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...

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.

Sample size determination for logistic regression on a logit-normal distribution.

Science.gov (United States)

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

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...

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.

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.

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

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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.

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

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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

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.

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

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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.

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

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

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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.

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...

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.

Unobserved Heterogeneity in the Binary Logit Model with Cross-Sectional Data and Short Panels

DEFF Research Database (Denmark)

Holm, Anders; Jæger, Mads Meier; Pedersen, Morten

This paper proposes a new approach to dealing with unobserved heterogeneity in applied research using the binary logit model with cross-sectional data and short panels. Unobserved heterogeneity is particularly important in non-linear regression models such as the binary logit model because, unlike...... in linear regression models, estimates of the effects of observed independent variables are biased even when omitted independent variables are uncorrelated with the observed independent variables. We propose an extension of the binary logit model based on a finite mixture approach in which we conceptualize...

"Logits and Tigers and Bears, Oh My! A Brief Look at the Simple Math of Logistic Regression and How It Can Improve Dissemination of Results"

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Jason W. Osborne

2012-06-01

Full Text Available Logistic regression is slowly gaining acceptance in the social sciences, and fills an important niche in the researcher's toolkit: being able to predict important outcomes that are not continuous in nature. While OLS regression is a valuable tool, it cannot routinely be used to predict outcomes that are binary or categorical in nature. These outcomes represent important social science lines of research: retention in, or dropout from school, using illicit drugs, underage alcohol consumption, antisocial behavior, purchasing decisions, voting patterns, risky behavior, and so on. The goal of this paper is to briefly lead the reader through the surprisingly simple mathematics that underpins logistic regression: probabilities, odds, odds ratios, and logits. Anyone with spreadsheet software or a scientific calculator can follow along, and in turn, this knowledge can be used to make much more interesting, clear, and accurate presentations of results (especially to non-technical audiences. In particular, I will share an example of an interaction in logistic regression, how it was originally graphed, and how the graph was made substantially more user-friendly by converting the original metric (logits to a more readily interpretable metric (probability through three simple steps.

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

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.

Environmental regulations and plant exit: A logit analysis based on established panel data

Energy Technology Data Exchange (ETDEWEB)

Bioern, E; Golombek, R; Raknerud, A

1995-12-01

This publication uses a model to study the relationship between environmental regulations and plant exit. It has the main characteristics of a multinomial qualitative response model of the logit type, but also has elements of a Markov chain model. The model uses Norwegian panel data for establishments in three manufacturing sectors with high shares of units which have been under strict environmental regulations. In two of the sectors, the exit probability of non-regulated establishments is about three times higher than for regulated ones. It is also found that the probability of changing regulation status from non-regulated to regulated depends significantly on economic factors. In particular, establishments with weak profitability are the most likely to become subject to environmental regulation. 12 refs., 2 figs., 6 tabs.

Analysis of RIA standard curve by log-logistic and cubic log-logit models

International Nuclear Information System (INIS)

Yamada, Hideo; Kuroda, Akira; Yatabe, Tami; Inaba, Taeko; Chiba, Kazuo

1981-01-01

In order to improve goodness-of-fit in RIA standard analysis, programs for computing log-logistic and cubic log-logit were written in BASIC using personal computer P-6060 (Olivetti). Iterative least square method of Taylor series was applied for non-linear estimation of logistic and log-logistic. Hear ''log-logistic'' represents Y = (a - d)/(1 + (log(X)/c)sup(b)) + d As weights either 1, 1/var(Y) or 1/σ 2 were used in logistic or log-logistic and either Y 2 (1 - Y) 2 , Y 2 (1 - Y) 2 /var(Y), or Y 2 (1 - Y) 2 /σ 2 were used in quadratic or cubic log-logit. The term var(Y) represents squares of pure error and σ 2 represents estimated variance calculated using a following equation log(σ 2 + 1) = log(A) + J log(y). As indicators for goodness-of-fit, MSL/S sub(e)sup(2), CMD% and WRV (see text) were used. Better regression was obtained in case of alpha-fetoprotein by log-logistic than by logistic. Cortisol standard curve was much better fitted with cubic log-logit than quadratic log-logit. Predicted precision of AFP standard curve was below 5% in log-logistic in stead of 8% in logistic analysis. Predicted precision obtained using cubic log-logit was about five times lower than that with quadratic log-logit. Importance of selecting good models in RIA data processing was stressed in conjunction with intrinsic precision of radioimmunoassay system indicated by predicted precision. (author)

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

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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.

Numerical proceessing of radioimmunoassay results using logit-log transformation method

International Nuclear Information System (INIS)

Textoris, R.

1983-01-01

The mathematical model and algorithm are described of the numerical processing of the results of a radioimmunoassay by the logit-log transformation method and by linear regression with weight factors. The limiting value of the curve for zero concentration is optimized with regard to the residual sum by the iterative method by multiple repeats of the linear regression. Typical examples are presented of the approximation of calibration curves. The method proved suitable for all hitherto used RIA sets and is well suited for small computers with internal memory of min. 8 Kbyte. (author)

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

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

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.

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…

Relating cost-benefit analysis results with transport project decisions in the Netherlands

NARCIS (Netherlands)

Annema, Jan Anne; Frenken, Koen|info:eu-repo/dai/nl/207145253; Koopmans, Carl; Kroesen, Maarten

2017-01-01

This paper relates the cost-benefit analysis (CBA) results of transportation policy proposals in the Netherlands with the decision to implement or abandon the proposal. The aim of this study is to explore the relation between the CBA results and decision-making. Multinomial logit regression models

Relating cost-benefit analysis results with transport project decisions in the Netherlands

NARCIS (Netherlands)

Annema, J.A.; Frenken, Koen; Koopmans, Carl; Kroesen, M.

2017-01-01

This paper relates the cost-benefit analysis (CBA) results of transportation policy proposals in the Netherlands with the decision to implement or abandon the proposal. The aim of this study is to explore the relation between the CBA results and decision-making. Multinomial logit regression

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.

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

Science.gov (United States)

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

2014-07-01

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

Farmers' choice of cattle marketing channels under transaction cost ...

African Journals Online (AJOL)

The theoretical predictions of transaction cost economics were tested based on primary data collected from 230 cattle farm households in 13 communities of the Okhahlamba Local Municipality. The results of a multinomial logit regression revealed some unique insights. They showed that the probability of selling at auction ...

An Analysis of Losses to the Southern Commercial Timberland Base

Science.gov (United States)

Ian A. Munn; David Cleaves

1998-01-01

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

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.

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.

Un procedimiento para selección de los modelos Logit Mixtos

OpenAIRE

Ruíz Gallegos, José de Jesús

2004-01-01

En el presente trabajo se hace una revisión de dos modelos que han tenido una fuerte aplicabilidad en los problemas de elecciones discretas: El modelo Logit y el modelo Logit Mixto. Además, se propone el uso del estadístico de Cox para seleccionar modelos, en el modelo Logit Mixto.

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.

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.

Ordered LOGIT Model approach for the determination of financial distress.

Science.gov (United States)

Kinay, B

2010-01-01

Nowadays, as a result of the global competition encountered, numerous companies come up against financial distresses. To predict and take proactive approaches for those problems is quite important. Thus, the prediction of crisis and financial distress is essential in terms of revealing the financial condition of companies. In this study, financial ratios relating to 156 industrial firms that are quoted in the Istanbul Stock Exchange are used and probabilities of financial distress are predicted by means of an ordered logit regression model. By means of Altman's Z Score, the dependent variable is composed by scaling the level of risk. Thus, a model that can compose an early warning system and predict financial distress is proposed.

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.

Age and pedestrian injury severity in motor-vehicle crashes: a heteroskedastic logit analysis.

Science.gov (United States)

Kim, Joon-Ki; Ulfarsson, Gudmundur F; Shankar, Venkataraman N; Kim, Sungyop

2008-09-01

This research explores the injury severity of pedestrians in motor-vehicle crashes. It is hypothesized that the variance of unobserved pedestrian characteristics increases with age. In response, a heteroskedastic generalized extreme value model is used. The analysis links explanatory factors with four injury outcomes: fatal, incapacitating, non-incapacitating, and possible or no injury. Police-reported crash data between 1997 and 2000 from North Carolina, USA, are used. The results show that pedestrian age induces heteroskedasticity which affects the probability of fatal injury. The effect grows more pronounced with increasing age past 65. The heteroskedastic model provides a better fit than the multinomial logit model. Notable factors increasing the probability of fatal pedestrian injury: increasing pedestrian age, male driver, intoxicated driver (2.7 times greater probability of fatality), traffic sign, commercial area, darkness with or without streetlights (2-4 times greater probability of fatality), sport-utility vehicle, truck, freeway, two-way divided roadway, speeding-involved, off roadway, motorist turning or backing, both driver and pedestrian at fault, and pedestrian only at fault. Conversely, the probability of a fatal injury decreased: with increasing driver age, during the PM traffic peak, with traffic signal control, in inclement weather, on a curved roadway, at a crosswalk, and when walking along roadway.

Pricing and lot sizing optimization in a two-echelon supply chain with a constrained Logit demand function

Directory of Open Access Journals (Sweden)

Yeison Díaz-Mateus

2017-07-01

Full Text Available Decision making in supply chains is influenced by demand variations, and hence sales, purchase orders and inventory levels are therefore concerned. This paper presents a non-linear optimization model for a two-echelon supply chain, for a unique product. In addition, the model includes the consumers’ maximum willingness to pay, taking socioeconomic differences into account. To do so, the constrained multinomial logit for discrete choices is used to estimate demand levels. Then, a metaheuristic approach based on particle swarm optimization is proposed to determine the optimal product sales price and inventory coordination variables. To validate the proposed model, a supply chain of a technological product was chosen and three scenarios are analyzed: discounts, demand segmentation and demand overestimation. Results are analyzed on the basis of profits, lotsizing and inventory turnover and market share. It can be concluded that the maximum willingness to pay must be taken into consideration, otherwise fictitious profits may mislead decision making, and although the market share would seem to improve, overall profits are not in fact necessarily better.

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.

Analisis Faktor yang Mempengaruhi Tingkat Kesehatan Bank dengan Regresi Logit

Directory of Open Access Journals (Sweden)

Titik Aryati

2007-09-01

Full Text Available The article aims to find the probability effects of bank’s health level using CAMEL ratio analysis. The statistic method used to test on the research hypothesis was logit regression. The dependent variable used in this research was bank’s health level and independent variables were CAMEL financial ratios consisting of CAR, NPL, ROA, ROE, LDR, and NIM. The report data were extracted from bank’s financial from financial report, which had been published and accumulated by Infobank research bureau with valuation, based on bank Indonesia policy. The sample consisted of 60 healthy banks and 14 unhealthy banks in 2005 and 2006. The empirical result of this research indicates that the Non Performing Loan is the significant variable affecting bank health level.

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.

Boosted beta regression.

Directory of Open Access Journals (Sweden)

Matthias Schmid

Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

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.

Gaussian Process Regression Model in Spatial Logistic Regression

Science.gov (United States)

Sofro, A.; Oktaviarina, A.

2018-01-01

Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

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

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.

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

Working Paper 175 - Youth Employment in Africa: New Evidence and Policies from Swaziland

OpenAIRE

Zuzana Brixiova; Thierry Kangoye

2013-01-01

Drawing on the 2007 and 2010 Swaziland Labor Force Surveys, this paper provides first systematic evidence on recent youth employment challenges in Swaziland, a small, land-locked, middle-income country with one of the highest youth unemployment rates in Africa. The paper first documents the various labor market disadvantages faced by the Swazi youth, such as high unemployment and discouragement, and how they changed from 2007 to 2010. A multinomial logit regression analysis is carried out to ...

Youth Employment in Africa: New Evidence and Policies from Swaziland

OpenAIRE

Brixiova, Zuzana; Kangoye, Thierry

2013-01-01

Drawing on the 2007 and 2010 Swaziland Labor Force Surveys, this paper provides first systematic evidence on recent youth employment challenges in Swaziland, a small, land-locked, middle-income country with one of the highest youth unemployment rates in Africa. The paper first documents the various labor market disadvantages faced by the Swazi youth, such as high unemployment and discouragement, and how they changed from 2007 to 2010. A multinomial logit regression analysis is then carried ou...

A hipótese de Cressey (1953) e a investigação da ocorrência de fraudes corporativas: uma análise empírica em instituições bancárias brasileiras

OpenAIRE

Machado, Michele Rílany Rodrigues; Gartner, Ivan Ricardo

2017-01-01

ABSTRACT This article fills a technical-scientific gap that currently exists in the Brazilian literature on corporative fraud, by combining the theoretical framework of agency theory, of criminology, and of the economics of crime. In addition, it focuses on a sector that is usually excluded from analyses due to its specific characteristics and shows the application of multinomial logit panel data regression with random effects, which is rarely used in studies in the area of accounting. The ai...

The Cressey hypothesis (1953) and an investigation into the occurrence of corporate fraud: an empirical analysis conducted in Brazilian banking institutions

OpenAIRE

Michele Rílany Rodrigues Machado; Ivan Ricardo Gartner

2017-01-01

ABSTRACT This article fills a technical-scientific gap that currently exists in the Brazilian literature on corporative fraud, by combining the theoretical framework of agency theory, of criminology, and of the economics of crime. In addition, it focuses on a sector that is usually excluded from analyses due to its specific characteristics and shows the application of multinomial logit panel data regression with random effects, which is rarely used in studies in the area of accounting. The ai...

Linking apple farmers to markets: Determinants and impacts of marketing contracts in China

OpenAIRE

Ma, Wanglin; Abdulai, Awudu

2015-01-01

This study investigates the determinants of marketing contract choices and the related impact on farm net returns of apple farmers in China. We employ a two-stage selection correction approach (BFG) for the multinomial logit model. On the basis of the BFG estimation, we also use an endogenous switching regression model and a propensity score matching technique to estimate the causal effects of marketing contract choices on net returns. The empirical results reveal that written contracts incre...

How do we value our income from which we save?

OpenAIRE

Barbara Liberda; Marek Pęczkowski; Ewa Gucwa-Leśny

2011-01-01

In this paper we analyze the relationship between the perception of income as satisfying household needs and saving rate of this household. Using the multinomial logit regression function we measure the probability of a household to fall into one of the groups categorized by the subjective perception of income in relation to the current household disposable income. The variable specified for the valuation of income is income perception, defined as a class of observed disposable income located...

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

Science.gov (United States)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

Generalised Partially Linear Regression with Misclassified Data and an Application to Labour Market Transitions

DEFF Research Database (Denmark)

Dlugosz, Stephan; Mammen, Enno; Wilke, Ralf

We consider the semiparametric generalised linear regression model which has mainstream empirical models such as the (partially) linear mean regression, logistic and multinomial regression as special cases. As an extension to related literature we allow a misclassified covariate to be interacted...

Pricing Mining Concessions Based on Combined Multinomial Pricing Model

Directory of Open Access Journals (Sweden)

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.

DETEKSI DINI KRISIS PERBANKAN INDONESIA: IDENTIFIKASI VARIABEL MAKRO DENGAN MODEL LOGIT

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Shanty Oktavilia

2012-01-01

Full Text Available Indonesia suffered from banking crisis for several times. It was the effect of the worst crisis occurredin 1997. Actually, Bath Thailand which plunged into 27,8% at the third quarter of the year 1997 was thebeginning problem that caused Asia currency crisis. This study analyzes the influence of macro indicatoras an early warning system by using logit econometrics model for predicting the possibilities of bankingcrisis that may occur in Indonesia.Kewords: Banking Crisis, macro economic indicator, EWS-logit model

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...

MEMPREDIKSI FINANCIAL DISTRESS DENGAN BINARY LOGIT REGRESSION PERUSAHAAN TELEKOMUNIKASI

Directory of Open Access Journals (Sweden)

Tiara Widya Antikasari

2017-04-01

Full Text Available In this globalization era, sub–sector telecommunication industry has rapid development as time goes by with the number of customers’ growth. However, its growth is not balanced with operational revenue development. Therefore, it is important to analyze the financial distress in telecommunication companies in order to avoid bankruptcy. This research aimed to investigate the effect of financial ratios to predict probability of financial distress. Financial ratios indicator used profitability ratio, liquidity ratio, activity ratio, and leverage ratio. The population in this research was telecommunication companies listed in the Indonesia Stock Exchange periods 2009-2016. Based on purposive sampling method, the criteria of financial distress in this study was measured by using net operation negative two years, while statistic analysis used was logistic regression with a significance level of 10%. The result was that liquidity ratio (current ratio and activity ratio (total asset turnover ratio had a negative significant value, and profitability ratio(return on asset and leverage ratio (debt to total asset had positive significant value to predict financial distress.

National and international graduate migration flows.

Science.gov (United States)

Mosca, Irene; Wright, Robert E

2010-01-01

This article examines the nature of national and international graduate migration flows in the UK. Migration equations are estimated with microdata from a matched dataset of Students and Destinations of Leavers from Higher Education, information collected by the Higher Education Statistical Agency. The probability of migrating is related to a set of observable characteristics using multinomial logit regression. The analysis suggests that migration is a selective process with graduates with certain characteristics having considerably higher probabilities of migrating, both to other regions of the UK and abroad.

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

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.

A nested recursive logit model for route choice analysis

DEFF Research Database (Denmark)

Mai, Tien; Frejinger, Emma; Fosgerau, Mogens

2015-01-01

choices and the model does not require any sampling of choice sets. Furthermore, the model can be consistently estimated and efficiently used for prediction.A key challenge lies in the computation of the value functions, i.e. the expected maximum utility from any position in the network to a destination....... The value functions are the solution to a system of non-linear equations. We propose an iterative method with dynamic accuracy that allows to efficiently solve these systems.We report estimation results and a cross-validation study for a real network. The results show that the NRL model yields sensible......We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link...

STAS and Logit Modeling of Advertising and Promotion Effects

DEFF Research Database (Denmark)

Hansen, Flemming; Yssing Hansen, Lotte; Grønholdt, Lars

2002-01-01

This paper describes the preliminary studies of the effect of advertising and promotion on purchases using the British single-source database Adlab. STAS and logit modeling are the two measures studied. Results from the two measures have been compared to determine the extent to which, they give...

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

Spatial age-length key modelling using continuation ratio logits

DEFF Research Database (Denmark)

Berg, Casper W.; Kristensen, Kasper

2012-01-01

-called age-length key (ALK) is then used to obtain the age distribution. Regional differences in ALKs are not uncommon, but stratification is often problematic due to a small number of samples. Here, we combine generalized additive modelling with continuation ratio logits to model the probability of age...

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

Science.gov (United States)

John Hogland; Nedret Billor; Nathaniel Anderson

2013-01-01

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

Comparison of IRT Likelihood Ratio Test and Logistic Regression DIF Detection Procedures

Science.gov (United States)

Atar, Burcu; Kamata, Akihito

2011-01-01

The Type I error rates and the power of IRT likelihood ratio test and cumulative logit ordinal logistic regression procedures in detecting differential item functioning (DIF) for polytomously scored items were investigated in this Monte Carlo simulation study. For this purpose, 54 simulation conditions (combinations of 3 sample sizes, 2 sample…

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.

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...

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...

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...

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

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

Determinants of Agricultural Diversification in a Hotspot Area: Evidence from Colonist and Indigenous Communities in the Sumaco Biosphere Reserve, Ecuadorian Amazon

Directory of Open Access Journals (Sweden)

Bolier Torres

2018-05-01

Full Text Available With data from a household survey covering migrant settlers and indigenous (Kichwa communities in the Sumaco Biosphere Reserve (SBR, this study analyses the drivers of agricultural diversification/specialisation, focusing on the role of ethnicity and the livelihood strategies (LS they follow. Data were collected using the Poverty and Environment Network methodology of the Center for International Forestry Research (CIFOR-PEN. In order to establish the drivers of agricultural diversification, the number of crops and the Shannon index of crops areas were used as the dependent variables in ordinary least square (OLS models, while a multinomial logit model (MLM was used to assess a household’s degree of diversification. The results of the OLS regression provides evidence supporting the notion that households, with Livestock-based and Wage-based livelihood strategies (LS are less diversified and more specialized than households with Crop-based LS. Ethnicity has a positive and significant effect on agricultural diversification, with Kichwa farms more diversified than those of their migrant colonist counterparts. The results of the multinomial logit model (MLM show that large Kichwa households, with Crop-based and Forest-based LS are more likely to adopt a highly diversified agricultural strategy. Based on these findings, we recommend a redirection of agricultural incentives, towards the adoption of diversified agricultural systems, as a strategy to promote more sustainable production systems in the Ecuadorian Amazon Region.

Construction of risk prediction model of type 2 diabetes mellitus based on logistic regression

Directory of Open Access Journals (Sweden)

Li Jian

2017-01-01

Full Text Available Objective: to construct multi factor prediction model for the individual risk of T2DM, and to explore new ideas for early warning, prevention and personalized health services for T2DM. Methods: using logistic regression techniques to screen the risk factors for T2DM and construct the risk prediction model of T2DM. Results: Male’s risk prediction model logistic regression equation: logit(P=BMI × 0.735+ vegetables × (−0.671 + age × 0.838+ diastolic pressure × 0.296+ physical activity× (−2.287 + sleep ×(−0.009 +smoking ×0.214; Female’s risk prediction model logistic regression equation: logit(P=BMI ×1.979+ vegetables× (−0.292 + age × 1.355+ diastolic pressure× 0.522+ physical activity × (−2.287 + sleep × (−0.010.The area under the ROC curve of male was 0.83, the sensitivity was 0.72, the specificity was 0.86, the area under the ROC curve of female was 0.84, the sensitivity was 0.75, the specificity was 0.90. Conclusion: This study model data is from a compared study of nested case, the risk prediction model has been established by using the more mature logistic regression techniques, and the model is higher predictive sensitivity, specificity and stability.

Multiple equilibria and limit cycles in evolutonary games with Logit Dynamics

NARCIS (Netherlands)

Hommes, C.H.; Ochea, M.I.

2012-01-01

This note shows, by means of two simple, three-strategy games, the existence of stable periodic orbits and of multiple, interior steady states in a smooth version of the Best-Response Dynamics, the Logit Dynamics. The main finding is that, unlike Replicator Dynamics, generic Hopf bifurcation and

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.

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 ...

Logit Estimation of a Gravity Model of the College Enrollment Decision.

Science.gov (United States)

Leppel, Karen

1993-01-01

A study investigated the factors influencing students' decisions about attending a college to which they had been admitted. Logit analysis confirmed gravity model predictions that geographic distance and student ability would most influence the enrollment decision and found other variables, although affecting earlier stages of decision making, did…

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.

—: 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...

Associations of financial stressors and physical intimate partner violence perpetration.

Science.gov (United States)

Schwab-Reese, Laura M; Peek-Asa, Corinne; Parker, Edith

2016-12-01

Contextual factors, such as exposure to stressors, may be antecedents to IPV perpetration. These contextual factors may be amenable to modification through intervention and prevention. However, few studies have examined specific contextual factors. To begin to address this gap, we examined the associations between financial stressors and three types of physical IPV perpetration. This analysis used data from Wave IV of The National Longitudinal Study of Adolescent to Adult Health. We used logistic regression to examine the associations of financial stressors and each type of IPV (minor, severe, causing injury), and multinomial logit regression to examine the associations of financial stressors and patterns of co-occurring types of IPV perpetration (only minor; only severe; minor and severe; minor, severe, and causing injury; compared with no perpetration). Fewer men perpetrated threats/minor physical IPV (6.7 %) or severe physical IPV (3.4 %) compared with women (11.4 % and 8.8 %, respectively). However, among physical IPV perpetrators, a higher percentage of men (32.0 %) than women (21.0 %) reported their partner was injured as a result of the IPV. In logistic regression models of each type of IPV perpetration, both the number of stressors experienced and several types of financial stressors were associated with perpetrating each type of IPV. Utilities nonpayment, housing nonpayment, food insecurity, and no phone service were associated with increased odds of perpetrating each form of IPV in adjusted analysis. Eviction was associated with perpetrating severe physical IPV but not threats/minor IPV or IPV causing injury. In multinomial logit regression comparing patterns of IPV perpetration to perpetrating no physical IPV, the relationships of financial stressors were less consistent. Food insecurity was associated with perpetrating only minor physical IPV. Comparatively, overall number of financial stressors and four types of financial stressors (utilities

Assessment of Poisson, logit, and linear models for genetic analysis of clinical mastitis in Norwegian Red cows.

Science.gov (United States)

Vazquez, A I; Gianola, D; Bates, D; Weigel, K A; Heringstad, B

2009-02-01

Clinical mastitis is typically coded as presence/absence during some period of exposure, and records are analyzed with linear or binary data models. Because presence includes cows with multiple episodes, there is loss of information when a count is treated as a binary response. The Poisson model is designed for counting random variables, and although it is used extensively in epidemiology of mastitis, it has rarely been used for studying the genetics of mastitis. Many models have been proposed for genetic analysis of mastitis, but they have not been formally compared. The main goal of this study was to compare linear (Gaussian), Bernoulli (with logit link), and Poisson models for the purpose of genetic evaluation of sires for mastitis in dairy cattle. The response variables were clinical mastitis (CM; 0, 1) and number of CM cases (NCM; 0, 1, 2, ..). Data consisted of records on 36,178 first-lactation daughters of 245 Norwegian Red sires distributed over 5,286 herds. Predictive ability of models was assessed via a 3-fold cross-validation using mean squared error of prediction (MSEP) as the end-point. Between-sire variance estimates for NCM were 0.065 in Poisson and 0.007 in the linear model. For CM the between-sire variance was 0.093 in logit and 0.003 in the linear model. The ratio between herd and sire variances for the models with NCM response was 4.6 and 3.5 for Poisson and linear, respectively, and for model for CM was 3.7 in both logit and linear models. The MSEP for all cows was similar. However, within healthy animals, MSEP was 0.085 (Poisson), 0.090 (linear for NCM), 0.053 (logit), and 0.056 (linear for CM). For mastitic animals the MSEP values were 1.206 (Poisson), 1.185 (linear for NCM response), 1.333 (logit), and 1.319 (linear for CM response). The models for count variables had a better performance when predicting diseased animals and also had a similar performance between them. Logit and linear models for CM had better predictive ability for healthy

Farmers’ Adaptation Strategies to Climate Change and Their Implications in the Zou Department of South Benin

Directory of Open Access Journals (Sweden)

Adégnandjou Mahouna Roland Fadina

2018-01-01

Full Text Available Climate change is a global phenomenon. Its impact on agricultural activities in developing countries has increased dramatically. Understanding how farmers perceive climate change and how they adapt to it is very important to the implementation of adequate policies for agricultural and food security. This paper aims to contribute to an understanding of farmers’ adaptation choices, determinants of the adaptation choices and the long-term implications of the adaptation choices. Data were collected from 120 respondents in the Zou Department of Benin. A binary logit model was used to analyze the factors influencing household decisions to adapt to climate change. Multinomial logistic regression analysis was estimated to analyze the factors influencing households’ choice of adaptation strategies to climate change. The results show that farmers have a developed perception of climate change. These changes are translated by rainfall disturbances (rainfall delays, early cessation, bad rainfall distribution etc., shortening of the small dry season, increasing of temperature and sometimes, violent winds. The survey reveals that Benin farmers adopt many strategies in response to climate change. These strategies include “Crop–livestock diversification and other good practices (mulching, organic fertilizer,” “Use of improved varieties, chemical fertilizers and pesticides,” “Agroforestry and perennial plantation” and “Diversification of income-generating activities.” The findings also reveal that most of the respondents use these strategies in combination. From the binary logit model, we know that “farming experience” and “educational level of household head” positively influence adaptation decisions. The result of the multinomial logit analysis shows that farming experience, educational level, farm size and gender have a significant impact on climate change adaptation strategies. Based on in-depth analysis of each strategy, we

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…

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, ...

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...

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.

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

Mixed logit model of intended residential mobility in renovated historical blocks in China

NARCIS (Netherlands)

Jiang, W.; Timmermans, H.J.P.; Li, H.; Feng, T.

2016-01-01

Using data from 8 historical blocks in China, the influence of socialdemographic characteristics and residential satisfaction on intended residentialmobility is analysed. The results of a mixed logit model indicate that higher residential satisfaction will lead to a lower intention to move house,

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...

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.

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...

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

Why entrepreneurs do not expect their businesses: lessons from Lithuania.

NARCIS (Netherlands)

Aidis, R.K.; Mickiewicz, T.

2006-01-01

This article applies a multinomial logit estimator to investigate which factors affect SME owners' expectations to grow their businesses in Lithuania. Our findings provide evidence that SME owners' human capital (education) matters and that growth expectations are positively related to exporting. In

Employees’ Preferences for more or fewer Working Hours. The Effects of Usual, Contractual and Standard Working Time, Family Phase and Household Characteristics, and Job Satisfaction

NARCIS (Netherlands)

Tijdens, K.

2002-01-01

This study seeks explanations for working time preferences, using cross-sectional multinomial logits for the 2001/2002 Wage Indicator dataset (N=21,727). As expected, the preferences are predominately influenced by working hours’ characteristics, showing that employees with long hours prefer to work

Users evaluation of transport mode characteristics with special attention to public transport

NARCIS (Netherlands)

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

2007-01-01

The paper focuses on the influence of public transport use on the evaluation of transport mode characteristics. Based on stated choice data, several multinomial logit models that include parameters representing differences between users and non-users of public transport are estimated. The estimation

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

Science.gov (United States)

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

Ordering the preference hierarchies for internal finance, bank laons, bond and share issue: evidence from Dutch firms

NARCIS (Netherlands)

de Haan, L.; Hinloopen, J.

