate the strolling routes of 46 visitors and obtained a total of 1211 street choices in their routes. We proposed a utility function, sum of weighted space syntax indices, and other indices, and estimated the parameters for weights on the basis of maximum likelihood. These models consider both street networks, distance from destination, direction of the street choice and other spatial compositions (numbers of pedestrians, cars, shops, and elevation). The first model explains the characteristics of the street where many people tend to walk or stay. The second model explains the mechanism underlying the street choice of visitors and clarifies the differences in the weights of street choice parameters among the various attributes, such as gender, existence of destinations, number of people, etc. For all the attributes considered, the influences of DISTANCE and DIRECTION are strong. On the other hand, the influences of Int.V, SHOPS, CARS, ELEVATION, and WIDTH are different for each attribute. People with defined destinations tend to choose streets that “have more shops, and are wider and lower”. In contrast, people with undefined destinations tend to choose streets of high Int.V. The choice of males is affected by Int.V, SHOPS, WIDTH (positive) and CARS (negative). Females prefer streets that have many shops, and couples tend to choose downhill streets. The behavior of individual persons is affected by all variables. The behavior of people visiting in groups is affected by SHOP and WIDTH (positive). PMID:25379274

  13. Willingness to pay for renewable energy investment in Korea: A choice experiment study

    International Nuclear Information System (INIS)

    Ku, Se-Ju; Yoo, Seung-Hoon

    2010-01-01

    Renewable energy sources are considered as alternatives for coping with the high price of oil and global warming. The Korean government has set a target that 11% of the total primary energy supply should be obtained through renewable energy sources until 2030. In order to develop proper policies for renewable energy investment, it is necessary to analyze the benefits of renewable energy investment based on households' willingness to pay. This study attempts to apply a choice experiment (CE) for assessing renewable energy investment in Korea. Moreover, we employ a multinomial probit (MNP) model to relax the assumption that all respondents have the same preferences for the attributes being valued, which is usually required in empirical CE studies. An MNP model allows the most flexible pattern of error correlation structure. The results reveal that the Korean public puts a value on the protection of wildlife, reduction of pollution, and increased employment opportunities. On the other hand, respondents do not derive significant values from the improvement of landscapes. This study is expected to provide policy-makers with useful information for evaluating and planning policies related to renewable energy investment. (author)

  14. Modeling Types of Pedal Applications Using a Driving Simulator.

    Science.gov (United States)

    Wu, Yuqing; Boyle, Linda Ng; McGehee, Daniel; Roe, Cheryl A; Ebe, Kazutoshi; Foley, James

    2015-11-01

    The aim of this study was to examine variations in drivers' foot behavior and identify factors associated with pedal misapplications. Few studies have focused on the foot behavior while in the vehicle and the mishaps that a driver can encounter during a potentially hazardous situation. A driving simulation study was used to understand how drivers move their right foot toward the pedals. The study included data from 43 drivers as they responded to a series of rapid traffic signal phase changes. Pedal application types were classified as (a) direct hit, (b) hesitated, (c) corrected trajectory, and (d) pedal errors (incorrect trajectories, misses, slips, or pressed both pedals). A mixed-effects multinomial logit model was used to predict the likelihood of one of these pedal applications, and linear mixed models with repeated measures were used to examine the response time and pedal duration given the various experimental conditions (stimuli color and location). Younger drivers had higher probabilities of direct hits when compared to other age groups. Participants tended to have more pedal errors when responding to a red signal or when the signal appeared to be closer. Traffic signal phases and locations were associated with pedal response time and duration. The response time and pedal duration affected the likelihood of being in one of the four pedal application types. Findings from this study suggest that age-related and situational factors may play a role in pedal errors, and the stimuli locations could affect the type of pedal application. © 2015, Human Factors and Ergonomics Society.

  15. Dental Care Coverage and Use: Modeling Limitations and Opportunities

    Science.gov (United States)

    Moeller, John F.; Chen, Haiyan

    2014-01-01

    Objectives. We examined why older US adults without dental care coverage and use would have lower use rates if offered coverage than do those who currently have coverage. Methods. We used data from the 2008 Health and Retirement Study to estimate a multinomial logistic model to analyze the influence of personal characteristics in the grouping of older US adults into those with and those without dental care coverage and dental care use. Results. Compared with persons with no coverage and no dental care use, users of dental care with coverage were more likely to be younger, female, wealthier, college graduates, married, in excellent or very good health, and not missing all their permanent teeth. Conclusions. Providing dental care coverage to uninsured older US adults without use will not necessarily result in use rates similar to those with prior coverage and use. We have offered a model using modifiable factors that may help policy planners facilitate programs to increase dental care coverage uptake and use. PMID:24328635

  16. A dynamic analysis of motorcycle ownership and usage: a panel data modeling approach.

    Science.gov (United States)

    Wen, Chieh-Hua; Chiou, Yu-Chiun; Huang, Wan-Ling

    2012-11-01

    This study aims to develop motorcycle ownership and usage models with consideration of the state dependence and heterogeneity effects based on a large-scale questionnaire panel survey on vehicle owners. To account for the independence among alternatives and heterogeneity among individuals, the modeling structure of motorcycle ownership adopts disaggregate choice models considering the multinomial, nested, and mixed logit formulations. Three types of panel data regression models--ordinary, fixed, and random effects--are developed and compared for motorcycle usage. The estimation results show that motorcycle ownership in the previous year does exercise a significantly positive effect on the number of motorcycles owned by households in the current year, suggesting that the state dependence effect does exist in motorcycle ownership decisions. In addition, the fixed effects model is the preferred specification for modeling motorcycle usage, indicating strong evidence for existence of heterogeneity. Among various management strategies evaluated under different scenarios, increasing gas prices and parking fees will lead to larger reductions in total kilometers traveled. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. Innovation and motivation in public health professionals.

    Science.gov (United States)

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

    2007-12-01

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

  18. Market Participation and Agro-Biodiversity Loss: The Case of Native Chili Varieties in the Amazon Rainforest of Peru

    Directory of Open Access Journals (Sweden)

    Jaqueline Garcia-Yi

    2014-01-01

    Full Text Available Policies for promoting the in situ conservation of underutilized crop varieties include the provision of economic incentives to farmers for their market commercialization. Nevertheless, market participation could also have the counter-effect of favoring the cultivation of uniform commercial crop varieties and inducing the erosion of crop genetic diversity. The objective of this research was to identify the determinants of the in situ conservation of native chili varieties, including market participation. To this end, 128 farmers were surveyed in the Amazon rainforest region of Ucayali in Peru. The data were analyzed using probit, multinomial logit and truncated Poisson models with covariance matrix correction for cluster errors by rural community. Results suggest that participation in commercial agriculture statistically significantly increases the in situ conservation of native chili varieties; only when farmers sell their products to local retailers, but not when they supply wholesalers. In particular, this result implies that policies designed to encourage specific forms of market participation could have a positive effect on farmers’ economic well-being and simultaneously could help to achieve crop genetic diversity conservation goals.

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

    Science.gov (United States)

    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.

  20. Innovation investment decisions: are post(transition economies different from the rest of the EU?

    Directory of Open Access Journals (Sweden)

    Ljiljana BOZIĆ

    2017-12-01

    Full Text Available The slow progress of innovation in transition economies is not related just to firms’ decision to invest in innovation activities. Rather, it is worth distinguishing between their decision to increase investment, reduce it, keep their investments at the same level or not invest in innovation activities at all. To understand these decisions we develop and estimate models for post-transition and developed European countries employing multinomial probit. The analysis relies on responses of 2580 firms from 11 post-transition countries and 4058 firms from 18 European countries collected by the Flash Eurobarometer 433 - Innobarometer 2016 survey. We have established that the firms’ decision making process in general is mostly related to previous innovation investment experience. In transition countries, the higher the percent of turnover invested in innovation, the lower the probability of an increase in the future. In the firms operating in developed economies, lower turnover from new products is related to the decision to decrease innovation investment in the future.

  1. Highway Expenditures and Associated Customer Satisfaction: A Case Study

    Directory of Open Access Journals (Sweden)

    Alexander Paz

    2016-01-01

    Full Text Available This study analyzes the satisfaction of the Nevadans with respect to their highway transportation system and the corresponding expenditures of Nevada Department of Transportation (NDOT. A survey questionnaire was designed to capture the opinions of the Nevadans (customers about a number of characteristics of their transportation system. Data from the financial data warehouse of the NDOT was used to evaluate expenditures. Multinomial probit models were estimated to study the correlations between customers’ opinion and the government expenditures in transportation. The results indicate the customer satisfaction is decreasing with respect to traffic safety throughout Northwestern and Southern Nevada highways. In addition, users of Northwestern highways are more likely to be satisfied, compared to their counterparts, with increasing construction spending to reduce the time taken to complete construction projects. In Southern Nevada highways, customers’ satisfaction increases with the expenditures associated with reduction of congestion. These insights are examples of the conclusions that were obtained as a consequence of simultaneously considering customer satisfaction and the corresponding expenditures in transportation.

  2. Probabilistic models for 2D active shape recognition using Fourier descriptors and mutual information

    CSIR Research Space (South Africa)

    Govender, N

    2014-08-01

    Full Text Available information to improve the initial shape recognition results. We propose an initial system which performs shape recognition using the euclidean distances of Fourier descriptors. To improve upon these results we build multinomial and Gaussian probabilistic...

  3. Semiparametric accelerated failure time cure rate mixture models with competing risks.

    Science.gov (United States)

    Choi, Sangbum; Zhu, Liang; Huang, Xuelin

    2018-01-15

    Modern medical treatments have substantially improved survival rates for many chronic diseases and have generated considerable interest in developing cure fraction models for survival data with a non-ignorable cured proportion. Statistical analysis of such data may be further complicated by competing risks that involve multiple types of endpoints. Regression analysis of competing risks is typically undertaken via a proportional hazards model adapted on cause-specific hazard or subdistribution hazard. In this article, we propose an alternative approach that treats competing events as distinct outcomes in a mixture. We consider semiparametric accelerated failure time models for the cause-conditional survival function that are combined through a multinomial logistic model within the cure-mixture modeling framework. The cure-mixture approach to competing risks provides a means to determine the overall effect of a treatment and insights into how this treatment modifies the components of the mixture in the presence of a cure fraction. The regression and nonparametric parameters are estimated by a nonparametric kernel-based maximum likelihood estimation method. Variance estimation is achieved through resampling methods for the kernel-smoothed likelihood function. Simulation studies show that the procedures work well in practical settings. Application to a sarcoma study demonstrates the use of the proposed method for competing risk data with a cure fraction. Copyright © 2017 John Wiley & Sons, Ltd.

  4. [Offered income, salary expectations, and the economic activity of married women: an analytic model].

    Science.gov (United States)

    Lollivier, S

    1984-06-01

    This study uses data from tax declarations for 40,000 French households for 1975 to propose a model that permits quantification of the effects of certain significant factors on the economic activity of married women. The PROBIT model of analysis of variance was used to determine the specific effect of several variables, including age of the woman, number of children under 25 years of age in the household, the age of the youngest child, husband's income and socioprofessional status, wife's level and type of education, size of community of residence and region of residence. The principal factors influencing activity rates were found to be educational level, age, and to those of childless women, but activity rates dropped by about 30% for mothers of 2 and even more for mothers of 3 or more children. Influence of the place of residence and the husband's income were associated with lesser disparities. The reasons for variations in female labor force participation can be viewed as analogous to a balance. Underlying factors can increase or decrease the income the woman hopes to earn (offered income) as well as the minimum income for which she will work (required salary). A TOBIT model was constructed in which income was a function of age, education, geographic location, and number of children, and salary required was a function of the variables related to the husband including income and socioprofessional status. For most of the effects considered, the observed variation in activity rates resulted from variations in offered income. The husband's income influences only the desired salary. The offered income decreases and the required salary increases when the number of children is 2 or more, reducing the rate of activity. More educated women have slightly greater salary expectations, but command much higher salaries, resulting in an increased rate of professional activity.

  5. An integrated model to simulate sown area changes for major crops at a global scale

    Institute of Scientific and Technical Information of China (English)

    WU WenBin; YANG Peng; MENG ChaoYing; SHIBASAKI Ryosuke; ZHOU QingBo; TANG HuaJun; SHI Yun

    2008-01-01

    Dynamics of land use systems have attracted much attention from scientists around the world due to their ecological and socio-economic implications. An integrated model to dynamically simulate future changes in sown areas of four major crops (rice, maize, wheat and soybean) on a global scale is presented. To do so, a crop choice model was developed on the basis of Multinomial Logit (Logit) model to model land users' decisions on crop choices among a set of available alternatives with using a crop utility function. A GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted to simulate the crop yields under a given geophysical environment and farming management conditions,while the International Food Policy and Agricultural Simulation (IFPSIM) model was utilized to estimate crop price in the international market. The crop choice model was linked with the GIS-based EPIC model and the IFPSIM model through data exchange. This integrated model was then validated against the FAO statistical data in 2001-2003 and the Moderate Resolution Imaging Spectroradiometer (MODIS)global land cover product in 2001. Both validation approaches indicated reliability of the model for addressing the dynamics in agricultural land use and its capability for long-term scenario analysis. Finally,the model application was designed to run over a time period of 30 a, taking the year 2000 as baseline.The model outcomes can help understand and explain the causes, locations and consequences of land use changes, and provide support for land use planning and policy making.

  6. A bivariate model for analyzing recurrent multi-type automobile failures

    Science.gov (United States)

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

    2017-09-01

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

  7. How much do incentives affect car purchase? Agent-based microsimulation of consumer choice of new cars. Part 1. Model structure, simulation of bounded rationality, and model validation

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, Michel G.; Haan, Peter de [ETH Zurich, Institute for Environmental Decisions, Natural and Social Science Interface, Universitaetstr. 22, CHN J 73.2, 8092 Zurich (Switzerland)

    2009-03-15

    This article presents an agent-based microsimulation capable of forecasting the effects of policy levers that influence individual choices of new passenger cars. The fundamental decision-making units are households distinguished by sociodemographic characteristics and car ownership. A two-stage model of individual decision processes is employed. In the first stage, individual choice sets are constructed using simple, non-compensatory rules that are based on previously owned cars. Second, decision makers evaluate alternatives in their individual choice set using a multi-attributive weighting rule. The attribute weights are based on a multinomial logit model for cross-country policy analysis in European countries. Additionally, prospect theory and the notion of mental accounting are used to model the perception of monetary values. The microsimulation forecasts actual market observations with high accuracy, both on the level of aggregate market characteristics as well as on a highly resolved level of distributions of market shares. The presented approach is useful for the assessment of policies that influence individual purchase decisions of new passenger cars; it allows accounting for a highly resolved car fleet and differentiated consumer segments. As a result, the complexity of incentive schemes can be represented and detailed structural changes can be investigated. (author)

  8. A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates.

    Science.gov (United States)

    An, Qian; Kang, Jian; Song, Ruiguang; Hall, H Irene

    2016-04-30

    Human immunodeficiency virus (HIV) infection is a severe infectious disease actively spreading globally, and acquired immunodeficiency syndrome (AIDS) is an advanced stage of HIV infection. The HIV testing rate, that is, the probability that an AIDS-free HIV infected person seeks a test for HIV during a particular time interval, given no previous positive test has been obtained prior to the start of the time, is an important parameter for public health. In this paper, we propose a Bayesian hierarchical model with two levels of hierarchy to estimate the HIV testing rate using annual AIDS and AIDS-free HIV diagnoses data. At level one, we model the latent number of HIV infections for each year using a Poisson distribution with the intensity parameter representing the HIV incidence rate. At level two, the annual numbers of AIDS and AIDS-free HIV diagnosed cases and all undiagnosed cases stratified by the HIV infections at different years are modeled using a multinomial distribution with parameters including the HIV testing rate. We propose a new class of priors for the HIV incidence rate and HIV testing rate taking into account the temporal dependence of these parameters to improve the estimation accuracy. We develop an efficient posterior computation algorithm based on the adaptive rejection metropolis sampling technique. We demonstrate our model using simulation studies and the analysis of the national HIV surveillance data in the USA. Copyright © 2015 John Wiley & Sons, Ltd.

  9. Airport terminal choice model

    Directory of Open Access Journals (Sweden)

    Claudia Helena Muñoz-Hoyos

    2014-01-01

    Full Text Available La mayoría de los estudios del modo aéreo han tratado individua lmente los aspectos de tarifas, demoras y demás variables inher entes a este medio de transporte, así como la elección del modo aéreo f rente a otros modos, pero poco se ha hecho por modelar cómo un viajero elige un aeropuerto entre dos opciones disponibles en una gran ciudad. En la actualidad un pasajero que parte de la ciudad de Medellín - Colombia a algunos destinos nacionales, tiene la opción de v iajar por alguno de los dos aeropuertos, el José María Córdova (JMC o el Enriqu e Olaya Herrera (EOH; esta investigación presenta los resultad os de una encuesta de preferencias declaradas en un experimento de elecci ón discreta, y partiendo de esto se obtiene un modelo por desti no; para cada uno de estos se hallaron modelos logit multinomial y logit mixt o; en cada trayecto evaluado se eligió el logit multinomial com o el mejor.

  10. Consequences, norms, and generalized inaction in moral dilemmas: The CNI model of moral decision-making.

    Science.gov (United States)

    Gawronski, Bertram; Armstrong, Joel; Conway, Paul; Friesdorf, Rebecca; Hütter, Mandy

    2017-09-01

    Research on moral dilemma judgments has been fundamentally shaped by the distinction between utilitarianism and deontology. According to the principle of utilitarianism, the moral status of behavioral options depends on their consequences; the principle of deontology states that the moral status of behavioral options depends on their consistency with moral norms. To identify the processes underlying utilitarian and deontological judgments, researchers have investigated responses to moral dilemmas that pit one principle against the other (e.g., trolley problem). However, the conceptual meaning of responses in this paradigm is ambiguous, because the central aspects of utilitarianism and deontology-consequences and norms-are not manipulated. We illustrate how this shortcoming undermines theoretical interpretations of empirical findings and describe an alternative approach that resolves the ambiguities of the traditional paradigm. Expanding on this approach, we present a multinomial model that allows researchers to quantify sensitivity to consequences (C), sensitivity to moral norms (N), and general preference for inaction versus action irrespective of consequences and norms (I) in responses to moral dilemmas. We present 8 studies that used this model to investigate the effects of gender, cognitive load, question framing, and psychopathy on moral dilemma judgments. The findings obtained with the proposed CNI model offer more nuanced insights into the determinants of moral dilemma judgments, calling for a reassessment of dominant theoretical assumptions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  11. Modeling the Joint Choice Decisions on Urban Shopping Destination and Travel-to-Shop Mode: A Comparative Study of Different Structures

    Directory of Open Access Journals (Sweden)

    Chuan Ding

    2014-01-01

    Full Text Available The joint choice of shopping destination and travel-to-shop mode in downtown area is described by making use of the cross-nested logit (CNL model structure that allows for potential interalternative correlation along the both choice dimensions. Meanwhile, the traditional multinomial logit (MNL model and nested logit (NL model are also formulated, respectively. This study uses the data collected in the downtown areas of Maryland-Washington, D.C. region, for shopping trips, considering household, individual, land use, and travel related characteristics. The results of the model reveal the significant influencing factors on joint choice travel behavior between shopping destination and travel mode. A comparison of the different models shows that the proposed CNL model structure offers significant improvements in capturing unobserved correlations between alternatives over MNL model and NL model. Moreover, a Monte Carlo simulation for a group of scenarios assuming that there is an increase in parking fees in downtown area is undertaken to examine the impact of a change in car travel cost on the joint choice of shopping destination and travel mode switching. The results are expected to give a better understanding on the shopping travel behavior.

