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

PubMed

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.

Consumer preferences for food product quality attributes from Swedish agriculture.

PubMed

Carlsson, Fredrik; Frykblom, Peter; Lagerkvist, Carl Johan

2005-06-01

This paper employs a choice experiment to obtain consumer preferences and willingness to pay for food product quality attributes currently not available in Sweden. Data were obtained from a large mail survey and estimated with a random parameter logit model. We found evidence for intraproduct differences in consumer preferences for identical attributes, as well as interproduct discrepancies in ranking of attributes. Furthermore, we found evidence of a market failure relating to the potential use of genetically modified animal fodder. Finally, we found support for the idea that a cheap-talk script can alleviate problems of external validity of choice experiments. Our results are useful in forming product differentiation strategies within the food industry, as well as for the formation of food policy.

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

NASA Astrophysics Data System (ADS)

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 data best, indication that allowing for both heterogeneous preferences across households and correlation between repeated choices may represent actual choice behaviors best of all the estimated models. The annual benefits to improve of the Anyancheon watershed for 1% improvement of each attribute was 406.7 billion Won(0.34 billion USD). This study is expected to contribute to the decision-making process for policy-makers by providing useful methodological framework and quantitative information related to watershed improvement projects.Table 1. Estimated Results of Conditional Logit and Mixed Logit Model 1) t-values are shown in brackets

Measuring Developmental Students' Mathematics Anxiety

ERIC Educational Resources Information Center

Ding, Yanqing

2016-01-01

This study conducted an item-level analysis of mathematics anxiety and examined the dimensionality of mathematics anxiety in a sample of developmental mathematics students (N = 162) by Multi-dimensional Random Coefficients Multinominal Logit Model (MRCMLM). The results indicate a moderately correlated factor structure of mathematics anxiety (r =…

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

PubMed

Warton, David I; Hui, Francis K C

2011-01-01

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

Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.

PubMed

Chan, Jennifer S K

2016-05-01

Dropouts are common in longitudinal study. If the dropout probability depends on the missing observations at or after dropout, this type of dropout is called informative (or nonignorable) dropout (ID). Failure to accommodate such dropout mechanism into the model will bias the parameter estimates. We propose a conditional autoregressive model for longitudinal binary data with an ID model such that the probabilities of positive outcomes as well as the drop-out indicator in each occasion are logit linear in some covariates and outcomes. This model adopting a marginal model for outcomes and a conditional model for dropouts is called a selection model. To allow for the heterogeneity and clustering effects, the outcome model is extended to incorporate mixture and random effects. Lastly, the model is further extended to a novel model that models the outcome and dropout jointly such that their dependency is formulated through an odds ratio function. Parameters are estimated by a Bayesian approach implemented using the user-friendly Bayesian software WinBUGS. A methadone clinic dataset is analyzed to illustrate the proposed models. Result shows that the treatment time effect is still significant but weaker after allowing for an ID process in the data. Finally the effect of drop-out on parameter estimates is evaluated through simulation studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Mixed Effects Trend Vector Model

ERIC Educational Resources Information Center

de Rooij, Mark; Schouteden, Martijn

2012-01-01

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

SU-F-T-104: Determining the NTCP Parameters of Pharyngeal Constrictors and Proximal Esophagus for Radiation Induced Swallowing Problems Recorded Six Months After Radiation Therapy for Head and Neck Tumors

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

Mavroidis, P; Price, A; Kostich, M

Purpose: To estimate the radiobiological parameters of four NTCP models that describe the dose-response relations of pharyngeal constrictors and proximal esophagus regarding the severity of patient reported swallowing problems 6 months post chemo-radiotherapy. To identify the section/structure that best correlates with the manifestation of the clinical endpoints. Finally, to compare the goodness-of-fit of those models. Methods: Forty-three patients were treated on a prospective multi-institutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric datamore » of superior, medium and inferior sections of pharyngeal constrictors (SPC, MPC and IPC), superior and inferior sections of esophagus (SES and IES) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patient data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the SPC for Grade ≥ 2 (0.719 for the RS and RL models, and 0.716 for LKB and Logit). For Grade ≥ 1, the respective values were 0.699 for RS, LKB and Logit and 0.676 for RL. For MPC the AUC values varied between 0.463–0.477, for IPC between 0.396–0.458, for SES between 0.556–0.613 and for IES between 0.410–0.519. The Odds Ratio for the SPC was 15.6 (1.7–146.4) for RS, LKB and Logit for NTCP of 55%. Conclusion: All the examined NTCP models could fit the clinical data with similar accuracy. The SPC appear to correlate best with the clinical endpoints of swallowing problems. A prospective study could establish the use of NTCP values of SPC as a constraint in treatment planning.« less

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

ERIC Educational Resources Information Center

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

2015-01-01

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

Design and analysis of simple choice surveys for natural resource management

USGS Publications Warehouse

Fieberg, John; Cornicelli, Louis; Fulton, David C.; Grund, Marrett D.

2010-01-01

We used a simple yet powerful method for judging public support for management actions from randomized surveys. We asked respondents to rank choices (representing management regulations under consideration) according to their preference, and we then used discrete choice models to estimate probability of choosing among options (conditional on the set of options presented to respondents). Because choices may share similar unmodeled characteristics, the multinomial logit model, commonly applied to discrete choice data, may not be appropriate. We introduced the nested logit model, which offers a simple approach for incorporating correlation among choices. This forced choice survey approach provides a useful method of gathering public input; it is relatively easy to apply in practice, and the data are likely to be more informative than asking constituents to rate attractiveness of each option separately.

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

PubMed

Sarma, Sisira; Simpson, Wayne

2007-12-01

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

A comparative injury severity analysis of motorcycle at-fault crashes on rural and urban roadways in Alabama.

PubMed

Islam, Samantha; Brown, Joshua

2017-11-01

The research described in this paper explored the factors contributing to the injury severity resulting from the motorcycle at-fault accidents in rural and urban areas in Alabama. Given the occurrence of a motorcycle at-fault crash, random parameter logit models of injury severity (with possible outcomes of fatal, major, minor, and possible or no injury) were estimated. The estimated models identified a variety of statistically significant factors influencing the injury severities resulting from motorcycle at-fault crashes. According to these models, some variables were found to be significant only in one model (rural or urban) but not in the other one. For example, variables such as clear weather, young motorcyclists, and roadway without light were found significant only in the rural model. On the other hand, variables such as older female motorcyclists, horizontal curve and at intersection were found significant only in the urban model. In addition, some variables (such as, motorcyclists under influence of alcohol, non-usage of helmet, high speed roadways, etc.) were found significant in both models. Also, estimation findings showed that two parameters (clear weather and roadway without light) in the rural model and one parameter (on weekend) in the urban model could be modeled as random parameters indicating their varying influences on the injury severity due to unobserved effects. Based on the results obtained, this paper discusses the effects of different variables on injury severities resulting from rural and urban motorcycle at-fault crashes and their possible explanations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects.

PubMed

Xie, Meiquan; Cheng, Wen; Gill, Gurdiljot Singh; Zhou, Jiao; Jia, Xudong; Choi, Simon

2018-02-17

Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR. This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model. Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime. This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider inner shoulders may be constructed to potentially reduce HR cases and street lights should be installed and maintained in working condition to make roads less prone to such crashes.

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

PubMed

Sun, Guanghao; Shinba, Toshikazu; Kirimoto, Tetsuo; Matsui, Takemi

2016-01-01

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. 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. 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). HRV indices recorded during a MT 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.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

Patient Preferences for Device-Aided Treatments Indicated for Advanced Parkinson Disease.

PubMed

Marshall, Thomas; Pugh, Amy; Fairchild, Angelyn; Hass, Steven

2017-12-01

Effective treatment for advanced Parkinson disease (PD) uncontrolled with oral medication includes device-aided therapies such as deep brain stimulation (DBS) and continuous levodopa-carbidopa infusion to the duodenum via a portable pump. Our objective was to quantify patient preferences for attributes of these device-aided treatments. We administered a Web-enabled survey to 401 patients in the United States. A discrete-choice experiment (DCE) was used to evaluate patients' willingness to accept tradeoffs among efficacy, tolerability, and convenience of alternative treatments. DCE data were analyzed using random-parameters logit. Best-worst scaling (BWS) was used to elicit the relative importance of device-specific attributes. Conditional logit was used to analyze the BWS data. We tested for differences in preferences among subgroups of patients. Improving ability to think clearly was twice as important as a 6-hour-per-day improvement in control of movement symptoms. After controlling for efficacy, treatment delivered via portable infusion pump was preferred over DBS, and both devices were preferred to oral therapy with poor symptom control. Patients were most concerned about device attributes relating to risk of stroke, difficulty thinking, and neurosurgery. Avoiding surgery to insert a wire in the brain was more important than avoiding surgery to insert a tube into the small intestine. Some differences in preferences among subgroups were statistically, but not qualitatively, significant. This study clarifies the patient perspective in therapeutic choices for advanced PD. These findings may help improve communication between patients and providers and also provide evidence on patient preferences to inform regulatory and access decisions. Copyright © 2017. Published by Elsevier Inc.

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

ERIC Educational Resources Information Center

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%…

Transformation of arbitrary distributions to the normal distribution with application to EEG test-retest reliability.

PubMed

van Albada, S J; Robinson, P A

2007-04-15

Many variables in the social, physical, and biosciences, including neuroscience, are non-normally distributed. To improve the statistical properties of such data, or to allow parametric testing, logarithmic or logit transformations are often used. Box-Cox transformations or ad hoc methods are sometimes used for parameters for which no transformation is known to approximate normality. However, these methods do not always give good agreement with the Gaussian. A transformation is discussed that maps probability distributions as closely as possible to the normal distribution, with exact agreement for continuous distributions. To illustrate, the transformation is applied to a theoretical distribution, and to quantitative electroencephalographic (qEEG) measures from repeat recordings of 32 subjects which are highly non-normal. Agreement with the Gaussian was better than using logarithmic, logit, or Box-Cox transformations. Since normal data have previously been shown to have better test-retest reliability than non-normal data under fairly general circumstances, the implications of our transformation for the test-retest reliability of parameters were investigated. Reliability was shown to improve with the transformation, where the improvement was comparable to that using Box-Cox. An advantage of the general transformation is that it does not require laborious optimization over a range of parameters or a case-specific choice of form.

Evaluation of Statistical Methods for Modeling Historical Resource Production and Forecasting

NASA Astrophysics Data System (ADS)

Nanzad, Bolorchimeg

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

Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model.

PubMed

Chen, Cong; Zhang, Guohui; Huang, Helai; Wang, Jiangfeng; Tarefder, Rafiqul A

2016-11-01

Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance. Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinary ordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed. Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring the determinants of pedestrian-vehicle crash severity in New York City.

PubMed

Aziz, H M Abdul; Ukkusuri, Satish V; Hasan, Samiul

2013-01-01

Pedestrian-vehicle crashes remain a major concern in New York City due to high percentage of fatalities. This study develops random parameter logit models for explaining pedestrian injury severity levels of New York City accounting for unobserved heterogeneity in the population and across the boroughs. A log-likelihood ratio test for joint model suitability suggests that separate models for each of the boroughs should be estimated. Among many variables, road characteristics (e.g., number of lanes, grade, light condition, road surface, etc.), traffic attributes (e.g., presence of signal control, type of vehicle, etc.), and land use (e.g., parking facilities, commercial and industrial land use, etc.) are found to be statistically significant in the estimated model. The study also suggests that the set of counter measures should be different for different boroughs in the New York City and the priority ranks of countermeasures should be different as well. Copyright © 2012 Elsevier Ltd. All rights reserved.

Heterogeneity and nonlinearity in consumers’ preferences: An application to the olive oil shopping behavior in Chile

PubMed Central

Romo-Muñoz, Rodrigo Alejandro; Cabas-Monje, Juan Hernán; Garrido-Henrríquez, Héctor Manuel

2017-01-01

In relatively unknown products, consumers use prices as a quality reference. Under such circumstances, the utility function can be non-negative for a specific price range and generate an inverted U-shaped function. The extra virgin olive oil market in Chile is a good example. Although domestic production and consumption have increased significantly in the last few years, consumer knowledge of this product is still limited. The objective of this study was to analyze Chilean consumer preferences and willingness to pay for extra virgin olive oil attributes. Consumers were segmented taking into account purchasing frequency. A Random Parameter Logit model was estimated for preference heterogeneity. Results indicate that the utility function is nonlinear allowing us to differentiate between two regimes. In the first regime, olive oil behaves as a conspicuous good, that is, higher utility is assigned to higher prices and consumers prefer foreign products in smaller containers. Under the second regime, Chilean olive oil in larger containers is preferred. PMID:28892516

Heterogeneity and nonlinearity in consumers' preferences: An application to the olive oil shopping behavior in Chile.

PubMed

Romo-Muñoz, Rodrigo Alejandro; Cabas-Monje, Juan Hernán; Garrido-Henrríquez, Héctor Manuel; Gil, José María

2017-01-01

In relatively unknown products, consumers use prices as a quality reference. Under such circumstances, the utility function can be non-negative for a specific price range and generate an inverted U-shaped function. The extra virgin olive oil market in Chile is a good example. Although domestic production and consumption have increased significantly in the last few years, consumer knowledge of this product is still limited. The objective of this study was to analyze Chilean consumer preferences and willingness to pay for extra virgin olive oil attributes. Consumers were segmented taking into account purchasing frequency. A Random Parameter Logit model was estimated for preference heterogeneity. Results indicate that the utility function is nonlinear allowing us to differentiate between two regimes. In the first regime, olive oil behaves as a conspicuous good, that is, higher utility is assigned to higher prices and consumers prefer foreign products in smaller containers. Under the second regime, Chilean olive oil in larger containers is preferred.

Patients' Preferences Related to Benefits, Risks, and Formulations of Schizophrenia Treatment.

PubMed

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

2015-07-01

The objective of this study was to quantify patients' preferences related to benefits and risks of antipsychotic treatments for schizophrenia and to assess the relative importance of treatment attributes and adherence. Treatment-related preferences among U.S. residents with a self-reported physician diagnosis of schizophrenia were assessed via a discrete-choice experiment. Patients chose between competing hypothetical scenarios characterized by improvements in positive symptoms, negative symptoms, and social functioning; incidence of weight gain, extrapyramidal symptoms (EPS), hyperprolactinemia, and hyperglycemia; and medication formulation. Preferences were estimated by using a random-parameters logit model, and the impact of adherence was estimated with conditional logit models. The final sample consisted of 271 patients. Complete improvement in positive symptoms was the most preferred outcome (relative importance score of 10.0), followed by elimination of hyperglycemia (3.6, 95% confidence interval [CI]=2.6-4.6), improvement in negative symptoms (3.0, CI=1.6-4.3), reduced weight gain (2.6, CI=1.2-4.0), avoidance of hyperprolactinemia (1.7, CI=.9-2.6), improved social functioning (1.5, CI=.4-2.5), and avoidance of EPS (1.0, CI=.3-1.8). Patients judged a daily pill superior to monthly injections (p<.01) and monthly injections superior to injections every three months (p<.01) for adherent patients and monthly injections superior to a daily pill for nonadherent patients (p=.01). Persons who self-identified as having schizophrenia judged improvement in positive symptoms as the most important treatment benefit. Hyperglycemia was identified as the most important adverse event. Patients judged oral formulations to be better than monthly injections for adherent patients and monthly injections to be a better choice for nonadherent patients.

SU-D-204-05: Fitting Four NTCP Models to Treatment Outcome Data of Salivary Glands Recorded Six Months After Radiation Therapy for Head and Neck Tumors

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

Mavroidis, P; Price, A; Kostich, M

Purpose: To estimate the radiobiological parameters of four popular NTCP models that describe the dose-response relations of salivary glands to the severity of patient reported dry mouth 6 months post chemo-radiotherapy. To identify the glands, which best correlate with the manifestation of those clinical endpoints. Finally, to evaluate the goodness-of-fit of the NTCP models. Methods: Forty-three patients were treated on a prospective multiinstitutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data ofmore » the parotid and submandibular glands (SMG) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patients data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the contralateral parotid for Grade ≥ 2 (0.762 for the LKB, RS, Logit and 0.753 for the RL). For the salivary glands the AUC values were: 0.725 for the LKB, RS, Logit and 0.721 for the RL. For the contralateral SMG the AUC values were: 0.721 for LKB, 0.714 for Logit and 0.712 for RS and RL. The Odds Ratio for the contralateral parotid was 5.8 (1.3–25.5) for all the four NTCP models for the radiobiological dose threshold of 21Gy. Conclusion: It was shown that all the examined NTCP models could fit the clinical data well with very similar accuracy. The contralateral parotid gland appears to correlated best with the clinical endpoints of severe/very severe dry mouth. An EQD2Gy dose of 21Gy appears to be a safe threshold to be used as a constraint in treatment planning.« less

Influence of Immunology Knowledge on Healthcare and Healthy Lifestyle.

PubMed

Abu Kassim, Noor Lide; Saleh Huddin, Afiqah Binti; Daoud, Jamal Ibrahim; Rahman, Mohammad Tariqur

2016-01-01

Completing a course in Immunology is expected to improve health care knowledge (HCK), which in turn is anticipated to influence a healthy lifestyle (HLS), controlled use of health care services (HCS) and an awareness of emerging health care concerns (HCC). This cross-sectional study was designed to determine whether these interrelationships are empirically supported. Participants involved in this study were government servants from two ministries in Malaysia (n = 356) and university students from a local university (n = 147). Participants were selected using the non-random purposive sampling method. Data were collected using a self-developed questionnaire, which had been validated in a pilot study involving similar subjects. The questionnaire items were analyzed using Rasch analysis, SPSS version 21 and AMOS version 22. Results have shown that participants who followed a course in Immunology (CoI) had a higher primary HCK (Mean = 0.69 logit, SD = 1.29 logits) compared with those who had not (Mean = -0.27logit, SD = 1.26 logits). Overall, there were significant correlations among the HLS, the awareness of emerging HCC, and the controlled use of HCS (p <0.001). However, no significant correlations were observed between primary HCK and the other variables. However, significant positive correlation was observed between primary HCK and controlled use of HCS for the group without CoI. Path analysis showed that the awareness of emerging HCC exerted a positive influence on controlled use of HCS (β = 0.156, p < .001) and on HLS (β = 0.224, p < .001). These findings suggest that having CoI helps increase primary HCK which influences controlled use of HCS but does not necessarily influence HLS. Hence, introducing Immunology at various levels of education and increasing the public awareness of emerging HCC might help to improve population health en masse. In addition, further investigations on the factors affecting HLS is required to provide a better understanding on the relationship between primary HCK and HLS.

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

Treesearch

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

1980-01-01

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

Topics in Bayesian Hierarchical Modeling and its Monte Carlo Computations

NASA Astrophysics Data System (ADS)

Tak, Hyung Suk

The first chapter addresses a Beta-Binomial-Logit model that is a Beta-Binomial conjugate hierarchical model with covariate information incorporated via a logistic regression. Various researchers in the literature have unknowingly used improper posterior distributions or have given incorrect statements about posterior propriety because checking posterior propriety can be challenging due to the complicated functional form of a Beta-Binomial-Logit model. We derive data-dependent necessary and sufficient conditions for posterior propriety within a class of hyper-prior distributions that encompass those used in previous studies. Frequency coverage properties of several hyper-prior distributions are also investigated to see when and whether Bayesian interval estimates of random effects meet their nominal confidence levels. The second chapter deals with a time delay estimation problem in astrophysics. When the gravitational field of an intervening galaxy between a quasar and the Earth is strong enough to split light into two or more images, the time delay is defined as the difference between their travel times. The time delay can be used to constrain cosmological parameters and can be inferred from the time series of brightness data of each image. To estimate the time delay, we construct a Gaussian hierarchical model based on a state-space representation for irregularly observed time series generated by a latent continuous-time Ornstein-Uhlenbeck process. Our Bayesian approach jointly infers model parameters via a Gibbs sampler. We also introduce a profile likelihood of the time delay as an approximation of its marginal posterior distribution. The last chapter specifies a repelling-attracting Metropolis algorithm, a new Markov chain Monte Carlo method to explore multi-modal distributions in a simple and fast manner. This algorithm is essentially a Metropolis-Hastings algorithm with a proposal that consists of a downhill move in density that aims to make local modes repelling, followed by an uphill move in density that aims to make local modes attracting. The downhill move is achieved via a reciprocal Metropolis ratio so that the algorithm prefers downward movement. The uphill move does the opposite using the standard Metropolis ratio which prefers upward movement. This down-up movement in density increases the probability of a proposed move to a different mode.

Logit Models for the Analysis of Two-Way Categorical Data

ERIC Educational Resources Information Center

Draxler, Clemens

2011-01-01

This article discusses the application of logit models for the analyses of 2-way categorical observations. The models described are generalized linear models using the logit link function. One of the models is the Rasch model (Rasch, 1960). The objective is to test hypotheses of marginal and conditional independence between explanatory quantities…

Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables

ERIC Educational Resources Information Center

Fullerton, Andrew S.; Xu, Jun

2018-01-01

Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which…

Minority Households' Willingness-to-Pay for Public and Private Wildfire Risk Reduction in Florida

NASA Astrophysics Data System (ADS)

Gonzalez-Caban, A.; Sanchez, J. J.

2017-12-01

The purpose of this work is to estimate willingness-to-pay (WTP) for minority (African-American and Hispanic) homeowners in Florida for private and public wildfire risk reduction programs and also to test for differences in response between the two groups. A random parameter logit and latent class models allowed us to determine if there is difference in wildfire mitigation program preferences, whether WTP is higher for public or private actions for wildfire risk reduction, and whether households with personal experience and who perceive that they live in higher-risk areas have significantly higher WTP. We also compare FL minority homeowners' WTP values with Florida original homeowners' estimates. Results suggest that FL minority homeowners are willing to invest in public programs, with African-Americans WTP values at a higher rate than Hispanics. In addition, the highest priority for cost sharing funds would go to low-income homeowners, especially to cost-share private actions on their own land. These results may help fire managers optimize allocation of scarce cost-sharing funds for public versus private actions.

Analyzing the severity of accidents on the German Autobahn.

PubMed

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.

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

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2009-07-01

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

Gaussian Process Regression Model in Spatial Logistic Regression

NASA Astrophysics Data System (ADS)

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.

An Empirical Bayes Approach to Spatial Analysis

NASA Technical Reports Server (NTRS)

Morris, C. N.; Kostal, H.

1983-01-01

Multi-channel LANDSAT data are collected in several passes over agricultural areas during the growing season. How empirical Bayes modeling can be used to develop crop identification and discrimination techniques that account for spatial correlation in such data is considered. The approach models the unobservable parameters and the data separately, hoping to take advantage of the fact that the bulk of spatial correlation lies in the parameter process. The problem is then framed in terms of estimating posterior probabilities of crop types for each spatial area. Some empirical Bayes spatial estimation methods are used to estimate the logits of these probabilities.

Estimating child mortality and modelling its age pattern for India.

PubMed

Roy, S G

1989-06-01

"Using data [for India] on proportions of children dead...estimates of infant and child mortality are...obtained by Sullivan and Trussell modifications of [the] Brass basic method. The estimate of child survivorship function derived after logit smoothing appears to be more reliable than that obtained by the Census Actuary. The age pattern of childhood mortality is suitably modelled by [a] Weibull function defining the probability of surviving from birth to a specified age and involving two parameters of level and shape. A recently developed linearization procedure based on [a] graphical approach is adopted for estimating the parameters of the function." excerpt

Genetic parameters for lamb birth weight, survival and death risk traits.

PubMed

Everett-Hincks, J M; Mathias-Davis, H C; Greer, G J; Auvray, B A; Dodds, K G

2014-07-01

This paper reports genetic parameters for lamb survival and mortality traits on sheep farms in New Zealand. Lamb survival and mortality records were obtained from 38 flocks (103,357 lambs) from 5 yr of lambing data (2007 to 2011) and include many breeds and their crosses (predominantly Romney, Perendale, Coopworth, and Texel). A number of models were tested, all including environmental weather effects and investigating the random environmental effect of dam and litter (dam/year) as well as logit transformation for binary traits. Total heritability (direct + maternal) estimates were low for lamb viability at birth (0.01), lamb death risk to dystocia (0.01), and lamb death risk to starvation exposure (0.01) from birth to 3 d of age in an analysis accounting for direct and maternal genetic effects and the maternal environmental effects. Lamb survival heritabilities reported are very low (total heritabilities range from 0.02 to 0.06). The total heritabilities for the lamb death risk traits are lower than reported estimates of survival to 3 d of age or to weaning suggesting selection for the postmortem traits are not warranted at this time within these flocks. The total heritability for lamb birth weight was moderate (0.38) and the genetic correlations with the lamb death risk traits suggested that directional selection on lamb birth weight would have an effect on survival, although it is likely to have a nonlinear effect and therefore an optimum birth weight at which survival is maximized. This study has also shown that the total heritabilities may be overestimated when not accounting for maternal genetic and environment effects and in particular not accounting for the random environmental effect of litter (dam/year).

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

PubMed

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

2014-07-01

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

What influences participation in genetic carrier testing? Results from a discrete choice experiment.

PubMed

Hall, Jane; Fiebig, Denzil G; King, Madeleine T; Hossain, Ishrat; Louviere, Jordan J

2006-05-01

This study explores factors that influence participation in genetic testing programs and the acceptance of multiple tests. Tay Sachs and cystic fibrosis are both genetically determined recessive disorders with differing severity, treatment availability, and prevalence in different population groups. We used a discrete choice experiment with a general community and an Ashkenazi Jewish sample; data were analysed using multinomial logit with random coefficients. Although Jewish respondents were more likely to be tested, both groups seem to be making very similar tradeoffs across attributes when they make genetic testing choices.

A Comparison between Discrimination Indices and Item-Response Theory Using the Rasch Model in a Clinical Course Written Examination of a Medical School.

PubMed

Park, Jong Cook; Kim, Kwang Sig

2012-03-01

The reliability of test is determined by each items' characteristics. Item analysis is achieved by classical test theory and item response theory. The purpose of the study was to compare the discrimination indices with item response theory using the Rasch model. Thirty-one 4th-year medical school students participated in the clinical course written examination, which included 22 A-type items and 3 R-type items. Point biserial correlation coefficient (C(pbs)) was compared to method of extreme group (D), biserial correlation coefficient (C(bs)), item-total correlation coefficient (C(it)), and corrected item-total correlation coeffcient (C(cit)). Rasch model was applied to estimate item difficulty and examinee's ability and to calculate item fit statistics using joint maximum likelihood. Explanatory power (r2) of Cpbs is decreased in the following order: C(cit) (1.00), C(it) (0.99), C(bs) (0.94), and D (0.45). The ranges of difficulty logit and standard error and ability logit and standard error were -0.82 to 0.80 and 0.37 to 0.76, -3.69 to 3.19 and 0.45 to 1.03, respectively. Item 9 and 23 have outfit > or =1.3. Student 1, 5, 7, 18, 26, 30, and 32 have fit > or =1.3. C(pbs), C(cit), and C(it) are good discrimination parameters. Rasch model can estimate item difficulty parameter and examinee's ability parameter with standard error. The fit statistics can identify bad items and unpredictable examinee's responses.

A general description of additive and nonadditive elements of sperm competitiveness and their relation to male fertilization success.

PubMed

Engqvist, Leif

2013-05-01

A complete understanding of male reproductive success, and thus sexual selection, often requires an insight into male success in sperm competition. Genuine conclusions on male sperm competitiveness can only be made in real competitive situations. However, statistical analyses of sperm competitiveness from fertilization success data have been shown to be problematic. Here, I first outline a comprehensive general description of the different additive and nonadditive elements relevant for the outcome of sperm competition staged between two males. Based on this description, I will highlight two main problems that are frequently encountered in experiments aiming at estimating sperm competitiveness. First, I focus on potential problems when using standardized competitors versus random mating trials, because trials with standardized competitors do not allow generalization if male-male interactions are important. Second, I illustrate the necessity to analyze data on the logit scale rather than on raw proportions, because only the logit scale allows a clean separation of additive and nonadditive effects (i.e., male × male and female × male interactions). © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution.

Applications manual for logit modes of express bus-fringe parking choices.

DOT National Transportation Integrated Search

1976-01-01

Manual computations and computerized applications of logit models are described. The models demonstrated reflect travel behavior concerning express bus-fringe parking transit. The specific travel issues addressed include the basic automobile vs. expr...

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

PubMed

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.

Assessing Success on the Uniform CPA Exam: A Logit Approach.

ERIC Educational Resources Information Center

Brahmasrene, Tantatape; Whitten, Donna

2001-01-01

A logit model was used to test the likelihood of success of 231 candidates on the Uniform Certified Public Accountants Examination. Significant determinants of success included undergraduate grade point average, age, private accounting experience, and gender. (SK)

What is clearance worth? Patients' stated risk tolerance for psoriasis treatments.

PubMed

Fairchild, Angelyn O; Reed, Shelby D; Johnson, F Reed; Anglin, Greg; Wolka, Anne M; Noel, Rebecca A

2017-12-01

The purpose of this study was to provide quantitative evidence of patients' tolerance for therapeutic risks associated with psoriasis treatments that could offer psoriasis improvements beyond the PASI 75 benchmark. We used a discrete-choice experiment in which respondents chose between competing psoriasis treatments characterized by benefits (i.e. reduced plaque severity, reduced plaque area), risks (i.e. 10-year risk of tuberculosis, 10-year risk of death from infection), and treatment regimen. We analyzed choice data using random-parameters logit models for psoriasis affecting the body, face, or hands. Of 927 eligible members of the National Psoriasis Foundation who completed the survey, 28% were unwilling to accept any greater risk of treatment-related infection mortality. Among the remaining 72%, respondents were willing to accept higher risks of infection-related mortality associated with treatment to completely remove plaques covering only 1% of the body, compared to reducing lesions from 10 to 1% of the affected area. This finding was more pronounced for lesions on the face. Most patients placed greater value on eliminating even very small plaques compared to avoiding treatment-related risks. The perceived importance of complete versus near-complete clearance was stronger than previously documented.

User fees across ecosystem boundaries: Are SCUBA divers willing to pay for terrestrial biodiversity conservation?

PubMed

Roberts, Michaela; Hanley, Nick; Cresswell, Will

2017-09-15

While ecological links between ecosystems have been long recognised, management rarely crosses ecosystem boundaries. Coral reefs are susceptible to damage through terrestrial run-off, and failing to account for this within management threatens reef protection. In order to quantify the extent to that coral reef users are willing to support management actions to improve ecosystem quality, we conducted a choice experiment with SCUBA divers on the island of Bonaire, Caribbean Netherlands. Specifically, we estimated their willingness to pay to reduce terrestrial overgrazing as a means to improve reef health. Willingness to pay was estimated using the multinomial, random parameter and latent class logit models. Willingness to pay for improvements to reef quality was positive for the majority of respondents. Estimates from the latent class model determined willingness to pay for reef improvements of between $31.17 - $413.18/year, dependent on class membership. This represents a significant source of funding for terrestrial conservation, and illustrates the potential for user fees to be applied across ecosystem boundaries. We argue that such across-ecosystem-boundary funding mechanisms are an important avenue for future investigation in many connected systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

An introduction to multidimensional measurement using Rasch models.

PubMed

Briggs, Derek C; Wilson, Mark

2003-01-01

The act of constructing a measure requires a number of important assumptions. Principle among these assumptions is that the construct is unidimensional. In practice there are many instances when the assumption of unidimensionality does not hold, and where the application of a multidimensional measurement model is both technically appropriate and substantively advantageous. In this paper we illustrate the usefulness of a multidimensional approach to measurement with the Multidimensional Random Coefficient Multinomial Logit (MRCML) model, an extension of the unidimensional Rasch model. An empirical example is taken from a collection of embedded assessments administered to 541 students enrolled in middle school science classes with a hands-on science curriculum. Student achievement on these assessments are multidimensional in nature, but can also be treated as consecutive unidimensional estimates, or as is most common, as a composite unidimensional estimate. Structural parameters are estimated for each model using ConQuest, and model fit is compared. Student achievement in science is also compared across models. The multidimensional approach has the best fit to the data, and provides more reliable estimates of student achievement than under the consecutive unidimensional approach. Finally, at an interpretational level, the multidimensional approach may well provide richer information to the classroom teacher about the nature of student achievement.

The effect of Saqez (Pistacia atlantica) ointment on the treatment of nipple fissure and nipple pain in breastfeeding women

PubMed Central

As’adi, Nayereh; Kariman, Nourossadat; Mojab, Faraz; Pourhoseingholi, Mohammad Amin

2017-01-01

Background Nipple fissure is a common problem in breastfeeding women, and the main reason for the early discontinuation of breastfeeding. Objective To determine the effect of Saqez (Pistacia atlantica) ointment on the treatment of nipple fissure and nipple pain in breastfeeding women. Methods This randomized clinical trial was conducted on 100 subjects admitted to the health centers in Tehran, Iran from mid-July to mid-November 2015. The subjects were randomly divided into two equal groups of 50 for the Saqez ointment group and the control group. The subjects were divided into the two groups through random allocation in Excel. The subjects were monitored on day 1, 3 and 7. Data were analyzed in SAS using the Cumulative Logit model and in SPSS-21 using Mann-Whitney, independent-samples t-test, the Chi square and Fisher’s exact test. Results No significant differences were observed between the two groups in terms of their demographic and fertility characteristics. The Cumulative Logit model showed that high levels of nipple fissure and pain were significantly less frequent in the Saqez group compared to the control group (p<0.001). There was about 83% reduction in the severity of fissure and 85 %in the severity of pain in the Saqez group compared to the control group (p<0.001). Conclusion Saqez ointment is more effective in the treatment of nipple fissures and pain than breast milk. As this study was done for the first time, judgment about the conclusive efficacy of Saqez ointment on the nipple fissure, needs further similar studies. Trial registration The trial was registered at the Iranian Registry of Clinical Trials (http://www.irct.ir) with the Irct ID: IRCT2015080723535N1. Funding The authors received no financial support for the research, authorship, and/or publication of this article. PMID:28979728

A comparison of two experimental design approaches in applying conjoint analysis in patient-centered outcomes research: a randomized trial.

PubMed

Kinter, Elizabeth T; Prior, Thomas J; Carswell, Christopher I; Bridges, John F P

2012-01-01

While the application of conjoint analysis and discrete-choice experiments in health are now widely accepted, a healthy debate exists around competing approaches to experimental design. There remains, however, a paucity of experimental evidence comparing competing design approaches and their impact on the application of these methods in patient-centered outcomes research. Our objectives were to directly compare the choice-model parameters and predictions of an orthogonal and a D-efficient experimental design using a randomized trial (i.e., an experiment on experiments) within an application of conjoint analysis studying patient-centered outcomes among outpatients diagnosed with schizophrenia in Germany. Outpatients diagnosed with schizophrenia were surveyed and randomized to receive choice tasks developed using either an orthogonal or a D-efficient experimental design. The choice tasks elicited judgments from the respondents as to which of two patient profiles (varying across seven outcomes and process attributes) was preferable from their own perspective. The results from the two survey designs were analyzed using the multinomial logit model, and the resulting parameter estimates and their robust standard errors were compared across the two arms of the study (i.e., the orthogonal and D-efficient designs). The predictive performances of the two resulting models were also compared by computing their percentage of survey responses classified correctly, and the potential for variation in scale between the two designs of the experiments was tested statistically and explored graphically. The results of the two models were statistically identical. No difference was found using an overall chi-squared test of equality for the seven parameters (p = 0.69) or via uncorrected pairwise comparisons of the parameter estimates (p-values ranged from 0.30 to 0.98). The D-efficient design resulted in directionally smaller standard errors for six of the seven parameters, of which only two were statistically significant, and no differences were found in the observed D-efficiencies of their standard errors (p = 0.62). The D-efficient design resulted in poorer predictive performance, but this was not significant (p = 0.73); there was some evidence that the parameters of the D-efficient design were biased marginally towards the null. While no statistical difference in scale was detected between the two designs (p = 0.74), the D-efficient design had a higher relative scale (1.06). This could be observed when the parameters were explored graphically, as the D-efficient parameters were lower. Our results indicate that orthogonal and D-efficient experimental designs have produced results that are statistically equivalent. This said, we have identified several qualitative findings that speak to the potential differences in these results that may have been statistically identified in a larger sample. While more comparative studies focused on the statistical efficiency of competing design strategies are needed, a more pressing research problem is to document the impact the experimental design has on respondent efficiency.

Adjunctive Self-hypnotic Relaxation for Outpatient Medical Procedures: A Prospective Randomized Trial with Women Undergoing Large Core Breast Biopsy

PubMed Central

Lang, Elvira V.; Berbaum, Kevin S.; Faintuch, Salomao; Hatsiopoulou, Olga; Halsey, Noami; Li, Xinyu; Berbaum, Michael L.; Laser, Eleanor; Baum, Janet

2008-01-01

Medical procedures in outpatient settings have limited options of managing pain and anxiety pharmacologically. We therefore assessed whether this can be achieved by adjunct self-hypnotic relaxation in a common and particularly anxiety provoking procedure. 236 women referred for large core needle breast biopsy to an urban tertiary university-affiliated medical center were prospectively randomized to receive standard care (n=76), structured empathic attention (n= 82), or self-hypnotic relaxation (n=78) during their procedures. Patients’ self-ratings at 10 minute-intervals of pain and anxiety on 0–10 verbal analog scales with 0=no pain/anxiety at all, 10=worst pain/anxiety possible, were compared in an ordinal logistic regression model. Women’s anxiety increased significantly in the standard group (logit slope = 0.18, p < 0.001), did not change in the empathy group (slope = −0.04, p = 0.45), and decreased significantly in the hypnosis group (slope = −0.27, p < 0.001). Pain increased significantly in all three groups (logit slopes: standard care = 0.53, empathy = 0.37, hypnosis = 0.34; all p < 0.001) though less steeply with hypnosis and empathy than standard care (p = 0.024 and p = 0.018 respectively). Room time and cost were not significantly different in an univariate ANOVA despite hypnosis and empathy requiring an additional professional: 46 minutes/$161 for standard care, 43 minutes/$163 for empathy, and 39 minutes/$152 for hypnosis. We conclude that, while both structured empathy and hypnosis decrease procedural pain and anxiety, hypnosis provides more powerful anxiety relief without undue cost and thus appears attractive for outpatient pain management. PMID:16959427

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Nested Logit Models for Multiple-Choice Item Response Data

ERIC Educational Resources Information Center

Suh, Youngsuk; Bolt, Daniel M.

2010-01-01

Nested logit item response models for multiple-choice data are presented. Relative to previous models, the new models are suggested to provide a better approximation to multiple-choice items where the application of a solution strategy precedes consideration of response options. In practice, the models also accommodate collapsibility across all…

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

ERIC Educational Resources Information Center

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…

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

Low Vision Rehabilitation for Adult African Americans in Two Settings.

PubMed

Draper, Erin M; Feng, Rui; Appel, Sarah D; Graboyes, Marcy; Engle, Erin; Ciner, Elise B; Ellenberg, Jonas H; Stambolian, Dwight

2016-07-01

The Vision Rehabilitation for African Americans with Central Vision Impairment (VISRAC) study is a demonstration project evaluating how modifications in vision rehabilitation can improve the use of functional vision. Fifty-five African Americans 40 years of age and older with central vision impairment were randomly assigned to receive either clinic-based (CB) or home-based (HB) low vision rehabilitation services. Forty-eight subjects completed the study. The primary outcome was the change in functional vision in activities of daily living, as assessed with the Veteran's Administration Low-Vision Visual Function Questionnaire (VFQ-48). This included scores for overall visual ability and visual ability domains (reading, mobility, visual information processing, and visual motor skills). Each score was normalized into logit estimates by Rasch analysis. Linear regression models were used to compare the difference in the total score and each domain score between the two intervention groups. The significance level for each comparison was set at 0.05. Both CB and HB groups showed significant improvement in overall visual ability at the final visit compared with baseline. The CB group showed greater improvement than the HB group (mean of 1.28 vs. 0.87 logits change), though the group difference is not significant (p = 0.057). The CB group visual motor skills score showed significant improvement over the HB group score (mean of 3.30 vs. 1.34 logits change, p = 0.044). The differences in improvement of the reading and visual information processing scores were not significant (p = 0.054 and p = 0.509) between groups. Neither group had significant improvement in the mobility score, which was not part of the rehabilitation program. Vision rehabilitation is effective for this study population regardless of location. Possible reasons why the CB group performed better than the HB group include a number of psychosocial factors as well as the more standardized distraction-free work environment within the clinic setting.

Social dilemmas in multistrategy evolutionary potential games

NASA Astrophysics Data System (ADS)

Szabó, György; Bunth, Gergely

2018-01-01

The nature of social dilemmas is studied in n -strategy evolutionary potential games on a square lattice with nearest-neighbor interactions and the logit rule. For symmetric games with symmetric payoff matrices there are no dilemmas because of the coincidence of individual and common interests. The dilemmas are caused by the antisymmetric parts of the self- and cross-dependent payoff components if it modifies the preferred Nash equilibrium. The contentment of players and the emergence of dilemmas in the preferred Nash equilibria are illustrated on some two-dimensional cross sections of the parameter space.

Decennial Life Tables for the White Population of the United States, 1790-1900.

PubMed

Hacker, J David

2010-04-01

This article constructs new life tables for the white population of the United States in each decade between 1790 and 1900. Drawing from several recent studies, it suggests best estimates of life expectancy at age 20 for each decade. These estimates are fitted to new standards derived from the 1900-02 rural and 1900-02 overall DRA life tables using a two-parameter logit model with fixed slope. The resulting decennial life tables more accurately represent sex-and age-specific mortality rates while capturing known mortality trends.

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Investigating risk factors of traffic casualties at private highway-railroad grade crossings in the United States.

PubMed

Haleem, Kirolos

2016-10-01

Private highway-railroad grade crossings (HRGCs) are intersections of highways and railroads on roadways that are not maintained by a public authority. Since no public authority maintains private HRGCs, fatal and injury crashes at these locations are of concern. However, no study has been conducted at private HRGCs to identify the safety issues that might exist and how to alleviate them. This study identifies the significant predictors of traffic casualties (including both injuries and fatalities) at private HRGCs in the U.S. using six years of nationwide crashes from 2009 to 2014. Two levels of injury severity were considered, injury (including fatalities and injuries) and no injury. The study investigates multiple predictors, e.g., temporal crash characteristics, geometry, railroad, traffic, vehicle, and environment. The study applies both the mixed logit and binary logit models. The mixed logit model was found to outperform the binary logit model. The mixed logit model revealed that drivers who did not stop, railroad equipment that struck highway users, higher train speeds, non-presence of advance warning signs, concrete road surface type, and cloudy weather were associated with an increase in injuries and fatalities. For example, a one-mile-per-hour higher train speed increases the probability of fatality by 22%. On the contrary, male drivers, PM peak periods, and presence of warning devices at both approaches were associated with a fatality reduction. Potential strategies are recommended to alleviate injuries and fatalities at private HRGCs. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Odds Ratio Approach for Detecting DDF under the Nested Logit Modeling Framework

ERIC Educational Resources Information Center

Terzi, Ragip; Suh, Youngsuk

2015-01-01

An odds ratio approach (ORA) under the framework of a nested logit model was proposed for evaluating differential distractor functioning (DDF) in multiple-choice items and was compared with an existing ORA developed under the nominal response model. The performances of the two ORAs for detecting DDF were investigated through an extensive…

Identifying Measurement Disturbance Effects Using Rasch Item Fit Statistics and the Logit Residual Index.

ERIC Educational Resources Information Center

Mount, Robert E.; Schumacker, Randall E.

1998-01-01

A Monte Carlo study was conducted using simulated dichotomous data to determine the effects of guessing on Rasch item fit statistics and the Logit Residual Index. Results indicate that no significant differences were found between the mean Rasch item fit statistics for each distribution type as the probability of guessing the correct answer…

The Application of the Cumulative Logistic Regression Model to Automated Essay Scoring

ERIC Educational Resources Information Center

Haberman, Shelby J.; Sinharay, Sandip

2010-01-01

Most automated essay scoring programs use a linear regression model to predict an essay score from several essay features. This article applied a cumulative logit model instead of the linear regression model to automated essay scoring. Comparison of the performances of the linear regression model and the cumulative logit model was performed on a…

Assessing community values for reducing agricultural emissions to improve water quality and protect coral health in the Great Barrier Reef

NASA Astrophysics Data System (ADS)

Rolfe, John; Windle, Jill

2011-12-01

Policymakers wanting to increase protection of the Great Barrier Reef from pollutants generated by agriculture need to identify when measures to improve water quality generate benefits to society that outweigh the costs involved. The research reported in this paper makes a contribution in several ways. First, it uses the improved science understanding about the links between management changes and reef health to bring together the analysis of costs and benefits of marginal changes, helping to demonstrate the appropriate way of addressing policy questions relating to reef protection. Second, it uses the scientific relationships to frame a choice experiment to value the benefits of improved reef health, with the results of mixed logit (random parameter) models linking improvements explicitly to changes in "water quality units." Third, the research demonstrates how protection values are consistent across a broader population, with some limited evidence of distance effects. Fourth, the information on marginal costs and benefits that are reported provide policymakers with information to help improve management decisions. The results indicate that while there is potential for water quality improvements to generate net benefits, high cost water quality improvements are generally uneconomic. A major policy implication is that cost thresholds for key pollutants should be set to avoid more expensive water quality proposals being selected.

Incentives for Blood Donation: A Discrete Choice Experiment to Analyze Extrinsic Motivation.

PubMed

Sadler, Andrew; Shi, Ling; Bethge, Susanne; Mühlbacher, Axel

2018-04-01

Background: Demographic trends affect size and age structure of populations. One of the consequences will be an increasing need for blood products to treat age-related diseases. Donation services rely on voluntariness and charitable motivation. It might be questioned whether there will be sufficient blood supply with voluntary donation. The present study focused on elicitation of preferences for incentives and aimed to contribute to the discussion on how to increase donation rates. Methods: A self-administered discrete choice experiment (DCE) was applied. Respondents were repeatedly asked to choose between hypothetical blood donation centers. In case of reluctance to receiving incentives a none-option was included. Random parameter logit (RPL) and latent class models (LCM) were used for analysis. Results: The study sample included 416 college students from the US and Germany. Choice decisions were significantly influenced by the characteristics of the donation center in the DCE. Incentives most preferred were monetary compensation, paid leave, and blood screening test. LCM identified subgroups with preference heterogeneity. Small subgroups indicated moderate to strong aversion to incentives. Conclusion: The majority of the sample positively responded to incentives and indicated a willingness to accept incentives. In face of future challenges, the judicious use and appropriate utilization of incentives might be an option to motivate potential donors and should be open to discussion.

Occupational Choice: A Conditional Logit Model with Special Reference to Wage Subsidies and Occupational Choice. Final Report.

ERIC Educational Resources Information Center

Boskin, Michael J.

A model of occupational choice based on the theory of human capital is developed and estimated by conditional logit analysis. The empirical results estimated the probability of individuals with certain characteristics (such as race, sex, age, and education) entering each of 11 occupational groups. The results indicate that individuals tend to…

Stochastic modeling of consumer preferences for health care institutions.

PubMed

Malhotra, N K

1983-01-01

This paper proposes a stochastic procedure for modeling consumer preferences via LOGIT analysis. First, a simple, non-technical exposition of the use of a stochastic approach in health care marketing is presented. Second, a study illustrating the application of the LOGIT model in assessing consumer preferences for hospitals is given. The paper concludes with several implications of the proposed approach.

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

ERIC Educational Resources Information Center

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

2016-01-01

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

Decennial Life Tables for the White Population of the United States, 1790–19001

PubMed Central

Hacker, J. David

2010-01-01

This article constructs new life tables for the white population of the United States in each decade between 1790 and 1900. Drawing from several recent studies, it suggests best estimates of life expectancy at age 20 for each decade. These estimates are fitted to new standards derived from the 1900–02 rural and 1900–02 overall DRA life tables using a two-parameter logit model with fixed slope. The resulting decennial life tables more accurately represent sex-and age-specific mortality rates while capturing known mortality trends. PMID:20563225

Estimation of social value of statistical life using willingness-to-pay method in Nanjing, China.

PubMed

Yang, Zhao; Liu, Pan; Xu, Xin

2016-10-01

Rational decision making regarding the safety related investment programs greatly depends on the economic valuation of traffic crashes. The primary objective of this study was to estimate the social value of statistical life in the city of Nanjing in China. A stated preference survey was conducted to investigate travelers' willingness to pay for traffic risk reduction. Face-to-face interviews were conducted at stations, shopping centers, schools, and parks in different districts in the urban area of Nanjing. The respondents were categorized into two groups, including motorists and non-motorists. Both the binary logit model and mixed logit model were developed for the two groups of people. The results revealed that the mixed logit model is superior to the fixed coefficient binary logit model. The factors that significantly affect people's willingness to pay for risk reduction include income, education, gender, age, drive age (for motorists), occupation, whether the charged fees were used to improve private vehicle equipment (for motorists), reduction in fatality rate, and change in travel cost. The Monte Carlo simulation method was used to generate the distribution of value of statistical life (VSL). Based on the mixed logit model, the VSL had a mean value of 3,729,493 RMB ($586,610) with a standard deviation of 2,181,592 RMB ($343,142) for motorists; and a mean of 3,281,283 RMB ($505,318) with a standard deviation of 2,376,975 RMB ($366,054) for non-motorists. Using the tax system to illustrate the contribution of different income groups to social funds, the social value of statistical life was estimated. The average social value of statistical life was found to be 7,184,406 RMB ($1,130,032). Copyright © 2016 Elsevier Ltd. All rights reserved.