2003-01-01

We estimate the incremental financing decision for a sample of some 150 Dutch companies for the years 1984 through 1997, thereby distinguishing internal finance and three types of external finance: bank borrowing, bond issues, and share issues. First, we estimate a multinomial logit model, which

The joint choice of tenure, dwelling type, size and location: the effect of home-oriented versus culture-oriented lifestyle

DEFF Research Database (Denmark)

Frenkel, Amnon; Kaplan, Sigal

2014-01-01

This study investigates knowledge-workers’ housing preferences in terms of tenure, dwelling type, location and size. The analysis is conducted by applying a joint multinomial-logit ordered-response model to the housing choices of knowledgeworkers residing in the Tel-Aviv metropolitan region and w...

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

Science.gov (United States)

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

2011-01-01

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

Networks and Selection in International Migration to Spain

DEFF Research Database (Denmark)

Neubecker, Nina; Smolka, Marcel; Steinbacher, Anne

This paper provides new evidence on migrant networks as determinants of the scale and skill structure of migration, using aggregate data from a recent migration boom to Spain. We develop a three-level nested multinomial logit migration model. Our model accommodates varying degrees of similarity...

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

African Journals Online (AJOL)

This study examines the patterns and correlations of solid waste disposal practices among households in urbanized and populated Dar es Salaam city in Tanzania. The Tanzanian Household Budget Survey (HBS) data covering many households' characteristics was used. Multinomial Logit (MNL) model was applied to ...

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.

Drivers of multidimensional eco-innovation: empirical evidence from the Brazilian industry.

Science.gov (United States)

da Silva Rabêlo, Olivan; de Azevedo Melo, Andrea Sales Soares

2018-03-08

The study analyses the relationships between the main drivers of eco-innovation introduced by innovative industries, focused on cooperation strategy. Eco-innovation is analysed by means of a multidimensional identification strategy, showing the relationships between the independent variables and the variable of interest. The literature discussing environmental innovation is different from the one discussing other types of innovation inasmuch as it seeks to grasp its determinants and to mostly highlight the relevance of environmental regulation. The key feature of this paper is that it ascribes special relevance to cooperation strategy with external partners and to the propensity of innovative industry introducing eco-innovation. A sample of 35,060 Brazilian industries were analysed, between 2003 and 2011, by means of Binomial, Multinomial and Ordinal logistic regressions with microdata collected with the research and innovation department (PINTEC) from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística). The econometric results estimated by the Logit Multinomial method suggest that the cooperation with external partners practiced by innovative industries facilitates the adoption of eco-innovation in dimension 01 with probability of 64.59%, 57.63% in dimension 02 and 81.02% in dimension 03. The data reveal that the higher the degree of eco-innovation complexity, the harder industries seek to obtain cooperation with external partners. When calculating with the Logit Ordinal and Binomial models, cooperation increases the probability that the industry is eco-innovative in 65.09% and 89.34%, respectively. Environmental regulation and innovation in product and information management were also positively correlated as drivers of eco-innovation.

Multiple steady states, limit cycles and chaotic attractors in evolutionary games with Logit Dynamics

NARCIS (Netherlands)

Hommes, C.H.; Ochea, M.I.

2010-01-01

This paper investigates, by means of simple, three and four strategy games, the occurrence of periodic and chaotic behaviour in a smooth version of the Best Response Dynamics, the Logit Dynamics. The main finding is that, unlike Replicator Dynamics, generic Hopf bifurcation and thus, stable limit

Analysis of Internet Usage Intensity in Iraq: An Ordered Logit Model

OpenAIRE

Almas Heshmati; Firas H. Al-Hammadany; Ashraf Bany-Mohammed

2013-01-01

Intensity of Internet use is significantly influenced by government policies, people’s levels of income, education, employment and general development and economic conditions. Iraq has very low Internet usage levels compared to the region and the world. This study uses an ordered logit model to analyse the intensity of Internet use in Iraq. The results showed that economic reasons (internet cost and income level) were key cause for low level usage intensity rates. About 68% of the population ...

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

Science.gov (United States)

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

2015-01-01

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

The determinants of the location of foreign direct investment in UK regions

NARCIS (Netherlands)

Dimitropoulou, Dimitra; McCann, Philip; Burke, Simon P.

2013-01-01

This article employs a database of over 2000 observations of Foreign Direct Investment (FDI) projects in UK regions. We analyse this data by means of various multinomial and conditional logit models in order to identify the major determinants of the location choices of these inward investments.

Entrepreneurial engagement levels in the European Union

NARCIS (Netherlands)

I. Grilo (Isabel); A.R. Thurik (Roy)

2005-01-01

textabstractA multinomial logit model and survey data from the 25 EU member states and the US are used to establish the effect of demographic and other variables on various entrepreneurial engagement levels. These engagement levels range from never thought about starting a business to thinking

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

Energy consumption and economic growth—New evidence from meta analysis

International Nuclear Information System (INIS)

Chen, Ping-Yu; Chen, Sheng-Tung; Chen, Chi-Chung

2012-01-01

The causal relationships between energy consumption and economic growth have given rise to much discussion but remain controversial. Alternative data sets based on different time spans, countries, energy policies and econometric approaches result in diverse outcomes. A meta analysis using a multinomial logit model with 174 samples governing the relationships between GDP and energy consumption is applied here to investigate the major factors that affect these controversial outcomes. The empirical results have demonstrated how the time spans, subject selections including GDP and energy consumption, econometric models, and tools for greenhouse gases emission reduction characteristics significantly affect these controversial outcomes. - Highlights: ► The controversial casual relationships between energy consumption and GDP are investigated. ► A meta analysis using a multinomial logit model is adopted. ► 74 studies governing the relationships between GDP and energy consumption was collected. ► The empirical results show how the probability of major factors affects such relationships.

Targeting: Logistic Regression, Special Cases and Extensions

Directory of Open Access Journals (Sweden)

Helmut Schaeben

2014-12-01

Full Text Available Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form. Weights-of-evidence is an ordinary logistic regression with parameters equal to the differences of the weights of evidence if all predictor variables are discrete and conditionally independent given the target variable. The hypothesis of conditional independence can be tested in terms of log-linear models. If the assumption of conditional independence is violated, the application of weights-of-evidence does not only corrupt the predicted conditional probabilities, but also their rank transform. Logistic regression models, including the interaction terms, can account for the lack of conditional independence, appropriate interaction terms compensate exactly for violations of conditional independence. Multilayer artificial neural nets may be seen as nested regression-like models, with some sigmoidal activation function. Most often, the logistic function is used as the activation function. If the net topology, i.e., its control, is sufficiently versatile to mimic interaction terms, artificial neural nets are able to account for violations of conditional independence and yield very similar results. Weights-of-evidence cannot reasonably include interaction terms; subsequent modifications of the weights, as often suggested, cannot emulate the effect of interaction terms.

Quantifying rural livelihood strategies in developing countries using an activity choice approach

DEFF Research Database (Denmark)

Nielsen, Øystein Juul; Rayamajhi, Santosh; Uberhuaga de Arratia, Patricia D C

2013-01-01

outcomes are compared across strategies and household differences in asset holdings are analyzed using multinomial logit regression. Findings reveal that income diversification is the norm, that a higher degree of specialization does not characterize more remunerative livelihood strategies, that nonfarm......This article uses a quantitative activity choice approach, based on identification of activity variables and application of latent class cluster analysis, to identify five major rural livelihood strategies pursued by households (n= 576) in Bolivia, Nepal, and Mozambique. Income sources and welfare...... income significantly contributes to higher income earnings, that environmental reliance does not vary across strategies, and that small-scale farmers are the largest and poorest livelihood group. Some livelihood strategies are superior to all other strategies in terms of income earned; access to more...

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.

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…

Has the Euro Affected the Choice of Invoicing Currency?

NARCIS (Netherlands)

Ligthart, J.E.; Werner, S.E.V.

2010-01-01

We present a new approach to study empirically the effect of the introduction of the euro on currency invoicing. Our approach uses a compositional multinomial logit model, in which currency choice depends on the characteristics of both the currency and the country. We use unique quarterly panel data

Heterogeneity in urban park use of aging visitors: a latent class analysis

NARCIS (Netherlands)

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

2006-01-01

This study describes and predicts urban parks use patterns for various age groups, with specific attention to the growing group of older adults. Park use intensity of various age groups is described. Subsequently, a multinomial logit model is estimated to describe urban park choice as a function of

Mobility in the Urban Labor Market : A Panel Data Analysis for Mexico

NARCIS (Netherlands)

Gong, X.; van Soest, A.H.O.; Villagomez, E.

2000-01-01

We analyze mobility in urban Mexico between three labor market states: working in the formal sector, working in the informal sector, and not working. We use a dynamic multinomial logit panel data model with random effects, explaining the labor market state of each individual during each time period.

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

An integrated Markov decision process and nested logit consumer response model of air ticket pricing

NARCIS (Netherlands)

Lu, J.; Feng, T.; Timmermans, H.P.J.; Yang, Z.

2017-01-01

The paper attempts to propose an optimal air ticket pricing model during the booking horizon by taking into account passengers' purchasing behavior of air tickets. A Markov decision process incorporating a nested logit consumer response model is established to modeling the dynamic pricing process.

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%).

Associating Crash Avoidance Maneuvers with Driver Attributes and Accident Characteristics: A Mixed Logit Model Approach

DEFF Research Database (Denmark)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

as from the key role of the ability of drivers to perform effective corrective maneuvers for the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that accommodates correlations across alternatives and heteroscedasticity. Data...

Determinants of the probability of adopting quality protein maize (QPM) technology in Tanzania: A logistic regression analysis

OpenAIRE

Gregory, T.; Sewando, P.

2013-01-01

Adoption of technology is an important factor in economic development. The thrust of this study was to establish factors affecting adoption of QPM technology in Northern zone of Tanzania. Primary data was collected from a random sample of 120 smallholder maize farmers in four villages. Data collected were analysed using descriptive and quantitative methods. Logit model was used to determine factors that influence adoption of QPM technology. The regression results indicated that education of t...

Valuing Non-market Benefits of Rehabilitation of Hydrologic Cycle Improvements in the Anyangcheon Watershed: Using Mixed Logit Models

Science.gov (United States)

Yoo, J.; Kong, K.

2010-12-01

This research the findings from a discrete-choice experiment designed to estimate the economic benefits associated with the Anyangcheon watershed improvements in Rep. of Korea. The Anyangcheon watershed has suffered from streamflow depletion and poor stream quality, which often negatively affect instream and near-stream ecologic integrity, as well as water supply. Such distortions in the hydrologic cycle mainly result from rapid increase of impermeable area due to urbanization, decreases of baseflow runoff due to groundwater pumping, and reduced precipitation inputs driven by climate forcing. As well, combined sewer overflows and increase of non-point source pollution from urban regions decrease water quality. The appeal of choice experiments (CE) in economic analysis is that it is based on random utility theory (McFadden, 1974; Ben-Akiva and Lerman, 1985). In contrast to contingent valuation method (CVM), which asks people to choose between a base case and a specific alternative, CE asks people to choice between cases that are described by attributes. The attributes of this study were selected from hydrologic vulnerability components that represent flood damage possibility, instreamflow depletion, water quality deterioration, form of the watershed and tax. Their levels were divided into three grades include status quo. Two grades represented the ideal conditions. These scenarios were constructed from a 35 orthogonal main effect design. This design resulted in twenty-seven choice sets. The design had nine different choice scenarios presented to each respondent. The most popular choice models in use are the conditional logit (CNL). This model provides closed-form choice probability calculation. The shortcoming of CNL comes from irrelevant alternatives (IIA). In this paper, the mixed logit (ML) is applied to allow the coefficient’s variation for random taste heterogeneity in the population. The mixed logit model(with normal distributions for the attributes) fit the

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....

Factors influencing farmers’ choices of adaptation to climate change in Ekiti State, Nigeria

Directory of Open Access Journals (Sweden)

Oluwakemi Adeola Obayelu

2014-06-01

Full Text Available Climate change poses a great threat to human security through erratic rainfall patterns and decreasing crop yields, contributing to increased hunger. The perceptions of the indigenous people about climate change and their responses to climate change have significant roles to play in addressing climate change. Therefore a critical study on farmers’ choices of adaptation to is critical for ensuring food security poverty alleviation. A multi-stage random sampling technique was used to select 156 households in Ekiti state while descriptive statistics and multinomial logit were used to analyze the data obtained from the households. The results showed that the most widely used adaptation method by the farmers were soil and water conservation measures (67 percent. The multinomial logit analysis revealed that the factors explaining farmer’s choices of climate change adaptation include age of the farmers, gender of the household head, years of education, years of farming experience, household size, farmers information on climate change, farmers access to credit, farm income, non-farm income, livestock ownership and extension contact.

DETERMINANTS OF CHOICE OF CROP VARIETY AS CLIMATE CHANGE ADAPTATION OPTION IN ARID REGIONS OF ZIMBABWE

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James Zivanomoyo

2013-03-01

Full Text Available Impacts of climate change in developing countries remain poorly understood because few studies have successfully analyses the overall impact of climate on developing country economies. Agricultural growth is widely viewed as an effective and most important way to reduce poverty in developing countries which are hardly hit by the adverse effects of climate change (Datt and Ravallion, 1996. Despite this knowledge the main challenge is how to increase agricultural productivity to improve household welfare and increase food security in these changing and challenging climatic conditions. This study used the multinomial logit model to analyse the determinants of farmers' choice of crop variety in the face of climate change. The estimation of the multinomial logit was done by using the sorghum variety options as dependent variable and where farmers grow other crop different from sorghum as the reference state. Results show that the key determinants of choosing crop variety are; the price of existing crop variety, level of education of farmers, the size of the farms, government policies and incentives and credit availability.

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.

Study on Emission Measurement of Vehicle on Road Based on Binomial Logit Model

OpenAIRE

Aly, Sumarni Hamid; Selintung, Mary; Ramli, Muhammad Isran; Sumi, Tomonori

2011-01-01

This research attempts to evaluate emission measurement of on road vehicle. In this regard, the research develops failure probability model of vehicle emission test for passenger car which utilize binomial logit model. The model focuses on failure of CO and HC emission test for gasoline cars category and Opacity emission test for diesel-fuel cars category as dependent variables, while vehicle age, engine size, brand and type of the cars as independent variables. In order to imp...

La influencia de la densidad competitiva en el resultado de los equipos en el fútbol de alto nivel. (The influence of a congested football calendar on the results obtained by teams in professional soccer.

Directory of Open Access Journals (Sweden)

Joaquín Lago Ballesteros

2009-01-01

Full Text Available Resumen Existe una considerable variación en el número de partidos disputados por los equipos de fútbol durante una temporada. Los mejores equipos juegan varios partidos a la semana tanto en las competiciones domesticas como en la Liga de Campeones. Se ha especulado que un período cargado de partidos puede limitar el rendimiento de los conjuntos. En este trabajo se estudia el efecto que tiene para un equipo disputar un partido de la Liga de Campeones sobre el resultado alcanzado en el encuentro de la Liga Española en el fin de semana anterior. La muestra consiste en 374 partidos de la Liga Española jugados por los equipos que se encontraban simultáneamente disputando la Liga de Campeones entre las temporadas 2003-2004 y 2006- 2007. Los resultados alcanzados mediante un modelo logit multinomial permiten demostrar que disputar un partido de la Liga de Campeones no reduce la probabilidad de ganar en el partido de la Liga Española. Además se ha verificado que la probabilidad de ganar en el partido del fin de semana de la Liga Española es mayor cuando el partido de la Liga de Campeones a disputar pertenece a la fase de liguilla respecto a si se corresponde con el formato de eliminación directa.Palabras clave: fútbol; liga española; liga de campeones; logit multinomial; densidad competitive. Abstract There is a considerable variation in the number of matches played per season by clubs in the Spanish Soccer. The successful top clubs play several matches a week in domestic leagues as well as in the UEFA Champions League. It has been speculated that a period full of matches can lead to player fatigue which may result in underperformance. Using data from 374 matches of the Spanish Soccer League played from the 2003-04 to the 2006-07 seasons and according to the estimation based on logit multinomial this study shows that Spanish Champions League teams did not perform below their normal standard at the weekend when they played a Champions

An Objective Screening Method for Major Depressive Disorder Using Logistic Regression Analysis of Heart Rate Variability Data Obtained in a Mental Task Paradigm

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Guanghao Sun

2016-11-01

Full Text Available Background and Objectives: Heart rate variability (HRV has been intensively studied as a promising biological marker of major depressive disorder (MDD. Our previous study confirmed that autonomic activity and reactivity in depression revealed by HRV during rest and mental task (MT conditions can be used as diagnostic measures and in clinical evaluation. In this study, logistic regression analysis (LRA was utilized for the classification and prediction of MDD based on HRV data obtained in an MT paradigm.Methods: Power spectral analysis of HRV on R-R intervals before, during, and after an MT (random number generation was performed in 44 drug-naïve patients with MDD and 47 healthy control subjects at Department of Psychiatry in Shizuoka Saiseikai General Hospital. Logit scores of LRA determined by HRV indices and heart rates discriminated patients with MDD from healthy subjects. The high frequency (HF component of HRV and the ratio of the low frequency (LF component to the HF component (LF/HF correspond to parasympathetic and sympathovagal balance, respectively.Results: The LRA achieved a sensitivity and specificity of 80.0% and 79.0%, respectively, at an optimum cutoff logit score (0.28. Misclassifications occurred only when the logit score was close to the cutoff score. Logit scores also correlated significantly with subjective self-rating depression scale scores (p < 0.05.Conclusion: HRV indices recorded during a mental task may be an objective tool for screening patients with MDD in psychiatric practice. The proposed method appears promising for not only objective and rapid MDD screening, but also evaluation of its severity.

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...

Efficiency Loss of Mixed Equilibrium Associated with Altruistic Users and Logit-based Stochastic Users in Transportation Network

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Xiao-Jun Yu

2014-02-01

Full Text Available The efficiency loss of mixed equilibrium associated with two categories of users is investigated in this paper. The first category of users are altruistic users (AU who have the same altruism coefficient and try to minimize their own perceived cost that assumed to be a linear combination of selfish com­ponent and altruistic component. The second category of us­ers are Logit-based stochastic users (LSU who choose the route according to the Logit-based stochastic user equilib­rium (SUE principle. The variational inequality (VI model is used to formulate the mixed route choice behaviours associ­ated with AU and LSU. The efficiency loss caused by the two categories of users is analytically derived and the relations to some network parameters are discussed. The numerical tests validate our analytical results. Our result takes the re­sults in the existing literature as its special cases.

The Cressey hypothesis (1953 and an investigation into the occurrence of corporate fraud: an empirical analysis conducted in Brazilian banking institutions

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Michele Rílany Rodrigues Machado

2017-11-01

Full Text Available ABSTRACT This article fills a technical-scientific gap that currently exists in the Brazilian literature on corporative fraud, by combining the theoretical framework of agency theory, of criminology, and of the economics of crime. In addition, it focuses on a sector that is usually excluded from analyses due to its specific characteristics and shows the application of multinomial logit panel data regression with random effects, which is rarely used in studies in the area of accounting. The aim of this study is to investigate the occurrence of corporative fraud, as well as cases of fraud in Brazilian banking institutions, by using detection variables related to the Cressey fraud triangle. Research into fraud and methods of detecting fraud has grown in management literature, especially after the occurrence of various corporative scandals in the 1990s. Although regulatory agencies have increased their investments in monitoring and control, fraud investigations and convictions are still common in the day-to-day administration of banks, as can be seen in the Brazilian Central Bank and the National Financial System Resource Council’s databases of punitive proceedings. We believe that this article will have a positive impact in the area of accounting sciences, since it involves corporative fraud in a multidisciplinary form and because it provides the incentive to use a quantitative tool that can help increase the development of similar studies in the area. This study tested the theory that the dimensions of the fraud triangle condition the occurrence of corporative fraud in Brazilian banking institutions. Thirty-two representative variables of corporative fraud were identified in the theoretical-empirical review, which were reduced to seven latent variables by the principal component analysis. Finally, the seven factors formed the independent variables in the multinomial logit models used in the hypothesis tests, which presented promising results.

Essays on pricing dynamics, price dispersion, and nested logit modelling

Science.gov (United States)

Verlinda, Jeremy Alan

The body of this dissertation comprises three standalone essays, presented in three respective chapters. Chapter One explores the possibility that local market power contributes to the asymmetric relationship observed between wholesale costs and retail prices in gasoline markets. I exploit an original data set of weekly gas station prices in Southern California from September 2002 to May 2003, and take advantage of highly detailed station and local market-level characteristics to determine the extent to which spatial differentiation influences price-response asymmetry. I find that brand identity, proximity to rival stations, bundling and advertising, operation type, and local market features and demographics each influence a station's predicted asymmetric relationship between prices and wholesale costs. Chapter Two extends the existing literature on the effect of market structure on price dispersion in airline fares by modeling the effect at the disaggregate ticket level. Whereas past studies rely on aggregate measures of price dispersion such as the Gini coefficient or the standard deviation of fares, this paper estimates the entire empirical distribution of airline fares and documents how the shape of the distribution is determined by market structure. Specifically, I find that monopoly markets favor a wider distribution of fares with more mass in the tails while duopoly and competitive markets exhibit a tighter fare distribution. These findings indicate that the dispersion of airline fares may result from the efforts of airlines to practice second-degree price discrimination. Chapter Three adopts a Bayesian approach to the problem of tree structure specification in nested logit modelling, which requires a heavy computational burden in calculating marginal likelihoods. I compare two different techniques for estimating marginal likelihoods: (1) the Laplace approximation, and (2) reversible jump MCMC. I apply the techniques to both a simulated and a travel mode

The importance of examining movements within the US health care system: sequential logit modeling

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Lee Chioun

2010-09-01

Full Text Available Abstract Background Utilization of specialty care may not be a discrete, isolated behavior but rather, a behavior of sequential movements within the health care system. Although patients may often visit their primary care physician and receive a referral before utilizing specialty care, prior studies have underestimated the importance of accounting for these sequential movements. Methods The sample included 6,772 adults aged 18 years and older who participated in the 2001 Survey on Disparities in Quality of Care, sponsored by the Commonwealth Fund. A sequential logit model was used to account for movement in all stages of utilization: use of any health services (i.e., first stage, having a perceived need for specialty care (i.e., second stage, and utilization of specialty care (i.e., third stage. In the sequential logit model, all stages are nested within the previous stage. Results Gender, race/ethnicity, education and poor health had significant explanatory effects with regard to use of any health services and having a perceived need for specialty care, however racial/ethnic, gender, and educational disparities were not present in utilization of specialty care. After controlling for use of any health services and having a perceived need for specialty care, inability to pay for specialty care via income (AOR = 1.334, CI = 1.10 to 1.62 or health insurance (unstable insurance: AOR = 0.26, CI = 0.14 to 0.48; no insurance: AOR = 0.12, CI = 0.07 to 0.20 were significant barriers to utilization of specialty care. Conclusions Use of a sequential logit model to examine utilization of specialty care resulted in a detailed representation of utilization behaviors and patient characteristics that impact these behaviors at all stages within the health care system. After controlling for sequential movements within the health care system, the biggest barrier to utilizing specialty care is the inability to pay, while racial, gender, and educational disparities

A Study of Commuters’ Decision-Making When Delaying Departure for Work-Home Trips

Science.gov (United States)

Que, Fangjie; Wang, Wei

2017-12-01

Studies on the travel behaviors and patterns of residents are important to the arrangement of urban layouts and urban traffic planning. However, research on the characteristics of the decision-making behavior regarding departure time is not fully expanded yet. In this paper, the research focuses on commuters’ decision-making behavior regarding departure delay. According to the 2013 travel survey data of Suzhou City, a nested logit (NL) model was built to represent the probabilities of individual choices. Parameter calibration was conducted, so that the significant factors influencing the departure delay were obtained. Ultimately, the results of the NL model indicated that it performed better and with higher precision, compared to the traditional multinomial logit (MNL) model.

Influence of Parking Price on Parking Garage Users’ Behaviour

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Jelena Simićević

2012-09-01

Full Text Available Parking charge is a powerful tool for solving parking and traffic congestion problems. In order to achieve the expected effects without any adverse impact it is necessary to understand well the users’ responses to this policy. This paper, based on a sample of interviewed parking garage users, has developed binary logit model for identification and quantification of characteristics of users and trips, on which the acceptance of parking price is dependent. In addition, multinomial logit model has been made in order to predict what the users will opt for when faced with an increase in parking price. For the first time the parameter “shorten duration” has been introduced which has shown to be the most significant in making behaviour-related decisions. The results show that the users with the purpose work are the most sensitive to an increase in parking charge, what can be deemed positive for policy makers. However, great sensitivity of the users with the purpose shopping should cause their concern. The results of the multinomial model show that they would not discontinue coming into the area after all.

Occupational segregation, selection effects and gender wage differences: evidence from urban Colombia

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Jairo Guillermo Isaza Castro

2014-06-01

Full Text Available This paper assesses the effects of occupational segregation on the gender wage gap in urban Colombia between 1986 and 2000. The empirical methodology involves a two step procedure where by the occupational distributions ofworkers by gender aremodelled using a multinomial logit model in the first stage. In the second stage, the multinomial logit estimates are used not only to derive a counterfactual occupational distribution of women in the absence of workplace discrimination but also to correct for selectivity bias in thewage equations for each occupational category using the procedure suggested by Lee (1983. Besides the explained and unexplained components in conventional decompositions of the gender wage gap, this methodology differentiates between the justified and unjustified effects of the gender allocation ofworkers across occupational categories. The results for urban Colombia indicate that controlling for selectivity bias at the occupational category level is found to be relevant in all years reviewed in this study. They also suggest that a changing composition of the female labour supply in terms of un observables (i.e., ability and motivation is playing a role in the dramatic reduction of the observed wage gap.

Disentangling WTP per QALY data: different analytical approaches, different answers.

Science.gov (United States)

Gyrd-Hansen, Dorte; Kjaer, Trine

2012-03-01

A large random sample of the Danish general population was asked to value health improvements by way of both the time trade-off elicitation technique and willingness-to-pay (WTP) using contingent valuation methods. The data demonstrate a high degree of heterogeneity across respondents in their relative valuations on the two scales. This has implications for data analysis. We show that the estimates of WTP per QALY are highly sensitive to the analytical strategy. For both open-ended and dichotomous choice data we demonstrate that choice of aggregated approach (ratios of means) or disaggregated approach (means of ratios) affects estimates markedly as does the interpretation of the constant term (which allows for disproportionality across the two scales) in the regression analyses. We propose that future research should focus on why some respondents are unwilling to trade on the time trade-off scale, on how to interpret the constant value in the regression analyses, and on how best to capture the heterogeneity in preference structures when applying mixed multinomial logit. Copyright © 2011 John Wiley & Sons, Ltd.

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...

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

Heterogeneity in the WTP for recreational access

DEFF Research Database (Denmark)

Campbell, Danny; Vedel, Suzanne Elizabeth; Thorsen, Bo Jellesmark

2014-01-01

In this study we have addressed appropriate modelling of heterogeneity in willingness to pay (WTP) for environmental goods, and have demonstrated its importance using a case of forest access in Denmark. We compared WTP distributions for four models: (1) a multinomial logit model, (2) a mixed logit...... model assuming a univariate Normal distribution, (3) or assuming a multivariate Normal distribution allowing for correlation across attributes, and (4) a mixture of two truncated Normal distributions, allowing for correlation among attributes. In the first two models mean WTP for enhanced access...... was negative. However, models accounting for preference heterogeneity found a positive mean WTP, but a large sub-group with negative WTP. Accounting for preference heterogeneity can alter overall conclusions, which highlights the importance of this for policy recommendations....

Memprediksi Financial Distress dengan Binary Logit Regression Perusahaan Telekomunikasi

OpenAIRE

antikasari, tiara widya; Djuminah, Djuminah

2017-01-01

In this globalization era, sub–sector telecommunication industry has rapid development as time goes by with the number of customers’ growth. However, its growth is not balanced with operational revenue development. Therefore, it is important to analyze the financial distress in telecommunication companies in order to avoid bankruptcy. This research aimed to investigate the effect of financial ratios to predict probability of financial distress. Financial ratios indicator used profitability ra...

Benefits of improved water quality: a discrete choice analysis of freshwater recreational demands

OpenAIRE

R S Tay; P S McCarthy

1994-01-01

Discrete choice methodologies are increasingly being used to estimate multiple-sites recreational demands and evaluate the welfare effects of alternative environmental policies aimed at water quality improvements. In this study the authors use 1985 data on Indiana anglers to estimate a multinomial logit model of destination choice and compute the benefits of alternative water quality improvements. In general, the results indicate that anglers are reasonably sensitive to changes in water quali...

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.

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.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

Science.gov (United States)

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

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.

Para Krizleri Öngörüsünde Logit Model ve Sinyal Yaklaşımının Değeri: Türkiye Tecrübesi

OpenAIRE

Kaya, Vedat; Yilmaz, Omer

2007-01-01

Logit model and the signal approach are two analysis methods being commonly used to forecast and explain currency crises. Logit model is successful to determine explaining variables of crisis and to calculate the probability of crisis in particular during the period experienced with a crisis. On the other hand, the signal approach aims at determining any possible currency crisis in advance, following some variables showing unusual change over the periods of economic fluctuation and thus it pr...