  12. Estimation of causal mediation effects for a dichotomous outcome in multiple-mediator models using the mediation formula.

    Science.gov (United States)

    Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M

    2013-10-30

    Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a nonzero total mediation effect increases as the correlation coefficient between two mediators increases, whereas power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. Copyright © 2013 John Wiley & Sons, Ltd.

  13. Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

    Science.gov (United States)

    Nelson, Suchitra; Albert, Jeffrey M.

    2013-01-01

    Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a non-zero total mediation effect increases as the correlation coefficient between two mediators increases, while power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. PMID:23650048

  14. Toxicоlogical evaluation of the plant products using Brine Shrimp (Artemia salina L. model

    Directory of Open Access Journals (Sweden)

    Меntor R. Hamidi

    2014-04-01

    Full Text Available Many natural products could serve as the starting point in the development of modern medicines because of their numerous biological and pharmacological activities. However, some of them are known to carry toxicological properties as well. In order to achieve a safe treatment with plant products, numerous research studies have recently been focused on both pharmacology and toxicity of medicinal plants. Moreover, these studies employed efforts for alternative biological assays. Brine Shrimp Lethality Assay is the most convenient system for monitoring biological activities of various plant species. This method is very useful for preliminary assessment of toxicity of the plant extracts. Rapidness, simplicity and low requirements are several advantages of this assay. However, several conditions need to be completed, especially in the means of standardized experimental conditions (temperature, pH of the medium, salinity, aeration and light. The toxicity of herbal extracts using this assay has been determined in a concentration range of 10, 100 and 1000 µg/ml of the examined herbal extract. Most toxicity studies which use the Brine Shrimp Lethality Assay determine the toxicity after 24 hours of exposure to the tested sample. The median lethal concentration (LC50 of the test samples is obtained by a plot of percentage of the dead shrimps against the logarithm of the sample concentration. LC50 values are estimated using a probit regression analysis and compared with either Meyer’s or Clarkson’s toxicity criteria. Furthermore, the positive correlation between Meyer’s toxicity scale for Artemia salina and Gosselin, Smith and Hodge’s toxicity scale for higher animal models confirmed that the Brine Shrimp Lethality Assay is an excellent predictive tool for the toxic potential of plant extracts in humans.

  15. CHAPTER 1

    African Journals Online (AJOL)

    Dr Olaleye

    The Probit regression showed statistical significant (p<0.05) impact of contact and precautionary indices .... parameters of the estimated model are denoted as β. ... Where is the constant term and is the stochastic error term.

  16. extent of use of ict by fish farmers in isoko agricultural zone of delta ...

    African Journals Online (AJOL)

    Mr. TONY A

    Descriptive statistics and binary probit model were the tools of analyses. ... extension services and affordable credit will help in promoting the ... Depending on the extension approach, farmers should either pay totally or partially the extension ...

  17. Factors influencing cassava - pulp fermentation period for gari ...

    African Journals Online (AJOL)

    Factors influencing cassava - pulp fermentation period for gari processing among ... Result of probit model analysis at 5% significance level shows an R value ... Marital status (2.236**) and respondents' cultural influences (1.960**) were ...

  18. The Dynamics of Poverty and Vulnerability in Rural Ethiopia

    African Journals Online (AJOL)

    from the random effects probit model suggest that determinants of poverty status in rural Ethiopia ... 1 School of Agricultural Economics and Agribusiness, ... security policies, strategies and programs in the last two decades (FDRE,. 2004 ...

  19. Determinants of Fisher's Choice of Fishing Activity along the Volta ...

    African Journals Online (AJOL)

    Determinants of Fisher's Choice of Fishing Activity along the Volta Lake in Yeji ... The analysis was done using the Ordered Probit Model and descriptive statistics. ... economic growth, reduce poverty and ensure household food security in Yeji.

  20. Modeling crash injury severity by road feature to improve safety.

    Science.gov (United States)

    Penmetsa, Praveena; Pulugurtha, Srinivas S

    2018-01-02

    The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature. Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity. Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway. The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.

  1. ADDING A NEW STEP WITH SPATIAL AUTOCORRELATION TO IMPROVE THE FOUR-STEP TRAVEL DEMAND MODEL WITH FEEDBACK FOR A DEVELOPING CITY

    Directory of Open Access Journals (Sweden)

    Xuesong FENG, Ph.D Candidate

    2009-01-01

    Full Text Available It is expected that improvement of transport networks could give rise to the change of spatial distributions of population-related factors and car ownership, which are expected to further influence travel demand. To properly reflect such an interdependence mechanism, an aggregate multinomial logit (A-MNL model was firstly applied to represent the spatial distributions of these exogenous variables of the travel demand model by reflecting the influence of transport networks. Next, the spatial autocorrelation analysis is introduced into the log-transformed A-MNL model (called SPA-MNL model. Thereafter, the SPA-MNL model is integrated into the four-step travel demand model with feedback (called 4-STEP model. As a result, an integrated travel demand model is newly developed and named as the SPA-STEP model. Using person trip data collected in Beijing, the performance of the SPA-STEP model is empirically compared with the 4-STEP model. It was proven that the SPA-STEP model is superior to the 4-STEP model in accuracy; most of the estimated parameters showed statistical differences in values. Moreover, though the results of the simulations to the same set of assumed scenarios by the 4-STEP model and the SPA-STEP model consistently suggested the same sustainable path for the future development of Beijing, it was found that the environmental sustainability and the traffic congestion for these scenarios were generally overestimated by the 4-STEP model compared with the corresponding analyses by the SPA-STEP model. Such differences were clearly generated by the introduction of the new modeling step with spatial autocorrelation.

  2. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Science.gov (United States)

    Tokuda, Tomoki; Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  3. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Directory of Open Access Journals (Sweden)

    Tomoki Tokuda

    Full Text Available We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  4. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

    Science.gov (United States)

    Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

  5. Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review.

    Science.gov (United States)

    McClelland, James L

    2013-01-01

    This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.

  6. Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

    KAUST Repository

    Khaki, M.

    2017-07-06

    The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, for the first time, we assess the performance of the most popular data assimilation sequential techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement and test stochastic and deterministic ensemble-based Kalman filters (EnKF), as well as Particle filters (PF) using two different resampling approaches of Multinomial Resampling and Systematic Resampling. These choices provide various opportunities for weighting observations and model simulations during the assimilation and also accounting for error distributions. Particularly, the deterministic EnKF is tested to avoid perturbing observations before assimilation (that is the case in an ordinary EnKF). Gaussian-based random updates in the EnKF approaches likely do not fully represent the statistical properties of the model simulations and TWS observations. Therefore, the fully non-Gaussian PF is also applied to estimate more realistic updates. Monthly GRACE TWS are assimilated into W3RA covering the entire Australia. To evaluate the filters performances and analyze their impact on model simulations, their estimates are validated by independent in-situ measurements. Our results indicate that all implemented filters improve the estimation of water storage simulations of W3RA. The best results are obtained using two versions of deterministic EnKF, i.e. the Square Root Analysis (SQRA) scheme and the Ensemble Square Root Filter (EnSRF), respectively improving the model groundwater estimations errors by 34% and 31% compared to a model run without assimilation. Applying the PF along with Systematic Resampling successfully decreases the model estimation error by 23%.

  7. Contribution of chronic conditions to functional limitations using a multinomial outcome: Results for the older population in Belgium and Brazil

    NARCIS (Netherlands)

    Yokota, R.T.C. (Renata T.C.); W.J. Nusselder (Wilma); J-M. Robine (Jean-Marie); J. Tafforeau (Jean); P. Deboosere (Patrick); Moura, L. (Lenildo); Andrade, S.S.C.A. (Silvânia S.C.A.); Castro, S.S. (Shamyr S.); H. van Oyen (Herman)

    2017-01-01

    textabstractBackground: The global phenomenon of population ageing is creating new challenges in both high and middle income countries, as functional limitations are expected to increase with age. The attribution method has been proposed to identify which conditions contribute most to disability

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

    Science.gov (United States)

    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…

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

    Science.gov (United States)

    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...

  10. How much do incentives affect car purchase? Agent-based microsimulation of consumer choice of new cars-Part I: Model structure, simulation of bounded rationality, and model validation

    International Nuclear Information System (INIS)

    Mueller, Michel G.; Haan, Peter de

    2009-01-01

    This article presents an agent-based microsimulation capable of forecasting the effects of policy levers that influence individual choices of new passenger cars. The fundamental decision-making units are households distinguished by sociodemographic characteristics and car ownership. A two-stage model of individual decision processes is employed. In the first stage, individual choice sets are constructed using simple, non-compensatory rules that are based on previously owned cars. Second, decision makers evaluate alternatives in their individual choice set using a multi-attributive weighting rule. The attribute weights are based on a multinomial logit model for cross-country policy analysis in European countries. Additionally, prospect theory and the notion of mental accounting are used to model the perception of monetary values. The microsimulation forecasts actual market observations with high accuracy, both on the level of aggregate market characteristics as well as on a highly resolved level of distributions of market shares. The presented approach is useful for the assessment of policies that influence individual purchase decisions of new passenger cars; it allows accounting for a highly resolved car fleet and differentiated consumer segments. As a result, the complexity of incentive schemes can be represented and detailed structural changes can be investigated

  11. How much do incentives affect car purchase? Agent-based microsimulation of consumer choice of new cars-Part I: Model structure, simulation of bounded rationality, and model validation

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, Michel G. [ETH Zurich, Institute for Environmental Decisions, Natural and Social Science Interface, Universitaetstr. 22, CHN J 73.2, 8092 Zurich (Switzerland); Haan, Peter de [ETH Zurich, Institute for Environmental Decisions, Natural and Social Science Interface, Universitaetstr. 22, CHN J 73.2, 8092 Zurich (Switzerland)], E-mail: peter.dehaan@env.ethz.ch

    2009-03-15

    This article presents an agent-based microsimulation capable of forecasting the effects of policy levers that influence individual choices of new passenger cars. The fundamental decision-making units are households distinguished by sociodemographic characteristics and car ownership. A two-stage model of individual decision processes is employed. In the first stage, individual choice sets are constructed using simple, non-compensatory rules that are based on previously owned cars. Second, decision makers evaluate alternatives in their individual choice set using a multi-attributive weighting rule. The attribute weights are based on a multinomial logit model for cross-country policy analysis in European countries. Additionally, prospect theory and the notion of mental accounting are used to model the perception of monetary values. The microsimulation forecasts actual market observations with high accuracy, both on the level of aggregate market characteristics as well as on a highly resolved level of distributions of market shares. The presented approach is useful for the assessment of policies that influence individual purchase decisions of new passenger cars; it allows accounting for a highly resolved car fleet and differentiated consumer segments. As a result, the complexity of incentive schemes can be represented and detailed structural changes can be investigated.

  12. Measuring fit of sequence data to phylogenetic model: gain of power using marginal tests.

    Science.gov (United States)

    Waddell, Peter J; Ota, Rissa; Penny, David

    2009-10-01

    Testing fit of data to model is fundamentally important to any science, but publications in the field of phylogenetics rarely do this. Such analyses discard fundamental aspects of science as prescribed by Karl Popper. Indeed, not without cause, Popper (Unended quest: an intellectual autobiography. Fontana, London, 1976) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (Nature 297:197-200, 1982) to the present. We compare the general log-likelihood ratio (the G or G (2) statistic) statistic between the evolutionary tree model and the multinomial model with that of marginalized tests applied to an alignment (using placental mammal coding sequence data). It is seen that the most general test does not reject the fit of data to model (P approximately 0.5), but the marginalized tests do. Tests on pairwise frequency (F) matrices, strongly (P < 0.001) reject the most general phylogenetic (GTR) models commonly in use. It is also clear (P < 0.01) that the sequences are not stationary in their nucleotide composition. Deviations from stationarity and homogeneity seem to be unevenly distributed amongst taxa; not necessarily those expected from examining other regions of the genome. By marginalizing the 4( t ) patterns of the i.i.d. model to observed and expected parsimony counts, that is, from constant sites, to singletons, to parsimony informative characters of a minimum possible length, then the likelihood ratio test regains power, and it too rejects the evolutionary model with P < 0.001. Given such behavior over relatively recent evolutionary time, readers in general should maintain a healthy skepticism of results, as the scale of the systematic errors in published trees may really be far larger than the analytical methods (e.g., bootstrap) report.

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

    OpenAIRE

    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...

  14. The memory state heuristic: A formal model based on repeated recognition judgments.

    Science.gov (United States)

    Castela, Marta; Erdfelder, Edgar

    2017-02-01

    The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e., recognition certainty, uncertainty, or rejection certainty). Specifically, the larger the discrepancy between memory states, the larger the probability of choosing the object in the higher state. The typical RH paradigm does not allow estimation of the underlying memory states because it is unknown whether the objects were previously experienced or not. Therefore, we extended the paradigm by repeating the recognition task twice. In line with high threshold models of recognition, we assumed that inconsistent recognition judgments result from uncertainty whereas consistent judgments most likely result from memory certainty. In Experiment 1, we fitted 2 nested multinomial models to the data: an MSH model that formalizes the relation between memory states and binary choices explicitly and an approximate model that ignores the (unlikely) possibility of consistent guesses. Both models provided converging results. As predicted, reliance on recognition increased with the discrepancy in the underlying memory states. In Experiment 2, we replicated these results and found support for choice consistency predictions of the MSH. Additionally, recognition and choice latencies were in agreement with the MSH in both experiments. Finally, we validated critical parameters of our MSH model through a cross-validation method and a third experiment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  15. Exacerbations of COPD: quantifying the patient's perspective using discrete choice modelling.

    Science.gov (United States)

    Haughney, J; Partridge, M R; Vogelmeier, C; Larsson, T; Kessler, R; Ståhl, E; Brice, R; Löfdahl, C-G

    2005-10-01

    Patient-centred care is the current vogue in chronic obstructive pulmonary disease (COPD), but it is only recently that robust techniques have become available to determine patients' values and preferences. In this international cross-sectional study, patients' concerns and expectations regarding COPD exacerbations were explored using discrete choice modelling. A fractional factorial design was used to develop scenarios comprising a combination of levels for nine different attributes. In face-to-face interviews, patients were presented with paired scenarios and asked to choose the least preferable. Multinomial logit (with hierarchical Bayes) methods were used to estimate utilities. A total of 125 patients (82 males; mean age 66 yrs; 4.6 mean exacerbations.yr-1) were recruited. The attributes of exacerbations considered most important were impact on everyday life (20%), need for medical care (16%), number of future attacks (12%) and breathlessness (11%). The next most important attributes were speed of recovery, productive cough and social impact (all 9%), followed by sleep disturbance and impact on mood (both 7%). Importantly, analysis of utility shifts showed that patients most feared being hospitalised, housebound or bedridden. These issues were more important than symptom improvement. Strategies for the clinical management of chronic obstructive pulmonary disease should clearly address patients' concerns and focus on preventing and treating exacerbations to avoid these feared outcomes.

  16. MODEL PERAWATAN KESEHATAN KESELAMATAN KERJA BERBASIS AGRICULTURAL NURSING: STUDI ANALISIS MASALAH KESEHATAN PETANI

    Directory of Open Access Journals (Sweden)

    Tantut Susanto

    2016-04-01

    Methods: A cross-sectional study of 169 farmers was done to investigate sociodemographic, lifestyles, environment of living and worked, health status and health problem. Data collected by the self administered questionnaire, physical assessment, and blood test. The descriptive and comparative analyses include chi-square tests and ogistic and multinomial regression analyses were used to assess the relationships between factors to the presence of health problems. Results: There was differences between sociodemographic, environment of living and worked and the health problems of farmers (p<0.05. Almost 37.9% of farmers is illness. Among 28.5% of underweight and 9.5% of overweight that related to age, drink of coffe, and excess day of work. 62.6% of anemia that related to gender and smoking habit. Meanwhile, 45.2% of sistolic hypertension and 35.8% diastolic hypertension that caused by worked of overload. Furthermore, 50.3% of pain on join and bone related to age and recess of worked. Discussion: The health problems of farmers was characterized of nutritional problem, anemia, hypertension, and pain that related to sociodemographic environment of biologic, psychologic, and worked. Agricultural nursing model could be develop for assessesment of related factors that formulated diagnoses of health problems on farmers at rural area.

  17. Analysing the Severity and Frequency of Traffic Crashes in Riyadh City Using Statistical Models

    Directory of Open Access Journals (Sweden)

    Saleh Altwaijri

    2012-12-01

    Full Text Available Traffic crashes in Riyadh city cause losses in the form of deaths, injuries and property damages, in addition to the pain and social tragedy affecting families of the victims. In 2005, there were a total of 47,341 injury traffic crashes occurred in Riyadh city (19% of the total KSA crashes and 9% of those crashes were severe. Road safety in Riyadh city may have been adversely affected by: high car ownership, migration of people to Riyadh city, high daily trips reached about 6 million, high rate of income, low-cost of petrol, drivers from different nationalities, young drivers and tremendous growth in population which creates a high level of mobility and transport activities in the city. The primary objective of this paper is therefore to explore factors affecting the severity and frequency of road crashes in Riyadh city using appropriate statistical models aiming to establish effective safety policies ready to be implemented to reduce the severity and frequency of road crashes in Riyadh city. Crash data for Riyadh city were collected from the Higher Commission for the Development of Riyadh (HCDR for a period of five years from 1425H to 1429H (roughly corresponding to 2004-2008. Crash data were classified into three categories: fatal, serious-injury and slight-injury. Two nominal response models have been developed: a standard multinomial logit model (MNL and a mixed logit model to injury-related crash data. Due to a severe underreporting problem on the slight injury crashes binary and mixed binary logistic regression models were also estimated for two categories of severity: fatal and serious crashes. For frequency, two count models such as Negative Binomial (NB models were employed and the unit of analysis was 168 HAIs (wards in Riyadh city. Ward-level crash data are disaggregated by severity of the crash (such as fatal and serious injury crashes. The results from both multinomial and binary response models are found to be fairly consistent but

  18. A comparison of dose-response characteristics of four NTCP models using outcomes of radiation-induced optic neuropathy and retinopathy

    International Nuclear Information System (INIS)

    Moiseenko, Vitali; Song, William Y; Mell, Loren K; Bhandare, Niranjan

    2011-01-01

    Biological models are used to relate the outcome of radiation therapy to dose distribution. As use of biological models in treatment planning expands, uncertainties associated with the use of specific models for predicting outcomes should be understood and quantified. In particular, the question to what extent model predictions are data-driven or dependent on the choice of the model has to be explored. Four dose-response models--logistic, log-logistic, Poisson-based and probit--were tested for their ability and consistency in describing dose-response data for radiation-induced optic neuropathy (RION) and retinopathy (RIRP). Dose to the optic nerves was specified as the minimum dose, D min , received by any segment of the organ to which the damage was diagnosed by ophthalmologic evaluation. For retinopathy, the dose to the retina was specified as the highest isodose covering at least 1/3 of the retinal surface (D 33% ) that geometrically covered the observed retinal damage. Data on both complications were modeled separately for patients treated once daily and twice daily. Model parameters D 50 and γ and corresponding confidence intervals were obtained using maximum-likelihood method. Model parameters were reasonably consistent for RION data for patients treated once daily, D 50 ranging from 94.2 to 104.7 Gy and γ from 0.88 to 1.41. Similar consistency was seen for RIRP data which span a broad range of complication incidence, with D 50 from 72.2 to 75.0 Gy and γ from 1.51 to 2.16 for patients treated twice daily; 72.2-74.0 Gy and 0.84-1.20 for patients treated once daily. However, large variations were observed for RION in patients treated twice daily, D 50 from 96.3 to 125.2 Gy and γ from 0.80 to 1.56. Complication incidence in this dataset in any dose group did not exceed 20%. For the considered data sets, the log-logistic model tends to lead to larger D 50 and lower γ compared to other models for all datasets. Statements regarding normal tissue

  19. Modelling Practice

    DEFF Research Database (Denmark)

    Cameron, Ian; Gani, Rafiqul

    2011-01-01

    This chapter deals with the practicalities of building, testing, deploying and maintaining models. It gives specific advice for each phase of the modelling cycle. To do this, a modelling framework is introduced which covers: problem and model definition; model conceptualization; model data...... requirements; model construction; model solution; model verification; model validation and finally model deployment and maintenance. Within the adopted methodology, each step is discussedthrough the consideration of key issues and questions relevant to the modelling activity. Practical advice, based on many...