Bayesian Inference for the Stereotype Regression Model: Application to a Case-control Study of Prostate Cancer

PubMed Central

Ahn, Jaeil; Mukherjee, Bhramar; Banerjee, Mousumi; Cooney, Kathleen A.

2011-01-01

Summary The stereotype regression model for categorical outcomes, proposed by Anderson (1984) is nested between the baseline category logits and adjacent category logits model with proportional odds structure. The stereotype model is more parsimonious than the ordinary baseline-category (or multinomial logistic) model due to a product representation of the log odds-ratios in terms of a common parameter corresponding to each predictor and category specific scores. The model could be used for both ordered and unordered outcomes. For ordered outcomes, the stereotype model allows more flexibility than the popular proportional odds model in capturing highly subjective ordinal scaling which does not result from categorization of a single latent variable, but are inherently multidimensional in nature. As pointed out by Greenland (1994), an additional advantage of the stereotype model is that it provides unbiased and valid inference under outcome-stratified sampling as in case-control studies. In addition, for matched case-control studies, the stereotype model is amenable to classical conditional likelihood principle, whereas there is no reduction due to sufficiency under the proportional odds model. In spite of these attractive features, the model has been applied less, as there are issues with maximum likelihood estimation and likelihood based testing approaches due to non-linearity and lack of identifiability of the parameters. We present comprehensive Bayesian inference and model comparison procedure for this class of models as an alternative to the classical frequentist approach. We illustrate our methodology by analyzing data from The Flint Men’s Health Study, a case-control study of prostate cancer in African-American men aged 40 to 79 years. We use clinical staging of prostate cancer in terms of Tumors, Nodes and Metastatsis (TNM) as the categorical response of interest. PMID:19731262

Patient choice modelling: how do patients choose their hospitals?

PubMed

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

2018-06-01

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

Using a metal detector to determine lead sinker abundance in waterbird habitat

USGS Publications Warehouse

Duerr, A.E.; DeStefano, S.

2000-01-01

Waterbirds have died of lead poisoning from ingesting lead fishing sinkers in the United States and Europe. Estimating abundance and distribution of sinkers in the environment will help researchers to understand the potential effects of lead poisoning from sinker ingestion. We used a metal detector to test how environmental conditions and sinker characteristics affected detection of sinkers. Odds of detecting a lead sinker depended on the interaction of sinker mass and depth where it was buried (P=0.002). The odds of detecting a sinker increased with mass and decreased with depth buried. Lead split-shot sinkers were less detectable than tin, brass, and stainless steel sinkers. Detecting lead sinkers was not influenced by sinker shape, substrate type, or whether we searched underwater or on land. We developed a model to determine the proportion of sinkers detected when this detector is used to search for sinkers, so sinker abundance can be estimated. The log odds (Logit) of detecting a lead sinker with mass M g buried D cm below the surface was Logit Y= -1.63 + 4.20 M - 0.45 D - 0.27 MD + 0.0002 D2. The probability of detecting a lead sinker was e(Logit Y)/(1 + e(Logit Y)). At the surface, 90% of sinkers with mass 0.9 g will be detected.

Interferon-based anti-viral therapy for hepatitis C virus infection after renal transplantation: an updated meta-analysis.

PubMed

Wei, Fang; Liu, Junying; Liu, Fen; Hu, Huaidong; Ren, Hong; Hu, Peng

2014-01-01

Hepatitis C virus (HCV) infection is highly prevalent in renal transplant (RT) recipients. Currently, interferon-based (IFN-based) antiviral therapies are the standard approach to control HCV infection. In a post-transplantation setting, however, IFN-based therapies appear to have limited efficacy and their use remains controversial. The present study aimed to evaluate the efficacy and safety of IFN-based therapies for HCV infection post RT. We searched Pubmed, Embase, Web of Knowledge, and The Cochrane Library (1997-2013) for clinical trials in which transplant patients were given Interferon (IFN), pegylated interferon (PEG), interferon plus ribavirin (IFN-RIB), or pegylated interferon plus ribavirin (PEG-RIB). The Sustained Virological Response (SVR) and/or drop-out rates were the primary outcomes. Summary estimates were calculated using the random-effects model of DerSimonian and Laird, with heterogeneity and sensitivity analysis. We identified 12 clinical trials (140 patients in total). The summary estimate for SVR rate, drop-out rate and graft rejection rate was 26.6% (95%CI, 15.0-38.1%), 21.1% (95% CI, 10.9-31.2%) and 4% (95%CI: 0.8%-7.1%), respectively. The overall SVR rate in PEG-based and standard IFN-based therapy was 40.6% (24/59) and 20.9% (17/81), respectively. The most frequent side-effect requiring discontinuation of treatment was graft dysfunction (14 cases, 45.1%). Meta-regression analysis showed the covariates included contribute to the heterogeneity in the SVR logit rate, but not in the drop-out logit rate. The sensitivity analyses by the random model yielded very similar results to the fixed-effects model. IFN-based therapy for HCV infection post RT has poor efficacy and limited safety. PEG-based therapy is a more effective approach for treating HCV infection post-RT than standard IFN-based therapy. Future research is required to develop novel strategies to improve therapeutic efficacy and tolerability, and reduce the liver-related morbidity and mortality in this important patient population.

Handling preference heterogeneity for river services' adaptation to climate change.

PubMed

Andreopoulos, Dimitrios; Damigos, Dimitrios; Comiti, Francesco; Fischer, Christian

2015-09-01

Climate projection models for the Southern Mediterranean basin indicate a strong drought trend. This pattern is anticipated to affect a range of services derived from river ecosystems and consecutively deteriorate the sectoral outputs and household welfare. This paper aims to evaluate local residents' adaptation preferences for the Piave River basin in Italy. A Discrete Choice Experiment accounting for adaptation scenarios of the Piave River services was conducted and the collected data were econometrically analyzed using Random Parameters Logit, Latent Class and Covariance Heterogeneity models. In terms of policy-relevant outcomes, the analysis indicates that respondents are willing to pay for adaptation plans. This attitude is reflected on the compensating surplus to sustain the current state of the Piave, which corresponds to a monthly contribution of 80€ per household. From an econometric point of view, the results show that it is not sufficient to take solely into account general heterogeneity, provided that distinct treatment of the heterogeneity produces rather different welfare estimates. This implies that analysts should examine a set of criteria when deciding on how to better approach heterogeneity for each empirical data set. Overall, non-market values of environmental services should be considered when formulating cost-effective adaptation measures for river systems undergoing climate change effects and appropriate heterogeneity approximation could render these values unbiased and accurate. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factors that influence beverage choices at meal times. An application of the food choice kaleidoscope framework.

PubMed

Mueller Loose, S; Jaeger, S R

2012-12-01

Beverages are consumed at almost every meal occasion, but knowledge about the factors that influence beverage choice is less than for food choice. The aim of this research was to characterize and quantify factors that influence beverage choices at meal times. Insights into what beverages are chosen by whom, when and where can be helpful for manufacturers, dieticians/health care providers, and health policy makers. A descriptive framework - the food choice kaleidoscope (Jaeger et al., 2011) - was applied to self-reported 24h food recall data from a sample of New Zealand consumers. Participants (n=164) described 8356 meal occasions in terms of foods and beverages consumed, and the contextual characteristics of the occasion. Beverage choice was explored with random-parameter logit regressions to reveal influences linked to food items eaten, context factors and person factors. Thereby this study contributed to the food choice kaleidoscope research approach by expressing the degree of context dependency in the form of odds ratios and according significance levels. The exploration of co-occurrence of beverages with food items suggests that beverage-meal item combinations can be meal specific. Furthermore, this study integrates psychographic variables into the 'person' mirror of the food choice kaleidoscope. A measure of habit in beverage choice was obtained from the inter-participant correlation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Demand for Health Insurance by Military Retirees

DTIC Science & Technology

2015-05-01

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

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

PubMed

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.

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields.

PubMed

Jahandideh, Samad; Abdolmaleki, Parviz; Movahedi, Mohammad Mehdi

2010-02-01

Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF-MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in "not changed melatonin level" pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF-MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in finding a relationship between electromagnetic fields and different biological processes. (c) 2009 Wiley-Liss, Inc.

Plasma myelin basic protein assay using Gilford enzyme immunoassay cuvettes.

PubMed

Groome, N P

1981-10-01

The assay of myelin basic protein in body fluids has potential clinical importance as a routine indicator of demyelination. Preliminary details of a competitive enzyme immunoassay for this protein have previously been published by the author (Groome, N. P. (1980) J. Neurochem. 35, 1409-1417). The present paper now describes the adaptation of this assay for use on human plasma and various aspects of routine data processing. A commercially available cuvette system was found to have advantages over microtitre plates but required a permuted arrangement of sample replicates for consistent results. For dose interpolation, the standard curve could be fitted to a three parameter non-linear equation by regression analysis or linearised by the logit/log transformation.

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

PubMed Central

Haas-Wilson, D; Savoca, E

1990-01-01

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

A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.

PubMed

Zeng, Ziqiang; Zhu, Wenbo; Ke, Ruimin; Ash, John; Wang, Yinhai; Xu, Jiuping; Xu, Xinxin

2017-02-01

The mixed multinomial logit (MNL) approach, which can account for unobserved heterogeneity, is a promising unordered model that has been employed in analyzing the effect of factors contributing to crash severity. However, its basic assumption of using a linear function to explore the relationship between the probability of crash severity and its contributing factors can be violated in reality. This paper develops a generalized nonlinear model-based mixed MNL approach which is capable of capturing non-monotonic relationships by developing nonlinear predictors for the contributing factors in the context of unobserved heterogeneity. The crash data on seven Interstate freeways in Washington between January 2011 and December 2014 are collected to develop the nonlinear predictors in the model. Thirteen contributing factors in terms of traffic characteristics, roadway geometric characteristics, and weather conditions are identified to have significant mixed (fixed or random) effects on the crash density in three crash severity levels: fatal, injury, and property damage only. The proposed model is compared with the standard mixed MNL model. The comparison results suggest a slight superiority of the new approach in terms of model fit measured by the Akaike Information Criterion (12.06 percent decrease) and Bayesian Information Criterion (9.11 percent decrease). The predicted crash densities for all three levels of crash severities of the new approach are also closer (on average) to the observations than the ones predicted by the standard mixed MNL model. Finally, the significance and impacts of the contributing factors are analyzed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Absence of a moderating effect of parent health literacy on Early Head Start enrollment and dental use.

PubMed

Burgette, Jacqueline M; Preisser, John S; Weinberger, Morris; King, Rebecca S; Lee, Jessica Y; Rozier, R Gary

2018-04-16

To examine the moderating effect of parents' health literacy (HL) on the effectiveness of North Carolina Early Head Start (EHS) in improving children's dental use. Parents of 479 children enrolled in EHS and 699 Medicaid-matched parent-child dyads were interviewed at baseline when children were approximately 10 months old and 24 months later. We used in-person computer-assisted, structured interviews to collect information on sociodemographic characteristics, dental use, and administer the Short Assessment of Health Literacy - Spanish and English (SAHL-S&E). This quasi-experimental study tested whether the interaction effect between EHS and parents' HL was associated with dental use. Logit (any use) and marginalized zero-inflated negative binomial count models (number of dental visits) included random effects to account for clustering and controlled for baseline dental use, dental need, survey language, and a propensity score covariate. Nineteen percent of parents in EHS had low literacy compared to 12 percent of parents in the non-EHS group (P < 0.01). The interaction term between EHS and parent's HL was not significant in the adjusted logit model (ratio of aORs 0.98, 95 percent CI: 0.43-2.20) or the adjusted count model (ratio of aRRs 0.88, 95 percent CI: 0.72-1.09). Parents in EHS had a higher prevalence of low HL compared to non-EHS parents. Parents' HL did not moderate the relationship between EHS and child dental use, suggesting that EHS results in similar improvements in dental use regardless of parent's HL levels. © 2018 American Association of Public Health Dentistry.

Street choice logit model for visitors in shopping districts.

PubMed

Kawada, Ko; Yamada, Takashi; Kishimoto, Tatsuya

2014-09-01

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).

Street Choice Logit Model for Visitors in Shopping Districts

PubMed Central

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

Rigorously testing multialternative decision field theory against random utility models.

PubMed

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

2014-06-01

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

Linkage Analysis of Urine Arsenic Species Patterns in the Strong Heart Family Study

PubMed Central

Gribble, Matthew O.; Voruganti, Venkata Saroja; Cole, Shelley A.; Haack, Karin; Balakrishnan, Poojitha; Laston, Sandra L.; Tellez-Plaza, Maria; Francesconi, Kevin A.; Goessler, Walter; Umans, Jason G.; Thomas, Duncan C.; Gilliland, Frank; North, Kari E.; Franceschini, Nora; Navas-Acien, Ana

2015-01-01

Arsenic toxicokinetics are important for disease risks in exposed populations, but genetic determinants are not fully understood. We examined urine arsenic species patterns measured by HPLC-ICPMS among 2189 Strong Heart Study participants 18 years of age and older with data on ∼400 genome-wide microsatellite markers spaced ∼10 cM and arsenic speciation (683 participants from Arizona, 684 from Oklahoma, and 822 from North and South Dakota). We logit-transformed % arsenic species (% inorganic arsenic, %MMA, and %DMA) and also conducted principal component analyses of the logit % arsenic species. We used inverse-normalized residuals from multivariable-adjusted polygenic heritability analysis for multipoint variance components linkage analysis. We also examined the contribution of polymorphisms in the arsenic metabolism gene AS3MT via conditional linkage analysis. We localized a quantitative trait locus (QTL) on chromosome 10 (LOD 4.12 for %MMA, 4.65 for %DMA, and 4.84 for the first principal component of logit % arsenic species). This peak was partially but not fully explained by measured AS3MT variants. We also localized a QTL for the second principal component of logit % arsenic species on chromosome 5 (LOD 4.21) that was not evident from considering % arsenic species individually. Some other loci were suggestive or significant for 1 geographical area but not overall across all areas, indicating possible locus heterogeneity. This genome-wide linkage scan suggests genetic determinants of arsenic toxicokinetics to be identified by future fine-mapping, and illustrates the utility of principal component analysis as a novel approach that considers % arsenic species jointly. PMID:26209557

Measuring the Value of Mortality Risk Reductions in Turkey

PubMed Central

Tekeşin, Cem; Ara, Shihomi

2014-01-01

The willingness to pay (WTP) for mortality risk reduction from four causes (lung cancer, other type of cancer, respiratory disease, traffic accident) are estimated using random parameter logit model with data from choice experiment for three regions in Turkey. The value of statistical life (VSL) estimated for Afsin-Elbistan, Kutahya-Tavsanli, Ankara and the pooled case are found as 0.56, 0.35, 0.46 and 0.49 million Purchasing Power Parity (PPP) adjusted 2012 US dollars (USD). Different types of risk cause different VSL estimates and we found the lung cancer premium of 213% against traffic accident. The effects of one-year-delayed provision of risk-reduction service are the reduction of WTP by 482 TL ($318 in PPP adjusted USD) per person on average, and the disutility from status-quo (zero risk reduction) against alternative is found to be 891 TL ($589 in PPP adjusted USD) per person on average. Senior discounts of VSL are partially determined by status-quo preference and the amount of discount decreases once the status-quo bias is removed. The peak VSL is found to be for the age group 30–39 and the average VSL for the age group is 0.8 million PPP adjusted USD). Turkey’s compliance to European Union (EU) air quality standard will cause welfare gains of total 373 million PPP adjusted USD for our study areas in terms of reduced number of premature mortality. PMID:25000150

Study on Commercialization of Biogasification Systems in Ishikari Bay New Port Area - Proposal of Estimation Method of Collectable Amount of Food Waste by using Binary Logit Model -

NASA Astrophysics Data System (ADS)

Watanabe, Sho; Furuichi, Toru; Ishii, Kazuei

This study proposed an estimation method for collectable amount of food waste considering the food waste generator's cooperation ratio ant the amount of food waste generation, and clarified the factors influencing the collectable amount of food waste. In our method, the cooperation ratio was calculated by using the binary logit model which is often used for the traffic multiple choice question. In order to develop a more precise binary logit model, the factors influencing on the cooperation ratio were extracted by a questionnaire survey asking food waste generator's intention, and the preference investigation was then conducted at the second step. As a result, the collectable amount of food waste was estimated to be 72 [t/day] in the Ishikari bay new port area under a condition of current collection system by using our method. In addition, the most critical factor influencing on the collectable amount of food waste was the treatment fee for households, and was the permitted mixture degree of improper materials for retail trade and restaurant businesses

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

NASA Astrophysics Data System (ADS)

Zhu, Wei; Timmermans, Harry

2011-06-01

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

Application of rrm as behavior mode choice on modelling transportation

NASA Astrophysics Data System (ADS)

Surbakti, M. S.; Sadullah, A. F.

2018-03-01

Transportation mode selection, the first step in transportation planning process, is probably one of the most important planning elements. The development of models that can explain the preference of passengers regarding their chosen mode of public transport option will contribute to the improvement and development of existing public transport. Logit models have been widely used to determine the mode choice models in which the alternative are different transport modes. Random Regret Minimization (RRM) theory is a theory developed from the behavior to choose (choice behavior) in a state of uncertainty. During its development, the theory was used in various disciplines, such as marketing, micro economy, psychology, management, and transportation. This article aims to show the use of RRM in various modes of selection, from the results of various studies that have been conducted both in north sumatera and western Java.

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

PubMed

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.

Exclusive queueing model including the choice of service windows

NASA Astrophysics Data System (ADS)

Tanaka, Masahiro; Yanagisawa, Daichi; Nishinari, Katsuhiro

2018-01-01

In a queueing system involving multiple service windows, choice behavior is a significant concern. This paper incorporates the choice of service windows into a queueing model with a floor represented by discrete cells. We contrived a logit-based choice algorithm for agents considering the numbers of agents and the distances to all service windows. Simulations were conducted with various parameters of agent choice preference for these two elements and for different floor configurations, including the floor length and the number of service windows. We investigated the model from the viewpoint of transit times and entrance block rates. The influences of the parameters on these factors were surveyed in detail and we determined that there are optimum floor lengths that minimize the transit times. In addition, we observed that the transit times were determined almost entirely by the entrance block rates. The results of the presented model are relevant to understanding queueing systems including the choice of service windows and can be employed to optimize facility design and floor management.

A PREFERENCE-OPPORTUNITY-CHOICE FRAMEWORK WITH APPLICATIONS TO INTERGROUP FRIENDSHIP*

PubMed Central

Zeng, Zhen; Xie, Yu

2009-01-01

A longstanding objective of friendship research is to identify the effects of personal preference and structural opportunity on intergroup friendship choice. Although past studies have used various methods to separate preference from opportunity, researchers have not yet systematically compared the properties and implications of these methods. We put forward a general framework for discrete choice, where choice probability is specified as proportional to the product of preference and opportunity. To implement this framework, we propose a modification to the conditional logit model for estimating preference parameters free from the influence of opportunity structure. We then compare our approach to several alternative methods for separating preference and opportunity used in the friendship choice literature. As an empirical example, we test hypotheses of homophily and status asymmetry in friendship choice using data from the National Longitudinal Study of Adolescent Health. The example also demonstrates the approach of conducting a sensitivity analysis to examine how parameter estimates vary by specification of the opportunity structure. PMID:19569394

Psychometric Evaluation of a Cultural Competency Assessment Instrument for Health Professionals

PubMed Central

Haywood, Sonja H.; Goode, Tawara; Gao, Yong; Smith, Kristyn; Bronheim, Suzanne; Flocke, Susan A; Zyzanski, Steve

2012-01-01

Background Few valid and reliable measures exist for health care professionals interested in determining their levels of cultural and linguistic competence. Objective To evaluate the measurement properties of the Cultural Competence Health Practitioner Assessment (CCHPA-129). Methods The CCHPA-129 is a 129-item web-based instrument, developed by the National Center for Cultural Competence (NCCC). Responses on the CCHPA -129 were examined using factor analysis; Rasch modeling; and Differential Item Functioning (DIF) across race, ethnicity, gender, and profession. Subjects 2504 practitioners, including 1864 nurses (RN/LPN,/BSN); 341 clinicians (PA/NP); and 299 physicians (MD/DO), who completed the CCHPA-129 online between 2005 and 2008. Results Three factors representing domains of knowledge, adapting practice, and promoting health for culturally and linguistically diverse populations accounted for 46% of the variance. Among Knowledge factor items, 53% (23/43) fit the Rasch model, item difficulties ranged from −1.01 logits (least difficult) to +1.11 logits (most difficult), separation index (SI) 13.82, and Cronbach’s α 0.92. Forty-seven percent (21/44) Adapting Practice factor items fit the model, item difficulties −0.07 to +1.11 logits, SI 11.59, Cronbach’s α 0.88; and 58% (23/39). Promoting Health factor items fit the model, item difficulties −1.01 to +1.38 logits, SI 22.64, Cronbach’s α 0.92. Early evidence of validity was established by known groups having statistically different scores. Conclusion The 67-item CCHPA-67 is psychometrically sound. This shorted instrument can be used to establish associations between practitioners’ cultural and linguistic competence and health outcomes as well as to evaluate interventions to increase practitioners’ cultural and linguistic competence. PMID:22437625

Item Banking Enables Stand-Alone Measurement of Driving Ability.

PubMed

Khadka, Jyoti; Fenwick, Eva K; Lamoureux, Ecosse L; Pesudovs, Konrad

2016-12-01

To explore whether large item sets, as used in item banking, enable important latent traits, such as driving, to form stand-alone measures. The 88-item activity limitation (AL) domain of the glaucoma module of the Eye-tem Bank was interviewer-administered to patients with glaucoma. Rasch analysis was used to calibrate all items in AL domain on the same interval-level scale and test its psychometric properties. Based on Rasch dimensionality metrics, the AL scale was separated into subscales. These subscales underwent separate Rasch analyses to test whether they could form stand-alone measures. Independence of these measures was tested with Bland and Altman (B&A) Limit of Agreement (LOA). The AL scale was completed by 293 patients (median age, 71 years). It demonstrated excellent precision (3.12). However, Rasch analysis dimensionality metrics indicated that the domain arguably had other dimensions which were driving, luminance, and reading. Once separated, the remaining AL items, driving and luminance subscales, were unidimensional and had excellent precision of 4.25, 2.94, and 2.22, respectively. The reading subscale showed poor precision (1.66), so it was not examined further. The luminance subscale demonstrated excellent agreement (mean bias, 0.2 logit; 95% LOA, -2.2 to 3.3 logit); however, the driving subscale demonstrated poor agreement (mean bias, 1.1 logit; 95% LOA, -4.8 to 7.0 logit) with the AL scale. These findings indicate that driving items in the AL domain of the glaucoma module were perceived and responded to differently from the other AL items, but the reading and luminance items were not. Therefore, item banking enables stand-alone measurement of driving ability in glaucoma.

Reliability measures in item response theory: manifest versus latent correlation functions.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Verbeke, Geert; De Boeck, Paul

2015-02-01

For item response theory (IRT) models, which belong to the class of generalized linear or non-linear mixed models, reliability at the scale of observed scores (i.e., manifest correlation) is more difficult to calculate than latent correlation based reliability, but usually of greater scientific interest. This is not least because it cannot be calculated explicitly when the logit link is used in conjunction with normal random effects. As such, approximations such as Fisher's information coefficient, Cronbach's α, or the latent correlation are calculated, allegedly because it is easy to do so. Cronbach's α has well-known and serious drawbacks, Fisher's information is not meaningful under certain circumstances, and there is an important but often overlooked difference between latent and manifest correlations. Here, manifest correlation refers to correlation between observed scores, while latent correlation refers to correlation between scores at the latent (e.g., logit or probit) scale. Thus, using one in place of the other can lead to erroneous conclusions. Taylor series based reliability measures, which are based on manifest correlation functions, are derived and a careful comparison of reliability measures based on latent correlations, Fisher's information, and exact reliability is carried out. The latent correlations are virtually always considerably higher than their manifest counterparts, Fisher's information measure shows no coherent behaviour (it is even negative in some cases), while the newly introduced Taylor series based approximations reflect the exact reliability very closely. Comparisons among the various types of correlations, for various IRT models, are made using algebraic expressions, Monte Carlo simulations, and data analysis. Given the light computational burden and the performance of Taylor series based reliability measures, their use is recommended. © 2014 The British Psychological Society.

Household's willingness to pay for heterogeneous attributes of drinking water quality and services improvement: an application of choice experiment

NASA Astrophysics Data System (ADS)

Dauda, Suleiman Alhaji; Yacob, Mohd Rusli; Radam, Alias

2015-09-01

The service of providing good quality of drinking water can greatly improve the lives of the community and maintain a normal health standard. For a large number of population in the world, specifically in the developing countries, the availability of safe water for daily sustenance is none. Damaturu is the capital of Yobe State, Nigeria. It hosts a population of more than two hundred thousand, yet only 45 % of the households are connected to the network of Yobe State Water Corporation's pipe borne water services; this has led people to source for water from any available source and thus, exposed them to the danger of contracting waterborne diseases. In order to address the problem, Yobe State Government has embarked on the construction of a water treatment plant with a capacity and facility to improve the water quality and connect the town with water services network. The objectives of this study are to assess the households' demand preferences of the heterogeneous water attributes in Damaturu, and to estimate their marginal willingness to pay, using mixed logit model in comparison with conditional logit model. A survey of 300 households randomly sampled indicated that higher education greatly influenced the households' WTP decisions. The most significant variable from both of the models is TWQ, which is MRS that rates the water quality from the level of satisfactory to very good. 219 % in simple model is CLM, while 126 % is for the interaction model. As for MLM, 685 % is for the simple model and 572 % is for the interaction model. Estimate of MLM has more explanatory powers than CLM. Essentially, this finding can help the government in designing cost-effective management and efficient tariff structure.

Quality of life of the most severely vision-impaired.

PubMed

Crewe, Julie M; Morlet, Nigel; Morgan, William H; Spilsbury, Katrina; Mukhtar, Aqif; Clark, Antony; Ng, Jonathon Q; Crowley, Margaret; Semmens, James B

2011-01-01

To explore the interaction between vision impairment, perceived quality of life loss and willingness to trade remaining life for vision gain. Community-based cross-sectional study. Legally blind or severely vision-impaired people selected randomly from the Association for the Blind of Western Australia register. Individuals were examined by consultant ophthalmologists and completed the Impact of Vision Impairment profile quality of life assessment and a Time Trade-Off evaluation. Vision-related utility values were calculated. The results were analysed using univariate and multivariate regression methods. IVI Rasch Logits and TTO utility values (TTO UV). 156 people volunteered to contribute to the study. The median age was 80 (19-97) years, and 56% were female. Being legally blind (logMAR > 1) (95% CI 1.1 to 5.2, P = 0.003), clinically depressed (95% CI -11.2 to -1.8, P = 0.007) or more than 40 years of age (95% CI 0.9 to 8.1, P = 0.015) significantly lowered overall impact of vision impairment scores. The emotional domain of impact of vision impairment was associated with willingness to trade part of remaining life. A 5-Logit increase in impact of vision impairment emotional score resulted in a 21% (95% CI 10 to 31) decrease in the odds of being likely to trade life for sight. The Australian definition of blindness compared with World Health Organisation or USA best separates those with perceived loss and appears useful in identifying vision loss-related morbidity. These results suggest that emotional health and lack of depression are important determinants for quality and value of life. © 2011 The Authors. Clinical and Experimental Ophthalmology © 2011 Royal Australian and New Zealand College of Ophthalmologists.

The choice of discount brand cigarettes: a comparative analysis of International Tobacco Control surveys in Canada and the USA (2002-2005).

PubMed

Nargis, Nigar; Fong, Geoffrey T; Chaloupka, Frank J; Li, Qiang

2014-03-01

Increasing tobacco taxes to increase price is a proven tobacco control measure. This article investigates how smokers respond to tax and price increases in their choice of discount brand cigarettes versus premium brands. To estimate how increase in the tax rate can affect smokers' choice of discount brands versus premium brands. Using data from International Tobacco Control surveys in Canada and the USA, a logit model was constructed to estimate the probability of choosing discount brand cigarettes in response to its price changes relative to premium brands, controlling for individual-specific demographic and socioeconomic characteristics and regional effects. The self-reported price of an individual smoker is used in a random-effects regression model to impute price and to construct the price ratio for discount and premium brands for each smoker, which is used in the logit model. An increase in the ratio of price of discount brand cigarettes to the price of premium brands by 0.1 is associated with a decrease in the probability of choosing discount brands by 0.08 in Canada. No significant effect is observed in case of the USA. The results of the model explain two phenomena: (1) the widened price differential between premium and discount brand cigarettes contributed to the increased share of discount brand cigarettes in Canada in contrast to a relatively steady share in the USA during 2002-2005 and (2) increasing the price ratio of discount brands to premium brands-which occurs with an increase in specific excise tax-may lead to upward shifting from discount to premium brands rather than to downward shifting. These results underscore the significance of studying the effectiveness of tax increases in reducing overall tobacco consumption, particularly for specific excise taxes.

How do patient characteristics influence informal payments for inpatient and outpatient health care in Albania: Results of logit and OLS models using Albanian LSMS 2005

PubMed Central

2011-01-01

Background Informal payments for health care are common in most former communist countries. This paper explores the demand side of these payments in Albania. By using data from the Living Standard Measurement Survey 2005 we control for individual determinants of informal payments in inpatient and outpatient health care. We use these results to explain the main factors contributing to the occurrence and extent of informal payments in Albania. Methods Using multivariate methods (logit and OLS) we test three models to explain informal payments: the cultural, economic and governance model. The results of logit models are presented here as odds ratios (OR) and results from OLS models as regression coefficients (RC). Results Our findings suggest differences in determinants of informal payments in inpatient and outpatient care. Generally our results show that informal payments are dependent on certain characteristics of patients, including age, area of residence, education, health status and health insurance. However, they are less dependent on income, suggesting homogeneity of payments across income categories. Conclusions We have found more evidence for the validity of governance and economic models than for the cultural model. PMID:21605459

Performance of the likelihood ratio difference (G2 Diff) test for detecting unidimensionality in applications of the multidimensional Rasch model.

PubMed

Harrell-Williams, Leigh; Wolfe, Edward W

2014-01-01

Previous research has investigated the influence of sample size, model misspecification, test length, ability distribution offset, and generating model on the likelihood ratio difference test in applications of item response models. This study extended that research to the evaluation of dimensionality using the multidimensional random coefficients multinomial logit model (MRCMLM). Logistic regression analysis of simulated data reveal that sample size and test length have a large effect on the capacity of the LR difference test to correctly identify unidimensionality, with shorter tests and smaller sample sizes leading to smaller Type I error rates. Higher levels of simulated misfit resulted in fewer incorrect decisions than data with no or little misfit. However, Type I error rates indicate that the likelihood ratio difference test is not suitable under any of the simulated conditions for evaluating dimensionality in applications of the MRCMLM.

Gender differences in farmers' responses to climate change adaptation in Yongqiao District, China.

PubMed

Jin, Jianjun; Wang, Xiaomin; Gao, Yiwei

2015-12-15

This study examines the gender differences in farmers' responses to climate change adaption in Yongqiao District, China. A random sampling technique was used to select 220 household heads, while descriptive statistics and binary logit models were used to analyze the data obtained from the households. We determine that male and female respondents are not significantly different in their knowledge and perceptions of climate change, but there is a gender difference in adopting climate change adaptation measures. Male-headed households are more likely to adopt new technology for water conservation and to increase investment in irrigation infrastructure. The research also indicates that the adaptation decisions of male and female heads are influenced by different sets of factors. The findings of this research help to elucidate the determinants of climate change adaptation decisions for male and female-headed households and the strategic interventions necessary for effective adaptation. Copyright © 2015 Elsevier B.V. All rights reserved.

The effect of distance to provider on employee response to changes in mental health benefits.

PubMed

Lindrooth, Richard C; Lo Sasso, Anthony T; Lurie, Ithai Z

2006-10-01

We assess whether distance to provider moderates the effect of a change in mental health benefits on treatment initiation of employees of a large US-based company for psychiatric disorders. Mental health treatment administrative claims data plus eligibility information provided by a Fortune 50 company for the years 1995-1998 are used for the analysis. The effect of distance is measured using the relative effect of the initiative on residents living far from providers compared to those living close to providers. We model the probability of treatment initiation using a random effects logit specification. We find that the effect of distance to provider has the potential to over-shadow other incentives to initiate treatment, especially at distances greater than 4 miles. These results lend further support to the notion that geographic dispersion of providers should be an important consideration when forming a selective contracting network. Copyright (c) 2006 John Wiley & Sons, Ltd.

Comprehensive analysis of single- and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama.

PubMed

Islam, Samantha; Jones, Steven L; Dye, Daniel

2014-06-01

The research described in this paper analyzed injury severities at a disaggregate level for single-vehicle (SV) and multi-vehicle (MV) large truck at-fault accidents for rural and urban locations in Alabama. Given the occurrence of a crash, four separate random parameter logit models of injury severity (with possible outcomes of major, minor, and possible or no injury) were estimated. The models identified different sets of factors that can lead to effective policy decisions aimed at reducing large truck-at-fault accidents for respective locations. The results of the study clearly indicated that there are differences between the influences of a variety of variables on the injury severities resulting from urban vs. rural SV and MV large truck at-fault accidents. The results showed that some variables were significant only in one type of accident model (SV or MV) but not in the other accident model. Again, some variables were found to be significant in one location (rural or urban) but not in other locations. The study also identified important factors that significantly impact the injury severity resulting from SV and MV large truck at-fault accidents in urban and rural locations based on the estimated values of average direct pseudo-elasticity. A careful study of the results of this study will help policy makers and transportation agencies identify location specific recommendations to increase safety awareness related to large truck involved accidents and to improve overall highway safety. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spatial occupancy models for large data sets

USGS Publications Warehouse

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

Azevedo, Caio L. N.; Migon, Helio S.

2012-10-01

In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

Ordered LOGIT Model approach for the determination of financial distress.

PubMed

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.

Development and validation of an energy-balance knowledge test for fourth- and fifth-grade students.

PubMed

Chen, Senlin; Zhu, Xihe; Kang, Minsoo

2017-05-01

A valid test measuring children's energy-balance (EB) knowledge is lacking in research. This study developed and validated the energy-balance knowledge test (EBKT) for fourth and fifth grade students. The original EBKT contained 25 items but was reduced to 23 items based on pilot result and intensive expert panel discussion. De-identified data were collected from 468 fourth and fifth grade students enrolled in four schools to examine the psychometric properties of the EBKT items. The Rasch model analysis was conducted using the Winstep 3.65.0 software. Differential item functioning (DIF) analysis flagged 1 item (item #4) functioning differently between boys and girls, which was deleted. The final 22-item EBKT showed desirable model-data fit indices. The items had large variability ranging from -3.58 logit (item #10, the easiest) to 1.70 logit (item #3, the hardest). The average person ability on the test was 0.28 logit (SD = .78). Additional analyses supported known-group difference validity of the EBKT scores in capturing gender- and grade-based ability differences. The test was overall valid but could be further improved by expanding test items to discern various ability levels. For lack of a better test, researchers and practitioners may use the EBKT to assess fourth- and fifth-grade students' EB knowledge.

The Application of Censored Regression Models in Low Streamflow Analyses

NASA Astrophysics Data System (ADS)

Kroll, C.; Luz, J.

2003-12-01

Estimation of low streamflow statistics at gauged and ungauged river sites is often a daunting task. This process is further confounded by the presence of intermittent streamflows, where streamflow is sometimes reported as zero, within a region. Streamflows recorded as zero may be zero, or may be less than the measurement detection limit. Such data is often referred to as censored data. Numerous methods have been developed to characterize intermittent streamflow series. Logit regression has been proposed to develop regional models of the probability annual lowflows series (such as 7-day lowflows) are zero. In addition, Tobit regression, a method of regression that allows for censored dependent variables, has been proposed for lowflow regional regression models in regions where the lowflow statistic of interest estimated as zero at some sites in the region. While these methods have been proposed, their use in practice has been limited. Here a delete-one jackknife simulation is presented to examine the performance of Logit and Tobit models of 7-day annual minimum flows in 6 USGS water resource regions in the United States. For the Logit model, an assessment is made of whether sites are correctly classified as having at least 10% of 7-day annual lowflows equal to zero. In such a situation, the 7-day, 10-year lowflow (Q710), a commonly employed low streamflow statistic, would be reported as zero. For the Tobit model, a comparison is made between results from the Tobit model, and from performing either ordinary least squares (OLS) or principal component regression (PCR) after the zero sites are dropped from the analysis. Initial results for the Logit model indicate this method to have a high probability of correctly classifying sites into groups with Q710s as zero and non-zero. Initial results also indicate the Tobit model produces better results than PCR and OLS when more than 5% of the sites in the region have Q710 values calculated as zero.

Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format.

PubMed

Norman, R; Viney, R; Aaronson, N K; Brazier, J E; Cella, D; Costa, D S J; Fayers, P M; Kemmler, G; Peacock, S; Pickard, A S; Rowen, D; Street, D J; Velikova, G; Young, T A; King, M T

2016-03-01

To assess the feasibility of using a discrete choice experiment (DCE) to value health states within the QLU-C10D, a utility instrument derived from the QLQ-C30, and to assess clarity, difficulty, and respondent preference between two presentation formats. We ran a DCE valuation task in an online panel (N = 430). Respondents answered 16 choice pairs; in half of these, differences between dimensions were highlighted, and in the remainder, common dimensions were described in text and differing attributes were tabulated. To simplify the cognitive task, only four of the QLU-C10D's ten dimensions differed per choice set. We assessed difficulty and clarity of the valuation task with Likert-type scales, and respondents were asked which format they preferred. We analysed the DCE data by format with a conditional logit model and used Chi-squared tests to compare other responses by format. Semi-structured telephone interviews (N = 8) explored respondents' cognitive approaches to the valuation task. Four hundred and forty-nine individuals were recruited, 430 completed at least one choice set, and 422/449 (94 %) completed all 16 choice sets. Interviews revealed that respondents found ten domains difficult but manageable, many adopting simplifying heuristics. Results for clarity and difficulty were identical between formats, but the "highlight" format was preferred by 68 % of respondents. Conditional logit parameter estimates were monotonic within domains, suggesting respondents were able to complete the DCE sensibly, yielding valid results. A DCE valuation task in which only four of the QLU-C10D's ten dimensions differed in any choice set is feasible for deriving utility weights for the QLU-C10D.

Rural practice preferences among medical students in Ghana: a discrete choice experiment

PubMed Central

Johnson, Jennifer C; Gyakobo, Mawuli; Agyei-Baffour, Peter; Asabir, Kwesi; Kotha, S Rani; Kwansah, Janet; Nakua, Emmanuel; Snow, Rachel C; Dzodzomenyo, Mawuli

2010-01-01

Abstract Objective To determine how specific job attributes influenced fourth year medical students’ stated preference for hypothetical rural job postings in Ghana. Methods Based on discussions with medical student focus groups and physicians in practice and in the Ministry of Health, we created a discrete choice experiment (DCE) that assessed how students’ stated preference for certain rural postings was influenced by various job attributes: a higher salary, free superior housing, an educational allowance for children, improved equipment, supportive management, shorter contracts before study leave and a car. We conducted the DCE among all fourth year medical students in Ghana using a brief structured questionnaire and used mixed logit models to estimate the utility of each job attribute. Findings Complete data for DCE analysis were available for 302 of 310 (97%) students. All attribute parameter estimates differed significantly from zero and had the expected signs. In the main effects mixed logit model, improved equipment and supportive management were most strongly associated with job preference (β = 1.42; 95% confidence interval, CI: 1.17 to 1.66, and β = 1.17; 95% CI: 0.96 to 1.39, respectively), although shorter contracts and salary bonuses were also associated. Discontinuing the provision of basic housing had a large negative influence (β = −1.59; 95% CI: −1.88 to −1.31). In models including gender interaction terms, women’s preferences were more influenced by supportive management and men’s preferences by superior housing. Conclusion Better working conditions were strongly associated with the stated choice of hypothetical rural postings among fourth year Ghanaian medical students. Studies are needed to find out whether job attributes determine the actual uptake of rural jobs by graduating physicians. PMID:20458371

Risk factors for subclinical and clinical ketosis and association with production parameters in dairy cows in the Netherlands.

PubMed

Vanholder, T; Papen, J; Bemers, R; Vertenten, G; Berge, A C B

2015-02-01

Ketosis is associated with many transition cow diseases and the subclinical form has been found to be a common condition in high-producing dairy cows. The objectives of this field study in the Netherlands were (1) to determine risk factors for subclinical ketosis [SCK; 1.2-2.9mmol of β-hydroxybutyrate (BHBA)/L of serum] and clinical ketosis (CK: ≥3.0mmol of BHBA/L of serum) at 7 to 14 d in milk and (2) to assess the association of SCK and CK with production parameters at the first dairy herd improvement (DHI) testing. Twenty-three dairies were enrolled by a local veterinary practice from 2009 to 2010, and 1,715 cows were screened for ketosis by measuring serum BHBA concentrations at 7 to 14 d in milk. Overall, 47.2% of cows had SCK and 11.6% had CK. Mixed generalized logit models with a random effect of herd were used to evaluate cow level factors associated with SCK and CK. The associations of SCK and CK with milk production parameters were tested using mixed linear models with a random effect of herd. Cows at a moderate (3.25-3.75) or fat (≥4) body condition score before calving were more likely to develop SCK and CK than thin (body condition score≤3.0) cows. The risk for developing SCK was higher in parity 2 and older cows compared with heifers, whereas for CK only, parity ≥3 cows had a higher risk. The quarter of the year in which a cow calved was associated with the risk for SCK and CK. For SCK quarter 1 (January-March) and quarter 2 (April-June), and for CK quarter 1, quarter 2, and quarter 3 (July-September) all increased the risk of development of the condition compared with quarter 4 (October-December). An increased yield of colostrum at first milking was associated with increasing risk for SCK and CK. Prolonged previous lactation length and dry period length were both associated with increased odds for SCK and CK. Subclinical ketosis and CK were associated with a higher milk yield, a higher milk fat percentage, and a lower milk protein percentage at first DHI test day. Overall the study reinforces previous findings that the major risk factors for both SCK and CK are increasing parity, overconditioning of animals prepartum, season of calving, and dry period length. In addition, previous lactation length and liters of colostrum have been identified as additional risk factors for the development of ketosis. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Cycle frequency in standard Rock-Paper-Scissors games: Evidence from experimental economics

NASA Astrophysics Data System (ADS)

Xu, Bin; Zhou, Hai-Jun; Wang, Zhijian

2013-10-01

The Rock-Paper-Scissors (RPS) game is a widely used model system in game theory. Evolutionary game theory predicts the existence of persistent cycles in the evolutionary trajectories of the RPS game, but experimental evidence has remained to be rather weak. In this work, we performed laboratory experiments on the RPS game and analyzed the social-state evolutionary trajectories of twelve populations of N=6 players. We found strong evidence supporting the existence of persistent cycles. The mean cycling frequency was measured to be 0.029±0.009 period per experimental round. Our experimental observations can be quantitatively explained by a simple non-equilibrium model, namely the discrete-time logit dynamical process with a noise parameter. Our work therefore favors the evolutionary game theory over the classical game theory for describing the dynamical behavior of the RPS game.

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

NASA Astrophysics Data System (ADS)

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.

Occupant Perceptions and a Health Outcome in Retail Stores

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

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

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 exchangemore » 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.« less

Preferences for tap water attributes within couples: An exploration of alternative mixed logit parameterizations

NASA Astrophysics Data System (ADS)

Scarpa, Riccardo; Thiene, Mara; Hensher, David A.

2012-01-01

Preferences for attributes of complex goods may differ substantially among members of households. Some of these goods, such as tap water, are jointly supplied at the household level. This issue of jointness poses a series of theoretical and empirical challenges to economists engaged in empirical nonmarket valuation studies. While a series of results have already been obtained in the literature, the issue of how to empirically measure these differences, and how sensitive the results are to choice of model specification from the same data, is yet to be clearly understood. In this paper we use data from a widely employed form of stated preference survey for multiattribute goods, namely choice experiments. The salient feature of the data collection is that the same choice experiment was applied to both partners of established couples. The analysis focuses on models that simultaneously handle scale as well as preference heterogeneity in marginal rates of substitution (MRS), thereby isolating true differences between members of couples in their MRS, by removing interpersonal variation in scale. The models employed are different parameterizations of the mixed logit model, including the willingness to pay (WTP)-space model and the generalized multinomial logit model. We find that in this sample there is some evidence of significant statistical differences in values between women and men, but these are of small magnitude and only apply to a few attributes.

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

NASA Astrophysics Data System (ADS)

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.

Determinants of Anemia and Hemoglobin Concentration in Haitian School-Aged Children

PubMed Central

Iannotti, Lora L.; Delnatus, Jacques R.; Odom, Audrey R.; Eaton, Jacob C.; Griggs, Jennifer J.; Brown, Sarah; Wolff, Patricia B.

2015-01-01

Anemia diminishes oxygen transport in the body, resulting in potentially irreversible growth and developmental consequences for children. Limited evidence for determinants of anemia exists for school-aged children. We conducted a cluster randomized controlled trial in Haiti from 2012 to 2013 to test the efficacy of a fortified school snack. Children (N = 1,047) aged 3–13 years were followed longitudinally at three time points for hemoglobin (Hb) concentrations, anthropometry, and bioelectrical impedance measures. Dietary intakes, infectious disease morbidities, and socioeconomic and demographic factors were collected at baseline and endline. Longitudinal regression modeling with generalized least squares and logit models with random effects identified anemia risk factors beyond the intervention effect. At baseline, 70.6% of children were anemic and 2.6% were severely anemic. Stunting increased the odds of developing anemia (adjusted odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.05–2.08) and severe anemia (adjusted OR: 2.47, 95% CI: 1.30–4.71). Parent-reported vitamin A supplementation and deworming were positively associated with Hb concentrations, whereas fever and poultry ownership showed a negative relationship with Hb concentration and increased odds of severe anemia, respectively. Further research should explore the full spectrum of anemia etiologies in school children, including genetic causes. PMID:26350448

Industrial water pollution, water environment treatment, and health risks in China.

PubMed

Wang, Qing; Yang, Zhiming

2016-11-01

The negative health effects of water pollution remain a major source of morbidity and mortality in China. The Chinese government is making great efforts to strengthen water environment treatment; however, no studies have evaluated the effects of water treatment on human health by water pollution in China. This study evaluated the association between water pollution and health outcomes, and determined the extent to which environmental regulations on water pollution may lead to health benefits. Data were extracted from the 2011 and 2013 China Health and Retirement Longitudinal Study (CHARLS). Random effects model and random effects Logit model were applied to study the relationship between health and water pollution, while a Mediator model was used to estimate the effects of environmental water treatment on health outcomes by the intensity of water pollution. Unsurprisingly, water pollution was negatively associated with health outcomes, and the common pollutants in industrial wastewater had differential impacts on health outcomes. The effects were stronger for low-income respondents. Water environment treatment led to improved health outcomes among Chinese people. Reduced water pollution mediated the associations between water environment treatment and health outcomes. The results of this study offer compelling evidence to support treatment of water pollution in China. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

PubMed

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

The choice of discount brand cigarettes: A comparative analysis of International Tobacco Control (ITC) Surveys in Canada and the United States (2002–2005)

PubMed Central

Nargis, Nigar; Fong, Geoffrey T.; Chaloupka, Frank J.; Li, Qiang

2014-01-01

Background Increasing tobacco taxes to increase price is a proven tobacco control measure. This paper investigates how smokers respond to tax and price increases in their choice of discount brand cigarettes vs. premium brands. Objective To estimate how increase in the tax rate can affect smokers’ choice of discount brands versus premium brands. Methods Using data from ITC Surveys in Canada and the United States, a logit model was constructed to estimate the probability of choosing discount brand cigarettes in response to its price changes relative to premium brands, controlling for individual-specific demographic and socio-economic characteristics and regional effects. The self-reported price of an individual smoker is used in a random-effects regression model to impute price and to construct the price ratio for discount and premium brands for each smoker, which is used in the logit model. Findings An increase in the ratio of price of discount brand cigarettes to the price of premium brands by 0.1 is associated with a decrease in the probability of choosing discount brands by 0.08 in Canada. No significant effect is observed in case of the United States. Conclusion The results of the model explain two phenomena: (1) the widened price differential between premium and discount brand cigarettes contributed to the increased share of discount brand cigarettes in Canada in contrast to a relatively steady share in the United States during 2002–2005, and (2) increasing the price ratio of discount brands to premium brands—which occurs with an increase in specific excise tax—may lead to upward shifting from discount to premium brands rather than to downward shifting. These results underscore the significance of studying the effectiveness of tax increases in reducing overall tobacco consumption, particularly for specific excise taxes. PMID:23986408

Regression Models For Multivariate Count Data

PubMed Central

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

2016-01-01

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

Regression Models For Multivariate Count Data.