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...

Effect of Advertising on the Brand Loyalty of Cosmetic Products among College Students

OpenAIRE

Ababio, Abraham Gyamfi; Yamoah, Emmanuel Erastus

2016-01-01

This study explored the relationship between advertising and brand loyalty of cosmetic products. The multinomial logit model was used to ascertain the effect of advertising on different loyalty profiles for cosmetic products among college students. Based on a survey of 200 Ghanaian students drawn randomly, findings indicated that advertising plays no significant role on college students’ loyalty for cosmetic products. It can be argued, however, that the most promiscuous buyer is more amenable...

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

Disability and multi-state labour force choices with state dependence

OpenAIRE

Oguzoglu, Umut

2010-01-01

I use a dynamic mixed multinomial logit model with unobserved heterogeneity to study the impact of work limiting disabilities on disaggregated labour choices. The first seven waves of the Household Income and Labour Dynamics in Australia survey are used to investigate this relationship. Findings point out to strong state dependence in employment choices. Further, the impact of disability on employment outcomes is highly significant. Model simulations suggest that high cross and own state depe...

Long Work Hours: Volunteers and Conscripts

OpenAIRE

Robert Drago; Mark Wooden; David Black

2006-01-01

Panel data from Australia are used to study the prevalence of work hours mismatch among long hours workers and, more importantly, how that mismatch persists and changes over time, and what factors are associated with these changes. Particular attention is paid to the roles played by household debt, ideal worker characteristics and gender. Both static and dynamic multinomial logit models are estimated, with the dependent variable distinguishing long hours workers from other workers, and within...

The Influence of Higher Moments of Earnings Distributions on Career Decisions.

OpenAIRE

Flyer, Fredrick A

1997-01-01

A model where choice of occupation is sequential is applied to college graduates from the National Longitudinal Study of High School Class of 1972 to investigate how higher moments of occupational earnings distributions influence initial field of work. Individual specific life-cycle earnings projections that incorporate option values of occupational mobility are generated, and the relationship between these pay measures and choice of initial occupation is explored within a multinomial logit f...

"Choice of Air Cargo Transshipment Airport: An Application to Air Cargo Traffic to/from Northeast Asia"

OpenAIRE

Hiroshi Ohashi; Tae-Seung Kim; Tae Hoon Oum; Chunyan Yu

2004-01-01

Based on a unique data set of 760 air cargo transshipment routings to/from the Northeast Asian region in 2000, this paper applies an aggregate form of multinomial logit model to identify the critical factors influencing air cargo transshipment route choice decisions. The analysis focuses on the trade-off between monetary cost and time cost while considering other variables relevant for choice of transshipment airport. The estimation method considers the presence of unobserved attributes, and ...

Employees’ Preferences for more or fewer Working Hours. The Effects of Usual, Contractual and Standard Working Time, Family Phase and Household Characteristics, and Job Satisfaction

OpenAIRE

Tijdens, K.

2002-01-01

This study seeks explanations for working time preferences, using cross-sectional multinomial logits for the 2001/2002 Wage Indicator dataset (N=21,727). As expected, the preferences are predominately influenced by working hours’ characteristics, showing that employees with long hours prefer to work shorter hours and that short-hours workers prefer longer hours. New is the finding that salaried employees indeed want to reduce hours whereas hourly paid employees prefer to work longer hours. In...

WP RR 15 - Employees' preferences for more or fewer working hours: The effects of usual, contractual and standard working time, family phase and household characteristics and job satisfaction

OpenAIRE

Kea Tijdens

2002-01-01

This study seeks explanations for working time preferences, using cross-sectional multinomial logits for the 2001/2002 Wage Indicator dataset (N=21,727). As expected, the preferences are predominately influenced by working hours’ characteristics, showing that employees with long hours prefer to work shorter hours and that short-hours workers prefer longer hours. New is the finding that salaried employees indeed want to reduce hours whereas hourly paid employees prefer to work longer hours. In...

Climate Change Adaptation via U.S. Land Use Transitions: A Spatial Econometric Analysis

OpenAIRE

Cho, Sung Ju; McCarl, Bruce A.; Wu, Ximing

2015-01-01

Climate change, coupled with biofuels development and other factors may well be changing US land usage patterns. We use a spatial econometric approach to estimate the drivers of US land use transitions in recent years. We consider transitions between six major land uses: agricultural land, forest, grassland, water, urban, and other uses. To examine drivers, we use a two-step linearized, spatial, multinomial logit model and estimate land use transition probabilities. Our results indicate that ...

Effective Exchange Rate Classifications and Growth

OpenAIRE

Justin M. Dubas; Byung-Joo Lee; Nelson C. Mark

2005-01-01

We propose an econometric procedure for obtaining de facto exchange rate regime classifications which we apply to study the relationship between exchange rate regimes and economic growth. Our classification method models the de jure regimes as outcomes of a multinomial logit choice problem conditional on the volatility of a country's effective exchange rate, a bilateral exchange rate and international reserves. An `effective' de facto exchange rate regime classification is then obtained by as...

Location-Price Competition in Airline Networks

Directory of Open Access Journals (Sweden)

H. Gao

2014-01-01

Full Text Available This paper addresses location-then-price competition in airline market as a two-stage game of n players on the graph. Passenger’s demand distribution is described by multinomial logit model. Equilibrium in price game is computed through best response dynamics. We solve location game using backward induction, knowing that airlines will choose prices from equilibrium for the second-stage game. Some numerical results for airline market under consideration are presented.

Propensity for Voluntary Travel Behavior Changes: An Experimental Analysis

DEFF Research Database (Denmark)

Meloni, Italo; Sanjust, Benedetta; Sottile, Eleonora

2013-01-01

In this paper we analyze individual propensity to voluntary travel behavior change combining concepts from theory of change with the methodologies deriving from behavioral models. In particular, following the theory of voluntary changes, we set up a two-week panel survey including soft measure...... implementation, which consisted of providing car users with a personalized travel plan after the first week of observation (before) and using the second week to monitoring the post-behavior (after). These data have then been used to estimate a Mixed Logit for the choice to use a personal vehicle or a light metro......; and a Multinomial Logit for the decision to change behavior. Results from both models show the relevance of providing information about available alternatives to individuals while promoting voluntary travel behavioral change....

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.

CORPORATE DIVIDEND POLICY AND BEHAVIOUR: THE MALAYSIAN EVIDENCE

Directory of Open Access Journals (Sweden)

I. M. Pandey

2003-01-01

Full Text Available This study examines corporate dividend policy and behaviour of the Kuala Lumpur Stock Exchange (KLSE companies. Our results confirm the influence of industry on payout ratios. We also find that payout ratios in a given industry vary significantly across time. The results of multinomial logit analysis reveal that the KLSE companies' dividend actions are sensitive to the changes in earnings. Probabilities of dividend increases, decreases and omissions are high, respectively, with earnings increases, decreases and losses. This causes volatility in dividend payments. The KLSE firms appear to be reluctant to omit dividend except when they suffer losses. Further, using Lintner's framework and panel data regression methodology, we find evidence in favour of regular, but less stable, dividend policies being pursued by the KLSE companies. This is contrary to the experiences of companies in the developed capital markets. The results of the two-way fixed firm and time effects model reveal that there are significant differences in dividend policies across individual firms and over time.

The effects of mandatory health insurance on equity in access to outpatient care in Indonesia.

Science.gov (United States)

Hidayat, Budi; Thabrany, Hasbullah; Dong, Hengjin; Sauerborn, Rainer

2004-09-01

This paper examines the effects of mandatory health insurance on access and equity in access to public and private outpatient care in Indonesia. Data from the second round of the 1997 Indonesian Family Life Survey were used. We adopted the concentration index as a measure of equity, and this was calculated from actual data and from predicted probability of outpatient-care use saved from a multinomial logit regression. The study found that a mandatory insurance scheme for civil servants (Askes) had a strongly positive impact on access to public outpatient care, while a mandatory insurance scheme for private employees (Jamsostek) had a positive impact on access to both public and private outpatient care. The greatest effects of Jamsostek were observed amongst poor beneficiaries. A substantial increase in access will be gained by expanding insurance to the whole population. However, neither Askes nor Jamsostek had a positive impact on equity. Policy implications are discussed.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis

Directory of Open Access Journals (Sweden)

Maarten van Smeden

2016-11-01

Full Text Available Abstract Background Ten events per variable (EPV is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. Methods The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth’s correction, are compared. Results The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect (‘separation’. We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth’s correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. Conclusions The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Analyzing Korean consumers’ latent preferences for electricity generation sources with a hierarchical Bayesian logit model in a discrete choice experiment

International Nuclear Information System (INIS)

Byun, Hyunsuk; Lee, Chul-Yong

2017-01-01

Generally, consumers use electricity without considering the source the electricity was generated from. Since different energy sources exert varying effects on society, it is necessary to analyze consumers’ latent preference for electricity generation sources. The present study estimates Korean consumers’ marginal utility and an appropriate generation mix is derived using the hierarchical Bayesian logit model in a discrete choice experiment. The results show that consumers consider the danger posed by the source of electricity as the most important factor among the effects of electricity generation sources. Additionally, Korean consumers wish to reduce the contribution of nuclear power from the existing 32–11%, and increase that of renewable energy from the existing 4–32%. - Highlights: • We derive an electricity mix reflecting Korean consumers’ latent preferences. • We use the discrete choice experiment and hierarchical Bayesian logit model. • The danger posed by the generation source is the most important attribute. • The consumers wish to increase the renewable energy proportion from 4.3% to 32.8%. • Korea's cost-oriented energy supply policy and consumers’ preference differ markedly.

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...

A Subpath-based Logit Model to Capture the Correlation of Routes

Directory of Open Access Journals (Sweden)

Xinjun Lai

2016-06-01

Full Text Available A subpath-based methodology is proposed to capture the travellers’ route choice behaviours and their perceptual correlation of routes, because the original link-based style may not be suitable in application: (1 travellers do not process road network information and construct the chosen route by a link-by-link style; (2 observations from questionnaires and GPS data, however, are not always link-specific. Subpaths are defined as important portions of the route, such as major roads and landmarks. The cross-nested Logit (CNL structure is used for its tractable closed-form and its capability to explicitly capture the routes correlation. Nests represent subpaths other than links so that the number of nests is significantly reduced. Moreover, the proposed method simplifies the original link-based CNL model; therefore, it alleviates the estimation and computation difficulties. The estimation and forecast validation with real data are presented, and the results suggest that the new method is practical.

Application of LogitBoost Classifier for Traceability Using SNP Chip Data.

Science.gov (United States)

Kim, Kwondo; Seo, Minseok; Kang, Hyunsung; Cho, Seoae; Kim, Heebal; Seo, Kang-Seok

2015-01-01

Consumer attention to food safety has increased rapidly due to animal-related diseases; therefore, it is important to identify their places of origin (POO) for safety purposes. However, only a few studies have addressed this issue and focused on machine learning-based approaches. In the present study, classification analyses were performed using a customized SNP chip for POO prediction. To accomplish this, 4,122 pigs originating from 104 farms were genotyped using the SNP chip. Several factors were considered to establish the best prediction model based on these data. We also assessed the applicability of the suggested model using a kinship coefficient-filtering approach. Our results showed that the LogitBoost-based prediction model outperformed other classifiers in terms of classification performance under most conditions. Specifically, a greater level of accuracy was observed when a higher kinship-based cutoff was employed. These results demonstrated the applicability of a machine learning-based approach using SNP chip data for practical traceability.

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.

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...

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.

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).

Airport Choice in Sao Paulo Metropolitan Area: An Application of the Conditional Logit Model

Science.gov (United States)

Moreno, Marcelo Baena; Muller, Carlos

2003-01-01

Using the conditional LOGIT model, this paper addresses the airport choice in the Sao Paulo Metropolitan Area. In this region, Guarulhos International Airport (GRU) and Congonhas Airport (CGH) compete for passengers flying to several domestic destinations. The airport choice is believed to be a result of the tradeoff passengers perform considering airport access characteristics, airline level of service characteristics and passenger experience with the analyzed airports. It was found that access time to the airports better explain the airport choice than access distance, whereas direct flight frequencies gives better explanation to the airport choice than the indirect (connections and stops) and total (direct plus indirect) flight frequencies. Out of 15 tested variables, passenger experience with the analyzed airports was the variable that best explained the airport choice in the region. Model specifications considering 1, 2 or 3 variables were tested. The model specification most adjusted to the observed data considered access time, direct flight frequencies in the travel period (morning or afternoon peak) and passenger experience with the analyzed airports. The influence of these variables was therefore analyzed across market segments according to departure airport and flight duration criteria. The choice of GRU (located neighboring Sao Paulo city) is not well explained by the rationality of access time economy and the increase of the supply of direct flight frequencies, while the choice of CGH (located inside Sao Paulo city) is. Access time was found to be more important to passengers flying shorter distances while direct flight frequencies in the travel period were more significant to those flying longer distances. Keywords: Airport choice, Multiple airport region, Conditional LOGIT model, Access time, Flight frequencies, Passenger experience with the analyzed airports, Transportation planning

Should we pay, and to whom, for biodiversity enhancement in private forests? An empirical study of attitudes towards payments for forest ecosystem services in Poland

OpenAIRE

Anna Bartczak; Katarzyna Metelska-Szaniawska

2015-01-01

This paper investigates the possibility of forest policy changes in Poland. The main objective is to investigate whether, and to whom, the society would be willing to pay for providing biodiversity enhancement in private forests. The empirical evidence is derived from a stated preference survey conducted on the national level and analyzed using a multinomial logit model (MNL). Our findings show a rather strong potential for the implementation of payments for ecosystem services (PES) in privat...

The impact of the residential built environment on work at home adoption frequency: An example from Northern California

OpenAIRE

Tang, Wei (Laura); Mokhtarian, Patricia L.; Handy, Susan L.

2011-01-01

Working at home is widely viewed as a useful travel-reduction strategy, and it is partly for that reason that considerable research related to telecommuting and home-based work has been conducted in the last two decades. This study examines the effect of residential neighborhood built environment (BE) factors on working at home. After systematically presenting and categorizing various relevant elements of the BE and reviewing related studies, we develop a multinomial logit (MNL) model of work...

Livelihood strategies, environmental dependency and rural poverty

DEFF Research Database (Denmark)

Walelign, Solomon Zena

2016-01-01

This article attempts to explore the nexus between rural households’ environmental dependency, poverty and livelihood strategies. Households’ income from each livelihood activities formed the basis for categorizing households according to livelihood strategies. The principal component analysis...... of livelihood choice were analyzed using multinomial logit model. The results indicate the existence of marked differences in environmental dependency, rural poverty and asset endowments across the livelihood groups. Household’s total saving, access to credit, production implements, business cost, exposure...

Estimating the Open Market Desk's Daily Reaction Function.

OpenAIRE

Feinman, Joshua N

1993-01-01

This paper presents the results of an empirical investigation into the proximate determinants of the Federal Reserve's daily open market operations. Using information available each morning at the Fed conference call, the author models the Open Market Desk's choice of both the quantity and the type of operation, using a friction model for the former and a multinomial logit framework for the latter. Different types of operations are shown to send different signals to the market about the under...

Local and/or organic: A study on consumer preferences for organic food and food from different origins

OpenAIRE

Feldmann , Corinna; Hamm, Ulrich

2014-01-01

The purpose of this paper is to get a deeper insight into consumer preferences for different food products varying in their places of origin (i.e. local, Germany, neighbouring country, non-EU country) and production practices (i.e. organic vs. non-organic). Therefore, consumer surveys combined with choice experiments were conducted with 641 consumers in eight supermarkets in different parts of Germany. Multinomial and mixed logit models were estimated to draw conclusions on the preference str...

Intrahousehold Health Care Financing Strategy and the Gender Gap: Empirical Evidence from India

OpenAIRE

Abay Asfaw; Stephan Klasen; Francesca Lamanna

2008-01-01

The 'missing women' dilemma in India has sparked interest in investigating gender discrimination in the provision of health care in the country. No studies, however, have directly examined this discrimination in relation to household behavior in health care financing. We hypothesize that households who face tight budget constraints are more likely to spend their meager resources on hospitalization of boys rather than girls. We use the 60th Indian National Sample Survey and a multinomial logit...

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...

Flexible link functions in nonparametric binary regression with Gaussian process priors.

Science.gov (United States)

Li, Dan; Wang, Xia; Lin, Lizhen; Dey, Dipak K

2016-09-01

In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. © 2015, The International Biometric Society.

Comparing Johnson’s SBB, Weibull and Logit-Logistic bivariate distributions for modeling tree diameters and heights using copulas

Energy Technology Data Exchange (ETDEWEB)

Cardil Forradellas, A.; Molina Terrén, D.M.; Oliveres, J.; Castellnou, M.

2016-07-01

Aim of study: In this study we compare the accuracy of three bivariate distributions: Johnson’s SBB, Weibull-2P and LL-2P functions for characterizing the joint distribution of tree diameters and heights. Area of study: North-West of Spain. Material and methods: Diameter and height measurements of 128 plots of pure and even-aged Tasmanian blue gum (Eucalyptus globulus Labill.) stands located in the North-west of Spain were considered in the present study. The SBB bivariate distribution was obtained from SB marginal distributions using a Normal Copula based on a four-parameter logistic transformation. The Plackett Copula was used to obtain the bivariate models from the Weibull and Logit-logistic univariate marginal distributions. The negative logarithm of the maximum likelihood function was used to compare the results and the Wilcoxon signed-rank test was used to compare the related samples of these logarithms calculated for each sample plot and each distribution. Main results: The best results were obtained by using the Plackett copula and the best marginal distribution was the Logit-logistic. Research highlights: The copulas used in this study have shown a good performance for modeling the joint distribution of tree diameters and heights. They could be easily extended for modelling multivariate distributions involving other tree variables, such as tree volume or biomass. (Author)

Transitions between states of labor-force participation among older Israelis

OpenAIRE

Achdut, Leah; Tur-Sinai, Aviad; Troitsky, Rita

2014-01-01

The study examines the labor-force behavior of Israelis at older ages, focusing on the determinants of the transitions between states of labor-force participation between 2005 and 2010. The study uses panel data from the first two waves of the SHARE-Israel longitudinal survey. A multinomial logit model is used to examine the impact of sociodemographic characteristics, health state, and economic resources on labor-force transitions of people aged 50–67. The results emphasize the role of age an...

The Role of Neighborhood Characteristics in the Adoption and Frequency of Working at Home: Empirical Evidence from Northern California

OpenAIRE

Tang, Wei; Mokhtarian, Patricia; Handy, Susan

2008-01-01

Working at home is widely viewed as a useful travel-reduction strategy, and partly for that reason, considerable research related to telecommuting and home-based work has been conducted in the last two decades. The contribution of this study is to examine the effect of residential neighborhood built environment (BE) factors on working at home. Using data from a survey of eight neighborhoods in Northern California, we develop a multinomial logit (MNL) model of work-at-home (WAH) frequency. Pot...

Comparison of four mathematical models for the calculation of radioimmunoassay data of LH, FSH and GH

International Nuclear Information System (INIS)

Geier, T.; Rohde, W.

1981-01-01

Weighted linear logit-log regression, point-to-point logit-log interpolation, smoothing spline approximation and the four-parameter logistic function calculated by non-linear regression have been compared. The data for comparison have been obtained from two different pool-sera for each of the LH-, FSH- and GH-RIA and from the basal serum LH values of two populations of children. The Wilcoxon matched pairs signed rank test was used for comparison: For GH there is no significant difference between all methods, for FSH the weighted linear logit-log regression and spline approximation appeared to be equivalent, but for LH no unequivocal assertion can be made. There is no significant difference between the mathematical models for determination of hormone concentration within one assay run of a population as exemplified for LH. In addition, pool sera data were subjected to an analysis of variance and the comparison of the results revealed that the different models did not lead to different statements about assay performance. The point-to-point logit-log interpolation is proposed as most simple curvilinear approximation for assays which cannot be linearized by logit-log transformation. (author)

Determinants of Health Insurance Coverage among People Aged 45 and over in China: Who Buys Public, Private and Multiple Insurance

Science.gov (United States)

Jin, Yinzi; Hou, Zhiyuan; Zhang, Donglan

2016-01-01

Background China is reforming and restructuring its health insurance system to achieve the goal of universal coverage. This study aims to understand the determinants of public, private and multiple insurance coverage among people of retirement-age in China. Methods We used data from the China Health and Retirement Longitudinal Survey 2011 and 2013, a nationally representative survey of Chinese people aged 45 and over. Multinomial logit regression was performed to identify the determinants of public, private and multiple health insurance coverage. We also conducted logit regression to examine the association between public insurance coverage and demand for private insurance. Results In 2013, 94.5% of this population had at least one type of public insurance, and 12.2% purchased private insurance. In general, we found that rural residents were less likely to be uninsured (Relative Risk Ratio (RRR) = 0.40, 95% Confidence Interval (CI): 0.34–0.47) and were less likely to buy private insurance (RRR = 0.22, 95% CI: 0.16–0.31). But rural-to-urban migrants were more likely to be uninsured (RRR = 1.39, 95% CI: 1.24–1.57). Public health insurance coverage may crowd out private insurance market (Odds Ratio = 0.55, 95% CI: 0.48–0.63), particularly among enrollees of Urban Resident Basic Medical Insurance. There exists a huge socioeconomic disparity in both public and private insurance coverage. Conclusion The migrants, the poor and the vulnerable remained in the edge of the system. The growing private insurance market did not provide sufficient financial protection and did not cover the people with the greatest need. To achieve universal coverage and reduce socioeconomic disparity, China should integrate the urban and rural public insurance schemes across regions and remove the barriers for the middle-income and low-income to access private insurance. PMID:27564320

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.

Logistic regression analysis of financial literacy implications for retirement planning in Croatia

Directory of Open Access Journals (Sweden)

Dajana Barbić

2016-12-01

Full Text Available The relationship between financial literacy and financial behavior is important, as individuals are increasingly being asked to take responsibility for their financial wellbeing, especially their retirement. Analyzing of individual savings and attitudes towards retirement planning is important, as these types of investments are a way of preserving security during years of financial vulnerability. Research indicates that individuals who do not save adequately for their retirement, generally have a relatively low level of financial literacy. This research investigates the relationship between financial literacy and retirement planning in Croatia. To analyze the relationship between financial literacy and planning for retirement, maximum likelihood logistic regression analysis was used. The paper shows that those who answer financial literacy questions correctly are more likely to have a positive attitude towards retirement planning and are more likely to save for retirement, ensuring them of higher levels of financial security in retirement. The Goodness-of-Fit evaluation for the estimated logit model was performed using the Andrews and Hosmer-Lemeshow Tests.

Stability of Mixed-Strategy-Based Iterative Logit Quantal Response Dynamics in Game Theory

Science.gov (United States)

Zhuang, Qian; Di, Zengru; Wu, Jinshan

2014-01-01

Using the Logit quantal response form as the response function in each step, the original definition of static quantal response equilibrium (QRE) is extended into an iterative evolution process. QREs remain as the fixed points of the dynamic process. However, depending on whether such fixed points are the long-term solutions of the dynamic process, they can be classified into stable (SQREs) and unstable (USQREs) equilibriums. This extension resembles the extension from static Nash equilibriums (NEs) to evolutionary stable solutions in the framework of evolutionary game theory. The relation between SQREs and other solution concepts of games, including NEs and QREs, is discussed. Using experimental data from other published papers, we perform a preliminary comparison between SQREs, NEs, QREs and the observed behavioral outcomes of those experiments. For certain games, we determine that SQREs have better predictive power than QREs and NEs. PMID:25157502

Performance of various mathematical methods for calculation of radioimmunoassay results

International Nuclear Information System (INIS)

Sandel, P.; Vogt, W.

1977-01-01

Interpolation and regression methods are available for computer aided determination of radioimmunological end results. We compared the performance of eight algorithms (weighted and unweighted linear logit-log regression, quadratic logit-log regression, Rodbards logistic model in the weighted and unweighted form, smoothing spline interpolation with a large and small smoothing factor and polygonal interpolation) on the basis of three radioimmunoassays with different reference curve characteristics (digoxin, estriol, human chorionic somatomammotropin = HCS). Great store was set by the accuracy of the approximation at the intermediate points on the curve, ie. those points that lie midway between two standard concentrations. These concentrations were obtained by weighing and inserted as unknown samples. In the case of digoxin and estriol the polygonal interpolation provided the best results while the weighted logit-log regression proved superior in the case of HCS. (orig.) [de

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...

Discrete Choice and Rational Inattention

DEFF Research Database (Denmark)

Fosgerau, Mogens; Melo, Emerson; de Palma, André

2017-01-01

This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015, AER) showed that when information costs are modelled using the Shannon entropy, the result- ing choice probabilities in the rational inattention model take the multinomial...... logit form. We show that when information costs are modelled using a class of generalized entropies, then the choice probabilities in any rational inattention model are observationally equivalent to some additive random utility discrete choice model and vice versa. This equivalence arises from convex...

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.

Meta-analysis data for 104 Energy-Economy Nexus papers

Directory of Open Access Journals (Sweden)

Vladimír Hajko

2017-06-01

Data cover papers indexed by Scopus, published in economic journals, written in English, after year 2000. In addition, papers were manually filtered to only those that deal with Energy-Economy Nexus investigation and have at least 10 citations at (at the time of query – November 2015. This data are to be used to conduct meta-analysis – associated dataset was used in Hajko [1]. Early version of the dataset was used for multinomial logit estimation in Master thesis by Kociánová [2].

Impacts of geographical locations and sociocultural traits on the Vietnamese entrepreneurship.

Science.gov (United States)

Vuong, Quan Hoang

2016-01-01

This paper presents new results obtained from investigating the data from a 2015 Vietnamese entrepreneurs' survey, containing 3071 observations. Evidence from the estimations using multinomial logits was found to support relationships between several sociocultural factors and entrepreneurship-related performance or traits. Specifically, those relationships include: (a) Active participation in entrepreneurs' social networks and reported value of creativity; (b) CSR-willingness and reported entrepreneurs' perseverance; (c) Transforming of sociocultural values and entrepreneurs' decisiveness; and, (d) Lessons learned from others' failures and perceived chance of success. Using geographical locations as the control variate, evaluations of the baseline-category logits models indicate their varying effects on the outcomes when combined with the sociocultural factors that are found to be statistically significant. Empirical probabilities that give further detail about behavioral patterns are provided; and toward the end, the paper offers some conclusions with some striking insights and useful explanations on the Vietnamese entrepreneurship processes.

Logits and Tigers and Bears, Oh My! A Brief Look at the Simple Math of Logistic Regression and How It Can Improve Dissemination of Results

Science.gov (United States)

Osborne, Jason W.

2012-01-01

Logistic regression is slowly gaining acceptance in the social sciences, and fills an important niche in the researcher's toolkit: being able to predict important outcomes that are not continuous in nature. While OLS regression is a valuable tool, it cannot routinely be used to predict outcomes that are binary or categorical in nature. These…

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

Determinants of the probability of adopting quality protein maize (QPM technology in Tanzania: A logistic regression analysis

Directory of Open Access Journals (Sweden)

Gregory, T.

2013-06-01

Full Text Available Adoption of technology is an important factor in economic development. The thrust of this study was to establish factors affecting adoption of QPM technology in Northern zone of Tanzania. Primary data was collected from a random sample of 120 smallholder maize farmers in four villages. Data collected were analysed using descriptive and quantitative methods. Logit model was used to determine factors that influence adoption of QPM technology. The regression results indicated that education of the household head, farmers’ participation on demonstration trials, attendance to field days, and numbers of livestock owned have positively influenced the rate of adoption of the technology. Access to credit, and poor QPM marketing problem perception by farmers negatively influenced the rate of adoption. The study recommended government to ensure efficiency input-output linkage for QPM production.

Improving navigability on the Kromme River Estuary: A choice ...

African Journals Online (AJOL)

2013-03-14

Mar 14, 2013 ... logit model, random parameters logit model. INTRODUCTION .... tives, is treated by the RUM as a stochastic, utility-maximising choice (Louviere et ..... comparable to the one estimated for a linear regression model. (the ones ...

Occupant Perceptions and a Health Outcome in Retail Stores

Energy Technology Data Exchange (ETDEWEB)

Zhao, Mingjie; Kim, Yang-Seon; Srebric, Jelena

2015-11-02

Indoor Environmental Quality (IEQ) in commercial buildings, such as retail stores, can affect employee satisfaction, productivity, and health. This study administered an IEQ survey to retail employees and found correlations between measured IEQ parameters and the survey responses. The survey included 611 employees in 14 retail stores located in Pennsylvania (climate zone 5A) and Texas (climate zone 2A). The survey questionnaire featured ratings of different aspects of IEQ, including thermal comfort, lighting and noise level, indoor smells, overall cleanness, and environmental quality. Simultaneously with the survey, on-site physical measurements were taken to collect data of relative humidity levels, air exchange rates, dry bulb temperatures, and contaminant concentrations. This data was analyzed using multinomial logit regression with independent variables being the measured IEQ parameters, employees’ gender, and age. This study found that employee perception of stuffy smells is related to formaldehyde and PM10 concentrations. Furthermore, the survey also asked the employees to report an annual frequency of common colds as a health indicator. The regression analysis showed that the cold frequency statistically correlates with the measured air exchange rates, outdoor temperatures, and indoor PM concentrations. Overall, the air exchange rate is the most influential parameter on the employee perception of the overall environmental quality and self-reported health outcome.