  20. Railway and road discrete choice model for foreign trade freight between Antioquia and the Port of Cartagena

    Directory of Open Access Journals (Sweden)

    J. D. Pineda-Jaramillo

    2016-09-01

    Full Text Available Most Colombian freight is transported on roads with barely acceptable conditions, and although there is a speculation about the need for a railway for freight transportation, there is not a study in Colombia showing the variables that influence the modal choice by the companies that generate freight transportation. This article presents the calculation of demand for a hypothetical railway through a discrete choice model. It begins with a qualitative research through focus group techniques to identify the variables that influence the choice of persons responsible for the transportation of large commercial companies in Antioquia (Colombia. The influential variables in the election were the cost and service frequency, and these variables were used to apply a Stated Preference (SP and Revealed Preference (RP survey, then to calibrate a Multinomial Logit Model (MNL, and to estimate the influence of each of them. We show that the probability of railway choice by the studied companies varies between 67% and 93%, depending on differences in these variables.

  1. Genetic parameters for racing records in trotters using linear and generalized linear models.

    Science.gov (United States)

    Suontama, M; van der Werf, J H J; Juga, J; Ojala, M

    2012-09-01

    Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.

  2. How does aging affect recognition-based inference? A hierarchical Bayesian modeling approach.

    Science.gov (United States)

    Horn, Sebastian S; Pachur, Thorsten; Mata, Rui

    2015-01-01

    The recognition heuristic (RH) is a simple strategy for probabilistic inference according to which recognized objects are judged to score higher on a criterion than unrecognized objects. In this article, a hierarchical Bayesian extension of the multinomial r-model is applied to measure use of the RH on the individual participant level and to re-evaluate differences between younger and older adults' strategy reliance across environments. Further, it is explored how individual r-model parameters relate to alternative measures of the use of recognition and other knowledge, such as adherence rates and indices from signal-detection theory (SDT). Both younger and older adults used the RH substantially more often in an environment with high than low recognition validity, reflecting adaptivity in strategy use across environments. In extension of previous analyses (based on adherence rates), hierarchical modeling revealed that in an environment with low recognition validity, (a) older adults had a stronger tendency than younger adults to rely on the RH and (b) variability in RH use between individuals was larger than in an environment with high recognition validity; variability did not differ between age groups. Further, the r-model parameters correlated moderately with an SDT measure expressing how well people can discriminate cases where the RH leads to a correct vs. incorrect inference; this suggests that the r-model and the SDT measures may offer complementary insights into the use of recognition in decision making. In conclusion, younger and older adults are largely adaptive in their application of the RH, but cognitive aging may be associated with an increased tendency to rely on this strategy. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Leadership Models.

    Science.gov (United States)

    Freeman, Thomas J.

    This paper discusses six different models of organizational structure and leadership, including the scalar chain or pyramid model, the continuum model, the grid model, the linking pin model, the contingency model, and the circle or democratic model. Each model is examined in a separate section that describes the model and its development, lists…

  4. Model for screened, charge-regulated electrostatics of an eye lens protein: Bovine gammaB-crystallin

    Science.gov (United States)

    Wahle, Christopher W.; Martini, K. Michael; Hollenbeck, Dawn M.; Langner, Andreas; Ross, David S.; Hamilton, John F.; Thurston, George M.

    2017-09-01

    We model screened, site-specific charge regulation of the eye lens protein bovine gammaB-crystallin (γ B ) and study the probability distributions of its proton occupancy patterns. Using a simplified dielectric model, we solve the linearized Poisson-Boltzmann equation to calculate a 54 ×54 work-of-charging matrix, each entry being the modeled voltage at a given titratable site, due to an elementary charge at another site. The matrix quantifies interactions within patches of sites, including γ B charge pairs. We model intrinsic p K values that would occur hypothetically in the absence of other charges, with use of experimental data on the dependence of p K values on aqueous solution conditions, the dielectric model, and literature values. We use Monte Carlo simulations to calculate a model grand-canonical partition function that incorporates both the work-of-charging and the intrinsic p K values for isolated γ B molecules and we calculate the probabilities of leading proton occupancy configurations, for 4 Debye screening lengths from 6 to 20 Å. We select the interior dielectric value to model γ B titration data. At p H 7.1 and Debye length 6.0 Å, on a given γ B molecule the predicted top occupancy pattern is present nearly 20% of the time, and 90% of the time one or another of the first 100 patterns will be present. Many of these occupancy patterns differ in net charge sign as well as in surface voltage profile. We illustrate how charge pattern probabilities deviate from the multinomial distribution that would result from use of effective p K values alone and estimate the extents to which γ B charge pattern distributions broaden at lower p H and narrow as ionic strength is lowered. These results suggest that for accurate modeling of orientation-dependent γ B -γ B interactions, consideration of numerous pairs of proton occupancy patterns will be needed.

  5. Models and role models.

    Science.gov (United States)

    ten Cate, Jacob M

    2015-01-01

    Developing experimental models to understand dental caries has been the theme in our research group. Our first, the pH-cycling model, was developed to investigate the chemical reactions in enamel or dentine, which lead to dental caries. It aimed to leverage our understanding of the fluoride mode of action and was also utilized for the formulation of oral care products. In addition, we made use of intra-oral (in situ) models to study other features of the oral environment that drive the de/remineralization balance in individual patients. This model addressed basic questions, such as how enamel and dentine are affected by challenges in the oral cavity, as well as practical issues related to fluoride toothpaste efficacy. The observation that perhaps fluoride is not sufficiently potent to reduce dental caries in the present-day society triggered us to expand our knowledge in the bacterial aetiology of dental caries. For this we developed the Amsterdam Active Attachment biofilm model. Different from studies on planktonic ('single') bacteria, this biofilm model captures bacteria in a habitat similar to dental plaque. With data from the combination of these models, it should be possible to study separate processes which together may lead to dental caries. Also products and novel agents could be evaluated that interfere with either of the processes. Having these separate models in place, a suggestion is made to design computer models to encompass the available information. Models but also role models are of the utmost importance in bringing and guiding research and researchers. 2015 S. Karger AG, Basel

  6. Model(ing) Law

    DEFF Research Database (Denmark)

    Carlson, Kerstin

    The International Criminal Tribunal for the former Yugoslavia (ICTY) was the first and most celebrated of a wave of international criminal tribunals (ICTs) built in the 1990s designed to advance liberalism through international criminal law. Model(ing) Justice examines the case law of the ICTY...

  7. Models and role models

    NARCIS (Netherlands)

    ten Cate, J.M.

    2015-01-01

    Developing experimental models to understand dental caries has been the theme in our research group. Our first, the pH-cycling model, was developed to investigate the chemical reactions in enamel or dentine, which lead to dental caries. It aimed to leverage our understanding of the fluoride mode of

  8. Application of economic models to estimate the acceptability of a vehicle congestion charge

    Directory of Open Access Journals (Sweden)

    José Carlos Jiménez Serpa

    2017-07-01

    Full Text Available Introduction: Through the study of the problems generated by vehicular traffic congestion during periods of maximum demand, the negative externality of congestion would be assessed using Multinomial Logit, Mixed and econometric models, and willingness to pay through a Pigouvian rate. Objective: In this article, we propose to implement a congestion charge to manage vehicular demand, through the application of declared preference gages and econometric models. Methodology: The study consists of the execution of 6 steps or stages: Background of the problem, Context of study, Methodological Foundations, Specification and estimation of the model, Estimation of the function average cost user and social marginal cost, Results obtained Discussion and report. Results: Analyzing the models obtained from the 2053 observations made through the declared preference surveys, it was observed that in order to discourage the use of the private car, a rate of COP 7000 per vehicle entering the congestion area or area should be charged, which would decrease the Use of Auto Particular in 68.7%, referring to this behavior we can say that the government policies that set the collection of the congestion charge is a policy that does not fit the perception of the users. Conclusions: This research identified the rate that reflects as closely as possible the marginal social cost and the generalized costs of each trip in terms of the impacts on the others. Now if we consider the marginal cost due to congestion, we have that the current demand is excessive, the users enjoy the benefit at a cost of $ 3,100COP, but impose to others a quota of $22,152COP. Finally, it is necessary to strengthen the legal basis with the regulation and creation of a National Vehicle Electronic Identification System, which will allow, in principle, charges for congestion.

  9. A new social-family model for eating disorders: A European multicentre project using a case-control design.

    Science.gov (United States)

    Krug, Isabel; Fuller-Tyszkiewicz, Matthew; Anderluh, Marija; Bellodi, Laura; Bagnoli, Silvia; Collier, David; Fernandez-Aranda, Fernando; Karwautz, Andreas; Mitchell, Sarah; Nacmias, Benedetta; Ricca, Valdo; Sorbi, Sandro; Tchanuria, Kate; Wagner, Gudrun; Treasure, Janet; Micali, Nadia

    2015-12-01

    To examine a new socio-family risk model of Eating Disorders (EDs) using path-analyses. The sample comprised 1264 (ED patients = 653; Healthy Controls = 611) participants, recruited into a multicentre European project. Socio-family factors assessed included: perceived maternal and parental parenting styles, family, peer and media influences, and body dissatisfaction. Two types of path-analyses were run to assess the socio-family model: 1.) a multinomial logistic path-model including ED sub-types [Anorexia Nervosa-Restrictive (AN-R), AN-Binge-Purging (AN-BP), Bulimia Nervosa (BN) and EDNOS)] as the key polychotomous categorical outcome and 2.) a path-model assessing whether the socio-family model differed across ED sub-types and healthy controls using body dissatisfaction as the outcome variable. The first path-analyses suggested that family and media (but not peers) were directly and indirectly associated (through body dissatisfaction) with all ED sub-types. There was a weak effect of perceived parenting directly on ED sub-types and indirectly through family influences and body dissatisfaction. For the second path-analyses, the socio-family model varied substantially across ED sub-types. Family and media influences were related to body dissatisfaction in the EDNOS and control sample, whereas perceived abusive parenting was related to AN-BP and BN. This is the first study providing support for this new socio-family model, which differed across ED sub-types. This suggests that prevention and early intervention might need to be tailored to diagnosis-specific ED profiles. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

    Science.gov (United States)

    Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

    2018-01-01

    Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

  11. Seeking treatment for symptomatic malaria in Papua New Guinea

    Directory of Open Access Journals (Sweden)

    Siba Peter

    2010-10-01

    Full Text Available Abstract Background Malaria places a significant burden on the limited resources of many low income countries. Knowing more about why and where people seek treatment will enable policy makers to better allocate the limited resources. This study aims to better understand what influences treatment-seeking behaviour for malaria in one such low-income country context, Papua New Guinea (PNG. Methods Two culturally, linguistically and demographically different regions in PNG were selected as study sites. A cross sectional household survey was undertaken in both sites resulting in the collection of data on 928 individuals who reported suffering from malaria in the previous four weeks. A probit model was then used to identify the factors determining whether or not people sought treatment for presumptive malaria. Multinomial logit models also assisted in identifying the factors that determined where people sought treatments. Results Results in this study build upon findings from other studies. For example, while distance in PNG has previously been seen as the primary factor in influencing whether any sort of treatment will be sought, in this study cultural influences and whether it was the first, second or even third treatment for a particular episode of malaria were also important. In addition, although formal health care facilities were the most popular treatment sources, it was also found that traditional healers were a common choice. In turn, the reasons why participants chose a particular type of treatment differed according to the whether they were seeking an initial or subsequent treatments. Conclusions Simply bringing health services closer to where people live may not always result in a greater use of formal health care facilities. Policy makers in PNG need to consider within-country variation in treatment-seeking behaviour, the important role of traditional healers and also ensure that the community fully understands the potential implications

  12. The effective effect-site propofol concentration for induction and intubation with two pharmacokinetic models in morbidly obese patients using total body weight.

    Science.gov (United States)

    Echevarría, Ghislaine C; Elgueta, María F; Donoso, María T; Bugedo, Diego A; Cortínez, Luis I; Muñoz, Hernán R

    2012-10-01

    Most pharmacokinetic (PK) models used for propofol administration are based on studies in normal-weight patients. Extrapolation of these models for morbidly obese patients is controversial. Using 2 PK models and a target-controlled infusion system, we determined the predicted propofol effect-site concentration (Ce) needed for induction of anesthesia in morbidly obese subjects using total body weight. Sixty-six morbidly obese subjects from 18 to 50 years of age were randomized to receive propofol to reach and maintain a predetermined propofol Ce, based on the PK models of either Marsh or Schnider. All patients were monitored with a Bispectral Index electroencephalographic monitor. Fentanyl 3 μg/kg total body weight was administered before starting the propofol infusion. After loss of consciousness, vecuronium was administered to facilitate endotracheal intubation. Groups of 6 patients each received propofol at a different, predetermined target propofol Ce. An "effective Ce" (ECe) was defined as the propofol Ce that provided adequate hypnosis (Bispectral Index <60) during the complete induction period (45 seconds after reaching the predetermined target Ce until 5 minutes after tracheal intubation). Heart rate and arterial blood pressure were measured every 1 minute throughout the study period. Probit regression analysis was performed to calculate the effective propofol Ce values to induce hypnosis in 50% (ECe(50)) and 95% (ECe(95)) of patients with 95% confidence intervals (CIs). Patient characteristics were similar between models and across the propofol target concentration groups. The ECe(50) of propofol was 3.4 μg/mL (95% CI: 2.9, 3.7 μg/mL) with the Marsh model and 4.5 μg/mL (95% CI: 4.1, 4.8 μg/mL) with the Schnider model (P < 0.001). The ECe(95) values were 4.2 μg/mL (95% CI: 3.8, 6.2 μg/mL) and 5.5 μg/mL (95% CI: 5.0, 7.2 μg/mL) with Marsh and Schnider models, respectively. At the ECe(95), hemodynamic effects were similar with the 2 PK models

  13. Models for predicting objective function weights in prostate cancer IMRT

    International Nuclear Information System (INIS)

    Boutilier, Justin J.; Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.

    2015-01-01

    Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

  14. Models for predicting objective function weights in prostate cancer IMRT

    Energy Technology Data Exchange (ETDEWEB)

    Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Craig, Tim [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Sharpe, Michael B. [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)

    2015-04-15

    Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

  15. A realistic closed-form radiobiological model of clinical tumor-control data incorporating intertumor heterogeneity

    International Nuclear Information System (INIS)

    Roberts, Stephen A.; Hendry, Jolyon H.

    1998-01-01

    Purpose: To investigate the role of intertumor heterogeneity in clinical tumor control datasets and the relationship to in vitro measurements of tumor biopsy samples. Specifically, to develop a modified linear-quadratic (LQ) model incorporating such heterogeneity that it is practical to fit to clinical tumor-control datasets. Methods and Materials: We developed a modified version of the linear-quadratic (LQ) model for tumor control, incorporating a (lagged) time factor to allow for tumor cell repopulation. We explicitly took into account the interpatient heterogeneity in clonogen number, radiosensitivity, and repopulation rate. Using this model, we could generate realistic TCP curves using parameter estimates consistent with those reported from in vitro studies, subject to the inclusion of a radiosensitivity (or dose)-modifying factor. We then demonstrated that the model was dominated by the heterogeneity in α (tumor radiosensitivity) and derived an approximate simplified model incorporating this heterogeneity. This simplified model is expressible in a compact closed form, which it is practical to fit to clinical datasets. Using two previously analysed datasets, we fit the model using direct maximum-likelihood techniques and obtained parameter estimates that were, again, consistent with the experimental data on the radiosensitivity of primary human tumor cells. This heterogeneity model includes the same number of adjustable parameters as the standard LQ model. Results: The modified model provides parameter estimates that can easily be reconciled with the in vitro measurements. The simplified (approximate) form of the heterogeneity model is a compact, closed-form probit function that can readily be fitted to clinical series by conventional maximum-likelihood methodology. This heterogeneity model provides a slightly better fit to the datasets than the conventional LQ model, with the same numbers of fitted parameters. The parameter estimates of the clinically

  16. Avaliação de um modelo de predição para apneia do sono em pacientes submetidos a polissonografia Evaluation of a prediction model for sleep apnea in patients submitted to polysomnography

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    Silvio Musman

    2011-02-01

    Full Text Available OBJETIVO: Testar um modelo de predição para apneia do sono a partir de variáveis sociodemográficas e clínicas em uma população com suspeita de distúrbio do sono e submetida à polissonografia. MÉTODOS: Foram incluídos no estudo 323 pacientes consecutivos submetidos à polissonografia por suspeita clínica de distúrbio do sono. Utilizou-se um questionário com questões sociodemográficas e a escala de sonolência de Epworth. Foram medidos pressão arterial, peso, altura e SpO2. A regressão linear múltipla, tendo o índice de apneia-hipopneia (IAH como variável dependente, foi utilizada para construir um modelo de predição de apneia do sono. A regressão logística multinomial foi realizada para verificar fatores associados de forma independente à gravidade da apneia (leve, moderada ou grave em comparação à ausência de apneia. RESULTADOS: A prevalência de apneia do sono na população de estudo foi de 71,2%, e foi mais prevalente nos homens que nas mulheres (81,2% vs. 56,8%; p OBJECTIVE: To test a prediction model for sleep apnea based on clinical and sociodemographic variables in a population suspected of having sleep disorders and submitted to polysomnography. METHODS: We included 323 consecutive patients submitted to polysomnography because of the clinical suspicion of having sleep disorders. We used a questionnaire with sociodemographic questions and the Epworth sleepiness scale. Blood pressure, weight, height, and SpO2 were measured. Multiple linear regression was used in order to create a prediction model for sleep apnea, the apnea-hypopnea index (AHI being the dependent variable. Multinomial logistic regression was used in order to identify factors independently associated with the severity of apnea (mild, moderate, or severe in comparison with the absence of apnea. RESULTS: The prevalence of sleep apnea in the study population was 71.2%. Sleep apnea was more prevalent in men than in women (81.2% vs. 56.8%; p < 0

  17. Modelling SDL, Modelling Languages

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    Michael Piefel

    2007-02-01

    Full Text Available Today's software systems are too complex to implement them and model them using only one language. As a result, modern software engineering uses different languages for different levels of abstraction and different system aspects. Thus to handle an increasing number of related or integrated languages is the most challenging task in the development of tools. We use object oriented metamodelling to describe languages. Object orientation allows us to derive abstract reusable concept definitions (concept classes from existing languages. This language definition technique concentrates on semantic abstractions rather than syntactical peculiarities. We present a set of common concept classes that describe structure, behaviour, and data aspects of high-level modelling languages. Our models contain syntax modelling using the OMG MOF as well as static semantic constraints written in OMG OCL. We derive metamodels for subsets of SDL and UML from these common concepts, and we show for parts of these languages that they can be modelled and related to each other through the same abstract concepts.