PubMed

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

2017-01-01

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

Using the choice experiment method in the design of breeding goals in dairy sheep.

PubMed

Ragkos, A; Abas, Z

2015-02-01

Market failures are the main cause of poor acknowledgement of the true impact of functional sheep traits on the management and economic performance of farms, which results in their omission from the breeding goal or the estimation of non-representative economic weights in the breeding goal. Consequently, stated-preference non-market valuation techniques, which recently emerged to mitigate these problems, are necessary to estimate economic weights for functional traits. The purpose of this paper is to present an example of the use of a choice experiment (CE) in the estimation of economic weights for sheep traits for the design of breeding goals. Through a questionnaire survey the preferences of sheep farmers are recorded and their marginal willingness to pay (MWTP) for 10 production and functional traits is estimated. Data are analysed using random parameter logit models. The results reveal unobserved preference heterogeneity for fertility, adaptability to grazing and resistance to disease, thus highlighting that these traits are appreciated differently by farmers, because their needs are diverse. Positive MWTP is found for Greek breeds, high milk production and lambs with low fat deposition, for which there is high demand in Greek markets. On the other hand, MWTP for the cheese-making ability of milk is negative, stemming from the fact that sheep milk prices in Greece are not formulated according to milk composition. In addition, farmers seem to understand differences between udder shapes and attribute different values to various types. This application of the CE method indicates that communication channels among farmers and breeders should be established in order to enhance market performance and to provide orientation to the design of breeding programmes. Non-market valuation can be used complementarily to market valuation techniques, in order to provide accurate estimates for production and functional traits.

Measuring Care-Related Quality of Life of Caregivers for Use in Economic Evaluations: CarerQol Tariffs for Australia, Germany, Sweden, UK, and US.

PubMed

Hoefman, Renske J; van Exel, Job; Brouwer, Werner B F

2017-04-01

Informal care is often not included in economic evaluations in healthcare, while the impact of caregiving can be relevant for cost-effectiveness recommendations from a societal perspective. The impact of informal care can be measured and valued with the CarerQol instrument, which measures the impact of informal care on seven important burden dimensions (CarerQol-7D) and values this in terms of general quality of life (CarerQol-VAS). The CarerQol can be included at the effect side of multi-criteria analyses of patient interventions or in cost-effectiveness or utility analysis of interventions targeted at caregivers. At present, utility scores based on relative utility weights for the CarerQol-7D are only available for the Netherlands. This study calculates CarerQol-7D tariffs for Australia, Germany, Sweden, UK, and US. Data were collected among the general population in Australia, Germany, Sweden, UK, and US by an Internet survey. Utility weights were collected with a discrete choice experiment with two unlabeled alternatives described in terms of the seven CarerQol-7D dimensions. An efficient experimental design with priors obtained from the Netherlands was used to create the choice sets. Data was analyzed with a panel mixed multinomial logit model with random parameters. In all five countries, the CarerQol-7D dimensions were significantly associated with the utility of informal care situations. Physical health problems were most strongly associated with the utility for informal care situations. The tariff was constructed by adding up the relative utility weights per category of all CarerQol-7D dimensions for each country separately. The CarerQol tariffs for Australia, Germany, Sweden, UK, and US facilitate the inclusion of informal care in economic evaluations.

How do physicians weigh benefits and risks associated with treatments in patients with osteoarthritis in the United Kingdom?

PubMed

Arden, Nigel K; Hauber, A Brett; Mohamed, Ateesha F; Johnson, F Reed; Peloso, Paul M; Watson, Douglas J; Mavros, Panagiotis; Gammaitoni, Arnold; Sen, Shuvayu S; Taylor, Stephanie D

2012-05-01

To quantify the relative importance that UK physicians attach to the benefits and risks of current drugs when making treatment decisions for patients with osteoarthritis (OA). Physicians treating at least 10 patients with OA per month completed an online discrete-choice experiment survey and answered 12 treatment-choice questions comparing medication profiles. Medication profiles were defined by 4 benefits (reduction in ambulatory pain, resting pain, stiffness, and difficulty doing daily activities) and 3 treatment-related risks [bleeding ulcer, stroke, and myocardial infarction (MI)]. Each physician made medication choices for 3 of 9 hypothetical patients (varied by age, history of MI, hypertension, and history of gastrointestinal bleeding). Importance weights were estimated using a random-parameters logit model. Treatment-related risks physicians were willing to accept in exchange for various reductions in ambulatory and resting pain also were calculated. The final sample was 475. A reduction in ambulatory pain from 75 mm to 25 mm (1.6 units) was 1.1 times as important as an increase in MI risk from 0% to 1.5% (1.5 units). The greatest importance was for eliminating a 3% treatment-related risk of MI or stroke. On average, physicians were willing to accept an increase in bleeding ulcer risk of 0.7% (95% CI 0.4%-1.7%) for a reduction in ambulatory pain of 75 mm to 50 mm. When presented with well-known benefits and risks of OA treatments, physicians placed greater importance on the risks than on the analgesic properties of the drug. This has implications for the reporting of the results of clinical research to physicians.

Preferences for breast cancer risk reduction among BRCA1/BRCA2 mutation carriers: a discrete-choice experiment.

PubMed

Liede, Alexander; Mansfield, Carol A; Metcalfe, Kelly A; Price, Melanie A; Snyder, Carrie; Lynch, Henry T; Friedman, Sue; Amelio, Justyna; Posner, Joshua; Narod, Steven A; Lindeman, Geoffrey J; Evans, D Gareth

2017-09-01

Unaffected women who carry BRCA1 or BRCA2 mutations face difficult choices about reducing their breast cancer risk. Understanding their treatment preferences could help us improve patient counseling and inform drug trials. The objective was to explore preferences for various risk-reducing options among women with germline BRCA1/2 mutations using a discrete-choice experiment survey and to compare expressed preferences with actual behaviors. A discrete-choice experiment survey was designed wherein women choose between hypothetical treatments to reduce breast cancer risk. The hypothetical treatments were characterized by the extent of breast cancer risk reduction, treatment duration, impact on fertility, hormone levels, risk of uterine cancer, and ease and mode of administration. Data were analyzed using a random-parameters logit model. Women were also asked to express their preference between surgical and chemoprevention options and to report on their actual risk-reduction actions. Women aged 25-55 years with germline BRCA1/2 mutations who were unaffected with breast or ovarian cancer were recruited through research registries at five clinics and a patient advocacy group. Between January 2015 and March 2016, 622 women completed the survey. Breast cancer risk reduction was the most important consideration expressed, followed by maintaining fertility. Among the subset of women who wished to have children in future, the ability to maintain fertility was the most important factor, followed by the extent of risk reduction. Many more women said they would take a chemoprevention drug than had actually taken chemoprevention. Women with BRCA1/2 mutations indicated strong preferences for breast cancer risk reduction and maintaining fertility. The expressed desire to have a safe chemoprevention drug available to them was not met by current chemoprevention options.

How important is local food to organic-minded consumers?

PubMed

Hempel, Corinna; Hamm, Ulrich

2016-01-01

The study deals with German consumers' attitudes towards organic food and local food, their food purchase behaviour and their personal characteristics. The purpose is to investigate the differences in attitudes and willingness-to-pay values between consumers who consider the organic production of food (very) important and those who consider it less important. This study combines a consumer survey with an in-store, discrete choice experiment. In the analysis, findings from the consumer survey were related to the choices made by consumers in the experiment. Consumers' preferences and willingness-to-pay values were estimated through random parameter logit modelling. Organic-minded consumers (i.e. those who regarded organic food production as (very) important in the survey) have stronger preferences and estimated willingness-to-pay values for organic as well as local products. Locally produced food, as opposed to food from neighbouring countries or non-EU countries, is preferred over organically produced food by both consumer groups which demonstrates that organic-minded consumers do not only consider organic food production as important, but also value local food production in a purchase situation. Hence, it can be assumed that local food production complements organic food production for the group of organic-minded consumers. This contribution is the first study dealing with local and organic food purchase behaviour in Germany that examines four different products and is carried out in rural as well as urban locations in four different regions. Due to the application of a choice experiment including no-choice options and binding purchase decisions, the results are expected to be closer to real purchase situations than results of direct questioning and choice experiments in online applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of US patient, rheumatologist, and dermatologist perceptions of psoriatic disease symptoms: results from the DISCONNECT study.

PubMed

Husni, M Elaine; Fernandez, Anthony; Hauber, Brett; Singh, Rakesh; Posner, Joshua; Sutphin, Jessie; Ganguli, Arijit

2018-05-31

The perceived bother of skin and joint-related manifestations of psoriatic disease may differ among patients, rheumatologists, and dermatologists. This study identified and compared the patient and dermatologist/rheumatologist-perceived bother of psoriatic disease manifestations. Online surveys were administered to patients with both psoriasis and psoriatic arthritis and to dermatologists and rheumatologists. Object-case best-worst scaling was used to identify the most and least bothersome items from a set of five items in a series of questions. Each item set was drawn from 20 items describing psoriatic disease skin and joint symptoms and impacts on daily activities. Survey responses were analyzed using random-parameters logit models for each surveyed group, yielding a relative-bother weight (RBW) for each item compared with joint pain, soreness, or tenderness. Surveys were completed by 200 patients, 150 dermatologists, and 150 rheumatologists. Patients and physicians agreed that joint pain, soreness, and tenderness are among the most bothersome manifestations of psoriatic disease (RBW 1.00). For patients, painful, inflamed, or broken skin (RBW 1.03) was more bothersome, while both rheumatologists and dermatologists considered painful skin much less bothersome (RBW 0.17 and 0.22, respectively) than joint pain. Relative to joint pain, rheumatologists were more likely to perceive other joint symptoms as bothersome, while dermatologists were more likely to perceive other skin symptoms as bothersome. This study has identified important areas of discordance both between patients and physicians and between rheumatologists and dermatologists about the relative bother of a comprehensive set of psoriatic disease symptoms and functional impacts. Both physician specialists should ask patients which manifestations of psoriatic disease are most bothersome to them, as these discussions may have important implications for drug and other patient management options.

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

PubMed

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

2014-09-01

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

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials.

PubMed

Theofilatos, Athanasios

2017-06-01

The effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece. Random Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively. Regarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity. The study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms. The identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Valuations of genetic test information for treatable conditions: the case of colorectal cancer screening.

PubMed

Kilambi, Vikram; Johnson, F Reed; González, Juan Marcos; Mohamed, Ateesha F

2014-12-01

The value of the information that genetic testing services provide can be questioned for insurance-based health systems. The results of genetic tests oftentimes may not lead to well-defined clinical interventions; however, Lynch syndrome, a genetic mutation for which carriers are at an increased risk for colorectal cancer, can be identified through genetic testing, and meaningful health interventions are available via increased colonoscopic surveillance. Valuations of test information for such conditions ought to account for the full impact of interventions and contingent outcomes. To conduct a discrete-choice experiment to elicit individuals' preferences for genetic test information. A Web-enabled discrete-choice experiment survey was administered to a representative sample of US residents aged 50 years and older. In addition to specifying expenditures on colonoscopies, respondents were asked to make a series of nine selections between two hypothetical genetic tests or a no-test option under the premise that a relative had Lynch syndrome. The hypothetical genetic tests were defined by the probability of developing colorectal cancer, the probability of a false-negative test result, privacy of the result, and out-of-pocket cost. A model specification identifying necessary interactions was derived from assumptions of risk behavior and the decision context and was estimated using random-parameters logit. A total of 650 respondents were contacted, and 385 completed the survey. The monetary equivalent of test information was approximately $1800. Expenditures on colonoscopies to reduce mortality risks affected valuations. Respondents with lower income or who reported being employed significantly valued genetic tests more. Genetic testing may confer benefits through the impact of subsequent interventions on private individuals. Copyright © 2014. Published by Elsevier Inc.

Hemodialysis patients' preferences for the management of secondary hyperparathyroidism.

PubMed

Hauber, Brett; Caloyeras, John; Posner, Joshua; Brommage, Deborah; Belozeroff, Vasily; Cooper, Kerry

2017-07-28

Patient engagement and patient-centered care are critical in optimally managing patients with end-stage renal disease (ESRD). Understanding patient preferences is a key element of patient-centered care and shared decision making. The objective of this study was to elicit patients' preferences for the treatment of secondary hyperparathyroidism (SHPT) associated with ESRD using a discrete-choice experiment survey. Clinical literature, nephrologist input, patient-education resources, and a patient focus group informed development of the survey instrument, which was qualitatively pretested before its administration to a broader sample of patients. The National Kidney Foundation invited individuals in the United States with ESRD who were undergoing hemodialysis to participate in the survey. Respondents chose among three hypothetical SHPT treatment alternatives (two medical alternatives and surgery) in each of a series of questions, which were defined by attributes of efficacy (effect on laboratory values and symptoms), safety, tolerability, mode of administration, and cost. The survey instrument included a best-worst scaling exercise to quantify the relative bother of the individual attributes of surgery. Random-parameters logit models were used to evaluate the conditional relative importance of the attributes. A total of 200 patients with ESRD completed the survey. The treatment attributes that were most important to the respondents were whether a treatment was a medication or surgery and out-of-pocket cost. Patients had statistically significant preferences for efficacy attributes related to symptom management and laboratory values, but placed less importance on the attributes related to mode of administration and side effects. The most bothersome attribute of surgery was the risk of surgical mortality. Patients with ESRD and SHPT who are undergoing hemodialysis understand SHPT and have clear and measurable treatment preferences. These results may help inform clinicians about patients' preferences regarding treatment options for a common complication of ESRD.

Economic considerations and patients' preferences affect treatment selection for patients with rheumatoid arthritis: a discrete choice experiment among European rheumatologists.

PubMed

Hifinger, M; Hiligsmann, M; Ramiro, S; Watson, V; Severens, J L; Fautrel, B; Uhlig, T; van Vollenhoven, R; Jacques, P; Detert, J; Canas da Silva, J; Scirè, C A; Berghea, F; Carmona, L; Péntek, M; Keat, A; Boonen, A

2017-01-01

To compare the value that rheumatologists across Europe attach to patients' preferences and economic aspects when choosing treatments for patients with rheumatoid arthritis. In a discrete choice experiment, European rheumatologists chose between two hypothetical drug treatments for a patient with moderate disease activity. Treatments differed in five attributes: efficacy (improvement and achieved state on disease activity), safety (probability of serious adverse events), patient's preference (level of agreement), medication costs and cost-effectiveness (incremental cost-effectiveness ratio (ICER)). A Bayesian efficient design defined 14 choice sets, and a random parameter logit model was used to estimate relative preferences for rheumatologists across countries. Cluster analyses and latent class models were applied to understand preference patterns across countries and among individual rheumatologists. Responses of 559 rheumatologists from 12 European countries were included in the analysis (49% females, mean age 48 years). In all countries, efficacy dominated treatment decisions followed by economic considerations and patients' preferences. Across countries, rheumatologists avoided selecting a treatment that patients disliked. Latent class models revealed four respondent profiles: one traded off all attributes except safety, and the remaining three classes disregarded ICER. Among individual rheumatologists, 57% disregarded ICER and these were more likely from Italy, Romania, Portugal or France, whereas 43% disregarded uncommon/rare side effects and were more likely from Belgium, Germany, Hungary, the Netherlands, Norway, Spain, Sweden or UK. Overall, European rheumatologists are willing to trade between treatment efficacy, patients' treatment preferences and economic considerations. However, the degree of trade-off differs between countries and among individuals. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Latent class analysis of factors that influence weekday and weekend single-vehicle crash severities.

PubMed

Adanu, Emmanuel Kofi; Hainen, Alexander; Jones, Steven

2018-04-01

This paper investigates factors that influence the severity of single-vehicle crashes that happen on weekdays and weekends. Crash data from 2012 to 2016 for the State of Alabama was used for this study. Latent class logit models were developed as alternative to the frequently used random parameters models to account for unobserved heterogeneity across crash-severity observations. Exploration of the data revealed that a high proportion of severe injury injury crashes happened on weekends. The study examined whether single-vehicle crash contributing factors differ between weekdays and weekends. The model estimation results indicate a significant association of severe injury crashes to risk factors such as driver unemployment, driving with invalid license, no seatbelt use, fatigue, driving under influence, old age, and driving on county roads for both weekdays and weekends. Research findings show a strong link between human factors and the occurrence of severe injury single-vehicle crashes, as it has been observed that many of the factors associated with severe-injury outcome are driver behavior related. To illustrate the significance of the findings of this study, a third model using the combined data was developed to explore the merit of using sub-populations of the data for improved and detailed segmentation of the crash-severity factors. It has also been shown that generally, the factors that influence single-vehicle crash injury outcomes were not very different between weekdays and weekends. The findings of this study show the importance of investigating sub-populations of data to reveal complex relationships that should be understood as a necessary step in targeted countermeasure application. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling Preference and Willingness to Pay for Drought Tolerance (DT) in Maize in Rural Zimbabwe.

PubMed

Kassie, Girma T; Abdulai, Awudu; Greene, William H; Shiferaw, Bekele; Abate, Tsedeke; Tarekegne, Amsal; Sutcliffe, Chloe

2017-06-01

Maize plays a leading role in the food security of millions in southern Africa, yet it is highly vulnerable to the moisture stress brought about by the erratic rainfall patterns that characterize weather systems in the area. Developing and making drought-tolerant maize varieties available to farmers in the region has thus long been a key goal on the regional development agenda. Farm-level adoption of these varieties, however, depends on local perceptions of the value they add, along with willingness to pay (WTP) for it. Focusing on Zimbabwe, this research aimed at estimating the implicit prices farmers are willing to pay for drought tolerance in maize compared to other preferred traits. Using a choice experiment framework, we generated 12,600 observations from a random sample of 1,400 households in communal areas within 14 districts of Zimbabwe. Taste parameters and heterogeneities were estimated using the generalized multinomial logit model (G-MNL). The results reveal drought tolerance, grain yield, covered cob tip, cob size, and semi-flint texture to be the most preferred traits by farm households in Zimbabwe. The WTP estimates show that farmers are willing to pay a premium for drought tolerance equal to 2.56, 7, 3.2, and 5 times higher than for an additional ton of yield per acre, bigger cob size, larger grain size, and covered cob tip, respectively. We suggest designing and implementing innovative ways of promoting DT maize along with awareness-raising activities to enhance contextual understandings of drought and drought risk to speed adoption of new DT maize varieties by risk-prone farming communities. Given the high level of rural literacy and the high rate of adoption of improved maize, trait-based promotion and marketing of varieties constitutes the right strategy.

Public preferences for establishing nephrology facilities in Greenland: estimating willingness-to-pay using a discrete choice experiment.

PubMed

Kjær, Trine; Bech, Mickael; Kronborg, Christian; Mørkbak, Morten Raun

2013-10-01

At present there are no nephrology facilities in Greenland. Greenlandic patients with renal failure needing dialysis thus have to travel to Denmark to obtain treatment. For patients in haemodialysis this necessitates a permanent residence in Denmark. Our study was aimed at examining Greenlanders' preferences for establishing nephrology facilities in Greenland at Queen Ingrid's Hospital in Nuuk, and to estimate the associated change in welfare. Preferences were elicited using a discrete choice experiment (DCE). A random sample of 500 individuals of the general population was sent a postal questionnaire in which they were asked to consider the trade-offs of establishing nephrology facilities in Greenland as opposed to the current situation. This involved trading off the benefits of having such facilities in their home country against the costs of the intervention. Besides including a payment attribute described in terms of incremental tax payment, the DCE included two interventions attributes related to (1) the organisation of labour, and (2) the physical settings of the patients. Respondents succeeded in answering the DCE despite cultural and linguistic disparity. We found that all the included attributes had a significant effect on respondents' choices, and that respondents' answers to the DCE were in keeping with their values as stated in the questionnaire. DCE data was analyzed using a random parameter logit model reparametrized in willingness-to-pay space. The results showed that establishing facilities in Greenland were preferred to the current treatment in Denmark. The welfare estimate from the DCE, at DKK 18.74 million, exceeds the estimated annual costs of establishing treatment facilities for patients with chronic renal failure. Given the estimated confidence interval this result seems robust. Establishing facilities in Greenland therefore would appear to be welfare-improving, deriving positive net benefits. Despite the relatively narrow policy focus, we believe that our findings provide some insight into individuals' preferences for decentralization of public services and on citizens' views of 'self-governance' that go beyond the case of Greenland. More generally, this paper illustrates how DCE can be applied successfully to developing countries with culturally, demographically, and geographically distinct features.

Writing and overwriting short-term memory

PubMed Central

Killeen, Peter R.

2008-01-01

An integrative account of short-term memory is based on data from pigeons trained to report the majority color in a sequence of lights. Performance showed strong recency effects, was invariant over changes in the interstimulus interval, and improved with increases in the intertrial interval. A compound model of binomial variance around geometrically decreasing memory described the data; a logit transformation rendered it isomorphic with other memory models. The model was generalized for variance in the parameters, where it was shown that averaging exponential and power functions from individuals or items with different decay rates generates new functions that are hyperbolic in time and in log time, respectively. The compound model provides a unified treatment of both the accrual and the dissipation of memory and is consistent with data from various experiments, including the choose-short bias in delayed recall, multielement stimuli, and Rubin and Wenzel’s (1996) meta-analyses of forgetting. PMID:11340865

Public-private sector partnership in household waste management as perceived by residents in south-west Nigeria.

PubMed

Ezebilo, Eugene E; Animasaun, Emmanuel D

2012-08-01

In most developing countries public-private sector partnership is becoming increasingly applied in household waste management service delivery especially in urban areas to reduce cost and improve effectiveness. This paper reports a study of householders' perceptions of public-private sector partnership in provision of household waste management services in Ilorin, south-west Nigeria. A multistage random sampling technique was used to select 224 households for the study. The data generated from the survey were analysed using a binary logit model. The results show that most of the respondents were of the opinion that the public-private partnership has not been able to improve household waste management services. Time taken to visit solid waste collection point, income and marital status negatively influenced their perceptions, while activities of sanitary inspectors, occupation and gender had positive influence. The public-private partnership will be more effective and sustainable if the public sector could pay more attention to performance monitoring and accountability.

Foot placement during error and pedal applications in naturalistic driving.

PubMed

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

2017-02-01

Data from a naturalistic driving study was used to examine foot placement during routine foot pedal movements and possible pedal misapplications. The study included four weeks of observations from 30 drivers, where pedal responses were recorded and categorized. The foot movements associated with pedal misapplications and errors were the focus of the analyses. A random forest algorithm was used to predict the pedal application types based the video observations, foot placements, drivers' characteristics, drivers' cognitive function levels and anthropometric measurements. A repeated multinomial logit model was then used to estimate the likelihood of the foot placement given various driver characteristics and driving scenarios. The findings showed that prior foot location, the drivers' seat position, and the drive sequence were all associated with incorrect foot placement during an event. The study showed that there is a potential to develop a driver assistance system that can reduce the likelihood of a pedal error. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Influence of Consumer Goals and Marketing Activities on Product Bundling

NASA Astrophysics Data System (ADS)

Haijun, Wang

Upon entering a store, consumers are faced with the questions of whether to buy, what to buy, and how much to buy. Consumers include products from different categories in their decision process. Product categories can be related in different ways. Product bundling is a process that involves the choice of at least two non-substitutable items. In this research, the consumers' explicit product bundling activity at the point of sale is focused. We focuses on the retailers' perspective and therefore leaves out consumers' brand choice decisions, concentrating on purchase incidence and quantity. At the base of the current model of the exist researches, we integrate behavioural choice analysis and predictive choice modelling through the underlying behavioural models, called random utility maximization (RUM) models. The methodological contribution of this research lies therein to combine a nested logit choice model with a latent variable factor model. We point out several limitations for both theory and practice at the end.

Preferences for the sex-composition of children in Europe: a multilevel examination of its effect on progression to a third child.

PubMed

Mills, Melinda; Begall, Katia

2010-03-01

Comparative research on the preferred sex of children in Western societies has generally focused on women only and ignored the role of gender equity and the need for children's economic support in old age. A multilevel analysis extends existing research by examining, for both men and women and across 24 European countries, the effect of the preferred sex-composition of offspring on whether parents have or intend to have a third child. Using the European Social Survey (2004/5), a multilevel (random coefficient) ordered logit regression of that intention (N = 3,323) and a binary logistic multilevel model of the transition to a third child (N = 6,502) demonstrate the presence of a mixed-sex preference. In countries with a high risk of poverty in old age, a preference for sons is found, particularly for men. In societies where there is lower gender equity, both men and women have a significant preference for boys.

Switching health insurers: the role of price, quality and consumer information search.

PubMed

Boonen, Lieke H H M; Laske-Aldershof, Trea; Schut, Frederik T

2016-04-01

We examine the impact of price, service quality and information search on people's propensity to switch health insurers in the competitive Dutch health insurance market. Using panel data from annual household surveys and data on health insurers' premiums and quality ratings over the period 2006-2012, we estimate a random effects logit model of people's switching decisions. We find that switching propensities depend on health plan price and quality, and on people's age, health, education and having supplementary or group insurance. Young people (18-35 years) are more sensitive to price, whereas older people are more sensitive to quality. Searching for health plan information has a much stronger impact on peoples' sensitivity to price than to service quality. In addition, searching for health plan information has a stronger impact on the switching propensity of higher than lower educated people, suggesting that higher educated people make better use of available health plan information. Finally, having supplementary insurance significantly reduces older people's switching propensity.

Parents and adolescents preferences for asthma control: a best-worst scaling choice experiment using an orthogonal main effects design.

PubMed

Ungar, Wendy J; Hadioonzadeh, Anahita; Najafzadeh, Mehdi; Tsao, Nicole W; Dell, Sharon; Lynd, Larry D

2015-11-17

The preferences of parents and children with asthma influence their ability to manage a child's asthma and achieve good control. Potential differences between parents and adolescents with respect to specific parameters of asthma control are not considered in clinical asthma guidelines. The objective was to measure and compare the preferences of parents and adolescents with asthma with regard to asthma control parameters using best worst scaling (BWS). Fifty-two parents of children with asthma and 44 adolescents with asthma participated in a BWS study to quantify preferences regarding night-time symptoms, wheezing/chest tightening, changes in asthma medications, emergency visits and physical activity limitations. Conditional logit regression was used to determine each group's utility for each level of each asthma control parameter. Parents displayed the strongest positive preference for the absence of night-time symptoms (β = 2.09, p < 0.00001) and the strongest negative preference for 10 emergency room visits per year (β = -2.15, p < 0.00001). Adolescents displayed the strongest positive preference for the absence of physical activity limitations (β = 2.17, p < 0.00001) and the strongest negative preference for ten physical activity limitations per month (β = -1.97). Both groups were least concerned with changes to medications. Parents and adolescents placed different weights on the importance of asthma control parameters and each group displayed unique preferences. Understanding the relative importance placed on each parameter by parents and adolescents is essential for designing effective patient-focused disease management plans.

Zero adjusted models with applications to analysing helminths count data.

PubMed

Chipeta, Michael G; Ngwira, Bagrey M; Simoonga, Christopher; Kazembe, Lawrence N

2014-11-27

It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess zeros exist. Main objective of the current paper is to apply such models to analyse risk factors associated with human helminths (S. haematobium) particularly in a case where there's a high proportion of zero counts. The data were collected during a community-based randomised control trial assessing the impact of mass drug administration (MDA) with praziquantel in Malawi, and a school-based cross sectional epidemiology survey in Zambia. Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle and negative binomial logit hurdle) were fitted and compared. Using Akaike information criteria (AIC), the negative binomial logit hurdle (NBLH) and zero inflated negative binomial (ZINB) showed best performance in both datasets. With regards to zero count capturing, these models performed better than other models. This paper showed that zero modified NBLH and ZINB models are more appropriate methods for the analysis of data with excess zeros. The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study.

Meta-analyses of the sensitivity and specificity of ante-mortem and post-mortem diagnostic tests for bovine tuberculosis in the UK and Ireland.

PubMed

Nuñez-Garcia, Javier; Downs, Sara H; Parry, Jessica E; Abernethy, Darrell A; Broughan, Jennifer M; Cameron, Angus R; Cook, Alasdair J; de la Rua-Domenech, Ricardo; Goodchild, Anthony V; Gunn, Jane; More, Simon J; Rhodes, Shelley; Rolfe, Simon; Sharp, Michael; Upton, Paul A; Vordermeier, H Martin; Watson, Eamon; Welsh, Michael; Whelan, Adam O; Woolliams, John A; Clifton-Hadley, Richard S; Greiner, Matthias

2018-05-01

Bovine Tuberculosis (bTB) in cattle is a global health problem and eradication of the disease requires accurate estimates of diagnostic test performance to optimize their efficiency. The objective of this study was, through statistical meta-analyses, to obtain estimates of sensitivity (Se) and specificity (Sp), for 14 different ante-mortem and post-mortem diagnostic tests for bTB in cattle. Using data from a systematic review of the scientific literature (published 1934-2009) diagnostic Se and Sp were estimated using Bayesian logistic regression models adjusting for confounding factors. Random effect terms were used to account for unexplained heterogeneity. Parameters in the models were implemented using Markov Chain Monte Carlo (MCMC), and posterior distributions for the diagnostic parameters with adjustment for covariates (confounding factors) were obtained using the inverse logit function. Estimates for Se and/or Sp of the tuberculin skin tests and the IFN-γ blood test were compared with estimates published 2010-2015. Median Se for the single intradermal comparative cervical tuberculin skin (SICCT) test (standard interpretation) was 0.50 and Bayesian credible intervals (CrI) were wide (95% CrI 0.26, 0.78). Median Sp for the SICCT test was 1.00 (95% CrI 0.99, 1.00). Estimates for the IFN-γ blood test Bovine Purified Protein Derivative (PPD)-Avian PPD and Early Secreted Antigen target 6 and Culture Filtrate Protein 10 (ESAT-6/CFP10) ESAT6/CFP10 were 0.67 (95% CrI 0.49, 0.82) and 0.78 (95% CrI 0.60, 0.90) respectively for Se, and 0.98 (95% CrI 0.96, 0.99) and 0.99 (95% CrI 0.99, 1.00) for Sp. The study provides an overview of the accuracy of a range of contemporary diagnostic tests for bTB in cattle. Better understanding of diagnostic test performance is essential for the design of effective control strategies and their evaluation. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Winter weather demand considerations.

DOT National Transportation Integrated Search

2015-04-01

Winter weather has varied effects on travel behavior. Using 418 survey responses from the Northern Virginia : commuting area of Washington, D.C. and binary logit models, this study examines travel related changes under : different types of winter wea...

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

PubMed

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.

Modeling the Effect of Enlarging Seating Room on Passengers' Preference of Taiwan's Domestic Airlines

NASA Technical Reports Server (NTRS)

Lu, Jin-Long; Tsai, Li-Non

2003-01-01

This study addresses the need for measuring the effect of enlarging seating room in airplane on passengers' preferences of airline in Taiwan. The results can assist Taiwan's domestic air carriers in better understanding their customers' expectations. Stated choice experiment is used to incorporate passengers' trade-offs in the preferred measurement, and three major attributes are taken into account in the stated choice experiment: (1) type of seat (enlarged or not), (2) price, and (3) brand names of airlines. Furthermore, a binary logit model is used to model the choice behavior of air passengers. The findings show that the type of seat is a major significant variable; price and airline's brand are also significant as well. It concludes that air carriers should put more emphasis on the issue of improving the quality of seat comfort. Keywords: Passengers' preference, Enlarged seating room, Stated choice experiment, Binary logit model.

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

PubMed

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.

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

PubMed Central

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

Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island.

PubMed

Fienberg, S E; Bromet, E J; Follmann, D; Lambert, D; May, S M

1985-11-01

The accident at the Three Mile Island nuclear power plant in 1979 led to an unprecedented set of events with potentially life threatening implications. This paper focusses on the analysis of a longitudinal study of the psychological well-being of the mothers of young children living within 10 miles of the plant. The initial analyses of the data utilize loglinear/logit model techniques from the contingency table literature, and involve the fitting of a sequence of logit models. The inadequancies of these analyses are noted, and a new class of mixture models for logistic response structures is introduced to overcome the noted shortcomings. The paper includes a brief outline of the methodology relevant for the fitting of these models using the method of maximum likelihood, and then the model is applied to the TMI data. The paper concludes with a discussion of some of the substantive implications of the mixture model analysis.

Patient Preferences for Features of Health Care Delivery Systems: A Discrete Choice Experiment.

PubMed

Mühlbacher, Axel C; Bethge, Susanne; Reed, Shelby D; Schulman, Kevin A

2016-04-01

To estimate the relative importance of organizational-, procedural-, and interpersonal-level features of health care delivery systems from the patient perspective. We designed four discrete choice experiments (DCEs) to measure patient preferences for 21 health system attributes. Participants were recruited through the online patient portal of a large health system. We analyzed the DCE data using random effects logit models. DCEs were performed in which respondents were provided with descriptions of alternative scenarios and asked to indicate which scenario they prefer. Respondents were randomly assigned to one of the three possible health scenarios (current health, new lung cancer diagnosis, or diabetes) and asked to complete 15 choice tasks. Each choice task included an annual out-of-pocket cost attribute. A total of 3,900 respondents completed the survey. The out-of-pocket cost attribute was considered the most important across the four different DCEs. Following the cost attribute, trust and respect, multidisciplinary care, and shared decision making were judged as most important. The relative importance of out-of-pocket cost was consistently lower in the hypothetical context of a new lung cancer diagnosis compared with diabetes or the patient's current health. This study demonstrates the complexity of patient decision making processes regarding features of health care delivery systems. Our findings suggest the importance of these features may change as a function of an individual's medical conditions. © Health Research and Educational Trust.

Improving hand functional use in subjects with multiple sclerosis using a musical keyboard: a randomized controlled trial.

PubMed

Gatti, Roberto; Tettamanti, Andrea; Lambiase, Simone; Rossi, Paolo; Comola, Mauro

2015-06-01

Playing an instrument implies neuroplasticity in different cerebral regions. This phenomenon has been described in subjects with stroke, suggesting that it could play a role in hand rehabilitation. The aim of this study is to analyse the effectiveness of playing a musical keyboard in improving hand function in subjects with multiple sclerosis. Nineteen hospitalized subjects were randomized in two groups: nine played a turned-on musical keyboard by sequences of fingers movements (audio feedback present) and 10 performed the same exercises on a turned-off musical keyboard (audio feedback absent). Training duration was half an hour per day for 15 days. Primary outcome was the perceived hand functional use measured by ABILHAND Questionnaire. Secondary outcomes were hand dexterity, measured by Nine-Hole Peg Test, and hand strength, measured by Jamar and Pinch dynamometers. Two-way analysis of variance was used for data analysis. The interaction time × group was significant (p = 0.003) for ABILHAND Questionnaire in favour of experimental group (mean between-group difference 0.99 logit [IC95%: 0.44; 1.54]). The two groups showed a significant time effect for all outcomes except for Jamar measure. Playing a musical keyboard seems a valid method to train the functional use of hands in subjects with multiple sclerosis. Copyright © 2014 John Wiley & Sons, Ltd.

Calibration and validation of the Physical Activity Barrier Scale for persons who are blind or visually impaired.

PubMed

Lee, Miyoung; Zhu, Weimo; Ackley-Holbrook, Elizabeth; Brower, Diana G; McMurray, Bryan

2014-07-01

It is critical to employ accurate measures when assessing physical activity (PA) barriers in any subpopulation, yet existing measures are not appropriate for persons with blindness or visual impairment (PBVI) due to a lack of validity or reliability evidence. To develop and calibrate a PA barrier scale for PBVI. An expert panel (n = 3) and 18 PBVI were recruited to establish content validity for a PA barriers subscale; 160 PBVI (96 females) completed the scale along with the Physical Activity Scale for Individuals with Physical Disabilities for calibration. To establish construct-related validity evidence, Confirmative factor analysis (CFA) and Rasch analysis were applied. To investigate internal consistency and reliability, Cronbach's alpha and the reliability coefficient (R) were employed, respectively. Following CFA and Rasch analyses, five items were eliminated due to misfits; reliability coefficients were unchanged upon deletion of these items. The barriers perceived by PBVI to have the most negative impact on PA included "lack of self-discipline" (logit = 1.40) and "lack of motivation" (logit = 1.27). "Too many stairs in the exercise facility" (logit = -1.49) was perceived to have the least impact. The newly-developed scale was found to be a valid and reliable tool for evaluating PA barriers in PBVI. To enhance promotion of health-producing levels of PA in PBVI, practitioners should consider applying this new tool as a precursor to programs aimed at improving PA participation in this group. Copyright © 2014 Elsevier Inc. All rights reserved.

Methodologies for Evaluating the Impact of Contraceptive Social Marketing Programs.

ERIC Educational Resources Information Center

Bertrand, Jane T.; And Others

1989-01-01

An overview of the evaluation issues associated with contraceptive social marketing programs is provided. Methodologies covered include survey techniques, cost-effectiveness analyses, retail audits of sales data, time series analysis, nested logit analysis, and discriminant analysis. (TJH)

Impact of First Eye versus Second Eye Cataract Surgery on Visual Function and Quality of Life.

PubMed

Shekhawat, Nakul S; Stock, Michael V; Baze, Elizabeth F; Daly, Mary K; Vollman, David E; Lawrence, Mary G; Chomsky, Amy S

2017-10-01

To compare the impact of first eye versus second eye cataract surgery on visual function and quality of life. Cohort study. A total of 328 patients undergoing separate first eye and second eye phacoemulsification cataract surgeries at 5 veterans affairs centers in the United States. Patients with previous ocular surgery, postoperative endophthalmitis, postoperative retinal detachment, reoperation within 30 days, dementia, anxiety disorder, hearing difficulty, or history of drug abuse were excluded. Patients received complete preoperative and postoperative ophthalmic examinations for first eye and second eye cataract surgeries. Best-corrected visual acuity (BCVA) was measured 30 to 90 days preoperatively and postoperatively. Patients completed the National Eye Institute Visual Functioning Questionnaire (NEI-VFQ) 30 to 90 days preoperatively and postoperatively. The NEI-VFQ scores were calculated using a traditional subscale scoring algorithm and a Rasch-refined approach producing visual function and socioemotional subscale scores. Postoperative NEI-VFQ scores and improvement in NEI-VFQ scores comparing first eye versus second eye cataract surgery. Mean age was 70.4 years (±9.6 standard deviation [SD]). Compared with second eyes, first eyes had worse mean preoperative BCVA (0.55 vs. 0.36 logarithm of the minimum angle of resolution (logMAR), P < 0.001), greater mean BCVA improvement after surgery (-0.50 vs. -0.32 logMAR, P < 0.001), and slightly worse postoperative BCVA (0.06 vs. 0.03 logMAR, P = 0.039). Compared with first eye surgery, second eye surgery resulted in higher postoperative NEI-VFQ scores for nearly all traditional subscales (P < 0.001), visual function subscale (-3.85 vs. -2.91 logits, P < 0.001), and socioemotional subscale (-2.63 vs. -2.10 logits, P < 0.001). First eye surgery improved visual function scores more than second eye surgery (-2.99 vs. -2.67 logits, P = 0.021), but both first and second eye surgeries resulted in similar improvements in socioemotional scores (-1.62 vs. -1.51 logits, P = 0.255). Second eye cataract surgery improves visual function and quality of life well beyond levels achieved after first eye cataract surgery alone. For certain socioemotional aspects of quality of life, second eye cataract surgery results in comparable improvement to first eye cataract surgery. Copyright © 2017 American Academy of Ophthalmology. All rights reserved.

Modeling pattern in collections of parameters

USGS Publications Warehouse

Link, W.A.

1999-01-01

Wildlife management is increasingly guided by analyses of large and complex datasets. The description of such datasets often requires a large number of parameters, among which certain patterns might be discernible. For example, one may consider a long-term study producing estimates of annual survival rates; of interest is the question whether these rates have declined through time. Several statistical methods exist for examining pattern in collections of parameters. Here, I argue for the superiority of 'random effects models' in which parameters are regarded as random variables, with distributions governed by 'hyperparameters' describing the patterns of interest. Unfortunately, implementation of random effects models is sometimes difficult. Ultrastructural models, in which the postulated pattern is built into the parameter structure of the original data analysis, are approximations to random effects models. However, this approximation is not completely satisfactory: failure to account for natural variation among parameters can lead to overstatement of the evidence for pattern among parameters. I describe quasi-likelihood methods that can be used to improve the approximation of random effects models by ultrastructural models.

Superstition, witchcraft and HIV prevention in sub-Saharan Africa: the case of Ghana.

PubMed

Tenkorang, Eric Y; Gyimah, Stephen O; Maticka-Tyndale, Eleanor; Adjei, Jones

2011-10-01

Belief in superstition and witchcraft is central to many African conceptions of illness, disease causation and etiology. While a number of anthropological studies have alluded to a theoretical link between such beliefs and HIV prevention in particular, there is limited empirical assessment of the association. Using data from the 2008 Ghana Demographic and Health Survey and applying random-effects logit models, we investigate whether the belief that AIDS can spread through witchcraft associates with the sexual decision making of never-married men and women. The results show that men who believed AIDS can spread through witchcraft and other supernatural means were less likely to have used condoms at last sexual intercourse, controlling for other socioeconomic and cultural variables. Women with similar beliefs were more likely to have experienced sexual intercourse but less likely to have used condoms at last sex. For women, however, the relationship between such superstitious beliefs and condom use was somewhat attenuated after controlling for ethnicity and region of residence. From a policy perspective, the findings suggest that local beliefs regarding AIDS causation must be considered in designing HIV/AIDS programmes and interventions.

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

PubMed

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.

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

PubMed Central

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

2010-01-01

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% female respondents ever consumed alcohol. Males reporting sexual behaviors (vaginal, anal, oral sex) had a significantly higher calculated peak BAC of 0.151 compared to 0.082 for males reporting no sexual intimacy (p < .0001). Females reporting sexual behaviors had a peak BAC of 0.072 compared to 0.027 for those reporting no sexual intimacy (p = .016). Fifty percent of (33/66) males and 30.4% (7/23) females report event specific drinking and engagement in sexual behaviors. Males reporting 11+ drinks in 30 days had more sexual partners than those reporting 1 to 10 drinks (p = .037). Data suggest different physical and psychosocial mediators between alcohol consumption and sexual behaviors by gender. PMID:21373363

Water system unreliability and diarrhea incidence among children in Guatemala.

PubMed

Trudeau, Jennifer; Aksan, Anna-Maria; Vásquez, William F

2018-03-01

This article examines the effect of water system unreliability on diarrhea incidence among children aged 0-5 in Guatemala. We use secondary data from a nationally representative sample of 7579 children to estimate the effects of uninterrupted and interrupted water services on diarrhea incidence. The national scope of this study imposes some methodological challenges due to unobserved geographical heterogeneity. To address this issue, we estimate mixed-effects logit models that control for unobserved heterogeneity by estimating random effects of selected covariates that can vary across geographical areas (i.e. water system reliability). Compared to children without access to piped water, children with uninterrupted water services have a lower probability of diarrhea incidence by approximately 33 percentage points. Conversely, there is no differential effect between children without access and those with at least one day of service interruptions in the previous month. Results also confirm negative effects of age, female gender, spanish language, and garbage disposal on diarrhea incidence. Public health benefits of piped water are realized through uninterrupted provision of service, not merely access. Policy implications are discussed.

Integrating geographic information systems and remote sensing with spatial econometric and mixed logit models for environmental valuation

NASA Astrophysics Data System (ADS)

Wells, Aaron Raymond

This research focuses on the Emory and Obed Watersheds in the Cumberland Plateau in Central Tennessee and the Lower Hatchie River Watershed in West Tennessee. A framework based on market and nonmarket valuation techniques was used to empirically estimate economic values for environmental amenities and negative externalities in these areas. The specific techniques employed include a variation of hedonic pricing and discrete choice conjoint analysis (i.e., choice modeling), in addition to geographic information systems (GIS) and remote sensing. Microeconomic models of agent behavior, including random utility theory and profit maximization, provide the principal theoretical foundation linking valuation techniques and econometric models. The generalized method of moments estimator for a first-order spatial autoregressive function and mixed logit models are the principal econometric methods applied within the framework. The dissertation is subdivided into three separate chapters written in a manuscript format. The first chapter provides the necessary theoretical and mathematical conditions that must be satisfied in order for a forest amenity enhancement program to be implemented. These conditions include utility, value, and profit maximization. The second chapter evaluates the effect of forest land cover and information about future land use change on respondent preferences and willingness to pay for alternative hypothetical forest amenity enhancement options. Land use change information and the amount of forest land cover significantly influenced respondent preferences, choices, and stated willingness to pay. Hicksian welfare estimates for proposed enhancement options ranged from 57.42 to 25.53, depending on the policy specification, information level, and econometric model. The third chapter presents economic values for negative externalities associated with channelization that affect the productivity and overall market value of forested wetlands. Results of robust, generalized moments estimation of a double logarithmic first-order spatial autoregressive error model (inverse distance weights with spatial dependence up to 1500m) indicate that the implicit cost of damages to forested wetlands caused by channelization equaled -$5,438 ha-1. Collectively, the results of this dissertation provide economic measures of the damages to and benefits of environmental assets, help private landowners and policy makers identify the amenity attributes preferred by the public, and improve the management of natural resources.

What factors drive heterogeneity of preferences for micro-health insurance in rural Malawi?

PubMed

Abiiro, Gilbert Abotisem; Torbica, Aleksandra; Kwalamasa, Kassim; De Allegri, Manuela

2016-11-01

Investigating the factors that drive differences in preferences for health insurance products among rural populations is a relevant policy issue that has so far received little attention. This study used a discrete choice experiment to explore heterogeneity of preferences for a prospective micro-health insurance (MHI) product in Malawi. Through an extensive qualitative study, six attributes, each associated with three levels, were derived and used to construct a D-efficient design. The attributes included unit of enrollment, management structure, health service benefit package, copayment levels, transportation coverage and monthly premium. The experiment was interviewer administered to a stratified random sample of household heads and their spouse(s). Using mixed logit and generalized multinomial logit models, respondent characteristics were interacted with MHI attributes to explore heterogeneity of preferences. The results showed that those in the higher age group (≥55 years) and those from households with higher household expenditure had significantly higher preferences for comprehensive and medium benefit packages than for a basic package. Those from households that incurred any healthcare expenditure within the past 4 weeks had lower preferences for the core family as a unit of enrollment than the individual, and higher preferences for coverage of transport costs. Women and non-micro-finance members had higher preferences for 25% copayment than for 50% copayment. There was evidence of scale heterogeneity signifying that the observed preference variations could have resulted from scale and variance differences, rather than real variations in the taste of respondents. To attract the relatively older and wealthier, prospective MHI should offer comprehensive health services benefit packages. Premium exemptions or subsidies should also be offered to the poor. Lower copayments can provide an incentive for women and non-micro-finance members, whilst coverage of transport costs can also attract those with recent history of incurring out-of-pocket healthcare expenditure to accept MHI. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

How to determine an optimal threshold to classify real-time crash-prone traffic conditions?

PubMed

Yang, Kui; Yu, Rongjie; Wang, Xuesong; Quddus, Mohammed; Xue, Lifang

2018-08-01

One of the proactive approaches in reducing traffic crashes is to identify hazardous traffic conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold selection is one of the essential steps of real-time crash prediction. And it provides the cut-off point for the posterior probability which is used to separate potential crash warnings against normal traffic conditions, after the outcome of the probability of a crash occurring given a specific traffic condition on the basis of crash risk evaluation models. There is however a dearth of research that focuses on how to effectively determine an optimal threshold. And only when discussing the predictive performance of the models, a few studies utilized subjective methods to choose the threshold. The subjective methods cannot automatically identify the optimal thresholds in different traffic and weather conditions in real application. Thus, a theoretical method to select the threshold value is necessary for the sake of avoiding subjective judgments. The purpose of this study is to provide a theoretical method for automatically identifying the optimal threshold. Considering the random effects of variable factors across all roadway segments, the mixed logit model was utilized to develop the crash risk evaluation model and further evaluate the crash risk. Cross-entropy, between-class variance and other theories were employed and investigated to empirically identify the optimal threshold. And K-fold cross-validation was used to validate the performance of proposed threshold selection methods with the help of several evaluation criteria. The results indicate that (i) the mixed logit model can obtain a good performance; (ii) the classification performance of the threshold selected by the minimum cross-entropy method outperforms the other methods according to the criteria. This method can be well-behaved to automatically identify thresholds in crash prediction, by minimizing the cross entropy between the original dataset with continuous probability of a crash occurring and the binarized dataset after using the thresholds to separate potential crash warnings against normal traffic conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Four classes of interactions for evolutionary games.