A mixed logit analysis of two-vehicle crash severities involving a motorcycle.

Science.gov (United States)

Shaheed, Mohammad Saad B; Gkritza, Konstantina; Zhang, Wei; Hans, Zachary

2013-12-01

Using motorcycle crash data for Iowa from 2001 to 2008, this paper estimates a mixed logit model to investigate the factors that affect crash severity outcomes in a collision between a motorcycle and another vehicle. These include crash-specific factors (such as manner of collision, motorcycle rider and non-motorcycle driver and vehicle actions), roadway and environmental conditions, location and time, motorcycle rider and non-motorcycle driver and vehicle attributes. The methodological approach allows the parameters to vary across observations as opposed to a single parameter representing all observations. Our results showed non-uniform effects of rear-end collisions on minor injury crashes, as well as of the roadway speed limit greater or equal to 55mph, the type of area (urban), the riding season (summer) and motorcyclist's gender on low severity crashes. We also found significant effects of the roadway surface condition, clear vision (not obscured by moving vehicles, trees, buildings, or other), light conditions, speed limit, and helmet use on severe injury outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

"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

Performance of various mathematical methods for computer-aided processing of radioimmunoassay results

International Nuclear Information System (INIS)

Vogt, W.; Sandel, P.; Langfelder, Ch.; Knedel, M.

1978-01-01

The performance of 6 algorithms were compared for computer aided determination of radioimmunological end results. These were weighted and unweighted linear logit log regression; quadratic logit log regression, smoothing spline interpolation with a large and small smoothing factor, respectively, and polygonal interpolation and the manual curve fitting on the basis of three radioimmunoassays with different reference curve characteristics (digoxin, estriol, human chorionic somatomammotrophin (HCS)). Great store was set by the accuracy of the approximation at the intermediate points on the curve, i.e. those points that lie midway between two standard concentrations. These concentrations were obtained by weighing and inserted as unknown samples. In the case of digoxin and estriol the polygonal interpolation provided the best results, while the weighted logit log regression proved superior in the case of HCS. (Auth.)

Electoral system, pesonal votes, and party choice

DEFF Research Database (Denmark)

Thomsen, Søren Risbjerg

Using local elections in Denmark as an example this paper shows that individual party choice is influenced both by individual level, municipality level, and national level characteristics. Some hypotheses about the effects of the electoral system on personal votes derived from a theory by Carey...... & Shugart (1995) are first tested using a fixed-effects model. The effect of the personal reputation of the candidates, measured by personal votes, on party choice is then tested using a multilevel multinomial logit model suggested by Rabe-Hesketh and Skrondal (2008). The paper shows that both the electoral...

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...

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...

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.

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.

EFFECT OF WAGES ON MULTIPLE JOB HOLDING DECISIONS IN INDONESIA: EVIDENCE FROM THE INDONESIAN FAMILY LIFE SURVEY (IFLS DATA OF 2007 AND 2014

Directory of Open Access Journals (Sweden)

Niken Dwi Wijayanti

2018-01-01

Full Text Available Multiple job holding - i.e., a phenomenon in which workers have more than one job has become a trend in developed countries and is beginning to occur in developing countries, such as Indonesia. Existing studies provide the evidence that wages are a significant and consistent criterion to determine multiple job decisions. Wage increases in the primary job will decrease the incentive to have a second job as the reservation wage increases. However, we do not find any study which links the current multiple job decision with the past multiple job status. In this study, we use data from the Indonesian Family Life Survey (IFLS in 2007 and 2014 to investigate whether or not a wage increase in the primary job reduces the incentive to have a second job in 2014, controlling for the multiple job status in 2007. Using logit and multinomial logit estimations, we find that the wage increase in the primary job decreases the probability of having a second job in 2014.

Maximum Simulated Likelihood and Expectation-Maximization Methods to Estimate Random Coefficients Logit with Panel Data

DEFF Research Database (Denmark)

Cherchi, Elisabetta; Guevara, Cristian

2012-01-01

with cross-sectional or with panel data, and (d) EM systematically attained more efficient estimators than the MSL method. The results imply that if the purpose of the estimation is only to determine the ratios of the model parameters (e.g., the value of time), the EM method should be preferred. For all......The random coefficients logit model allows a more realistic representation of agents' behavior. However, the estimation of that model may involve simulation, which may become impractical with many random coefficients because of the curse of dimensionality. In this paper, the traditional maximum...... simulated likelihood (MSL) method is compared with the alternative expectation- maximization (EM) method, which does not require simulation. Previous literature had shown that for cross-sectional data, MSL outperforms the EM method in the ability to recover the true parameters and estimation time...

Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.

Science.gov (United States)

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

2018-06-01

Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

Radiation effects on cancer mortality among A-bomb survivors, 1950-72. Comparison of some statistical models and analysis based on the additive logit model

Energy Technology Data Exchange (ETDEWEB)

Otake, M [Hiroshima Univ. (Japan). Faculty of Science

1976-12-01

Various statistical models designed to determine the effects of radiation dose on mortality of atomic bomb survivors in Hiroshima and Nagasaki from specific cancers were evaluated on the basis of a basic k(age) x c(dose) x 2 contingency table. From the aspects of application and fits of different models, analysis based on the additive logit model was applied to the mortality experience of this population during the 22year period from 1 Oct. 1950 to 31 Dec. 1972. The advantages and disadvantages of the additive logit model were demonstrated. Leukemia mortality showed a sharp rise with an increase in dose. The dose response relationship suggests a possible curvature or a log linear model, particularly if the dose estimated to be more than 600 rad were set arbitrarily at 600 rad, since the average dose in the 200+ rad group would then change from 434 to 350 rad. In the 22year period from 1950 to 1972, a high mortality risk due to radiation was observed in survivors with doses of 200 rad and over for all cancers except leukemia. On the other hand, during the latest period from 1965 to 1972 a significant risk was noted also for stomach and breast cancers. Survivors who were 9 year old or less at the time of the bomb and who were exposed to high doses of 200+ rad appeared to show a high mortality risk for all cancers except leukemia, although the number of observed deaths is yet small. A number of interesting areas are discussed from the statistical and epidemiological standpoints, i.e., the numerical comparison of risks in various models, the general evaluation of cancer mortality by the additive logit model, the dose response relationship, the relative risk in the high dose group, the time period of radiation induced cancer mortality, the difference of dose response between Hiroshima and Nagasaki and the relative biological effectiveness of neutrons.

Food insufficiency and food insecurity as risk factors for physical disability among Palestinian refugees in Lebanon: Evidence from an observational study.

Science.gov (United States)

Salti, Nisreen; Ghattas, Hala

2016-10-01

Potential interactions between malnutrition and disability are increasingly recognized, and both are important global health issues. Causal effects working from nutrition to disability and from disability back to nutrition present an empirical challenge to measuring either of these effects. However, disability affects nutrition whatever the cause of disability, whereas nutrition is likelier to affect disease-related disability than war- or work-related disability. This paper investigates the association of food insufficiency with the risk of physical disability. Data on disability by cause allow us to address the difficulty of reverse causality. Multinomial logit regressions of disability by cause on food insufficiency are run using survey data from 2010 on 2575 Palestinian refugee households in Lebanon. Controls include household sociodemographic, health and economic characteristics. Regressions of food insufficiency on disability by cause are also run. Disability has a significant coefficient in regressions of food insufficiency, whatever the cause of disability; but in regressions of disability on food insufficiency, food insufficiency is significant only for disease-related disability (log odds of disease-related disability .78 higher, p = .008). The difference in the results by cause of disability is evidence of a significant association between food insufficiency and disease-related disability, net of any reverse effect from disability to food access. The association between disease-related disability and food insufficiency is statistically significant suggesting that even taking into account feedback from disability to nutrition, nutrition is an effective level of intervention to avert the poverty-disability trap resulting from the impoverishing effect of disability. Copyright © 2016 Elsevier Inc. All rights reserved.

Using continuation-ratio logits to analyze the variation of the age composition of fish catches

DEFF Research Database (Denmark)

Kvist, Trine; Gislason, Henrik; Thyregod, Poul

2000-01-01

Major sources of information for the estimation of the size of the fish stocks and the rate of their exploitation are samples from which the age composition of catches may be determined However, the age composition in the catches often varies as a result of several factors. Stratification...... of the sampling is desirable, because it leads to better estimates of the age composition, and the corresponding variances and covariances. The analysis is impeded by the fact that the response is ordered categorical. This paper introduces an easily applicable method to analyze such data. The method combines...... be applied separately to each level of the logits. The method is illustrated by the analysis of age-composition data collected from the Danish sandeel fishery in the North Sea in 1993. The significance of possible sources of variation is evaluated, and formulae for estimating the proportions of each age...

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.

Estrutura do mercado de trabalho metropolitano na região sul do Brasil, em 1995 e em 2005

OpenAIRE

Sampaio,Armando Vaz

2012-01-01

Para melhor compreender as transições que ocorrem no mercado de trabalho, é importante considerar os fluxos de estar empregado, desempregado e fora do mercado de trabalho e as probabilidades envolvidas em função de variáveis socioeconômicas e geográficas. O modelo econométrico utilizado foi o multinomial logit, em que se observou que há diferença de gênero com respeito a estar ocupado e fora do mercado de trabalho, sendo que, para a primeira situação, a probabilidade é maior para o homem e, p...

Getting the right balance? A mixed logit analysis of the relationship between UK training doctors' characteristics and their specialties using the 2013 National Training Survey.

Science.gov (United States)

Rodriguez Santana, Idaira; Chalkley, Martin

2017-08-11

To analyse how training doctors' demographic and socioeconomic characteristics vary according to the specialty that they are training for. Descriptive statistics and mixed logistic regression analysis of cross-sectional survey data to quantify evidence of systematic relationships between doctors' characteristics and their specialty. Doctors in training in the United Kingdom in 2013. 27 530 doctors in training but not in their foundation year who responded to the National Training Survey 2013. Mixed logit regression estimates and the corresponding odds ratios (calculated separately for all doctors in training and a subsample comprising those educated in the UK), relating gender, age, ethnicity, place of studies, socioeconomic background and parental education to the probability of training for a particular specialty. Being female and being white British increase the chances of being in general practice with respect to any other specialty, while coming from a better-off socioeconomic background and having parents with tertiary education have the opposite effect. Mixed results are found for age and place of studies. For example, the difference between men and women is greatest for surgical specialties for which a man is 12.121 times more likely to be training to a surgical specialty (relative to general practice) than a woman (p-valuevalue<0.01). There are systematic and substantial differences between specialties in respect of training doctors' gender, ethnicity, age and socioeconomic background. The persistent underrepresentation in some specialties of women, minority ethnic groups and of those coming from disadvantaged backgrounds will impact on the representativeness of the profession into the future. Further research is needed to understand how the processes of selection and the self-selection of applicants into specialties gives rise to these observed differences. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article

Early Warning Models for Systemic Banking Crises in Montenegro

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Željka Asanović

2013-06-01

Full Text Available The purpose of this research is to create an adequate early warning model for systemic banking crises in Montenegro. The probability of banking crisis occurrence is calculated using discrete dependent variable models, more precisely, estimating logit regression. Afterwards, seven simple logit regressions that individually have two explanatory variables are estimated. Adequate weights have been assigned to all seven regressions using the technique of Bayesian model averaging. The advantage of this technique is that it takes into account the model uncertainty by considering various combinations of models in order to minimize the author’s subjective judgment when determining reliable early warning indicators. The results of Bayesian model averaging largely coincide with the results of a previously estimated dynamic logit model. Indicators of credit expansion, thanks to their performances, have a dominant role in early warning models for systemic banking crises in Montenegro. The results have also shown that the Montenegrin banking system is significantly exposed to trends on the global level.

Risk factors associated with bus accident severity in the United States: A generalized ordered logit model

DEFF Research Database (Denmark)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

of 2011. Method: The current study investigates the underlying risk factors of bus accident severity in the United States by estimating a generalized ordered logit model. Data for the analysis are retrieved from the General Estimates System (GES) database for the years 2005–2009. Results: Results show...... that accident severity increases: (i) for young bus drivers under the age of 25; (ii) for drivers beyond the age of 55, and most prominently for drivers over 65 years old; (iii) for female drivers; (iv) for very high (over 65 mph) and very low (under 20 mph) speed limits; (v) at intersections; (vi) because......Introduction: Recent years have witnessed a growing interest in improving bus safety operations worldwide. While in the United States buses are considered relatively safe, the number of bus accidents is far from being negligible, triggering the introduction of the Motor-coach Enhanced Safety Act...

Valuing energy-saving measures in residential buildings. A choice experiment study

Energy Technology Data Exchange (ETDEWEB)

Kwak, So-Yoon; Kwak, Seung-Jun [Department of Economics, Korea University, 5-1 Anam-Dong, Seoul 136-701 (Korea); Yoo, Seung-Hoon [Department of International Area Studies, Hoseo University, 268 Anseo-Dong, Cheonan, Chungnam 330-713 (Korea)

2010-01-15

Air-conditioning and heating energy-saving measures can cut back the usage of energy. This paper attempts to apply a choice experiment in evaluating the consumer's willingness to pay (WTP) for air-conditioning and heating energy-saving measures in Korea's residential buildings. We consider the trade-offs between price and three attributes of energy-saving (window, facade, and ventilation) for selecting a preferred alternative and derive the marginal WTP (MWTP) estimate for each attribute. We also try to test irrelevant alternatives property for the estimation model holds and compare the estimation results of the multinomial logit (MNL) and the nested logit (NL) models. The NL model outperforms the MNL model. The NL model show that MWTPs for increasing the number of glasses and their variety, for increasing the thickness of facade for 1 mm, and for establishing a ventilation system are KRW 17,392 (USD 18.2), 1,112 (1.2), and 11,827 (12.4), respectively. Overall, the potential consumers have significant amount of WTP. (author)

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.

Valoração de contingente pelas modelagens logit e análise multivariada: um estudo de caso da disposição a aceitar compensação dos cafeicultores vinculados ao PRO-CAFÉ de Viçosa - MG Contingent valuation with modeling logit and multivariate analyses: a case study of the willingness of coffee planters linked to the PRO-COFFEE of Viçosa - MG to accept compensation

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Pedro Silveira Máximo

2009-12-01

Full Text Available O objetivo deste estudo foi, justamente, identificar, entre os métodos LOGIT e a análise multivariada, qual a mais eficaz para estimar a Disposição a Aceitar Compensação (DAC dos cafeicultores quando o viés da utilidade marginal é passível de ocorrência. Para tal, foi elaborado um formulário com 33 perguntas envolvendo informações sobre características socioeconômicas dos cafeicultores, o uso da metodologia de valoração de contingente (MVC e do veículo de pagamento dos "Jogos de Lances", que revelou a Disposição a Aceitar uma Compensação (DAC na troca de um hectare de café por um hectare de mata. Como esperado, por causa do viés da utilidade marginal o método LOGIT foi incapaz de produzir resultados consistentes. Já a estimação da DAC pela análise multivariada mostrou que, caso o governo estivesse disposto a aumentar a provisão de mata em 70 ha, ele deveria despender 254.200 reais por ano, tratando apenas dos cafeicultores vinculados ao programa do PRO-CAFÉ.The object of this study was to identify which method, either LOGIT or multivariate analyses, was the most efficient to estimate the coffee planters' Willingness to Accept a Compensation, when there was a possibility of occurrence of marginal utility. For such, a questionnaire was formulated, with 33 questions involving information on coffee planters' socio - economic characteristics, the use of the methodology of contingent valuation (MCV, and the payment of the "offer game" that reveled the willingness to accept a compensation (WAC, by exchanging a hectare of coffee by a hectare of forest. As expected, because of the marginal utility's bias, the LOGIT method was unable to produce consistent results. However, when the WAC was estimated by multivariate analyses, the results showed that if the government is willing to increase the provision of forest to 70 hectares, it should pay out 254,200 reais (around 116,000 dollars, dealing only with the coffee planters

The importance of regret minimization in the choice for renewable energy programmes: Evidence from a discrete choice experiment

International Nuclear Information System (INIS)

Boeri, Marco; Longo, Alberto

2017-01-01

This study provides a methodologically rigorous attempt to disentangle the impact of various factors – unobserved heterogeneity, information and environmental attitudes – on the inclination of individuals to exhibit either a utility maximization or a regret minimization behaviour in a discrete choice experiment for renewable energy programmes described by four attributes: greenhouse gas emissions, power outages, employment in the energy sector, and electricity bill. We explore the ability of different models – multinomial logit, random parameters logit, and hybrid latent class – and of different choice paradigms – utility maximization and regret minimization – in explaining people's choices for renewable energy programmes. The “pure” random regret random parameters logit model explains the choices of our respondents better than other models, indicating that regret is an important choice paradigm, and that choices for renewable energy programmes are mostly driven by regret, rather than by rejoice. In particular, we find that our respondents' choices are driven more by changes in greenhouse gas emissions than by reductions in power outages. Finally, we find that changing the level of information to one attribute has no effect on choices, and that being a member of an environmental organization makes a respondent more likely to be associated with the utility maximization choice framework. - Highlights: • The first paper to use the Random Regret Minimization choice paradigm in energy economics • With a hybrid latent class model, choices conform to either utility or pure random regret. • The pure random regret random parameters logit model outperforms other models. • Reducing greenhouse gas emissions is more important than reducing power outages.

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...

The Milking Profile of Dairy Cattle Farms in Central Macedonia (Greece

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Ioannis Mitsopoulos

2013-05-01

Full Text Available The purpose of this paper is to provide insights of the profile of the dairy farms of Central Macedonia (Greece, in terms of their milking practices. The analysis is based on data from a random sample of 123 dairy farms, obtained by means of a survey. The employment of the Categorical Principal Component Analysis on the 14 variables initially used to describe milking practices and of the Two-Step Cluster Analysis led to the grouping of the 123 farms to three clusters. Farms of the first cluster, named “Innovative”, use state-of-the-art equipment, automatic systems and innovative milking techniques (31.1% of the sample farms. “Peasant” farms (11.4% are mainly extensive, using mainly bucket plants. The third and most abundant group, the “Modernizing” farms (54.5% are use equipment of reasonable standards and some of them are on the process of renewing it. The results of a Multinomial Logit model verify that “Innovative” farms are large and achieve high yields, while the “Modernizing” ones are smaller, producing milk of lower quality and they are owned by relatively older dairy farmers. An interesting profile is depicted for “Peasant” farms, as they achieve satisfactory economic performance, combined with adequate milk quality. The analytical framework included the reduction of analysis variables to a smaller group of “dimensions”, using the Categorical Principal Component Analysis (CatPCA, based on which farms were clustered to alternative profiles, by employing a Two-Step Cluster (TSC Analysis. Differences in elements of milk quality and in the social profile of farms and farmers were examined among alternative profiles through the estimation of Multinomial Logit Models.

The Impact of Cigarette Packaging Design Among Young Females in Canada: Findings From a Discrete Choice Experiment.

Science.gov (United States)

Kotnowski, Kathy; Fong, Geoffrey T; Gallopel-Morvan, Karine; Islam, Towhidul; Hammond, David

2016-05-01

The tobacco industry uses various aspects of cigarette packaging design to market to specific groups. The current study examined the relative importance of five cigarette packaging attributes--pack structure (eg, "slims"), brand, branding, warning label size, and price--on perceptions of product taste, harm, and interest in trying, among young females in Canada. A discrete choice experiment was conducted with smoking and nonsmoking females, aged 16 to 24 (N = 448). Respondents were shown 10 choice sets, each containing four packs with different combinations of the attributes: pack structure (slim, lipstick, booklet, traditional); brand ("Vogue," "du Maurier"); branding (branded, plain); warning label size (50%, 75%); and price ($8.45, $10.45). For each choice set, respondents chose the brand that they: (1) would rather try, (2) would taste better, and (3) would be less harmful, or "none." For each outcome, the attributes' impact on consumer choice was analyzed using a multinomial logit model. The multinomial logit analyses revealed that young females weighted pack structure to be most important to their intention to try (46%), judgment of product taste (52%), and judgment of product harm (48%). Price and branding were weighted important in trial intent decisions (23% and 18%, respectively) and product taste judgments (29% and 15%, respectively). Whereas warning label size and brand were weighted important when judging product harm (23% and 17%, respectively). The findings suggest that standardized cigarette packaging may decrease demand and reduce misleading perceptions about product harm among young females. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Poverty dynamics in Brazilian metropolitan areas: An analysis based on Hulme and Shepherd's categorization (2002–2011

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Solange Ledi Gonçalves

2015-09-01

Full Text Available Ever-more sophisticated studies on the methodological approach and the conceptual scope of poverty have led to a consensus among scholars on the dynamic characteristic of this phenomenon – in other words, the existence of an in-and-out of privation movement of individuals and families. Within this context, Hulme and Shepherd (2003 defined five groups according to the location of the punctual and average indicators of poverty vis-à-vis the poverty line. This paper's objective is to adapt this typology to Brazil, using PME (Monthly Job Survey micro-data for the 2002–2011 timeframe and the six Brazilian Metropolitan Regions covered by PME as well as, by estimating a multinomial logit, investigate which family characteristics relate to a greater or lesser chance of belonging to each of the chronic and transitory poverty categories. Categorization allows observation that, despite a sweeping across-the-board decline in the percentage of families in all poverty categories in the past decade, those families always or usually poor display demographic, socioeconomic, access to and insertion into the labor market categories which differ from families in transitory poverty or classified as never poor. Moreover, Northeastern metropolitan regions (Salvador and Recife have higher percentages of chronic or transitory poverty. Multinomial logit estimates make it possible to verify that families whose members have completed secondary schooling or college or hold a higher-qualified occupation stand lesser chances of entering into or remaining in poverty. Results call for differentiating among poor families, as they enter into or leave poverty – which is tantamount to saying that the dynamics of poverty must be taken into account as public policies are drawn up.

LA INFLUENCIA DE JUGAR LA LIGA DE CAMPEONES EN EL RESULTADO DE LOS EQUIPOS EN LA LIGA ESPAÑOLA DE FÚTBOL. LA IMPORTANCIA DE LA DENSIDAD COMPETITIVA

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C. Lago Peñas

2010-09-01

Full Text Available

RESUMEN

Los objetivos de este trabajo son dos. En primer lugar estudiar los efectos que tiene disputar un partido de la Liga de Campeones sobre el resultado alcanzado por los equipos en la Liga Española en esa misma semana. En segundo lugar, verificar si la probabilidad de ganar frente a perder en la Liga Española es mayor o no para los equipos con experiencia en la Liga de Campeones frente a aquellos otros conjuntos que disputan por primera vez esta competición. La muestra consiste en 184 partidos de la Liga Española de Fútbol jugados por los equipos que se encontraban simultáneamente disputando la primera fase de la Liga de Campeones en las temporadas 2003-2004, 2004-2005 y 2005-2006. Los datos utilizados en la investigación han sido tomados de la página oficial de la Liga de Campeones, de la Liga Española y suministrados por GECA SPORT.

De acuerdo con los resultados de la estimación de un modelo logit multinomial, disputar un partido de la Liga de Campeones durante la semana de competición no reduce la probabilidad de los equipos de ganar frente a perder en el partido de la Liga Nacional. Incluso tiene un efecto positivo para los equipos debutantes en la competición europea: cuando juegan durante la semana tienen más probabilidades de ganar en la Liga Nacional (p<0,01.

Palabras clave: resultado, fútbol, Liga de Campeones. logit multinomial, Liga Española

ABSTRACT

This paper has two goals. First, studying the impact of playing in the Champions League on the results in the Spanish League. Second, analyzing whether being a beginner team in the

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

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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.

Differentiating regressed melanoma from regressed lichenoid keratosis.

Science.gov (United States)

Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

2017-04-01

Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

AFRREV IJAH, Vol.1 (4) November, 2012

African Journals Online (AJOL)

First Lady

Department of Banking & Finance, University of Benin, Nigeria. E-mail: ... discriminant analysis, ordinary least squares regression, correlation Matrix and Logit - Probit regression, ..... The use of financial statements for control and profit,ŗ In the ...

assessment of expenditure on food in nigerian urban households ...

African Journals Online (AJOL)

USER

2014-04-02

Apr 2, 2014 ... through a structured questionnaire. Descriptive statistics, food security index, multiple linear regression and logit regression were employed to analyze data. ... It is a situation where households are not at risk of losing access.

Investigating the Differences of Single-Vehicle and Multivehicle Accident Probability Using Mixed Logit Model

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Bowen Dong

2018-01-01

Full Text Available Road traffic accidents are believed to be associated with not only road geometric feature and traffic characteristic, but also weather condition. To address these safety issues, it is of paramount importance to understand how these factors affect the occurrences of the crashes. Existing studies have suggested that the mechanisms of single-vehicle (SV accidents and multivehicle (MV accidents can be very different. Few studies were conducted to examine the difference of SV and MV accident probability by addressing unobserved heterogeneity at the same time. To investigate the different contributing factors on SV and MV, a mixed logit model is employed using disaggregated data with the response variable categorized as no accidents, SV accidents, and MV accidents. The results indicate that, in addition to speed gap, length of segment, and wet road surfaces which are significant for both SV and MV accidents, most of other variables are significant only for MV accidents. Traffic, road, and surface characteristics are main influence factors of SV and MV accident possibility. Hourly traffic volume, inside shoulder width, and wet road surface are found to produce statistically significant random parameters. Their effects on the possibility of SV and MV accident vary across different road segments.

Time-varying mixed logit model for vehicle merging behavior in work zone merging areas.

Science.gov (United States)

Weng, Jinxian; Du, Gang; Li, Dan; Yu, Yao

2018-08-01

This study aims to develop a time-varying mixed logit model for the vehicle merging behavior in work zone merging areas during the merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. From the safety perspective, vehicle crash probability and severity between the merging vehicle and its surrounding vehicles are regarded as major factors influencing vehicle merging decisions. Model results show that the model with the use of vehicle crash risk probability and severity could provide higher prediction accuracy than previous models with the use of vehicle speeds and gap sizes. It is found that lead vehicle type, through lead vehicle type, through lag vehicle type, crash probability of the merging vehicle with respect to the through lag vehicle, crash severities of the merging vehicle with respect to the through lead and lag vehicles could exhibit time-varying effects on the merging behavior. One important finding is that the merging vehicle could become more and more aggressive in order to complete the merging maneuver as quickly as possible over the elapsed time, even if it has high vehicle crash risk with respect to the through lead and lag vehicles. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

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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.

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

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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.

Malaria care seeking behavior of individuals in Ghana under the NHIS: Are we back to the use of informal care?

Science.gov (United States)

Fenny, Ama Pokuaa; Asante, Felix A; Enemark, Ulrika; Hansen, Kristian S

2015-04-12

Malaria is Ghana's most endemic disease; occurring across most parts of the country with a significant impact on individuals and the health system as whole. Treatment seeking for malaria care takes various forms. The National Health Insurance Scheme (NHIS) was introduced in 2004 to promote access to health services to mitigate the negative impact of the user fee regime. Ten years on, national coverage is less than 40% of the total population and patients continue to make direct payments for health services. This paper analyses the care-seeking behaviour of households for treatment of malaria in Ghana under the NHI policy. Using a cross-sectional survey of household data collected from three districts in Ghana covering the 3 ecological zones namely the coastal, forest and savannah, a multinomial logit model is estimated. The sample consists of 365 adults and children reporting being ill with malaria in the last four weeks prior to the study. Out of the total, 58% were insured and 71% of them sought care from a formal health facility. Among the insured, 15% chose informal care compared to 48% among the uninsured. The results from the multinomial logit estimations show that health insurance and travel time to health facility are significant determinants of health care demand. The results show that the insured are 6 times more likely to choose regional/district hospitals: 5 times more likely to choose health centres/clinics and 7 times more likely to choose private hospitals/clinics over informal care when compared with the uninsured. Individual characteristics such as age, education and wealth status were significant determinants of health care provider choice for specific categories of health facilities. Overall, for malaria care the uninsured are more likely to choose informal care compared to the insured for the treatment of malaria.

Emergence Corporate Financial Distressin Emerging Market: Empirical Evidence from Indonesia Stock Exchange(IDX 2004-2008

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Koes Pranowo

2011-11-01

Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 st1\\:*{behavior:url(#ieooui } /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} Financial recovery is the most difficult in financial management. Therefore, this is important to study how a company in financially-distress can survive to rise up to a healthy financial condition (emergence financial distress. The research consists of 200 non financial companies which are listed on Indonesia Stock Exchange (IDX for the period of 2004-2008. This study focuses on management of working capital. How a company fulfill its current liabilities, and its sources in current assets which shall be cashed at the short term period. By using Multinomial logit, we analyzed the probability a financially-distress company rise up to emergence financial distress or stay of the status of financial distress and what are financial indicators affect to a company in the status of Non Financial Distress tend to Financial Distress. Thus, the important thing is to determine financial ratios which can be an indicator to determine of emergence financial distress. We find a positive relationship between Profit, efficiency and emergence financial distress and a negative relationship between leverage and emergence financial distress.   Keywords: Emergence Financial Distress, Indonesia Stock Exchange (IDX, Multinomial Logit JEL Classification Codes: G 3

The Dynamics of Online Purchase Visits: Inertia or Switching?