  18. Empirical Analysis and Modeling of Stop-Line Crossing Time and Speed at Signalized Intersections

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    Keshuang Tang

    2016-12-01

    Full Text Available In China, a flashing green (FG indication of 3 s followed by a yellow (Y indication of 3 s is commonly applied to end the green phase at signalized intersections. Stop-line crossing behavior of drivers during such a phase transition period significantly influences safety performance of signalized intersections. The objective of this study is thus to empirically analyze and model drivers’ stop-line crossing time and speed in response to the specific phase transition period of FG and Y. High-resolution trajectories for 1465 vehicles were collected at three rural high-speed intersections with a speed limit of 80 km/h and two urban intersections with a speed limit of 50 km/h in Shanghai. With the vehicle trajectory data, statistical analyses were performed to look into the general characteristics of stop-line crossing time and speed at the two types of intersections. A multinomial logit model and a multiple linear regression model were then developed to predict the stop-line crossing patterns and speeds respectively. It was found that the percentage of stop-line crossings during the Y interval is remarkably higher and the stop-line crossing time is approximately 0.7 s longer at the urban intersections, as compared with the rural intersections. In addition, approaching speed and distance to the stop-line at the onset of FG as well as area type significantly affect the percentages of stop-line crossings during the FG and Y intervals. Vehicle type and stop-line crossing pattern were found to significantly influence the stop-line crossing speed, in addition to the above factors. The red-light-running seems to occur more frequently at the large intersections with a long cycle length.

  19. Systems with Many Degrees of Freedom: from Mean - Theories of Non-Fermi Liquid Behavior in Impurity Models to Implied Binomial Trees for Modeling Financial Markets

    Science.gov (United States)

    Barle, Stanko

    In this dissertation, two dynamical systems with many degrees of freedom are analyzed. One is the system of highly correlated electrons in the two-impurity Kondo problem. The other deals with building a realistic model of diffusion underlying financial markets. The simplest mean-field theory capable of mimicking the non-Fermi liquid behavior of the critical point in the two-impurity Kondo problem is presented. In this approach Landau's adiabaticity assumption--of a one-to-one correspondence between the low-energy excitations of the interacting and noninteracting systems--is violated through the presence of decoupled local degrees of freedom. These do not couple directly to external fields but appear indirectly in the physical properties leading, for example, to the log(T, omega) behavior of the staggered magnetic susceptibility. Also, as observed previously, the correlation function = -1/4 is a consequence of the equal weights of the singlet and triplet impurity configurations at the critical point. In the second problem, a numerical model is developed to describe the diffusion of prices in the market. Implied binomial (or multinomial) trees are constructed to enable practical pricing of derivative securities in consistency with the existing market. The method developed here is capable of accounting for both the strike price and term structure of the implied volatility. It includes the correct treatment of interest rate and dividends which proves robust even if these quantities are unusually large. The method is explained both as a set of individual innovations and, from a different prospective, as a consequence of a single plausible transformation from the tree of spot prices to the tree of futures prices.

  20. Determinantes de la participación laboral femenina en Venezuela: Aplicación de un modelo probit para el año 2005

    OpenAIRE

    Martínez, Ángel

    2010-01-01

    La participación laboral de la mujer es un tema de análisis en muchos estudios a nivel mundial, cuyo objetivo es presentar un panorama acerca de la igualdad de género en el empleo. La oferta y la demanda en el mercado de trabajo es el resultado de la interacción de variables principalmente sociales y económicas que se encuentran interconectadas. Este trabajo realiza un análisis conjunto de los determinantes de la participación laboral femenina en Venezuela. También analiza los determinantes d...

  1. Modelling the models

    CERN Multimedia

    Anaïs Schaeffer

    2012-01-01

    By analysing the production of mesons in the forward region of LHC proton-proton collisions, the LHCf collaboration has provided key information needed to calibrate extremely high-energy cosmic ray models.   Average transverse momentum (pT) as a function of rapidity loss ∆y. Black dots represent LHCf data and the red diamonds represent SPS experiment UA7 results. The predictions of hadronic interaction models are shown by open boxes (sibyll 2.1), open circles (qgsjet II-03) and open triangles (epos 1.99). Among these models, epos 1.99 shows the best overall agreement with the LHCf data. LHCf is dedicated to the measurement of neutral particles emitted at extremely small angles in the very forward region of LHC collisions. Two imaging calorimeters – Arm1 and Arm2 – take data 140 m either side of the ATLAS interaction point. “The physics goal of this type of analysis is to provide data for calibrating the hadron interaction models – the well-known &...

  2. Multi-disciplinary decision making in general practice.

    Science.gov (United States)

    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.

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

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    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.

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

    Science.gov (United States)

    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.

  5. Vocational and General Education of Girls and Boys in Tunisia: The Effects of Income and Parental Education

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    Mohamed Siala

    2014-05-01

    Full Text Available Throughout Tunisia, basic education is compulsory. Children are required to enroll for at least 9 years from age 6. This paper examines gender differences in education choice of upper basic education of youths aged 15–24 in Tunisia. To investigate the factors that influence an individual’s choice between vocational education, general education (secondary and high education and leaving school, the paper estimates a multinomial probit model of education choice. We focus on the impact of household income, parental education, sector of economic activity of father, household size, urban location and region of residence on investments in children. These issues are addressed using data from the 2010 National PopulationEmployment Survey that provided information on educational attainment and vocational training of more than 55,000 youths aged 15-24. The findings of this paper suggest that there are gender differences in education choice. Increases in permanent income contribute more to the probabilities of the two types of education of girls than of boys. Parental education has a positive significant effect on their attitudes towards children education and the impact of mother’s higher education was more important for the education of boys than of girls. While, father’s coefficient estimates show the relative benefit to girls general education. Children whose fathers work in agriculture are at disadvantage. The negative effect on girls’ education was larger than on boys’ at the two streams of education. The coefficient estimates on the manufacturing sector increase the probabilities of receiving general education and decrease the probabilities of undertaking vocational education for both girls and boys.

  6. The effects of a subpsychotic dose of ketamine on recognition and source memory for agency: implications for pharmacological modelling of core symptoms of schizophrenia.

    Science.gov (United States)

    Honey, Garry D; O'loughlin, Chris; Turner, Danielle C; Pomarol-Clotet, Edith; Corlett, Philip R; Fletcher, Paul C

    2006-02-01

    Ketamine is increasingly used to model the cognitive deficits and symptoms of schizophrenia. We investigated the extent to which ketamine administration in healthy volunteers reproduces the deficits in episodic recognition memory and agency source monitoring reported in schizophrenia. Intravenous infusions of placebo or 100 ng/ml ketamine were administered to 12 healthy volunteers in a double-blind, placebo-controlled, randomized, within-subjects study. In response to presented words, the subject or experimenter performed a deep or shallow encoding task, providing a 2(drug) x 2(depth of processing) x 2(agency) factorial design. At test, subjects discriminated old/new words, and recalled the sources (task and agent). Data were analyzed using multinomial modelling to identify item recognition, source memory for agency and task, and guessing biases. Under ketamine, item recognition and cued recall of deeply encoded items were impaired, replicating previous findings. In contrast to schizophrenia, there was a reduced tendency to externalize agency source guessing biases under ketamine. While the recognition memory deficit observed with ketamine is consistent with previous work and with schizophrenia, the changes in source memory differ from those reported in schizophrenic patients. This difference may account for the pattern of psychopathology induced by ketamine.

  7. Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model.

    Science.gov (United States)

    Islam, Mohammad Mafijul; Alam, Morshed; Tariquzaman, Md; Kabir, Mohammad Alamgir; Pervin, Rokhsona; Begum, Munni; Khan, Md Mobarak Hossain

    2013-01-08

    Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance variable namely mother's education, father's education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh.

  8. Thermal niche for in situ seed germination by Mediterranean mountain streams: model prediction and validation for Rhamnus persicifolia seeds

    Science.gov (United States)

    Porceddu, Marco; Mattana, Efisio; Pritchard, Hugh W.; Bacchetta, Gianluigi

    2013-01-01

    Background and Aims Mediterranean mountain species face exacting ecological conditions of rainy, cold winters and arid, hot summers, which affect seed germination phenology. In this study, a soil heat sum model was used to predict field emergence of Rhamnus persicifolia, an endemic tree species living at the edge of mountain streams of central eastern Sardinia. Methods Seeds were incubated in the light at a range of temperatures (10–25 and 25/10 °C) after different periods (up to 3 months) of cold stratification at 5 °C. Base temperatures (Tb), and thermal times for 50 % germination (θ50) were calculated. Seeds were also buried in the soil in two natural populations (Rio Correboi and Rio Olai), both underneath and outside the tree canopy, and exhumed at regular intervals. Soil temperatures were recorded using data loggers and soil heat sum (°Cd) was calculated on the basis of the estimated Tb and soil temperatures. Key Results Cold stratification released physiological dormancy (PD), increasing final germination and widening the range of germination temperatures, indicative of a Type 2 non-deep PD. Tb was reduced from 10·5 °C for non-stratified seeds to 2·7 °C for seeds cold stratified for 3 months. The best thermal time model was obtained by fitting probit germination against log °Cd. θ50 was 2·6 log °Cd for untreated seeds and 2·17–2·19 log °Cd for stratified seeds. When θ50 values were integrated with soil heat sum estimates, field emergence was predicted from March to April and confirmed through field observations. Conclusions Tb and θ50 values facilitated model development of the thermal niche for in situ germination of R. persicifolia. These experimental approaches may be applied to model the natural regeneration patterns of other species growing on Mediterranean mountain waterways and of physiologically dormant species, with overwintering cold stratification requirement and spring germination. PMID:24201139

  9. Modeling the Travel Behavior Impacts of Micro-Scale Land Use and Socio-Economic Factors

    Directory of Open Access Journals (Sweden)

    Houshmand Ebrahimpour Masoumi

    2013-06-01

    Full Text Available The effects of neighborhood-level land use characteristics on urban travel behavior of Iranian cities are under-researched. The present paper examines such influences in a microscopic scale. In this study the role of socio-economic factors is also studies and compared to that of urban form. Two case-study neighborhoods in west of Tehran are selected and considered, first of which is a centralized and compact neighborhood and the other is a sprawled and centerless one. A Multinomial Logit Regression model is developed to consider the effects of socio-economic and land use factors on urban travel pattern. In addition, to consider the effective factors, cross-sectional comparison between the influences of local accessibility and attractiveness of the neighborhood centers of the two case-study areas are undertaken. Also the causality relationships are considered according to the findings of the survey. The findings indicate significant effects of age and household income as socio-economic factors on transportation mode choice in neighborhoods with central structure. One the other hand, no meaningful association between socio-economic or land use variables are resulted by the model for the sprawled case. The most effective land use concept in micro-scale is considered to be satisfaction of entertainment facilities of the neighborhood. Also the descriptive findings show that the centralized neighborhood that gives more local accessibility to shops and retail generates less shopping trips. In considering the causal relations, the study shows that providing neighborhood infrastructures that increase or ease the accessibility to neighborhood amenities can lead to higher shares of sustainable transportation modes like walking, biking, or public transportation use.

  10. Development of a Multivariate Prediction Model for Early-Onset Bronchiolitis Obliterans Syndrome and Restrictive Allograft Syndrome in Lung Transplantation

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    Angela Koutsokera

    2017-07-01

    Full Text Available BackgroundChronic lung allograft dysfunction and its main phenotypes, bronchiolitis obliterans syndrome (BOS and restrictive allograft syndrome (RAS, are major causes of mortality after lung transplantation (LT. RAS and early-onset BOS, developing within 3 years after LT, are associated with particularly inferior clinical outcomes. Prediction models for early-onset BOS and RAS have not been previously described.MethodsLT recipients of the French and Swiss transplant cohorts were eligible for inclusion in the SysCLAD cohort if they were alive with at least 2 years of follow-up but less than 3 years, or if they died or were retransplanted at any time less than 3 years. These patients were assessed for early-onset BOS, RAS, or stable allograft function by an adjudication committee. Baseline characteristics, data on surgery, immunosuppression, and year-1 follow-up were collected. Prediction models for BOS and RAS were developed using multivariate logistic regression and multivariate multinomial analysis.ResultsAmong patients fulfilling the eligibility criteria, we identified 149 stable, 51 BOS, and 30 RAS subjects. The best prediction model for early-onset BOS and RAS included the underlying diagnosis, induction treatment, immunosuppression, and year-1 class II donor-specific antibodies (DSAs. Within this model, class II DSAs were associated with BOS and RAS, whereas pre-LT diagnoses of interstitial lung disease and chronic obstructive pulmonary disease were associated with RAS.ConclusionAlthough these findings need further validation, results indicate that specific baseline and year-1 parameters may serve as predictors of BOS or RAS by 3 years post-LT. Their identification may allow intervention or guide risk stratification, aiming for an individualized patient management approach.

  11. Multiple-Strain Approach and Probabilistic Modeling of Consumer Habits in Quantitative Microbial Risk Assessment: A Quantitative Assessment of Exposure to Staphylococcal Enterotoxin A in Raw Milk.

    Science.gov (United States)

    Crotta, Matteo; Rizzi, Rita; Varisco, Giorgio; Daminelli, Paolo; Cunico, Elena Cosciani; Luini, Mario; Graber, Hans Ulrich; Paterlini, Franco; Guitian, Javier

    2016-03-01

    Quantitative microbial risk assessment (QMRA) models are extensively applied to inform management of a broad range of food safety risks. Inevitably, QMRA modeling involves an element of simplification of the biological process of interest. Two features that are frequently simplified or disregarded are the pathogenicity of multiple strains of a single pathogen and consumer behavior at the household level. In this study, we developed a QMRA model with a multiple-strain approach and a consumer phase module (CPM) based on uncertainty distributions fitted from field data. We modeled exposure to staphylococcal enterotoxin A in raw milk in Lombardy; a specific enterotoxin production module was thus included. The model is adaptable and could be used to assess the risk related to other pathogens in raw milk as well as other staphylococcal enterotoxins. The multiplestrain approach, implemented as a multinomial process, allowed the inclusion of variability and uncertainty with regard to pathogenicity at the bacterial level. Data from 301 questionnaires submitted to raw milk consumers were used to obtain uncertainty distributions for the CPM. The distributions were modeled to be easily updatable with further data or evidence. The sources of uncertainty due to the multiple-strain approach and the CPM were identified, and their impact on the output was assessed by comparing specific scenarios to the baseline. When the distributions reflecting the uncertainty in consumer behavior were fixed to the 95th percentile, the risk of exposure increased up to 160 times. This reflects the importance of taking into consideration the diversity of consumers' habits at the household level and the impact that the lack of knowledge about variables in the CPM can have on the final QMRA estimates. The multiple-strain approach lends itself to use in other food matrices besides raw milk and allows the model to better capture the complexity of the real world and to be capable of geographical

  12. Advances in nonmarket valuation econometrics: Spatial heterogeneity in hedonic pricing models and preference heterogeneity in stated preference models

    Science.gov (United States)

    Yoo, Jin Woo

    In my 1st essay, the study explores Pennsylvania residents. willingness to pay for development of renewable energy technologies such as solar power, wind power, biomass electricity, and other renewable energy using a choice experiment method. Principle component analysis identified 3 independent attitude components that affect the variation of preference, a desire for renewable energy and environmental quality and concern over cost. The results show that urban residents have a higher desire for environmental quality and concern less about cost than rural residents and consequently have a higher willingness to pay to increase renewable energy production. The results of sub-sample analysis show that a representative respondent in rural (urban) Pennsylvania is willing to pay 3.8(5.9) and 4.1(5.7)/month for increasing the share of Pennsylvania electricity generated from wind power and other renewable energy by 1 percent point, respectively. Mean WTP for solar and biomass electricity was not significantly different from zero. In my second essay, heterogeneity of individual WTP for various renewable energy technologies is investigated using several different variants of the multinomial logit model: a simple MNL with interaction terms, a latent class choice model, a random parameter mixed logit choice model, and a random parameter-latent class choice model. The results of all models consistently show that respondents. preference for individual renewable technology is heterogeneous, but the degree of heterogeneity differs for different renewable technologies. In general, the random parameter logit model with interactions and a hybrid random parameter logit-latent class model fit better than other models and better capture respondents. heterogeneity of preference for renewable energy. The impact of the land under agricultural conservation easement (ACE) contract on the values of nearby residential properties is investigated using housing sales data in two Pennsylvania

  13. A predictive model for the utilization of curative ambulatory health services in Mexico Un modelo predictivo de la utilización de servicios de salud ambulatorios curativos en México

    Directory of Open Access Journals (Sweden)

    Atanacio Valencia-Mendoza

    2008-10-01

    Full Text Available OBJECTIVES: To estimate the degree to which individual and household variables jointly predict utilization of curative ambulatory services in Mexico for four types of health providers. MATERIAL AND METHODS: Patient choice of provider (self-care, Ministry of Health, social security, or private provider when they become ill is modeled using a nested multinomial logit model that uses household and individual variables as predictors. The data are from the Mexican National Health Survey conducted in 2000. RESULTS: Being a social security beneficiary is one of the most important predictors of utilization. A strong positive relationship between socio-economic status (SES and demand for services was also found, with the strongest relationship being for private providers, followed by social security. Utilization of Ministry of Health (MoH services was negatively associated with household SES. CONCLUSIONS: Expansion of health insurance coverage should significantly reduce health inequalities due to reduced care-seeking by non-beneficiaries.OBJETIVO: Estimar el grado en el cual variables individuales, del hogar y comunitarias predicen la utilización de servicios ambulatorios curativos en México. MATERIAL Y MÉTODOS: Ante un problema de salud los individuos pueden elegir utilizar servicios médicos, servicios de la Secretaría de Salud (SSa, de la Seguridad Social (SS o Privados (SP. Esta elección es modelada con datos de la ENSA 2000 mediante un modelo logístico multinomial anidado. RESULTADOS: El predictor más importante de la utilización de servicios de salud fue la derechohabiencia a la SS. Se encontró una fuerte relación positiva entre estatus socioeconómico (ESE y la utilización de servicios de salud. Dicha relación es mayor para la utilización de SP, seguida de la SS. Se encontró una relación negativa entre el ESE y la utilización de servicios de la SSa. CONCLUSIÓN: Expandir la cobertura de aseguramiento reduciría significativamente

  14. Ambiente sonoro e percezione di alcune caratteristiche dei parchi urbani: analisi e modelli - Sonic environment and perception of some features of urban parks: analysis and models

    Directory of Open Access Journals (Sweden)

    Giovanni Brambilla

    2016-07-01

    Full Text Available Sui dati raccolti in otto parchi urbani, comprendenti alcuni parametri acustici e le valutazioni dei fruitori sulla qualità complessiva del parco percepita e di alcune sue caratteristiche, si è proceduto a diverse analisi statistiche. L’analisi delle componenti principali e quella cluster gerarchica sui dati acustici ha fornito una classificazione in tre gruppi risultata poco sovrapponibile a quella ottenuta con l’analisi cluster e delle corrispondenze multiple condotta sui responsi soggettivi. La discrepanza, confermata anche da alcuni modelli di regressione logistica multinomiale, evidenzia l’influenza di altri fattori non acustici sulla percezione dell’ambiente dei parchi urbani. ------ Different statistical analyses have been carried out on data collected in eight urban parks, including some acoustical parameters and the appraisals of park visitors on the perceived overall quality of the park and some of its features. Principal component analysis and hierarchical cluster one on the acoustic data have identified three groups. This classification poorly overlaps that obtained by hierarchical cluster analysis and multiple correspondence one performed on subjective appraisals data. The difference, confirmed also by models developed by multinomial logistic regression, points out the influence of other non-acoustic factors on the perception of the urban parks environment.