PubMed

Szabó, György; Bodó, Kinga S; Allen, Benjamin; Nowak, Martin A

2015-08-01

The symmetric four-strategy games are decomposed into a linear combination of 16 basis games represented by orthogonal matrices. Among these basis games four classes can be distinguished as it is already found for the three-strategy games. The games with self-dependent (cross-dependent) payoffs are characterized by matrices consisting of uniform rows (columns). Six of 16 basis games describe coordination-type interactions among the strategy pairs and three basis games span the parameter space of the cyclic components that are analogous to the rock-paper-scissors games. In the absence of cyclic components the game is a potential game and the potential matrix is evaluated. The main features of the four classes of games are discussed separately and we illustrate some characteristic strategy distributions on a square lattice in the low noise limit if logit rule controls the strategy evolution. Analysis of the general properties indicates similar types of interactions at larger number of strategies for the symmetric matrix games.

The compression of deaths above the mode.

PubMed

Thatcher, A Roger; Cheung, Siu Lan K; Horiuchi, Shiro; Robine, Jean-Marie

2010-03-26

Kannisto (2001) has shown that as the frequency distribution of ages at death has shifted to the right, the age distribution of deaths above the modal age has become more compressed. In order to further investigate this old-age mortality compression, we adopt the simple logistic model with two parameters, which is known to fit data on old-age mortality well (Thatcher 1999). Based on the model, we show that three key measures of old-age mortality (the modal age of adult deaths, the life expectancy at the modal age, and the standard deviation of ages at death above the mode) can be estimated fairly accurately from death rates at only two suitably chosen high ages (70 and 90 in this study). The distribution of deaths above the modal age becomes compressed when the logits of death rates fall more at the lower age than at the higher age. Our analysis of mortality time series in six countries, using the logistic model, endorsed Kannisto's conclusion. Some possible reasons for the compression are discussed.

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

PubMed

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

2015-08-18

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

[The importance of memory bias in obtaining age of menarche by recall method in Brazilian adolescents].

PubMed

Castilho, Silvia Diez; Nucci, Luciana Bertoldi; Assuino, Samanta Ramos; Hansen, Lucca Ortolan

2014-06-01

To compare the age at menarche obtained by recall method according to the time elapsed since the event, in order to verify the importance of the recall bias. Were evaluated 1,671 girls (7-18 years) at schools in Campinas-SP regarding the occurrence of menarche by the status quo method (menarche: yes or no) and the recall method (date of menarche, for those who mentioned it). The age at menarche obtained by the status quo method was calculated by logit, which considers the whole group, and the age obtained by the recall method was calculated as the average of the mentioned age at menarche. In this group, the age at menarche was obtained by the difference between the date of the event and the date of birth. Girls who reported menarche (883, 52.8%) were divided into four groups according to the time elapsed since the event. To analyze the results, we used ANOVA and logistic regression for the analysis, with a significance level of 0.05. The age at menarche calculated by logit was 12.14 y/o (95% CI 12.08 to 12.20). Mean ages obtained by recall were: for those who experienced menarche within the previous year 12.26 y/o (±1.14), between > 1-2 years before, 12.29 y (±1.22); between > 2-3 years before, 12.23 y/o (±1.27); and more than 3 years before, 11.55y/o (±1.24), p < 0.001. The age at menarche obtained by the recall method was similar for girls who menstruated within the previous 3 years (and approaches the age calculated by logit); when more than 3 years have passed, the recall bias was significant.

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

NASA Technical Reports Server (NTRS)

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

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

PubMed

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

2011-08-05

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

Economic Evaluation of Low-Vision Rehabilitation for Veterans With Macular Diseases in the US Department of Veterans Affairs.

PubMed

Stroupe, Kevin T; Stelmack, Joan A; Tang, X Charlene; Wei, Yongliang; Sayers, Scott; Reda, Domenic J; Kwon, Ellen; Massof, Robert W

2018-05-01

Examining costs and consequences of different low-vision (LV) programs provides important information about resources needed to expand treatment options efficiently. To examine the costs and consequences of LV rehabilitation or basic LV services. The US Department of Veterans Affairs (VA) Low Vision Intervention Trial (LOVIT) II was conducted from September 27, 2010, to July 31, 2014, at 9 VA facilities and included 323 veterans with macular diseases and a best-corrected distance visual acuity of 20/50 to 20/200. Veterans were randomized to receive basic LV services that provided LV devices without therapy, or LV rehabilitation that added a therapist to LV services who provided instruction and homework on using LV devices, eccentric viewing, and environmental modification. We compared costs and consequences between these groups. Low-vision devices without therapy and LV devices with therapy. Costs of providing basic LV services or LV rehabilitation were assessed. We measured consequences as changes in functional visual ability from baseline to follow-up 4 months after randomization using the VA Low Vision Visual Functioning Questionnaire. Visual ability was measured in dimensionless log odds units (logits). Of 323 randomized patients, the mean (SD) age was 80 (10.5) years, 314 (97.2%) were men, and 292 (90.4%) were white. One hundred sixty (49.5%) received basic LV services and 163 (50.1%) received LV rehabilitation. The mean (SD) total direct health care costs per patient were similar between patients who were randomized to receive basic LV services ($1662 [$671]) or LV rehabilitation ($1788 [$864]) (basic LV services, $126 lower; 95% CI, $299 lower to $35 higher; P = .15). However, basic LV services required less time and had lower transportation costs. Patients receiving LV rehabilitation had greater improvements in overall visual ability, reading ability, visual information processing, and visual motor skill scores.

Employment and paid work among participants in a randomized controlled trial comparing diacetylmorphine and hydromorphone.

PubMed

Nikoo, Mohammadali; Vogel, Marc; Choi, Fiona; Song, Michael J; Burghardt, Jensen; Zafari, Zafar; Tabi, Katarina; Frank, Anastasia; Barbic, Skye; Schütz, Christian; Jang, Kerry; Krausz, Michael

2018-04-12

Employment is one of the less studied but a significant outcome of medication-assisted treatment. Thus, we aimed to explore employment outcomes of medication-assisted treatment with hydromorphone (HDM) or diacetylmorphine (DAM). The secondary aim was to estimate characteristics of this population as well as treatment-related factors associated with these outcomes. This was a secondary analysis of a randomized, double blind controlled trial. A total of 102 and 100 participants were randomized to receive injectable DAM or HDM for 6 months respectively. In stage 2, 144 participants were randomized again to receive either oral or injectable forms of the medication they received for another 6 months. Participants were interviewed at 5 timepoints: before and 3, 6, 9 and 12 months after treatment assignment. Generalized estimating equations (GEE) with a logit link was fitted to determine factors related to paid work in the past 30 days. Mean age of participants was 44.3 (SD = 9.6) and 59 (29.2%) participants were men. At each timepoint, 6-8 (3.6%-4.1%) participants reported employment in the past 30 days and 40 to 52 (19.7%-26.7%) reported minimum 1 day of paid work. University or college education [OR = 2.12: 95% CI = (1.25, 3.62), P = 0.01] was significantly associated with paid work after adjustment for age, gender, treatment arms, timepoints, days receiving study treatment, physical health, psychological health and crack cocaine use in the past 30 days. The rate of employment was lower among participants of this study compared to similar studies on heroin-assisted treatment. Higher education was associated with increased odds of paid work. A large gap exists between employment rate and the proportion of participants who reported paid work. Supported employment and occupational therapy could optimize the employment outcomes of this population. Copyright © 2018 Elsevier B.V. All rights reserved.

Anger and Desire for Retribution among Bereaved Parents.

ERIC Educational Resources Information Center

Drenovsky, Cynthia K.

1994-01-01

Logit results show suddenness of death contributes to likelihood parent will feel anger while anticipatory socialization to death or recency of death decreases odds of feeling anger toward child. All variables decrease likelihood parents will feel desire to punish someone for death of child. (BF)

Dropout from Secondary Education: All's Well That Begins Well

ERIC Educational Resources Information Center

De Witte, Kristof; Rogge, Nicky

2013-01-01

Despite the increased attention to students leaving secondary education without a diploma numerous students still dropout yearly. This paper makes a distinction between the "individual perspective" and the "institutional perspective" of dropping out. The former is explored by multinominal logit models. We observe that…

Community forestry as perceived by local people around Cross River National Park, Nigeria.

PubMed

Ezebilo, Eugene E

2012-01-01

The prior identification of local people's preferences for conservation-development projects will help gear nature-conservation strategies toward the needs of different groups of local people. This will help policy-makers in designing a more acceptable and effective conservation strategy. This article reports a study of local perceptions of a community forestry project that aims to help improve the design as well as local acceptance of the project. The data originated from personal interviews conducted in communities around Okwangwo Division of the Cross River National Park in southeast Nigeria and were analysed using ordered logit and binary logit models. The results showed that >50% of the respondents were satisfied with the community forestry project. The respondents' perceptions were mainly influenced by education, age, gender, and willingness to contribute money to tourism as well as the contributions of cocoa, banana, and afang (Gnetum africanum) to the respondents' income. The results from this study have important implications for nature conservation in Nigeria and potentially other conservation contexts across the developing world.

Community Forestry as Perceived by Local People Around Cross River National Park, Nigeria

NASA Astrophysics Data System (ADS)

Ezebilo, Eugene E.

2012-01-01

The prior identification of local people's preferences for conservation-development projects will help gear nature-conservation strategies toward the needs of different groups of local people. This will help policy-makers in designing a more acceptable and effective conservation strategy. This article reports a study of local perceptions of a community forestry project that aims to help improve the design as well as local acceptance of the project. The data originated from personal interviews conducted in communities around Okwangwo Division of the Cross River National Park in southeast Nigeria and were analysed using ordered logit and binary logit models. The results showed that >50% of the respondents were satisfied with the community forestry project. The respondents' perceptions were mainly influenced by education, age, gender, and willingness to contribute money to tourism as well as the contributions of cocoa, banana, and afang ( Gnetum africanum) to the respondents' income. The results from this study have important implications for nature conservation in Nigeria and potentially other conservation contexts across the developing world.

Willingness to Pay for Improving the Residential Waste Disposal System in Korea: A Choice Experiment Study

NASA Astrophysics Data System (ADS)

Ku, Se-Ju; Yoo, Seung-Hoon; Kwak, Seung-Jun

2009-08-01

This study attempts to apply choice experiments with regard to the residential waste disposal system (RWDS) in Korea by considering various attributes that are related to RWDS. Using data from a survey conducted on 492 households, the empirical analysis yields estimates of the willingness to pay for a clean food-waste collection facility, the collection of small items (such as obsolete mobile phones and add-ons for personal computers), and a more convenient large waste disposal system. The estimation results of multinomial logit models are quite similar to those of nested logit models. The results reveal that residents have preferences for the cleanliness of facilities and the collection of small items. In Korea, residents are required to purchase and attach stickers for the disposal of large items; they want to be able to obtain stickers at not only village offices but also supermarkets. On the other hand, the frequency of waste collection is not a significant factor in the choice of the improved waste management program.

Reviews Equipment: Data logger Book: Imagined Worlds Equipment: Mini data loggers Equipment: PICAXE-18M2 data logger Books: Engineering: A Very Short Introduction and To Engineer Is Human Book: Soap, Science, & Flat-Screen TVs Equipment: uLog and SensorLab Web Watch

NASA Astrophysics Data System (ADS)

2012-07-01

WE RECOMMEND Data logger Fourier NOVA LINK: data logging and analysis To Engineer is Human Engineering: essays and insights Soap, Science, & Flat-Screen TVs People, politics, business and science overlap uLog sensors and sensor adapter A new addition to the LogIT range offers simplicity and ease of use WORTH A LOOK Imagined Worlds Socio-scientific predictions for the future Mini light data logger and mini temperature data logger Small-scale equipment for schools SensorLab Plus LogIT's supporting software, with extra features HANDLE WITH CARE CAXE110P PICAXE-18M2 data logger Data logger 'on view' but disappoints Engineering: A Very Short Introduction A broad-brush treatment fails to satisfy WEB WATCH Two very different websites for students: advanced physics questions answered and a more general BBC science resource

Application of LogitBoost Classifier for Traceability Using SNP Chip Data

PubMed Central

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. PMID:26436917

Application of LogitBoost Classifier for Traceability Using SNP Chip Data.

PubMed

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.

Willingness to pay for improving the residential waste disposal system in Korea: a choice experiment study.

PubMed

Ku, Se-Ju; Yoo, Seung-Hoon; Kwak, Seung-Jun

2009-08-01

This study attempts to apply choice experiments with regard to the residential waste disposal system (RWDS) in Korea by considering various attributes that are related to RWDS. Using data from a survey conducted on 492 households, the empirical analysis yields estimates of the willingness to pay for a clean food-waste collection facility, the collection of small items (such as obsolete mobile phones and add-ons for personal computers), and a more convenient large waste disposal system. The estimation results of multinomial logit models are quite similar to those of nested logit models. The results reveal that residents have preferences for the cleanliness of facilities and the collection of small items. In Korea, residents are required to purchase and attach stickers for the disposal of large items; they want to be able to obtain stickers at not only village offices but also supermarkets. On the other hand, the frequency of waste collection is not a significant factor in the choice of the improved waste management program.

Compensation of hospital-based physicians.

PubMed Central

Steinwald, B

1983-01-01

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

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

PubMed

Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D

2017-01-01

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

Random Item IRT Models

ERIC Educational Resources Information Center

De Boeck, Paul

2008-01-01

It is common practice in IRT to consider items as fixed and persons as random. Both, continuous and categorical person parameters are most often random variables, whereas for items only continuous parameters are used and they are commonly of the fixed type, although exceptions occur. It is shown in the present article that random item parameters…

Predicting juvenile recidivism: new method, old problems.

PubMed

Benda, B B

1987-01-01

This prediction study compared three statistical procedures for accuracy using two assessment methods. The criterion is return to a juvenile prison after the first release, and the models tested are logit analysis, predictive attribute analysis, and a Burgess procedure. No significant differences are found between statistics in prediction.

Choice-Based Segmentation as an Enrollment Management Tool

ERIC Educational Resources Information Center

Young, Mark R.

2002-01-01

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

Palliative radiotherapy practice within Western European countries: impact of the radiotherapy financing system?

PubMed

Lievens, Y; Van den Bogaert, W; Rijnders, A; Kutcher, G; Kesteloot, K

2000-09-01

To analyze the reimbursement modalities for radiotherapy in the different Western European countries, as well as to investigate if these differences have an impact on the palliative radiotherapy practice for bone metastases. A questionnaire was sent to 565 radiotherapy centres included in the 1997 ESTRO directory. In this questionnaire the reimbursement strategy applied in the different centres was assessed, with respect to the use of a budget (departmental or hospital budget), case payment and/or fee-for-service reimbursement. The differences were analyzed according to country and to type and size of the radiotherapy centre. A total of 170 centres (86% of the responders) returned the questionnaire. Most frequent is budget reimbursement: some form of budget reimbursement is found in 69% of the centres, whereas 46% of the centres are partly reimbursed through fee-for-service and 35% through case payment. The larger the department, the more frequent the reimbursement through a budget or a case payment system and the less the importance of fee-for-service reimbursement (chi(2): P=0.0012; logit: P=0.0055). Whereas private centres are almost equally reimbursed by fee-for-service financing as by budget or case payment, radiotherapy departments in university hospitals receive the largest part of their financial resources through a budget or by case payment (83%) (chi(2): P=0.002; logit: P=0.0073). A correlation between the country and the radiotherapy reimbursement system was also demonstrated (P=0.002), radiotherapy centres in Spain, the Netherlands and the United Kingdom being almost entirely reimbursed through a budget and/or case payment and centres in Germany and Switzerland mostly through a fee-for-service system. In budget and case payment financing lower total number of fractions and lower total dose (chi(2): P=0.003; logit: P=0.0120) as well as less shielding blocks (chi(2): P=0.003; logit: P=0.0066) are used. A same tendency is found for the use of isodose calculations and field set-up, but without being statistically significant (P=0.264 and P=0.061 res.). The type of the centre and the reimbursement modality influence the fractionation regimen independently (P=0.0274). This is not the case for the centre size and the reimbursement, which were found to exert correlated effects on the fractionation schedule (P=0.1042). Reimbursement systems seem to influence radiotherapy practice. One should therefore aim to develop reimbursement criteria that pursue to deliver, not only the best qualitative, but also the most cost-effective treatments to the patients.

Effect of pill burden on dosing preferences, willingness to pay, and likely adherence among patients with type 2 diabetes

PubMed Central

Hauber, A Brett; Han, Steven; Yang, Jui-Chen; Gantz, Ira; Tunceli, Kaan; Gonzalez, Juan Marcos; Brodovicz, Kimberly; Alexander, Charles M; Davies, Michael; Iglay, Kristy; Zhang, Qiaoyi; Radican, Larry

2013-01-01

Purpose To quantify willingness-to-pay (WTP) for reducing pill burden and dosing frequency among patients with type 2 diabetes mellitus (T2DM), and to examine the effect of dosing frequency and pill burden on likely medication adherence. Patients and methods Participants were US adults with T2DM on oral antihyperglycemic therapy. Each patient completed an online discrete-choice experiment (DCE) with eight choice questions, each including a pair of hypothetical medication profiles. Each profile was defined by reduction in average glucose (AG), daily dosing, chance of mild-to-moderate stomach problems, frequency of hypoglycemia, weight change, incremental risk of congestive heart failure (CHF), and cost. Patients were asked to rate their likely adherence to the profiles presented in each question. Choice questions were based on a predetermined experimental design. Choice data were analyzed using random-parameters logit. Likely treatment adherence was analyzed using a Heckman two-stage model. Results Of the 1,114 patients who completed the survey, 90 had lower dosing burden (<5 pills/day taken once/day or as needed) for all medications, and 1,024 had higher dosing burden (≥5 pills/day or more than once/day). Reduction in AG was valued most highly by patients. Hypoglycemia, chance of mild-to-moderate stomach problems, weight change, incremental risk of CHF, and daily dosing were less valued. Patients with higher current dosing burden had lower WTP for more convenient dosing schedules than patients with lower current dosing burden. Changes in dosing and cost impacted likely adherence. The magnitude of the impact of dosing on likely adherence was higher for patients with lower current dosing burden than for patients with higher current dosing burden. Conclusion Patients with T2DM were willing to pay for improvements in efficacy, side effects, and dosing. Patients’ WTP for more convenient dosing depended on current dosing burden, as did the effect of these attributes on likely adherence. PMID:24086104

German travelers' preferences for travel vaccines assessed by a discrete choice experiment.

PubMed

Poulos, Christine; Curran, Desmond; Anastassopoulou, Anastassia; De Moerlooze, Laurence

2018-02-08

Many travelers to regions with endemic infectious diseases do not follow health authorities' recommendations regarding vaccination against vaccine-preventable infectious diseases, before traveling. The determinants of individual travelers' decisions to vaccinate before traveling are largely unknown. This study aimed to provide this information using a discrete choice experiment (DCE) administered to four types of German travelers: (1) business travelers; (2) travelers visiting friends and relatives (VFR); (3) leisure travelers; and (4) backpackers. A DCE survey was developed, pretested and administered online. It included a series of choice questions in which respondents chose between two hypothetical vaccines, each characterized by four disease attributes with varying levels describing the of risk, health impact, curability and transmissibility of the disease they would prevent (described with four disease attributes with varying levels of risk, health impact, curability and transmissibility), and varying levels of four vaccine attributes (duration of protection, number of doses required, time required for vaccination, and vaccine cost). A random-parameters logit model was used to estimate the importance weights each traveler type placed on the various attribute levels. These weights were used to calculate mean monetary equivalents (MMEs) of changes in each attribute (holding all others constant) and of hypothetical disease-vaccine combinations. All traveler types' choices indicated that they attached the greatest importance to the risk and health impact of disease and to the vaccine cost whereas the other disease and vaccine attributes were less important for their decisions about travel vaccines. An option of not choosing any of the vaccine-pairs presented was rarely selected indicating that travelers' generally prefer to be vaccinated rather than not. The MMEs of changes in vaccine attributes indicated a very high variability between the individual travelers within each type. The travelers' responses indicated strong preferences for selecting vaccination rather than opting out of vaccination, and disease risk, health impact and vaccine cost were the most important features for vaccine choice. Copyright © 2018. Published by Elsevier Ltd.

A discrete-choice experiment to determine patient preferences for injectable multiple sclerosis treatments in Germany.

PubMed

Poulos, Christine; Kinter, Elizabeth; Yang, Jui-Chen; Bridges, John F P; Posner, Joshua; Gleißner, Erika; Mühlbacher, Axel; Kieseier, Bernd

2016-03-01

The aim of this study was to assess the relative importance of features of a hypothetical injectable disease-modifying treatment for patients with multiple sclerosis using a discrete-choice experiment. German residents at least 18 years of age with a self-reported physician diagnosis of multiple sclerosis completed a 25-30 minute online discrete-choice experiment. Patients were asked to choose one of two hypothetical injectable treatments for multiple sclerosis, defined by different levels of six attributes (disability progression, the number of relapses in the next 4 years, injection time, frequency of injections, presence of flu-like symptoms, and presence of injection-site reactions). The data were analyzed using a random-parameters logit model. Of 202 adults who completed the survey, results from 189 were used in the analysis. Approximately 50% of all patients reported a diagnosis of relapsing-remitting multiple sclerosis, and 31% reported secondary progressive multiple sclerosis. Approximately 71% of patients had current or prior experience with injectable multiple sclerosis medication. Approximately 53% had experienced flu-like symptoms caused by their medication, and 47% had experienced mild injection-site reactions. At least one significant difference was seen between levels in all attributes, except injection time. The greatest change in relative importance between levels of an attribute was years until symptoms get worse from 1 to 4 years. The magnitude of this difference was about twice that of relapses in the next 4 years, frequency of injections, and flu-like symptoms. Most attributes examined in this experiment had an influence on patient preference. Patients placed a significant value on improvements in the frequency of dosing and disability progression. Results suggest that changes in injection frequency can be as important as changes in efficacy and safety attributes. Understanding which attributes of injectable therapies influence patient preference could potentially improve outcomes and adherence in patients with multiple sclerosis.

Modeling avian abundance from replicated counts using binomial mixture models

USGS Publications Warehouse

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

2005-01-01

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

Young People’s Preferences for Family Planning Service Providers in Rural Malawi: A Discrete Choice Experiment

PubMed Central

Michaels-Igbokwe, Christine; Terris-Prestholt, Fern; Lagarde, Mylene; Chipeta, Effie; Cairns, John

2015-01-01

Objective To quantify the impact of service provider characteristics on young people’s choice of family planning (FP) service provider in rural Malawi in order to identify strategies for increasing access and uptake of FP among youth. Methods and Findings A discrete choice experiment was developed to assess the relative impact of service characteristics on preferences for FP service providers among young people (aged 15–24). Four alternative providers were included (government facility, private facility, outreach and community based distribution of FP) and described by six attributes (the distance between participants’ home and the service delivery point, frequency of service delivery, waiting time at the facility, service providers’ attitude, availability of FP commodities and price). A random parameters logit model was used to estimate preferences for service providers and the likely uptake of services following the expansion of outreach and community based distribution (CBDA) services. In the choice experiment young people were twice as likely to choose a friendly provider (government service odds ratio [OR] = 2.45, p<0.01; private service OR = 1.99, p<0.01; CBDA OR = 1.88, p<0.01) and more than two to three times more likely to choose a provider with an adequate supply of FP commodities (government service OR = 2.48, p<0.01; private service OR = 2.33, p<0.01; CBDA = 3.85, p<0.01). Uptake of community based services was greater than facility based services across a variety of simulated service scenarios indicating that such services may be an effective means of expanding access for youth in rural areas and an important tool for increasing service uptake among youth. Conclusions Ensuring that services are acceptable to young people may require additional training for service providers in order to ensure that all providers are friendly and non-judgemental when dealing with younger clients and to ensure that supplies are consistently available. PMID:26630492

Differentiating between Glioblastoma and Primary CNS Lymphoma Using Combined Whole-tumor Histogram Analysis of the Normalized Cerebral Blood Volume and the Apparent Diffusion Coefficient.

PubMed

Bao, Shixing; Watanabe, Yoshiyuki; Takahashi, Hiroto; Tanaka, Hisashi; Arisawa, Atsuko; Matsuo, Chisato; Wu, Rongli; Fujimoto, Yasunori; Tomiyama, Noriyuki

2018-05-31

This study aimed to determine whether whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) and apparent diffusion coefficient (ADC) for contrast-enhancing lesions can be used to differentiate between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL). From 20 patients, 9 with PCNSL and 11 with GBM without any hemorrhagic lesions, underwent MRI, including diffusion-weighted imaging and dynamic susceptibility contrast perfusion-weighted imaging before surgery. Histogram analysis of nCBV and ADC from whole-tumor voxels in contrast-enhancing lesions was performed. An unpaired t-test was used to compare the mean values for each type of tumor. A multivariate logistic regression model (LRM) was performed to classify GBM and PCNSL using the best parameters of ADC and nCBV. All nCBV histogram parameters of GBMs were larger than those of PCNSLs, but only average nCBV was statistically significant after Bonferroni correction. Meanwhile, ADC histogram parameters were also larger in GBM compared to those in PCNSL, but these differences were not statistically significant. According to receiver operating characteristic curve analysis, the nCBV average and ADC 25th percentile demonstrated the largest area under the curve with values of 0.869 and 0.838, respectively. The LRM combining these two parameters differentiated between GBM and PCNSL with a higher area under the curve value (Logit (P) = -21.12 + 10.00 × ADC 25th percentile (10 -3 mm 2 /s) + 5.420 × nCBV mean, P < 0.001). Our results suggest that whole-tumor histogram analysis of nCBV and ADC combined can be a valuable objective diagnostic method for differentiating between GBM and PCNSL.

Estimating riparian understory vegetation cover with beta regression and copula models

USGS Publications Warehouse

Eskelson, Bianca N.I.; Madsen, Lisa; Hagar, Joan C.; Temesgen, Hailemariam

2011-01-01

Understory vegetation communities are critical components of forest ecosystems. As a result, the importance of modeling understory vegetation characteristics in forested landscapes has become more apparent. Abundance measures such as shrub cover are bounded between 0 and 1, exhibit heteroscedastic error variance, and are often subject to spatial dependence. These distributional features tend to be ignored when shrub cover data are analyzed. The beta distribution has been used successfully to describe the frequency distribution of vegetation cover. Beta regression models ignoring spatial dependence (BR) and accounting for spatial dependence (BRdep) were used to estimate percent shrub cover as a function of topographic conditions and overstory vegetation structure in riparian zones in western Oregon. The BR models showed poor explanatory power (pseudo-R2 ≤ 0.34) but outperformed ordinary least-squares (OLS) and generalized least-squares (GLS) regression models with logit-transformed response in terms of mean square prediction error and absolute bias. We introduce a copula (COP) model that is based on the beta distribution and accounts for spatial dependence. A simulation study was designed to illustrate the effects of incorrectly assuming normality, equal variance, and spatial independence. It showed that BR, BRdep, and COP models provide unbiased parameter estimates, whereas OLS and GLS models result in slightly biased estimates for two of the three parameters. On the basis of the simulation study, 93–97% of the GLS, BRdep, and COP confidence intervals covered the true parameters, whereas OLS and BR only resulted in 84–88% coverage, which demonstrated the superiority of GLS, BRdep, and COP over OLS and BR models in providing standard errors for the parameter estimates in the presence of spatial dependence.

The Statistical Power of the Cluster Randomized Block Design with Matched Pairs--A Simulation Study

ERIC Educational Resources Information Center

Dong, Nianbo; Lipsey, Mark

2010-01-01

This study uses simulation techniques to examine the statistical power of the group- randomized design and the matched-pair (MP) randomized block design under various parameter combinations. Both nearest neighbor matching and random matching are used for the MP design. The power of each design for any parameter combination was calculated from…

Patient Preferences for Injectable Treatments for Multiple Sclerosis in the United States: A Discrete-Choice Experiment.

PubMed

Poulos, Christine; Kinter, Elizabeth; Yang, Jui-Chen; Bridges, John F P; Posner, Joshua; Reder, Anthony T

2016-04-01

Patients' perceptions and experiences of medication efficacy, medication adverse events, dosing frequency, and dosing complexity have been found to influence adherence to injectable disease-modifying treatments (DMTs) in patients with multiple sclerosis (MS). The aim of this study was to quantify patient preferences for features of injectable DMTs for MS. Adult patients in the United States (US) with a self-reported diagnosis of MS completed an online discrete-choice experiment survey to assess preference for a number of features of a hypothetical injectable DMT. Patients chose hypothetical treatments in paired comparisons, where each treatment was described by features or attributes, including the number of years until disability progression, the number of relapses in the next 4 years, injection time, the frequency of injections, the occurrence of flu-like symptoms (FLS), and severity of injection-site reactions. Random-parameters logit regression parameters were used to calculate preference weights of attribute levels and the relative importance of changes in treatment features. Of the 205 patients who completed the survey, 192 provided sufficient data for analysis. The results indicated a broad range of tradeoffs that patients would be willing to make. With regard to this, the relative importance of an improvement in the number of years until disability progression from 1 to 2 (i.e., vertical distance between preference weights for these attribute levels) was 0.9 [95% confidence interval (CI) 0.5-1.2], the relative importance of this change was approximately equivalent to that of an improvement from 12 injections per month to two (mean 0.8, 95% CI 0.4-1.2), or approximately equivalent to a decrease from four to one relapses in the next 4 years (mean 0.8, 95% CI 0.5-1.2), or FLS 3 days after every injection to 3 days after some injections (mean 1.0, 95% CI 0.6-1.4). These results suggest that an improvement in treatment efficacy may be as important as a reduction in injection frequency or a reduction in some adverse events for patients who self-administer injectable DMTs for MS. Understanding the preferences of patients who use injectable treatments will inform the development of such treatments, which may in turn improve patient medication adherence and well-being.

A Note on the Heterogeneous Choice Model

ERIC Educational Resources Information Center

Rohwer, Goetz

2015-01-01

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Entrepreneurship and Adolescents

ERIC Educational Resources Information Center

Santana Vega, Lidia E.; González-Morales, Olga; Feliciano García, Luis

2016-01-01

This work studied the entrepreneurial aspirations of 3,987 adolescents regarding self-employment and the influence of gender, age, nationality, type of school, location of the school, educational level and performance. The Logit model is used to analyze the data. The results indicate that the pupils' aspirations to be self-employed increase in the…

Freight Demand Characteristics and Mode Choice: An Analysis of the Results of Modeling with Disaggregate Revealed Preference Data

DOT National Transportation Integrated Search

1999-12-01

This paper analyzes the freight demand characteristics that drive modal choice by means of a large scale, national, disaggregate revealed preference database for shippers in France in 1988, using a nested logit. Particular attention is given to priva...

Monitoring Antitobacco Sentiment among Community Leaders

ERIC Educational Resources Information Center

Bechtel, Gordon G.; Lyons-Lepke, Elaine M.

2003-01-01

Two public health objectives, one methodological and the other substantive, are realized in the present study. First, average survey ratings are replaced by negated mean cumulative logits (MCLs), which have the advantage of interitem commensuration. Second, these negated MCLs improve the analysis of two Florida tobacco control surveys of community…

Modelling Student Misconceptions Using Nested Logit Item Response Models

ERIC Educational Resources Information Center

Yildiz, Mustafa

2017-01-01

Student misconceptions have been studied for decades from a curricular/instructional perspective and from the assessment/test level perspective. Numerous misconception assessment tools have been developed in order to measure students' misconceptions relative to the correct content. Often, these tools are used to make a variety of educational…

The Impact of Nontraditional Training on the Occupational Attainment of Women.

ERIC Educational Resources Information Center

Streker-Seeborg, Irmtraud; And Others

1984-01-01

Using a logit model of occupational attainment, researchers found that economically disadvantaged women who received nontraditional training were much less likely to be employed in male-dominated occupations and received lower hourly wages. Direct labor market discrimination seems to be responsible for the inhibited occupational attainment of…

Using Neural Networks to Predict MBA Student Success

ERIC Educational Resources Information Center

Naik, Bijayananda; Ragothaman, Srinivasan

2004-01-01

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

Predicting Faculty Membership--Application of Student Choice Logit Model

ERIC Educational Resources Information Center

Kopanidis, Foula Zografina; Shaw, Michael John

2017-01-01

Purpose: Educational institutions are caught between increasing their offer rates and attracting and retaining those prospective students who are most suited to course completion. The purpose of this paper is to demonstrate the influence of demographic and psychological constructs on students' preferences when choosing to study in a particular…

A Multimonial Logit Analysis of Teenage Fertility and High School Completion.

ERIC Educational Resources Information Center

Ribar, David C.

1993-01-01

Uses data from the 1979 National Longitudinal Survey of Youth to examine economic, institutional, and sociological antecedents of high school completion and adolescent fertility. Welfare generosity appears to have a significant positive effect on adolescent childbearing. Other important determinants of teenage parenthood and educational attainment…

Academic Achievement of Girls in Rural Schools in Kenya

ERIC Educational Resources Information Center

Mungai, A. M.

2012-01-01

This study examined the effect of two family factors (financial, social capital) and school factors on students' achievement. One hundred eighty two, seventh-grade female students from nine schools in Muranga district, Kenya, were studied. The statistical procedures included logit regression, cross-tabulations, frequency counting and chi-square…

On the potential of models for location and scale for genome-wide DNA methylation data

PubMed Central

2014-01-01

Background With the help of epigenome-wide association studies (EWAS), increasing knowledge on the role of epigenetic mechanisms such as DNA methylation in disease processes is obtained. In addition, EWAS aid the understanding of behavioral and environmental effects on DNA methylation. In terms of statistical analysis, specific challenges arise from the characteristics of methylation data. First, methylation β-values represent proportions with skewed and heteroscedastic distributions. Thus, traditional modeling strategies assuming a normally distributed response might not be appropriate. Second, recent evidence suggests that not only mean differences but also variability in site-specific DNA methylation associates with diseases, including cancer. The purpose of this study was to compare different modeling strategies for methylation data in terms of model performance and performance of downstream hypothesis tests. Specifically, we used the generalized additive models for location, scale and shape (GAMLSS) framework to compare beta regression with Gaussian regression on raw, binary logit and arcsine square root transformed methylation data, with and without modeling a covariate effect on the scale parameter. Results Using simulated and real data from a large population-based study and an independent sample of cancer patients and healthy controls, we show that beta regression does not outperform competing strategies in terms of model performance. In addition, Gaussian models for location and scale showed an improved performance as compared to models for location only. The best performance was observed for the Gaussian model on binary logit transformed β-values, referred to as M-values. Our results further suggest that models for location and scale are specifically sensitive towards violations of the distribution assumption and towards outliers in the methylation data. Therefore, a resampling procedure is proposed as a mode of inference and shown to diminish type I error rate in practically relevant settings. We apply the proposed method in an EWAS of BMI and age and reveal strong associations of age with methylation variability that are validated in an independent sample. Conclusions Models for location and scale are promising tools for EWAS that may help to understand the influence of environmental factors and disease-related phenotypes on methylation variability and its role during disease development. PMID:24994026

Activity interference and noise annoyance

NASA Astrophysics Data System (ADS)

Hall, F. L.; Taylor, S. M.; Birnie, S. E.

1985-11-01

Debate continues over differences in the dose-response functions used to predict the annoyance at different sources of transportation noise. This debate reflects the lack of an accepted model of noise annoyance in residential communities. In this paper a model is proposed which is focussed on activity interference as a central component mediating the relationship between noise exposure and annoyance. This model represents a departure from earlier models in two important respects. First, single event noise levels (e.g., maximum levels, sound exposure level) constitute the noise exposure variables in place of long-term energy equivalent measures (e.g., 24-hour Leq or Ldn). Second, the relationships within the model are expressed as probabilistic rather than deterministic equations. The model has been tested by using acoustical and social survey data collected at 57 sites in the Toronto region exposed to aircraft, road traffic or train noise. Logit analysis was used to estimate two sets of equations. The first predicts the probability of activity interference as a function of event noise level. Four types of interference are included: indoor speech, outdoor speech, difficulty getting to sleep and awakening. The second set predicts the probability of annoyance as a function of the combination of activity interferences. From the first set of equations, it was possible to estimate a function for indoor speech interference only. In this case, the maximum event level was the strongest predictor. The lack of significant results for the other types of interference is explained by the limitations of the data. The same function predicts indoor speech interference for all three sources—road, rail and aircraft noise. The results for the second set of equations show strong relationships between activity interference and the probability of annoyance. Again, the parameters of the logit equations are similar for the three sources. A trial application of the model predicts a higher probability of annoyance for aircraft than for road traffic situations with the same 24-hour Leq. This result suggests that the model may account for previously reported source differences in annoyance.

Uncertainty quantification of voice signal production mechanical model and experimental updating

NASA Astrophysics Data System (ADS)

Cataldo, E.; Soize, C.; Sampaio, R.

2013-11-01

The aim of this paper is to analyze the uncertainty quantification in a voice production mechanical model and update the probability density function corresponding to the tension parameter using the Bayes method and experimental data. Three parameters are considered uncertain in the voice production mechanical model used: the tension parameter, the neutral glottal area and the subglottal pressure. The tension parameter of the vocal folds is mainly responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. The three uncertain parameters are modeled by random variables. The probability density function related to the tension parameter is considered uniform and the probability density functions related to the neutral glottal area and the subglottal pressure are constructed using the Maximum Entropy Principle. The output of the stochastic computational model is the random voice signal and the Monte Carlo method is used to solve the stochastic equations allowing realizations of the random voice signals to be generated. For each realization of the random voice signal, the corresponding realization of the random fundamental frequency is calculated and the prior pdf of this random fundamental frequency is then estimated. Experimental data are available for the fundamental frequency and the posterior probability density function of the random tension parameter is then estimated using the Bayes method. In addition, an application is performed considering a case with a pathology in the vocal folds. The strategy developed here is important mainly due to two things. The first one is related to the possibility of updating the probability density function of a parameter, the tension parameter of the vocal folds, which cannot be measured direct and the second one is related to the construction of the likelihood function. In general, it is predefined using the known pdf. Here, it is constructed in a new and different manner, using the own system considered.

Complementary nonparametric analysis of covariance for logistic regression in a randomized clinical trial setting.

PubMed

Tangen, C M; Koch, G G

1999-03-01

In the randomized clinical trial setting, controlling for covariates is expected to produce variance reduction for the treatment parameter estimate and to adjust for random imbalances of covariates between the treatment groups. However, for the logistic regression model, variance reduction is not obviously obtained. This can lead to concerns about the assumptions of the logistic model. We introduce a complementary nonparametric method for covariate adjustment. It provides results that are usually compatible with expectations for analysis of covariance. The only assumptions required are based on randomization and sampling arguments. The resulting treatment parameter is a (unconditional) population average log-odds ratio that has been adjusted for random imbalance of covariates. Data from a randomized clinical trial are used to compare results from the traditional maximum likelihood logistic method with those from the nonparametric logistic method. We examine treatment parameter estimates, corresponding standard errors, and significance levels in models with and without covariate adjustment. In addition, we discuss differences between unconditional population average treatment parameters and conditional subpopulation average treatment parameters. Additional features of the nonparametric method, including stratified (multicenter) and multivariate (multivisit) analyses, are illustrated. Extensions of this methodology to the proportional odds model are also made.

Decision-theoretic approach to data acquisition for transit operations planning

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

Ritchie, S.G.

The most costly element of transportation planning and modeling activities in the past has usually been that of data acquisition. This is even truer today when the unit costs of data collection are increasing rapidly and at the same time budgets are severely limited by continuing policies of fiscal austerity in the public sector. The overall objectives of this research were to improve the decisions and decision-making capabilities of transit operators or planners in short-range transit planning, and to improve the quality and cost-effectiveness of associated route or corridor-level data collection and service monitoring activities. A new approach was presentedmore » for sequentially updating the parameters of both simple and multiple linear regression models with stochastic regressors, and for determining the expected value of sample information and expected net gain of sampling for associated sample designs. A new approach was also presented for estimating and updating (both spatially and temporally) the parameters of multinomial logit discrete choice models, and for determining associated optimal sample designs for attribute-based and choice-based sampling methods. The approach provides an effective framework for addressing the issue of optimal sampling method and sample size, which to date have been largely unresolved. The application of these methodologies and the feasibility of the decision-theoretic approach was illustrated with a hypothetical case study example.« less

Novel image encryption algorithm based on multiple-parameter discrete fractional random transform

NASA Astrophysics Data System (ADS)

Zhou, Nanrun; Dong, Taiji; Wu, Jianhua

2010-08-01

A new method of digital image encryption is presented by utilizing a new multiple-parameter discrete fractional random transform. Image encryption and decryption are performed based on the index additivity and multiple parameters of the multiple-parameter fractional random transform. The plaintext and ciphertext are respectively in the spatial domain and in the fractional domain determined by the encryption keys. The proposed algorithm can resist statistic analyses effectively. The computer simulation results show that the proposed encryption algorithm is sensitive to the multiple keys, and that it has considerable robustness, noise immunity and security.

The concordance index C and the Mann-Whitney parameter Pr(X>Y) with randomly censored data.

PubMed

Koziol, James A; Jia, Zhenyu

2009-06-01

Harrell's c-index or concordance C has been widely used as a measure of separation of two survival distributions. In the absence of censored data, the c-index estimates the Mann-Whitney parameter Pr(X>Y), which has been repeatedly utilized in various statistical contexts. In the presence of randomly censored data, the c-index no longer estimates Pr(X>Y); rather, a parameter that involves the underlying censoring distributions. This is in contrast to Efron's maximum likelihood estimator of the Mann-Whitney parameter, which is recommended in the setting of random censorship.

Hybrid computer optimization of systems with random parameters

NASA Technical Reports Server (NTRS)

White, R. C., Jr.

1972-01-01

A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

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

ERIC Educational Resources Information Center

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…

Forest amenities and location choice in the Southwest

Treesearch

Michael S. Hand; Jennifer A. Thacher; Daniel R. McCollum; Robert P. Berrens

2008-01-01

Locations with natural characteristics, such as forests, are thought to be attractive residential locations. This proposition is tested in the Southwest United States, composed of Arizona and New Mexico. This paper presents a conditional logit model of location choice estimated with household observations from the U.S. Census, geographic information system (GIS) data,...

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

Ian A. Munn; David Cleaves

1998-01-01

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

Self-Reported Frequency and Perceived Severity of Being Bullied among Elementary School Students

ERIC Educational Resources Information Center

Chen, Li-Ming

2015-01-01

Background: This study reports students' perspectives on the frequency and perceived severity of being bullied. Methods: A sample of 1816 elementary school students completed self-report surveys of perceived severity and frequency of being bullied. A Rasch technique aligned different victimized behaviors on interval logit scales. A 4-fold schema…

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

ERIC Educational Resources Information Center

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…

The Postsecondary Resource Trinity Model: Exploring the Interaction between Socioeconomic, Academic, and Institutional Resources

ERIC Educational Resources Information Center

Giani, Matt S.

2015-01-01

The purpose of this study is to revisit the widely held assumption that the impact of socioeconomic background declines steadily across educational transitions, particularly at the postsecondary level. Sequential logit modeling, a staple methodological approach for estimating the relative impact of SES across educational stages, is applied to a…

Minimum Wages and Teenagers' Enrollment--Employment Outcomes: A Multinominal Logit Model.

ERIC Educational Resources Information Center

Ehrenberg, Ronald G.; Marcus, Alan J.

1982-01-01

This paper tests the hypothesis that the effect of minimum wage legislation on teenagers' education decisions is asymmetrical across family income classes, with the legislation inducing children from low-income families to reduce their levels of schooling and children from higher-income families to increase their educational attainment. (Author)

Does race matter in landowners' participation in conservation incentive programs?

Treesearch

Jianbang Gan; Okwuldili O. Onianwa; John Schelhas; Gerald C. Wheelock; Mark R. Dubois

2005-01-01

This study investigated and compared the participation behavior of white and minority small landowners in Alabama in eight conservation incentive programs. Using nonparametric tests and logit modeling, we found both similarities and differences in participation behavior between these two landowner groups. Both white and minority landowners tended not to participate in...

The Sex Difference in Depression across 29 Countries

ERIC Educational Resources Information Center

Hopcroft, Rosemary L.; Bradley, Dana Burr

2007-01-01

The sex difference in depression is well documented in westernized, developed societies, although there has been little quantitative cross-cultural research on the topic. In this study, we use multilevel logit models to examine sex differences in depression across 29 countries using data from the World Values Survey. We find that in no country are…

Optional contributions have positive effects for volunteering public goods games

NASA Astrophysics Data System (ADS)

Song, Qi-Qing; Li, Zhen-Peng; Fu, Chang-He; Wang, Lai-Sheng

2011-11-01

Public goods (PG) games with the volunteering mechanism are referred to as volunteering public goods (VPG) games, in which loners are introduced to the PG games, and a loner obtains a constant payoff but not participating the game. Considering that small contributions may have positive effects to encourage more players with bounded rationality to contribute, this paper introduces optional contributions (high value or low value) to these typical VPG games-a cooperator can contribute a high or low payoff to the public pools. With the low contribution, the logit dynamics show that cooperation can be promoted in a well mixed population comparing to the typical VPG games, furthermore, as the multiplication factor is greater than a threshold, the average payoff of the population is also enhanced. In spatial VPG games, we introduce a new adjusting mechanism that is an approximation to best response. Some results in agreement with the prediction of the logit dynamics are found. These simulation results reveal that for VPG games the option of low contributions may be a better method to stimulate the growth of cooperation frequency and the average payoff of the population.

Syndromic surveillance models using Web data: the case of scarlet fever in the UK.

PubMed

Samaras, Loukas; García-Barriocanal, Elena; Sicilia, Miguel-Angel

2012-03-01

Recent research has shown the potential of Web queries as a source for syndromic surveillance, and existing studies show that these queries can be used as a basis for estimation and prediction of the development of a syndromic disease, such as influenza, using log linear (logit) statistical models. Two alternative models are applied to the relationship between cases and Web queries in this paper. We examine the applicability of using statistical methods to relate search engine queries with scarlet fever cases in the UK, taking advantage of tools to acquire the appropriate data from Google, and using an alternative statistical method based on gamma distributions. The results show that using logit models, the Pearson correlation factor between Web queries and the data obtained from the official agencies must be over 0.90, otherwise the prediction of the peak and the spread of the distributions gives significant deviations. In this paper, we describe the gamma distribution model and show that we can obtain better results in all cases using gamma transformations, and especially in those with a smaller correlation factor.

How uncertain is the future of electric vehicle market: Results from Monte Carlo simulations using a nested logit model

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

Liu, Changzheng; Oak Ridge National Lab.; Lin, Zhenhong

Plug-in electric vehicles (PEVs) are widely regarded as an important component of the technology portfolio designed to accomplish policy goals in sustainability and energy security. However, the market acceptance of PEVs in the future remains largely uncertain from today's perspective. By integrating a consumer choice model based on nested multinomial logit and Monte Carlo simulation, this study analyzes the uncertainty of PEV market penetration using Monte Carlo simulation. Results suggest that the future market for PEVs is highly uncertain and there is a substantial risk of low penetration in the early and midterm market. Top factors contributing to market sharemore » variability are price sensitivities, energy cost, range limitation, and charging availability. The results also illustrate the potential effect of public policies in promoting PEVs through investment in battery technology and infrastructure deployment. Here, continued improvement of battery technologies and deployment of charging infrastructure alone do not necessarily reduce the spread of market share distributions, but may shift distributions toward right, i.e., increase the probability of having great market success.« less

A Multilevel Logit Estimation on the Determinants of Utilization of Preventive Health Care and Healthy Lifestyle Practice in China

PubMed Central

Fan, Lida; Liu, Jianye; Habibov, Nazim N

2015-01-01

The purpose of this study is to provide policy implications by estimating the individual and community level determinants of preventive health-care utilization in China based upon data from the China Health and Nutrition Survey. Two different frameworks, a human capital model and a psychological-behavioral model, are tested using a multilevel logit estimation. The results demonstrate different patterns for medical and nonmedical preventive activities. There is a strong correlation between having medical insurance and utilizing preventive health services. For the usage of medical-related preventive health care (MP), age, gender, education, urban residence, and medical insurance are strong predictors. High income did not provide much of an increase in the usage level of MP, but the lack of income was a huge obstacle for low-income people to overcome. Community variation in number of facilities accounted for about one third of the total variation in the utilization of MP. The utilization of MP in China remains dependent upon the individual's social-economic conditions. PMID:26688776

Preference elicitation approach for measuring the willingness to pay for liver cancer treatment in Korea.