Institute of Scientific and Technical Information of China (English)

Zelin Zhang; Xia Wang; Peter T.L.Popkowski Leszczyc; Xiao Zuo

2016-01-01

This paper studies the dynamics of online purchase patterns,focusing on the impact of the channel used on conversion probability,as well as the transition of channel use over time.A novel data set from a major Chinese online travel agency is used for analysis,consisting of four months of data with 24,337 store visits through three types of channels:direct visit,search advertising and referral.Results of a Bayesian multinomial logit model show that the search channel significantly affects consumers' conversion probability,and show a high degree of inertia in channel use.This finding contrasts sharply with suggestions of previous research that most future purchases will converge to the direct-visit channel.

Pobreza subjetiva y reconocimiento étnico en Colombia: análisis para principales regiones, año 2013

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José Santiago Arroyo-Mina

2017-01-01

Full Text Available En este artículo se contrasta empíricamente la hipótesis que, en Colombia, laraza tiene un efecto significativo en la percepción de pobreza de los propiosindividuos y condiciona la manera como éstos perciben los diferentes aspectosde bienestar. Se emplea la Encuesta Nacional de Calidad de Vida (ECV reali-zada en Colombia para el año 2013. La estimación de un modelo logit multi-nomial revela que el ser afrocolombiano aumenta la probabilidad de percibir queel ingreso promedio del hogar no es suficiente para cubrir sus gastos mínimos yaleja la probabilidad de percibir que éstos sean, al menos, suficientes.

Can a publicly funded home care system successfully allocate service based on perceived need rather than socioeconomic status? A Canadian experience.

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Laporte, Audrey; Croxford, Ruth; Coyte, Peter C

2007-03-01

The present quantitative study evaluates the degree to which socioeconomic status (SES), as opposed to perceived need, determines utilisation of publicly funded home care in Ontario, Canada. The Registered Persons Data Base of the Ontario Health Insurance Plan was used to identify the age, sex and place of residence for all Ontarians who had coverage for the complete calendar year 1998. Utilisation was characterised in two dimensions: (1) propensity - the probability that an individual received service, which was estimated using a multinomial logit equation; and (2) intensity - the amount of service received, conditional on receipt. Short- and long-term service intensity were modelled separately using ordinary least squares regression. Age, sex and co-morbidity were the best predictors (P funded home care as well as how much care was received, with sicker individuals having increased utilisation. The propensity and intensity of service receipt increased with lower SES (P funded home care service was primarily based on perceived need rather than ability to pay, barriers to utilisation for those from areas with a high proportion of recent immigrants were identified. Future research is needed to assess whether the current mix and level of publicly funded resources are indeed sufficient to offset the added costs associated with the provision of high-quality home care.

Smallholder farmer’s perceived effects of climate change on crop production and household livelihoods in rural Limpopo province, South Africa

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Ubisi Nomcebo R.

2017-01-01

Full Text Available This study investigated the perceived effects of climate change on crop production and household livelihoods of smallholder farmers in Mopani and Vhembe district, South Africa. Data was collected through a questionnaire administered to 150 smallholder farmers. The questionnaires were complemented by 8 focus group discussions and secondary data. Multinomial logit regression model was used to analyse the factors influencing smallholder farmers’ choice of climate change adaptation strategies. The study findings revealed that subsistence farmers perceived prolonged droughts (56.4% as the main shock stressing crop production. Droughts often lead to low crop yield and high crop failure (73.3%. In response to the prevailing climatic conditions different gender adopted different strategies, 41% of female farmers adapted by changing planting dates, while male farmers employed crop variety and diversification (35% and mixed cropping (15%. The smallholder farmers were vulnerable with limited adaptive capacity to withstand climate change due to compromised social, human, physical, natural and financial assets. The results showed that smallholder farmers tend to adapt better when they have access to extension officers (P<0.01. Therefore, it is important for the government to strengthen the relationship between smallholder farmers and extension officers for better climate change adaptation.

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

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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.

FACTORS THAT AFFECT TRANSPORT MODE PREFERENCE FOR GRADUATE STUDENTS IN THE NATIONAL UNIVERSITY OF MALAYSIA BY LOGIT METHOD

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ALI AHMED MOHAMMED

2013-06-01

Full Text Available A study was carried out to examine the perceptions and preferences of students on choosing the type of transportation for their travels in university campus. This study focused on providing personal transport users road transport alternatives as a countermeasure aimed at shifting car users to other modes of transportation. Overall 456 questionnaires were conducted to develop a choice of transportation mode preferences. Consequently, Logit model and SPSS were used to identify the factors that affect the determination of the choice of transportation mode. Results indicated that by reducing travel time by 70% the amount of private cars users will be reduced by 84%, while reduction the travel cost was found to be highly improving the public modes of utilization. This study revealed positive aspects is needed to shift travellers from private modes to public. The positive aspect contributes to travel time and travel cost reduction, hence improving the services, whereby contributing to sustainability.

Retro-regression--another important multivariate regression improvement.

Science.gov (United States)

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

Modified Regression Correlation Coefficient for Poisson Regression Model

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Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Disposición a pagar por reducir el tiempo de viaje en Tunja (Colombia): Comparación entre estudiantes y trabajadores con un modelo Logit mixto

OpenAIRE

Luis Gabriel Márquez Díaz

2013-01-01

Resumen: El estudio analiza la diferencia en la disposición a pagar de estudiantes y trabajadores por reducir el tiempo de viaje, en un contexto de elección de modo de transporte para la ciudad de Tunja (Colombia). Se utilizó un modelo logit mixto, calibrado con datos provenientes de una encuesta de preferencias declaradas. La especificación del modelo supuso la variación aleatoria de los coeficientes del tiempo de acceso, tiempo de espera y tiempo de viaje. Se encontró que la disposición a p...

The Eldicus prospective, observational study of triage decision making in European intensive care units: Part I-European Intensive Care Admission Triage Scores (EICATS)

DEFF Research Database (Denmark)

Sprung, Charles L; Baras, Mario; Iapichino, Gaetano

2012-01-01

built. Values for variables were grouped into categories determined by the locally weighted least squares graphical method applied to the logit of the mortality and by univariate logistic regressions for reducing candidates for the score. Multivariate logistic regression was used to construct the final...

The relationship between venture capital investment and macro economic variables via statistical computation method

Science.gov (United States)

Aygunes, Gunes

2017-07-01

The objective of this paper is to survey and determine the macroeconomic factors affecting the level of venture capital (VC) investments in a country. The literary depends on venture capitalists' quality and countries' venture capital investments. The aim of this paper is to give relationship between venture capital investment and macro economic variables via statistical computation method. We investigate the countries and macro economic variables. By using statistical computation method, we derive correlation between venture capital investments and macro economic variables. According to method of logistic regression model (logit regression or logit model), macro economic variables are correlated with each other in three group. Venture capitalists regard correlations as a indicator. Finally, we give correlation matrix of our results.

Dual Regression

OpenAIRE

Spady, Richard; Stouli, Sami

2012-01-01

We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

Risk factors associated with the presence and severity of food insecurity in rural Honduras.

Science.gov (United States)

Ben-Davies, Maureen E; Kinlaw, Alan; Estrada Del Campo, Yaniré; Bentley, Margaret E; Siega-Riz, Anna Maria

2014-01-01

To identify factors associated with the presence and severity of food insecurity among a sample of Honduran caregivers of young children. Cross-sectional study in which the dependent variable, household food insecurity, was measured using a fourteen-item questionnaire developed and validated in a population of similar cultural context. A predictive modelling strategy used backwards elimination in logistic regression and multinomial logit regression models to compute odds ratios and 95% confidence intervals for food insecurity. Rural Honduras in the department of Intibucá, between March and April 2009. Two-hundred and ninety-eight Honduran caregivers of children aged 6-18 months. Ninety-three per cent of households were classified as having some degree of food insecurity (mild, moderate or severe). After controlling for caregiver age and marital status, compared with caregivers with more than primary-school education, those with less than primary-school education had 3·47 (95% CI 1·34, 8·99) times the odds of severe food insecurity and 2·29 (95% CI 1·00, 5·25) times the odds of moderate food insecurity. Our results also found that child anthropometric status was not associated with the presence or severity of food insecurity. These results show that among the sociodemographic factors assessed, food insecurity in rural Honduras is associated with maternal education. Understanding key factors associated with food insecurity that are unique to Honduras can inform the design of interventions to effectively mitigate the negative impact of food insecurity on children.

Analysis of Salmonella sp bacterial contamination on Vannamei Shrimp using binary logit model approach

Science.gov (United States)

Oktaviana, P. P.; Fithriasari, K.

2018-04-01

Mostly Indonesian citizen consume vannamei shrimp as their food. Vannamei shrimp also is one of Indonesian exports comodities mainstay. Vannamei shrimp in the ponds and markets could be contaminated by Salmonella sp bacteria. This bacteria will endanger human health. Salmonella sp bacterial contamination on vannamei shrimp could be affected by many factors. This study is intended to identify what factors that supposedly influence the Salmonella sp bacterial contamination on vannamei shrimp. The researchers used the testing result of Salmonella sp bacterial contamination on vannamei shrimp as response variable. This response variable has two categories: 0 = if testing result indicate that there is no Salmonella sp on vannamei shrimp; 1 = if testing result indicate that there is Salmonella sp on vannamei shrimp. There are four factors that supposedly influence the Salmonella sp bacterial contamination on vannamei shrimp, which are the testing result of Salmonella sp bacterial contamination on farmer hand swab; the subdistrict of vannamei shrimp ponds; the fish processing unit supplied by; and the pond are in hectare. This four factors used as predictor variables. The analysis used is Binary Logit Model Approach according to the response variable that has two categories. The analysis result indicates that the factors or predictor variables which is significantly affect the Salmonella sp bacterial contamination on vannamei shrimp are the testing result of Salmonella sp bacterial contamination on farmer hand swab and the subdistrict of vannamei shrimp ponds.

Best-Worst scaling…reflections on presentation, analysis, and lessons learnt from case 3 BWS experiments

DEFF Research Database (Denmark)

Adamsen, Jannie Mia; Rundle-Thiele, Sharyn; Whitty, Jennifer

2013-01-01

Surveys based on Likert scales and similar ratings-based scales continue to dominate market research practice despite their many and well-documented limitations. Key issues of concern for Likert scales include over- or under-reporting depending on the context, and variation in responses based......,600 respondents. One case 3 BW experiment investigating consumer preferences for organic apples is featured and evaluated using two approaches. The first analysis treats the data as a case 1 BW experiment to outline the simplicity of case 1 analysis. Case 3 BW analysis involving multinomial logit and latent class...... do believe the BWS method has a significant potential to improve predictability in market research – the response rate and positive participant feedback speaks for itself....

Completion of Upper Secondary Education: What Mechanisms Are at Stake?

DEFF Research Database (Denmark)

Munk, Martin D.

2013-01-01

also investigate the importance of characteristics other than the traditional variables, such as fathers’ and mothers’ occupations, their education and household income, often applied in studies of educational attainment. I used a recent 1984 cohort database with information about educational...... completion and an informative set of measurements on non-cognitive capacities, parental cultural capital, cultural capital, reading score, several school-related variables, and a rich set of family background variables. Attainment of upper secondary education was analyzed by a multinomial logit model......, showing that characteristics other than the traditional variables all have significant importance. The analysis clearly depicted that the social position and educational levels of both parents remain important in determining whether the child embarks on completing an upper secondary education...

Land related grievances shape tropical forest-cover in areas affected by armed-conflict

DEFF Research Database (Denmark)

Nunez, Augusto Carlos Castro; Mertz, Ole; Buritica, Alexander

2017-01-01

Armed-conflicts often occur in tropical areas considered to be of high ‘conservation-value’, termed as such for their biodiversity or carbon-storage functions. Despite this important overlap, few studies have assessed how forest-biomass is affected by armed-conflicts. Thus, in this paper we develop...... a multinomial logit model to examine how outcomes of the interactions between carbon-storage, armed-conflict and deforestation rates are linked to social, institutional and economic factors. We use Colombia as a case study because of its protracted armed-conflict, high forest-cover, sustained deforestation......-ownership disputes, the Colombian government might uphold their international climate change commitments via reducing deforestation and hence forest based carbon emissions, while pursuing their national security objective via undermining opportunities for guerrilla groups to operate....

Internal migration in Mexico and its determinants

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Rogelio Varela Llamas

2016-12-01

Full Text Available This paper presents an analysis of internal migration in Mexico. Using micro data from the National Survey on Occupation and Employment (enoe, we estimate a multinomial logit model for the case of intrastate and interstate migration. We also conduct estimations for municipalities of different sizes. The results suggest that the probability of migrating increases with the number of weeks spent searching for a job, regardless of whether the search is conducted while the individual is employed or unemployed. In addition, we find that as the number of hours of work per week increases, the probability of migrating rises. The search process does not increase the probability of migrating in rural communities as it does in urban centers.

Working hours and depressive symptoms over 7 years: evidence from a Korean panel study.

Science.gov (United States)

Ahn, Seoyeon

2018-04-01

This study aims to examine how working hours influence depressive symptoms and the association between working hours and depressive symptoms differently across genders. The sample consists of salaried workers aged 25-64 years who participated in two consecutive waves of the seven-wave Korean Welfare Panel Study (2007-2013) (n = 6813 individuals, 27,986 observations) which is a survey of a nationally representative sample of the South Korean population. I apply logit regression and fixed-effects logit regression to examine the causal relation between (intra-)individual changes of working hours and depressive symptoms over a 7-year period. Results from logit model and fixed-effects logit model show that less than 30 h of work per week and more than 60 h of work per week are associated with significantly higher levels of depressive symptoms. Sex-stratified analyses reveal that women who worked over 60 h per week were at increased risk of showing depressive symptoms compared with women who worked 30-40 h per week. No significant increase in depressive symptoms was seen in men who worked more than 60 h per week. However, men working less than 30 h per week are more likely to report higher levels of depressive symptoms. These results suggest that work arrangement affects the mental health of men and women differently.

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

Valuing attributes of enhanced traffic information: an experience in Kolkata

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D. Basu

2007-10-01

Full Text Available Most of the traffic information considers a single item like travel time or delay. In the present work, enhanced traffic information displaying instantaneous travel time and its variation from the previous interval to the present, is considered. An initial investigation is made on the effectiveness of such traffic information on route choice behavior of trip makers by valuation of attributes of the traffic information. Taking a case study of two urban corridors in the Kolkata metro city, India, the valuation is done separately for private car and taxi trip makers. The stated preference (choice based data collected from trip makers are analyzed using both multinomial logit (MNL and mixed logit (ML modeling techniques. Assuming sparsely used constrained triangular distribution of random parameters, two different types of ML model are developed: one with independent choice sets and the other one by accounting heterogeneity around the mean of random parameter(s. Both family income and trip purpose are found to decompose heterogeneity around the mean estimate(s. The values of travel time and their variation presented in the paper encourage further investigation on such type of traffic information for management of congestion on alternative urban corridors both spatially and temporally.

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

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

Science.gov (United States)

Cade, Brian S.; Noon, Barry R.; Scherer, Rick D.; Keane, John J.

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical conditional distribution of a bounded discrete random variable. The logistic quantile regression model requires that counts are randomly jittered to a continuous random variable, logit transformed to bound them between specified lower and upper values, then estimated in conventional linear quantile regression, repeating the 3 steps and averaging estimates. Back-transformation to the original discrete scale relies on the fact that quantiles are equivariant to monotonic transformations. We demonstrate this statistical procedure by modeling 20 years of California Spotted Owl fledgling production (0−3 per territory) on the Lassen National Forest, California, USA, as related to climate, demographic, and landscape habitat characteristics at territories. Spotted Owl fledgling counts increased nonlinearly with decreasing precipitation in the early nesting period, in the winter prior to nesting, and in the prior growing season; with increasing minimum temperatures in the early nesting period; with adult compared to subadult parents; when there was no fledgling production in the prior year; and when percentage of the landscape surrounding nesting sites (202 ha) with trees ≥25 m height increased. Changes in production were primarily driven by changes in the proportion of territories with 2 or 3 fledglings. Average variances of the discrete cumulative distributions of the estimated fledgling counts indicated that temporal changes in climate and parent age class explained 18% of the annual variance in owl fledgling production, which was 34% of the total variance. Prior fledgling production explained as much of

Regression: A Bibliography.

Science.gov (United States)

Pedrini, D. T.; Pedrini, Bonnie C.

Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

Analysis of the Retention and Affiliation Factors Affecting the Active and Reserve Naval Nurse Corps

National Research Council Canada - National Science Library

Messmer, Scott J; Pizanti, Kimberly A

2007-01-01

...) an empirical analysis to analyze characteristics of those who are retained in the active Naval Nurse Corps and those who affiliate with the reserve Naval Nurse Corps using multivariate logit regressions...

Survey Probability and Factors affecting Farmers Participation in Future and Option Markets Case Study: Cotton product in Gonbad kavos city

Directory of Open Access Journals (Sweden)

F. sakhi

2016-03-01

Full Text Available Introduction: Farmers are facing with a variety of natural and unnatural risks in agricultural activities, and thus their income is unstable. A wide range of risks such as risks of production, price risk, financial and human risks, influence the income of agricultural products. One of the major risks that farmers faced is the risk of price volatility of agricultural products. Cotton is one of the agricultural products with high real price volatility. Numerous tools for marketing and risk management for agricultural products in the face of price risks are available. Futures and options contracts may be the most important available tools (to reduce price volatility in agricultural products. The purpose of the current study was to look at the possibility of farmers participations in the future and option markets that presented as a means to reduce the cotton prices volatility. The dependent variable for this purpose had four categories and these included: participate in both the market, participation in the future market, participation in the option market and participation in both future and option markets. Materials and Methods: data gathered with interview and completing 200 questionnaires of cotton growers using simple random sampling. Multinomial Logit Regression Model was used for data analysis. Results and Discussion: To measure content validity of the preliminary study the validity of confirmatory factor analysis were used. For calculating reliability, the pre-test done with 30 questionnaires and reliability, coefficient Cronbach alpha was 0.79. The independence of dependent variables categories was confirmed by Hausman test results. The Likelihood ratio and Wald showed these categories are not combinable. Results indicated into period 2014 -2015 and the sample under study, 35% of cotton growers unwilling to participate in future and option markets. Farmers willingness to participate in future and option market was 19% and %21

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...

Advanced statistics: linear regression, part I: simple linear regression.

Science.gov (United States)

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Spatial Distribution of Underweight, Overweight and Obesity among Women and Children: Results from the 2011 Uganda Demographic and Health Survey

Directory of Open Access Journals (Sweden)

Kedir N. Turi

2013-10-01

Full Text Available While undernutrition and infectious diseases are still persistent in developing countries, overweight, obesity, and associated comorbidities have become more prevalent. Uganda, a developing sub-Saharan African country, is currently experiencing the public health paradox of undernutrition and overnutrition. We utilized the 2011 Uganda Demographic and Health Survey (DHS to examine risk factors and hot spots for underweight, overweight, and obesity among adult females (N = 2,420 and their children (N = 1,099 using ordinary least squares and multinomial logit regression and the ArcGIS Getis-Ord Gi* statistic. Overweight and obese women were significantly more likely to have overweight children, and overweight was correlated with being in the highest wealth class (OR = 2.94, 95% CI = 1.99–4.35, and residing in an urban (OR = 1.76, 95% CI = 1.34–2.29 but not a conflict prone (OR = 0.48, 95% CI = 0.29–0.78 area. Underweight clustered significantly in the Northern and Northeastern regions, while overweight females and children clustered in the Southeast. We demonstrate that the DHS can be used to assess geographic clustering and burden of disease, thereby allowing for targeted programs and policies. Further, we pinpoint specific regions and population groups in Uganda for targeted preventive measures and treatment to reduce the burden of overweight and chronic diseases in Uganda.

Influence of coronary artery disease prevalence on predictive values of coronary CT angiography: a meta-regression analysis

Energy Technology Data Exchange (ETDEWEB)

Schlattmann, Peter [University Hospital of Friedrich-Schiller University Jena, Department of Medical Statistics, Informatics and Documentation, Jena (Germany); Schuetz, Georg M. [Freie Universitaet Berlin, Charite, Medical School, Department of Radiology, Humboldt-Universitaet zu Berlin, Berlin (Germany); Dewey, Marc [Freie Universitaet Berlin, Charite, Medical School, Department of Radiology, Humboldt-Universitaet zu Berlin, Berlin (Germany); Charite, Institut fuer Radiologie, Berlin (Germany)

2011-09-15

To evaluate the impact of coronary artery disease (CAD) prevalence on the predictive values of coronary CT angiography. We performed a meta-regression based on a generalised linear mixed model using the binomial distribution and a logit link to analyse the influence of the prevalence of CAD in published studies on the per-patient negative and positive predictive values of CT in comparison to conventional coronary angiography as the reference standard. A prevalence range in which the negative predictive value was higher than 90%, while at the same time the positive predictive value was higher than 70% was considered appropriate. The summary negative and positive predictive values of coronary CT angiography were 93.7% (95% confidence interval [CI] 92.8-94.5%) and 87.5% (95% CI, 86.5-88.5%), respectively. With 95% confidence, negative and positive predictive values higher than 90% and 70% were available with CT for a CAD prevalence of 18-63%. CT systems with >16 detector rows met these requirements for the positive (P < 0.01) and negative (P < 0.05) predictive values in a significantly broader range than systems with {<=}16 detector rows. It is reasonable to perform coronary CT angiography as a rule-out test in patients with a low-to-intermediate likelihood of disease. (orig.)

Influence of coronary artery disease prevalence on predictive values of coronary CT angiography: a meta-regression analysis

International Nuclear Information System (INIS)

Schlattmann, Peter; Schuetz, Georg M.; Dewey, Marc

2011-01-01

To evaluate the impact of coronary artery disease (CAD) prevalence on the predictive values of coronary CT angiography. We performed a meta-regression based on a generalised linear mixed model using the binomial distribution and a logit link to analyse the influence of the prevalence of CAD in published studies on the per-patient negative and positive predictive values of CT in comparison to conventional coronary angiography as the reference standard. A prevalence range in which the negative predictive value was higher than 90%, while at the same time the positive predictive value was higher than 70% was considered appropriate. The summary negative and positive predictive values of coronary CT angiography were 93.7% (95% confidence interval [CI] 92.8-94.5%) and 87.5% (95% CI, 86.5-88.5%), respectively. With 95% confidence, negative and positive predictive values higher than 90% and 70% were available with CT for a CAD prevalence of 18-63%. CT systems with >16 detector rows met these requirements for the positive (P < 0.01) and negative (P < 0.05) predictive values in a significantly broader range than systems with ≤16 detector rows. It is reasonable to perform coronary CT angiography as a rule-out test in patients with a low-to-intermediate likelihood of disease. (orig.)

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

Revealing additional preference heterogeneity with an extended random parameter logit model: the case of extra virgin olive oil

Directory of Open Access Journals (Sweden)

Ahmed Yangui

2014-07-01

Full Text Available Methods that account for preference heterogeneity have received a significant amount of attention in recent literature. Most of them have focused on preference heterogeneity around the mean of the random parameters, which has been specified as a function of socio-demographic characteristics. This paper aims at analyzing consumers’ preferences towards extra-virgin olive oil in Catalonia using a methodological framework with two novelties over past studies: 1 it accounts for both preference heterogeneity around the mean and the variance; and 2 it considers both socio-demographic characteristics of consumers as well as their attitudinal factors. Estimated coefficients and moments of willingness to pay (WTP distributions are compared with those obtained from alternative Random Parameter Logit (RPL models. Results suggest that the proposed framework increases the goodness-of-fit and provides more useful insights for policy analysis. The most important attributes affecting consumers’ preferences towards extra virgin olive oil are the price and the product’s origin. The consumers perceive the organic olive oil attribute negatively, as they think that it is not worth paying a premium for a product that is healthy in nature.

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...

UN MODELO LOGIT PARA LA FRAGILIDAD DEL SISTEMA FINANCIERO VENEZOLANO DENTRO DEL CONTEXTO DE LOS PROCESOS DE FUSIÓN E INTERVENCIÓN | A LOGIT APPROACH OF THE VENEZUELAN FINANCIAL SYSTEM WITHIN THE CONTEXT OF MERGER AND INTERVENTION

Directory of Open Access Journals (Sweden)

César Rubicundo

2016-08-01

Full Text Available In Venezuela there have been more than 30 mergers, after the approval of the Banking Act in 1999, since from 103 institutions, the financial system closed the year 2013 with 35 brokerage firms, which represents a decrease of 66% due to 20 coalitions, 30 transformations and 18 settlements. Therefore, an analysis is proposed of the current economic situation of the financial system in the context of mergers and interventions, considering internal and external factors according to the constituted capital. The study was based on information from 37 private capital institutions and 04 public institutions, between January 2009 and December 2013. The previous analysis for privately held banks, showed that these institutions have a 78.40% chance of not incurring in situations of fragility; while the State capital banks have 83.30% of surviving in the market. As for the estimated logit models, it was found that the liquidity ratio, ROE, management index and inflation, are components that push towards a fragile situation for privately held banks, with a probability forecast of fragility. With regard to the state capital banks, this situation is explained by a 62.50% equity index, ROE, and inflation. A probability of stability for these banks is expected. The joint model forecasted a probability of a stable financial system for the coming months.

Education and Occupational Outcomes

DEFF Research Database (Denmark)

Johnes, Geraint; Freguglia, Ricardo; Spricigo, Gisele

2016-01-01

Purpose: The purpose of this paper is to examine the dynamic relationship between policies related to educational provision and both educational participation and occupational outcomes in Brazil, using PNAD and RAIS-Migra data. Design/methodology/approach: Outcomes are examined using: static...... multinomial logit analysis, and structural dynamic discrete choice modelling. The latter approach, coupled with the quality of the RAIS-Migra data source, allows the authors to evaluate the education policy impacts over time. Findings: The main results show that the education level raises the propensity...... that the individual will be in formal sector work or still in education, and reduces the probability of the other outcomes. Transition into non-manual formal sector work following education may, however, occur via a spell of manual work. Originality/value: This is the first study of occupational destination...

Bottom fish assemblages at the shelf and continental slope off East Greenland

DEFF Research Database (Denmark)

Jørgensen, Ole A; Hvingel, Carsten; Møller, P.R.

2015-01-01

During 2006 and 2008 two bottom trawl surveys were conducted at East Greenland to 72°N covering depths down to 1500 m. In the 149 trawl hauls in total 113 fish species were recorded of which 37 were considered pelagic and excluded from the analyses. As a first step the abundance data for the 76...... benthic species were used for analyses of the fish fauna diversity and fish assemblages. Nine assemblages were found by a standard type of cluster analysis. A Bayesian multinomial logit model was then applied to calculate vectors of probabilities defining the likelihood of each haul belonging to each...... distribution, species composition, temperature and depth. Three of the assemblages were located in the cold Iceland Sea while six were found in the somewhat warmer Irminger Sea...

Meta-analysis data for 104 Energy-Economy Nexus papers.

Science.gov (United States)

Hajko, Vladimír; Kociánová, Agáta; Buličková, Martina

2017-06-01

The data presented here are manually encoded characteristics of research papers in the area of Energy-Economy Nexus (empirical investigation of Granger causality between energy consumption and economic growth) that describe the methods, samples, and other details related to the individual estimations done in the examined empirical papers. Data cover papers indexed by Scopus, published in economic journals, written in English, after year 2000. In addition, papers were manually filtered to only those that deal with Energy-Economy Nexus investigation and have at least 10 citations at (at the time of query - November 2015). This data are to be used to conduct meta-analysis - associated dataset was used in Hajko [1]. Early version of the dataset was used for multinomial logit estimation in Master thesis by Kociánová [2].

The role of respondents’ comfort for variance in stated choice surveys

DEFF Research Database (Denmark)

Emang, Diana; Lundhede, Thomas; Thorsen, Bo Jellesmark

2017-01-01

they complete surveys correlates with the error variance in stated choice models of their responses. Comfort-related variables are included in the scale functions of the scaled multinomial logit models. The hypothesis was that higher comfort reduces error variance in answers, as revealed by a higher scale...... parameter and vice versa. Information on, e.g., sleep and time since eating (higher comfort) correlated with scale heterogeneity, and produced lower error variance when controlled for in the model. That respondents’ comfort may influence choice behavior suggests that knowledge of the respondents’ activity......Preference elicitation among outdoor recreational users is subject to measurement errors that depend, in part, on survey planning. This study uses data from a choice experiment survey on recreational SCUBA diving to investigate whether self-reported information on respondents’ comfort when...

Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

International Nuclear Information System (INIS)

Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

2007-01-01

Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

Polynomial regression analysis and significance test of the regression function

International Nuclear Information System (INIS)

Gao Zhengming; Zhao Juan; He Shengping

2012-01-01

In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

Determinants of Informal Employment: A Case of Tanzania's ...

African Journals Online (AJOL)

industry. A Logit regression model is employed in estimating factors that influence the choice ... International Labour Organization (ILO) (2013), the informal economy ... This study uses primary data which was collected in six most vibrant urban.

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

Frequency and predictors of psychological distress after a diagnosis of epilepsy: A community-based study.