  15. Com obtenir un Model de Regressió Logística Binària amb SPSS

    Directory of Open Access Journals (Sweden)

    Vanesa Berlanga-Silvente

    2014-04-01

    Full Text Available Els models de regressió logística són models estadístics en què es desitja conèixer la relació entre: una variable dependent qualitativa dicotòmica (regressió logística binària o binomial i una o més variables explicatives independents, o covariables, ja siguin qualitatives o quantitatives. També és possible una variable dependent qualitativa amb més de dos valors (regressió logística multinomial, encara que en aquesta fitxa ens centrarem en la regressió logística binària. En qualsevol cas, l'equació inicial del model és de tipus exponencial, si bé la seva transformació logarítmica (logit permet el seu ús com una funció lineal. L'objectiu primordial que resol aquesta tècnica és el de modelar com influeixen la probabilitat d'aparició d'un succés, habitualment dicotòmic, la presència o no de diversos factors, i el valor o nivell dels mateixos. Aquesta fitxa sobre la Regressió Logística Binària explica les opcions que té el programa estadístic SPSS (mètodes automàtics "per passos" i la interpretació dels principals resultats.

  16. Modelling Overview

    DEFF Research Database (Denmark)

    Larsen, Lars Bjørn; Vesterager, Johan

    This report provides an overview of the existing models of global manufacturing, describes the required modelling views and associated methods and identifies tools, which can provide support for this modelling activity.The model adopted for global manufacturing is that of an extended enterprise s...

  17. Document Models

    Directory of Open Access Journals (Sweden)

    A.A. Malykh

    2017-08-01

    Full Text Available In this paper, the concept of locally simple models is considered. Locally simple models are arbitrarily complex models built from relatively simple components. A lot of practically important domains of discourse can be described as locally simple models, for example, business models of enterprises and companies. Up to now, research in human reasoning automation has been mainly concentrated around the most intellectually intensive activities, such as automated theorem proving. On the other hand, the retailer business model is formed from ”jobs”, and each ”job” can be modelled and automated more or less easily. At the same time, the whole retailer model as an integrated system is extremely complex. In this paper, we offer a variant of the mathematical definition of a locally simple model. This definition is intended for modelling a wide range of domains. Therefore, we also must take into account the perceptual and psychological issues. Logic is elitist, and if we want to attract to our models as many people as possible, we need to hide this elitism behind some metaphor, to which ’ordinary’ people are accustomed. As such a metaphor, we use the concept of a document, so our locally simple models are called document models. Document models are built in the paradigm of semantic programming. This allows us to achieve another important goal - to make the documentary models executable. Executable models are models that can act as practical information systems in the described domain of discourse. Thus, if our model is executable, then programming becomes redundant. The direct use of a model, instead of its programming coding, brings important advantages, for example, a drastic cost reduction for development and maintenance. Moreover, since the model is well and sound, and not dissolved within programming modules, we can directly apply AI tools, in particular, machine learning. This significantly expands the possibilities for automation and

  18. Model theory

    CERN Document Server

    Chang, CC

    2012-01-01

    Model theory deals with a branch of mathematical logic showing connections between a formal language and its interpretations or models. This is the first and most successful textbook in logical model theory. Extensively updated and corrected in 1990 to accommodate developments in model theoretic methods - including classification theory and nonstandard analysis - the third edition added entirely new sections, exercises, and references. Each chapter introduces an individual method and discusses specific applications. Basic methods of constructing models include constants, elementary chains, Sko

  19. Multiple Chronic Conditions, Resilience, and Workforce Transitions in Later Life: A Socio-Ecological Model.

    Science.gov (United States)

    Jason, Kendra J; Carr, Dawn C; Washington, Tiffany R; Hilliard, Tandrea S; Mingo, Chivon A

    2017-04-01

    Despite the growing prevalence of multiple chronic conditions (MCC), a problem that disproportionally affects older adults, few studies have examined the impact of MCC status on changes in workforce participation in later life. Recent research suggests that resilience, the ability to recover from adversity, may buffer the negative impact of chronic disease. Guided by an adapted socio-ecological risk and resilience conceptual model, this study examined the buffering effect of resilience on the relationship between individual and contextual risks, including MCC, and workforce transitions (i.e., leaving the workforce, working fewer hours, working the same hours, or working more hours). Using the Health and Retirement Study, this study pooled a sample of 4,861 older workers aged 51 and older with 2 consecutive biannual waves of data. Nonnested multinomial logistic regression analysis was applied. MCC are related to higher risk of transitioning out of the workforce. Resilience buffered the negative effects of MCC on workforce engagement and remained independently associated with increased probability of working the same or more hours compared with leaving work. MCC are associated with movement out of the paid workforce in later life. Despite the challenges MCC impose on older workers, having higher levels of resilience may provide the psychological resources needed to sustain work engagement in the face of new deficits. These findings suggest that identifying ways to bolster resilience may enhance the longevity of productive workforce engagement. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  20. Risk Pricing in Emerging Economies: Credit Scoring and Private Banking in Iran

    Directory of Open Access Journals (Sweden)

    Yiannis Anagnostopoulos

    2016-01-01

    Full Text Available Iran’s banking industry as a developing country is comparatively very new to risk management practices. An inevitable predictive implication of this rapid growth is the growing concerns with regard to credit risk management which is the motivation of conducting this research. The paper focuses on the credit scoring aspect of credit risk management using both logit and probit regression approaches. Real data on corporate customers are available for conducting this research which is also a contribution to this area for all other developing countries. Our questions focus on how future customers can be classified in terms of credibility, which models and methods are more effective in better capturing risks. Findings suggest that probit approaches are more effective in capturing the significance of variables and goodness-of-fitness tests. Seven variables of the Ohlson O-Score model are used: CL_CA, INTWO, OENEG, TA_TL, SIZE, WCAP_TA, and ROA; two were found to be statistically significant in logit (ROA, TL_TA and three were statistically significant in probit (ROA, TL_TA, SIZE. Also, CL_CA, ROA, and WCAP_TA were the three variables with an unexpected correlation to the probability of default. The prediction power with the cut-off point is set equal to 26% and 56.91% for defaulted customers in both logit and probit models. However, logit achieved 54.85% correct estimation of defaulted assets, 0.37% more than what probit estimated.

  1. Modeling Methods

    Science.gov (United States)

    Healy, Richard W.; Scanlon, Bridget R.

    2010-01-01

    Simulation models are widely used in all types of hydrologic studies, and many of these models can be used to estimate recharge. Models can provide important insight into the functioning of hydrologic systems by identifying factors that influence recharge. The predictive capability of models can be used to evaluate how changes in climate, water use, land use, and other factors may affect recharge rates. Most hydrological simulation models, including watershed models and groundwater-flow models, are based on some form of water-budget equation, so the material in this chapter is closely linked to that in Chapter 2. Empirical models that are not based on a water-budget equation have also been used for estimating recharge; these models generally take the form of simple estimation equations that define annual recharge as a function of precipitation and possibly other climatic data or watershed characteristics.Model complexity varies greatly. Some models are simple accounting models; others attempt to accurately represent the physics of water movement through each compartment of the hydrologic system. Some models provide estimates of recharge explicitly; for example, a model based on the Richards equation can simulate water movement from the soil surface through the unsaturated zone to the water table. Recharge estimates can be obtained indirectly from other models. For example, recharge is a parameter in groundwater-flow models that solve for hydraulic head (i.e. groundwater level). Recharge estimates can be obtained through a model calibration process in which recharge and other model parameter values are adjusted so that simulated water levels agree with measured water levels. The simulation that provides the closest agreement is called the best fit, and the recharge value used in that simulation is the model-generated estimate of recharge.

  2. Galactic models

    International Nuclear Information System (INIS)

    Buchler, J.R.; Gottesman, S.T.; Hunter, J.H. Jr.

    1990-01-01

    Various papers on galactic models are presented. Individual topics addressed include: observations relating to galactic mass distributions; the structure of the Galaxy; mass distribution in spiral galaxies; rotation curves of spiral galaxies in clusters; grand design, multiple arm, and flocculent spiral galaxies; observations of barred spirals; ringed galaxies; elliptical galaxies; the modal approach to models of galaxies; self-consistent models of spiral galaxies; dynamical models of spiral galaxies; N-body models. Also discussed are: two-component models of galaxies; simulations of cloudy, gaseous galactic disks; numerical experiments on the stability of hot stellar systems; instabilities of slowly rotating galaxies; spiral structure as a recurrent instability; model gas flows in selected barred spiral galaxies; bar shapes and orbital stochasticity; three-dimensional models; polar ring galaxies; dynamical models of polar rings

  3. Model-model Perencanaan Strategik

    OpenAIRE

    Amirin, Tatang M

    2005-01-01

    The process of strategic planning, used to be called as long-term planning, consists of several components, including strategic analysis, setting strategic direction (covering of mission, vision, and values), and action planning. Many writers develop models representing the steps of the strategic planning process, i.e. basic planning model, problem-based planning model, scenario model, and organic or self-organizing model.

  4. Event Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2001-01-01

    The purpose of this chapter is to discuss conceptual event modeling within a context of information modeling. Traditionally, information modeling has been concerned with the modeling of a universe of discourse in terms of information structures. However, most interesting universes of discourse...... are dynamic and we present a modeling approach that can be used to model such dynamics.We characterize events as both information objects and change agents (Bækgaard 1997). When viewed as information objects events are phenomena that can be observed and described. For example, borrow events in a library can...

  5. Modelling survival

    DEFF Research Database (Denmark)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight

    2016-01-01

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test...

  6. Constitutive Models

    DEFF Research Database (Denmark)

    Sales-Cruz, Mauricio; Piccolo, Chiara; Heitzig, Martina

    2011-01-01

    covered, illustrating several models such as the Wilson equation and NRTL equation, along with their solution strategies. A section shows how to use experimental data to regress the property model parameters using a least squares approach. A full model analysis is applied in each example that discusses...... the degrees of freedom, dependent and independent variables and solution strategy. Vapour-liquid and solid-liquid equilibrium is covered, and applications to droplet evaporation and kinetic models are given....

  7. Interface models

    DEFF Research Database (Denmark)

    Ravn, Anders P.; Staunstrup, Jørgen

    1994-01-01

    This paper proposes a model for specifying interfaces between concurrently executing modules of a computing system. The model does not prescribe a particular type of communication protocol and is aimed at describing interfaces between both software and hardware modules or a combination of the two....... The model describes both functional and timing properties of an interface...

  8. Co-development of Problem Gambling and Depression Symptoms in Emerging Adults: A Parallel-Process Latent Class Growth Model.

    Science.gov (United States)

    Edgerton, Jason D; Keough, Matthew T; Roberts, Lance W

    2018-02-21

    This study examines whether there are multiple joint trajectories of depression and problem gambling co-development in a sample of emerging adults. Data were from the Manitoba Longitudinal Study of Young Adults (n = 679), which was collected in 4 waves across 5 years (age 18-20 at baseline). Parallel process latent class growth modeling was used to identified 5 joint trajectory classes: low decreasing gambling, low increasing depression (81%); low stable gambling, moderate decreasing depression (9%); low stable gambling, high decreasing depression (5%); low stable gambling, moderate stable depression (3%); moderate stable problem gambling, no depression (2%). There was no evidence of reciprocal growth in problem gambling and depression in any of the joint classes. Multinomial logistic regression analyses of baseline risk and protective factors found that only neuroticism, escape-avoidance coping, and perceived level of family social support were significant predictors of joint trajectory class membership. Consistent with the pathways model framework, we observed that individuals in the problem gambling only class were more likely using gambling as a stable way to cope with negative emotions. Similarly, high levels of neuroticism and low levels of family support were associated with increased odds of being in a class with moderate to high levels of depressive symptoms (but low gambling problems). The results suggest that interventions for problem gambling and/or depression need to focus on promoting more adaptive coping skills among more "at-risk" young adults, and such interventions should be tailored in relation to specific subtypes of comorbid mental illness.

  9. Hydrological models are mediating models

    Science.gov (United States)

    Babel, L. V.; Karssenberg, D.

    2013-08-01

    Despite the increasing role of models in hydrological research and decision-making processes, only few accounts of the nature and function of models exist in hydrology. Earlier considerations have traditionally been conducted while making a clear distinction between physically-based and conceptual models. A new philosophical account, primarily based on the fields of physics and economics, transcends classes of models and scientific disciplines by considering models as "mediators" between theory and observations. The core of this approach lies in identifying models as (1) being only partially dependent on theory and observations, (2) integrating non-deductive elements in their construction, and (3) carrying the role of instruments of scientific enquiry about both theory and the world. The applicability of this approach to hydrology is evaluated in the present article. Three widely used hydrological models, each showing a different degree of apparent physicality, are confronted to the main characteristics of the "mediating models" concept. We argue that irrespective of their kind, hydrological models depend on both theory and observations, rather than merely on one of these two domains. Their construction is additionally involving a large number of miscellaneous, external ingredients, such as past experiences, model objectives, knowledge and preferences of the modeller, as well as hardware and software resources. We show that hydrological models convey the role of instruments in scientific practice by mediating between theory and the world. It results from these considerations that the traditional distinction between physically-based and conceptual models is necessarily too simplistic and refers at best to the stage at which theory and observations are steering model construction. The large variety of ingredients involved in model construction would deserve closer attention, for being rarely explicitly presented in peer-reviewed literature. We believe that devoting

  10. Labour market transitions and job satisfaction

    NARCIS (Netherlands)

    G.E. Bijwaard (Govert); A. van Dijk (Bram); J. de Koning (Jaap)

    2003-01-01

    textabstractThe paper investigates the relationship between job satisfaction and labour market transitions. Using a multinomial logit model, a model is estimated on the basis of individual data in which transitions are explained from individual characteristics, job characteristics, dissatisfaction

  11. The Smoothed Dirichlet Distribution: Understanding Cross-Entropy Ranking in Information Retrieval

    National Research Council Canada - National Science Library

    Nallapati, Ramesh

    2006-01-01

    .... Another related and interesting observation is that the naive Bayes model for text classification uses the same multinomial distribution to model documents but in contrast, employs document-log...

  12. ICRF modelling

    International Nuclear Information System (INIS)

    Phillips, C.K.

    1985-12-01

    This lecture provides a survey of the methods used to model fast magnetosonic wave coupling, propagation, and absorption in tokamaks. The validity and limitations of three distinct types of modelling codes, which will be contrasted, include discrete models which utilize ray tracing techniques, approximate continuous field models based on a parabolic approximation of the wave equation, and full field models derived using finite difference techniques. Inclusion of mode conversion effects in these models and modification of the minority distribution function will also be discussed. The lecture will conclude with a presentation of time-dependent global transport simulations of ICRF-heated tokamak discharges obtained in conjunction with the ICRF modelling codes. 52 refs., 15 figs

  13. Modelling in Business Model design

    NARCIS (Netherlands)

    Simonse, W.L.

    2013-01-01

    It appears that business model design might not always produce a design or model as the expected result. However when designers are involved, a visual model or artefact is produced. To assist strategic managers in thinking about how they can act, the designers challenge is to combine strategy and

  14. Eclipse models

    International Nuclear Information System (INIS)

    Michel, F.C.

    1989-01-01

    Three existing eclipse models for the PSR 1957 + 20 pulsar are discussed in terms of their requirements and the information they yield about the pulsar wind: the interacting wind from a companion model, the magnetosphere model, and the occulting disk model. It is shown out that the wind model requires an MHD wind from the pulsar, with enough particles that the Poynting flux of the wind can be thermalized; in this model, a large flux of energetic radiation from the pulsar is required to accompany the wind and drive the wind off the companion. The magnetosphere model requires an EM wind, which is Poynting flux dominated; the advantage of this model over the wind model is that the plasma density inside the magnetosphere can be orders of magnitude larger than in a magnetospheric tail blown back by wind interaction. The occulting disk model also requires an EM wind so that the interaction would be pushed down onto the companion surface, minimizing direct interaction of the wind with the orbiting macroscopic particles

  15. Ventilation Model

    International Nuclear Information System (INIS)

    Yang, H.

    1999-01-01

    The purpose of this analysis and model report (AMR) for the Ventilation Model is to analyze the effects of pre-closure continuous ventilation in the Engineered Barrier System (EBS) emplacement drifts and provide heat removal data to support EBS design. It will also provide input data (initial conditions, and time varying boundary conditions) for the EBS post-closure performance assessment and the EBS Water Distribution and Removal Process Model. The objective of the analysis is to develop, describe, and apply calculation methods and models that can be used to predict thermal conditions within emplacement drifts under forced ventilation during the pre-closure period. The scope of this analysis includes: (1) Provide a general description of effects and heat transfer process of emplacement drift ventilation. (2) Develop a modeling approach to simulate the impacts of pre-closure ventilation on the thermal conditions in emplacement drifts. (3) Identify and document inputs to be used for modeling emplacement ventilation. (4) Perform calculations of temperatures and heat removal in the emplacement drift. (5) Address general considerations of the effect of water/moisture removal by ventilation on the repository thermal conditions. The numerical modeling in this document will be limited to heat-only modeling and calculations. Only a preliminary assessment of the heat/moisture ventilation effects and modeling method will be performed in this revision. Modeling of moisture effects on heat removal and emplacement drift temperature may be performed in the future

  16. Mathematical modelling

    DEFF Research Database (Denmark)

    Blomhøj, Morten

    2004-01-01

    Developing competences for setting up, analysing and criticising mathematical models are normally seen as relevant only from and above upper secondary level. The general belief among teachers is that modelling activities presuppose conceptual understanding of the mathematics involved. Mathematical...... roots for the construction of important mathematical concepts. In addition competences for setting up, analysing and criticising modelling processes and the possible use of models is a formative aim in this own right for mathematics teaching in general education. The paper presents a theoretical...... modelling, however, can be seen as a practice of teaching that place the relation between real life and mathematics into the centre of teaching and learning mathematics, and this is relevant at all levels. Modelling activities may motivate the learning process and help the learner to establish cognitive...

  17. Mathematical modelling

    CERN Document Server

    2016-01-01

    This book provides a thorough introduction to the challenge of applying mathematics in real-world scenarios. Modelling tasks rarely involve well-defined categories, and they often require multidisciplinary input from mathematics, physics, computer sciences, or engineering. In keeping with this spirit of modelling, the book includes a wealth of cross-references between the chapters and frequently points to the real-world context. The book combines classical approaches to modelling with novel areas such as soft computing methods, inverse problems, and model uncertainty. Attention is also paid to the interaction between models, data and the use of mathematical software. The reader will find a broad selection of theoretical tools for practicing industrial mathematics, including the analysis of continuum models, probabilistic and discrete phenomena, and asymptotic and sensitivity analysis.

  18. Model : making

    OpenAIRE

    Bottle, Neil

    2013-01-01

    The Model : making exhibition was curated by Brian Kennedy in collaboration with Allies & Morrison in September 2013. For the London Design Festival, the Model : making exhibition looked at the increased use of new technologies by both craft-makers and architectural model makers. In both practices traditional ways of making by hand are increasingly being combined with the latest technologies of digital imaging, laser cutting, CNC machining and 3D printing. This exhibition focussed on ...

  19. Model building

    International Nuclear Information System (INIS)

    Frampton, Paul H.

    1998-01-01

    In this talk I begin with some general discussion of model building in particle theory, emphasizing the need for motivation and testability. Three illustrative examples are then described. The first is the Left-Right model which provides an explanation for the chirality of quarks and leptons. The second is the 331-model which offers a first step to understanding the three generations of quarks and leptons. Third and last is the SU(15) model which can accommodate the light leptoquarks possibly seen at HERA

  20. Model building

    International Nuclear Information System (INIS)

    Frampton, P.H.