PubMed

Cho, Donghun; Jo, Changik

2015-09-01

The Korean government has expanded the coverage of the national insurance scheme for four major diseases: cancers, cardiovascular diseases, cerebrovascular diseases, and rare diseases. This policy may have a detrimental effect on the budget of the national health insurance agency. Like taxes, national insurance premiums are levied on the basis of the income or wealth of the insured. Using a preference elicitation method, we attempted to estimate how much people are willing to pay for insurance premiums that would expand their coverage for liver cancer treatment. We calculated the marginal willingness to pay (MWTP) through the marginal rate of substitution between the two attributes of the insurance premium and the total annual treatment cost by adopting conditional logit and mixed logit models. The effects of various other terms that could interact with socioeconomic status were also estimated, such as gender, income level, educational attainment, age, employment status, and marital status. The estimated MWTP values of the monthly insurance premium for liver cancer treatment range from 4,130 KRW to 9,090 KRW.

How uncertain is the future of electric vehicle market: Results from Monte Carlo simulations using a nested logit model

DOE PAGES

Liu, Changzheng; Oak Ridge National Lab.; Lin, Zhenhong; ...

2016-12-08

Plug-in electric vehicles (PEVs) are widely regarded as an important component of the technology portfolio designed to accomplish policy goals in sustainability and energy security. However, the market acceptance of PEVs in the future remains largely uncertain from today's perspective. By integrating a consumer choice model based on nested multinomial logit and Monte Carlo simulation, this study analyzes the uncertainty of PEV market penetration using Monte Carlo simulation. Results suggest that the future market for PEVs is highly uncertain and there is a substantial risk of low penetration in the early and midterm market. Top factors contributing to market sharemore » variability are price sensitivities, energy cost, range limitation, and charging availability. The results also illustrate the potential effect of public policies in promoting PEVs through investment in battery technology and infrastructure deployment. Here, continued improvement of battery technologies and deployment of charging infrastructure alone do not necessarily reduce the spread of market share distributions, but may shift distributions toward right, i.e., increase the probability of having great market success.« less

Stochastic analysis of uncertain thermal parameters for random thermal regime of frozen soil around a single freezing pipe

NASA Astrophysics Data System (ADS)

Wang, Tao; Zhou, Guoqing; Wang, Jianzhou; Zhou, Lei

2018-03-01

The artificial ground freezing method (AGF) is widely used in civil and mining engineering, and the thermal regime of frozen soil around the freezing pipe affects the safety of design and construction. The thermal parameters can be truly random due to heterogeneity of the soil properties, which lead to the randomness of thermal regime of frozen soil around the freezing pipe. The purpose of this paper is to study the one-dimensional (1D) random thermal regime problem on the basis of a stochastic analysis model and the Monte Carlo (MC) method. Considering the uncertain thermal parameters of frozen soil as random variables, stochastic processes and random fields, the corresponding stochastic thermal regime of frozen soil around a single freezing pipe are obtained and analyzed. Taking the variability of each stochastic parameter into account individually, the influences of each stochastic thermal parameter on stochastic thermal regime are investigated. The results show that the mean temperatures of frozen soil around the single freezing pipe with three analogy method are the same while the standard deviations are different. The distributions of standard deviation have a great difference at different radial coordinate location and the larger standard deviations are mainly at the phase change area. The computed data with random variable method and stochastic process method have a great difference from the measured data while the computed data with random field method well agree with the measured data. Each uncertain thermal parameter has a different effect on the standard deviation of frozen soil temperature around the single freezing pipe. These results can provide a theoretical basis for the design and construction of AGF.

Statistical inference for Hardy-Weinberg proportions in the presence of missing genotype information.

PubMed

Graffelman, Jan; Sánchez, Milagros; Cook, Samantha; Moreno, Victor

2013-01-01

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.

Study on mobile phone use while driving in a sample of Iranian drivers.

PubMed

Arvin, Ramin; Khademi, Mostafa; Razi-Ardakani, Hesamoddin

2017-06-01

The use of cell phone is a significant source of driver distraction. Phone use while driving can impair a number of factors critical for safe driving which can cause serious traffic safety problems. The objective of this paper was to investigate the frequency of using cell phones while driving in Iran's roads through an observational survey with a random sample of drivers, to recognize contributing factors to cell phone usage and to understand the magnitude of the problem. A total of 1794 observations were collected from 12 sites at controlled intersections, entrance and exit points of highways. The cell phone use rate among drivers (talking or texting) was estimated at 10% which is significantly higher than that in other countries such as Australia, USA and Canada. Rate of cell phone use among younger drivers (14.15%) was higher in comparison with other groups. In order to identify factors affecting cell phone use while driving, a binary logit model is estimated. Variables which significantly contribute to the rate of using cell phone were found to be the age of driver, number of passengers, presence of kids under the age of 8, time of observation, vehicle price and type of car.

Social isolation, drunkenness, and cigarette use among adolescents.

PubMed

Niño, Michael D; Cai, Tianji; Ignatow, Gabe

2016-02-01

This study compares isolated to sociable youth to investigate the relations between different network types of social isolation and alcohol and cigarette use. Using data from the National Longitudinal Study of Adolescent to Adult Health we developed a network measure that includes various types of social isolation. Types of social isolation were operationalized as socially avoidant, actively isolated, and socially disinterested, with sociable youth as the reference category. Random effects ordinal logit models were fit to estimate the association between different types of social isolation and drunkenness and cigarette use. Different types of social isolation had varying effects on drunkenness and cigarette use. On the one hand, socially disinterested youth were at an increased risk for drunkenness and cigarette use. On the other hand, socially avoidant youth had lower odds of drunkenness and no significant differences in cigarette use when compared to sociable youth. Actively isolated youth showed no differences in drunkenness and cigarette use. The role played by marginalized social positions in youth substance use is an important yet overlooked problem. This study can contribute to better targeted and more effective health behavior prevention efforts for vulnerable adolescents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Economic reforms and health insurance in China.

PubMed

Du, Juan

2009-08-01

During the 1990s, Chinese state-owned enterprises (SOEs) and collective enterprises continually decreased coverage of public health insurance to their employees. This paper investigates this changing pattern of health insurance coverage in China using panel data from the China Nutrition and Health Survey (1991-2000). It is the first attempt in this literature that tries to identify precisely the effects of specific policies and reforms on health insurance coverage in the transitional period of China. The fixed effects linear model clustering at the province level is used for estimation, and results are compared to alternative models, including pooled OLS, random effects GLS model and fixed effects logit model. Strong empirical evidence is found that unemployment as a side effect of the Open Door Policy, and the deregulation of SOE and collective enterprises were the main causes for the decreasing trend. For example, urban areas that were highly affected by the Open Door Policy were associated with 17 percentage points decrease in the insurance coverage. Moreover, I found evidence that the gaps between SOE and non-SOE employees, collective and non-collective employees, urban and rural employees have considerably decreased during the ten years.

A Bayesian hierarchical model for discrete choice data in health care.

PubMed

Antonio, Anna Liza M; Weiss, Robert E; Saigal, Christopher S; Dahan, Ely; Crespi, Catherine M

2017-01-01

In discrete choice experiments, patients are presented with sets of health states described by various attributes and asked to make choices from among them. Discrete choice experiments allow health care researchers to study the preferences of individual patients by eliciting trade-offs between different aspects of health-related quality of life. However, many discrete choice experiments yield data with incomplete ranking information and sparsity due to the limited number of choice sets presented to each patient, making it challenging to estimate patient preferences. Moreover, methods to identify outliers in discrete choice data are lacking. We develop a Bayesian hierarchical random effects rank-ordered multinomial logit model for discrete choice data. Missing ranks are accounted for by marginalizing over all possible permutations of unranked alternatives to estimate individual patient preferences, which are modeled as a function of patient covariates. We provide a Bayesian version of relative attribute importance, and adapt the use of the conditional predictive ordinate to identify outlying choice sets and outlying individuals with unusual preferences compared to the population. The model is applied to data from a study using a discrete choice experiment to estimate individual patient preferences for health states related to prostate cancer treatment.

Factors influencing smallholder farmers' behavioural intention towards adaptation to climate change in transitional climatic zones: A case study of Hwedza District in Zimbabwe.

PubMed

Zamasiya, Byron; Nyikahadzoi, Kefasi; Mukamuri, Billy Billiard

2017-08-01

This paper examines factors influencing behavioural change among smallholder farmers towards adaptation to climate change in transitional climatic zones of Africa, specifically, Hwedza District in Zimbabwe. Data for this study were collected from 400 randomly-selected smallholder farmers, using a structured questionnaire, focus group discussions and key informant interviews. The study used an ordered logit model to examine the factors that influence smallholder farmers' behavioural intention towards adaptation to climate change. Results from the study show that the gender of the household head, access to extension services on crop and livestock production, access to climate information, membership to social groups and experiencing a drought have a positive influence on farmers' attitude towards adaptation to climate change and variability. The study concluded that although the majority of smallholder farmers perceive that the climate is changing, they continue to habour negative attitudes towards prescribed climate change adaptation techniques. This study recommends more education on climate change, as well as adaptation strategies for both agricultural extension workers and farmers. This can be complemented by disseminating timely climate information through extension officers and farmers' groups. Copyright © 2017 Elsevier Ltd. All rights reserved.

Widowed Mothers’ Coresidence With Adult Children

PubMed Central

2014-01-01

Objectives. Coresidence is one way that middle-aged offspring assist vulnerable, aging parents. This study investigated which characteristics of widowed mothers and adult children predict coresidence. When coresidence occurred, the analysis explored how individual children’s characteristics were associated with their coresidence with the mother. Method. Survey data from adults 53–54 years old in 1993 (N = 2,324) and a random sibling reported about their living situation, other siblings, and their mother, median age 80. Results. Logistic regressions revealed that mothers in poor health, who were older, and who had a daughter were more likely to live with a child. Among coresiding families, results from discrete choice conditional logit models showed that widowed mothers were more likely to live with an unmarried son than an unmarried daughter. Married children were less likely to coreside than unmarried children, but married daughters were more likely than married sons to coreside. Past receipt of financial help from parents was not associated with coresidence. Coresidence was more likely for those with a close relationship with the mother. Discussion. The discussion considers coresidence as an intergenerational transfer and its importance for the contemporary aging society. Data are needed on characteristics of all offspring to test theories about parent–child relationships. PMID:24013798

Does the EU sugar policy reform increase added sugar consumption? An empirical evidence on the soft drink market.

PubMed

Bonnet, Céline; Requillart, Vincent

2011-09-01

Whereas National Health authorities recommend a decrease in the consumption of 'added' sugar, a reform on the sugar market will lead to a 36% decrease of the sugar price in the EU. Using French data on soft drinks purchases, this paper investigates the anticipated impact of this reform on the consumption of sugar-sweetened beverages. The reform of the EU sugar policy leads to a decrease in regular soft drink prices by 3% and varies across brands. To assess substitution within this food category, we use a random-coefficients logit model that takes into account a large number of differentiated products and heterogeneity in consumers' behavior. Results suggest that price changes would lead to an increase in market shares of regular products by 7.5% and to substitutions between brands to the benefit of products with the highest sugar content. On the whole, it would raise consumption of regular soft drinks by more than 1 litre per person per year and consumption of added sugar by 124 g per person per year, this increase being larger in households composed of overweight and obese individuals. Copyright © 2011 John Wiley & Sons, Ltd.

Employee choice of flexible spending account participation and health plan.

PubMed

Hamilton, Barton H; Marton, James

2008-07-01

Despite the fact that flexible spending accounts (FSAs) are becoming an increasingly popular employer-provided health benefit, there has been very little empirical study of FSA use among employees at the individual level. This study contributes to the literature on FSAs using a unique data set that provides three years of employee-level-matched benefits data. Motivated by the theoretical model of FSA choice presented in Cardon and Showalter (J. Health Econ. 2001; 20(6):935-954), we examine the determinants of FSA participation and contribution levels using cross-sectional and random-effect two-part models. FSA participation and health plan choice are also modeled jointly in each year using conditional logit models. We find that, even after controlling for a number of other demographic characteristics, non-whites are less likely to participate in the FSA program, have lower contributions conditional on participation, and have a lower probability of switching to new lower cost share, higher premium plans when they were introduced. We also find evidence that choosing health plans with more expected out-of-pocket expenses is correlated with participation in the FSA program. Copyright (c) 2007 John Wiley & Sons, Ltd.

Multi-agent fare optimization model of two modes problem and its analysis based on edge of chaos

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Li, Xue-wei; Qiu, He-ting

2017-03-01

This paper proposes a new framework of fare optimization & game model for studying the competition between two travel modes (high speed railway and civil aviation) in which passengers' group behavior is taken into consideration. The small-world network is introduced to construct the multi-agent model of passengers' travel mode choice. The cumulative prospect theory is adopted to depict passengers' bounded rationality, the heterogeneity of passengers' reference point is depicted using the idea of group emotion computing. The conceptions of "Langton parameter" and "evolution entropy" in the theory of "edge of chaos" are introduced to create passengers' "decision coefficient" and "evolution entropy of travel mode choice" which are used to quantify passengers' group behavior. The numerical simulation and the analysis of passengers' behavior show that (1) the new model inherits the features of traditional model well and the idea of self-organizing traffic flow evolution fully embodies passengers' bounded rationality, (2) compared with the traditional model (logit model), when passengers are in the "edge of chaos" state, the total profit of the transportation system is higher.

Metro passengers’ route choice model and its application considering perceived transfer threshold

PubMed Central

Jin, Fanglei; Zhang, Yongsheng; Liu, Shasha

2017-01-01

With the rapid development of the Metro network in China, the greatly increased route alternatives make passengers’ route choice behavior and passenger flow assignment more complicated, which presents challenges to the operation management. In this paper, a path sized logit model is adopted to analyze passengers’ route choice preferences considering such parameters as in-vehicle time, number of transfers, and transfer time. Moreover, the “perceived transfer threshold” is defined and included in the utility function to reflect the penalty difference caused by transfer time on passengers’ perceived utility under various numbers of transfers. Next, based on the revealed preference data collected in the Guangzhou Metro, the proposed model is calibrated. The appropriate perceived transfer threshold value and the route choice preferences are analyzed. Finally, the model is applied to a personalized route planning case to demonstrate the engineering practicability of route choice behavior analysis. The results show that the introduction of the perceived transfer threshold is helpful to improve the model’s explanatory abilities. In addition, personalized route planning based on route choice preferences can meet passengers’ diversified travel demands. PMID:28957376

Reading Ability and Reading Engagement in Older Adults With Glaucoma

PubMed Central

Nguyen, Angeline M.; van Landingham, Suzanne W.; Massof, Robert W.; Rubin, Gary S.; Ramulu, Pradeep Y.

2014-01-01

Purpose. We evaluated the impact of glaucoma-related vision loss on reading ability and reading engagement in 10 reading activities. Methods. A total of 63 glaucoma patients and 59 glaucoma suspect controls self-rated their level of reading difficulty for 10 reading items, and responses were analyzed using Rasch analysis to determine reading ability. Reading engagement was assessed by asking subjects to report the number of days per week they engaged in each reading activity. Reading restriction was determined as a decrement in engagement. Results. Glaucoma subjects more often described greater reading difficulty than controls for all tasks except puzzles (P < 0.05). The most difficult reading tasks involved puzzles, books, and finances, while the least difficult reading tasks involved notes, bills, and mail. In multivariable weighted least squares regression models of Rasch-estimated person measures of reading ability, less reading ability was found for glaucoma patients compared to controls (β = −1.60 logits, P < 0.001). Among glaucoma patients, less reading ability was associated with more severe visual field (VF) loss (β = −0.68 logits per 5-dB decrement in better-eye VF mean deviation [MD], P < 0.001) and contrast sensitivity (β = −0.76 logits per 0.1-unit lower log CS, P < 0.001). Each 5-dB decrement in the better-eye VF MD was associated with book reading on 18% fewer days (P = 0.003) and newspaper reading on 10% fewer days (P = 0.008). No statistically significant reading restriction was observed for other reading activities (P > 0.05). Conclusions. Glaucoma patients have less reading ability and engage less in a variety of different reading activities, particularly those requiring sustained reading. Future work should evaluate the mechanisms underlying reading disability in glaucoma to determine how patients can maintain reading ability and engagement. PMID:25052992

Multi-parameter fiber optic sensors based on fiber random grating

NASA Astrophysics Data System (ADS)

Xu, Yanping; Zhang, Mingjiang; Lu, Ping; Mihailov, Stephen; Bao, Xiaoyi

2017-04-01

Two novel configurations of multi-parameter fiber-optic sensing systems based on the fiber random grating are reported. The fiber random grating is fabricated through femtosecond laser induced refractive index modification over a 10cm standard telecom single mode fiber. In one configuration, the reflective spectrum of the fiber random grating is directly detected and a wavelength-division spectral cross-correlation algorithm is adopted to extract the spectral shifts for simultaneous measurement of temperature, axial strain, and surrounding refractive index. In the other configuration, a random fiber ring laser is constructed by incorporating the random feedback from the random grating. Numerous polarization-dependent spectral filters are formed along the random grating and superimposed to provide multiple lasing lines with high signal-to-noise ratio up to 40dB, which enables a high-fidelity multi-parameter sensing scheme by monitoring the spectral shifts of the lasing lines. Without the need of phase mask for fabrication and with the high physical strength, the random grating based sensors are much simpler and more compact, which could be potentially an excellent alternative for liquid medical sample sensing in biomedical and biochemical applications.

Transient Oscilliations in Mechanical Systems of Automatic Control with Random Parameters

NASA Astrophysics Data System (ADS)

Royev, B.; Vinokur, A.; Kulikov, G.

2018-04-01

Transient oscillations in mechanical systems of automatic control with random parameters is a relevant but insufficiently studied issue. In this paper, a modified spectral method was applied to investigate the problem. The nature of dynamic processes and the phase portraits are analyzed depending on the amplitude and frequency of external influence. It is evident from the obtained results, that the dynamic phenomena occurring in the systems with random parameters under external influence are complex, and their study requires further investigation.

Analysis on pseudo excitation of random vibration for structure of time flight counter

NASA Astrophysics Data System (ADS)

Wu, Qiong; Li, Dapeng

2015-03-01

Traditional computing method is inefficient for getting key dynamical parameters of complicated structure. Pseudo Excitation Method(PEM) is an effective method for calculation of random vibration. Due to complicated and coupling random vibration in rocket or shuttle launching, the new staging white noise mathematical model is deduced according to the practical launch environment. This deduced model is applied for PEM to calculate the specific structure of Time of Flight Counter(ToFC). The responses of power spectral density and the relevant dynamic characteristic parameters of ToFC are obtained in terms of the flight acceptance test level. Considering stiffness of fixture structure, the random vibration experiments are conducted in three directions to compare with the revised PEM. The experimental results show the structure can bear the random vibration caused by launch without any damage and key dynamical parameters of ToFC are obtained. The revised PEM is similar with random vibration experiment in dynamical parameters and responses are proved by comparative results. The maximum error is within 9%. The reasons of errors are analyzed to improve reliability of calculation. This research provides an effective method for solutions of computing dynamical characteristic parameters of complicated structure in the process of rocket or shuttle launching.

Physician preferences for medication attributes for the prophylactic treatment of patients with severe haemophilia A with inhibitors to factor VIII.

PubMed

Gelhorn, H; Merikle, E; Krishnan, S; Nemes, L; Leissinger, C; Valentino, L

2013-01-01

Prophylaxis may be beneficial for patients with severe haemophilia A who have developed inhibitors to factor VIII. The aim of this study was to determine physicians' preferences for medication attributes in the prophylactic treatment of this patient population. Haematologists from Europe (EU) and the United States (US) participated in a discrete choice exercise to explore their preferences for medication attributes (efficacy, cost, scientific evidence, dosing frequency and administration time) associated with prophylaxis for severe haemophilia A in patients with inhibitors to factor VIII. Physicians' preferences for medication attributes were assessed through completion of 25 trade-off tasks that included a choice between two hypothetical medications each comprised of one randomized level of each medication attribute. Participants also completed a sociodemographic questionnaire. Data were analysed using a random effects logit model. Participants (N = 36: US = 19; EU = 17) were 80.6% men, had a mean of 19.8 years (SD ± 8.1) [range 6-35] of practice experience. The physicians treated an average of 5.7 (± 5.5) patients with severe haemophilia A and inhibitors per month and reported treating 36.2% of these patients prophylactically. The most important medication attributes for prophylactic treatment were efficacy [Relative Importance (RI) = 35.0%] and scientific evidence (RI = 34.1%), whereas treatment cost (12.0%), dosing frequency (10.8%) and administration time (8.2%) were less important. Results were similar across the EU and US. Efficacy and scientific evidence are the primary considerations for physicians' choice of prophylactic medications for use in this patient population. © 2012 Blackwell Publishing Ltd.

Paradoxical ventilator associated pneumonia incidences among selective digestive decontamination studies versus other studies of mechanically ventilated patients: benchmarking the evidence base

PubMed Central

2011-01-01

Introduction Selective digestive decontamination (SDD) appears to have a more compelling evidence base than non-antimicrobial methods for the prevention of ventilator associated pneumonia (VAP). However, the striking variability in ventilator associated pneumonia-incidence proportion (VAP-IP) among the SDD studies remains unexplained and a postulated contextual effect remains untested for. Methods Nine reviews were used to source 45 observational (benchmark) groups and 137 component (control and intervention) groups of studies of SDD and studies of three non-antimicrobial methods of VAP prevention. The logit VAP-IP data were summarized by meta-analysis using random effects methods and the associated heterogeneity (tau2) was measured. As group level predictors of logit VAP-IP, the mode of VAP diagnosis, proportion of trauma admissions, the proportion receiving prolonged ventilation and the intervention method under study were examined in meta-regression models containing the benchmark groups together with either the control (models 1 to 3) or intervention (models 4 to 6) groups of the prevention studies. Results The VAP-IP benchmark derived here is 22.1% (95% confidence interval; 95% CI; 19.2 to 25.5; tau2 0.34) whereas the mean VAP-IP of control groups from studies of SDD and of non-antimicrobial methods, is 35.7 (29.7 to 41.8; tau2 0.63) versus 20.4 (17.2 to 24.0; tau2 0.41), respectively (P < 0.001). The disparity between the benchmark groups and the control groups of the SDD studies, which was most apparent for the highest quality studies, could not be explained in the meta-regression models after adjusting for various group level factors. The mean VAP-IP (95% CI) of intervention groups is 16.0 (12.6 to 20.3; tau2 0.59) and 17.1 (14.2 to 20.3; tau2 0.35) for SDD studies versus studies of non-antimicrobial methods, respectively. Conclusions The VAP-IP among the intervention groups within the SDD evidence base is less variable and more similar to the benchmark than among the control groups. These paradoxical observations cannot readily be explained. The interpretation of the SDD evidence base cannot proceed without further consideration of this contextual effect. PMID:21214897

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

PubMed Central

Salomon, Joshua A

2003-01-01

Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO) or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC) between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99). Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions Modeling health-state valuations based on ordinal ranks can provide results that are similar to those obtained from more widely analyzed valuation techniques such as the TTO. The information content in aggregate ranking data is not currently exploited to full advantage. The possibility of estimating cardinal valuations from ordinal ranks could also simplify future data collection dramatically and facilitate wider empirical study of health-state valuations in diverse settings and population groups. PMID:14687419

The RANDOM computer program: A linear congruential random number generator

NASA Technical Reports Server (NTRS)

Miles, R. F., Jr.

1986-01-01

The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.

Exploring Factors Related to Young Children's Word-Meaning Derivations during Read-Alouds

ERIC Educational Resources Information Center

Christ, Tanya; Wang, X. Christine; Chiu, Ming Ming

2017-01-01

This study explores how child and text clues were related to 31 kindergarteners' word-meaning derivation outcomes for 372 words presented in books read aloud to children. Data were analyzed using a multilevel, cross-classification, ordered logit model. Children showed no word-meaning derivation 40% of the time, indicating a need for instruction.…

The Effect of Family Characteristics on Higher Education Attendance in India: A Multivariate Logit Approach

ERIC Educational Resources Information Center

Pramanik, Shaswati

2015-01-01

Family characteristics in terms of parental education and income are an important influence on individual's participation in higher education. In India it could be found that categorically those who are out of the higher education system belong to marginalized groups due to their economic class, caste, gender, religion etc. despite massive…

Does Education Affect Happiness? Evidence for Spain

ERIC Educational Resources Information Center

Cunado, Juncal; de Gracia, Fernando Perez

2012-01-01

In this paper we study the impact of education on happiness in Spain using individual-level data from the European Social Survey, by means of estimating Ordinal Logit Models. We find both direct and indirect effects of education on happiness. First, we find an indirect effect of education on happiness through income and labour status. That is, we…

Building social capital in forest communities: Analysis of New Mexico's Collaborative Forest Restoration Program

Treesearch

Tyler Prante; Jennifer A. Thacher; Daniel W. McCollum; Robert P. Berrens

2007-01-01

In part because of its emphasis on building social capital, the Collaborative Forest Restoration Program (CFRP) in New Mexico represents a unique experiment in public lands management. This study uses logit probability modeling to investigate what factors determined CFRP funding, which totaled $26 million between 2001 and 2006. Results reveal program preferences for...

Suicidality Among High School Students in Hong Kong, SAR

ERIC Educational Resources Information Center

Yip, Paul S. F.; Liu, K. Y.; Lam, T. H.; Stewart, Sunita M.; Chen, Eric; Fan, Susan

2004-01-01

Suicide is the leading cause of death in Hong Kong SAR for the youth aged 15?24. This study examined the prevalence of suicidality among secondary school students in Hong Kong using a representative, territory-wide sample of 2,586 students. Suicidal behaviors can be conceptualized as a spectrum of self-destructive behaviors. Cumulative logit model…

An Evaluation of the Adoption of Integrated Soil Fertility Management Practices among Women Farmers in Danja, Nigeria

ERIC Educational Resources Information Center

Damisa, M. A.; Igonoh, E.

2007-01-01

The relationship between technology adoption and farmers' socio-economic characteristics can never be over emphasized. This study tests the determinants of technology adoption by women farmers. The result from the Logit analysis of data from Unguwan-Madaki showed that the socio-economic characteristics of women farmers significantly affect their…

Estimating a family forest landowner's likelihood of posting against trespass

Treesearch

Stephanie A. Snyder; Michael A. Kilgore; Steven J. Taff; Joseph M. Schertz

2008-01-01

Hunters and other recreators face challenges to gain access to private forestland in the United States because of an increasing number of landowners posting their land. A landowners' decision to post their land is influenced by a variety of factors, including landowner characteristics, hunter behavior, and parcel attributes. We used a logit model to help...

Senate Hearing on Assured Access to Space

NASA Image and Video Library

2014-07-16

The Hon. Alan Estevez, Principle Deputy Under Secretary of Defense for Acquision, TEchnology, and Logitics, answers a question during testimony in front of the Senate Subcommittee on Strategic Forces and Senate Committee on Commerce, Science, and Transportation on Wednesday, July 16, 2014, at the Hart Senate Office Building in Washington, DC. The Senate hearing focused on assured access to space.

Do You Know What You Owe? Students' Understanding of Their Student Loans

ERIC Educational Resources Information Center

Andruska, Emily A.; Hogarth, Jeanne M.; Fletcher, Cynthia Needles; Forbes, Gregory R.; Wohlgemuth, Darin R.

2014-01-01

Using a data set that augments a student survey with administrative data from the Iowa State University Office of Financial Aid, the authors posed two questions: Do students know whether they have student loans? Do students know how much they owe on outstanding student loans? We used logistic and ordered logit regressions to answer these…

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

ERIC Educational Resources Information Center

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

2004-01-01

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

A Multinomial Logit Approach to Estimating Regional Inventories by Product Class

Treesearch

Lawrence Teeter; Xiaoping Zhou

1998-01-01

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

Adoption of Agri-Environmental Measures by Organic Farmers: The Role of Interpersonal Communication

ERIC Educational Resources Information Center

Unay Gailhard, Ilkay; Bavorová, Miroslava; Pirscher, Frauke

2015-01-01

Purpose: The purpose of this study is to investigate the impact of interpersonal communication on the adoption of agri-environmental measures (AEM) by organic farmers in Germany. Methodology: The study used the logit model to predict the probability of adoption behaviour, and Social Network Analysis (SNA) was conducted to analyse the question of…

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

ERIC Educational Resources Information Center

Albaqshi, Amani Mohammed H.

2017-01-01

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

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

ERIC Educational Resources Information Center

Agnew, Steve

2011-01-01

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

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

NASA Technical Reports Server (NTRS)

Molusis, J. A.

1982-01-01

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

A modified hybrid uncertain analysis method for dynamic response field of the LSOAAC with random and interval parameters

NASA Astrophysics Data System (ADS)

Zi, Bin; Zhou, Bin

2016-07-01

For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .

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

USGS Publications Warehouse

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 the variance in the fledgling counts as climate, parent age class, and landscape habitat predictors. Our logistic quantile regression model can be used for any discrete response variables with fixed upper and lower bounds.

Improved Compressive Sensing of Natural Scenes Using Localized Random Sampling

PubMed Central

Barranca, Victor J.; Kovačič, Gregor; Zhou, Douglas; Cai, David

2016-01-01

Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, localized random sampling, which yields significantly improved CS image reconstructions. For each set of localized image measurements, our sampling method first randomly selects an image pixel and then measures its nearby pixels with probability depending on their distance from the initially selected pixel. We compare the uniformly-random and localized random sampling methods over a large space of sampling parameters, and show that, for the optimal parameter choices, higher quality image reconstructions can be consistently obtained by using localized random sampling. In addition, we argue that the localized random CS optimal parameter choice is stable with respect to diverse natural images, and scales with the number of samples used for reconstruction. We expect that the localized random sampling protocol helps to explain the evolutionarily advantageous nature of receptive field structure in visual systems and suggests several future research areas in CS theory and its application to brain imaging. PMID:27555464

Bridges for Pedestrians with Random Parameters using the Stochastic Finite Elements Analysis

NASA Astrophysics Data System (ADS)

Szafran, J.; Kamiński, M.

2017-02-01

The main aim of this paper is to present a Stochastic Finite Element Method analysis with reference to principal design parameters of bridges for pedestrians: eigenfrequency and deflection of bridge span. They are considered with respect to random thickness of plates in boxed-section bridge platform, Young modulus of structural steel and static load resulting from crowd of pedestrians. The influence of the quality of the numerical model in the context of traditional FEM is shown also on the example of a simple steel shield. Steel structures with random parameters are discretized in exactly the same way as for the needs of traditional Finite Element Method. Its probabilistic version is provided thanks to the Response Function Method, where several numerical tests with random parameter values varying around its mean value enable the determination of the structural response and, thanks to the Least Squares Method, its final probabilistic moments.

Effect of cinnamon on glucose control and lipid parameters.

PubMed

Baker, William L; Gutierrez-Williams, Gabriela; White, C Michael; Kluger, Jeffrey; Coleman, Craig I

2008-01-01

To perform a meta-analysis of randomized controlled trials of cinnamon to better characterize its impact on glucose and plasma lipids. A systematic literature search through July 2007 was conducted to identify randomized placebo-controlled trials of cinnamon that reported data on A1C, fasting blood glucose (FBG), or lipid parameters. The mean change in each study end point from baseline was treated as a continuous variable, and the weighted mean difference was calculated as the difference between the mean value in the treatment and control groups. A random-effects model was used. Five prospective randomized controlled trials (n = 282) were identified. Upon meta-analysis, the use of cinnamon did not significantly alter A1C, FBG, or lipid parameters. Subgroup and sensitivity analyses did not significantly change the results. Cinnamon does not appear to improve A1C, FBG, or lipid parameters in patients with type 1 or type 2 diabetes.

Case factors affecting hearing aid recommendations by hearing care professionals.

PubMed

Gioia, Carmine; Ben-Akiva, Moshe; Kirkegaard, Matilde; Jørgensen, Ole; Jensen, Kasper; Schum, Don

2015-03-01

Professional recommendations to patients concerning hearing instrument (HI) technology levels are not currently evidence-based. Pre-fitting parameters have not been proven to be the primary indicators for optimal patient outcome with different HI technology levels. This results in subjective decision-making as regards the technology level recommendation made by professionals. The objective of this study is to gain insight into the decision-making criteria utilized by professionals when recommending HI technology levels to hearing-impaired patients. A set of patient variables (and their respective levels) was identified by professionals as determinant for their recommendation of HIs. An experimental design was developed and 21 representative patient cases were generated. The design was based on a contrastive vignette technique according to which different types of vignettes (patient cases) were randomly presented to respondents in an online survey. Based on these patient cases, professionals were asked in the survey to make a treatment recommendation. The online survey was sent to approximately 3,500 professionals from the US, Germany, France, and Italy. The professionals were randomly selected from the databases of Oticon sales companies. The manufacturer sponsoring the survey remained anonymous and was only revealed after completing the survey, if requested by the respondent. The response rate was 20.5%. Data comprised of respondent descriptions and patient case recommendations that were collected from the online survey. A binary logit modeling approach was used to identify the variables that discriminate between the respondents' recommendations of HI technology levels. The results show that HI technology levels are recommended by professionals based on their perception of the patient's activity level in life, the level of HI usage for experienced users, their age, and their speech discrimination score. Surprisingly, the patient's lifestyle as perceived by the hearing care professional, followed by speech discrimination, were the strongest factors in explaining treatment recommendation. An active patient with poor speech discrimination had a 17% chance of being recommended the highest technology level HI. For a very active patient with good speech discrimination, the probability increases to 68%. The discrepancies in HI technology level recommendations are not justified by academic research or evidence of optimal patient outcome with a different HI technology level. The paradigm of lifestyle as the significant variable identified in this study is apparently deeply anchored in the mindset of the professional despite the lack of supporting evidence. These results call for a shift in the professional's technology level recommendation practice, from nonevidence-based to a proven practice that can maximize patient outcome. American Academy of Audiology.

Onset of white striping and progression into wooden breast as defined by myopathic changes underlying Pectoralis major growth. Estimation of growth parameters as predictors for stage of myopathy progression.

PubMed

Griffin, Jacqueline Reedy; Moraes, Luis; Wick, Macdonald; Lilburn, Michael Snell

2018-02-01

The broiler industry has incurred significant economic losses due to two muscle myopathies, white striping (WS) and wooden breast (WB), affecting the Pectoralis major (P. major) of commercial broilers. The present study documented macroscopic changes occurring with age/growth in the P. major and P. minor muscles of commercial broilers from day 2 through day 46 (n = 27/day). Distinct myopathic aberrations observed in both breast muscles corresponded to the onset of WB. These distinct morphological changes were used as determinants in developing a ranking system, defining the ontogeny of WB as the following four stages: (1) WS, (2) petechial epimysium haemorrhages, (3) intramuscular haemorrhages and (4) ischaemia. A cumulative logit proportional odds model was used to relate the rank probabilities with the following growth parameters: body weight, P. major and P. minor weight/yield/length/width/depth. The best-fit model included P. major length/width/depth, P. minor width, P. major and P. minor yield as predictors for rank. Increasing P. major depth, P. minor width and P. major yield increased the odds of falling into higher ranks (more severe myopathy). Conversely, increasing P. major length, P. major width and P. minor yield increased the odds of falling into smaller ranks (less severe myopathy). This study describes the macroscopic changes associated with WB ontogeny in the development of a ranking system and the contribution of growth parameters in the determination of rank (WB severity). Results suggest that physical measurements inherent to selection for high-yielding broiler genotypes are contributing to the occurrence and severity of WS and WB.

Study on Nonlinear Vibration Analysis of Gear System with Random Parameters

NASA Astrophysics Data System (ADS)

Tong, Cao; Liu, Xiaoyuan; Fan, Li

2018-03-01

In order to study the dynamic characteristics of gear nonlinear vibration system and the influence of random parameters, firstly, a nonlinear stochastic vibration analysis model of gear 3-DOF is established based on Newton’s Law. And the random response of gear vibration is simulated by stepwise integration method. Secondly, the influence of stochastic parameters such as meshing damping, tooth side gap and excitation frequency on the dynamic response of gear nonlinear system is analyzed by using the stability analysis method such as bifurcation diagram and Lyapunov exponent method. The analysis shows that the stochastic process can not be neglected, which can cause the random bifurcation and chaos of the system response. This study will provide important reference value for vibration engineering designers.

Enhancing Security of Double Random Phase Encoding Based on Random S-Box

NASA Astrophysics Data System (ADS)

Girija, R.; Singh, Hukum

2018-06-01

In this paper, we propose a novel asymmetric cryptosystem for double random phase encoding (DRPE) using random S-Box. While utilising S-Box separately is not reliable and DRPE does not support non-linearity, so, our system unites the effectiveness of S-Box with an asymmetric system of DRPE (through Fourier transform). The uniqueness of proposed cryptosystem lies on employing high sensitivity dynamic S-Box for our DRPE system. The randomness and scalability achieved due to applied technique is an additional feature of the proposed solution. The firmness of random S-Box is investigated in terms of performance parameters such as non-linearity, strict avalanche criterion, bit independence criterion, linear and differential approximation probabilities etc. S-Boxes convey nonlinearity to cryptosystems which is a significant parameter and very essential for DRPE. The strength of proposed cryptosystem has been analysed using various parameters such as MSE, PSNR, correlation coefficient analysis, noise analysis, SVD analysis, etc. Experimental results are conferred in detail to exhibit proposed cryptosystem is highly secure.

A Note on Parameters of Random Substitutions by γ-Diagonal Matrices

NASA Astrophysics Data System (ADS)

Kang, Ju-Sung

Random substitutions are very useful and practical method for privacy-preserving schemes. In this paper we obtain the exact relationship between the estimation errors and three parameters used in the random substitutions, namely the privacy assurance metric γ, the total number n of data records, and the size N of transition matrix. We also demonstrate some simulations concerning the theoretical result.

Economic Analysis of Job-Related Attributes in Undergraduate Students' Initial Job Selection

ERIC Educational Resources Information Center

Jin, Yanhong H.; Mjelde, James W.; Litzenberg, Kerry K.

2014-01-01

Economic tradeoffs students place on location, salary, distances to natural resource amenities, size of the city where the job is located, and commuting times for their first college graduate job are estimated using a mixed logit model for a sample of Texas A&M University students. The Midwest is the least preferred area having a mean salary…

Elasticity of Demand for Tuition Fees at an Institution of Higher Education

ERIC Educational Resources Information Center

Langelett, George; Chang, Kuo-Liang; Ola' Akinfenwa, Samson; Jorgensen, Nicholas; Bhattarai, Kopila

2015-01-01

Using a conjoint survey of 161 students at South Dakota State University (SDSU), we mapped a probability-of-enrolment curve for SDSU students, consistent with demand theory. A quasi-demand curve was created from the conditional-logit model. This study shows that along with the price of tuition fees, distance from home, availability of majors, and…

Ethnic and Gender Differences in Science Graduation at Selective Colleges with Implications for Admission Policy and College Choice

ERIC Educational Resources Information Center

Smyth, Frederick L.; McArdle, John J.

2004-01-01

Using Bowen and Bok's data from 23 selective colleges, we fit multilevel logit models to test two hypotheses with implications for affirmative action and group differences in attainment of science, math, or engineering (SME) degrees. Hypothesis 1, that differences in precollege academic preparation will explain later SME graduation disparities,…

Biochemical Control of Marine Fouling

DTIC Science & Technology

1988-01-14

characterized directly. The receptors are specifically labeled with tritiated (-)- baclofen ( -chlorophenyl-GABA). This labeling is saturable, reversible (with...no change in the radioactive baclofen molecule), and stereochemically specific. Scatchard and log-logit analyses of binding data indicate that there...are approximately 1010 receptors per larva; the affinity of these receptors for (-)- baclofen is reflected by a KD = 3 x 10-7. [Our original results

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

ERIC Educational Resources Information Center

Sigfusdottir, Inga-Dora; Silver, Eric

2009-01-01

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

Exploring the Effects of Financial Aid on the Gap in Student Dropout Risks by Income Level

ERIC Educational Resources Information Center

Chen, Rong; DesJardins, Stephen L.

2008-01-01

Using national survey data and discrete-time logit modeling, this research seeks to understand whether student aid mediates the relationship between parental income and student dropout behavior. Our analysis confirms that there is a gap in dropout rates for low-income students compared with their upper income peers, and suggests that some types of…

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

Treesearch

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

1981-01-01

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

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

ERIC Educational Resources Information Center

Dixon, Pauline; Humble, Steve

2017-01-01

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

The Relation between Test Formats and Kindergarteners' Expressions of Vocabulary Knowledge

ERIC Educational Resources Information Center

Christ, Tanya; Chiu, Ming Ming; Currie, Ashelin; Cipielewski, James

2014-01-01

This study tested how 53 kindergarteners' expressions of depth of vocabulary knowledge and use in novel contexts were related to in-context and out-of-context test formats for 16 target words. Applying multilevel, multi-categorical Logit to all 1,696 test item responses, the authors found that kindergarteners were more likely to express deep…

Developing the Impossible Figures Task to Assess Visual-Spatial Talents among Chinese Students: A Rasch Measurement Model Analysis

ERIC Educational Resources Information Center

Chan, David W.

2010-01-01

Data of item responses to the Impossible Figures Task (IFT) from 492 Chinese primary, secondary, and university students were analyzed using the dichotomous Rasch measurement model. Item difficulty estimates and person ability estimates located on the same logit scale revealed that the pooled sample of Chinese students, who were relatively highly…

Cyclists' red-light running behaviours: an examination of risk-taking, opportunistic, and law-obeying behaviours.

PubMed

Pai, Chih-Wei; Jou, Rong-Chang

2014-01-01

Literature has suggested that bicyclists' red-light violations (RLVs) tend not to cause accidents although RLV is a frequent and typical bicyclist's behaviour. High association between bicyclist RLVs and accidents were, however, revealed in Taiwan. The current research explores bicyclists' RLVs by classifying crossing behaviours into three distinct manners: risk-taking, opportunistic, and law-obeying. Other variables, as well as bicyclists' crossing behaviours, were captured through the use of video cameras that were installed at selected intersections in Taoyuan County, Taiwan. Considering the unobserved heterogeneity, this research develops a mixed logit model of bicyclists' three distinct crossing behaviours. Several variables (pupils in uniform, speed limit with 60km/h) appear to have heterogeneous effects, lending support to the use of mixed logit models in bicyclist RLV research. Several factors were found to significantly increase the likelihood of bicyclists' risky behaviours, most notably: intersections with short red-light duration, T/Y intersections, when riders were pupils in uniform, when riders were riding electric bicycles, when riders were unhelmeted. Implications of the research findings, and the concluding remarks, are finally provided. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adoption and Diffusion of Evidence-Based Addiction Medications in Substance Abuse Treatment

PubMed Central

Heinrich, Carolyn J; Cummings, Grant R

2014-01-01

ObjectiveTo examine the roles of facility-and state-level factors in treatment facilities’ adoption and diffusion of pharmaceutical agents used in addiction treatment. Data SourcesSecondary data from the National Survey of Substance Abuse Treatment Services (N-SSATS), Substance Abuse and Mental Health Services Administration (SAMHSA), Centers for Medicare and Medicaid Services, Alcohol Policy Information System, and Kaiser Family Foundation. Study DesignWe estimate ordered logit and multinomial logit models to examine the relationship of state and treatment facility characteristics to the adoption and diffusion of three pharmaceutical agents over 4 years when each was at a different stage of adoption or diffusion. Data CollectionN-SSATS data with facility codes, obtained directly from SAMHSA, were linked by state identifiers to the other publicly available, secondary data. Principal FindingsThe analysis confirms the importance of awareness and exposure to the adoption behavior of others, dissemination of information about the feasibility and effectiveness of innovations, geographical clustering, and licensing and accreditation in legitimizing facilities’ adoption and continued use of pharmacotherapies in addiction treatment. ConclusionsPolicy and administrative levers exist to increase the availability of pharmaceutical technologies and their continued use by substance abuse treatment facilities. PMID:23855719

Heterogeneity in general practitioners' preferences for quality improvement programs: a choice experiment and policy simulation in France.

PubMed

Ammi, Mehdi; Peyron, Christine

2016-12-01

Despite increasing popularity, quality improvement programs (QIP) have had modest and variable impacts on enhancing the quality of physician practice. We investigate the heterogeneity of physicians' preferences as a potential explanation of these mixed results in France, where the national voluntary QIP - the CAPI - has been cancelled due to its unpopularity. We rely on a discrete choice experiment to elicit heterogeneity in physicians' preferences for the financial and non-financial components of QIP. Using mixed and latent class logit models, results show that the two models should be used in concert to shed light on different aspects of the heterogeneity in preferences. In particular, the mixed logit demonstrates that heterogeneity in preferences is concentrated on the pay-for-performance component of the QIP, while the latent class model shows that physicians can be grouped in four homogeneous groups with specific preference patterns. Using policy simulation, we compare the French CAPI with other possible QIPs, and show that the majority of the physician subgroups modelled dislike the CAPI, while favouring a QIP using only non-financial interventions. We underline the importance of modelling preference heterogeneity in designing and implementing QIPs.

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

PubMed

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

2013-10-15

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

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

PubMed

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.

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

PubMed

Tian, Xinyu; Wang, Xuefeng; Chen, Jun

2014-01-01

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

Diversity-induced resonance in the response to social norms

NASA Astrophysics Data System (ADS)

Tessone, Claudio J.; Sánchez, Angel; Schweitzer, Frank

2013-02-01

In this paper we focus on diversity-induced resonance, which was recently found in bistable, excitable, and other physical systems. We study the appearance of this phenomenon in a purely economic model of cooperating and defecting agents. An agent's contribution to a public good is seen as a social norm, so defecting agents face a social pressure, which decreases if free riding becomes widespread. In this model, diversity among agents naturally appears because of the different sensitivities towards the social norm. We study the evolution of cooperation as a response to the social norm (i) for the replicator dynamics and (ii) for the logit dynamics by means of numerical simulations. Diversity-induced resonance is observed as a maximum in the response of agents to changes in the social norm as a function of the degree of heterogeneity in the population. We provide an analytical, mean-field approach for the logit dynamics and find very good agreement with the simulations. From a socioeconomic perspective, our results show that, counterintuitively, diversity in the individual sensitivity to social norms may result in a society that better follows such norms as a whole, even if part of the population is less prone to follow them.

Joint Analysis of Binomial and Continuous Traits with a Recursive Model: A Case Study Using Mortality and Litter Size of Pigs

PubMed Central

Varona, Luis; Sorensen, Daniel

2014-01-01

This work presents a model for the joint analysis of a binomial and a Gaussian trait using a recursive parametrization that leads to a computationally efficient implementation. The model is illustrated in an analysis of mortality and litter size in two breeds of Danish pigs, Landrace and Yorkshire. Available evidence suggests that mortality of piglets increased partly as a result of successful selection for total number of piglets born. In recent years there has been a need to decrease the incidence of mortality in pig-breeding programs. We report estimates of genetic variation at the level of the logit of the probability of mortality and quantify how it is affected by the size of the litter. Several models for mortality are considered and the best fits are obtained by postulating linear and cubic relationships between the logit of the probability of mortality and litter size, for Landrace and Yorkshire, respectively. An interpretation of how the presence of genetic variation affects the probability of mortality in the population is provided and we discuss and quantify the prospects of selecting for reduced mortality, without affecting litter size. PMID:24414548

Preferences, beliefs, and self-management of diabetes.

PubMed

Sloan, Frank A; Padrón, Norma A; Platt, Alyssa C

2009-06-01

To assess relationships between self-assessed control over life events, subjective beliefs about longevity, time and risk preference, and other factors on use of recommended care for diabetes mellitus (DM), self-assessed control of diabetes, general health, and laboratory measures of HbA1c levels. Health and Retirement Study (HRS) and 2003 HRS Diabetes Study (HRS-DS). We used logit and ordered logit analyses to assess use of recommended care, and subjective and objective measures of health outcomes. Secondary analysis of HRS and HRS-DS data. Individuals with higher self-assessed control over life events and higher subjective probabilities of living 10 years engaged in more recommended DM care practices and had better self-assessed DM control and general health. However, these beliefs did not influence HbA1c levels. More highly educated and cognitively able persons were more likely to follow care recommendations. There were differences by race/ethnicity in health outcomes, but not in health investment among Hispanics. Individuals' beliefs about control over life events and longevity influenced health investment and subjective health outcomes, although these beliefs did not translate into differences in HbA1c levels. Hispanics may realize lower returns on health investments, at least for diabetes care.

CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests.

PubMed

Ma, Li; Fan, Suohai

2017-03-14

The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.

Modelling malaria incidence by an autoregressive distributed lag model with spatial component.