Science.gov (United States)

Xu, Ying; Hackett, Maree L; Glozier, Nick; Nikpour, Armin; Bleasel, Andrew; Somerville, Ernest; Lawson, John; Jan, Stephen; Hyde, Lorne; Todd, Lisa; Martiniuk, Alexandra; Ireland, Carol; Anderson, Craig S

2017-10-01

The objective of the study was to determine the frequency and predictors of psychological distress after a diagnosis of epilepsy. The Sydney Epilepsy Incidence Study to Measure Illness Consequences (SEISMIC) was a prospective, multicenter, community-based study of people of all ages with newly diagnosed epilepsy in Sydney, Australia. Analyses involved multivariate logistic regression and multinomial logit regression to identify predictors of psychological distress, assessed using the Hospital Anxiety and Depression Scale (HADS) and the Strengths and Difficulties Questionnaire (SDQ), as part of structured interviews. Psychological distress occurred in 33% (95% confidence interval [CI] 26 to 40%) and 24% (95% CI 18 to 31%) of 180 adults at baseline and 12months, respectively, and 23% (95% CI 14 to 33%) of 77 children at both time points. Thirty adults and 7 children had distress at baseline who recovered at 12months, while 15 adults and 7 children had new onset of distress during this period. History of psychiatric or behavioral disorder (for adults, odds ratio [OR] 6.82, 95% CI 3.08 to 15.10; for children, OR 28.85, 95% CI 2.88 to 288.60) and higher psychosocial disability (adults, OR 1.17, 95% CI 1.07 to 1.27) or lower family functioning (children, OR 1.80, 95% CI 1.08 to 3.02) were associated with psychological distress (C statistics 0.80 and 0.78). Psychological distress is common and fluctuates in frequency after a diagnosis of epilepsy. Those with premorbid psychological, psychosocial, and family problems are at high risk of this adverse outcome. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantile Regression Methods

DEFF Research Database (Denmark)

Fitzenberger, Bernd; Wilke, Ralf Andreas

2015-01-01

if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

SHORT COMMUNICATIONS

African Journals Online (AJOL)

The relationships between S. mansoni, hookworm and S. mansoni + hookworm with P. falciparum were investigated by fitting logistic regression model taking P. falciparum as response variable. Furthermore, co-infections analysis was investigated by fitting multinomial logistic regression model where all combination of ...

Transaction cost determinants of credit governance structures of ...

African Journals Online (AJOL)

This paper explores transaction cost determinants of credit governance structures (CGS) of commercial banks in Tanzania. Descriptive statistics, linear regression model, binary and multinomial logistic regression models were employed for analysis. Findings revealed four modes of credit governance structures that are ...

Regression Phalanxes

OpenAIRE

Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

2017-01-01

Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

OpenAIRE

Nicolas Sommet; Davide Morselli

2017-01-01

This paper aims to introduce multilevel logistic regression analysis in a simple and practical way. First, we introduce the basic principles of logistic regression analysis (conditional probability, logit transformation, odds ratio). Second, we discuss the two fundamental implications of running this kind of analysis with a nested data structure: In multilevel logistic regression, the odds that the outcome variable equals one (rather than zero) may vary from one cluster to another (i.e. the i...

Advanced statistics: linear regression, part II: multiple linear regression.

Science.gov (United States)

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Regression to Causality : Regression-style presentation influences causal attribution

DEFF Research Database (Denmark)

Bordacconi, Mats Joe; Larsen, Martin Vinæs

2014-01-01

of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

Going Back Part-time: Family Leave Legislation and Women's Return to Work.

Science.gov (United States)

Schott, Whitney

2012-02-01

Using a multinomial logit model with data from the Survey of Income and Program Participation, this paper tests whether the implementation of the Family and Medical Leave Act (FMLA) is associated with an increase in return to work at part-time status among first-time mothers working full-time during their pregnancy. I find a statistically significant trend of increasingly higher odds of returning to work at part-time status relative to return at full-time status, beginning in 1993 (the year in which the FMLA is implemented). Furthermore, an additional week of either state or federal leave is significantly associated with a higher odds of return at part-time status. This article provides evidence that job protection and leave legislation may help facilitate higher levels of labor force participation among women with small children, through more flexible work arrangements.

Going Back Part-time: Family Leave Legislation and Women’s Return to Work

Science.gov (United States)

2012-01-01

Using a multinomial logit model with data from the Survey of Income and Program Participation, this paper tests whether the implementation of the Family and Medical Leave Act (FMLA) is associated with an increase in return to work at part-time status among first-time mothers working full-time during their pregnancy. I find a statistically significant trend of increasingly higher odds of returning to work at part-time status relative to return at full-time status, beginning in 1993 (the year in which the FMLA is implemented). Furthermore, an additional week of either state or federal leave is significantly associated with a higher odds of return at part-time status. This article provides evidence that job protection and leave legislation may help facilitate higher levels of labor force participation among women with small children, through more flexible work arrangements. PMID:22685365

Sources of Variation in the Age Composition of Sandeel Landings

DEFF Research Database (Denmark)

Kvist, Trine; Gislason, Hannes; Thyregod, Poul

2001-01-01

in the samples is significantly lower in the start and end of the fishing season. This suggests that the older sandeel are available to the fishery for a shorter time period that the 1-group. Significant differences are found in the age composition between the four laboratories involved in the age determination......The variation of the age composition of the landings of lesser sandeel in the Danish industrial fishery in the North Sea over the period From 1984-1993 is analysed by continuation-ratio logits and generalised linear models. The analysis takes the multinomial characteristics of the age composition....... Although the variation between ICES statistical rectangles is substantial there is a significant difference between the age composition in the northern and southern part of the North Sea. However, only one of the three finer geographical stratifications proposed to improve the assessment results...

[Depression Symptoms of Mothers and Fathers of Persons with Schizophrenia].

Science.gov (United States)

Alexandrowicz, Rainer W; König, Daniel; Unger, Annemarie; Klug, Günter; Soulier, Nathalie; Freidl, Marion; Friedrich, Fabian

2016-05-01

The purpose of the present study was to investigate if depression symptomatology of patients' parents is predicted by the symptoms of schizophrenia. 101 mothers and 101 fathers of the same patients suffering from schizophrenia were included into this study. Parents filled in the "Beck Depression Inventory". Patients were assessed by means of the "Positive and Negative Syndrome Scale". For statistical analyses a Multidimensional Random Coefficients Multinomial Logit Model was applied. We found a significant positive association between negative symptoms and depression severity of fathers and mothers. Further, a significant positive association between positive symptoms and depression severity of fathers, but not of mothers was found. Our results show that depression of mothers and of fathers is associated with symptoms of schizophrenia even when controlling for potential predictors. © Georg Thieme Verlag KG Stuttgart · New York.

Oracle or Obstacle?

DEFF Research Database (Denmark)

Vaarst Andersen, Kristina

Boundary spanning is one way to accumulate diverse knowledge. This paper examines the conditions under which boundary spanning increases the value of project participants contributions to team production. Statistical findings from logit regressions show that the cost-benefit tradeoff of boundary ...

Modelování vybraných ukazatelů o finanční situaci domácností v České republice

Czech Academy of Sciences Publication Activity Database

Řezanková, Hana

2013-01-01

Roč. 21, č. 3 (2013), s. 32-50 ISSN 0572-3043 R&D Projects: GA ČR GAP202/10/0262 Keywords : Czech households * financial indicator * household classification * classification tree * binary logistic regression * multinomial logistic regression * F-measure Subject RIV: BB - Applied Statistics, Operational Research

Predictive features of CT for risk stratifications in patients with primary gastrointestinal stromal tumour

International Nuclear Information System (INIS)

Zhou, Cuiping; Zhang, Xiang; Duan, Xiaohui; Hu, Huijun; Wang, Dongye; Shen, Jun

2016-01-01

To determine the predictive CT imaging features for risk stratifications in patients with primary gastrointestinal stromal tumours (GISTs). One hundred and twenty-nine patients with histologically confirmed primary GISTs (diameter >2 cm) were enrolled. CT imaging features were reviewed. Tumour risk stratifications were determined according to the 2008 NIH criteria where GISTs were classified into four categories according to the tumour size, location, mitosis count, and tumour rupture. The association between risk stratifications and CT features was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. CT imaging features including tumour margin, size, shape, tumour growth pattern, direct organ invasion, necrosis, enlarged vessels feeding or draining the mass (EVFDM), lymphadenopathy, and contrast enhancement pattern were associated with the risk stratifications, as determined by univariate analysis (P < 0.05). Only lesion size, growth pattern and EVFDM remained independent risk factors in multinomial logistic regression analysis (OR = 3.480-100.384). ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.806 (95 % CI: 0.727-0.885). CT features including lesion size, tumour growth pattern, and EVFDM were predictors of the risk stratifications for GIST. (orig.)

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

Science.gov (United States)

Warton, David I; Hui, Francis K C

2011-01-01

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

Push or Pull: Changes in the Relative Risk and Growth of Entrepreneurship Among Older Households.

Science.gov (United States)

Weller, Christian E; Wenger, Jeffrey B; Lichtenstein, Benyamin; Arcand, Carolyn

2018-03-19

Amid insufficient retirement savings and the growing need to work longer, it is important to understand why self-employment, especially entrepreneurship, has grown among older households. Older households may have been pushed into entrepreneurship by the growing risks of wage-and-salary employment as wages and jobs have become less stable. Alternatively, older households may have been pulled into entrepreneurship as the associated risks have declined, for instance, due to greater opportunities to diversify income away from risky business income. We examine the economic causes of the rise in entrepreneurship among older households. We use summary statistics and multinomial logit regressions to analyze the link between economic pressures in wage-and-salary employment, financial strength of entrepreneurship, and the presence and change of entrepreneurship among older households-aged 50 years or older. We use household data from the Federal Reserve's Survey of Consumer Finances from 1989 to 2013. We find little support for the claim that increased economic pressures are correlated with rising entrepreneurship. Instead, our results suggest that the growth of older entrepreneurship is coincident with increasing access to dividend and interest income. We also find some evidence that access to Social Security and other annuity benefits increases the likelihood of self-employment. Implications: Entrepreneurship among older households increasingly correlates with income diversification. Policymakers interested in encouraging more entrepreneurship among older households could consider increased access to income diversification through social insurance.

Citizen participation in patient prioritization policy decisions: an empirical and experimental study on patients' characteristics.

Science.gov (United States)

Diederich, Adele; Swait, Joffre; Wirsik, Norman

2012-01-01

Health systems worldwide are grappling with the need to control costs to maintain system viability. With the combination of worsening economic conditions, an aging population and reductions in tax revenues, the pressures to make structural changes are expected to continue growing. Common cost control mechanisms, e.g. curtailment of patient access and treatment prioritization, are likely to be adversely viewed by citizens. It seems therefore wise to include them in the decision making processes that lead up to policy changes. In the context of a multilevel iterative mixed-method design a quantitative survey representative of the German population (N = 2031) was conducted to probe the acceptance of priority setting in medicine and to explore the practicability of direct public involvement. Here we focus on preferences for patients' characteristics (medical aspects, lifestyle and socio-economic status) as possible criteria for prioritizing medical services. A questionnaire with closed response options was fielded to gain insight into attitudes toward broad prioritization criteria of patient groups. Furthermore, a discrete choice experiment was used as a rigorous approach to investigate citizens' preferences toward specific criteria level in context of other criteria. Both the questionnaire and the discrete choice experiment were performed with the same sample. The citizens' own health and social situation are included as explanatory variables. Data were evaluated using corresponding analysis, contingency analysis, logistic regression and a multinomial exploded logit model. The results show that some medical criteria are highly accepted for prioritizing patients whereas socio-economic criteria are rejected.

Levels and patterns of physical activity and sedentary time among superdiverse adolescents in East London: a cross-sectional study.

Science.gov (United States)

Curry, Whitney B; Dagkas, Symeon; Wilson, Marcia

2017-06-01

Little is known about the physical activity (PA) and sedentary time (ST) habits of adolescents from superdiverse communities in the UK. The objectives of this study are to examine and report the patterns of PA/ST among adolescents in East London living in superdiverse communities, to identify opportunities/barriers to PA and inform policy/practice. A total of 1260 young people (aged 11-13 years) from seven secondary schools in East London completed a questionnaire on PA/ST over the past seven days as part of the Newham's Every Child a Sports Person (NECaSP) intervention. Socio-demographic and anthropometric data were obtained. Significance tests were conducted to determine differences between socio-demographic and anthropometric predictors and PA/ST. Multinomial logit regression was used to explore the effects of ethnicity, sex, and body mass index (BMI) on PA levels. Males were significantly more likely to engage in PA at least five times during school in the past week (U = 5.07, z = -11.76, p times in the past week (U = 4.11, z =-1.17, p times after school in the last week than boys (b = .11, Wald X 2 (1) = 9.81, p current work presented and provide substantial evidence of the ways young people from minority ethnic groups process and act on the public health policy and the ways they understand and enact PA.

Social Entrepreneurship and Performance: The Role of Perceived Barriers and Risk

NARCIS (Netherlands)

B. Hoogendoorn (Brigitte); P.W. van der Zwan (Peter); A.R. Thurik (Roy)

2011-01-01

textabstractThis study investigates if and in what way social entrepreneurs are hampered in turning their efforts into sustainable organizations. Using binary logit regressions and unique data containing approximately 26,000 individual-level data points for 36 countries, this study assesses the

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.

Very short-term probabilistic forecasting of wind power with generalized logit-Normal distributions

DEFF Research Database (Denmark)

Pinson, Pierre

2012-01-01

and probability masses at the bounds. Both auto-regressive and conditional parametric auto-regressive models are considered for the dynamics of their location and scale parameters. Estimation is performed in a recursive least squares framework with exponential forgetting. The superiority of this proposal over......Very-short-term probabilistic forecasts, which are essential for an optimal management of wind generation, ought to account for the non-linear and double-bounded nature of that stochastic process. They take here the form of discrete–continuous mixtures of generalized logit–normal distributions...

Regression analysis with categorized regression calibrated exposure: some interesting findings

Directory of Open Access Journals (Sweden)

Hjartåker Anette

2006-07-01

Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

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.

Use of two-part regression calibration model to correct for measurement error in episodically consumed foods in a single-replicate study design: EPIC case study.

Science.gov (United States)

Agogo, George O; van der Voet, Hilko; van't Veer, Pieter; Ferrari, Pietro; Leenders, Max; Muller, David C; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A; Boshuizen, Hendriek

2014-01-01

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Assessing farmer involvement in collective action for enhancing the ...

African Journals Online (AJOL)

Assessing farmer involvement in collective action for enhancing the sorghum value chain in Soroti, Uganda. ... in six sub-counties of Soroti, Uganda, where associations are established. A binomial logit regression model was employed to ascertain socio-economic factors that influenced membership to farmer associations.

Association of Rotating Night Shift Work with BMI and Abdominal Obesity among Nurses and Midwives.

Science.gov (United States)

Peplonska, Beata; Bukowska, Agnieszka; Sobala, Wojciech

2015-01-01

Mounting epidemiological evidence suggests that night shift work may contribute to the etiology of increased body weight. The present study aimed to examine association between rotating night shift work and body mass index (BMI), and abdominal adiposity respectively among nurses and midwives. A cross-sectional study was conducted among 724 female nurses and midwives, aged 40-60 years (354 rotating night shift and 370 daytime workers) in Łódź, Poland, between 2008 and 2011. Information about occupational history and potential confounders was collected during personal interviews. Anthropometric measurements of body weight, height, waist (WC) and hip (HC) circumference were made, and body mass index (BMI), waist to hip ratio (WHR) and waist to height ratio (WHtR) were calculated. GLM regression models and multinomial logit regression models were fitted to explore the association between night shift work and anthropometric parameters, with adjustment for age, body silhouette at age 20, current smoking status, packyears, marital status, and menopausal hormone therapy use. Cumulative night shift work showed significant associations with BMI, WC, HC and WHtR, with BMI increasing by 0.477 kg/m2 per 1000 night duties and by 0.432 kg/m2 per 10000 night shift hours, WC increasing respectively by 1.089 cm and 0.99 cm, and HC by 0.72 cm and WHtR by 0.007 cm for both metrics. Both current and cumulative night work was associated with obesity (BMI≥30kg/m2), with OR=3.9 (95%CI:1.5-9.9), in women reporting eight or more night shifts per month. The results of the study support the previously reported relations between night shift work and development of obesity.

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.

Effect of dietary fatty acid intake on prospective weight change in the Heidelberg cohort of the European Prospective Investigation into Cancer and Nutrition

DEFF Research Database (Denmark)

Nimptsch, Katharina; Berg-Beckhoff, Gabi; Linseisen, Jakob

2010-01-01

OBJECTIVE: To evaluate the association between fatty acid (alpha-linolenic acid (ALA), EPA, DHA, palmitic, stearic, oleic, linoleic and arachidonic acids) intake and prospective weight change in the Heidelberg cohort of the European Prospective Investigation into Cancer and Nutrition. DESIGN....... RESULTS: Stearic acid intake was linearly associated with weight gain (P acid intake, significantly so in women. In multinomial models, women in the highest tertile of ALA and stearic acid intake showed increased OR (95 % CI......) and categorised into four groups (weight loss, or =2.5 to or =7.5%/5 years). Energy-adjusted dietary fatty acid intake data were estimated from the FFQ completed at baseline. Multivariate linear regression models as well as multinomial logistic regression analyses (carbohydrate replacement models) were conducted...

Time-adaptive quantile regression

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

2008-01-01

and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

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.

Treatment preferences of originator versus biosimilar drugs in Crohn's disease; discrete choice experiment among gastroenterologists.

Science.gov (United States)

Baji, Petra; Gulácsi, László; Lovász, Barbara D; Golovics, Petra A; Brodszky, Valentin; Péntek, Márta; Rencz, Fanni; Lakatos, Péter L

2016-01-01

To explore preferences of gastroenterologists for biosimilar drugs in Crohn's disease. Discrete choice experiment was carried out involving 51 Hungarian gastroenterologists in May 2014. The following attributes were used to describe hypothetical choice sets: 1) type of the treatment (biosimilar/originator), 2) severity of disease, 3) availability of continuous medicine supply, 4) frequency of the efficacy check-ups. Multinomial logit model was used to differentiate between three attitude types: 1) always opting for the originator, 2) willing to consider biosimilar for biological-naïve patients only, 3) willing to consider biosimilar treatment for both types of patients. Conditional logit model was used to estimate the probabilities of choosing a given profile. Men, senior consultants, working in inflammatory bowel disease center and treating more patients were more likely willing to consider biosimilar for biological-naïve patients only. Treatment type (originator/biosimilar) was the most important determinant of choice for patients already treated with biologicals, and the availability of continuous medicine supply in case of biological-naïve patients. The probabilities of choosing the biosimilar with all the benefits offered over the originator under current reimbursement conditions are 89% versus 11% for new patients, and 44% versus 56% for patients already treated with biological. For gastroenterologist, the continuous medical supply would be one of the major benefits of biosimilars. However, benefits offered in the scenarios do not compensate for the change from the originator to the biosimilar treatment of patients already treated with biologicals.

Short-term poverty dynamics of rural households: Evidence from Central Sulawesi, Indonesia

Directory of Open Access Journals (Sweden)

Stefan Schwarze

2011-12-01

Full Text Available The understanding of poverty dynamics is crucial for the design of appropriate poverty reduction strategies. Taking the case of Central Sulawesi, we investigate the determinants of both chronic and transitory poverty using data from 264 randomly selected households interviewed in 2005 and 2007. Regarding the US 1$/day poverty line, the headcount index declined from 19.3% in 2005 to 18.2% in 2007. However, we observed an increasing number of people living on less than US 2$/day expressed in purchasing power parity (PPP. The results of the estimated multinomial logit model applied in this study indicate that a lack of non-agricultural employment opportunities and low endowment of social capital are major determinants of chronic as well as transitory poverty in this province of Indonesia. These results are used to draw policy conclusions with respect to the alleviation of transitory and chronic poverty in Central Sulawesi.

Fidelización y rentabilización de usuarios de seguros todo riesgo de vehículos por medio de la venta cruzada y la venta escalonada. Un enfoque promocional para la industria aseguradora

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Carlos Gabriel Contreras Serrano

2016-02-01

Full Text Available Mantener relaciones activas con clientes rentables es uno de los principales objetivos de la industria aseguradora en Colombia. Para esto y para generar campañas de retención, se han desarrollado modelos tácticos de segmentación que tienen en cuenta la probabilidad de fuga del cliente y el valor vitalicio del mismo. Esta investigación propone un diseño de análisis conjunto con 560 tomadores de pólizas de seguros de autos en diversas latitudes del país. Se examinan los esquemas promocionales que aceleran la probabilidad de renovar la póliza de seguro que tienen con su agencia aseguradora actual. La aplicación de un modelo logit multinomial ofrece evidencia de que las promociones bajo venta cruzada son eficientes para fidelizar usuarios rentables, mientras la venta escalonada es propicia para rentabilizar clientes fieles.

Should We Leave? Attitudes towards Relocation in Response to Sea Level Rise

Directory of Open Access Journals (Sweden)

Jie Song

2017-12-01

Full Text Available The participation of individuals contributes significantly to the success of sea level rise adaptation. This study therefore addresses what influences people’s likelihood of relocating away from low-lying areas in response to rising sea levels. The analysis was based on a survey conducted in the City of Panama Beach in Florida (USA. Survey items relate to people’s risk perception, hazard experience, threat appraisal, and coping appraisal, whose theoretical background is Protection Motivation Theory. Descriptive and correlation analysis was first performed to highlight critical factors which were then examined by a multinomial Logit model. Results show that sea level rise awareness is the major explanatory variable. Coping appraisal is qualitatively viewed as a strong predictor for action, while threat appraisal is statistically significant in driving relocation intention. These factors should be integrated in current risk communication regarding sea level rise.

Human capital accumulation and its effect on agribusiness performance: the case of China.

Science.gov (United States)

Udimal, Thomas Bilaliib; Jincai, Zhuang; Ayamba, Emmanuel Caesar; Sarpong, Patrick Boateng

2017-09-01

This study investigates the effect of accumulated human capital on the performance of agribusinesses in China. Four hundred fifty agribusiness owners were interviewed for the study. Growth in sales over the last 5 years was used as a measure of performance. The following variables were reviewed and captured as those constituting human capital: education, raised in the area, parents being entrepreneurs, attending business seminars/trade fairs, managerial experience, similar work experience, cooperative membership, and training. Logit regression model and inferential statistics were used to analyze the data. The logit regression model was used to analyze the effect of accumulated human capital on growth in sales. The inferential statistics on the other hand was used to measure the association between age, education, sex, provinces, and the categories of growth. Our study found that parents who are entrepreneurs and attend business seminars/trade fairs, as well as have managerial experience, similar work experience, education, and training, display a statistically significant positive effect on the growth in sales.

Regression analysis by example

CERN Document Server

Chatterjee, Samprit

2012-01-01

Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

Applied logistic regression

CERN Document Server

Hosmer, David W; Sturdivant, Rodney X

2013-01-01

 A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

Science.gov (United States)

Bulcock, J. W.

The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

Vector regression introduced

Directory of Open Access Journals (Sweden)

Mok Tik

2014-06-01

Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

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

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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.

Applied linear regression

CERN Document Server

Weisberg, Sanford

2013-01-01

Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

Determinants of Anabolic-Androgenic Steroid Risk Perceptions in Youth Populations: A Multivariate Analysis

Science.gov (United States)

Denham, Bryan E.

2009-01-01

Grounded conceptually in social cognitive theory, this research examines how personal, behavioral, and environmental factors are associated with risk perceptions of anabolic-androgenic steroids. Ordinal logistic regression and logit log-linear models applied to data gathered from high-school seniors (N = 2,160) in the 2005 Monitoring the Future…

Farmers' Willingness to Pay for Private Irrigation Supply in Nandom ...

African Journals Online (AJOL)

This study investigated farmers willingness to pay (WTP) for private irrigation in Nandom district, Ghana. The study randomly sampled 236 farmers and analyzed data using descriptive statistics and ordered logit regression model. Results revealed that 94.5 percent of the farmers were WTP for private irrigation services with ...

Factors affecting the choice of cropping systems in Kebbi State ...

African Journals Online (AJOL)

The study examined the factors that influence choice of cropping systems in Kebbi State Nigeria. The technique applied in the study was Logit regression. Data to conduct the research was obtained mainly from primary sources through a questionnaire survey of 256 farmers, comprising 98 monocroppers and 158 ...

Understanding poisson regression.

Science.gov (United States)

Hayat, Matthew J; Higgins, Melinda

2014-04-01

Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

Integration of logistic regression and multicriteria land evaluation to simulation establishment of sustainable paddy field zone in Indramayu Regency, West Java Province, Indonesia

Science.gov (United States)

Nahib, Irmadi; Suryanta, Jaka; Niedyawati; Kardono, Priyadi; Turmudi; Lestari, Sri; Windiastuti, Rizka

2018-05-01

Ministry of Agriculture have targeted production of 1.718 million tons of dry grain harvest during period of 2016-2021 to achieve food self-sufficiency, through optimization of special commodities including paddy, soybean and corn. This research was conducted to develop a sustainable paddy field zone delineation model using logistic regression and multicriteria land evaluation in Indramayu Regency. A model was built on the characteristics of local function conversion by considering the concept of sustainable development. Spatial data overlay was constructed using available data, and then this model was built upon the occurrence of paddy field between 1998 and 2015. Equation for the model of paddy field changes obtained was: logit (paddy field conversion) = - 2.3048 + 0.0032*X1 – 0.0027*X2 + 0.0081*X3 + 0.0025*X4 + 0.0026*X5 + 0.0128*X6 – 0.0093*X7 + 0.0032*X8 + 0.0071*X9 – 0.0046*X10 where X1 to X10 were variables that determine the occurrence of changes in paddy fields, with a result value of Relative Operating Characteristics (ROC) of 0.8262. The weakest variable in influencing the change of paddy field function was X7 (paddy field price), while the most influential factor was X1 (distance from river). Result of the logistic regression was used as a weight for multicriteria land evaluation, which recommended three scenarios of paddy fields protection policy: standard, protective, and permissive. The result of this modelling, the priority paddy fields for protected scenario were obtained, as well as the buffer zones for the surrounding paddy fields.

Alternative Methods of Regression

CERN Document Server

Birkes, David

2011-01-01

Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

Introduction to regression graphics

CERN Document Server

Cook, R Dennis

2009-01-01

Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

STRUCTURAL ANALYSIS OF MERGERS AND ACQUISITIONS IN THE FOOD INDUSTRY

OpenAIRE

Adams, Wendi L.; Love, H. Alan; Capps, Oral, Jr.

1997-01-01

Determinants of merger and acquisition activity in the food industry are analyzed using logit regression analysis. Factors affecting the food processing, food retailing and food service sectors are considered. Results indicate merger and acquisition activity in all three sectors are significantly influenced by antitrust activity, profitability and real gross domestic product.

Small scale banana farmers' awareness level and adoption of ...

African Journals Online (AJOL)

Descriptive statistics and binary logit regression were employed for data analyses. The results show that although majority of the farmers (96.67%) were aware of and had access to improved banana varieties, only 15.83% of them adopted the use of improved planting materials. Gros mitchel, Cavendish and sweet bananas ...

Associating crash avoidance maneuvers with driver attributes and accident characteristics: a mixed logit model approach.

Science.gov (United States)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that represents the selection among 5 emergency lateral and speed control maneuvers (i.e., "no avoidance maneuvers," "braking," "steering," "braking and steering," and "other maneuvers) while accommodating correlations across maneuvers and heteroscedasticity. Data for the analysis were retrieved from the General Estimates System (GES) crash database for the year 2009 by considering drivers for which crash avoidance maneuvers are known. The results show that (1) the nature of the critical event that made the crash imminent greatly influences the choice of crash avoidance maneuvers, (2) women and elderly have a relatively lower propensity to conduct crash avoidance maneuvers, (3) drowsiness and fatigue have a greater negative marginal effect on the tendency to engage in crash avoidance maneuvers than alcohol and drug consumption, (4) difficult road conditions increase the propensity to perform crash avoidance maneuvers, and (5) visual obstruction and artificial illumination decrease the probability to carry out crash avoidance maneuvers. The results emphasize the need for public awareness campaigns to promote safe driving style for senior drivers and warning about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing

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.

Citizen participation in patient prioritization policy decisions: an empirical and experimental study on patients' characteristics.

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Adele Diederich

Full Text Available Health systems worldwide are grappling with the need to control costs to maintain system viability. With the combination of worsening economic conditions, an aging population and reductions in tax revenues, the pressures to make structural changes are expected to continue growing. Common cost control mechanisms, e.g. curtailment of patient access and treatment prioritization, are likely to be adversely viewed by citizens. It seems therefore wise to include them in the decision making processes that lead up to policy changes. In the context of a multilevel iterative mixed-method design a quantitative survey representative of the German population (N = 2031 was conducted to probe the acceptance of priority setting in medicine and to explore the practicability of direct public involvement. Here we focus on preferences for patients' characteristics (medical aspects, lifestyle and socio-economic status as possible criteria for prioritizing medical services. A questionnaire with closed response options was fielded to gain insight into attitudes toward broad prioritization criteria of patient groups. Furthermore, a discrete choice experiment was used as a rigorous approach to investigate citizens' preferences toward specific criteria level in context of other criteria. Both the questionnaire and the discrete choice experiment were performed with the same sample. The citizens' own health and social situation are included as explanatory variables. Data were evaluated using corresponding analysis, contingency analysis, logistic regression and a multinomial exploded logit model. The results show that some medical criteria are highly accepted for prioritizing patients whereas socio-economic criteria are rejected.