    1998-01-01

    In this talk I begin with some general discussion of model building in particle theory, emphasizing the need for motivation and testability. Three illustrative examples are then described. The first is the Left-Right model which provides an explanation for the chirality of quarks and leptons. The second is the 331-model which offers a first step to understanding the three generations of quarks and leptons. Third and last is the SU(15) model which can accommodate the light leptoquarks possibly seen at HERA. copyright 1998 American Institute of Physics

  1. Modeling Documents with Event Model

    Directory of Open Access Journals (Sweden)

    Longhui Wang

    2015-08-01

    Full Text Available Currently deep learning has made great breakthroughs in visual and speech processing, mainly because it draws lessons from the hierarchical mode that brain deals with images and speech. In the field of NLP, a topic model is one of the important ways for modeling documents. Topic models are built on a generative model that clearly does not match the way humans write. In this paper, we propose Event Model, which is unsupervised and based on the language processing mechanism of neurolinguistics, to model documents. In Event Model, documents are descriptions of concrete or abstract events seen, heard, or sensed by people and words are objects in the events. Event Model has two stages: word learning and dimensionality reduction. Word learning is to learn semantics of words based on deep learning. Dimensionality reduction is the process that representing a document as a low dimensional vector by a linear mode that is completely different from topic models. Event Model achieves state-of-the-art results on document retrieval tasks.

  2. Animal models

    DEFF Research Database (Denmark)

    Gøtze, Jens Peter; Krentz, Andrew

    2014-01-01

    In this issue of Cardiovascular Endocrinology, we are proud to present a broad and dedicated spectrum of reviews on animal models in cardiovascular disease. The reviews cover most aspects of animal models in science from basic differences and similarities between small animals and the human...

  3. Battery Modeling

    NARCIS (Netherlands)

    Jongerden, M.R.; Haverkort, Boudewijn R.H.M.

    2008-01-01

    The use of mobile devices is often limited by the capacity of the employed batteries. The battery lifetime determines how long one can use a device. Battery modeling can help to predict, and possibly extend this lifetime. Many different battery models have been developed over the years. However,

  4. Didactical modelling

    DEFF Research Database (Denmark)

    Højgaard, Tomas; Hansen, Rune

    The purpose of this paper is to introduce Didactical Modelling as a research methodology in mathematics education. We compare the methodology with other approaches and argue that Didactical Modelling has its own specificity. We discuss the methodological “why” and explain why we find it useful...

  5. Design modelling

    NARCIS (Netherlands)

    Kempen, van A.; Kok, H.; Wagter, H.

    1992-01-01

    In Computer Aided Drafting three groups of three-dimensional geometric modelling can be recognized: wire frame, surface and solid modelling. One of the methods to describe a solid is by using a boundary based representation. The topology of the surface of a solid is the adjacency information between

  6. Education models

    NARCIS (Netherlands)

    Poortman, Sybilla; Sloep, Peter

    2006-01-01

    Educational models describes a case study on a complex learning object. Possibilities are investigated for using this learning object, which is based on a particular educational model, outside of its original context. Furthermore, this study provides advice that might lead to an increase in

  7. VENTILATION MODEL

    International Nuclear Information System (INIS)

    V. Chipman

    2002-01-01

    The purpose of the Ventilation Model is to simulate the heat transfer processes in and around waste emplacement drifts during periods of forced ventilation. The model evaluates the effects of emplacement drift ventilation on the thermal conditions in the emplacement drifts and surrounding rock mass, and calculates the heat removal by ventilation as a measure of the viability of ventilation to delay the onset of peak repository temperature and reduce its magnitude. The heat removal by ventilation is temporally and spatially dependent, and is expressed as the fraction of heat carried away by the ventilation air compared to the fraction of heat produced by radionuclide decay. One minus the heat removal is called the wall heat fraction, or the remaining amount of heat that is transferred via conduction to the surrounding rock mass. Downstream models, such as the ''Multiscale Thermohydrologic Model'' (BSC 2001), use the wall heat fractions as outputted from the Ventilation Model to initialize their postclosure analyses

  8. Modelling Constructs

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2009-01-01

    , these notations have been extended in order to increase expressiveness and to be more competitive. This resulted in an increasing number of notations and formalisms for modelling business processes and in an increase of the different modelling constructs provided by modelling notations, which makes it difficult......There are many different notations and formalisms for modelling business processes and workflows. These notations and formalisms have been introduced with different purposes and objectives. Later, influenced by other notations, comparisons with other tools, or by standardization efforts...... to compare modelling notations and to make transformations between them. One of the reasons is that, in each notation, the new concepts are introduced in a different way by extending the already existing constructs. In this chapter, we go the opposite direction: We show that it is possible to add most...

  9. Liberalización económica y crecimiento económico. Modelo Logit Multinomial aplicado a la metodología de "Doing Business"

    Directory of Open Access Journals (Sweden)

    Alberto Gómez Mejía

    2011-01-01

    de Doing Business explican cómo, cuando un país implementa estos criterios, incrementa las posibilidades de pasar a un nivel de ingreso per cápita superior, lo cual implica mayor crecimiento económico y potencial desarrollo económico.

  10. A comparison of a new multinomial stopping rule with stopping rules of fleming and gehan in single arm phase II cancer clinical trials

    Directory of Open Access Journals (Sweden)

    Tu Dongsheng

    2011-06-01

    Full Text Available Abstract Background Response rate (RR alone may be insensitive to drug activity in phase II trials. Early progressive disease (EPD could improve sensitivity as well as increase stage I stopping rates. This study compares the previously developed dual endpoint stopping rule (DESR, which incorporates both RR and EPD into a two-stage, phase II trial, with rules using only RR. Methods Stopping rules according to the DESR were compared with studies conducted under the Fleming (16 trials or Gehan (23 trials designs. The RR hypothesis for the DESR was consistent with the comparison studies (ralt = 0.2, rnul = 0.05. Two parameter sets were used for EPD rates of interest and disinterest respectively (epdalt, epdnul: (0.4, 0.6 and (0.3, 0.5. Results Compared with Fleming, the DESR was more likely to allow stage two of accrual and to reject the null hypothesis (Hnul after stage two, with rejection being more common with EPD parameters (0.4, 0.6 than (0.3, 0.5. Compared with Gehan, both DESR parameter sets accepted Hnul in 15 trials after stage I compared with 8 trials by Gehan, with consistent conclusions in all 23 trials after stage II. Conclusions The DESR may reject Hnul when EPD rates alone are low, and thereby may improve phase II trial sensitivity to active, cytostatic drugs having limited response rates. Conversely, the DESR may invoke early stopping when response rates are low and EPD rates are high, thus shortening trials when drug activity is unlikely. EPD parameters should be chosen specific to each trial.

  11. STEREOMETRIC MODELLING

    Directory of Open Access Journals (Sweden)

    P. Grimaldi

    2012-07-01

    Full Text Available These mandatory guidelines are provided for preparation of papers accepted for publication in the series of Volumes of The The stereometric modelling means modelling achieved with : – the use of a pair of virtual cameras, with parallel axes and positioned at a mutual distance average of 1/10 of the distance camera-object (in practice the realization and use of a stereometric camera in the modeling program; – the shot visualization in two distinct windows – the stereoscopic viewing of the shot while modelling. Since the definition of "3D vision" is inaccurately referred to as the simple perspective of an object, it is required to add the word stereo so that "3D stereo vision " shall stand for "three-dimensional view" and ,therefore, measure the width, height and depth of the surveyed image. Thanks to the development of a stereo metric model , either real or virtual, through the "materialization", either real or virtual, of the optical-stereo metric model made visible with a stereoscope. It is feasible a continuous on line updating of the cultural heritage with the help of photogrammetry and stereometric modelling. The catalogue of the Architectonic Photogrammetry Laboratory of Politecnico di Bari is available on line at: http://rappresentazione.stereofot.it:591/StereoFot/FMPro?-db=StereoFot.fp5&-lay=Scheda&-format=cerca.htm&-view

  12. Modeling complexes of modeled proteins.

    Science.gov (United States)

    Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

    2017-03-01

    Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  13. Longitudinal categorical data analysis

    CERN Document Server

    Sutradhar, Brajendra C

    2014-01-01

    This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses. This book is a natural generalization of the longitudinal binary data analysis to the multinomial data setup with more than two categories. Thus, unlike the existing books on cross-sectional categorical data analysis using log linear models, this book uses multinomial probability models both in cross-sectional and longitudinal setups. A theoretical foundation is provided for the analysis of univariate multinomial responses, by developing models systematically for the cases with no covariates as well as categorical covariates, both in cross-sectional and longitudinal setups. In the longitudinal setup, both stationary and non-stationary covariates are considered. These models have also been extended to the bivariate multinomial setup along with suitable covariates. For the inferences, the book uses the generalized quasi-likelihood as w...

  14. Graphical Rasch models

    DEFF Research Database (Denmark)

    Kreiner, Svend; Christensen, Karl Bang

    Rasch models; Partial Credit models; Rating Scale models; Item bias; Differential item functioning; Local independence; Graphical models......Rasch models; Partial Credit models; Rating Scale models; Item bias; Differential item functioning; Local independence; Graphical models...

  15. Supernova models

    International Nuclear Information System (INIS)

    Woosley, S.E.; California, University, Livermore, CA); Weaver, T.A.

    1981-01-01

    Recent progress in understanding the observed properties of type I supernovae as a consequence of the thermonuclear detonation of white dwarf stars and the ensuing decay of the Ni-56 produced therein is reviewed. The expected nucleosynthesis and gamma-line spectra for this model of type I explosions and a model for type II explosions are presented. Finally, a qualitatively new approach to the problem of massive star death and type II supernovae based upon a combination of rotation and thermonuclear burning is discussed. While the theoretical results of existing models are predicated upon the assumption of a successful core bounce calculation and the neglect of such two-dimensional effects as rotation and magnetic fields the new model suggests an entirely different scenario in which a considerable portion of the energy carried by an equatorially ejected blob is deposited in the red giant envelope overlying the mantle of the star

  16. Model theory

    CERN Document Server

    Hodges, Wilfrid

    1993-01-01

    An up-to-date and integrated introduction to model theory, designed to be used for graduate courses (for students who are familiar with first-order logic), and as a reference for more experienced logicians and mathematicians.

  17. Markov model

    Indian Academy of Sciences (India)

    2School of Water Resources, Indian Institute of Technology,. Kharagpur ... the most accepted method for modelling LULCC using current .... We used UTM coordinate system with zone 45 .... need to develop criteria for making decision about.

  18. Paleoclimate Modeling

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Computer simulations of past climate. Variables provided as model output are described by parameter keyword. In some cases the parameter keywords are a subset of all...

  19. Energy Models

    Science.gov (United States)

    Energy models characterize the energy system, its evolution, and its interactions with the broader economy. The energy system consists of primary resources, including both fossil fuels and renewables; power plants, refineries, and other technologies to process and convert these r...

  20. Linear Models

    CERN Document Server

    Searle, Shayle R

    2012-01-01

    This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.

  1. Ventilation models

    Science.gov (United States)

    Skaaret, Eimund

    Calculation procedures, used in the design of ventilating systems, which are especially suited for displacement ventilation in addition to linking it to mixing ventilation, are addressed. The two zone flow model is considered and the steady state and transient solutions are addressed. Different methods of supplying air are discussed, and different types of air flow are considered: piston flow, plane flow and radial flow. An evaluation model for ventilation systems is presented.

  2. Differentiated influences of benefit and risk perceptions on nuclear power acceptance according to acceptance levels. Evidence from Korea

    International Nuclear Information System (INIS)

    Roh, Seungkook; Lee Jinwon

    2017-01-01

    The perceived benefit and risk of nuclear power generation have received considerable attention as determinants of the public's nuclear power acceptance. However, the contingency of the relative importance of these benefit and risk has been less explored. Using Korea as an example, this study explores the possibility that the relative importance of perceived benefit and risk on nuclear power acceptance depends on acceptance levels. Our results from latent class analysis and multinomial probit show that, in determining whether an individual shows a moderate level of nuclear power acceptance rather than a low level, perceived risk plays a dominant role compared to perceived benefit; however, regarding whether he/she shows a high level of nuclear power acceptance rather than a moderate level, this relative importance is reversed. These results carry practical implications for risk governance of nuclear power, particularly with regard to communication with the public. (author)

  3. Model uncertainty: Probabilities for models?

    International Nuclear Information System (INIS)

    Winkler, R.L.

    1994-01-01

    Like any other type of uncertainty, model uncertainty should be treated in terms of probabilities. The question is how to do this. The most commonly-used approach has a drawback related to the interpretation of the probabilities assigned to the models. If we step back and look at the big picture, asking what the appropriate focus of the model uncertainty question should be in the context of risk and decision analysis, we see that a different probabilistic approach makes more sense, although it raise some implementation questions. Current work that is underway to address these questions looks very promising

  4. An Econometric Analysis of the Mexican Peso Crisis of 1994-1995 = 1994-1995 Meksika Pezo Krizi'nin Ekonometrik Bir Analizi

    Directory of Open Access Journals (Sweden)

    Mete FERİDUN

    2007-01-01

    Full Text Available This article aims at identifying the factors behind the Mexican Peso Crisis of 1994-1995 through building a probit model incorporating 20 monthly macroeconomic, political, and financial sector variables from 1970:1 - 1995:1. As a result of the probit regressions, strong evidence emerges that the significant variables are political instability, foreign exchange reserves, domestic credit/GDP, lending and deposit rate spread, national savings, and foreign direct investment/GDP. Evidence further indicates that the signs of the variables are mostly in line with our expectations, with the exception of inflation, bank reserves/bank assets, export growth, and lending and deposit rate spread.

  5. The role of education for current, former and never-smoking among non-western immigrants in Norway. Does the pattern fit the model of the cigarette epidemic?

    Science.gov (United States)

    Vedøy, Tord Finne

    2013-01-01

    The aim was (1) to investigate the association between education and smoking status (current, former and never-smoking) among non-western immigrants in Norway and (2) examine if these associations fit the pattern predicted by the model of the cigarette epidemic. Data came from the Oslo Health Study and the Oslo Immigrant Health study (2000-2002). The first included all Oslo citizens from seven selected birth cohorts. The second included all Oslo citizens born in Turkey, Iran, Pakistan, Vietnam and Sri Lanka. 14,768 respondents answered questions on smoking, education and relevant background variables (over-all response rate 43.3%). Two gender specific multinomial logistic regression models with smoking status [current, former or never-smoker (reference)] as dependent variable were computed and predicted probabilities of smoking status among groups with different levels of education were calculated. Smoking prevalence among men ranged from 19% among Sri Lankans to 56% among Turks. Compared to the smoking prevalence among Norwegian men (27%), smoking was widespread among Iranians (42%) and Vietnamese (36%). Higher education was associated with lower probability of current smoking among all male immigrant groups except Sri Lankans. Never having smoked was positively associated with education among Pakistani and Norwegian men. Among women, education was higher than for other levels of education. The probability of being a never-smoker was high among Turkish and Iranian women with primary education. High smoking prevalence among Turkish and Iranian men highlights the importance of addressing smoking behaviour in subgroups of the general population. Smoking was almost non-existent among Pakistani, Vietnamese and Sri Lankan women and indicates strong persistent social norms against smoking.

  6. Political instability and country risk : new evidence

    NARCIS (Netherlands)

    DeHaan, J; Siermann, CLJ; VanLubek, E

    1997-01-01

    This note presents new estimates of a probit model for the debt rescheduling, using a sample of 65 countries over the period 1984-93. Apart from economic variables, a whole range of indicators for political instability are included in the model as explanatory variables. It turns out, that none is

  7. Balance in competition in Dutch soccer

    NARCIS (Netherlands)

    Koning, Ruud H.

    2000-01-01

    In this paper, we estimate an ordered probit model for soccer results in The Netherlands. The result of a game is assumed to be determined by home advantage and quality differences of the opposing teams. The parameters of the model are used to assess whether competitive balance in Dutch professional

  8. Unpaid overtime in the Netherlands : forward- or backward-looking incentives?

    NARCIS (Netherlands)

    Van der Meer, Peter H.; Wielers, Rudi

    2015-01-01

    The purpose of this paper is to test forward-looking incentives against backward-looking incentives. Design/methodology/approach ? Wage growth model to estimate forward-looking effects of unpaid overtime and a probit model of participation in unpaid overtime controlling for excessive pay to estimate

  9. 630 understanding farmers' response to climate variability in nigeria

    African Journals Online (AJOL)

    Osondu

    Data were analyzed using descriptive statistics, and multinomial logit models. Farmers used multiple adaptation strategies; Crop Diversification (CD), Soil ... Increases in temperature, cloud ... and the effect of climate elements and their extreme ...

  10. West African Journal of Industrial and Academic Research - Vol 13 ...

    African Journals Online (AJOL)

    On The Comparison of Artificial Neural Network (ANN) and Multinomial Logistic ... ICT-Based Framework for Improved Food Security in Nigeria · EMAIL FREE FULL ... towards HIV/AIDS Patients in Zambia: A Generalized Additive Mixed Model ...

  11. Determinants of agricultural micro-credit repayment-evidence from ...

    African Journals Online (AJOL)

    Agro-Science ... for the study while descriptive statistics and multinomial binary logit model were employed for data analyses. ... on long term funds (without prejudice to the existing revolving loan mechanism) such as the pension contributions, ...

  12. Thermocouple modeling

    International Nuclear Information System (INIS)

    Fryer, M.O.

    1984-01-01

    The temperature measurements provided by thermocouples (TCs) are important for the operation of pressurized water reactors. During severe inadequate core cooling incidents, extreme temperatures may cause type K thermocouples (TCs) used for core exit temperature monitoring to perform poorly. A model of TC electrical behavior has been developed to determine how TCs react under extreme temperatures. The model predicts the voltage output of the TC and its impedance. A series of experiments were conducted on a length of type K thermocouple to validate the model. Impedance was measured at several temperatures between 22 0 C and 1100 0 C and at frequencies between dc and 10 MHz. The model was able to accurately predict impedance over this wide range of conditions. The average percentage difference between experimental data and the model was less than 6.5%. Experimental accuracy was +-2.5%. There is a sriking difference between impedance versus frequency plots at 300 0 C and at higher temperatures. This may be useful in validating TC data during accident conditions

  13. Photoionization Modeling

    Science.gov (United States)

    Kallman, T.

    2010-01-01

    Warm absorber spectra are characterized by the many lines from partially ionized intermediate-Z elements, and iron, detected with the grating instruments on Chandra and XMM-Newton. If these ions are formed in a gas which is in photoionization equilibrium, they correspond to a broad range of ionization parameters, although there is evidence for certain preferred values. A test for any dynamical model for these outflows is to reproduce these properties, at some level of detail. In this paper we present a statistical analysis of the ionization distribution which can be applied both the observed spectra and to theoretical models. As an example, we apply it to our dynamical models for warm absorber outflows, based on evaporation from the molecular torus.

  14. Reflectance Modeling

    Science.gov (United States)

    Smith, J. A.; Cooper, K.; Randolph, M.

    1984-01-01

    A classical description of the one dimensional radiative transfer treatment of vegetation canopies was completed and the results were tested against measured prairie (blue grama) and agricultural canopies (soybean). Phase functions are calculated in terms of directly measurable biophysical characteristics of the canopy medium. While the phase functions tend to exhibit backscattering anisotropy, their exact behavior is somewhat more complex and wavelength dependent. A Monte Carlo model was developed that treats soil surfaces with large periodic variations in three dimensions. A photon-ray tracing technology is used. Currently, the rough soil surface is described by analytic functions and appropriate geometric calculations performed. A bidirectional reflectance distribution function is calculated and, hence, available for other atmospheric or canopy reflectance models as a lower boundary condition. This technique is used together with an adding model to calculate several cases where Lambertian leaves possessing anisotropic leaf angle distributions yield non-Lambertian reflectance; similar behavior is exhibited for simulated soil surfaces.