PubMed

Laguna, Francisco; Grillet, María Eugenia; León, José R; Ludeña, Carenne

2017-08-01

The influence of climatic variables on the dynamics of human malaria has been widely highlighted. Also, it is known that this mosquito-borne infection varies in space and time. However, when the data is spatially incomplete most popular spatio-temporal methods of analysis cannot be applied directly. In this paper, we develop a two step methodology to model the spatio-temporal dependence of malaria incidence on local rainfall, temperature, and humidity as well as the regional sea surface temperatures (SST) in the northern coast of Venezuela. First, we fit an autoregressive distributed lag model (ARDL) to the weekly data, and then, we adjust a linear separable spacial vectorial autoregressive model (VAR) to the residuals of the ARDL. Finally, the model parameters are tuned using a Markov Chain Monte Carlo (MCMC) procedure derived from the Metropolis-Hastings algorithm. Our results show that the best model to account for the variations of malaria incidence from 2001 to 2008 in 10 endemic Municipalities in North-Eastern Venezuela is a logit model that included the accumulated local precipitation in combination with the local maximum temperature of the preceding month as positive regressors. Additionally, we show that although malaria dynamics is highly heterogeneous in space, a detailed analysis of the estimated spatial parameters in our model yield important insights regarding the joint behavior of the disease incidence across the different counties in our study. Copyright © 2017 Elsevier Ltd. All rights reserved.

NTCP Modeling of Subacute/Late Laryngeal Edema Scored by Fiberoptic Examination

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

Rancati, Tiziana; Fiorino, Claudio, E-mail: fiorino.claudio@hsr.i; Sanguineti, Giuseppe

2009-11-01

Purpose: Finding best-fit parameters of normal tissue complication probability (NTCP) models for laryngeal edema after radiotherapy for head and neck cancer. Methods and Materials: Forty-eight patients were considered for this study who met the following criteria: (1) grossly uninvolved larynx, (2) no prior major surgery except for neck dissection and tonsillectomy, (3) at least one fiberoptic examination of the larynx within 2 years from radiotherapy, (4) minimum follow-up of 15 months. Larynx dose-volume histograms (DVHs) were corrected into a linear quadratic equivalent one at 2 Gy/fr with alpha/beta = 3 Gy. Subacute/late edema was prospectively scored at each follow-up examinationmore » according to the Radiation Therapy Oncology Group scale. G2-G3 edema within 15 months from RT was considered as our endpoint. Two NTCP models were considered: (1) the Lyman model with DVH reduced to the equivalent uniform dose (EUD; LEUD) and (2) the Logit model with DVH reduced to the EUD (LOGEUD). The parameters for the models were fit to patient data using a maximum likelihood analysis. Results: All patients had a minimum of 15 months follow-up (only 8/48 received concurrent chemotherapy): 25/48 (52.1%) experienced G2-G3 edema. Both NTCP models fit well the clinical data: with LOGEUD the relationship between EUD and NTCP can be described with TD50 = 46.7 +- 2.1 Gy, n = 1.41 +- 0.8 and a steepness parameter k = 7.2 +- 2.5 Gy. Best fit parameters for LEUD are n = 1.17 +- 0.6, m = 0.23 +- 0.07 and TD50 = 47.3 +- 2.1 Gy. Conclusions: A clear volume effect was found for edema, consistent with a parallel architecture of the larynx for this endpoint. On the basis of our findings, an EUD <30-35 Gy should drastically reduce the risk of G2-G3 edema.« less

The Influence of Disease Severity of Preceding Clinical Cases on Pathologists' Medical Decision Making.

PubMed

Frederick, Paul D; Nelson, Heidi D; Carney, Patricia A; Brunyé, Tad T; Allison, Kimberly H; Weaver, Donald L; Elmore, Joann G

2017-01-01

Medical decision making may be influenced by contextual factors. We evaluated whether pathologists are influenced by disease severity of recently observed cases. Pathologists independently interpreted 60 breast biopsy specimens (one slide per case; 240 total cases in the study) in a prospective randomized observational study. Pathologists interpreted the same cases in 2 phases, separated by a washout period of >6 months. Participants were not informed that the cases were identical in each phase, and the sequence was reordered randomly for each pathologist and between phases. A consensus reference diagnosis was established for each case by 3 experienced breast pathologists. Ordered logit models examined the effect the pathologists' diagnoses on the preceding case or the 5 preceding cases had on their diagnosis for the subsequent index case. Among 152 pathologists, 49 provided interpretive data in both phases I and II, 66 from only phase I, and 37 from phase II only. In phase I, pathologists were more likely to indicate a more severe diagnosis than the reference diagnosis when the preceding case was diagnosed as ductal carcinoma in situ (DCIS) or invasive cancer (proportional odds ratio [POR], 1.28; 95% confidence interval [CI], 1.15-1.42). Results were similar when considering the preceding 5 cases and for the pathologists in phase II who interpreted the same cases in a different order compared with phase I (POR, 1.17; 95% CI, 1.05-1.31). Physicians appear to be influenced by the severity of previously interpreted test cases. Understanding types and sources of diagnostic bias may lead to improved assessment of accuracy and better patient care. © The Author(s) 2016.

Changes in DNA Methylation from Age 18 to Pregnancy in Type 1, 2, and 17 T Helper and Regulatory T-Cells Pathway Genes

PubMed Central

Iqbal, Sabrina; Lockett, Gabrielle A.; Arshad, S. Hasan; Zhang, Hongmei; Kaushal, Akhilesh; Tetali, Sabarinath R.; Mukherjee, Nandini

2018-01-01

To succeed, pregnancies need to initiate immune biases towards T helper 2 (Th2) responses, yet little is known about what establishes this bias. Using the Illumina 450 K platform, we explored changes in DNA methylation (DNAm) of Th1, Th2, Th17, and regulatory T cell pathway genes before and during pregnancy. Female participants were recruited at birth (1989), and followed through age 18 years and their pregnancy (2011–2015). Peripheral blood DNAm was measured in 245 girls at 18 years; from among these girls, the DNAm of 54 women was repeatedly measured in the first (weeks 8–21, n = 39) and second (weeks 22–38, n = 35) halves of pregnancy, respectively. M-values (logit-transformed β-values of DNAm) were analyzed: First, with repeated measurement models, cytosine–phosphate–guanine sites (CpGs) of pathway genes in pregnancy and at age 18 (nonpregnant) were compared for changes (p ≤ 0.05). Second, we tested how many of the 348 pathway-related CpGs changed compared to 10 randomly selected subsets of all other CpGs and compared to 10 randomly selected subsets of other CD4+-related CpGs (348 in each subset). Contrasted to the nonpregnant state, 27.7% of Th1-related CpGs changed in the first and 36.1% in the second half of pregnancy. Among the Th2 pathway CpGs, proportions of changes were 35.1% (first) and 33.8% (second half). The methylation changes suggest involvement of both Th1 and Th2 pathway CpGs in the immune bias during pregnancy. Changes in regulatory T cell and Th17 pathways need further exploration. PMID:29415463

Randomized Controlled Trial Comparing Smartphone Assisted Versus Traditional Guided Self-Help for Adults with Binge Eating

PubMed Central

Hildebrandt, Tom; Michaelides, Andreas; Mackinnon, Dianna; Greif, Rebecca; DeBar, Lynn; Sysko, Robyn

2017-01-01

Objective Guided self-help treatments based on cognitive-behavior therapy (CBT-GSH) are efficacious for binge eating. With limited availability of CBT-GSH in the community, mobile technology offers a means to increase use of these interventions. The purpose of this study was to test the initial efficacy of Noom Monitor, a smartphone application designed to facilitate CBT-GSH (CBT-GSH+Noom), on study retention, adherence, and eating disorder symptoms compared to traditional CBT-GSH. Method Sixty-six men and women with DSM-5 binge eating disorder (BED) or bulimia nervosa (BN) were randomized to receive 8 sessions of CBT-GSH + Noom (n = 33) or CBT-GSH (n = 33) over 12 weeks. Primary symptom outcomes were Eating Disorder Examination objective bulimic episodes (OBEs), subjective bulimic episodes (SBEs), and compensatory behaviors. Assessments were collected at 0, 4, 8, 12, 24, and 36 weeks. Behavioral outcomes were modeled using zero-inflated negative-binomial latent growth curve models with intent-to-treat. Results There was a significant effect of treatment on change in OBEs (β =−0.84, 95%CI = −1.49, −0.19) favoring CBT-GSH + Noom. Remission rates were not statistically different between treatments for OBEs (βlogit =−0.73, 95%CI = −1.86, 3.27; CBT-GSH + Noom = 17/27, 63.0% vs. CBT-GSH 11/27, 40.7%, NNT = 4.5), but CBT-GSH + Noom participants reported greater meal and snack adherence and regular meal adherence mediated treatment effects on OBEs. The treatments did not differ at the 6-month follow-up. Discussion Smartphone applications for the treatment binge eating appear to have advantages for adherence, a critical component of treatment dissemination. PMID:28960384

How Caregivers and Workers Fared in Cash and Counseling

PubMed Central

Foster, Leslie; Dale, Stacy B; Brown, Randall

2007-01-01

Objectives To assess the effects of Cash and Counseling on Medicaid beneficiaries' primary informal caregivers and describe the experiences of their directly hired workers. Study Setting Beneficiaries in Arkansas, Florida, and New Jersey voluntarily enrolled in the demonstration and were randomly assigned to direct their own Medicaid supportive services as Cash and Counseling consumers (the treatment group) or to rely on Medicaid services as usual (the control group). Beneficiaries identified their primary informal caregiver during a baseline interview and their primary paid worker during a 9-month follow-up interview. Data Sources Data were collected through telephone interviews with caregivers and workers. These interviews were conducted about 10 months after beneficiaries' random assignment, between February 2000 and May 2003, depending on the state. Data Analysis Methods We estimated program effects with regression and logit models and compared the mean characteristics of directly hired workers and agency workers, by state. Principal Findings Compared with caregivers in the control group, those in the treatment group had modestly to substantially better outcomes for measures of satisfaction with care, worry, and physical and financial strain. For hours of care and emotional strain, outcomes in the treatment group were similar to or somewhat better than those in the control group. Directly hired workers reported greater satisfaction with wages, similar satisfaction with working conditions, and similar rates of injuries as agency workers. Workers who were related to the beneficiary reported more emotional strain than agency workers. Conclusions Cash and Counseling can lessen some of the burden associated with caring for a child or adult with disabilities. The experiences of hired workers suggest consumer direction is a sustainable option, but support networks for workers might be a welcome program improvement. PMID:17244295

Randomized controlled trial comparing smartphone assisted versus traditional guided self-help for adults with binge eating.

PubMed

Hildebrandt, Tom; Michaelides, Andreas; Mackinnon, Dianna; Greif, Rebecca; DeBar, Lynn; Sysko, Robyn

2017-11-01

Guided self-help treatments based on cognitive-behavior therapy (CBT-GSH) are efficacious for binge eating. With limited availability of CBT-GSH in the community, mobile technology offers a means to increase use of these interventions. The purpose of this study was to test the initial efficacy of Noom Monitor, a smartphone application designed to facilitate CBT-GSH (CBT-GSH + Noom), on study retention, adherence, and eating disorder symptoms compared to traditional CBT-GSH. Sixty-six men and women with DSM-5 binge-eating disorder (BED) or bulimia nervosa (BN) were randomized to receive eight sessions of CBT-GSH + Noom (n = 33) or CBT-GSH (n = 33) over 12 weeks. Primary symptom outcomes were eating disorder examination objective bulimic episodes (OBEs), subjective bulimic episodes (SBEs), and compensatory behaviors. Assessments were collected at 0, 4, 8, 12, 24, and 36 weeks. Behavioral outcomes were modeled using zero-inflated negative-binomial latent growth curve models with intent-to-treat. There was a significant effect of treatment on change in OBEs (β = -0.84, 95% CI = -1.49, -0.19) favoring CBT-GSH + Noom. Remission rates were not statistically different between treatments for OBEs (β logit  = -0.73, 95% CI = -1.86, 3.27; CBT-GSH-Noom = 17/27, 63.0% vs. CBT-GSH 11/27, 40.7%, NNT = 4.5), but CBT-GSH-Noom participants reported greater meal and snack adherence and regular meal adherence mediated treatment effects on OBEs. The treatments did not differ at the 6-month follow-up. Smartphone applications for the treatment binge eating appear to have advantages for adherence, a critical component of treatment dissemination. © 2017 Wiley Periodicals, Inc.

Nonlinear consolidation in randomly heterogeneous highly compressible aquitards

NASA Astrophysics Data System (ADS)

Zapata-Norberto, Berenice; Morales-Casique, Eric; Herrera, Graciela S.

2018-05-01

Severe land subsidence due to groundwater extraction may occur in multiaquifer systems where highly compressible aquitards are present. The highly compressible nature of the aquitards leads to nonlinear consolidation where the groundwater flow parameters are stress-dependent. The case is further complicated by the heterogeneity of the hydrogeologic and geotechnical properties of the aquitards. The effect of realistic vertical heterogeneity of hydrogeologic and geotechnical parameters on the consolidation of highly compressible aquitards is investigated by means of one-dimensional Monte Carlo numerical simulations where the lower boundary represents the effect of an instant drop in hydraulic head due to groundwater pumping. Two thousand realizations are generated for each of the following parameters: hydraulic conductivity ( K), compression index ( C c), void ratio ( e) and m (an empirical parameter relating hydraulic conductivity and void ratio). The correlation structure, the mean and the variance for each parameter were obtained from a literature review about field studies in the lacustrine sediments of Mexico City. The results indicate that among the parameters considered, random K has the largest effect on the ensemble average behavior of the system when compared to a nonlinear consolidation model with deterministic initial parameters. The deterministic solution underestimates the ensemble average of total settlement when initial K is random. In addition, random K leads to the largest variance (and therefore largest uncertainty) of total settlement, groundwater flux and time to reach steady-state conditions.

Random sampling and validation of covariance matrices of resonance parameters

NASA Astrophysics Data System (ADS)

Plevnik, Lucijan; Zerovnik, Gašper

2017-09-01

Analytically exact methods for random sampling of arbitrary correlated parameters are presented. Emphasis is given on one hand on the possible inconsistencies in the covariance data, concentrating on the positive semi-definiteness and consistent sampling of correlated inherently positive parameters, and on the other hand on optimization of the implementation of the methods itself. The methods have been applied in the program ENDSAM, written in the Fortran language, which from a file from a nuclear data library of a chosen isotope in ENDF-6 format produces an arbitrary number of new files in ENDF-6 format which contain values of random samples of resonance parameters (in accordance with corresponding covariance matrices) in places of original values. The source code for the program ENDSAM is available from the OECD/NEA Data Bank. The program works in the following steps: reads resonance parameters and their covariance data from nuclear data library, checks whether the covariance data is consistent, and produces random samples of resonance parameters. The code has been validated with both realistic and artificial data to show that the produced samples are statistically consistent. Additionally, the code was used to validate covariance data in existing nuclear data libraries. A list of inconsistencies, observed in covariance data of resonance parameters in ENDF-VII.1, JEFF-3.2 and JENDL-4.0 is presented. For now, the work has been limited to resonance parameters, however the methods presented are general and can in principle be extended to sampling and validation of any nuclear data.

Effects of messages emphasizing environmental determinants of obesity on intentions to engage in diet and exercise behaviors.

PubMed

Niederdeppe, Jeff; Roh, Sungjong; Shapiro, Michael A; Kim, Hye Kyung

2013-12-12

Reducing rates of obesity will require interventions that influence both individual decisions and environmental factors through changes in public policy. Previous work indicates that messages emphasizing environmental determinants increases support for public policies, but some suspect this strategy may undermine motivation to engage in diet and exercise. Study 1 involved 485 adults recruited from a shopping mall in New York. Study 2 involved 718 adult members of a Web-based national panel of US adults. Respondents in both studies were randomly assigned to read a story that emphasized environmental determinants of health or a control condition. The stories varied in the extent to which they described the story character as taking personal responsibility for weight management. Logistic regression and ordered logit models were used to test for differences in intentions to engage in diet and exercise behaviors based on which story the participant read. Analyses were also performed separately by participants' weight status. In both studies, messages that acknowledged personal responsibility while emphasizing environmental causes of obesity increased intentions to engage in healthy behavior for at least 1 weight status group. Emphasizing factors outside of personal control appears to enhance rather than undermine motivations to engage in healthy diet and exercise behavior.

Willingness-To-Accept Pharmaceutical Retail Inconvenience: Evidence from a Contingent Choice Experiment

PubMed Central

Finlay, Keith; Stoecker, Charles; Cunningham, Scott

2015-01-01

Objectives Restrictions on retail purchases of pseudoephedrine are one regulatory approach to reduce the social costs of methamphetamine production and use, but may impose costs on legitimate users of nasal decongestants. This is the first study to evaluate the costs of restricting access to medications on consumer welfare. Our objective was to measure the inconvenience cost consumers place on restrictions for cold medication purchases including identification requirements, purchase limits, over-the-counter availability, prescription requirements, and the active ingredient. Methods We conducted a contingent choice experiment with Amazon Mechanical Turk workers that presented participants with randomized, hypothetical product prices and combinations of restrictions that reflect the range of public policies. We used a conditional logit model to calculate willingness-to-accept each restriction. Results Respondents’ willingness-to-accept prescription requirements was $14.17 ($9.76–$18.58) and behind-the-counter restrictions was $9.68 ($7.03–$12.33) per box of pseudoephedrine product. Participants were willing to pay $4.09 ($1.66–$6.52) per box to purchase pseudoephedrine-based products over phenylephrine-based products. Conclusions Restricting access to medicines as a means of reducing the social costs of non-medical use can imply large inconvenience costs for legitimate consumers. These results are relevant to discussions of retail access restrictions on other medications. PMID:26024444

Willingness-to-accept pharmaceutical retail inconvenience: evidence from a contingent choice experiment.

PubMed

Finlay, Keith; Stoecker, Charles; Cunningham, Scott

2015-01-01

Restrictions on retail purchases of pseudoephedrine are one regulatory approach to reduce the social costs of methamphetamine production and use, but may impose costs on legitimate users of nasal decongestants. This is the first study to evaluate the costs of restricting access to medications on consumer welfare. Our objective was to measure the inconvenience cost consumers place on restrictions for cold medication purchases including identification requirements, purchase limits, over-the-counter availability, prescription requirements, and the active ingredient. We conducted a contingent choice experiment with Amazon Mechanical Turk workers that presented participants with randomized, hypothetical product prices and combinations of restrictions that reflect the range of public policies. We used a conditional logit model to calculate willingness-to-accept each restriction. Respondents' willingness-to-accept prescription requirements was $14.17 ($9.76-$18.58) and behind-the-counter restrictions was $9.68 ($7.03-$12.33) per box of pseudoephedrine product. Participants were willing to pay $4.09 ($1.66-$6.52) per box to purchase pseudoephedrine-based products over phenylephrine-based products. Restricting access to medicines as a means of reducing the social costs of non-medical use can imply large inconvenience costs for legitimate consumers. These results are relevant to discussions of retail access restrictions on other medications.

Preferences for physician services in Ukraine: a discrete choice experiment.

PubMed

Danyliv, Andriy; Pavlova, Milena; Gryga, Irena; Groot, Wim

2015-01-01

Evidence on preferences of Ukrainian consumers for healthcare improvements can help to design reforms that correspond to societal priorities. This study aims to elicit and to place monetary values on public preferences for out-patient physician services in Ukraine. The method of discrete choice experiment is used on a sample of 303 respondents, representative of the adult Ukrainian population. The random effect logit model with interactions provides the best fit for the data and is used to calculate the marginal willingness to pay (MWTP) for quality and access improvements. At a sample level, there is no clear preference to pay formally rather than informally or vice versa. We also do not find that visiting a general practitioner is preferred over direct access to a medical specialist. However, there are differences between population groups. Quality-related attributes of physician services appear important to respondents, especially the attitude of medical staff. Thus, interpersonal aspects of out-patient care should be given priority in decisions about investments in quality improvements. Other aspects, that is social quality and access, are important as well but their improvement brings fewer social gains. Measures should be taken to eradicate the informal payment channels and to strengthen the gate-keeping role of primary care. Copyright © 2014 John Wiley & Sons, Ltd.

The Effect of Mystery Shopper Reports on Age Verification for Tobacco Purchases

PubMed Central

KREVOR, BRAD S.; PONICKI, WILLIAM R.; GRUBE, JOEL W.; DeJONG, WILLIAM

2011-01-01

Mystery shops (MS) involving attempted tobacco purchases by young buyers have been employed to monitor retail stores’ performance in refusing underage sales. Anecdotal evidence suggests that MS visits with immediate feedback to store personnel can improve age verification. This study investigated the impact of monthly and twice-monthly MS reports on age verification. Forty-five Walgreens stores were each visited 20 times by mystery shoppers. The stores were randomly assigned to one of three conditions. Control group stores received no feedback, whereas two treatment groups received feedback communications every visit (twice monthly) or every second visit (monthly) after baseline. Logit regression models tested whether each treatment group improved verification rates relative to the control group. Post-baseline verification rates were higher in both treatment groups than in the control group, but only the stores receiving monthly communications had a significantly greater improvement than control group stores. Verification rates increased significantly during the study period for all three groups, with delayed improvement among control group stores. Communication between managers regarding the MS program may account for the delayed age-verification improvements observed in the control group stores. Encouraging inter-store communication might extend the benefits of MS programs beyond those stores that receive this intervention. PMID:21541874

Patient satisfaction, empowerment, and health and disability status effects of a disease management-health promotion nurse intervention among Medicare beneficiaries with disabilities.

PubMed

Friedman, Bruce; Wamsley, Brenda R; Liebel, Dianne V; Saad, Zabedah B; Eggert, Gerald M

2009-12-01

To report the impact on patient and informal caregiver satisfaction, patient empowerment, and health and disability status of a primary care-affiliated disease self-management-health promotion nurse intervention for Medicare beneficiaries with disabilities and recent significant health services use. The Medicare Primary and Consumer-Directed Care Demonstration was a 24-month randomized controlled trial that included a nurse intervention. The present study (N = 766) compares the nurse (n = 382) and control (n = 384) groups. Generalized linear models for repeated measures, linear regression, and ordered logit regression were used. The patients whose activities of daily living (ADL) were reported by the same respondent at baseline and 22 months following baseline had significantly fewer dependencies at 22 months than did the control group (p = .038). This constituted the vast majority of respondents. In addition, patient satisfaction significantly improved for 6 of 7 domains, whereas caregiver satisfaction improved for 2 of 8 domains. However, the intervention had no effect on empowerment, self-rated health, the SF-36 physical and mental health summary scores, and the number of dependencies in instrumental ADL. If confirmed in other studies, this intervention holds the potential to reduce the rate of functional decline and improve satisfaction for Medicare beneficiaries with ADL dependence.

Stability and change in fertility preferences among young women in Malawi.

PubMed

Sennott, Christie; Yeatman, Sara

2012-03-01

Although studies have demonstrated change in fertility preferences over time, there is a lack of definitive knowledge about the level and direction of change among individuals, especially young and unmarried women. Furthermore, little is known about the factors associated with changes in fertility preferences over time. The analysis uses the first five waves of data from a longitudinal study of a random sample of women aged 15-25 in southern Malawi. The data were collected four months apart over an 18-month period, between June 2009 and December 2010. Multinomial logit regression models were used to calculate relative risk ratios and identify associations between four categories of life events-reproductive, relationship, health and economic-and shifts in fertility timing preferences. In each four-month period, more than half of the women reported changes in the desired timing of their next birth, and delays and accelerations in timing desires were common. Several life events, including having a child, entering a serious relationship and changes in household finances were associated with changes in the level and direction of fertility preference. Shifts in fertility timing preferences often occur in response to changes in life circumstances. Understanding the reasons for these shifts may aid family planning providers in meeting women's contraceptive needs.

A fashion model with social interaction

NASA Astrophysics Data System (ADS)

Nakayama, Shoichiro; Nakamura, Yasuyuki

2004-06-01

In general, it is difficult to investigate social phenomena mathematically or quantitatively due to non-linear interactions. Statistical physics can provide powerful methods for studying social phenomena with interactions, and could be very useful for them. In this study, we take a focus on fashion as a social phenomenon with interaction. The social interaction considered here are “bandwagon effect” and “snob effect.” In the bandwagon effect, the correlation between one's behavior and others is positive. People feel fashion weary or boring when it is overly popular. This is the snob effect. It is assumed that the fashion phenomenon is formed by the aggregation of individual's binary choice, that is, the fashion is adopted or not. We formulate the fashion phenomenon as the logit model, which is based on the random utility theory in social science, especially economics. The model derived here basically has the similarity with the pioneering model by Weidlich (Phys. Rep. 204 (1991) 1), which was derived from the master equation, the Langevin equation, or the Fokker-Planck equation. This study seems to give the behavioral or behaviormetrical foundation to his model. As a result of dynamical analysis, it is found that in the case that both the bandwagon effect and the snob effect work, periodic or chaotic behavior of fashion occurs under certain conditions.

Effects of Messages Emphasizing Environmental Determinants of Obesity on Intentions to Engage in Diet and Exercise Behaviors

PubMed Central

Roh, Sungjong; Shapiro, Michael A.; Kim, Hye Kyung

2013-01-01

Introduction Reducing rates of obesity will require interventions that influence both individual decisions and environmental factors through changes in public policy. Previous work indicates that messages emphasizing environmental determinants increases support for public policies, but some suspect this strategy may undermine motivation to engage in diet and exercise. Methods Study 1 involved 485 adults recruited from a shopping mall in New York. Study 2 involved 718 adult members of a Web-based national panel of US adults. Respondents in both studies were randomly assigned to read a story that emphasized environmental determinants of health or a control condition. The stories varied in the extent to which they described the story character as taking personal responsibility for weight management. Logistic regression and ordered logit models were used to test for differences in intentions to engage in diet and exercise behaviors based on which story the participant read. Analyses were also performed separately by participants’ weight status. Results In both studies, messages that acknowledged personal responsibility while emphasizing environmental causes of obesity increased intentions to engage in healthy behavior for at least 1 weight status group. Conclusion Emphasizing factors outside of personal control appears to enhance rather than undermine motivations to engage in healthy diet and exercise behavior. PMID:24331282

Development and validation of a mortality risk model for pediatric sepsis.

PubMed

Chen, Mengshi; Lu, Xiulan; Hu, Li; Liu, Pingping; Zhao, Wenjiao; Yan, Haipeng; Tang, Liang; Zhu, Yimin; Xiao, Zhenghui; Chen, Lizhang; Tan, Hongzhuan

2017-05-01

Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial.We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities.According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively.The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients.

Development and validation of a mortality risk model for pediatric sepsis

PubMed Central

Chen, Mengshi; Lu, Xiulan; Hu, Li; Liu, Pingping; Zhao, Wenjiao; Yan, Haipeng; Tang, Liang; Zhu, Yimin; Xiao, Zhenghui; Chen, Lizhang; Tan, Hongzhuan

2017-01-01

Abstract Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial. We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities. According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively. The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients. PMID:28514310

The effect of mystery shopper reports on age verification for tobacco purchases.

PubMed

Krevor, Brad S; Ponicki, William R; Grube, Joel W; DeJong, William

2011-09-01

Mystery shops involving attempted tobacco purchases by young buyers have been implemented in order to monitor retail stores' performance in refusing underage sales. Anecdotal evidence suggests that mystery shop visits with immediate feedback to store personnel can improve age verification. This study investigated the effect of monthly and twice-monthly mystery shop reports on age verification. Mystery shoppers visited 45 Walgreens stores 20 times. The stores were randomly assigned to 1 of 3 conditions. Control group stores received no feedback, whereas 2 treatment groups received feedback communications on every visit (twice monthly) or on every second visit (monthly) after baseline. Logit regression models tested whether each treatment group improved verification rates relative to the control group. Postbaseline verification rates were higher in both treatment groups than in the control group, but only the stores receiving monthly communications had a significantly greater improvement compared with the control group stores. Verification rates increased significantly during the study period for all 3 groups, with delayed improvement among control group stores. Communication between managers regarding the mystery shop program may account for the delayed age-verification improvements observed in the control group stores. Encouraging interstore communication might extend the benefits of mystery shop programs beyond those stores that receive this intervention. Copyright © Taylor & Francis Group, LLC

Stay or Migrate? An Empirical Study of the Relationship between Place of Work, Place of Study and Birthplace

ERIC Educational Resources Information Center

Liping, Ma; Kunfeng, Pan

2014-01-01

Based on a 2009 national survey on college graduate employment in China, this article analyzes the relationship of college graduates' place of work to their birthplace and where they attend college, using a conditional logit model. The findings indicate that graduates tend to stay to work in their birthplaces or places of study, controlling for…

Determining the Relationship Between Moral Waivers and Marine Corps Unsuitability Attrition

DTIC Science & Technology

2008-03-01

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

An analysis of factors affecting participation behavior of limited resource farmers in agricultural cost-share programs in Alabama

Treesearch

Okwudili Onianwa; Gerald Wheelock; Buddhi Gyawali; Jianbang Gan; Mark Dubois; John Schelhas

2004-01-01

This study examines factors that affect the participation behavior of limited resource farmers in agricultural cost-share programs in Alabama. The data were generated from a survey administered to a sample of limited resource farm operators. A binary logit model was employed to analyze the data. Results indicate that college education, age, gross sales, ratio of owned...

A mixed logit model of homeowner preferences for wildfire hazard reduction

Treesearch

Thomas P. Holmes; John Loomis; Armando González-Cabán

2009-01-01

People living in the wildland-urban interface (WUI) are at greater risk of suffering major losses of property and life from wildfires. Over the past several decades the prevailing view has been that wildfire risk in rural areas was exogenous to the activities of homeowners. In response to catastrophic fires in the WUI over the past few years, recent approaches to fire...

A Mixed Logit Model of Homeowner Preferences for Wildfire Hazard Reduction

Treesearch

Thomas P. Holmes; John Loomis; Armando Gonzalez-Caban

2010-01-01

People living in the wildland-urban interface (WUI) are at greater risk of suffering major losses of property and life from wildfires. Over the past several decades the prevailing view has been that wildfire risk in rural areas was exogenous to the activities of homeowners. In response to catastrophic fires in the WUI over the past few years, recent approaches to fire...

Life Satisfaction among Turkish and Moroccan Immigrants in the Netherlands: The Role of Absolute and Relative Income

ERIC Educational Resources Information Center

Gokdemir, Ozge; Dumludag, Devrim

2012-01-01

In this paper we investigate the role of several socio-economic and non-economic factors such as absolute and relative income, education and religion to explain the differences of happiness levels of Turkish and Moroccan Immigrants in the Netherlands by using ordered logit model. We focus on members of the Moroccan and Turkish communities, as…

Three-dimensional prediction of soil physical, chemical, and hydrological properties in a forested catchment of the Santa Catalina CZO

NASA Astrophysics Data System (ADS)

Shepard, C.; Holleran, M.; Lybrand, R. A.; Rasmussen, C.

2014-12-01

Understanding critical zone evolution and function requires an accurate assessment of local soil properties. Two-dimensional (2D) digital soil mapping provides a general assessment of soil characteristics across a sampled landscape, but lacks the ability to predict soil properties with depth. The utilization of mass-preserving spline functions enable the extrapolation of soil properties with depth, extending predictive functions to three-dimensions (3D). The present study was completed in the Marshall Gulch (MG) catchment, located in the Santa Catalina Mountains, 30 km northwest of Tucson, Arizona, as part of the Santa Catalina-Jemez Mountains Critical Zone Observatory. Twenty-four soil pits were excavated and described following standard procedures. Mass-preserving splines were used to extrapolate mass carbon (kg C m-2); percent clay, silt, and sand (%); sodium mass flux (kg Na m-2); and pH for 24 sampled soil pits in 1-cm depth increments. Saturated volumetric water content (θs) and volumetric water content at 10 kPa (θ10) were predicted using ROSETTA and established empirical relationships. The described profiles were all sampled to differing depths; to compensate for the unevenness of the profile descriptions, the soil depths were standardized from 0.0 to 1.0 and then split into five equal standard depth sections. A logit-transformation was used to normalize the target variables. Step-wise regressions were calculated using available environmental covariates to predict the properties of each variable across the catchment in each depth section, and interpolated model residuals added back to the predicted layers to generate the final soil maps. Logit-transformed R2 for the predictive functions varied widely, ranging from 0.20 to 0.79, with logit-transformed RMSE ranging from 0.15 to 2.77. The MG catchment was further classified into clusters with similar properties based on the environmental covariates, and representative depth functions for each target variable in each cluster calculated. Mass-preserving splines combined with stepwise regressions are an effective tool for predicting soil physical, chemical, and hydrological properties with depth, enhancing our understanding of the critical zone.

Advanced techniques for modeling avian nest survival

USGS Publications Warehouse

Dinsmore, S.J.; White, Gary C.; Knopf, F.L.

2002-01-01

Estimation of avian nest survival has traditionally involved simple measures of apparent nest survival or Mayfield constant-nest-survival models. However, these methods do not allow researchers to build models that rigorously assess the importance of a wide range of biological factors that affect nest survival. Models that incorporate greater detail, such as temporal variation in nest survival and covariates representative of individual nests represent a substantial improvement over traditional estimation methods. In an attempt to improve nest survival estimation procedures, we introduce the nest survival model now available in the program MARK and demonstrate its use on a nesting study of Mountain Plovers (Charadrius montanus Townsend) in Montana, USA. We modeled the daily survival of Mountain Plover nests as a function of the sex of the incubating adult, nest age, year, linear and quadratic time trends, and two weather covariates (maximum daily temperature and daily precipitation) during a six-year study (1995–2000). We found no evidence for yearly differences or an effect of maximum daily temperature on the daily nest survival of Mountain Plovers. Survival rates of nests tended by female and male plovers differed (female rate = 0.33; male rate = 0.49). The estimate of the additive effect for males on nest survival rate was 0.37 (95% confidence limits were 0.03, 0.71) on a logit scale. Daily survival rates of nests increased with nest age; the estimate of daily nest-age change in survival in the best model was 0.06 (95% confidence limits were 0.04, 0.09) on a logit scale. Daily precipitation decreased the probability that the nest would survive to the next day; the estimate of the additive effect of daily precipitation on the nest survival rate was −1.08 (95% confidence limits were −2.12, −0.13) on a logit scale. Our approach to modeling daily nest-survival rates allowed several biological factors of interest to be easily included in nest survival models and allowed us to generate more biologically meaningful estimates of nest survival.

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

NASA Astrophysics Data System (ADS)

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 choice data set, and find that model selection is invariant to prior specification, while model derivatives like willingness-to-pay are notably sensitive to model choice. I also find that the Laplace approximation is remarkably accurate in spite of the potential for nested logit models to have irregular likelihood surfaces.

Dialysis modality preference of patients with CKD and family caregivers: a discrete-choice study.

PubMed

Morton, Rachael L; Snelling, Paul; Webster, Angela C; Rose, John; Masterson, Rosemary; Johnson, David W; Howard, Kirsten

2012-07-01

Dialysis modality preferences of patients with chronic kidney disease (CKD) and family caregivers are important, yet rarely quantified. Prospective, unlabeled, discrete-choice experiment with random-parameter logit analysis. Adults with stages 3-5 CKD and caregivers educated about dialysis treatment options from 8 Australian renal clinics. Preferences for and trade-offs between the dialysis treatment attributes of life expectancy, number of hospital visits per week, ability to travel, hours per treatment, treatment time of day, subsidized transport service, and flexibility of treatment schedule. Results presented as ORs for preferring home-based or in-center dialysis to conservative care. 105 predialysis patients and 73 family caregivers completed the study. Median patient age was 63 years, and mean estimated glomerular filtration rate was 18.1 (range, 6-34) mL/min/1.73 m(2). Median caregiver age was 61 years. Home-based dialysis (either peritoneal or home hemodialysis) was chosen by patients in 65% of choice sets; in-center dialysis, in 35%; and conservative care, in 10%. For caregivers, this was 72%, 25%, and 3%, respectively. Both patients and caregivers preferred longer rather than shorter hours of dialysis (ORs of 2.02 [95% CI, 1.51-2.70] and 2.67 [95% CI, 1.85-3.85] for patients and caregivers, respectively), but were less likely to choose nocturnal than daytime dialysis (ORs of 0.07 [95% CI, 0.01-0.75] and 0.03 [95% CI, 0.01-0.20]). Patients were willing to forgo 23 (95% CI, 19-27) months of life expectancy with home-based dialysis to decrease their travel restrictions. For caregivers, this was 17 (95% CI, 16-18) patient-months. Data were limited to stated preferences rather than actual choice of dialysis modality. Our study suggests that it is rare for caregivers to prefer conservative nondialytic care for family members with CKD. Home-based dialysis modalities that enable patients and their family members to travel with minimal restriction would be strongly aligned with the preferences of both parties. Copyright © 2012 National Kidney Foundation, Inc. All rights reserved.

A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.

PubMed

Fiero, Mallorie H; Hsu, Chiu-Hsieh; Bell, Melanie L

2017-11-20

We extend the pattern-mixture approach to handle missing continuous outcome data in longitudinal cluster randomized trials, which randomize groups of individuals to treatment arms, rather than the individuals themselves. Individuals who drop out at the same time point are grouped into the same dropout pattern. We approach extrapolation of the pattern-mixture model by applying multilevel multiple imputation, which imputes missing values while appropriately accounting for the hierarchical data structure found in cluster randomized trials. To assess parameters of interest under various missing data assumptions, imputed values are multiplied by a sensitivity parameter, k, which increases or decreases imputed values. Using simulated data, we show that estimates of parameters of interest can vary widely under differing missing data assumptions. We conduct a sensitivity analysis using real data from a cluster randomized trial by increasing k until the treatment effect inference changes. By performing a sensitivity analysis for missing data, researchers can assess whether certain missing data assumptions are reasonable for their cluster randomized trial. Copyright © 2017 John Wiley & Sons, Ltd.

Large Uncertainty in Estimating pCO2 From Carbonate Equilibria in Lakes

NASA Astrophysics Data System (ADS)

Golub, Malgorzata; Desai, Ankur R.; McKinley, Galen A.; Remucal, Christina K.; Stanley, Emily H.

2017-11-01

Most estimates of carbon dioxide (CO2) evasion from freshwaters rely on calculating partial pressure of aquatic CO2 (pCO2) from two out of three CO2-related parameters using carbonate equilibria. However, the pCO2 uncertainty has not been systematically evaluated across multiple lake types and equilibria. We quantified random errors in pH, dissolved inorganic carbon, alkalinity, and temperature from the North Temperate Lakes Long-Term Ecological Research site in four lake groups across a broad gradient of chemical composition. These errors were propagated onto pCO2 calculated from three carbonate equilibria, and for overlapping observations, compared against uncertainties in directly measured pCO2. The empirical random errors in CO2-related parameters were mostly below 2% of their median values. Resulting random pCO2 errors ranged from ±3.7% to ±31.5% of the median depending on alkalinity group and choice of input parameter pairs. Temperature uncertainty had a negligible effect on pCO2. When compared with direct pCO2 measurements, all parameter combinations produced biased pCO2 estimates with less than one third of total uncertainty explained by random pCO2 errors, indicating that systematic uncertainty dominates over random error. Multidecadal trend of pCO2 was difficult to reconstruct from uncertain historical observations of CO2-related parameters. Given poor precision and accuracy of pCO2 estimates derived from virtually any combination of two CO2-related parameters, we recommend direct pCO2 measurements where possible. To achieve consistently robust estimates of CO2 emissions from freshwater components of terrestrial carbon balances, future efforts should focus on improving accuracy and precision of CO2-related parameters (including direct pCO2) measurements and associated pCO2 calculations.

Item selection via Bayesian IRT models.

PubMed

Arima, Serena

2015-02-10

With reference to a questionnaire that aimed to assess the quality of life for dysarthric speakers, we investigate the usefulness of a model-based procedure for reducing the number of items. We propose a mixed cumulative logit model, which is known in the psychometrics literature as the graded response model: responses to different items are modelled as a function of individual latent traits and as a function of item characteristics, such as their difficulty and their discrimination power. We jointly model the discrimination and the difficulty parameters by using a k-component mixture of normal distributions. Mixture components correspond to disjoint groups of items. Items that belong to the same groups can be considered equivalent in terms of both difficulty and discrimination power. According to decision criteria, we select a subset of items such that the reduced questionnaire is able to provide the same information that the complete questionnaire provides. The model is estimated by using a Bayesian approach, and the choice of the number of mixture components is justified according to information criteria. We illustrate the proposed approach on the basis of data that are collected for 104 dysarthric patients by local health authorities in Lecce and in Milan. Copyright © 2014 John Wiley & Sons, Ltd.

PEER REVIEW FOR THE CONSUMER VEHICLE CHOICE ...

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency’s (EPA) Office of Transportation and Air Quality (OTAQ) has recently sponsored the development of a Consumer Vehicle Choice Model (CVCM) by the Oak Ridge National Laboratory (ORNL). The specification by OTAQ to ORNL for consumer choice model development was to develop a Nested Multinomial Logit (NMNL) or other appropriate model capable of estimating the consumer surplus impacts and the sales mix effects of greenhouse gas (GHG) emission standards. The CVCM will use output from the EPA’s Optimization Model for reducing Emissions of Greenhouse gases from Automobiles (OMEGA), including changes in retail price equivalents, changes in fuel economy, and changes in emissions, to estimate these impacts. In addition, the CVCM will accept approximately 60 vehicle types, with the flexibility to function with fewer or more vehicle types, and will use a 15 year planning horizon, matching the OMEGA parameters. It will be calibrated to baseline sales projection data provided by the EPA and will include a buy/no-buy option to simulate the possibility that consumers will choose to keep their old vehicle or to buy a used vehicle. To support EPA's future assessment of potential light duty greenhouse gas standards

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)

PubMed Central

Xu, Chonggang; Gertner, George

2013-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements. PMID:24143037

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

PubMed

Xu, Chonggang; Gertner, George

2011-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

Parameter identification using a creeping-random-search algorithm

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1971-01-01

A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.

Conservation of Shannon's redundancy for proteins. [information theory applied to amino acid sequences

NASA Technical Reports Server (NTRS)

Gatlin, L. L.

1974-01-01

Concepts of information theory are applied to examine various proteins in terms of their redundancy in natural originators such as animals and plants. The Monte Carlo method is used to derive information parameters for random protein sequences. Real protein sequence parameters are compared with the standard parameters of protein sequences having a specific length. The tendency of a chain to contain some amino acids more frequently than others and the tendency of a chain to contain certain amino acid pairs more frequently than other pairs are used as randomness measures of individual protein sequences. Non-periodic proteins are generally found to have random Shannon redundancies except in cases of constraints due to short chain length and genetic codes. Redundant characteristics of highly periodic proteins are discussed. A degree of periodicity parameter is derived.

From micro-correlations to macro-correlations

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

Eliazar, Iddo, E-mail: iddo.eliazar@intel.com

2016-11-15

Random vectors with a symmetric correlation structure share a common value of pair-wise correlation between their different components. The symmetric correlation structure appears in a multitude of settings, e.g. mixture models. In a mixture model the components of the random vector are drawn independently from a general probability distribution that is determined by an underlying parameter, and the parameter itself is randomized. In this paper we study the overall correlation of high-dimensional random vectors with a symmetric correlation structure. Considering such a random vector, and terming its pair-wise correlation “micro-correlation”, we use an asymptotic analysis to derive the random vector’smore » “macro-correlation” : a score that takes values in the unit interval, and that quantifies the random vector’s overall correlation. The method of obtaining macro-correlations from micro-correlations is then applied to a diverse collection of frameworks that demonstrate the method’s wide applicability.« less

Them That's Got: How Tie Formation in Partnership Networks Gives High Schools Differential Access to Social Capital

ERIC Educational Resources Information Center

Bridwell-Mitchell, E. N.

2017-01-01

School partnerships are important sources of school social capital. Schools may have unequal access to social capital due to the pattern of relationships in the school-partner network. Using data on school resource needs, sociometric measures, and a set of multilevel logit models, the results of a study of 211 New York City public high schools and…

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

ERIC Educational Resources Information Center

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

2006-01-01

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

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

Treesearch

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

2008-01-01

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

Forest resources, government policy, and investment location decisions of the forest products industry in the southern United States

Treesearch

Changyou Sun; Daowei Zhang

2010-01-01

In this article, the results of an initial attempt to estimate the effects of state attributes on plant location and investment expenditure were presented for the forest products industry in the southern United States. A conditional logit model was used to analyze new plant births, and a time-series cross-section model to assess the total capital expenditure....

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

ERIC Educational Resources Information Center

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…

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

ERIC Educational Resources Information Center

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…

AGARD Flight Test Instrumentation Series. Volume 14. The Analysis of Random Data

DTIC Science & Technology

1981-11-01

obtained at arbitrary times during a number of flights. No constraints have been placed upon the controlling parameters, so that the process is non ...34noisy" environment controlling a non -linear system (the aircraft) using a redundant net of control parameters. when aircraft were flown manually with...structure. Cuse 2. Non -Stationary Measurements. When the 114S value of a random signal varies with parameters which cannot be controlled , then the method

Why Did People Move During the Great Recession?: The Role of Economics in Migration Decisions

PubMed Central

Levy, Brian L.; Mouw, Ted; Daniel Perez, Anthony

2017-01-01

Labor migration offers an important mechanism to reallocate workers when there are regional differences in employment conditions. Whereas conventional wisdom suggests migration rates should increase during recessions as workers move out of areas that are hit hardest, initial evidence suggested that overall migration rates declined during the Great Recession, despite large regional differences in unemployment and growth rates. In this paper, we use data from the American Community Survey to analyze internal migration trends before and during the economic downturn. First, we find only a modest decline in the odds of adults leaving distressed labor market areas during the recession, which may result in part from challenges related to the housing price crash. Second, we estimate conditional logit models of destination choice for individuals who migrate across labor market areas and find a substantial effect of economic factors such as labor demand, unemployment, and housing values. We also estimate latent class conditional logit models that test whether there is heterogeneity in preferences for destination characteristics among migrants. Over all, the latent class models suggest that roughly equal percentages of migrants were motivated by economic factors before and during the recession. We conclude that fears of dramatic declines in labor migration seem to be unsubstantiated. PMID:28547003

Valuing air quality impacts using stated choice analysis: trading off visibility against morbidity effects.

PubMed

Rizzi, Luis Ignacio; Maza, Cristóbal De La; Cifuentes, Luis Abdón; Gómez, Jorge

2014-12-15

Direct valuation of air quality has as a drawback; that estimated willingness to pay figures cannot be apportioned to the several environmental goods affected by air quality, such as mortality and morbidity effects, visibility, outdoor recreation, among others. To address this issue, we implemented a survey in Santiago de Chile to identify component values of confounded environmental services by means of a choice experiment. We designed a survey where two environmental goods, a morbidity health endpoint and improved visibility, had to be jointly traded off against each other and against money in a unified framework. The health endpoint is a respiratory illness that results in an emergency room visit with a probability of hospitalization being required for appropriate treatment. Visibility is described as an aesthetic effect related to the number of days per year of high visibility. Modeling comprises both a logit model with covariates and a mixed-logit model. The results suggest that the health endpoint midpoint value is in a range from USD 2,800 to USD 13,000, mainly depending on the model and age stratum. The mid point value of an extra day of high visibility per year ranges from USD 281,000 to USD 379,000. Copyright © 2014 Elsevier Ltd. All rights reserved.

Why Did People Move During the Great Recession?: The Role of Economics in Migration Decisions.

PubMed

Levy, Brian L; Mouw, Ted; Daniel Perez, Anthony

2017-04-01

Labor migration offers an important mechanism to reallocate workers when there are regional differences in employment conditions. Whereas conventional wisdom suggests migration rates should increase during recessions as workers move out of areas that are hit hardest, initial evidence suggested that overall migration rates declined during the Great Recession, despite large regional differences in unemployment and growth rates. In this paper, we use data from the American Community Survey to analyze internal migration trends before and during the economic downturn. First, we find only a modest decline in the odds of adults leaving distressed labor market areas during the recession, which may result in part from challenges related to the housing price crash. Second, we estimate conditional logit models of destination choice for individuals who migrate across labor market areas and find a substantial effect of economic factors such as labor demand, unemployment, and housing values. We also estimate latent class conditional logit models that test whether there is heterogeneity in preferences for destination characteristics among migrants. Over all, the latent class models suggest that roughly equal percentages of migrants were motivated by economic factors before and during the recession. We conclude that fears of dramatic declines in labor migration seem to be unsubstantiated.

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

PubMed

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.

Airline Choice for Domestic Flights in Sao Paulo Metropolitan Area: An Application of the Conditional Logit Model

NASA Technical Reports Server (NTRS)

Moreno, Marcelo Baena

2006-01-01

Using the conditional (multinomial) LOGIT model, this paper addresses airline choice in the S o Paulo Metropolitan Area. There are two airports in this region, where two, three or even four airlines compete for passengers flying to an array of domestic destinations. The airline choice is believed to be a result of the tradeoff passengers face among flight cost, flight frequency and airline performance. It was found that the lowest fare better explains airline choice than the highest fare, whereas direct flight frequencies give better explanation to airline choice than indirect (connections and stops) and total (direct plus indirect) ones. Out of 15 variables tested, the lowest fare was the variable that best explained airline choice. However, its signal was counterintuitive (positive) possibly because the cheapest airline was offering few flights, so passengers overwhelmingly failed to choose the cheapest airline. The model specification most adjusted to the data considered the lowest fare, direct flight frequency in the travel day and period (morning or afternoon peak) and airline age. Passengers departing from S o Paulo-Guarulhos International Airport (GRU) airport make their airline choice in terms of cost whereas those from Sao Paulo-Congonhas Airport (CGH) airport do not. Finally, senior passengers place more importance on airline age than junior passengers.