Choosing a Doctor: Does Presentation Format Affect the Way Consumers Use Health Care Performance Information?

Science.gov (United States)

Kenny, Patricia; Goodall, Stephen; Street, Deborah J; Greene, Jessica

2017-12-01

Choosing a new health service provider can be difficult and is dependent on the type and clarity of the information available. This study examines if the presentation of service quality information affects the decisions of consumers choosing a general medical practice. The aim was to examine the impact of presentation format on attribute level interpretation and relative importance. A discrete choice experiment eliciting preferences for a general medical practice was conducted using four different presentation formats for service quality attributes: (1) frequency and percentage with an icon array, (2) star ratings, (3) star ratings with a text benchmark, and (4) percentage alone. A total of 1208 respondents from an online panel were randomised to see two formats, answering nine choices for each, where one was a dominated choice. Logistic regression was used to assess the impact of presentation format on the probability of choosing a dominated alternative. A generalised multinomial logit model was used to estimate the relative importance of the attribute levels. The probability of incorrectly choosing a dominated alternative was significantly higher when the quality information was presented as a percentage relative to a frequency with icon array, star rating or bench-marked star rating. Preferences for a practice did not differ significantly by presentation format, nor did the probability of finding the information difficult to understand. Quantitative health service quality information will be more useful to consumers if presented by combining the numerical information with a graphic, or using a star rating if appropriate for the context.

Sequencing the real time of the elderly: Evidence from South Africa

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Erofili Grapsa

2016-09-01

Full Text Available Background: Understanding how the elderly in developing countries spend their time has received little attention. Moreover, the potential of time use data to discern variation in activity patterns has not been fully realized by methods which use a mean added time approach. Objective: To uncover patterns of time use among the elderly (60 years and older in South Africa by applying an innovative methodology that incorporates the timing, duration, and frequency of activities in the analysis. Methods: We use sequence analysis, which treats the daily series of activities of each individual as a sequence, and cluster analysis, to group these sequences into common clusters of time use behaviour. We then estimate multinomial logit regressions to identify the characteristics of the elderly which predict cluster membership. Results: We find that the time use behaviour of the elderly in South Africa can be divided into five distinct clusters, according to the relative importance in their day of personal care, household maintenance, work, mass media, and social or cultural activities. In comparison to men, women are overrepresented in the cluster where household work dominates, while they are underrepresented in the cluster of the elderly who engage in production work. A range of other individual and household characteristics are also important in predicting cluster membership. Contribution: Sequence and cluster analysis permit a nuanced examination of the differences and commonalities in time use patterns among the elderly in South Africa. There is considerable potential to extend these methods to other studies of time use behaviour.

Cohabitation among secular Jews in Israel: How ethnicity, education, and employment characteristics are related to young adults' living arrangements

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Avital Manor

2016-09-01

Full Text Available Background: Economic and ideational theories offer various explanations for the roles of ethnicity, education, and employment characteristics in determining cohabitation behavior in various contexts. Objective: We focus on young, native-born secular Jewish adults in Israel, a subpopulation that has been shown to display Second Demographic Transition behaviors. Within this group we investigate whether a person's ethnicity, education, and employment characteristics are associated with their current living arrangements. Methods: We employ multinomial logit regression on a series of five annual data files from the Israeli Social Survey (ISS, 2005-2009. We consider the association between various explanatory variables and the odds of cohabitation vs. being married as well as the odds of cohabitation vs. being unpartnered. Results: Higher odds of cohabiting vs. being married are significantly associated with (1 tertiary education and student status, among men and women; (2 having accumulated fewer than five years of work experience, among men; (3 working full-time, among women; and (4 European-American ethnicity and being third-generation Israeli, among women. Higher odds of cohabiting vs. being unpartnered are significantly associated with (1 tertiary education and student status, among men; and (2 working full-time, among men. Conclusions: We suggest that in Israel a multicausal model that accounts for both economic and ideational factors is appropriate. While limited work experience among men encourages cohabitation as an alternative to marriage, as suggested by some economic theories, associations between cohabitation and educational characteristics (among men and women as well as ethnicity (among women are more consistent with ideational theories.

Optimising import phytosanitary inspection

NARCIS (Netherlands)

Surkov, I.

2007-01-01

Keywords: quarantine pest, plant health policy, optimization, import phytosanitary inspection, ‘reduced checks’, optimal allocation of resources, multinomial logistic regression, the Netherlands World trade is a major vector of spread of quarantine plant pests. Border phytosanitary inspection

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

Science.gov (United States)

Agnew, Steve

2011-01-01

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

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.

Customization in prescribing for bipolar disorder.

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Hodgkin, Dominic; Volpe-Vartanian, Joanna; Merrick, Elizabeth L; Horgan, Constance M; Nierenberg, Andrew A; Frank, Richard G; Lee, Sue

2012-06-01

For many disorders, patient heterogeneity requires physicians to customize their treatment to each patient's needs. We test for the existence of customization in physicians' prescribing for bipolar disorder, using data from a naturalistic clinical effectiveness trial of bipolar disorder treatment (STEP-BD), which did not constrain physician prescribing. Multinomial logit is used to model the physician's choice among five combinations of drug classes. We find that our observed measure of the patient's clinical status played only a limited role in the choice among drug class combinations, even for conditions such as mania that are expected to affect class choice. However, treatment of a patient with given characteristics differed widely depending on which physician was seen. The explanatory power of the model was low. There was variation within each physician's prescribing, but the results do not suggest a high degree of customization in physicians' prescribing, based on our measure of clinical status. Copyright © 2011 John Wiley & Sons, Ltd.

Making difficult decisions: the role of quality of care in choosing a nursing home.

Science.gov (United States)

Pesis-Katz, Irena; Phelps, Charles E; Temkin-Greener, Helena; Spector, William D; Veazie, Peter; Mukamel, Dana B

2013-05-01

We investigated how quality of care affects choosing a nursing home. We examined nursing home choice in California, Ohio, New York, and Texas in 2001, a period before the federal Nursing Home Compare report card was published. Thus, consumers were less able to observe clinical quality or clinical quality was masked. We modeled nursing home choice by estimating a conditional multinomial logit model. In all states, consumers were more likely to choose nursing homes of high hotel services quality but not clinical care quality. Nursing home choice was also significantly associated with shorter distance from prior residence, not-for-profit status, and larger facility size. In the absence of quality report cards, consumers choose a nursing home on the basis of the quality dimensions that are easy for them to observe, evaluate, and apply to their situation. Future research should focus on identifying the quality information that offers the most value added to consumers.

Modeling the Perceptions and Preferences of Pedestrians on Crossing Facilities

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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.

Social influence, agent heterogeneity and the emergence of the urban informal sector

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García-Díaz, César; Moreno-Monroy, Ana I.

2012-02-01

We develop an agent-based computational model in which the urban informal sector acts as a buffer where rural migrants can earn some income while queuing for higher paying modern-sector jobs. In the model, the informal sector emerges as a result of rural-urban migration decisions of heterogeneous agents subject to social influence in the form of neighboring effects of varying strengths. Besides using a multinomial logit choice model that allows for agent idiosyncrasy, explicit agent heterogeneity is introduced in the form of socio-demographic characteristics preferred by modern-sector employers. We find that different combinations of the strength of social influence and the socio-economic composition of the workforce lead to very different urbanization and urban informal sector shares. In particular, moderate levels of social influence and a large proportion of rural inhabitants with preferred socio-demographic characteristics are conducive to a higher urbanization rate and a larger informal sector.

Assessing Tourists’ Preferences for Recreational Trips in National and Natural Parks as a Premise for Long-Term Sustainable Management Plans

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Diana E. Dumitras

2017-09-01

Full Text Available Sustainable tourism management plans rely on relevant and consistent information about factors that can influence the decision to visit a protected area. This paper uses the choice experiment method to investigate tourists’ preferences with regard to recreational trip characteristics in national and natural parks in Romania. An on-site survey questionnaire was administered to visitors. The multinomial logit model was employed to investigate the preference orderings of the identified groups of recreational users. Overall, results indicate that tourists gain benefits after visiting the parks. Main preference differences were found for information sources and location of campsites. Visitors who stated that the park was the main trip destination were willing to have access to more information sources, the marks on trails being insufficient. Camping is preferred only in organized places, expressing the concern for environmental protection. The results of this study have management implications, highlighting the importance of assessing tourists’ preferences as a foundation for developing sustainable tourism strategies.

Price elasticity and pharmaceutical selection: the influence of managed care.

Science.gov (United States)

Domino, Marisa Elena; Salkever, David S

2003-07-01

State Medicaid programs are turning increasingly to managed care to control expenditures, although the types of managed care programs in use have changed dramatically. Little is known about the influence of the shifting Medicaid managed care arena on treatment decisions. This paper investigates factors affecting the selection of treatments for depression by providers participating in either of two Medicaid managed care programs. Of particular interest is the influence of medication price on the choice of treatment, since one vehicle through which managed care organizations can reduce total expenditures is by increasing the price sensitivity of participating providers. We take a new approach by phrasing the problem as a discrete choice, using a nested multinomial logit model for the analyses. Contrary to earlier literature, we find some evidence that physicians in both programs do take price into consideration when selecting among treatment options. HMO providers in particular demonstrate increased price sensitivity in the two most commonly prescribed categories of antidepressants. Copyright 2002 John Wiley & Sons, Ltd.

Health Care Workers’ Risk Perceptions and Willingness to Report for Work during an Influenza Pandemic

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Georges Dionne

2018-02-01

Full Text Available The ability and willingness of health care workers to report for work during a pandemic are essential to pandemic response. The main contribution of this article is to examine the relationship between risk perception of personal and work activities and willingness to report for work during an influenza pandemic. Data were collected through a quantitative Web-based survey sent to health care workers on the island of Montreal. Respondents were asked about their perception of various risks to obtain index measures of risk perception. A multinomial logit model was applied for the probability estimations, and a factor analysis was conducted to compute risk perception indexes (scores. Risk perception associated with personal and work activities is a significant predictor of intended presence at work during an influenza pandemic. This means that correcting perceptual biases should be a public policy concern. These results have not been previously reported in the literature. Many organizational variables are also significant.

Differential Role of Self-Congruity in the Consideration and Choice of a Store

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André Carlos Martins Menck

2014-03-01

Full Text Available The variable measuring the matching/mismatching between a shopper's self-image and the image he/she has of the personality of a store—self-congruity—has deserved attention in the literature, but limited to single-phased decision models. This research extends the investigation to a two-phased decision model, and finds support for the idea that self-congruity has an explanatory role on store consideration probability. Also, no statistical evidence was found that it helps explaining choice probability among stores in the consideration set. The results were obtained by binary and multinomial logit models, permitting the assessment of the relative explanatory importance of the variable, in relation to other variables whose importance in explaining behavior have long been established. A discussion on the differential effects of the shopping situation on the role played by the explanatory variables on considering and choice probabilities was also done and empirical support was found for shopping situation-dependency.

Determinants of edible oil choice by households in Tamil Nadu, India.

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Govindaraj, Gurrappa Naidu; Suryaprakash, Satrasala

2013-01-01

This study investigated the major determinants that influence the choice of edible oils by households across geographical zones in Tamil Nadu state, India. The primary data from 1,000 sample households were collected using a structured pre-tested questionnaire. Multinomial logit model was fitted for determining the factors. The results revealed that education, income, and households with a history of health problems were the important determinants that influenced the choice of low-saturated-fat oils, whereas the larger size households and weaker section households preferred low-priced palm oil. Income and education levels in Tamil Nadu state surged ahead in recent years. In consonance to these changes the nontraditional low-saturated fat containing sunflower oil demand will increase in many folds in coming years. Hence, besides traditional oils, sunflower oil production has to be stepped up on "mission mode" through appropriate production programs to meet the present and future edible oil demand domestically.

Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

International Nuclear Information System (INIS)

Jafri, Y.Z.; Kamal, L.

2007-01-01

Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

Linear regression in astronomy. I

Science.gov (United States)

Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

1990-01-01

Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

Logic regression and its extensions.

Science.gov (United States)

Schwender, Holger; Ruczinski, Ingo

2010-01-01

Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

Tumor regression patterns in retinoblastoma

International Nuclear Information System (INIS)

Zafar, S.N.; Siddique, S.N.; Zaheer, N.

2016-01-01

To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

Combining Alphas via Bounded Regression

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Zura Kakushadze

2015-11-01

Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.

riskRegression

DEFF Research Database (Denmark)

Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

2017-01-01

In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....

Regression in autistic spectrum disorders.

Science.gov (United States)

Stefanatos, Gerry A

2008-12-01

A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

Understanding logistic regression analysis

OpenAIRE

Sperandei, Sandro

2014-01-01

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

Gender, Alcohol Consumption Patterns, and Engagement in Sexually Intimate Behaviors among Adolescents and Young Adults in Nha Trang, Viet Nam

Science.gov (United States)

Kaljee, Linda M.; Green, Mackenzie S.; Zhan, Min; Riel, Rosemary; Lerdboon, Porntip; Lostutter, Ty W.; Tho, Le Huu; Luong, Vo Van; Minh, Truong Tan

2011-01-01

A randomly selected cross-sectional survey was conducted with 880 youth (16 to 24 years) in Nha Trang City to assess relationships between alcohol consumption and sexual behaviors. A timeline followback method was employed. Chi-square, generalized logit modeling and logistic regression analyses were performed. Of the sample, 78.2% male and 56.1%…

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.

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.

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

Science.gov (United States)

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.

Values for the ICECAP-Supportive Care Measure (ICECAP-SCM) for use in economic evaluation at end of life.

Science.gov (United States)

Huynh, Elisabeth; Coast, Joanna; Rose, John; Kinghorn, Philip; Flynn, Terry

2017-09-01

End of life care may have elements of value that go beyond health. A generic measure of the benefits of end of life care could be helpful to decision makers. Such a measure, based on the capability approach, has recently been developed: the ICECAP Supportive Care Measure. This paper reports the first valuation exercise for that measure, with data from 6020 individuals collected from an on-line general population panel during June 2013. Individuals were asked to complete a stated choice experiment that combined best-worst scaling and a standard discrete choice experiment. Analysis of the best-worst data used limited dependent variable models within the random utility framework including the multinomial logit models and latent class choice model analysis. Exploratory steps were taken to determine the similarity of the best-worst and DCE data before formal testing and pooling of the two data sources. Combined data were analysed in a heteroscedastic conditional logit model adjusting for continuous scale. Two sets of tariffs were generated, one from the best-worst data capturing only main effects, and a second from the pooled data allowing for two-way interactions. Either tariff could be used in economic evaluation of interventions at the end of life, although there are advantages and disadvantages with each. This extensive valuation exercise for the ICECAP Supportive Care Measure, with a large number of members of the general public, could be complemented in the future with best-worst scaling studies amongst those experiencing the end of life. Copyright © 2017 Elsevier Ltd. All rights reserved.

Age norms, family relationships, and home leaving in Italy

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Marco Tosi

2017-01-01

Full Text Available Background: Previous research has shown that social norms have an influence on young adults' life course transitions. However, few studies have explicitly and directly tested the idea that perceived age norms affect the decision to leave the parental home. Objective: I ask whether normative factors are correlated with the decision to leave the family nest in Italy, and whether this association depends on a system of perceived costs and benefits, parental approval of their children's decisions, and the quality of parent-child relationships. Methods: Using the panel component of Family and Social Subjects data (2003 and 2007, logit and multinomial logit models were adopted to analyze the connection between perceived norms and behavior. The Karlson, Holm, and Breen (2012 decomposition method was used to test the relevance of confounding and mediating factors. Results: The findings show that young adults who consider themselves as too young to leave the parental home are less likely to move out of the family nest in order to marry. The interaction between a 'stay' norm, the perceived benefits of leaving home, and parental approval significantly affects the transition to independence. Contribution: In Italy, decision-making about leaving home and getting married is shaped by age norms concerning extended coresidence. Young adults tend to comply with age norms when they perceive that their decision implies benefits and/or a violation will lead to penalties. Perceived parental disapproval reduces the influence of normative factors on individual actual behaviors, which suggests that young adults adhere to norms that are supported by parents.

Linear regression in astronomy. II

Science.gov (United States)

Feigelson, Eric D.; Babu, Gutti J.

1992-01-01

A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

Alcohol Use-Related Problems Among a Rural Indian Population of West Bengal: An Application of the Alcohol Use Disorders Identification Test (AUDIT).

Science.gov (United States)

Barik, Anamitra; Rai, Rajesh Kumar; Chowdhury, Abhijit

2016-03-01

To examine alcohol use and related problems among a rural subset of the Indian population. The Alcohol Use Disorders Identification Test (AUDIT) was used as part of Health and Demographic Surveillance of 36,611 individuals aged ≥18 years. From this survey data on 3671 current alcohol users were analysed using bivariate and multivariate ordered logit regression. Over 19% of males and 2.4% of females were current alcohol users. Mean ethanol consumption on a typical drinking day among males was estimated to be higher (96.3 gm) than females (56.5 gm). Mean AUDIT score was 11 among current alcohol users. AUDIT showed in the ordered logit regression estimated alcohol use-related problems to be low among women, Scheduled Tribes and unmarried people, whereas alcohol use-related problems registered high among Muslims. This rural population appears to be in need of an effective intervention program, perhaps targeting men and the household, aimed at reducing the level of alcohol use and related problems. © The Author 2015. Medical Council on Alcohol and Oxford University Press. All rights reserved.

A Matlab program for stepwise regression

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Yanhong Qi

2016-03-01

Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

Perceived fairness of the division of household labor: A comparative study in 29 countries

NARCIS (Netherlands)

Jansen, L.; Weber, T.; Kraaykamp, G.L.M.; Verbakel, C.M.C.

2016-01-01

This study investigates the relationship between the division of household labor and individuals' perceived fairness concerning this division. We applied multilevel multinomial logistic regression to analyze data on both men and women across 29 countries using the International Social Survey

A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market

DEFF Research Database (Denmark)

Hurn, A.S.; Silvennoinen, Annastiina; Teräsvirta, Timo

We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting of specific......We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting...... of specification, including testing linearity, estimation and evaluation of these models is constructed. Nonlinear least squares estimation of the parameters of the model is discussed. Evaluation by misspecification tests is carried out using tests derived in a companion paper. The use of the modelling strategy...

Quantile regression theory and applications

CERN Document Server

Davino, Cristina; Vistocco, Domenico

2013-01-01

A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

Fungible weights in logistic regression.

Science.gov (United States)

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Part-Time Community-College Faculty and the Desire for Full-Time Tenure-Track Positions: Results of a Single Institution Case Study

Science.gov (United States)

Jacoby, Dan

2005-01-01

According to data derived from a community-college survey in the state of Washington, the majority of part-time faculty prefer full-time work. Using a logit regression analysis, the study reported in this paper suggests that typical part-timers enter their part-time teaching situations with the intent of becoming full-time, but gradually become…

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…

Principal component regression analysis with SPSS.

Science.gov (United States)

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

Social determinants of alcohol use among drivers in Calabar | Bello ...

African Journals Online (AJOL)

A semistructured questionnaire, which included the World Health Organization Alcohol Use Disorders Identification Test, was administered at interview. Binary and multinomial logistic regression analyses were used to identify social determinants of any and hazardous alcohol use. Results: Determinants of any alcohol use ...

Logistic regression models

CERN Document Server

Hilbe, Joseph M

2009-01-01

This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

Logistic regression applied to natural hazards: rare event logistic regression with replications

Science.gov (United States)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Disposición a pagar por reducir el tiempo de viaje en Tunja (Colombia: Comparación entre estudiantes y trabajadores con un modelo Logit mixto

Directory of Open Access Journals (Sweden)

Luis Gabriel Marquez Diaz

2013-01-01

Full Text Available Resumen: El estudio analiza la diferencia en la disposición a pagar de estudiantes y trabajadores por reducir el tiempo de viaje, en un contexto de elección de modo de transporte para la ciudad de Tunja (Colombia. Se utilizó un modelo logit mixto, calibrado con datos provenientes de una encuesta de preferencias declaradas. La especificación del modelo supuso la variación aleatoria de los coeficientes del tiempo de acceso, tiempo de espera y tiempo de viaje. Se encontró que la disposición a pagar por reducir el tiempo de viaje es de 38.14 $/min para estudiantes, siendo 23% mayor para trabajadores de menor ingreso y 73% mayor para los trabajadores de mayor ingreso. Se determinó que el valor del tiempo de espera es 1.95 veces mayor que el tiempo viaje, en tanto que el tiempo de acceso mantiene una relación de 1 a 2.57 con respecto al tiempo de viaje, la cual se considera válida únicamente para el contexto estudiado.

Understanding logistic regression analysis.

Science.gov (United States)

Sperandei, Sandro

2014-01-01

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

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

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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.

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

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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

Minimax Regression Quantiles

DEFF Research Database (Denmark)

Bache, Stefan Holst

A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....

Regression with Sparse Approximations of Data

DEFF Research Database (Denmark)

Noorzad, Pardis; Sturm, Bob L.

2012-01-01

We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

Logistic regression applied to natural hazards: rare event logistic regression with replications

Directory of Open Access Journals (Sweden)

M. Guns

2012-06-01

Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

Science.gov (United States)

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

The role of agri-business incentive on under-five child immunization ...

African Journals Online (AJOL)

A multinomial logistic regression model used to analyze the determinant of partial or noneimmunized. Maternal health practices and access to a motivating intervention are significant factors that ensure a parent/guardian's compliance to their child immunization. The study recommends sustainability and diversification of ...

The Role of Predictor Courses and Teams on Individual Student Success

Science.gov (United States)

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

2014-01-01

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

In-season and out-of-season variation of rotavirus genotype distribution and age of infection across 12 European countries before the introduction of routine vaccination, 2007/08 to 2012/13

DEFF Research Database (Denmark)

Hungerford, Daniel; Vivancos, Roberto; Read, Jonathan M

2016-01-01

distribution and age distribution of rotavirus gastroenteritis (RVGE) cases in and out of peak season in 12 countries which were yet to implement routine rotavirus vaccination. In multinomial multivariate logistic regression, adjusting for year, country and age, the odds of infection caused by genotype...

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

NARCIS (Netherlands)

Lubbers, M.; Jaspers, E.; Ultee, W.C.

2009-01-01

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

Ethnicity at the individual and neighborhood level as an explanation for moving out of the neighborhood

NARCIS (Netherlands)

Schaake, K.; Burgers, J.; Mulder, C.H.

2010-01-01

We address the influence of both the ethnic composition of the neighborhood and the ethnicity of individual residents on moving out of neighborhoods in the Netherlands. Using the Housing Research Netherlands survey and multinomial logistic regression analyses of moving out versus not moving or

Predictors of Early Termination in a University Counseling Training Clinic

Science.gov (United States)

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

2009-01-01

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

Evaluating the Locational Attributes of Education Management Organizations (EMOs)

Science.gov (United States)

Gulosino, Charisse; Miron, Gary

2017-01-01

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

Post-processing through linear regression

Science.gov (United States)

van Schaeybroeck, B.; Vannitsem, S.

2011-03-01

Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

Regression modeling methods, theory, and computation with SAS

CERN Document Server

Panik, Michael

2009-01-01

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,

Better Autologistic Regression

Directory of Open Access Journals (Sweden)

Mark A. Wolters

2017-11-01

Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

Semiparametric regression during 2003–2007

KAUST Repository

Ruppert, David; Wand, M.P.; Carroll, Raymond J.

2009-01-01

Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

Unbalanced Regressions and the Predictive Equation

DEFF Research Database (Denmark)

Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...

A Study Comparing the Pedagogical Effectiveness of Virtual Worlds and of Classical Methods

Science.gov (United States)

2014-08-01

left from Houston, Texas en route to the McAllen Bus Station has stopped on the side of Highway 281 near by Monte Cristo . One of the passengers in...Regression: Explosion_1 versus RSP Assessment Link Function: Logit Response Information Variable Value Count Explosion_1 Yes 30...Variable Value Count Diff Score 1 15 2 12 3 3 4 26 5

Interpretation of commonly used statistical regression models.

Science.gov (United States)

Kasza, Jessica; Wolfe, Rory

2014-01-01

A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Linear regression

CERN Document Server

Olive, David J

2017-01-01

This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

Regression modeling of ground-water flow

Science.gov (United States)

Cooley, R.L.; Naff, R.L.

1985-01-01

Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

Post-processing through linear regression

Directory of Open Access Journals (Sweden)

B. Van Schaeybroeck

2011-03-01

Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.

These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

Gingival crevicular fluid alkaline phosphatase activity in relation to pubertal growth spurt and dental maturation: A multiple regression study

Directory of Open Access Journals (Sweden)

Perinetti, G.

2016-04-01

Full Text Available Introduction: The identification of the onset of the pubertal growth spurt has major clinical implications when dealing with orthodontic treatment in growing subjects. Aim: Through multivariate methods, this study evaluated possible relationships between the gingival crevicular fluid (GCF alkaline phosphatase (ALP activity and pubertal growth spurt and dentition phase. Materials and methods: One hundred healthy growing subjects (62 females, 38 males; mean age, 11.5±2.4 years were enrolled into this doubleblind, prospective, cross-sectional-design study. Phases of skeletal maturation (pre - pubertal, pubertal, post - pubertal was assessed using the cervical vertebral maturation method. Samples of GCF for the ALP activity determination were collected at the mesial and distal sites of the mandibular central incisors. The phases of the dentition were recorded as intermediate mixed, late mixed, or permanent. A multinomial multiple logistic regression model was used to assess relationships of the enzymatic activity to growth phases and dentition phases. Results: The GCF ALP activity was greater in the pubertal growth phase as compared to the pre - pubertal and post - pubertal growth phases. Significant adjusted odds ratios for the GCF ALP activity for the pre - pubertal and post - pubertal subjects, in relation to the pubertal group, were 0.76 and 0.84, respectively. No significant correlations were seen for the dentition phase. Conclusions: The GCF ALP activity is a valid candidate as a non - invasive biomarker for the identification of the pubertal growth spurt irrespective of the dentition phase.

A comparison of random forest regression and multiple linear regression for prediction in neuroscience.

Science.gov (United States)

Smith, Paul F; Ganesh, Siva; Liu, Ping

2013-10-30

Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.

Logistic regression applied to natural hazards: rare event logistic regression with replications

OpenAIRE

Guns, M.; Vanacker, Veerle

2012-01-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logisti...

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

Science.gov (United States)

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

2016-01-01

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

Factors influencing the planning of social activities : empirical analysis of social interaction diary data

NARCIS (Netherlands)

Berg, van den P.E.W.; Arentze, T.A.; Timmermans, H.J.P.

2010-01-01

Results of a study on the planning of social activities are reported. Data collected in the Netherlands from social interaction diaries were used to estimate a multinomial logistic regression model to analyze whether a social activity is prearranged, routine, or spontaneous as a function of personal

Primary and secondary socialization impacts on support for same-sex marriage after legalization in the Netherlands.

NARCIS (Netherlands)

Lubbers, M; Jaspers, E.; Ultee, W.C.

2009-01-01

Two years after the legalization of same-sex marriages in the Netherlands, 65% of the Dutch population largely or completely disagrees with the statement “gay marriage should be abolished.” This article shows, by way of multinomial logistic regression analysis of survey data, which socializing

Utility of DSM-5 section III personality traits in differentiating borderline personality disorder from comparison groups

DEFF Research Database (Denmark)

Bach, B; Sellbom, M; Bo, S

2016-01-01

with the categorical DSM-IV/5 diagnosis of BPD (n=101) from systematically matched samples of other PD patients (n=101) and healthy controls (n=101). This was investigated using one-way ANOVA and multinomial logistic regression analyses. RESULTS: Results indicated that Emotional Lability, Risk Taking...

Household Income during Childhood and Young Adult Weight Status: Evidence from a Nutrition Transition Setting

Science.gov (United States)

Schmeer, Kammi K.

2010-01-01

This article explores whether household income at different stages of childhood is associated with weight status in early adulthood in a nutrition transition setting (a developing country with both underweight and overweight populations). I use multinomial logistic regression to analyze prospective, longitudinal data from Cebu, Philippines.…

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

Saltonstall, Margot

2013-01-01

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

Duration and setting of rural immersion during the medical degree relates to rural work outcomes.

Science.gov (United States)

O'Sullivan, Belinda; McGrail, Matthew; Russell, Deborah; Walker, Judi; Chambers, Helen; Major, Laura; Langham, Robyn

2018-04-19

Providing year-long rural immersion as part of the medical degree is commonly used to increase the number of doctors with an interest in rural practice. However, the optimal duration and setting of immersion has not been fully established. This paper explores associations between various durations and settings of rural immersion during the medical degree and whether doctors work in rural areas after graduation. Eligible participants were medical graduates of Monash University between 2008 and 2016 in postgraduate years 1-9, whose characteristics, rural immersion information and work location had been prospectively collected. Separate multiple logistic regression and multinomial logit regression models tested associations between the duration and setting of any rural immersion they did during the medical degree and (i) working in a rural area and (ii) working in large or smaller rural towns, in 2017. The adjusted odds of working in a rural area were significantly increased if students were immersed for one full year (odds ratio [OR], 1.79; 95% confidence interval [CI], 1.15-2.79), for between 1 and 2 years (OR, 2.26; 95% CI, 1.54-3.32) and for 2 or more years (OR, 4.43; 95% CI, 3.03-6.47) relative to no rural immersion. The strongest association was for immersion in a mix of both regional hospitals and rural general practice (OR, 3.26; 95% CI, 2.31-4.61), followed by immersion in regional hospitals only (OR, 1.94; 95% CI, 1.39-2.70) and rural general practice only (OR, 1.91; 95% CI, 1.06-3.45). More than 1 year's immersion in a mix of regional hospitals and rural general practices was associated with working in smaller regional or rural towns (immersion programmes. Longer rural immersion and immersion in both regional hospitals and rural general practices are likely to increase rural work and rural distribution of early career doctors. © 2018 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

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.