  15. Mathematical modeling

    CERN Document Server

    Eck, Christof; Knabner, Peter

    2017-01-01

    Mathematical models are the decisive tool to explain and predict phenomena in the natural and engineering sciences. With this book readers will learn to derive mathematical models which help to understand real world phenomena. At the same time a wealth of important examples for the abstract concepts treated in the curriculum of mathematics degrees are given. An essential feature of this book is that mathematical structures are used as an ordering principle and not the fields of application. Methods from linear algebra, analysis and the theory of ordinary and partial differential equations are thoroughly introduced and applied in the modeling process. Examples of applications in the fields electrical networks, chemical reaction dynamics, population dynamics, fluid dynamics, elasticity theory and crystal growth are treated comprehensively.

  16. Genetic parameter estimation of reproductive traits of Litopenaeus vannamei

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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 European countries. We recommend future researches studying the effect of other characteristics of respondents on health assessment. PMID:29020343

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

    Science.gov (United States)

    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.

  19. Modelling language

    CERN Document Server

    Cardey, Sylviane

    2013-01-01

    In response to the need for reliable results from natural language processing, this book presents an original way of decomposing a language(s) in a microscopic manner by means of intra/inter‑language norms and divergences, going progressively from languages as systems to the linguistic, mathematical and computational models, which being based on a constructive approach are inherently traceable. Languages are described with their elements aggregating or repelling each other to form viable interrelated micro‑systems. The abstract model, which contrary to the current state of the art works in int

  20. Molecular modeling

    Directory of Open Access Journals (Sweden)

    Aarti Sharma

    2009-01-01

    Full Text Available The use of computational chemistry in the development of novel pharmaceuticals is becoming an increasingly important tool. In the past, drugs were simply screened for effectiveness. The recent advances in computing power and the exponential growth of the knowledge of protein structures have made it possible for organic compounds to be tailored to decrease the harmful side effects and increase the potency. This article provides a detailed description of the techniques employed in molecular modeling. Molecular modeling is a rapidly developing discipline, and has been supported by the dramatic improvements in computer hardware and software in recent years.

  1. Supernova models

    International Nuclear Information System (INIS)

    Woosley, S.E.; Weaver, T.A.

    1980-01-01

    Recent progress in understanding the observed properties of Type I supernovae as a consequence of the thermonuclear detonation of white dwarf stars and the ensuing decay of the 56 Ni produced therein is reviewed. Within the context of this model for Type I explosions and the 1978 model for Type II explosions, the expected nucleosynthesis and gamma-line spectra from both kinds of supernovae are presented. Finally, a qualitatively new approach to the problem of massive star death and Type II supernovae based upon a combination of rotation and thermonuclear burning is discussed

  2. Development of Head Injury Assessment Reference Values Based on NASA Injury Modeling

    Science.gov (United States)

    Somers, Jeffrey T.; Melvin, John W.; Tabiei, Ala; Lawrence, Charles; Ploutz-Snyder, Robert; Granderson, Bradley; Feiveson, Alan; Gernhardt, Michael; Patalak, John

    2011-01-01

    zero. For the parameters head translational acceleration, head translational velocity change, head rotational acceleration, HIC-15, and HIC-36, conservative values (in the lower 95% confidence interval) that gave rise to a 5% risk of any injury occurring were estimated as 40.0 G, 7.9 m/s, 2200 rad/s2, 98.4, and 77.4 respectively. Because NASA is interested in the consequence of any particular injury on the ability of the crew to perform egress tasks, the head injuries that occurred in the NASCAR dataset were classified according to a NASA-developed scale (Classes I - III) for operationally relevant injuries, which classifies injuries on the basis of their operational significance. Additional analysis of the data was performed to determine the probability of each injury class occurring, and this was estimated using an ordered probit model. For head translational acceleration, head translational velocity change, head rotational acceleration, head rotational velocity, HIC-36, and head 3ms clip, conservative values of IARVs that produced a 5% risk of Class II injury were estimated as 50.7 G, 9.5 m/s, 2863 rad/s2, 11.0 rad/s, 30.3, and 46.4 G respectively. The results indicate that head IARVs developed from the NASCAR dataset may be useful to protect crews during landing impact.

  3. Painting models

    Science.gov (United States)

    Baart, F.; Donchyts, G.; van Dam, A.; Plieger, M.

    2015-12-01

    The emergence of interactive art has blurred the line between electronic, computer graphics and art. Here we apply this art form to numerical models. Here we show how the transformation of a numerical model into an interactive painting can both provide insights and solve real world problems. The cases that are used as an example include forensic reconstructions, dredging optimization, barrier design. The system can be fed using any source of time varying vector fields, such as hydrodynamic models. The cases used here, the Indian Ocean (HYCOM), the Wadden Sea (Delft3D Curvilinear), San Francisco Bay (3Di subgrid and Delft3D Flexible Mesh), show that the method used is suitable for different time and spatial scales. High resolution numerical models become interactive paintings by exchanging their velocity fields with a high resolution (>=1M cells) image based flow visualization that runs in a html5 compatible web browser. The image based flow visualization combines three images into a new image: the current image, a drawing, and a uv + mask field. The advection scheme that computes the resultant image is executed in the graphics card using WebGL, allowing for 1M grid cells at 60Hz performance on mediocre graphic cards. The software is provided as open source software. By using different sources for a drawing one can gain insight into several aspects of the velocity fields. These aspects include not only the commonly represented magnitude and direction, but also divergence, topology and turbulence .

  4. Entrepreneurship Models.

    Science.gov (United States)

    Finger Lakes Regional Education Center for Economic Development, Mount Morris, NY.

    This guide describes seven model programs that were developed by the Finger Lakes Regional Center for Economic Development (New York) to meet the training needs of female and minority entrepreneurs to help their businesses survive and grow and to assist disabled and dislocated workers and youth in beginning small businesses. The first three models…

  5. Lens Model

    DEFF Research Database (Denmark)

    Nash, Ulrik William

    2014-01-01

    Firms consist of people who make decisions to achieve goals. How do these people develop the expectations which underpin the choices they make? The lens model provides one answer to this question. It was developed by cognitive psychologist Egon Brunswik (1952) to illustrate his theory of probabil...

  6. Eclipse models

    International Nuclear Information System (INIS)

    Michel, F.C.

    1989-01-01

    This paper addresses the question of, if one overlooks their idiosyncratic difficulties, what could be learned from the various models about the pulsar wind? The wind model requires an MHD wind from the pulsar, namely, one with enough particles that the Poynting flux of the wind can be thermalized. Otherwise, there is no shock and the pulsar wind simply reflects like a flashlight beam. Additionally, a large flux of energetic radiation from the pulsar is required to accompany the wind and drive the wind off the companion. The magnetosphere model probably requires an EM wind, which is Poynting flux dominated. Reflection in this case would arguably minimize the intimate interaction between the two flows that leads to tail formation and thereby permit a weakly magnetized tail. The occulting disk model also would point to an EM wind so that the interaction would be pushed down onto the companion surface (to form the neutral fountain) and so as to also minimize direct interaction of the wind with the orbiting macroscopic particles

  7. (SSE) model

    African Journals Online (AJOL)

    Simple analytic polynomials have been proposed for estimating solar radiation in the traditional Northern, Central and Southern regions of Malawi. There is a strong agreement between the polynomials and the SSE model with R2 values of 0.988, 0.989 and 0.989 and root mean square errors of 0.061, 0.057 and 0.062 ...

  8. Successful modeling?

    Science.gov (United States)

    Lomnitz, Cinna

    Tichelaar and Ruff [1989] propose to “estimate model variance in complicated geophysical problems,” including the determination of focal depth in earthquakes, by means of unconventional statistical methods such as bootstrapping. They are successful insofar as they are able to duplicate the results from more conventional procedures.

  9. Defect modelling

    International Nuclear Information System (INIS)

    Norgett, M.J.

    1980-01-01

    Calculations, drawing principally on developments at AERE Harwell, of the relaxation about lattice defects are reviewed with emphasis on the techniques required for such calculations. The principles of defect modelling are outlined and various programs developed for defect simulations are discussed. Particular calculations for metals, ionic crystals and oxides, are considered. (UK)

  10. Cadastral Modeling

    DEFF Research Database (Denmark)

    Stubkjær, Erik

    2005-01-01

    to the modeling of an industrial sector, as it aims at rendering the basic concepts that relate to the domain of real estate and the pertinent human activities. The palpable objects are pieces of land and buildings, documents, data stores and archives, as well as persons in their diverse roles as owners, holders...

  11. The Model

    DEFF Research Database (Denmark)

    About the reconstruction of Palle Nielsen's (f. 1942) work The Model from 1968: a gigantic playground for children in the museum, where they can freely romp about, climb in ropes, crawl on wooden structures, work with tools, jump in foam rubber, paint with finger paints and dress up in costumes....

  12. Biotran model

    International Nuclear Information System (INIS)

    Wenzel, W.J.; Gallegos, A.F.; Rodgers, J.C.

    1985-01-01

    The BIOTRAN model was developed at Los Alamos to help predict short- and long-term consequences to man from releases of radionuclides into the environment. It is a dynamic model that simulates on a daily and yearly basis the flux of biomass, water, and radionuclides through terrestrial and aquatic ecosystems. Biomass, water, and radionuclides are driven within the ecosystems by climate variables stochastically generated by BIOTRAN each simulation day. The climate variables influence soil hydraulics, plant growth, evapotranspiration, and particle suspension and deposition. BIOTRAN has 22 different plant growth strategies for simulating various grasses, shrubs, trees, and crops. Ruminants and humans are also dynamically simulated by using the simulated crops and forage as intake for user-specified diets. BIOTRAN has been used at Los Alamos for long-term prediction of health effects to populations following potential accidental releases of uranium and plutonium. Newly developed subroutines are described: a human dynamic physiological and metabolic model; a soil hydrology and irrigation model; limnetic nutrient and radionuclide cycling in fresh-water lakes. 7 references

  13. Turbulence Model

    DEFF Research Database (Denmark)

    Nielsen, Mogens Peter; Shui, Wan; Johansson, Jens

    2011-01-01

    term with stresses depending linearly on the strain rates. This term takes into account the transfer of linear momentum from one part of the fluid to another. Besides there is another term, which takes into account the transfer of angular momentum. Thus the model implies a new definition of turbulence...

  14. Hydroballistics Modeling

    Science.gov (United States)

    1975-01-01

    thai h’liathe0in antd is finaull’ %IIIrd alt %tramlit And drohlttle. Mike aplpars Ito inua•,e upward in outler a rei and dowoi. ward it %iunr areli, Oil...fiducial marks should be constant and the edges phobic nor hydrophilic is better for routine sharpl ) defined. model testing. Before each launching in

  15. Molecular Modeling

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 5. Molecular Modeling: A Powerful Tool for Drug Design and Molecular Docking. Rama Rao Nadendla. General Article Volume 9 Issue 5 May 2004 pp 51-60. Fulltext. Click here to view fulltext PDF. Permanent link:

  16. Spatial capture-recapture design and modelling for the study of small mammals.

    Directory of Open Access Journals (Sweden)

    Juan Romairone

    Full Text Available Spatial capture-recapture modelling (SCR is a powerful analytical tool to estimate density and derive information on space use and behaviour of elusive animals. Yet, SCR has been seldom applied to the study of ecologically keystone small mammals. Here we highlight its potential and requirements with a case study on common voles (Microtus arvalis. First, we address mortality associated with live-trapping, which can be high in small mammals, and must be kept minimal. We designed and tested a nest box coupled with a classic Sherman trap and show that it allows a 5-fold reduction of mortality in traps. Second, we address the need to adjust the trapping grid to the individual home range to maximize spatial recaptures. In May-June 2016, we captured and tagged with transponders 227 voles in a 1.2-ha area during two monthly sessions. Using a Bayesian SCR with a multinomial approach, we estimated: (1 the baseline detection rate and investigated variation according to sex, time or behaviour (aversion/attraction after a previous capture; (2 the parameter sigma that describes how detection probability declines as a function of the distance to an individual´s activity centre, and investigated variation according to sex; and (3 density and population sex-ratio. We show that reducing the maximum distance between traps from 12 to 9.6m doubled spatial recaptures and improved model predictions. Baseline detection rate increased over time (after overcoming a likely aversion to entering new odourless traps and was greater for females than males in June. The sigma parameter of males was twice that of females, indicating larger home ranges. Density estimates were of 142.92±38.50 and 168.25±15.79 voles/ha in May and June, respectively, with 2-3 times more females than males. We highlight the potential and broad applicability that SCR offers and provide specific recommendations for using it to study small mammals like voles.

  17. Criticality Model

    International Nuclear Information System (INIS)

    Alsaed, A.

    2004-01-01

    The ''Disposal Criticality Analysis Methodology Topical Report'' (YMP 2003) presents the methodology for evaluating potential criticality situations in the monitored geologic repository. As stated in the referenced Topical Report, the detailed methodology for performing the disposal criticality analyses will be documented in model reports. Many of the models developed in support of the Topical Report differ from the definition of models as given in the Office of Civilian Radioactive Waste Management procedure AP-SIII.10Q, ''Models'', in that they are procedural, rather than mathematical. These model reports document the detailed methodology necessary to implement the approach presented in the Disposal Criticality Analysis Methodology Topical Report and provide calculations utilizing the methodology. Thus, the governing procedure for this type of report is AP-3.12Q, ''Design Calculations and Analyses''. The ''Criticality Model'' is of this latter type, providing a process evaluating the criticality potential of in-package and external configurations. The purpose of this analysis is to layout the process for calculating the criticality potential for various in-package and external configurations and to calculate lower-bound tolerance limit (LBTL) values and determine range of applicability (ROA) parameters. The LBTL calculations and the ROA determinations are performed using selected benchmark experiments that are applicable to various waste forms and various in-package and external configurations. The waste forms considered in this calculation are pressurized water reactor (PWR), boiling water reactor (BWR), Fast Flux Test Facility (FFTF), Training Research Isotope General Atomic (TRIGA), Enrico Fermi, Shippingport pressurized water reactor, Shippingport light water breeder reactor (LWBR), N-Reactor, Melt and Dilute, and Fort Saint Vrain Reactor spent nuclear fuel (SNF). The scope of this analysis is to document the criticality computational method. The criticality

  18. Identifying community healthcare supports for the elderly and the factors affecting their aging care model preference: evidence from three districts of Beijing

    Directory of Open Access Journals (Sweden)

    Tianyang Liu

    2016-11-01

    Full Text Available Abstract Background The Chinese tradition of filial piety, which prioritized family-based care for the elderly, is transitioning and elders can no longer necessarily rely on their children. The purpose of this study was to identify community support for the elderly, and analyze the factors that affect which model of old-age care elderly people dwelling in communities prefer. Methods We used the database “Health and Social Support of Elderly Population in Community”. Questionnaires were issued in 2013, covering 3 districts in Beijing. A group of 1036 people over 60 years in age were included in the study. The respondents’ profile variables were organized in Andersen’s Model and community healthcare resource factors were added. A multinomial logistic model was applied to analyze the factors associated with the desired aging care models. Results Cohabiting with children and relying on care from family was still the primary desired aging care model for seniors (78 %, followed by living in institutions (14.8 % and living at home independently while relying on community resources (7.2 %. The regression result indicated that predisposing, enabling and community factors were significantly associated with the aging care model preference. Specifically, compared with those who preferred to cohabit with children, those having higher education, fewer available family and friend helpers, and shorter distance to healthcare center were more likely to prefer to live independently and rely on community support. And compared with choosing to live in institutions, those having fewer available family and friend helpers and those living alone were more likely to prefer to live independently and rely on community. Need factors (health and disability condition were not significantly associated with desired aging care models, indicating that desired aging care models were passive choices resulted from the balancing of family and social caring resources

  19. Building Models and Building Modelling

    DEFF Research Database (Denmark)

    Jørgensen, Kaj; Skauge, Jørn

    2008-01-01

    I rapportens indledende kapitel beskrives de primære begreber vedrørende bygningsmodeller og nogle fundamentale forhold vedrørende computerbaseret modulering bliver opstillet. Desuden bliver forskellen mellem tegneprogrammer og bygnings­model­lerings­programmer beskrevet. Vigtige aspekter om comp...

  20. Persistent Modelling

    DEFF Research Database (Denmark)

    2012-01-01

    The relationship between representation and the represented is examined here through the notion of persistent modelling. This notion is not novel to the activity of architectural design if it is considered as describing a continued active and iterative engagement with design concerns – an evident....... It also provides critical insight into the use of contemporary modelling tools and methods, together with an examination of the implications their use has within the territories of architectural design, realisation and experience....... on this subject, this book makes essential reading for anyone considering new ways of thinking about architecture. In drawing upon both historical and contemporary perspectives this book provides evidence of the ways in which relations between representation and the represented continue to be reconsidered...

  1. Persistent Modelling

    DEFF Research Database (Denmark)

    The relationship between representation and the represented is examined here through the notion of persistent modelling. This notion is not novel to the activity of architectural design if it is considered as describing a continued active and iterative engagement with design concerns – an evident....... It also provides critical insight into the use of contemporary modelling tools and methods, together with an examination of the implications their use has within the territories of architectural design, realisation and experience....... on this subject, this book makes essential reading for anyone considering new ways of thinking about architecture. In drawing upon both historical and contemporary perspectives this book provides evidence of the ways in which relations between representation and the represented continue to be reconsidered...

  2. Acyclic models

    CERN Document Server

    Barr, Michael

    2002-01-01

    Acyclic models is a method heavily used to analyze and compare various homology and cohomology theories appearing in topology and algebra. This book is the first attempt to put together in a concise form this important technique and to include all the necessary background. It presents a brief introduction to category theory and homological algebra. The author then gives the background of the theory of differential modules and chain complexes over an abelian category to state the main acyclic models theorem, generalizing and systemizing the earlier material. This is then applied to various cohomology theories in algebra and topology. The volume could be used as a text for a course that combines homological algebra and algebraic topology. Required background includes a standard course in abstract algebra and some knowledge of topology. The volume contains many exercises. It is also suitable as a reference work for researchers.

  3. Molecular Modelling

    Directory of Open Access Journals (Sweden)

    Aarti Sharma

    2009-12-01

    Full Text Available

    The use of computational chemistry in the development of novel pharmaceuticals is becoming an increasingly important
    tool. In the past, drugs were simply screened for effectiveness. The recent advances in computing power and
    the exponential growth of the knowledge of protein structures have made it possible for organic compounds to tailored to
    decrease harmful side effects and increase the potency. This article provides a detailed description of the techniques
    employed in molecular modeling. Molecular modelling is a rapidly developing discipline, and has been supported from
    the dramatic improvements in computer hardware and software in recent years.

  4. RNICE Model

    DEFF Research Database (Denmark)

    Pedersen, Mogens Jin; Stritch, Justin Michael

    2018-01-01

    Replication studies relate to the scientific principle of replicability and serve the significant purpose of providing supporting (or contradicting) evidence regarding the existence of a phenomenon. However, replication has never been an integral part of public administration and management...... research. Recently, scholars have issued calls for more replication, but academic reflections on when replication adds substantive value to public administration and management research are needed. This concise article presents a conceptual model, RNICE, for assessing when and how a replication study...... contributes knowledge about a social phenomenon and advances knowledge in the public administration and management literatures. The RNICE model provides a vehicle for researchers who seek to evaluate or demonstrate the value of a replication study systematically. We illustrate the practical application...

  5. Maturity Models

    DEFF Research Database (Denmark)

    Lasrado, Lester Allan; Vatrapu, Ravi

    2016-01-01

    Recent advancements in set theory and readily available software have enabled social science researchers to bridge the variable-centered quantitative and case-based qualitative methodological paradigms in order to analyze multi-dimensional associations beyond the linearity assumptions, aggregate...... effects, unicausal reduction, and case specificity. Based on the developments in set theoretical thinking in social sciences and employing methods like Qualitative Comparative Analysis (QCA), Necessary Condition Analysis (NCA), and set visualization techniques, in this position paper, we propose...... and demonstrate a new approach to maturity models in the domain of Information Systems. This position paper describes the set-theoretical approach to maturity models, presents current results and outlines future research work....