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

PubMed

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.

Adoption of health information technologies by physicians for clinical practice: The Andalusian case.

PubMed

Villalba-Mora, Elena; Casas, Isabel; Lupiañez-Villanueva, Francisco; Maghiros, Ioannis

2015-07-01

We investigated the level of adoption of Health Information Technologies (HIT) services, and the factors that influence this, amongst specialised and primary care physicians; in Andalusia, Spain. We analysed the physicians' responses to an online survey. First, we performed a statistical descriptive analysis of the data; thereafter, a principal component analysis; and finally an order logit model to explain the effect of the use in the adoption and to analyse which are the existing barriers. The principal component analysis revealed three main uses of Health Information Technologies: Electronic Health Records (EHR), ePrescription and patient management and telemedicine services. Results from an ordered logit model showed that the frequency of use of HIT is associated with the physicians' perceived usefulness. Lack of financing appeared as a common barrier to the adoption of the three types of services. For ePrescription and patient management, the physician's lack of skills is still a barrier. In the case of telemedicine services, lack of security and lack of interest amongst professionals are the existing barriers. EHR functionalities are fully adopted, in terms of perceived usefulness. EPrescription and patient management are almost fully adopted, while telemedicine is in an early stage of adoption. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Impact of socioeconomic status and medical conditions on health and healthcare utilization among aging Ghanaians.

PubMed

Saeed, Bashiru Ii; Xicang, Zhao; Yawson, Alfred Edwin; Nguah, Samuel Blay; Nsowah-Nuamah, Nicholas N N

2015-03-20

This study attempts to examine the impact of socioeconomic and medical conditions in health and healthcare utilization among older adults in Ghana. Five separate models with varying input variables were estimated for each response variable. Data (Wave 1 data) were drawn from the World Health Organization Global Ageing and Adult Health (SAGE) conducted during 2007-2008 and included a total of 4770 respondents aged 50+ and 803 aged 18-49 in Ghana. Ordered logits was estimated for self-rated health, and binary logits for functional limitation and healthcare utilization. Our results show that the study provides enough grounds for further research on the interplay between socioeconomic and medical conditions on one hand and the health of the aged on the other. Controlling for socioeconomic status substantially contributes significantly to utilization. Also, aged women experience worse health than men, as shown by functioning assessment, self-rated health, chronic conditions and functional limitations. Women have higher rates of healthcare utilization, as shown by significantly higher rates of hospitalization and outpatient encounters. Expansion of the national health insurance scheme to cover the entire older population--for those in both formal and informal employments--is likely to garner increased access and improved health states for the older population.

Performance of Random Effects Model Estimators under Complex Sampling Designs

ERIC Educational Resources Information Center

Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan

2011-01-01

In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…

An uncertainty model of acoustic metamaterials with random parameters

NASA Astrophysics Data System (ADS)

He, Z. C.; Hu, J. Y.; Li, Eric

2018-01-01

Acoustic metamaterials (AMs) are man-made composite materials. However, the random uncertainties are unavoidable in the application of AMs due to manufacturing and material errors which lead to the variance of the physical responses of AMs. In this paper, an uncertainty model based on the change of variable perturbation stochastic finite element method (CVPS-FEM) is formulated to predict the probability density functions of physical responses of AMs with random parameters. Three types of physical responses including the band structure, mode shapes and frequency response function of AMs are studied in the uncertainty model, which is of great interest in the design of AMs. In this computation, the physical responses of stochastic AMs are expressed as linear functions of the pre-defined random parameters by using the first-order Taylor series expansion and perturbation technique. Then, based on the linear function relationships of parameters and responses, the probability density functions of the responses can be calculated by the change-of-variable technique. Three numerical examples are employed to demonstrate the effectiveness of the CVPS-FEM for stochastic AMs, and the results are validated by Monte Carlo method successfully.

Macroscopically constrained Wang-Landau method for systems with multiple order parameters and its application to drawing complex phase diagrams

NASA Astrophysics Data System (ADS)

Chan, C. H.; Brown, G.; Rikvold, P. A.

2017-05-01

A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional random-walk process in phase space into many separate, one-dimensional random-walk processes in well-defined subspaces. Each of these random walks is constrained to a different set of values of the macroscopic order parameters. When the multivariable density of states is obtained for one set of values of fieldlike model parameters, the density of states for any other values of these parameters can be obtained by a simple transformation of the total system energy. All thermodynamic quantities of the system can then be rapidly calculated at any point in the phase diagram. We demonstrate how to use the multivariable density of states to draw the phase diagram, as well as order-parameter probability distributions at specific phase points, for a model spin-crossover material: an antiferromagnetic Ising model with ferromagnetic long-range interactions. The fieldlike parameters in this model are an effective magnetic field and the strength of the long-range interaction.

Bayesian statistics and Monte Carlo methods

NASA Astrophysics Data System (ADS)

Koch, K. R.

2018-03-01

The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

Smoothing the redshift distributions of random samples for the baryon acoustic oscillations: applications to the SDSS-III BOSS DR12 and QPM mock samples

NASA Astrophysics Data System (ADS)

Wang, Shao-Jiang; Guo, Qi; Cai, Rong-Gen

2017-12-01

We investigate the impact of different redshift distributions of random samples on the baryon acoustic oscillations (BAO) measurements of D_V(z)r_d^fid/r_d from the two-point correlation functions of galaxies in the Data Release 12 of the Baryon Oscillation Spectroscopic Survey (BOSS). Big surveys, such as BOSS, usually assign redshifts to the random samples by randomly drawing values from the measured redshift distributions of the data, which would necessarily introduce fiducial signals of fluctuations into the random samples, weakening the signals of BAO, if the cosmic variance cannot be ignored. We propose a smooth function of redshift distribution that fits the data well to populate the random galaxy samples. The resulting cosmological parameters match the input parameters of the mock catalogue very well. The significance of BAO signals has been improved by 0.33σ for a low-redshift sample and by 0.03σ for a constant-stellar-mass sample, though the absolute values do not change significantly. Given the precision of the measurements of current cosmological parameters, it would be appreciated for the future improvements on the measurements of galaxy clustering.

The glassy random laser: replica symmetry breaking in the intensity fluctuations of emission spectra

PubMed Central

Antenucci, Fabrizio; Crisanti, Andrea; Leuzzi, Luca

2015-01-01

The behavior of a newly introduced overlap parameter, measuring the correlation between intensity fluctuations of waves in random media, is analyzed in different physical regimes, with varying amount of disorder and non-linearity. This order parameter allows to identify the laser transition in random media and describes its possible glassy nature in terms of emission spectra data, the only data so far accessible in random laser measurements. The theoretical analysis is performed in terms of the complex spherical spin-glass model, a statistical mechanical model describing the onset and the behavior of random lasers in open cavities. Replica Symmetry Breaking theory allows to discern different kinds of randomness in the high pumping regime, including the most complex and intriguing glassy randomness. The outcome of the theoretical study is, eventually, compared to recent intensity fluctuation overlap measurements demonstrating the validity of the theory and providing a straightforward interpretation of qualitatively different spectral behaviors in different random lasers. PMID:26616194

Exploring activity-driven network with biased walks

NASA Astrophysics Data System (ADS)

Wang, Yan; Wu, Ding Juan; Lv, Fang; Su, Meng Long

We investigate the concurrent dynamics of biased random walks and the activity-driven network, where the preferential transition probability is in terms of the edge-weighting parameter. We also obtain the analytical expressions for stationary distribution and the coverage function in directed and undirected networks, all of which depend on the weight parameter. Appropriately adjusting this parameter, more effective search strategy can be obtained when compared with the unbiased random walk, whether in directed or undirected networks. Since network weights play a significant role in the diffusion process.

Survival and recovery rates of American woodcock banded in Michigan

USGS Publications Warehouse

Krementz, David G.; Hines, James E.; Luukkonen, David R.

2003-01-01

American woodcock (Scolopax minor) population indices have declined since U.S. Fish and Wildlife Service (USFWS) monitoring began in 1968. Management to stop and/or reverse this population trend has been hampered by the lack of recent information on woodcock population parameters. Without recent information on survival rate trends, managers have had to assume that the recent declines in recruitment indices are the only parameter driving woodcock declines. Using program MARK, we estimated annual survival and recovery rates of adult and juvenile American woodcock, and estimated summer survival of local (young incapable of sustained flight) woodcock banded in Michigan between 1978 and 1998. We constructed a set of candidate models from a global model with age (local, juvenile, adult) and time (year)-dependent survival and recovery rates to no age or time-dependent survival and recovery rates. Five models were supported by the data, with all models suggesting that survival rates differed among age classes, and 4 models had survival rates that were constant over time. The fifth model suggested that juvenile and adult survival rates were linear on a logit scale over time. Survival rates averaged over likelihood-weighted model results were 0.8784 +/- 0.1048 (SE) for locals, 0.2646 +/- 0.0423 (SE) for juveniles, and 0.4898 +/- 0.0329 (SE) for adults. Weighted average recovery rates were 0.0326 +/- 0.0053 (SE) for juveniles and 0.0313 +/- 0.0047 (SE) for adults. Estimated differences between our survival estimates and those from prior years were small, and our confidence around those differences was variable and uncertain. juvenile survival rates were low.

Recursive Branching Simulated Annealing Algorithm

NASA Technical Reports Server (NTRS)

Bolcar, Matthew; Smith, J. Scott; Aronstein, David

2012-01-01

This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal solution, and the region from which new configurations can be selected shrinks as the search continues. The key difference between these algorithms is that in the SA algorithm, a single path, or trajectory, is taken in parameter space, from the starting point to the globally optimal solution, while in the RBSA algorithm, many trajectories are taken; by exploring multiple regions of the parameter space simultaneously, the algorithm has been shown to converge on the globally optimal solution about an order of magnitude faster than when using conventional algorithms. Novel features of the RBSA algorithm include: 1. More efficient searching of the parameter space due to the branching structure, in which multiple random configurations are generated and multiple promising regions of the parameter space are explored; 2. The implementation of a trust region for each parameter in the parameter space, which provides a natural way of enforcing upper- and lower-bound constraints on the parameters; and 3. The optional use of a constrained gradient- search optimization, performed on the continuous variables around each branch s configuration in parameter space to improve search efficiency by allowing for fast fine-tuning of the continuous variables within the trust region at that configuration point.

Substituting whole grains for refined grains in a 6-week randomized trial favorably affects energy balance parameters in healthy men and post-menopausal women

USDA-ARS?s Scientific Manuscript database

Background: The effect of whole grains on the regulation of energy balance remains controversial. Objective: To determine the effects of substituting whole grains for refined grains, independent of body weight change, on energy metabolism parameters and glycemic control. Design: A randomized, con...

Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks

PubMed Central

Hosseini, S. M. Hadi; Kesler, Shelli R.

2013-01-01

In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures. PMID:23840672

New Estimates of Design Parameters for Clustered Randomization Studies: Findings from North Carolina and Florida. Working Paper 43

ERIC Educational Resources Information Center

Xu, Zeyu; Nichols, Austin

2010-01-01

The gold standard in making causal inference on program effects is a randomized trial. Most randomization designs in education randomize classrooms or schools rather than individual students. Such "clustered randomization" designs have one principal drawback: They tend to have limited statistical power or precision. This study aims to…

Ready-to-use supplementary food increases fat mass and BMI in Haitian school-aged children.

PubMed

Iannotti, Lora L; Henretty, Nicole M; Delnatus, Jacques Raymond; Previl, Windy; Stehl, Tom; Vorkoper, Susan; Bodden, Jaime; Maust, Amanda; Smidt, Rachel; Nash, Marilyn L; Tamimie, Courtney A; Owen, Bridget C; Wolff, Patricia B

2015-04-01

In Haiti and other countries, large-scale investments in school feeding programs have been made with marginal evidence of nutrition outcomes. We aimed to examine the effectiveness of a fortified ready-to-use supplementary food (RUSF), Mamba, on reduced anemia and improved body composition in school-aged children compared to an unfortified cereal bar, Tablet Yo, and control groups. A cluster, randomized trial with children ages 3-13 y (n = 1167) was conducted in the north of Haiti. Six schools were matched and randomized to the control group, Tablet Yo group (42 g, 165 kcal), or Mamba group (50 g, 260 kcal, and >75% of the RDA for critical micronutrients). Children in the supplementation groups received the snack daily for 100 d, and all were followed longitudinally for hemoglobin concentrations, anthropometry, and bioelectrical impedance measures: baseline (December 2012), midline (March 2013), and endline (June 2013). Parent surveys were conducted at baseline and endline to examine secondary outcomes of morbidities and dietary intakes. Longitudinal regression modeling using generalized least squares and logit with random effects tested the main effects. At baseline,14.0% of children were stunted, 14.5% underweight, 9.1% thin, and 73% anemic. Fat mass percentage (mean ± SD) was 8.1% ± 4.3% for boys and 12.5% ± 4.4% for girls. In longitudinal modeling, Mamba supplementation increased body mass index z score (regression coefficient ± SEE) 0.25 ± 0.06, fat mass 0.45 ± 0.14 kg, and percentage fat mass 1.28% ± 0.27% compared with control at each time point (P < 0.001). Among boys, Mamba increased fat mass (regression coefficient ± SEE) 0.73 ± 0.19 kg and fat-free mass 0.62 ± 0.34 kg compared with control (P < 0.001). Mamba reduced the odds of developing anemia by 28% compared to control (adjusted OR: 0.72; 95% CI: 0.57, 0.91; P < 0.001). No treatment effect was found for hemoglobin concentration. To our knowledge, this is the first study to give evidence of body composition effects from an RUSF in school-aged children. © 2015 American Society for Nutrition.

Evaluation of random errors in Williams’ series coefficients obtained with digital image correlation

NASA Astrophysics Data System (ADS)

Lychak, Oleh V.; Holyns'kiy, Ivan S.

2016-03-01

The use of the Williams’ series parameters for fracture analysis requires valid information about their error values. The aim of this investigation is the development of the method for estimation of the standard deviation of random errors of the Williams’ series parameters, obtained from the measured components of the stress field. Also, the criteria for choosing the optimal number of terms in the truncated Williams’ series for derivation of their parameters with minimal errors is proposed. The method was used for the evaluation of the Williams’ parameters, obtained from the data, and measured by the digital image correlation technique for testing a three-point bending specimen.

Stochastic reduced order models for inverse problems under uncertainty

PubMed Central

Warner, James E.; Aquino, Wilkins; Grigoriu, Mircea D.

2014-01-01

This work presents a novel methodology for solving inverse problems under uncertainty using stochastic reduced order models (SROMs). Given statistical information about an observed state variable in a system, unknown parameters are estimated probabilistically through the solution of a model-constrained, stochastic optimization problem. The point of departure and crux of the proposed framework is the representation of a random quantity using a SROM - a low dimensional, discrete approximation to a continuous random element that permits e cient and non-intrusive stochastic computations. Characterizing the uncertainties with SROMs transforms the stochastic optimization problem into a deterministic one. The non-intrusive nature of SROMs facilitates e cient gradient computations for random vector unknowns and relies entirely on calls to existing deterministic solvers. Furthermore, the method is naturally extended to handle multiple sources of uncertainty in cases where state variable data, system parameters, and boundary conditions are all considered random. The new and widely-applicable SROM framework is formulated for a general stochastic optimization problem in terms of an abstract objective function and constraining model. For demonstration purposes, however, we study its performance in the specific case of inverse identification of random material parameters in elastodynamics. We demonstrate the ability to efficiently recover random shear moduli given material displacement statistics as input data. We also show that the approach remains effective for the case where the loading in the problem is random as well. PMID:25558115

Preference heterogeneity in a count data model of demand for off-highway vehicle recreation

Treesearch

Thomas P Holmes; Jeffrey E Englin

2010-01-01

This paper examines heterogeneity in the preferences for OHV recreation by applying the random parameters Poisson model to a data set of off-highway vehicle (OHV) users at four National Forest sites in North Carolina. The analysis develops estimates of individual consumer surplus and finds that estimates are systematically affected by the random parameter specification...

Statistical characteristics of trajectories of diamagnetic unicellular organisms in a magnetic field.

PubMed

Gorobets, Yu I; Gorobets, O Yu

2015-01-01

The statistical model is proposed in this paper for description of orientation of trajectories of unicellular diamagnetic organisms in a magnetic field. The statistical parameter such as the effective energy is calculated on basis of this model. The resulting effective energy is the statistical characteristics of trajectories of diamagnetic microorganisms in a magnetic field connected with their metabolism. The statistical model is applicable for the case when the energy of the thermal motion of bacteria is negligible in comparison with their energy in a magnetic field and the bacteria manifest the significant "active random movement", i.e. there is the randomizing motion of the bacteria of non thermal nature, for example, movement of bacteria by means of flagellum. The energy of the randomizing active self-motion of bacteria is characterized by the new statistical parameter for biological objects. The parameter replaces the energy of the randomizing thermal motion in calculation of the statistical distribution. Copyright © 2014 Elsevier Ltd. All rights reserved.

Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable

ERIC Educational Resources Information Center

du Toit, Stephen H. C.; Cudeck, Robert

2009-01-01

A method is presented for marginal maximum likelihood estimation of the nonlinear random coefficient model when the response function has some linear parameters. This is done by writing the marginal distribution of the repeated measures as a conditional distribution of the response given the nonlinear random effects. The resulting distribution…

Assessing coastal plain wetland composition using advanced spaceborne thermal emission and reflection radiometer imagery

NASA Astrophysics Data System (ADS)

Pantaleoni, Eva

Establishing wetland gains and losses, delineating wetland boundaries, and determining their vegetative composition are major challenges that can be improved through remote sensing studies. We used the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to separate wetlands from uplands in a study of 870 locations on the Virginia Coastal Plain. We used the first five bands from each of two ASTER scenes (6 March 2005 and 16 October 2005), covering the visible to the short-wave infrared region (0.52-2.185mum). We included GIS data layers for soil survey, topography, and presence or absence of water in a logistic regression model that predicted the location of over 78% of the wetlands. While this was slightly less accurate (78% vs. 86%) than current National Wetland Inventory (NWI) aerial photo interpretation procedures of locating wetlands, satellite imagery analysis holds great promise for speeding wetland mapping, lowering costs, and improving update frequency. To estimate wetland vegetation composition classes, we generated a classification and regression tree (CART) model and a multinomial logistic regression (logit) model, and compared their accuracy in separating woody wetlands, emergent wetlands and open water. The overall accuracy of the CART model was 73.3%, while for the logit model was 76.7%. The CART producer's accuracy of the emergent wetlands was higher than the accuracy from the multinomial logit (57.1% vs. 40.7%). However, we obtained the opposite result for the woody wetland category (68.7% vs. 52.6%). A McNemar test between the two models and NWI maps showed that their accuracies were not statistically different. We conducted a subpixel analysis of the ASTER images to estimate canopy cover of forested wetlands. We used top-of-atmosphere reflectance from the visible and near infrared bands, Delta Normalized Difference Vegetation Index, and a tasseled cap brightness, greenness, and wetness in linear regression model with canopy cover as the dependent variable. The model achieved an adjusted-R 2 of 0.69 (RMSE = 2.7%) for canopy cover less than 16%, and an adjusted-R 2 of 0.04 (RMSE = 19.8%) for higher canopy cover values. Taken together, these findings suggest that satellite remote sensing, in concert with other spatial data, has strong potential for mapping both wetland presence and type.

Annual survival and population estimates of Mountain Plovers in Southern Phillips County, Montana

USGS Publications Warehouse

Dinsmore, S.J.; White, Gary C.; Knopf, F.L.

2003-01-01

Information about the demography of declining species is especially relevant to their conservation and future recovery. Knowledge of survival rates and population size can be used to assess long-term viability and population trends, both of which are of interest to conservation biologists. We used capture–recapture techniques to study the demography of Mountain Plovers (Charadrius montanus Townsend) in southern Phillips County, Montana, USA, in 1995–2000. We used the robust design to estimate annual survival (φ), conditional capture (p and r) and recapture (c) probabilities, and the annual population size (N) in the presence of temporary emigration. The results support age-specific differences in annual survival that are a function of juvenile body mass and are correlated with the area occupied by prairie dogs. Body mass had a positive effect on juvenile survival; the slope coefficient for the additive effect of body mass on juvenile survival was 0.77 (95% ci = 0.25, 1.28) on a logit scale. A measure of plover habitat (the area occupied by prairie dogs) appeared to have no effect on survival; the slope coefficient for the additive effect of area occupied by prairie dogs on survival was –0.00004 (95% ci = –0.00003, –0.0001) on a logit scale. Estimated annual apparent survival rates were 0.46–0.49 for juveniles and 0.68 for adult plovers. Using these estimates, the life span of a Mountain Plover was 1.92 ± 0.17 years (mean ± 1 se) from time of capture as a chick. Resighting rates positively influenced capture probabilities; the slope coefficient for the additive resighting effect was –0.49 (95% ci = –0.86, –0.11) on a logit scale. The size of this adult Mountain Plover population was estimated at 95–180 adults annually. Population size closely tracked annual changes in the area occupied by black-tailed prairie dogs, with both plovers and prairie dogs rapidly recovering from an outbreak of sylvatic plague in the mid-1990s. Given the low annual survival rates and low mean life expectancy of Mountain Plovers, we conclude that sustainable local populations are currently maintained by annual rates of productivity greater than those for other ground-nesting birds.

U.S. consumer demand for restaurant calorie information: targeting demographic and behavioral segments in labeling initiatives.

PubMed

Kolodinsky, Jane; Reynolds, Travis William; Cannella, Mark; Timmons, David; Bromberg, Daniel

2009-01-01

To identify different segments of U.S. consumers based on food choices, exercise patterns, and desire for restaurant calorie labeling. Using a stratified (by region) random sample of the U.S. population, trained interviewers collected data for this cross-sectional study through telephone surveys. Center for Rural Studies U.S. national health survey. The final sample included 580 responses (22% response rate); data were weighted to be representative of age and gender characteristics of the U.S. population. Self-reported behaviors related to food choices, exercise patterns, desire for calorie information in restaurants, and sample demographics. Clusters were identified using Schwartz Bayesian criteria. Impacts of demographic characteristics on cluster membership were analyzed using bivariate tests of association and multinomial logit regression. Cluster analysis revealed three clusters based on respondents' food choices, activity levels, and desire for restaurant labeling. Two clusters, comprising three quarters of the sample, desired calorie labeling in restaurants. The remaining cluster opposed restaurant labeling. Demographic variables significantly predicting cluster membership included region of residence (p < .10), income (p < .05), gender (p < .01), and age (p < .10). Though limited by a low response and potential self-reporting bias in the phone survey, this study suggests that several groups are likely to benefit from restaurant calorie labeling. Specific demographic clusters could be targeted through labeling initiatives.

Built Environment and Active Commuting: Rural-Urban Differences in the U.S.

PubMed

Fan, Jessie X; Wen, Ming; Wan, Neng

2017-12-01

The purpose of this research was to investigate rural-urban differences in participation rates in three modes of active commuting (AC) and their built environmental correlates. The 2010 Census supplemented with other datasets were used to analyze AC rates in percent of workers age 16+ walking, biking, or taking public transportation to work in 70,172 Census tracts, including 12,844 rural and 57,328 urban. Random-intercept factional logit regressions were used to account for zero-inflated data and for clustering of tracts within counties. We found that the average AC rates were 3.44% rural and 2.77% urban (p<0.01) for walking to work, 0.40% rural and 0.58% urban (p<0.01) for biking to work, and 0.59% rural and 5.86% urban (p<0.01) for public transportation to work. Some environmental variables had similar relationships with AC in rural and urban tracts, such as a negative association between tract greenness and prevalence of walking to work. Others had opposite correlational directions for rural vs. urban, such as street connectivity for walking to work and population density for both walking to work and public transportation to work. We concluded that rurality is an important moderator in AC-environment relationships. In developing strategies to promote AC, attention needs to be paid to rural-urban differences to avoid unintended consequences.

Neighborhood-Level Social Processes and Substantiated Cases of Child Maltreatment

PubMed Central

Molnar, Beth E.; Goerge, Robert M.; Gilsanz, Paola; Hill, Andrea; Subramanian, SV; Holton, John K.; Duncan, Dustin T.; Beatriz, Elizabeth D.; Beardslee, William R.

2015-01-01

Child maltreatment is a preventable public health problem. Research has demonstrated that neighborhood structural factors (e.g. poverty, crime) can influence the proportion of a neighborhood’s children who are victims of maltreatment. A newer strategy is the identification of potentially modifiable social processes at the neighborhood level that can also influence maltreatment. Toward this end, this study examines neighborhood-level data (maltreatment cases substantiated by Illinois’ child protection agency, 1995–2005, social processes measured by the Project on Human Development in Chicago Neighborhoods, U.S. Census data, proportions of neighborhoods on public assistance, and crime data) that were linked across clusters of contiguous, relatively homogenous Chicago, IL census tracts with respect to racial/ethnic and socioeconomic composition. Our analysis—an ecological-level, repeated cross-sectional design utilizing random-intercept logit models— with a sensitivity analysis using spatial models to control for spatial autocorrelation – revealed consistent associations between neighborhood social processes and maltreatment. Neighborhoods higher in collective efficacy, intergenerational closure, and social networks, and lower in disorder had lower proportions of neglect, physical abuse, and sexual abuse substantiated cases, controlling for differences in structural factors. Higher collective efficacy and social network size also predicted a lower proportion of substance-exposed infants. This research indicates that strategies to mobilize neighborhood-level protective factors may decrease child maltreatment more effectively than individual and family-focused efforts alone. PMID:26684963

Neighborhood-level social processes and substantiated cases of child maltreatment.

PubMed

Molnar, Beth E; Goerge, Robert M; Gilsanz, Paola; Hill, Andrea; Subramanian, S V; Holton, John K; Duncan, Dustin T; Beatriz, Elizabeth D; Beardslee, William R

2016-01-01

Child maltreatment is a preventable public health problem. Research has demonstrated that neighborhood structural factors (e.g. poverty, crime) can influence the proportion of a neighborhood's children who are victims of maltreatment. A newer strategy is the identification of potentially modifiable social processes at the neighborhood level that can also influence maltreatment. Toward this end, this study examines neighborhood-level data (maltreatment cases substantiated by Illinois' child protection agency, 1995-2005, social processes measured by the Project on Human Development in Chicago Neighborhoods, U.S. Census data, proportions of neighborhoods on public assistance, and crime data) that were linked across clusters of contiguous, relatively homogenous Chicago, IL census tracts with respect to racial/ethnic and socioeconomic composition. Our analysis-an ecological-level, repeated cross-sectional design utilizing random-intercept logit models-with a sensitivity analysis using spatial models to control for spatial autocorrelation-revealed consistent associations between neighborhood social processes and maltreatment. Neighborhoods higher in collective efficacy, intergenerational closure, and social networks, and lower in disorder had lower proportions of neglect, physical abuse, and sexual abuse substantiated cases, controlling for differences in structural factors. Higher collective efficacy and social network size also predicted a lower proportion of substance-exposed infants. This research indicates that strategies to mobilize neighborhood-level protective factors may decrease child maltreatment more effectively than individual and family-focused efforts alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

Physics and financial economics (1776-2014): puzzles, Ising and agent-based models.

PubMed

Sornette, Didier

2014-06-01

This short review presents a selected history of the mutual fertilization between physics and economics--from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the 'Emerging Intelligence Market Hypothesis' to reconcile the pervasive presence of 'noise traders' with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

Insurees' preferences in hospital choice-A population-based study.

PubMed

Schuldt, Johannes; Doktor, Anna; Lichters, Marcel; Vogt, Bodo; Robra, Bernt-Peter

2017-10-01

In Germany, the patient himself makes the choice for or against a health service provider. Hospital comparison websites offer him possibilities to inform himself before choosing. However, it remains unclear, how health care consumers use those websites, and there is little information about how preferences in hospital choice differ interpersonally. We conducted a Discrete-Choice-Experiment (DCE) on hospital choice with 1500 randomly selected participants (age 40-70) in three different German cities selecting four attributes for hospital vignettes. The analysis of the study draws on multilevel mixed effects logit regression analyses with the dependent variables: "chance to select a hospital" and "choice confidence". Subsequently, we performed a Latent-Class-Analysis to uncover consumer segments with distinct preferences. 590 of the questionnaires were evaluable. All four attributes of the hospital vignettes have a significant impact on hospital choice. The attribute "complication rate" exerts the highest impact on consumers' decisions and reported choice confidence. Latent-Class-Analysis results in one dominant consumer segment that considered the complication rate the most important decision criterion. Using DCE, we were able to show that the complication rate is an important trusted criterion in hospital choice to a large group of consumers. Our study supports current governmental efforts in Germany to concentrate the provision of specialized health care services. We suggest further national and cross-national research on the topic. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A generalized mixed effects model of abundance for mark-resight data when sampling is without replacement

USGS Publications Warehouse

McClintock, B.T.; White, Gary C.; Burnham, K.P.; Pryde, M.A.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

In recent years, the mark-resight method for estimating abundance when the number of marked individuals is known has become increasingly popular. By using field-readable bands that may be resighted from a distance, these techniques can be applied to many species, and are particularly useful for relatively small, closed populations. However, due to the different assumptions and general rigidity of the available estimators, researchers must often commit to a particular model without rigorous quantitative justification for model selection based on the data. Here we introduce a nonlinear logit-normal mixed effects model addressing this need for a more generalized framework. Similar to models available for mark-recapture studies, the estimator allows a wide variety of sampling conditions to be parameterized efficiently under a robust sampling design. Resighting rates may be modeled simply or with more complexity by including fixed temporal and random individual heterogeneity effects. Using information theory, the model(s) best supported by the data may be selected from the candidate models proposed. Under this generalized framework, we hope the uncertainty associated with mark-resight model selection will be reduced substantially. We compare our model to other mark-resight abundance estimators when applied to mainland New Zealand robin (Petroica australis) data recently collected in Eglinton Valley, Fiordland National Park and summarize its performance in simulation experiments.

Employment Condition, Economic Deprivation and Self-Evaluated Health in Europe: Evidence from EU-SILC 2009-2012.

PubMed

Bacci, Silvia; Pigini, Claudia; Seracini, Marco; Minelli, Liliana

2017-02-03

Background : The mixed empirical evidence about employment conditions (i.e., permanent vs. temporary job, full-time vs. part-time job) as well as unemployment has motivated the development of conceptual models with the aim of assessing the pathways leading to effects of employment status on health. Alongside physically and psychologically riskier working conditions, one channel stems in the possibly severe economic deprivation faced by temporary workers. We investigate whether economic deprivation is able to partly capture the effect of employment status on Self-evaluated Health Status (SHS). Methods : Our analysis is based on the European Union Statistics on Income and Living Conditions (EU-SILC) survey, for a balanced sample from 26 countries from 2009 to 2012. We estimate a correlated random-effects logit model for the SHS that accounts for the ordered nature of the dependent variable and the longitudinal structure of the data. Results and Discussion : Material deprivation and economic strain are able to partly account for the negative effects on SHS from precarious and part-time employment as well as from unemployment that, however, exhibits a significant independent negative association with SHS. Conclusions : Some of the indicators used to proxy economic deprivation are significant predictors of SHS and their correlation with the employment condition is such that it should not be neglected in empirical analysis, when available and further to the monetary income.

Employment Condition, Economic Deprivation and Self-Evaluated Health in Europe: Evidence from EU-SILC 2009–2012

PubMed Central

Bacci, Silvia; Pigini, Claudia; Seracini, Marco; Minelli, Liliana

2017-01-01

Background: The mixed empirical evidence about employment conditions (i.e., permanent vs. temporary job, full-time vs. part-time job) as well as unemployment has motivated the development of conceptual models with the aim of assessing the pathways leading to effects of employment status on health. Alongside physically and psychologically riskier working conditions, one channel stems in the possibly severe economic deprivation faced by temporary workers. We investigate whether economic deprivation is able to partly capture the effect of employment status on Self-evaluated Health Status (SHS). Methods: Our analysis is based on the European Union Statistics on Income and Living Conditions (EU-SILC) survey, for a balanced sample from 26 countries from 2009 to 2012. We estimate a correlated random-effects logit model for the SHS that accounts for the ordered nature of the dependent variable and the longitudinal structure of the data. Results and Discussion: Material deprivation and economic strain are able to partly account for the negative effects on SHS from precarious and part-time employment as well as from unemployment that, however, exhibits a significant independent negative association with SHS. Conclusions: Some of the indicators used to proxy economic deprivation are significant predictors of SHS and their correlation with the employment condition is such that it should not be neglected in empirical analysis, when available and further to the monetary income. PMID:28165375

Physics and financial economics (1776-2014): puzzles, Ising and agent-based models

NASA Astrophysics Data System (ADS)

Sornette, Didier

2014-06-01

This short review presents a selected history of the mutual fertilization between physics and economics—from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the ‘Emerging Intelligence Market Hypothesis’ to reconcile the pervasive presence of ‘noise traders’ with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

Pay Matters: The Piece Rate and Health in the Developing World.

PubMed

Davis, Mary E

Piece rate pay remains a common form of compensation in developing-world industries. While the piece rate may boost productivity, it has been shown to have unintended consequences for occupational safety and health, including increased accident and injury risk. This paper explores the relationship between worker pay and physical and emotional health, and questions the modern day business case for piece rate pay in the developing world. The relationship between piece rate and self-reported measures of physical and emotional health is estimated using a large survey of garment workers in 109 Vietnamese factories between 2010 and 2014. A random effects logit model controls for factory and year, predicting worker health as a function of pay type, demographics, and factory characteristics. Workers paid by the piece report worse physical and emotional health than workers paid by the hour (OR = 1.38-1.81). Wage incentives provide the most consistently significant evidence of all demographic and factory-level variables, including the factory's own performance on occupational safety and health compliance measures. These results highlight the importance of how workers are paid to understanding the variability in worker health outcomes. More research is needed to better understand the business case supporting the continued use of piece rate pay in the developing world. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

Effects of behavioral patterns and network topology structures on Parrondo’s paradox

PubMed Central

Ye, Ye; Cheong, Kang Hao; Cen, Yu-wan; Xie, Neng-gang

2016-01-01

A multi-agent Parrondo’s model based on complex networks is used in the current study. For Parrondo’s game A, the individual interaction can be categorized into five types of behavioral patterns: the Matthew effect, harmony, cooperation, poor-competition-rich-cooperation and a random mode. The parameter space of Parrondo’s paradox pertaining to each behavioral pattern, and the gradual change of the parameter space from a two-dimensional lattice to a random network and from a random network to a scale-free network was analyzed. The simulation results suggest that the size of the region of the parameter space that elicits Parrondo’s paradox is positively correlated with the heterogeneity of the degree distribution of the network. For two distinct sets of probability parameters, the microcosmic reasons underlying the occurrence of the paradox under the scale-free network are elaborated. Common interaction mechanisms of the asymmetric structure of game B, behavioral patterns and network topology are also revealed. PMID:27845430

Visible and near infrared spectroscopy coupled to random forest to quantify some soil quality parameters

NASA Astrophysics Data System (ADS)

de Santana, Felipe Bachion; de Souza, André Marcelo; Poppi, Ronei Jesus

2018-02-01

This study evaluates the use of visible and near infrared spectroscopy (Vis-NIRS) combined with multivariate regression based on random forest to quantify some quality soil parameters. The parameters analyzed were soil cation exchange capacity (CEC), sum of exchange bases (SB), organic matter (OM), clay and sand present in the soils of several regions of Brazil. Current methods for evaluating these parameters are laborious, timely and require various wet analytical methods that are not adequate for use in precision agriculture, where faster and automatic responses are required. The random forest regression models were statistically better than PLS regression models for CEC, OM, clay and sand, demonstrating resistance to overfitting, attenuating the effect of outlier samples and indicating the most important variables for the model. The methodology demonstrates the potential of the Vis-NIR as an alternative for determination of CEC, SB, OM, sand and clay, making possible to develop a fast and automatic analytical procedure.

Effects of behavioral patterns and network topology structures on Parrondo’s paradox

NASA Astrophysics Data System (ADS)

Ye, Ye; Cheong, Kang Hao; Cen, Yu-Wan; Xie, Neng-Gang

2016-11-01

A multi-agent Parrondo’s model based on complex networks is used in the current study. For Parrondo’s game A, the individual interaction can be categorized into five types of behavioral patterns: the Matthew effect, harmony, cooperation, poor-competition-rich-cooperation and a random mode. The parameter space of Parrondo’s paradox pertaining to each behavioral pattern, and the gradual change of the parameter space from a two-dimensional lattice to a random network and from a random network to a scale-free network was analyzed. The simulation results suggest that the size of the region of the parameter space that elicits Parrondo’s paradox is positively correlated with the heterogeneity of the degree distribution of the network. For two distinct sets of probability parameters, the microcosmic reasons underlying the occurrence of the paradox under the scale-free network are elaborated. Common interaction mechanisms of the asymmetric structure of game B, behavioral patterns and network topology are also revealed.

The Impact of Two Workplace-Based Health Risk Appraisal Interventions on Employee Lifestyle Parameters, Mental Health and Work Ability: Results of a Randomized Controlled Trial

ERIC Educational Resources Information Center

Addley, K.; Boyd, S.; Kerr, R.; McQuillan, P.; Houdmont, J.; McCrory, M.

2014-01-01

Health risk appraisals (HRA) are a common type of workplace health promotion programme offered by American employers. In the United Kingdom, evidence of their effectiveness for promoting health behaviour change remains inconclusive. This randomized controlled trial examined the effects of two HRA interventions on lifestyle parameters, mental…

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

DTIC Science & Technology

1987-12-01

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

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

DTIC Science & Technology

1980-04-01

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

An Analysis of Army Dentists Using Logistic Regression: A Discrete-Time Logit Model for Predicting Retention

DTIC Science & Technology

2009-06-10

Reports (0704 0188), 1215 Jefferson Devis Highway, Suite 1204, Arlington, VA 22202 4302 Respondents should be aware that notwithstanding any other...NAME(S) AND ADDRESS(ES) US Army Medical Department Center and School BLDG 2841 MCCS-HGE-HA (Army-Baylor Program in Health & Business Administration...been used to model negative occurrences in the medical field, such as time to death from a certain disease. However, questions of whether and when

Complementarity in dietary supplements and foods: are supplement users vegetable eaters?

PubMed

Kang, Hyoung-Goo; Joo, Hailey Hayeon; Choi, Kyong Duk; Lee, Dongmin; Moon, Junghoon

2017-01-01

Background : The consumption of fruits, vegetables, and dietary supplements correlate. Most previous studies have aimed to identify the determinants of supplement uses or the distinct features of supplement users; this literature lacks a discussion on dietary supplement consumption as a predictor of fruit and vegetable consumption. Objective : This study examines how dietary supplement consumption correlates with fruit and vegetable consumption by combining scanner data and surveys of Korean household grocery shopping. Methods : Propensity score matching (PSM) is used to identify the relationship between dietary supplement consumption and fruit and vegetable consumption in a household. A logit regression using supplement consumption as the dependent variable is used. Then, the supplement takers (the treatment group) are matched with non-takers (the control group) based on the propensity scores estimated in the logit regression. The fruit and vegetable consumption levels of the groups are then compared. Results : We found that dietary supplement use is associated with higher fruit and vegetable consumption. This supports the health consciousness hypothesis based on attention bias, availability heuristics, the focusing effect, and the consumption episode effect. It rejects the health substitute hypothesis based on economic substitutes and mental accounting. Conclusions : Future research on the health benefits of dietary supplements should address the complementary consumption of fruits/vegetables and their health benefits to avoid misstating the health effects of supplements.

Main Determinants of Catastrophic Health Expenditures: A Bayesian Logit Approach on Iranian Household Survey Data (2010)

PubMed Central

Fazaeli, Ali Akbar; Ghaderi, Hossein; Fazaeli, Amir Abbas; Lotfi, Farhad; Salehi, Masoud; Mehrara, Mohsen

2015-01-01

Background: During recent decades, increase in both health care expenditures and improvement of the awareness as well as health expectations have created some problems with regard to finance healthcare expenditures so that the issue of health financing by households has been determined as a major challenge in health sector. According to the definition by the World Health Organization, catastrophic health expenditure is considered if financial contribution for health service is more than 40% of income remaining after subsistence needs have been met. Objectives: The purpose of our study was determination of Main factors on catastrophic health expenditures in Iranian households. Patients and Methods: In this study, using an econometrics Bayesian logit model, determinants of the appearance of catastrophic health expenditure based on household budget data collected in 2010 were evaluated. Results: Among Iranian households, the following groups were more likely to encounter with unsustainable health expenditures: rural households, households with the numbers of the elderly more than 65 years, illiterate householders, unemployed householders, households with some unemployed persons, households in upper rank and households with larger equivalent household size were higher than the average of community could significantly predict catastrophic health expenditures. Conclusions: About 2.1% of households were faced with catastrophic health expenditures in 2010. Thus, the implemented policies could not make considerable and significant change in improving justice in financing in health systems. PMID:25946936

Main determinants of catastrophic health expenditures: a Bayesian logit approach on Iranian household survey data (2010).

PubMed

Fazaeli, Ali Akbar; Ghaderi, Hossein; Abbas Fazaeli, Amir; Lotfi, Farhad; Salehi, Masoud; Mehrara, Mohsen

2015-01-26

During recent decades, increase in both health care expenditures and improvement of the awareness as well as health expectations have created some problems with regard to finance healthcare expenditures so that the issue of health financing by households has been determined as a major challenge in health sector. According to the definition by the World Health Organization, catastrophic health expenditure is considered if financial contribution for health service is more than 40% of income remaining after subsistence needs have been met. The purpose of our study was determination of Main factors on catastrophic health expenditures in Iranian households. In this study, using an econometrics Bayesian logit model, determinants of the appearance of catastrophic health expenditure based on household budget data collected in 2010 were evaluated. Among Iranian households, the following groups were more likely to encounter with unsustainable health expenditures: rural households, households with the numbers of the elderly more than 65 years, illiterate householders, unemployed householders, households with some unemployed persons, households in upper rank and households with larger equivalent household size were higher than the average of community could significantly predict catastrophic health expenditures. About 2.1% of households were faced with catastrophic health expenditures in 2010. Thus, the implemented policies could not make considerable and significant change in improving justice in financing in health systems.

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

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

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 ofmore » 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.« less

The economic value of stream restoration

NASA Astrophysics Data System (ADS)

Collins, Alan; Rosenberger, Randy; Fletcher, Jerald

2005-02-01

The economic value of restoring Deckers Creek in Monongalia and Preston counties of West Virginia was determined from mail, Internet, and personal contact surveys. Multiattribute, choice experiments were conducted and nested logit models were estimated to derive the economic values of full restoration for three attributes of this creek: aquatic life, swimming, and scenic quality. Their relative economic values were that aquatic life > scenic quality ≈ swimming. These economic values imply that respondents had the highest value for aquatic life when fully restoring Deckers Creek to a sustainable fishery rather than a "put and take" fishery that cannot sustain fish populations. The welfare improvement estimates for full restoration of all three attributes ranged between 12 and 16 per month per household. Potential stream users (anglers) had the largest welfare gain from restoration, while nonangler respondents had the lowest. When these estimates were aggregated up to the entire watershed population, the benefit from restoration of Deckers Creek was estimated to be about $1.9 million annually. This benefit does not account for any economic values from partial stream restoration. On the basis of log likelihood tests of the nested logit models, two subsamples of the survey population (the general population and stream users) were found to be from the same population. Thus restoration choices by stream users may be representative of the watershed population, although the sample size of stream users was small in this research.

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

PubMed

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

2016-05-18

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

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

PubMed

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

2015-11-01

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

Complementarity in dietary supplements and foods: are supplement users vegetable eaters?

PubMed Central

Kang, Hyoung-Goo; Joo, Hailey Hayeon; Choi, Kyong Duk; Lee, Dongmin; Moon, Junghoon

2017-01-01

ABSTRACT Background: The consumption of fruits, vegetables, and dietary supplements correlate. Most previous studies have aimed to identify the determinants of supplement uses or the distinct features of supplement users; this literature lacks a discussion on dietary supplement consumption as a predictor of fruit and vegetable consumption. Objective: This study examines how dietary supplement consumption correlates with fruit and vegetable consumption by combining scanner data and surveys of Korean household grocery shopping. Methods: Propensity score matching (PSM) is used to identify the relationship between dietary supplement consumption and fruit and vegetable consumption in a household. A logit regression using supplement consumption as the dependent variable is used. Then, the supplement takers (the treatment group) are matched with non-takers (the control group) based on the propensity scores estimated in the logit regression. The fruit and vegetable consumption levels of the groups are then compared. Results: We found that dietary supplement use is associated with higher fruit and vegetable consumption. This supports the health consciousness hypothesis based on attention bias, availability heuristics, the focusing effect, and the consumption episode effect. It rejects the health substitute hypothesis based on economic substitutes and mental accounting. Conclusions: Future research on the health benefits of dietary supplements should address the complementary consumption of fruits/vegetables and their health benefits to avoid misstating the health effects of supplements. PMID:28904529

The associations between self-reported sleep duration and adolescent health outcomes: what is the role of time spent on Internet use?

PubMed

Do, Young Kyung; Shin, Eunhae; Bautista, Mary Ann; Foo, Kelvin

2013-02-01

This study aimed to examine the associations of self-reported sleep duration with adolescent health outcomes, taking into account time spent on Internet use. We used data from the 2008-2009 Korea Youth Behavioral Risk Factor Survey, a cross-sectional online survey of middle and high school students aged 13-18years in South Korea (N=136,589) to examine the associations of self-reported sleep duration with four mental and physical health measures, e.g. self-report of depressive symptoms, suicidal ideation, weight status, and self-rated health. The binary logit and generalized ordered logit models controlled for time spent on Internet use for non-study purposes and other factors. Shorter self-reported sleep duration was associated with a higher likelihood of reporting depressive symptoms, suicidal ideation, and overweight or obese status, and a lower likelihood of reporting better self-rated health, even after accounting for time spent on Internet use. Excessive Internet use was found to be an independent risk factor for these outcomes. Among in-school adolescents in South Korea, shorter sleep duration and excessive Internet use are independently and additively associated with multiple indicators of adverse health status. Excessive Internet use may have not only direct adverse health consequences, but also have indirect negative effects through sleep deprivation. Copyright © 2012 Elsevier B.V. All rights reserved.

A new look at the WHOQOL as health-related quality of life instrument among visually impaired people using Rasch analysis.

PubMed

Gothwal, Vijaya K; Srinivas, Marmamula; Rao, Gullapalli N

2013-05-01

To examine the psychometric characteristics of the World Health Organization quality of life instrument-modified Indian version (modified WHOQOL) and its subscales in adults with visual impairment (VI) using Rasch analysis. Cross-sectional data were of people aged ≥40 years with VI (n = 1,333) who responded to the modified WHOQOL in the Andhra Pradesh Eye Disease Study, India. Rasch analysis was used to explore the instrument and its subscales for key indices such as measurement precision by person separation reliability, PSR (i.e., discrimination between strata of participants' health-related QOL [HRQOL], recommended minimum value 0.8), unidimensionality (i.e., measurement of a single construct), and targeting (i.e., matching of item difficulty to participants' HRQOL). Rasch-guided iterative approach including category re-organization to enable threshold ordering and item deletion to overcome multidimensionality resulted in a unidimensional 9-item WHOQOL and a 6-item level of independence (LOI) subscale with adequate PSR (0.81 and 0.82, respectively). Targeting was sub-optimal for both (-1.58 logits for WHOQOL and -2.55 logits for the subscale). Remaining subscales were dysfunctional. The WHOQOL and LOI subscale can be improved and shortened, and the Rasch-revised versions are likely to assess the HROQL of VI patients best because of their brevity, reliability, and unidimensionality.

Measuring order in disordered systems and disorder in ordered systems: Random matrix theory for isotropic and nematic liquid crystals and its perspective on pseudo-nematic domains

NASA Astrophysics Data System (ADS)

Zhao, Yan; Stratt, Richard M.

2018-05-01

Surprisingly long-ranged intermolecular correlations begin to appear in isotropic (orientationally disordered) phases of liquid crystal forming molecules when the temperature or density starts to close in on the boundary with the nematic (ordered) phase. Indeed, the presence of slowly relaxing, strongly orientationally correlated, sets of molecules under putatively disordered conditions ("pseudo-nematic domains") has been apparent for some time from light-scattering and optical-Kerr experiments. Still, a fully microscopic characterization of these domains has been lacking. We illustrate in this paper how pseudo-nematic domains can be studied in even relatively small computer simulations by looking for order-parameter tensor fluctuations much larger than one would expect from random matrix theory. To develop this idea, we show that random matrix theory offers an exact description of how the probability distribution for liquid-crystal order parameter tensors converges to its macroscopic-system limit. We then illustrate how domain properties can be inferred from finite-size-induced deviations from these random matrix predictions. A straightforward generalization of time-independent random matrix theory also allows us to prove that the analogous random matrix predictions for the time dependence of the order-parameter tensor are similarly exact in the macroscopic limit, and that relaxation behavior of the domains can be seen in the breakdown of the finite-size scaling required by that random-matrix theory.