Application of an almost ideal demand system (AIDS) to Ethiopian rural residential energy use: Panel data evidence

International Nuclear Information System (INIS)

Guta, Dawit Diriba

2012-01-01

It is well known that poor rural households in low-income economies are reliant on traditional fuels to meet basic domestic energy needs, but little is known about the specific underlying socio-economic drivers of residential fuel choices in Ethiopia. I used the linear approximation almost ideal demand system (LAAIDS) with normalized prices to compute expenditure elasticity and a multinomial logit model (MLM) to examine household fuel use. The LAAIDS model result showed that expenditure was elastic for modern fuels, but inelastic for traditional fuels. Regression results from the MLM indicated that fuel choice behaviour of rural households could be more accurately described as ‘fuel stacking’ behaviour as opposed to the ‘energy ladder’ hypothesis. In rural areas household fuel choice may be constrained by limited access to commercial fuels and efficient cook stoves, supply dependency and affordability, consumer preferences and a web of other intricate factors. Rural households had less incentive for fuel switching due to underlying factors and the availability of fuel wood without direct financial cost. With continued deforestation and receding forests, households are expected to develop inter fuel substitution and switching behaviour conditional on access to modern energy technologies. - Highlights: ► Two step LAAIDS model and MLM were applied to analysis of residential fuel use. ► I examined issues of ‘energy ladder’ versus ‘fuel stacking’ behavior of households. ► Controlling other factors increase in welfare increases demand for modern fuel. ► Traditional fuels are income inelastic but not necessarily cheaper. ► Residential fuel choice is determined by intricate web of socio-economic factors.

SKENARIO PENGEMBANGAN SISTEM ANGKUTAN UMUM DI KOTA PALANGKA RAYA BERBASIS SISTEM TRANSPORTASI BERKELANJUTAN

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Sutan Parasian Silitonga

2017-07-01

Full Text Available The concept of a sustainable and environmental transportation system emphasizes the widespread use of public transport, but the fact is very contrary to the development of the motorization trend era in Asian countries, especially the use of private vehicles motorcycles type. This is very closely related to the low functionality of public transport utilities, so it is not interesting to use. The success in the implementation of sustainable transportation policy is highly depended on the situation and condition of a city and the approach and understanding of the characteristics of society behavior, so that in the development of a city's public transport system there are not only technical and economic considerations but also community (social preference consideration as an important part that unignoreable.  This research specifically aimed to respond the community preferences using Multinomial Logit  (MNL model on several development scenarios of public transportation system in Palangka Raya based on scenario of road network pattern, traffic flow characteristic and land use type where the scenario analyzed using Analytic Hierarchy Procces (AHP based on key parameters such as costs, construction and planning time, passenger capacity, flexibility, velocity, influence on city development and environment. The results of the study based on AHP analysis and regression analysis on community responses provided clear guidance on appropriate scenarios developed in Palangka Raya City where one of the main factor in the implementation consideration was the financial capability of the city. Final conclusion, the development of public transportation system scenario of Bus Rapid Transit (BRT model equipped with feeder became a worthy considered option by the government of Palangka Raya City. Keywords: AHP, MNL, Development Scenario, BRT

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

International Nuclear Information System (INIS)

Hooman, A.; Mohammadzadeh, M.

2008-01-01

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

A Seemingly Unrelated Poisson Regression Model

OpenAIRE

King, Gary

1989-01-01

This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.

Recursive Algorithm For Linear Regression

Science.gov (United States)

Varanasi, S. V.

1988-01-01

Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.

Applied regression analysis a research tool

CERN Document Server

Pantula, Sastry; Dickey, David

1998-01-01

Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

Standards for Standardized Logistic Regression Coefficients

Science.gov (United States)

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

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

Science.gov (United States)

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Logistic regression for dichotomized counts.

Science.gov (United States)

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

The Influences of Health Insurance and Access to Information on Prostate Cancer Screening among Men in Dominican Republic

International Nuclear Information System (INIS)

Kangmennaang, J.; Luginaah, I.

2016-01-01

Although research demonstrates the public health burden of prostate cancer among men in the Caribbean, relatively little is known about the factors that underlie the low levels of testing for the disease among this population. Study Design. A cross-sectional study of prostate cancer testing behaviours among men aged 40-60 years in Dominican Republic using the Demographic and Health Survey (2013). Methods. We use hierarchical binary logit regression models and average treatment effects combined with propensity score matching to explore the determinants of prostate screening as well as the average effect of health insurance coverage on screening. The use of hierarchical binary logit regression enabled us to control for the effect of unobserved heterogeneity at the cluster level that may affect prostate cancer testing behaviours. Results. Screening varied significantly with health insurance coverage, knowledge of cholesterol level, education, and wealth. Insured men were more likely to test for prostate cancer (OR=1.65, P=0.01) compared to the uninsured. Conclusions. The expansion and restructuring of Dominican Republic universal health insurance scheme to ensure equity in access may improve health access that would potentially impact positively on prostate cancer screening among men.

Bayesian ARTMAP for regression.

Science.gov (United States)

Sasu, L M; Andonie, R

2013-10-01

Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mechanisms of neuroblastoma regression

Science.gov (United States)

Brodeur, Garrett M.; Bagatell, Rochelle

2014-01-01

Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients

Science.gov (United States)

Gorgees, HazimMansoor; Mahdi, FatimahAssim

2018-05-01

This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.

Multicollinearity and Regression Analysis

Science.gov (United States)

Daoud, Jamal I.

2017-12-01

In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

Panel Smooth Transition Regression Models

DEFF Research Database (Denmark)

González, Andrés; Terasvirta, Timo; Dijk, Dick van

We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...

Credit Scoring Problem Based on Regression Analysis

OpenAIRE

Khassawneh, Bashar Suhil Jad Allah

2014-01-01

ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....

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

Science.gov (United States)

Storen, Liv Anne; Wiers-Jenssen, Jannecke

2010-01-01

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

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

Science.gov (United States)

Lubbers, Marcel; Jaspers, Eva; Ultee, Wout

2009-01-01

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

Support vector machines classifiers of physical activities in preschoolers

Science.gov (United States)

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

Determinants of Male Circumcision for HIV/AIDS Prevention in East ...

African Journals Online (AJOL)

Safe Male Circumcision (SMC) is one the effective strategies for reducing HIV transmission. The paper examines factors associated with SMC for HIV prevention, based on 4,979 males from East Central Uganda. Data were analysed using chi-squared tests and multinomial logistic regression. Older males aged 31 years ...

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

Science.gov (United States)

Grinshteyn, Erin; Yang, Y. T.

2017-01-01

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

How bicycle level of traffic stress correlate with reported cyclist accidents injury severities: A geospatial and mixed logit analysis.

Science.gov (United States)

Chen, Chen; Anderson, Jason C; Wang, Haizhong; Wang, Yinhai; Vogt, Rachel; Hernandez, Salvador

2017-11-01

Transportation agencies need efficient methods to determine how to reduce bicycle accidents while promoting cycling activities and prioritizing safety improvement investments. Many studies have used standalone methods, such as level of traffic stress (LTS) and bicycle level of service (BLOS), to better understand bicycle mode share and network connectivity for a region. However, in most cases, other studies rely on crash severity models to explain what variables contribute to the severity of bicycle related crashes. This research uniquely correlates bicycle LTS with reported bicycle crash locations for four cities in New Hampshire through geospatial mapping. LTS measurements and crash locations are compared visually using a GIS framework. Next, a bicycle injury severity model, that incorporates LTS measurements, is created through a mixed logit modeling framework. Results of the visual analysis show some geospatial correlation between higher LTS roads and "Injury" type bicycle crashes. It was determined, statistically, that LTS has an effect on the severity level of bicycle crashes and high LTS can have varying effects on severity outcome. However, it is recommended that further analyses be conducted to better understand the statistical significance and effect of LTS on injury severity. As such, this research will validate the use of LTS as a proxy for safety risk regardless of the recorded bicycle crash history. This research will help identify the clustering patterns of bicycle crashes on high-risk corridors and, therefore, assist with bicycle route planning and policy making. This paper also suggests low-cost countermeasures or treatments that can be implemented to address high-risk areas. Specifically, with the goal of providing safer routes for cyclists, such countermeasures or treatments have the potential to substantially reduce the number of fatalities and severe injuries. Published by Elsevier Ltd.

Unbalanced Regressions and the Predictive Equation

DEFF Research Database (Denmark)

Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...... in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... to aggregation or unexpected level shifts. In this setup, the practitioner estimates a misspecified, unbalanced, and endogenous predictive regression. We show that the OLS estimate of this regression is inconsistent, but standard inference is possible. To obtain a consistent slope estimate, we then suggest...

[From clinical judgment to linear regression model.

Science.gov (United States)

Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

2013-01-01

When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

Autistic Regression

Science.gov (United States)

Matson, Johnny L.; Kozlowski, Alison M.

2010-01-01

Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation

Directory of Open Access Journals (Sweden)

Sharad Damodar Gore

2009-10-01

Full Text Available Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR. This estimator is obtained from unbiased ridge regression (URR in the same way that ordinary ridge regression (ORR is obtained from ordinary least squares (OLS. Properties of MUR are derived. Results on its matrix mean squared error (MMSE are obtained. MUR is compared with ORR and URR in terms of MMSE. These results are illustrated with an example based on data generated by Hoerl and Kennard (1975.

Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

2017-03-01

In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

Participation in Farm Markets in Rural Northwest Pakistan: A Regression Analysis

Directory of Open Access Journals (Sweden)

Inayatullah Jan

2012-12-01

Full Text Available Participation in farm markets is important for increasing income of farmers in the developing countries. A number of factors account for a household participation in agricultural marketing. This study attempts to explore such associated factors which playa significant role in farmers’ participation in farm markets in rural northwest Pakistan. Drawing on empirical data from the field survey; gur, vegetables, and milk were the main products offered for marketing in the area. The degree of specialization of marketrelations was based on the nature of the farm product. In gur markets, the marketing relations were based on personalized terms whereas in vegetable markets, they were exclusively commercialized. The results of the binary logit model show that size of selfcultivatedland and number of livestock, were important determinants of a household participation in agricultural marketing. The study concludes that participation in agricultural markets could be substantially increased through improved infrastructure,commercialized farming systems, and increased number of farm markets so that the dominance of few selected commission agents is minimized.

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.

The morality of attitudes toward nanotechnology: about God, techno-scientific progress, and interfering with nature

International Nuclear Information System (INIS)

Vandermoere, Frederic; Blanchemanche, Sandrine; Bieberstein, Andrea; Marette, Stephan; Roosen, Jutta

2010-01-01

Using survey data, we examine public attitudes toward and awareness of nanotechnology in Germany (N = 750). First, it is shown that a majority of the people are still not familiar with nanotechnology. In addition, diffusion of information about nanotechnology thus far mostly seems to reach men and people with a relative higher educational background. Also, pro-science and technology views are positively related with nanotech familiarity. Results further show that a majority of the people have an indifferent, ambiguous, or non-attitude toward nanotechnology. Multinomial logit analyses further reveal that nanotech familiarity is positively related with people's attitudes. In addition, it is shown that traditional religiosity is unrelated to attitudes and that individual religiosity is weakly related to nanotechnology attitudes. However, moral covariates other than religiosity seem of major importance. In particular, our results show that more negative views on technological and scientific progress as well as more holistic views about the relation between people and the environment increase the likelihood of having a negative attitude toward nanotechnology.

Transitions between states of labor-force participation among older Israelis.

Science.gov (United States)

Achdut, Leah; Tur-Sinai, Aviad; Troitsky, Rita

2015-03-01

The study examines the labor-force behavior of Israelis at older ages, focusing on the determinants of the transitions between states of labor-force participation between 2005 and 2010. The study uses panel data from the first two waves of the SHARE-Israel longitudinal survey. A multinomial logit model is used to examine the impact of sociodemographic characteristics, health state, and economic resources on labor-force transitions of people aged 50-67. The results emphasize the role of age and poor health in "pushing" older people out of the labor force or "keeping" them there. Spouse's participation is found to encourage individuals to leave the labor force or to refrain from joining it. However, living with a participating spouse is negatively associated with staying out of the labor force, consistent with the dominance of the complementarity of leisure effect found in the literature. Wealth as an economic resource available to individuals for retirement is also found to encourage individuals to leave the labor force or to refrain from joining it.

Farmer preference for improved corn seeds in Chiapas, Mexico: A choice experiment approach

International Nuclear Information System (INIS)

Sánchez-Toledano, Blanca I.; Kallas, Zein; Gil-Roig, José M.

2017-01-01

Appropriate technologies must be developed for adoption of improved seeds based on the farmers’ preferences and needs. Our research identified the farmers’ willingness to pay (WTP) as a key determinant for selecting the improved varieties of maize seeds and landraces in Chiapas, Mexico. This work also analyzed the farmers’ observed heterogeneity on the basis of their socio-economic characteristics. Data were collected using a semi-structured questionnaire from 200 farmers. A proportional choice experiment approach was applied using a proportional choice variable, where farmers were asked to state the percentage of preference for different alternative varieties in a choice set. The generalized multinomial logit model in WTP-space approach was used. The results suggest that the improved seed varieties are preferred over the Creole alternatives, thereby ensuring higher yields, resistance to diseases, and larger ear size. For the preference heterogeneity analyses, a latent class model was applied. Three types of farmers were identified: innovators (60.5%), transition farmers (29.4%), and conservative farmers (10%). An understanding of farmers’ preferences is useful in designing agricultural policies and creati

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.

Analysis on Time Window of Shared Parking in Hospitals Based on Parking Behaviors

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Qin Chen

2017-01-01

Full Text Available Hospitals are essential components of a city; huge traffic demand is generated and attracted, causing contradiction between parking supply and demand. By sharing parking berths, limited space can serve more demand which is beneficial to alleviating parking problems. Aimed at improving the capacity of shared parking, the paper analyzes four parking groups in typical hospitals, which are medical staff, outpatients, emergency patients, and visiting groups. The parking demand of medical staff is rigid. For outpatients and visiting groups, longer walking distance is acceptable and more attention is paid to parking fee. By contrast, emergency patients can accept shorter walking distance and focus more on convenience due to urgency. Under this circumstance, parking behaviors selection models are established by means of Multinomial Logit Model. On this basis, time value is adopted to calculate the tolerance of alterative parking time. Moreover, this paper explores the variation of time window, under different parking impedance. A case study is conducted and suggests that start and end point of a certain time window can be influenced by external factors.

Residents’ Preferences for Household Kitchen Waste Source Separation Services in Beijing: A Choice Experiment Approach

Directory of Open Access Journals (Sweden)

Yalin Yuan

2014-12-01

Full Text Available A source separation program for household kitchen waste has been in place in Beijing since 2010. However, the participation rate of residents is far from satisfactory. This study was carried out to identify residents’ preferences based on an improved management strategy for household kitchen waste source separation. We determine the preferences of residents in an ad hoc sample, according to their age level, for source separation services and their marginal willingness to accept compensation for the service attributes. We used a multinomial logit model to analyze the data, collected from 394 residents in Haidian and Dongcheng districts of Beijing City through a choice experiment. The results show there are differences of preferences on the services attributes between young, middle, and old age residents. Low compensation is not a major factor to promote young and middle age residents accept the proposed separation services. However, on average, most of them prefer services with frequent, evening, plastic bag attributes and without instructor. This study indicates that there is a potential for local government to improve the current separation services accordingly.

Dynamic Competition and Cooperation of Road Infrastructure Investment of Multiple Tourism Destinations: A Case Study of Xidi and Hongcun World Cultural Heritage

Directory of Open Access Journals (Sweden)

Jun Li

2015-01-01

Full Text Available The transportation infrastructure always plays an important role in the development of the local tourism. A system dynamics method incorporated with a destination choice model is proposed in this paper to analyze the dynamic impacts of transportation infrastructure on the tourism development, where multiple tourism destinations share a common market. Tourists’ destination choice behaviors are characterized by a multinomial logit choice model based on the utility of destinations, which depends heavily on the accessibility of destinations that the local administration has strong willingness to improve. The system dynamics method is used to model dynamic interactions among destinations and to simulate the dynamic evolution of the competition on the tourism market. A case study of the World Cultural Heritage Sites, Xidi and Hongcun villages, shows the competition for road infrastructure investment can produce a win-win situation and bring the cooperation on investment due to the positive externality of transport infrastructure and two villages show a tendency to merge into one bigger destination. Finally, the tourism development strategies for two villages are discussed based on the scenario analysis.

Household waste disposal in Mekelle city, Northern Ethiopia

International Nuclear Information System (INIS)

Tadesse, Tewodros; Ruijs, Arjan; Hagos, Fitsum

2008-01-01

In many cities of developing countries, such as Mekelle (Ethiopia), waste management is poor and solid wastes are dumped along roadsides and into open areas, endangering health and attracting vermin. The effects of demographic factors, economic and social status, waste and environmental attributes on household solid waste disposal are investigated using data from household survey. Household level data are then analyzed using multinomial logit estimation to determine the factors that affect household waste disposal decision making. Results show that demographic features such as age, education and household size have an insignificant impact over the choice of alternative waste disposal means, whereas the supply of waste facilities significantly affects waste disposal choice. Inadequate supply of waste containers and longer distance to these containers increase the probability of waste dumping in open areas and roadsides relative to the use of communal containers. Higher household income decreases the probability of using open areas and roadsides as waste destinations relative to communal containers. Measures to make the process of waste disposal less costly and ensuring well functioning institutional waste management would improve proper waste disposal

Analyzing the severity of accidents on the German Autobahn.

Science.gov (United States)

Manner, Hans; Wünsch-Ziegler, Laura

2013-08-01

We study the severity of accidents on the German Autobahn in the state of North Rhine-Westphalia using data for the years 2009 until 2011. We use a multinomial logit model to identify statistically relevant factors explaining the severity of the most severe injury, which is classified into the four classes fatal, severe injury, light injury and property damage. Furthermore, to account for unobserved heterogeneity we use a random parameter model. We study the effect of a number of factors including traffic information, road conditions, type of accidents, speed limits, presence of intelligent traffic control systems, age and gender of the driver and location of the accident. Our findings are in line with studies in different settings and indicate that accidents during daylight and at interchanges or construction sites are less severe in general. Accidents caused by the collision with roadside objects, involving pedestrians and motorcycles, or caused by bad sight conditions tend to be more severe. We discuss the measures of the 2011 German traffic safety programm in the light of our results. Copyright © 2013 Elsevier Ltd. All rights reserved.

The morality of attitudes toward nanotechnology: about God, techno-scientific progress, and interfering with nature

Science.gov (United States)

Vandermoere, Frederic; Blanchemanche, Sandrine; Bieberstein, Andrea; Marette, Stephan; Roosen, Jutta

2010-02-01

Using survey data, we examine public attitudes toward and awareness of nanotechnology in Germany ( N = 750). First, it is shown that a majority of the people are still not familiar with nanotechnology. In addition, diffusion of information about nanotechnology thus far mostly seems to reach men and people with a relative higher educational background. Also, pro-science and technology views are positively related with nanotech familiarity. Results further show that a majority of the people have an indifferent, ambiguous, or non-attitude toward nanotechnology. Multinomial logit analyses further reveal that nanotech familiarity is positively related with people's attitudes. In addition, it is shown that traditional religiosity is unrelated to attitudes and that individual religiosity is weakly related to nanotechnology attitudes. However, moral covariates other than religiosity seem of major importance. In particular, our results show that more negative views on technological and scientific progress as well as more holistic views about the relation between people and the environment increase the likelihood of having a negative attitude toward nanotechnology.

Farmer preference for improved corn seeds in Chiapas, Mexico: A choice experiment approach

Energy Technology Data Exchange (ETDEWEB)

Sánchez-Toledano, Blanca I.; Kallas, Zein; Gil-Roig, José M.

2017-07-01

Appropriate technologies must be developed for adoption of improved seeds based on the farmers’ preferences and needs. Our research identified the farmers’ willingness to pay (WTP) as a key determinant for selecting the improved varieties of maize seeds and landraces in Chiapas, Mexico. This work also analyzed the farmers’ observed heterogeneity on the basis of their socio-economic characteristics. Data were collected using a semi-structured questionnaire from 200 farmers. A proportional choice experiment approach was applied using a proportional choice variable, where farmers were asked to state the percentage of preference for different alternative varieties in a choice set. The generalized multinomial logit model in WTP-space approach was used. The results suggest that the improved seed varieties are preferred over the Creole alternatives, thereby ensuring higher yields, resistance to diseases, and larger ear size. For the preference heterogeneity analyses, a latent class model was applied. Three types of farmers were identified: innovators (60.5%), transition farmers (29.4%), and conservative farmers (10%). An understanding of farmers’ preferences is useful in designing agricultural policies and creati.

Access to Bridge Employment: Who Finds and Who Does Not Find Work After Retirement?

Science.gov (United States)

Dingemans, Ellen; Henkens, Kène; Solinge, Hanna van

2016-08-01

Empirical studies on the determinants of bridge employment have often neglected the fact that some retirees may be unsuccessful in finding a bridge job. We present an integrative framework that emphasizes socioeconomic factors, health status, social context, and psychological factors to explain why some people fully retired after career exit, some participated in bridge jobs, while others unsuccessfully searched for one. Using Dutch panel data for 1,221 retirees, we estimated a multinomial logit model to explain participation in, and unsuccessful searches for, bridge employment. About 1 in 4 retirees participated in bridge employment after retirement, while 7% searched unsuccessfully for such work. Particularly those who experienced involuntary career exit were found to have a higher probability of being unsuccessful at finding bridge employment. The current study provides evidence for the impact of the social context on postretirement work and suggests a cumulative disadvantage in the work domain in later life. © 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.

Patient Preferences for Managing Insomnia: A Discrete Choice Experiment.

Science.gov (United States)

Cheung, Janet M Y; Bartlett, Delwyn J; Armour, Carol L; Saini, Bandana; Laba, Tracey-Lea

2018-03-03

Despite the rapid development of effective treatments, both pharmacological and non-pharmacological, insomnia management remains suboptimal at the practice interface. Patient preferences play a critical role in influencing treatment outcomes. However, there is currently a mismatch between patient preferences and clinician recommendations, partly perpetuated by a limited understanding of the patients' decision-making process. The aim of our study was to empirically quantify patient preferences for treatment attributes common to both pharmacological and non-pharmacological insomnia treatments. An efficient dual-response discrete choice experiment was conducted to evaluate patient treatment preferences for managing insomnia. The sample included 205 patients with self-reported insomnia and an Insomnia Severity Index ≥ 14. Participants were presented with two unlabelled hypothetical scenarios with an opt-out option across 12 choice sets. Data were analyzed using a mixed multinomial logit model to investigate the influence of five attributes (i.e. time, onset of action, maintainability of improved sleep, length of treatment, and monthly cost) on treatment preferences. Treatments were preferentially viewed if they conferred long-term sleep benefits (p managing insomnia.

What factors influence choice of waste management practice? Evidence from rice straw management in the Philippines.

Science.gov (United States)

Launio, Cheryll C; Asis, Constancio A; Manalili, Rowena G; Javier, Evelyn F; Belizario, Annabelle F

2014-02-01

This study applied a multinomial logit model to understand why farmers choose to burn, incorporate or remove rice straw in the field. Four hundred randomly selected farmers were interviewed in four major rice-producing provinces covering the 2009 wet and 2010 dry seasons. Results of the model with burning as the baseline category indicate farm type, location dummies, number of household members with older than 13 years, cow ownership and distance from farm to house as significant variables influencing farmers' choice of straw incorporation or removal over burning. Significant perception variables are the negative impacts of open-field burning, awareness of environmental regulations and attitude towards incentives. Other factors significantly influencing the decision to incorporate over-burn are training attendance and perceptions of effects of straw incorporation. Income from non-rice farming, total area cultivated, tenure status, presence of burning and solid waste management provincial ordinances are significant factors affecting choice to remove over burn. Continually providing farmers' training in rice production, increasing demand for rice straw for other uses, and increasing awareness of environmental laws and regulations are policy directions recommended.

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...

The morality of attitudes toward nanotechnology: about God, techno-scientific progress, and interfering with nature

Energy Technology Data Exchange (ETDEWEB)

Vandermoere, Frederic, E-mail: Frederic_Vandermoere@hks.harvard.ed [Program on Science, Technology and Society, Harvard Kennedy School (United States); Blanchemanche, Sandrine [INRA Paris, Metarisk Department (France); Bieberstein, Andrea [Technische Universitaet Muenchen, Marketing und Konsumforschung (Germany); Marette, Stephan [INRA, UMR Economie publique (France); Roosen, Jutta [Technische Universitaet Muenchen, Lehrstuhl fuer BWL - Marketing und Konsumforschung (Germany)

2010-02-15

Using survey data, we examine public attitudes toward and awareness of nanotechnology in Germany (N = 750). First, it is shown that a majority of the people are still not familiar with nanotechnology. In addition, diffusion of information about nanotechnology thus far mostly seems to reach men and people with a relative higher educational background. Also, pro-science and technology views are positively related with nanotech familiarity. Results further show that a majority of the people have an indifferent, ambiguous, or non-attitude toward nanotechnology. Multinomial logit analyses further reveal that nanotech familiarity is positively related with people's attitudes. In addition, it is shown that traditional religiosity is unrelated to attitudes and that individual religiosity is weakly related to nanotechnology attitudes. However, moral covariates other than religiosity seem of major importance. In particular, our results show that more negative views on technological and scientific progress as well as more holistic views about the relation between people and the environment increase the likelihood of having a negative attitude toward nanotechnology.

Mobilidade ocupacional no Brasil: uma análise das chances de mobilidade e inserção ocupacional segundo a origem, a cor e a situação de migração e não-migração para homens chefes do domicílio (1988-1996

Directory of Open Access Journals (Sweden)

Lygia Gonçalves Costa

2009-01-01

Full Text Available Our goal in this article is twofold. Firstly, we present a short overview of theoretical and empirical studies about social stratification and mobility in Brazil. Secondly, we analyze mobility and occupational insertion chances according to origin, color and various migrational status such as migrants from the Northeast Region to the Southeast Region, non-migrants from the Northeast Region and non-migrants from the Southeast Region. The Logit Multinomial model is used for the hypothesis test where the relative chances for occupational insertion of the various migration groups were analyzed. We use the same occupational classes as the ones used by Erikson, Goldthorpe and Portocarrero (EGP (Erikson et al., 1979, also the same as in the classical mobility study 'The Constant Flux' (Erikson and Goldthorpe, 1993, only adapting the self-employed category to the Brazilian reality. By the lack of recent data we only analyze the last two editions of the "National Sample Survey of Households" (Pesquisa Nacional por Amostra de Domicílios - PNAD/IBGE 1988 and 1996.

Categorical regression dose-response modeling

Science.gov (United States)

The goal of this training is to provide participants with training on the use of the U.S. EPA’s Categorical Regression soft¬ware (CatReg) and its application to risk assessment. Categorical regression fits mathematical models to toxicity data that have been assigned ord...

Abstract Expression Grammar Symbolic Regression

Science.gov (United States)

Korns, Michael F.

This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.

Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

OpenAIRE

KELEŞ, Taliha; ALTUN, Murat

2016-01-01

Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

Pathological assessment of liver fibrosis regression

Directory of Open Access Journals (Sweden)

WANG Bingqiong

2017-03-01

Full Text Available Hepatic fibrosis is the common pathological outcome of chronic hepatic diseases. An accurate assessment of fibrosis degree provides an important reference for a definite diagnosis of diseases, treatment decision-making, treatment outcome monitoring, and prognostic evaluation. At present, many clinical studies have proven that regression of hepatic fibrosis and early-stage liver cirrhosis can be achieved by effective treatment, and a correct evaluation of fibrosis regression has become a hot topic in clinical research. Liver biopsy has long been regarded as the gold standard for the assessment of hepatic fibrosis, and thus it plays an important role in the evaluation of fibrosis regression. This article reviews the clinical application of current pathological staging systems in the evaluation of fibrosis regression from the perspectives of semi-quantitative scoring system, quantitative approach, and qualitative approach, in order to propose a better pathological evaluation system for the assessment of fibrosis regression.

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

Science.gov (United States)

Lo, Celia C.; Cheng, Tyrone C.

2013-01-01

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

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

Science.gov (United States)

Stroope, Samuel

2012-01-01

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

Logistic Regression: Concept and Application

Science.gov (United States)

Cokluk, Omay

2010-01-01

The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

Science.gov (United States)

Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

2007-09-01

Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha

2014-12-08

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha; Huang, Jianhua Z.

2014-01-01

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

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

Science.gov (United States)

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

2016-03-01

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