  6. Modelling Defiguration

    DEFF Research Database (Denmark)

    Bork Petersen, Franziska

    2013-01-01

    advantageous manner. Stepping on the catwalk’s sloping, moving surfaces decelerates the models’ walk and makes it cautious, hesitant and shaky: suddenly the models lack exactly the affirmative, staccato, striving quality of motion, and the condescending expression that they perform on most contemporary......For the presentation of his autumn/winter 2012 collection in Paris and subsequently in Copenhagen, Danish designer Henrik Vibskov installed a mobile catwalk. The article investigates the choreographic impact of this scenography on those who move through it. Drawing on Dance Studies, the analytical...... focus centres on how the catwalk scenography evokes a ‘defiguration’ of the walking models and to what effect. Vibskov’s mobile catwalk draws attention to the walk, which is a key element of models’ performance but which usually functions in fashion shows merely to present clothes in the most...

  7. Cheating models

    DEFF Research Database (Denmark)

    Arnoldi, Jakob

    The article discusses the use of algorithmic models for so-called High Frequency Trading (HFT) in finance. HFT is controversial yet widespread in modern financial markets. It is a form of automated trading technology which critics among other things claim can lead to market manipulation. Drawing....... The article analyses these challenges and argues that we witness a new post-social form of human-technology interaction that will lead to a reconfiguration of professional codes for financial trading....

  8. Biomimetic modelling.

    OpenAIRE

    Vincent, Julian F V

    2003-01-01

    Biomimetics is seen as a path from biology to engineering. The only path from engineering to biology in current use is the application of engineering concepts and models to biological systems. However, there is another pathway: the verification of biological mechanisms by manufacture, leading to an iterative process between biology and engineering in which the new understanding that the engineering implementation of a biological system can bring is fed back into biology, allowing a more compl...

  9. Ozone modeling

    Energy Technology Data Exchange (ETDEWEB)

    McIllvaine, C M

    1994-07-01

    Exhaust gases from power plants that burn fossil fuels contain concentrations of sulfur dioxide (SO{sub 2}), nitric oxide (NO), particulate matter, hydrocarbon compounds and trace metals. Estimated emissions from the operation of a hypothetical 500 MW coal-fired power plant are given. Ozone is considered a secondary pollutant, since it is not emitted directly into the atmosphere but is formed from other air pollutants, specifically, nitrogen oxides (NO), and non-methane organic compounds (NMOQ) in the presence of sunlight. (NMOC are sometimes referred to as hydrocarbons, HC, or volatile organic compounds, VOC, and they may or may not include methane). Additionally, ozone formation Alternative is a function of the ratio of NMOC concentrations to NO{sub x} concentrations. A typical ozone isopleth is shown, generated with the Empirical Kinetic Modeling Approach (EKMA) option of the Environmental Protection Agency's (EPA) Ozone Isopleth Plotting Mechanism (OZIPM-4) model. Ozone isopleth diagrams, originally generated with smog chamber data, are more commonly generated with photochemical reaction mechanisms and tested against smog chamber data. The shape of the isopleth curves is a function of the region (i.e. background conditions) where ozone concentrations are simulated. The location of an ozone concentration on the isopleth diagram is defined by the ratio of NMOC and NO{sub x} coordinates of the point, known as the NMOC/NO{sub x} ratio. Results obtained by the described model are presented.

  10. Ozone modeling

    International Nuclear Information System (INIS)

    McIllvaine, C.M.

    1994-01-01

    Exhaust gases from power plants that burn fossil fuels contain concentrations of sulfur dioxide (SO 2 ), nitric oxide (NO), particulate matter, hydrocarbon compounds and trace metals. Estimated emissions from the operation of a hypothetical 500 MW coal-fired power plant are given. Ozone is considered a secondary pollutant, since it is not emitted directly into the atmosphere but is formed from other air pollutants, specifically, nitrogen oxides (NO), and non-methane organic compounds (NMOQ) in the presence of sunlight. (NMOC are sometimes referred to as hydrocarbons, HC, or volatile organic compounds, VOC, and they may or may not include methane). Additionally, ozone formation Alternative is a function of the ratio of NMOC concentrations to NO x concentrations. A typical ozone isopleth is shown, generated with the Empirical Kinetic Modeling Approach (EKMA) option of the Environmental Protection Agency's (EPA) Ozone Isopleth Plotting Mechanism (OZIPM-4) model. Ozone isopleth diagrams, originally generated with smog chamber data, are more commonly generated with photochemical reaction mechanisms and tested against smog chamber data. The shape of the isopleth curves is a function of the region (i.e. background conditions) where ozone concentrations are simulated. The location of an ozone concentration on the isopleth diagram is defined by the ratio of NMOC and NO x coordinates of the point, known as the NMOC/NO x ratio. Results obtained by the described model are presented

  11. Animal models.

    Science.gov (United States)

    Walker, Ellen A

    2010-01-01

    As clinical studies reveal that chemotherapeutic agents may impair several different cognitive domains in humans, the development of preclinical animal models is critical to assess the degree of chemotherapy-induced learning and memory deficits and to understand the underlying neural mechanisms. In this chapter, the effects of various cancer chemotherapeutic agents in rodents on sensory processing, conditioned taste aversion, conditioned emotional response, passive avoidance, spatial learning, cued memory, discrimination learning, delayed-matching-to-sample, novel-object recognition, electrophysiological recordings and autoshaping is reviewed. It appears at first glance that the effects of the cancer chemotherapy agents in these many different models are inconsistent. However, a literature is emerging that reveals subtle or unique changes in sensory processing, acquisition, consolidation and retrieval that are dose- and time-dependent. As more studies examine cancer chemotherapeutic agents alone and in combination during repeated treatment regimens, the animal models will become more predictive tools for the assessment of these impairments and the underlying neural mechanisms. The eventual goal is to collect enough data to enable physicians to make informed choices about therapeutic regimens for their patients and discover new avenues of alternative or complementary therapies that reduce or eliminate chemotherapy-induced cognitive deficits.

  12. Modeling biomembranes.

    Energy Technology Data Exchange (ETDEWEB)

    Plimpton, Steven James; Heffernan, Julieanne; Sasaki, Darryl Yoshio; Frischknecht, Amalie Lucile; Stevens, Mark Jackson; Frink, Laura J. Douglas

    2005-11-01

    Understanding the properties and behavior of biomembranes is fundamental to many biological processes and technologies. Microdomains in biomembranes or ''lipid rafts'' are now known to be an integral part of cell signaling, vesicle formation, fusion processes, protein trafficking, and viral and toxin infection processes. Understanding how microdomains form, how they depend on membrane constituents, and how they act not only has biological implications, but also will impact Sandia's effort in development of membranes that structurally adapt to their environment in a controlled manner. To provide such understanding, we created physically-based models of biomembranes. Molecular dynamics (MD) simulations and classical density functional theory (DFT) calculations using these models were applied to phenomena such as microdomain formation, membrane fusion, pattern formation, and protein insertion. Because lipid dynamics and self-organization in membranes occur on length and time scales beyond atomistic MD, we used coarse-grained models of double tail lipid molecules that spontaneously self-assemble into bilayers. DFT provided equilibrium information on membrane structure. Experimental work was performed to further help elucidate the fundamental membrane organization principles.

  13. To Be or Not to Be Associated: Power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies

    Directory of Open Access Journals (Sweden)

    Elise eVaumourin

    2014-05-01

    Full Text Available A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide statistical tests. Furthermore, they generally test for an overall detection of association and do not identify which parasite is associated with which other one. Here, we developed a new approach, the association screening approach, to detect the overall and the detail of multi-parasite associations. We studied the power of this new approach and of three other known ones (i.e. the generalized chi-square, the network and the multinomial GLM approaches to identify parasite associations either due to parasite interactions or to confounding factors. We applied these four approaches to detect associations within two populations of multi-infected hosts: 1 rodents infected with Bartonella sp., Babesia microti and Anaplasma phagocytophilum and 2 bovine population infected with Theileria sp. and Babesia sp.. We found that the best power is obtained with the screening model and the generalized chi-square test. The differentiation between associations, which are due to confounding factors and parasite interactions was not possible. The screening approach significantly identified associations between Bartonella doshiae and B. microti, and between T. parva, T. mutans and T. velifera. Thus, the screening approach was relevant to test the overall presence of parasite associations and identify the parasite combinations that are significantly over- or under-represented. Unravelling whether the associations are due to real biological interactions or confounding factors should be further investigated. Nevertheless, in the age of genomics and the advent of new technologies, it is a considerable asset to speed up researches focusing on the mechanisms driving interactions

  14. Practice Pattern Variation in Pediatric Eosinophilic Esophagitis in the Carolinas EoE Collaborative: A Research Model in Community and Academic Practices.

    Science.gov (United States)

    Huang, Kevin Z; Jensen, Elizabeth T; Chen, Hannah X; Landes, Lisa E; McConnell, Kristen A; Almond, M Angie; Johnston, Douglas T; Durban, Raquel; Jobe, Laura; Frost, Carrie; Donnelly, Sarah; Antonio, Brady; Safta, Anca M; Quiros, J Antonio; Markowitz, Jonathan E; Dellon, Evan S

    2018-06-01

    Differences in the initial management of pediatric eosinophilic esophagitis (EoE) by practice setting have not been well characterized. We aimed to characterize these differences for sites in the Carolinas EoE Collaborative (CEoEC), a multicenter network of academic and community practices. We performed a retrospective cohort study of pediatric EoE patients at five CEoEC sites: University of North Carolina (UNC) Hospital, Charlotte Asthma and Allergy Specialists, Greenville Health Systems, Wake Forest Baptist Medical Center, and the Medical University of South Carolina Hospital. Cases of EoE were defined by consensus guidelines. Data were extracted from electronic medical records. We tested for differences among sites and used a multinomial model (polytomous regression) to assess associations between treatment and site, adjusting on patient factors. We identified 464 children with EoE across the CEoEC sites. The median age was highest at Wake Forest (11.4 years), the median eosinophil count was highest at UNC (69 eos/hpf), and UNC had the most male patients (82%). UNC used topical steroids for initial treatment in 86% of cases, compared with <1% in Greenville ( P < 0.01). Greenville used dietary elimination more frequently than UNC (81% vs 2%, P < 0.01). Differences in treatment approach held after adjusting for potential baseline confounders. There was no significant association between patient factors and initial treatment approach. Significant differences in EoE patient factors and treatment approaches were identified across CEoEC sites and were not explained by patient or practice factors. This suggests that institutional or provider preferences drive initial treatment approaches, and that more data are needed to drive best practice decisions.

  15. Model visionary

    Energy Technology Data Exchange (ETDEWEB)

    Chandler, Graham

    2011-03-15

    Ken Dedeluk is the president and CEO of Computer Modeling Group (CMG). Dedeluk started his career with Gulf Oil in 1972, worked in computer assisted design; then joined Imperial Esso and Shell, where he became international operations' VP; and finally joined CMG in 1998. CMG made a decision that turned out to be the company's turning point: they decided to provide intensive support and service to their customer to better use their technology. Thanks to this service, their customers' satisfaction grew as well as their revenues.

  16. The Effect of Overskilling Dynamics on Wages

    Science.gov (United States)

    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…

  17. Determinants of farmers' perception of land degradation and ...

    African Journals Online (AJOL)

    The study investigated farmers' perception of land degradation, and adoption of soil conservation practices using a two-stage decision making process. The data for the study were collected with the aid of structured questionnaire and analyzed with descriptive analysis and simultaneous probit model. The results show ...

  18. Socio-economic impacts and determinants of parasitic weed infestation in rainfed rice systems of sub-Saharan Africa

    NARCIS (Netherlands)

    N'cho, A.S.

    2014-01-01

    Keywords: rice; weed; weed management practices, adoption, impact, parasitic weeds; Rhamphicarpa fistulosa; Striga asiatica; Striga hermonthica, double hurdle model; multivariate probit, productivity, stochastic frontier analysis, data

  19. Land degradation and adoption of soil conservation technologies ...

    African Journals Online (AJOL)

    The study investigates the causes of land degradation, and adoption of soil conservation practices using a two-stage decision making process. The data for the study were collected with the aid of structured questionnaire and analyzed with descriptive analysis, difference regression equation and simultaneous probit model.

  20. Factors influencing the stay-exit intention of small livestock farmers

    NARCIS (Netherlands)

    Carter-Leal, Luis M.; Oude-Lansink, Alfons; Saatkamp, Helmut

    2018-01-01

    This study analyses the factors driving the stay-exit intention of small livestock farmers located in southern Chile. Technical, economic, and social characteristics from 212 farmers were included in this study. Through an empirical probit model we identified the variables that should be considered

  1. Explaining Preferences and Actual Involvement in Self-Employment: New Insights into the Role of Gender

    NARCIS (Netherlands)

    I. Verheul (Ingrid); A.R. Thurik (Roy); I. Grilo (Isabel)

    2008-01-01

    textabstractThis paper investigates why women’s self-employment rates are consistently lower than those of men. It has three focal points. It discriminates between the preference for self-employment and actual involvement in self-employment using a two (probit) equation model. It makes a systematic

  2. Grades as Information

    Science.gov (United States)

    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…

  3. Reasons for U.S. Producer Selection of a Goat Enterprise

    OpenAIRE

    Dunn, Brittany; Nyaupane, Narayan; Gillispie, Jeffrey; McMillan, Kenneth

    2014-01-01

    This paper addresses 14 possible reasons why meat goat producers selected to engage in meat goat production, with results having implications for research, extension, and teaching efforts. A survey of meat goat producers was conducted. Reasons for entering meat goat production were assessed and analyzed using ordered probit models.

  4. A comparison between Daphnia pulex and Hydra vulgaris as ...

    African Journals Online (AJOL)

    2017-04-02

    Apr 2, 2017 ... dependence thereon, has led not only to valuable products ... effects, estimating environmental risk based on measured ... The LC50-values were statistically determined using the EPA Probit Analysis Model ..... and organic contaminants. ..... green algae on the response of Hydra viridissima (Pallas 1776).

  5. Determinants of firms' investment behaviour : a multilevel approach

    NARCIS (Netherlands)

    Farla, K.

    2013-01-01

    This paper investigates micro and macro determinants of firms' investment behaviour using firm data from 101 developing and emerging economies. A substantial number of firms in our sample does not invest in fixed capital or invests little relative to sales revenue. Using a multilevel probit model we

  6. The British American Tobacco out growers scheme: Determinants of ...

    African Journals Online (AJOL)

    The study analyzed the operation and performance of Tobacco Out grower Scheme in Oyo State, Nigeria. The data for the analysis came from a random sample survey of the area of study. The treatment effect model was adopted in analyzing the data. Evidence from the probit analysis indicates that membership of the ...

  7. Econometric analyses of microfinance credit group formation, contractual risks and welfare impacts in Northern Ethiopia

    NARCIS (Netherlands)

    Berhane Tesfay, G.

    2009-01-01

    Key words
    Microfinance, joint liability, contractual risk, group formation, risk-matching, impact evaluation, Panel data econometrics, dynamic panel probit, trend models, fixed-effects, composite counterfactuals, propensity score matching, farm households, Ethiopia.

    Lack of

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

    Science.gov (United States)

    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…

  9. Credit Default Risk and its Determinants of Microfinance Industry in ...

    African Journals Online (AJOL)

    user

    limitations prevailed in the selected 6 MFIs in Ethiopia schemed by determining the ... the probit model show that education, income, loan supervision, suitability of repayment ..... of Ethiopia as Large, Medium, and Small MFIs. ..... /sigma. 0.5177089. 0.0467682. *significant at 1%. ***significant at 10% .... businesses default.

  10. A multivariate analysis of factors affecting adoption of improved ...

    African Journals Online (AJOL)

    This paper analyzes the synergies/tradeoffs involved in the adoption of improved varieties of multiple crops in the mixed crop-livestock production systems of the highlands of Ethiopia A multivariate probit (MVP) model involving a system of four equations for the adoption decision of improved varieties of barley, potatoes, ...

  11. Incidence and Severity of Poverty among Oyan Lake Host ...

    African Journals Online (AJOL)

    It is recommended that development oriented policies aimed at discouraging early marriages, polygamy, having improved family planning, housing scheme, education and access to loans should be given consideration for these communities. Keywords: Host communities, Poverty, Household, Multivariate Probit Model, ...

  12. Firm-Level Determinants of Exporting Behaviour: Evidence from ...

    African Journals Online (AJOL)

    This paper uses firm-level panel data to investigate the exporting behaviour of the Kenyan manufacturing firms. Using probit and tobit regression models, the results obtained show that factors determining the decision to export are different from those affecting the share exported. Likewise, factors determining exporting ...

  13. Getting stuck, falling behind or moving forward

    DEFF Research Database (Denmark)

    Walelign, Solomon Zena

    2017-01-01

    Research on household livelihood dynamics is central to rural poverty reduction. In this paper, we adopt a three-wave panel dataset to explore the persistence of and transitions in household livelihoods in three districts of Nepal using duration and dynamic probit models. The results demonstrate ...

  14. Exploring National Concerted Practices in an Open Small Economy : What Does the Change in the Competition Law in the Netherlands Reveal?

    NARCIS (Netherlands)

    Ozbugday, F.C.

    2011-01-01

    The present study examines the impact of several industry characteristics on the propensity to collude using a dataset on the existence of collusion across Dutch industries during the late 1990s and early 2000s. The results of the Probit model with sample selection indicate that our sample of Dutch

  15. Gender differences, HIV risk perception and condom use

    NARCIS (Netherlands)

    Lammers, J.; van Wijnbergen, S.; Willebrands, D.

    This paper analyzes how different types of HIV-knowledge influence condom use across the sexes. The empirical work is based on a household survey conducted among 1,979 households of a representative group of market persons in Lagos in 2008. Last time condom use is analyzed based on a Probit model

  16. Video games playing: A substitute for cultural consumptions?

    DEFF Research Database (Denmark)

    Borowiecki, Karol Jan; Prieto-Rodriguez, Juan

    2015-01-01

    This article provides an applied investigation of video game usage. Using data for Spain, we estimate zero-inflated ordered probit models to control for an excess of zeros in our ordinal dependent variable. We find that the probability of game playing increases with the consumption of other...

  17. Education choices in Ethiopia: what determines whether poor households send their children to school?

    NARCIS (Netherlands)

    Woldehanna, T.; Mekonnen, A.; Jones, N.

    2008-01-01

    The paper uses data from a 2002 survey of 1000 rural and urban households with eight-year old children sampled from food insecure communities in Tigray, Amhara, Oromia, SNNP and Addis Ababa Regional States. Using a probit regression model, we investigated external factors associated with child

  18. Factors leading to inflation targeting : The impact of adoption

    NARCIS (Netherlands)

    Samarina, Anna; Sturm, Jan-Egbert

    2013-01-01

    This paper examines how the analysis of inflation targeting (IT) adoption is affected by allowing for a structural change after adoption, using panel probit models for 60 countries over the period 1985-2008. Our findings suggest that there is a structural change after IT adoption. Including the

  19. Factors leading to inflation targeting - the impact of adoption

    NARCIS (Netherlands)

    Samarina, Anna; Sturm, Jan-Egbert

    2013-01-01

    This paper examines how the analysis of inflation targeting (IT) adoption is affected by the choice of the analyzed period. We test whether country characteristics influence the decision to apply IT differently before and after its adoption, using panel probit models for 60 countries over the period

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

    Science.gov (United States)

    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…