Economical analysis of saturation mutagenesis experiments

PubMed Central

Acevedo-Rocha, Carlos G.; Reetz, Manfred T.; Nov, Yuval

2015-01-01

Saturation mutagenesis is a powerful technique for engineering proteins, metabolic pathways and genomes. In spite of its numerous applications, creating high-quality saturation mutagenesis libraries remains a challenge, as various experimental parameters influence in a complex manner the resulting diversity. We explore from the economical perspective various aspects of saturation mutagenesis library preparation: We introduce a cheaper and faster control for assessing library quality based on liquid media; analyze the role of primer purity and supplier in libraries with and without redundancy; compare library quality, yield, randomization efficiency, and annealing bias using traditional and emergent randomization schemes based on mixtures of mutagenic primers; and establish a methodology for choosing the most cost-effective randomization scheme given the screening costs and other experimental parameters. We show that by carefully considering these parameters, laboratory expenses can be significantly reduced. PMID:26190439

Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

PubMed Central

Liu, Fei; Heiner, Monika; Yang, Ming

2016-01-01

Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information. PMID:26910830

Construction and identification of a D-Vine model applied to the probability distribution of modal parameters in structural dynamics

NASA Astrophysics Data System (ADS)

Dubreuil, S.; Salaün, M.; Rodriguez, E.; Petitjean, F.

2018-01-01

This study investigates the construction and identification of the probability distribution of random modal parameters (natural frequencies and effective parameters) in structural dynamics. As these parameters present various types of dependence structures, the retained approach is based on pair copula construction (PCC). A literature review leads us to choose a D-Vine model for the construction of modal parameters probability distributions. Identification of this model is based on likelihood maximization which makes it sensitive to the dimension of the distribution, namely the number of considered modes in our context. To this respect, a mode selection preprocessing step is proposed. It allows the selection of the relevant random modes for a given transfer function. The second point, addressed in this study, concerns the choice of the D-Vine model. Indeed, D-Vine model is not uniquely defined. Two strategies are proposed and compared. The first one is based on the context of the study whereas the second one is purely based on statistical considerations. Finally, the proposed approaches are numerically studied and compared with respect to their capabilities, first in the identification of the probability distribution of random modal parameters and second in the estimation of the 99 % quantiles of some transfer functions.

Investigation of the contextual interference effect in the manipulation of the motor parameter of over-all force.

PubMed

Goodwin, J E; Meeuwsen, H J

1996-12-01

This investigation examined the contextual interference effect when manipulating over-all force in a golf-putting task. Undergraduate women (N = 30) were randomly assigned to a Random, Blocked-Random, or Blocked practice condition and practiced golf putting from distances of 2.43 m, 3.95 m, and 5.47 m during acquisition. Subjects in the Random condition practiced trials in a quasirandom sequence and those in the Blocked-Random condition practiced trials initially in a blocked sequence with the remainder of the trials practiced in a quasirandom sequence. In the Blocked condition subjects practiced trials in a blocked sequence. A 24-hr. transfer test consisted of 30 trials with 10 trials each from 1.67 m, 3.19 m, and 6.23 m. Transfer scores supported the Magill and Hall (1990) hypothesis that, when task variations involve learning parameters of a generalized motor program, the benefit of random practice over blocked practice would not be found.

Effects of live sax music on various physiological parameters, pain level, and mood level in cancer patients: a randomized controlled trial.

PubMed

Burrai, Francesco; Micheluzzi, Valentina; Bugani, Valentina

2014-01-01

Few randomized controlled trial studies have focused on the effect of music in cancer patients, and there are no randomized controlled trials on the effects of live music with saxophone in cancer patients. To determine the effects of live saxophone music on various physiological parameters, pain level, and mood level. A randomized controlled trial study. 52 cancer patients were randomized to a control group (n = 26), an experimental group (n = 26) whose members received 30 minutes of live music therapy with saxophone. Systolic and diastolic blood pressure, pulse rate, glycemia, oxygen saturation, pain level, and mood level were measured before and after the live music performance. There was a statistical difference between the groups for oxygen saturation (0.003) and mood level (0.001). Live music performed with a saxophone could be introduced in oncology care to improve the oxygen saturation and mood in cancer patients.

Polynomial chaos expansion with random and fuzzy variables

NASA Astrophysics Data System (ADS)

Jacquelin, E.; Friswell, M. I.; Adhikari, S.; Dessombz, O.; Sinou, J.-J.

2016-06-01

A dynamical uncertain system is studied in this paper. Two kinds of uncertainties are addressed, where the uncertain parameters are described through random variables and/or fuzzy variables. A general framework is proposed to deal with both kinds of uncertainty using a polynomial chaos expansion (PCE). It is shown that fuzzy variables may be expanded in terms of polynomial chaos when Legendre polynomials are used. The components of the PCE are a solution of an equation that does not depend on the nature of uncertainty. Once this equation is solved, the post-processing of the data gives the moments of the random response when the uncertainties are random or gives the response interval when the variables are fuzzy. With the PCE approach, it is also possible to deal with mixed uncertainty, when some parameters are random and others are fuzzy. The results provide a fuzzy description of the response statistical moments.

Dynamic defense and network randomization for computer systems

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

Chavez, Adrian R.; Stout, William M. S.; Hamlet, Jason R.

The various technologies presented herein relate to determining a network attack is taking place, and further to adjust one or more network parameters such that the network becomes dynamically configured. A plurality of machine learning algorithms are configured to recognize an active attack pattern. Notification of the attack can be generated, and knowledge gained from the detected attack pattern can be utilized to improve the knowledge of the algorithms to detect a subsequent attack vector(s). Further, network settings and application communications can be dynamically randomized, wherein artificial diversity converts control systems into moving targets that help mitigate the early reconnaissancemore » stages of an attack. An attack(s) based upon a known static address(es) of a critical infrastructure network device(s) can be mitigated by the dynamic randomization. Network parameters that can be randomized include IP addresses, application port numbers, paths data packets navigate through the network, application randomization, etc.« less

Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

NASA Technical Reports Server (NTRS)

Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

2010-01-01

This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine.

PubMed

Howard, Jeremy T; Ashwell, Melissa S; Baynes, Ronald E; Brooks, James D; Yeatts, James L; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs ( n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

PubMed Central

Howard, Jeremy T.; Ashwell, Melissa S.; Baynes, Ronald E.; Brooks, James D.; Yeatts, James L.; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study. PMID:29487615

Model's sparse representation based on reduced mixed GMsFE basis methods

NASA Astrophysics Data System (ADS)

Jiang, Lijian; Li, Qiuqi

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous media is simulated by the proposed sparse representation method.

Model's sparse representation based on reduced mixed GMsFE basis methods

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

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a largemore » number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous media is simulated by the proposed sparse representation method.« less

Oscillations and chaos in neural networks: an exactly solvable model.

PubMed Central

Wang, L P; Pichler, E E; Ross, J

1990-01-01

We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

[Econometric and ethical validation of regression logistics. Reducing of the number of patients in the evaluation of mortality].

PubMed

Castiel, D; Herve, C

1992-01-01

In general, a large number of patients is needed to conclude whether the results of a therapeutic strategy are significant or not. One can lower this number with a logit. The method has been proposed in an article published recently (Cost-utility analysis of early thrombolytic therapy, Pharmaco Economics, 1992). The present article is an essay aimed at validating the method, both from the econometric and ethical points of view.

Superslow relaxation in identical phase oscillators with random and frustrated interactions

NASA Astrophysics Data System (ADS)

Daido, H.

2018-04-01

This paper is concerned with the relaxation dynamics of a large population of identical phase oscillators, each of which interacts with all the others through random couplings whose parameters obey the same Gaussian distribution with the average equal to zero and are mutually independent. The results obtained by numerical simulation suggest that for the infinite-size system, the absolute value of Kuramoto's order parameter exhibits superslow relaxation, i.e., 1/ln t as time t increases. Moreover, the statistics on both the transient time T for the system to reach a fixed point and the absolute value of Kuramoto's order parameter at t = T are also presented together with their distribution densities over many realizations of the coupling parameters.

Estimation of correlation functions by stochastic approximation.

NASA Technical Reports Server (NTRS)

Habibi, A.; Wintz, P. A.

1972-01-01

Consideration of the autocorrelation function of a zero-mean stationary random process. The techniques are applicable to processes with nonzero mean provided the mean is estimated first and subtracted. Two recursive techniques are proposed, both of which are based on the method of stochastic approximation and assume a functional form for the correlation function that depends on a number of parameters that are recursively estimated from successive records. One technique uses a standard point estimator of the correlation function to provide estimates of the parameters that minimize the mean-square error between the point estimates and the parametric function. The other technique provides estimates of the parameters that maximize a likelihood function relating the parameters of the function to the random process. Examples are presented.

Safety assessment of a shallow foundation using the random finite element method

NASA Astrophysics Data System (ADS)

Zaskórski, Łukasz; Puła, Wojciech

2015-04-01

A complex structure of soil and its random character are reasons why soil modeling is a cumbersome task. Heterogeneity of soil has to be considered even within a homogenous layer of soil. Therefore an estimation of shear strength parameters of soil for the purposes of a geotechnical analysis causes many problems. In applicable standards (Eurocode 7) there is not presented any explicit method of an evaluation of characteristic values of soil parameters. Only general guidelines can be found how these values should be estimated. Hence many approaches of an assessment of characteristic values of soil parameters are presented in literature and can be applied in practice. In this paper, the reliability assessment of a shallow strip footing was conducted using a reliability index β. Therefore some approaches of an estimation of characteristic values of soil properties were compared by evaluating values of reliability index β which can be achieved by applying each of them. Method of Orr and Breysse, Duncan's method, Schneider's method, Schneider's method concerning influence of fluctuation scales and method included in Eurocode 7 were examined. Design values of the bearing capacity based on these approaches were referred to the stochastic bearing capacity estimated by the random finite element method (RFEM). Design values of the bearing capacity were conducted for various widths and depths of a foundation in conjunction with design approaches DA defined in Eurocode. RFEM was presented by Griffiths and Fenton (1993). It combines deterministic finite element method, random field theory and Monte Carlo simulations. Random field theory allows to consider a random character of soil parameters within a homogenous layer of soil. For this purpose a soil property is considered as a separate random variable in every element of a mesh in the finite element method with proper correlation structure between points of given area. RFEM was applied to estimate which theoretical probability distribution fits the empirical probability distribution of bearing capacity basing on 3000 realizations. Assessed probability distribution was applied to compute design values of the bearing capacity and related reliability indices β. Conducted analysis were carried out for a cohesion soil. Hence a friction angle and a cohesion were defined as a random parameters and characterized by two dimensional random fields. A friction angle was described by a bounded distribution as it differs within limited range. While a lognormal distribution was applied in case of a cohesion. Other properties - Young's modulus, Poisson's ratio and unit weight were assumed as deterministic values because they have negligible influence on the stochastic bearing capacity. Griffiths D. V., & Fenton G. A. (1993). Seepage beneath water retaining structures founded on spatially random soil. Géotechnique, 43(6), 577-587.

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

PubMed

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

2014-09-01

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

Heritability estimations for inner muscular fat in Hereford cattle using random regressions

USDA-ARS?s Scientific Manuscript database

Random regressions make possible to make genetic predictions and parameters estimation across a gradient of environments, allowing a more accurate and beneficial use of animals as breeders in specific environments. The objective of this study was to use random regression models to estimate heritabil...

Estimation of Parameters from Discrete Random Nonstationary Time Series

NASA Astrophysics Data System (ADS)

Takayasu, H.; Nakamura, T.

For the analysis of nonstationary stochastic time series we introduce a formulation to estimate the underlying time-dependent parameters. This method is designed for random events with small numbers that are out of the applicability range of the normal distribution. The method is demonstrated for numerical data generated by a known system, and applied to time series of traffic accidents, batting average of a baseball player and sales volume of home electronics.

Dirty two-band superconductivity with interband pairing order

NASA Astrophysics Data System (ADS)

Asano, Yasuhiro; Sasaki, Akihiro; Golubov, Alexander A.

2018-04-01

We study theoretically the effects of random nonmagnetic impurities on the superconducting transition temperature T c in a two-band superconductor characterized by an equal-time s-wave interband pairing order parameter. Because of the two-band degree of freedom, it is possible to define a spin-triplet s-wave pairing order parameter as well as a spin-singlet s-wave order parameter. The former belongs to odd-band-parity symmetry class, whereas the latter belongs to even-band-parity symmetry class. In a spin-singlet superconductor, T c is insensitive to the impurity concentration when we estimate the self-energy due to the random impurity potential within the Born approximation. On the other hand in a spin-triplet superconductor, T c decreases with the increase of the impurity concentration. We conclude that Cooper pairs belonging to odd-band-parity symmetry class are fragile under the random impurity potential even though they have s-wave pairing symmetry.

Geometric Modeling of Inclusions as Ellipsoids

NASA Technical Reports Server (NTRS)

Bonacuse, Peter J.

2008-01-01

Nonmetallic inclusions in gas turbine disk alloys can have a significant detrimental impact on fatigue life. Because large inclusions that lead to anomalously low lives occur infrequently, probabilistic approaches can be utilized to avoid the excessively conservative assumption of lifing to a large inclusion in a high stress location. A prerequisite to modeling the impact of inclusions on the fatigue life distribution is a characterization of the inclusion occurrence rate and size distribution. To help facilitate this process, a geometric simulation of the inclusions was devised. To make the simulation problem tractable, the irregularly sized and shaped inclusions were modeled as arbitrarily oriented, three independent dimensioned, ellipsoids. Random orientation of the ellipsoid is accomplished through a series of three orthogonal rotations of axes. In this report, a set of mathematical models for the following parameters are described: the intercepted area of a randomly sectioned ellipsoid, the dimensions and orientation of the intercepted ellipse, the area of a randomly oriented sectioned ellipse, the depth and width of a randomly oriented sectioned ellipse, and the projected area of a randomly oriented ellipsoid. These parameters are necessary to determine an inclusion s potential to develop a propagating fatigue crack. Without these mathematical models, computationally expensive search algorithms would be required to compute these parameters.

Modeling the effects of multicontextual physics instruction on learner expectations and understanding of force and motion systems

NASA Astrophysics Data System (ADS)

Deese Becht, Sara-Maria Francis

1999-11-01

The purpose of this study is two-fold involving both practical and theoretical modeling components. The practical component, an experiential-learning phase, investigated a study population for effects that increasing levels of multicontextual physics activities have on student understanding of Newtonian systems of motion. This contextual-learning model measured learner convictions and non-response gaps and analyzed learner response trends on context, technology, challenge, growth, and success. The theoretical component, a model-building phase, designed a dynamic-knowing model for learning along a range of experiential tasks, from low to high context, monitored for indicators of learning in science and mathematics: learner academic performance and ability, learner control and academic attitude, and a learner non- response gap. This knowing model characterized a learner's process-of-knowing on a less to more expert- like learner-response continuum using performance and perspective indices associated with level of contextual- imagery referent system. Data for the contextual-learning model were collected on 180 secondary subjects: 72 middle and 108 high, with 36 physics subjects as local experts. Subjects were randomly assigned to one of three experimental groups differing only on context level of force and motion activities. Three levels of information were presented through context-based tasks: momentum constancy as inertia, momentum change as impulse, and momentum rate of change as force. The statistical analysis used a multi-level factorial design with repeated measures and discriminate analysis of response-conviction items. Subject grouping criteria included school level, ability level in science and mathematics, gender and race. Assessment criteria used pre/post performance scores, confidence level in physics concepts held, and attitude towards science, mathematics, and technology. Learner indices were computed from logit- transforms applied to learner outcomes and to study control and prediction criteria parameters. Findings suggest learner success rates vary with multicontextual experience level. When controlling for context, learner success seems to depend on technology level of assessment tool, learner attitude toward technology learning tools, learner attitude toward science and mathematics, and challenge level of force and motion problems. A learner non-response gap seems important when monitoring learner conviction. Application of the knowing model to the study population pictures learners on a journey towards success referenced to a local expert response.

The effects of drug and alcohol consumption on driver injury severities in single-vehicle crashes.

PubMed

Behnood, Ali; Mannering, Fred L

2017-07-04

It is well known that alcohol and drugs influence driving behavior by affecting the central nervous system, awareness, vision, and perception/reaction times, but the resulting effect on driver injuries in car crashes is not fully understood. The purpose of this study was to identify factors affecting the injury severities of unimpaired, alcohol-impaired, and drug-impaired drivers. The current article applies a random parameters logit model to study the differences in injury severities among unimpaired, alcohol-impaired, and drug-impaired drivers. Using data from single-vehicle crashes in Cook County, Illinois, over a 9-year period from January 1, 2004, to December 31, 2012, separate models for unimpaired, alcohol-impaired, and drug-impaired drivers were estimated. A wide range of variables potentially affecting driver injury severity was considered, including roadway and environmental conditions, driver attributes, time and location of the crash, and crash-specific factors. The estimation results show significant differences in the determinants of driver injury severities across groups of unimpaired, alcohol-impaired, and drug-impaired drivers. The findings also show that unimpaired drivers are understandably more responsive to variations in lighting, adverse weather, and road conditions, but these drivers also tend to have much more heterogeneity in their behavioral responses to these conditions, relative to impaired drivers. In addition, age and gender were found to be important determinants of injury severity, but the effects varied significantly across all drivers, particularly among alcohol-impaired drivers. The model estimation results show that statistically significant differences exist in driver injury severities among the unimpaired, alcohol-impaired, and drug-impaired driver groups considered. Specifically, we find that unimpaired drivers tend to have more heterogeneity in their injury outcomes in the presence potentially adverse weather and road surface conditions. This makes sense because one would expect unimpaired drivers to apply their full knowledge/judgment range to deal with these conditions, and the variability of this range across the driver population (with different driving experiences, etc.) should be great. In contrast, we find, for the most part, that alcohol-impaired and drug-impaired drivers have far less heterogeneity in the factors that affect injury severity, suggesting an equalizing effect resulting from the decision-impairing substance.

Estimation for the Rasch Model When Both Ability and Difficulty Parameters are Random.

DTIC Science & Technology

1987-02-01

Office of Naval Research. The authors would also like to thank Hsin Ying Lin for performing the computations of the third section and the reviewers of an...MODEL 0’) WHEN BOTH ABILITY AND_ DIFFICULTY PARAMETERS ARE RANDOM Steven E. Rigdon and Robert K. Tsutakawa Mathematical Sciences Technical Report No...13, NR 150-535 with the Personnel and Training Research Programs Psychological Sciences Division Office of Naval Research Approved for public release

An approximate generalized linear model with random effects for informative missing data.

PubMed

Follmann, D; Wu, M

1995-03-01

This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are linked by a common random parameter. Such models have been developed in the econometrics (Heckman, 1979, Econometrica 47, 153-161) and biostatistics (Wu and Carroll, 1988, Biometrics 44, 175-188) literature for a Gaussian primary response. We allow the primary response, conditional on the random parameter, to follow a generalized linear model and approximate the generalized linear model by conditioning on the data that describes missingness. The resultant approximation is a mixed generalized linear model with possibly heterogeneous random effects. An example is given to illustrate the approximate approach, and simulations are performed to critique the adequacy of the approximation for repeated binary data.

Under-sampling trajectory design for compressed sensing based DCE-MRI.

PubMed

Liu, Duan-duan; Liang, Dong; Zhang, Na; Liu, Xin; Zhang, Yuan-ting

2013-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) needs high temporal and spatial resolution to accurately estimate quantitative parameters and characterize tumor vasculature. Compressed Sensing (CS) has the potential to accomplish this mutual importance. However, the randomness in CS under-sampling trajectory designed using the traditional variable density (VD) scheme may translate to uncertainty in kinetic parameter estimation when high reduction factors are used. Therefore, accurate parameter estimation using VD scheme usually needs multiple adjustments on parameters of Probability Density Function (PDF), and multiple reconstructions even with fixed PDF, which is inapplicable for DCE-MRI. In this paper, an under-sampling trajectory design which is robust to the change on PDF parameters and randomness with fixed PDF is studied. The strategy is to adaptively segment k-space into low-and high frequency domain, and only apply VD scheme in high-frequency domain. Simulation results demonstrate high accuracy and robustness comparing to VD design.

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

PubMed

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

2018-02-01

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

A random utility model of delay discounting and its application to people with externalizing psychopathology.

PubMed

Dai, Junyi; Gunn, Rachel L; Gerst, Kyle R; Busemeyer, Jerome R; Finn, Peter R

2016-10-01

Previous studies have demonstrated that working memory capacity plays a central role in delay discounting in people with externalizing psychopathology. These studies used a hyperbolic discounting model, and its single parameter-a measure of delay discounting-was estimated using the standard method of searching for indifference points between intertemporal options. However, there are several problems with this approach. First, the deterministic perspective on delay discounting underlying the indifference point method might be inappropriate. Second, the estimation procedure using the R2 measure often leads to poor model fit. Third, when parameters are estimated using indifference points only, much of the information collected in a delay discounting decision task is wasted. To overcome these problems, this article proposes a random utility model of delay discounting. The proposed model has 2 parameters, 1 for delay discounting and 1 for choice variability. It was fit to choice data obtained from a recently published data set using both maximum-likelihood and Bayesian parameter estimation. As in previous studies, the delay discounting parameter was significantly associated with both externalizing problems and working memory capacity. Furthermore, choice variability was also found to be significantly associated with both variables. This finding suggests that randomness in decisions may be a mechanism by which externalizing problems and low working memory capacity are associated with poor decision making. The random utility model thus has the advantage of disclosing the role of choice variability, which had been masked by the traditional deterministic model. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Assessing variance components in multilevel linear models using approximate Bayes factors: A case study of ethnic disparities in birthweight

PubMed Central

Saville, Benjamin R.; Herring, Amy H.; Kaufman, Jay S.

2013-01-01

Racial/ethnic disparities in birthweight are a large source of differential morbidity and mortality worldwide and have remained largely unexplained in epidemiologic models. We assess the impact of maternal ancestry and census tract residence on infant birth weights in New York City and the modifying effects of race and nativity by incorporating random effects in a multilevel linear model. Evaluating the significance of these predictors involves the test of whether the variances of the random effects are equal to zero. This is problematic because the null hypothesis lies on the boundary of the parameter space. We generalize an approach for assessing random effects in the two-level linear model to a broader class of multilevel linear models by scaling the random effects to the residual variance and introducing parameters that control the relative contribution of the random effects. After integrating over the random effects and variance components, the resulting integrals needed to calculate the Bayes factor can be efficiently approximated with Laplace’s method. PMID:24082430

A stratification approach using logit-based models for confounder adjustment in the study of continuous outcomes.

PubMed

Tan, Chuen Seng; Støer, Nathalie C; Chen, Ying; Andersson, Marielle; Ning, Yilin; Wee, Hwee-Lin; Khoo, Eric Yin Hao; Tai, E-Shyong; Kao, Shih Ling; Reilly, Marie

2017-01-01

The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.

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

NASA Astrophysics Data System (ADS)

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.

Utilization of infertility services: how much does money matter?

PubMed

Farley Ordovensky Staniec, J; Webb, Natalie J

2007-06-01

To estimate the effects of financial access and other individual characteristics on the likelihood that a woman pursues infertility treatment and the choice of treatment type. The 1995 National Survey of Family Growth. We use a binomial logit model to estimate the effects of financial access and individual characteristics on the likelihood that a woman pursues infertility treatment. We then use a multinomial logit model to estimate the differential effects of these variables across treatment types. This study analyzes the subset of 1,210 women who meet the definition of infertile or subfecund from the 1995 National Survey of Family Growth. We find that income, insurance coverage, age, and parity (number of previous births) all significantly affect the probability of seeking infertility treatment; however, the effect of these variables on choice of treatment type varies significantly. Neither income nor insurance influences the probability of seeking advice, a relatively low cost, low yield treatment. At the other end of the spectrum, the choice to pursue assisted reproductive technologies (ARTs)-a much more expensive but potentially more productive option-is highly influenced by income, but merely having private insurance has no significant effect. In the middle of the spectrum are treatment options such as testing, surgery, and medications, for which "financial access" increases their probability of selection. Our results illustrate that for the sample of infertile of subfecund women of childbearing age studied, and considering their options, financial access to infertility treatment does matter.

Circulating Prolactin Associates With Diabetes and Impaired Glucose Regulation

PubMed Central

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

2013-01-01

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

Analysis of crash proportion by vehicle type at traffic analysis zone level: A mixed fractional split multinomial logit modeling approach with spatial effects.

PubMed

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

2018-02-01

In traffic safety literature, crash frequency variables are analyzed using univariate count models or multivariate count models. In this study, we propose an alternative approach to modeling multiple crash frequency dependent variables. Instead of modeling the frequency of crashes we propose to analyze the proportion of crashes by vehicle type. A flexible mixed multinomial logit fractional split model is employed for analyzing the proportions of crashes by vehicle type at the macro-level. In this model, the proportion allocated to an alternative is probabilistically determined based on the alternative propensity as well as the propensity of all other alternatives. Thus, exogenous variables directly affect all alternatives. The approach is well suited to accommodate for large number of alternatives without a sizable increase in computational burden. The model was estimated using crash data at Traffic Analysis Zone (TAZ) level from Florida. The modeling results clearly illustrate the applicability of the proposed framework for crash proportion analysis. Further, the Excess Predicted Proportion (EPP)-a screening performance measure analogous to Highway Safety Manual (HSM), Excess Predicted Average Crash Frequency is proposed for hot zone identification. Using EPP, a statewide screening exercise by the various vehicle types considered in our analysis was undertaken. The screening results revealed that the spatial pattern of hot zones is substantially different across the various vehicle types considered. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predictors of functional vision changes after cataract surgery: the PROVISION study.

PubMed

Chaudhary, Varun; Popovic, Marko; Holmes, Julie; Robinson, Tammy; Mak, Michael; Mohaghegh P, S Mohammad; Eino, Dalia; Mann, Keith; Kobetz, Lawrence; Gusenbauer, Kaela; Barbosa, Joshua

2016-08-01

To ascertain whether time-to-treatment, sex, age, preoperative functional vision scores, education, and ocular comorbidities predict change in functional vision pre- to postoperatively in patients receiving cataract surgery. Prospective cohort study. Three hundred and forty-three cataract patients at the Hamilton Regional Eye Institute. Participants 18 years or older scheduled to undergo cataract surgery completed the Catquest-9SF functional vision questionnaire on the day of their surgery and were mailed a survey 2-3 months postoperatively. Multivariate linear regression was used to determine the ability of predictors to explain variability in functional vision change between questionnaire administrations. One hundred and sixty-six patients completed both baseline and follow-up questionnaires. Mean age of the cohort was 73.8 ± 8.1 years. Most patients were female (59.6%), had cataract surgery performed for the first time (66.9%), and had spent a mean time of 20.3 ± 20.7 weeks waiting for surgery. Functional vision improved in 83.7% of patients. The mean baseline Catquest-9SF score was the only significant predictor of functional vision improvement (adjusted R(2) = 0.47; F1,159 = 144.6; p < 0.001). Controlling for other variables, functional vision improved by 0.74 logits when mean baseline survey score increased by 1 logit. In most patients, functional vision improved after cataract surgery. Mean baseline Catquest-9SF score was a moderate predictor of the observed improvement. Copyright © 2016 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

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

PubMed

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.

Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

NASA Astrophysics Data System (ADS)

Zhang, Min; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Liu, Ke

2016-01-01

Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.

Kalman filter data assimilation: targeting observations and parameter estimation.

PubMed

Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex

2014-06-01

This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

Kalman filter data assimilation: Targeting observations and parameter estimation

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

Bellsky, Thomas, E-mail: bellskyt@asu.edu; Kostelich, Eric J.; Mahalov, Alex

2014-06-15

This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly locatedmore » observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.« less

Deterministic diffusion in flower-shaped billiards.

PubMed

Harayama, Takahisa; Klages, Rainer; Gaspard, Pierre

2002-08-01

We propose a flower-shaped billiard in order to study the irregular parameter dependence of chaotic normal diffusion. Our model is an open system consisting of periodically distributed obstacles in the shape of a flower, and it is strongly chaotic for almost all parameter values. We compute the parameter dependent diffusion coefficient of this model from computer simulations and analyze its functional form using different schemes, all generalizing the simple random walk approximation of Machta and Zwanzig. The improved methods we use are based either on heuristic higher-order corrections to the simple random walk model, on lattice gas simulation methods, or they start from a suitable Green-Kubo formula for diffusion. We show that dynamical correlations, or memory effects, are of crucial importance in reproducing the precise parameter dependence of the diffusion coefficent.

Robot-assisted gait training in multiple sclerosis patients: a randomized trial.

PubMed

Schwartz, Isabella; Sajin, Anna; Moreh, Elior; Fisher, Iris; Neeb, Martin; Forest, Adina; Vaknin-Dembinsky, Adi; Karusis, Dimitrios; Meiner, Zeev

2012-06-01

Preservation of locomotor activity in multiple sclerosis (MS) patients is of utmost importance. Robotic-assisted body weight-supported treadmill training is a promising method to improve gait functions in neurologically impaired patients, although its effectiveness in MS patients is still unknown. To compare the effectiveness of robot-assisted gait training (RAGT) with that of conventional walking treatment (CWT) on gait and generalized functions in a group of stable MS patients. A prospective randomized controlled trial of 12 sessions of RAGT or CWT in MS patients of EDSS score 5-7. Primary outcome measures were gait parameters and the secondary outcomes were functional and quality of life parameters. All tests were performed at baseline, 3 and 6 months post-treatment by a blinded rater. Fifteen and 17 patients were randomly allocated to RAGT and CWT, respectively. Both groups were comparable at baseline in all parameters. As compared with baseline, although some gait parameters improved significantly following the treatment at each time point there was no difference between the groups. Both FIM and EDSS scores improved significantly post-treatment with no difference between the groups. At 6 months, most gait and functional parameters had returned to baseline. Robot-assisted gait training is feasible and safe and may be an effective additional therapeutic option in MS patients with severe walking disabilities.

The effects of the one-step replica symmetry breaking on the Sherrington-Kirkpatrick spin glass model in the presence of random field with a joint Gaussian probability density function for the exchange interactions and random fields

NASA Astrophysics Data System (ADS)

Hadjiagapiou, Ioannis A.; Velonakis, Ioannis N.

2018-07-01

The Sherrington-Kirkpatrick Ising spin glass model, in the presence of a random magnetic field, is investigated within the framework of the one-step replica symmetry breaking. The two random variables (exchange integral interaction Jij and random magnetic field hi) are drawn from a joint Gaussian probability density function characterized by a correlation coefficient ρ, assuming positive and negative values. The thermodynamic properties, the three different phase diagrams and system's parameters are computed with respect to the natural parameters of the joint Gaussian probability density function at non-zero and zero temperatures. The low temperature negative entropy controversy, a result of the replica symmetry approach, has been partly remedied in the current study, leading to a less negative result. In addition, the present system possesses two successive spin glass phase transitions with characteristic temperatures.

Optimal strategy analysis based on robust predictive control for inventory system with random demand

NASA Astrophysics Data System (ADS)

Saputra, Aditya; Widowati, Sutrisno

2017-12-01

In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.

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

PubMed

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

2013-10-01

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

Uncertainty Analysis in 3D Equilibrium Reconstruction

DOE PAGES

Cianciosa, Mark R.; Hanson, James D.; Maurer, David A.

2018-02-21

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the resultsmore » of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.« less

Uncertainty Analysis in 3D Equilibrium Reconstruction

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

Cianciosa, Mark R.; Hanson, James D.; Maurer, David A.

Reconstruction is an inverse process where a parameter space is searched to locate a set of parameters with the highest probability of describing experimental observations. Due to systematic errors and uncertainty in experimental measurements, this optimal set of parameters will contain some associated uncertainty. This uncertainty in the optimal parameters leads to uncertainty in models derived using those parameters. V3FIT is a three-dimensional (3D) equilibrium reconstruction code that propagates uncertainty from the input signals, to the reconstructed parameters, and to the final model. Here in this paper, we describe the methods used to propagate uncertainty in V3FIT. Using the resultsmore » of whole shot 3D equilibrium reconstruction of the Compact Toroidal Hybrid, this propagated uncertainty is validated against the random variation in the resulting parameters. Two different model parameterizations demonstrate how the uncertainty propagation can indicate the quality of a reconstruction. As a proxy for random sampling, the whole shot reconstruction results in a time interval that will be used to validate the propagated uncertainty from a single time slice.« less

A Probabilistic Design Method Applied to Smart Composite Structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1995-01-01

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

PubMed

Hossain, Moinul; Muromachi, Yasunori

2012-03-01

The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.

Driven to Support: Individual- and County-Level Factors Associated With Public Support for Active Transportation Policies.

PubMed

Cradock, Angie L; Barrett, Jessica L; Chriqui, Jamie F; Evenson, Kelly R; Goins, Karin Valentine; Gustat, Jeanette; Heinrich, Katie M; Perry, Cynthia K; Scanze, Michele; Schmid, Thomas L; Tabak, Rachel G; Umstattd Meyer, M Renee; Valko, Cheryl

2018-03-01

To assess predictors of stated support for policies promoting physically active transportation. Cross-sectional. US counties selected on county-level physical activity and obesity health status. Participants completing random-digit dialed telephone survey (n = 906). Survey measures assessed stated support for 5 policies to promote physically active transportation, access to active transportation facilities, and time spent in a car. County-level estimates included household car dependence and funding for bicycle-pedestrian projects. Multivariable generalized linear mixed models using binary distribution and logit link, accounting for clustering within county. Respondents supported policies for accommodating bicyclists and pedestrians through street improvements (89%), school active transportation programs (75%), employer-funded active commuting incentives (67%), and allocation of public funding (68%) and tax support (56%) for building and maintaining public transit. Residents spending >2 h/d (vs <0.7 hours) in cars were more likely to support street (odds ratio [OR]: 1.87; confidence interval [CI]: 1.09-3.22) and public transit (OR: 1.85; CI: 1.24-2.77) improvements. Residents in counties investing >$1.6 million in bicycle and pedestrian improvements expressed greater support for funding (OR: 1.71; CI: 1.04-2.83) and tax increases (OR: 1.73; CI: 1.08-2.75) for transit improvements compared to those with lower prior investments (<$276 100). Support for policies to enable active transportation is higher where relevant investments in active transportation infrastructure are large (>$1.6 M), public transit is nearby, and respondents drive >2 h/d.

Asthma and subjective sleep disordered breathing in a large cohort of urban adolescents.

PubMed

Zandieh, Stephanie O; Cespedes, Amarilis; Ciarleglio, Adam; Bourgeois, Wallace; Rapoport, David M; Bruzzese, Jean-Marie

2017-01-02

Sleep disordered breathing (SDB) has not been well studied in urban adolescents with asthma in community settings. Nor has the association of SDB symptoms and asthma severity been studied. We characterized self-reported symptoms suggesting SDB and investigated the association of SDB symptoms, probable asthma, and asthma severity. 9,565 adolescents from 21 inner-city high schools were screened for an asthma intervention study. Students reported on symptoms suggesting SDB using questions from the 2007 NHANES, if they were ever diagnosed with asthma, and on asthma symptoms. Using generalized linear mixed models with logit link with school as a random intercept and adjusting for age, gender, and race/ethnicity, we examined associations of SDB symptoms, and demographic characteristics, probable asthma, and asthma severity. 12% reported SDB symptoms. Older and bi-racial participants (compared to Caucasian) had higher odds of symptoms suggesting SDB (p <.001). Compared to those without probable asthma, adolescents with probable asthma had 2.63 greater odds of reporting SDB symptoms (p <.001). Among those with probable asthma, the odds of reporting SDB symptoms increased with asthma severity. When exploring daytime severity and severity due to night wakening separately, results were similar. All results remained significant when controlling for age, gender, and ethnicity. In a large urban community cohort of predominately ethnic minority adolescents, self-reported SDB symptoms were associated with probable asthma and increased asthma severity. This study highlights the importance of SDB as a modifiable co-morbidity of asthma.

Asthma and Subjective Sleep Disordered Breathing in a Large Cohort of Urban Adolescents

PubMed Central

Zandieh, Stephanie O.; Cespedes, Amarilis; Ciarleglio, Adam; Bourgeois, Wallace; Rapoport, David M.; Bruzzese, Jean-Marie

2017-01-01

Objective Sleep disordered breathing (SDB) has not been well studied in urban adolescents with asthma in community settings. Nor has the association of SDB symptoms and asthma severity been studied. We characterized self-reported symptoms suggesting SDB and investigated the association of SDB symptoms, probable asthma, and asthma severity. Methods 9,565 adolescents from 21 inner-city high schools were screened for an asthma intervention study. Students reported on symptoms suggesting SDB using questions from the 2007 NHANES, if they were ever diagnosed with asthma, and on asthma symptoms. Using generalized linear mixed models with logit link with school as a random intercept and adjusting for age, gender, and race/ethnicity, we examined associations of SDB symptoms, and demographic characteristics, probable asthma, and asthma severity. Results 12% reported SDB symptoms. Older and biracial participants (compared to Caucasian) had higher odds of symptoms suggesting SDB (p<.001). Compared to those without probable asthma, adolescents with probable asthma had 2.63 greater odds of reporting SDB symptoms (p<.001). Among those with probable asthma, the odds of reporting SDB symptoms increased with asthma severity. When exploring daytime severity and severity due to night wakening separately, results were similar. All results remained significant when controlling for age, gender, and ethnicity. Conclusions In a large urban community cohort of predominately ethnic minority adolescents, self-reported SDB symptoms were associated with probable asthma and increased asthma severity. This study highlights the importance of SDB as a modifiable co-morbidity of asthma. PMID:27740900

Development of scales relating to professional development of community college administrators.

PubMed

Wolfe, Edward W; Van Der Linden, Kim E

2010-01-01

This article reports the results of an application of the Multidimensional Random Coefficients Multinomial Logit Model (MRCMLM) to the measurement of professional development activities in which community college administrators participate. The analyses focus on confirmation of the factorial structure of the instrument, evaluation of the quality of the activities calibrations, examination of the internal structure of the instrument, and comparison of groups of administrators. The dimensionality analysis results suggest a five-dimensional model that is consistent with previous literature concerning career paths of community college administrators - education and specialized training, internal professional development and mentoring, external professional development, employer support, and seniority. The indicators of the quality of the activity calibrations suggest that measures of the five dimensions are adequately reliable, that the activities in each dimension are internally consistent, and that the observed responses to each activity are consistent with the expected values of the MRCMLM. The hierarchy of administrator measure means and of activity calibrations is consistent with substantive theory relating to professional development for community college administrators. For example, readily available activities that occur at the institution were most likely to be engaged in by administrators, while participation in selective specialized training institutes were the least likely activities. Finally, group differences with respect to age and title were consistent with substantive expectations - the greater the administrator's age and the higher the rank of the administrator's title, the greater the probability of having engaged in various types of professional development.

An application of the SF-6D to create heath values in Portuguese working age adults.

PubMed

Ferreira, Lara Noronha; Ferreira, Pedro Lopes; Pereira, Luís Nobre; Brazier, John

2008-01-01

This study describes the health-related quality of life (HRQOL) of the Portuguese working age population and investigates sociodemographic differences. Subjects randomly selected from the working age population (n=2,459) were assessed using the SF-36v2 and converted into the preference-based SF-6D. The mean SF-6D utility value was 0.70 (range 0.63-0.73). The mean utility value was lower for the lower educational level than for the highest. Women, people living in rural areas and older adults reported lower levels of utility values. Non-parametric tests showed that health utility values were significantly related to employment; unskilled manual workers reported utility values lower than non-manual workers. For different diseases, mean utility values ranged from 0.58 (sexual diseases) to 0.66 (hepatic conditions). Cluster analysis was adopted to classify individuals into three groups according to their answers to the SF-6D dimensions. Multinomial logit regression was used to detect sociodemographic characteristics affecting the probability of following each cluster pattern. This study yielded normative data by age and gender for the SF-6D. The authors conclude that SF-6D is an effective tool for measuring HRQOL in the community so that different population groups can be compared. The preference-based measure used seems to discriminate adequately across sociodemographic differences. These results allow a better understanding of the impact of sociodemographic variables on the burden of illness perception.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Under What Circumstances Does External Knowledge about the Correlation Structure Improve Power in Cluster Randomized Designs?

ERIC Educational Resources Information Center

Rhoads, Christopher

2014-01-01

Recent publications have drawn attention to the idea of utilizing prior information about the correlation structure to improve statistical power in cluster randomized experiments. Because power in cluster randomized designs is a function of many different parameters, it has been difficult for applied researchers to discern a simple rule explaining…

The Random-Threshold Generalized Unfolding Model and Its Application of Computerized Adaptive Testing

ERIC Educational Resources Information Center

Wang, Wen-Chung; Liu, Chen-Wei; Wu, Shiu-Lien

2013-01-01

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…

Radiation-related quality of life parameters after targeted intraoperative radiotherapy versus whole breast radiotherapy in patients with breast cancer: results from the randomized phase III trial TARGIT-A.

PubMed

Welzel, Grit; Boch, Angela; Sperk, Elena; Hofmann, Frank; Kraus-Tiefenbacher, Uta; Gerhardt, Axel; Suetterlin, Marc; Wenz, Frederik

2013-01-07

Intraoperative radiotherapy (IORT) is a new treatment approach for early stage breast cancer. This study reports on the effects of IORT on radiation-related quality of life (QoL) parameters. Two hundred and thirty women with stage I-III breast cancer (age, 31 to 84 years) were entered into the study. A single-center subgroup of 87 women from the two arms of the randomized phase III trial TARGIT-A (TARGeted Intra-operative radioTherapy versus whole breast radiotherapy for breast cancer) was analyzed. Furthermore, results were compared to non-randomized control groups: n = 90 receiving IORT as a tumor bed boost followed by external beam whole breast radiotherapy (EBRT) outside of TARGIT-A (IORT-boost), and n = 53 treated with EBRT followed by an external-beam boost (EBRT-boost). QoL was collected using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaires C30 (QLQ-C30) and BR23 (QLQ-BR23). The mean follow-up period in the TARGIT-A groups was 32 versus 39 months in the non-randomized control groups. Patients receiving IORT alone reported less general pain (21.3 points), breast (7.0 points) and arm (15.1 points) symptoms, and better role functioning (78.7 points) as patients receiving EBRT (40.9; 19.0; 32.8; and 60.5 points, respectively, P < 0.01). Patients receiving IORT alone also had fewer breast symptoms than TARGIT-A patients receiving IORT followed by EBRT for high risk features on final pathology (IORT-EBRT; 7.0 versus 29.7 points, P < 0.01). There were no significant differences between TARGIT-A patients receiving IORT-EBRT compared to non-randomized IORT-boost or EBRT-boost patients and patients receiving EBRT without a boost. In the randomized setting, important radiation-related QoL parameters after IORT were superior to EBRT. Non-randomized comparisons showed equivalent parameters in the IORT-EBRT group and the control groups.

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

PubMed

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

2017-09-01

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

Systematic review and network meta-analysis of combination and monotherapy treatments in disease-modifying antirheumatic drug-experienced patients with rheumatoid arthritis: analysis of American College of Rheumatology criteria scores 20, 50, and 70

PubMed Central

Orme, Michelle E; MacGilchrist, Katherine S; Mitchell, Stephen; Spurden, Dean; Bird, Alex

2012-01-01

Background Biologic disease-modifying antirheumatic drugs (bDMARDs) extend the treatment choices for rheumatoid arthritis patients with suboptimal response or intolerance to conventional DMARDs. The objective of this systematic review and meta-analysis was to compare the relative efficacy of EU-licensed bDMARD combination therapy or monotherapy for patients intolerant of or contraindicated to continued methotrexate. Methods Comprehensive, structured literature searches were conducted in Medline, Embase, and the Cochrane Library, as well as hand-searching of conference proceedings and reference lists. Phase II or III randomized controlled trials reporting American College of Rheumatology (ACR) criteria scores of 20, 50, and 70 between 12 and 30 weeks’ follow-up and enrolling adult patients meeting ACR classification criteria for rheumatoid arthritis previously treated with and with an inadequate response to conventional DMARDs were eligible. To estimate the relative efficacy of treatments whilst preserving the randomized comparisons within each trial, a Bayesian network meta-analysis was conducted in WinBUGS using fixed and random-effects, logit-link models fitted to the binomial ACR 20/50/70 trial data. Results The systematic review identified 10,625 citations, and after a review of 2450 full-text papers, there were 29 and 14 eligible studies for the combination and monotherapy meta-analyses, respectively. In the combination analysis, all licensed bDMARD combinations had significantly higher odds of ACR 20/50/70 compared to DMARDs alone, except for the rituximab comparison, which did not reach significance for the ACR 70 outcome (based on the 95% credible interval). The etanercept combination was significantly better than the tumor necrosis factor-α inhibitors adalimumab and infliximab in improving ACR 20/50/70 outcomes, with no significant differences between the etanercept combination and certolizumab pegol or tocilizumab. Licensed-dose etanercept, adalimumab, and tocilizumab monotherapy were significantly better than placebo in improving ACR 20/50/70 outcomes. Sensitivity analysis indicated that including studies outside the target population could affect the results. Conclusion Licensed bDMARDs are efficacious in patients with an inadequate response to conventional therapy, but tumor necrosis factor-α inhibitor combination therapies are not equally effective. PMID:23269860

Prebiotics, Prosynbiotics and Synbiotics: Can They Reduce Plasma Oxidative Stress Parameters? A Systematic Review.

PubMed

Salehi-Abargouei, Amin; Ghiasvand, Reza; Hariri, Mitra

2017-03-01

This study assessed the effectiveness of presybiotics, prosybiotics and synbiotics on reducing serum oxidative stress parameters. PubMed/Medline, Ovid, Google Scholar, ISI Web of Science and SCOPUS were searched up to September 2016. English language randomized clinical trials reporting the effect of presybiotics, prosybiotics or synbiotic interventions on serum oxidative stress parameters in human adults were included. Twenty-one randomized clinical trials met the inclusion criteria for systematic review. Two studies investigated prebiotics, four studies synbiotics and fifteen studies probiotics. According to our systematic review, prebiotic could decrease malondialdehyde and increase superoxidative dismutase, but evidence is not enough. In comparison with fructo-oligosaccharide, inulin is much more useful for oxidative stress reduction. Using probiotics with dairy products could reduce oxidative stress significantly, but probiotic in form of supplementation did not have any effect on oxidative stress. There is limited but supportive evidence that presybiotics, prosybiotics and synbiotics are effective for reducing oxidative stress parameters. Further randomized clinical trials with longer duration of intervention especially on population with increased oxidative stress are needed to provide more definitive results before any recommendation for clinical use of these interventions.

Effect of aromatherapy massage on anxiety, depression, and physiologic parameters in older patients with the acute coronary syndrome: A randomized clinical trial.

PubMed

Bahrami, Tahereh; Rejeh, Nahid; Heravi-Karimooi, Majideh; Vaismoradi, Mojtaba; Tadrisi, Seyed Davood; Sieloff, Christina

2017-12-01

This study aimed to investigate the effect of aromatherapy massage on anxiety, depression, and physiologic parameters in older patients with acute coronary syndrome. This randomized controlled trial was conducted on 90 older women with acute coronary syndrome. The participants were randomly assigned into the intervention and control groups (n = 45). The intervention group received reflexology with lavender essential oil, but the control group only received routine care. Physiologic parameters, the levels of anxiety and depression in the hospital were evaluated using a checklist and the Hospital's Anxiety and Depression Scale, respectively, before and immediately after the intervention. Significant differences in the levels of anxiety and depression were reported between the groups after the intervention. The analysis of physiological parameters revealed a statistically significant reduction (P < .05) in systolic blood pressure, diastolic blood pressure, mean arterial pressure, and heart rate. However, no significant difference was observed in the respiratory rate. Aromatherapy massage can be considered by clinical nurses an efficient therapy for alleviating psychological and physiological responses among older women suffering from acute coronary syndrome. © 2017 John Wiley & Sons Australia, Ltd.

Studies of the DIII-D disruption database using Machine Learning algorithms

NASA Astrophysics Data System (ADS)

Rea, Cristina; Granetz, Robert; Meneghini, Orso

2017-10-01

A Random Forests Machine Learning algorithm, trained on a large database of both disruptive and non-disruptive DIII-D discharges, predicts disruptive behavior in DIII-D with about 90% of accuracy. Several algorithms have been tested and Random Forests was found superior in performances for this particular task. Over 40 plasma parameters are included in the database, with data for each of the parameters taken from 500k time slices. We focused on a subset of non-dimensional plasma parameters, deemed to be good predictors based on physics considerations. Both binary (disruptive/non-disruptive) and multi-label (label based on the elapsed time before disruption) classification problems are investigated. The Random Forests algorithm provides insight on the available dataset by ranking the relative importance of the input features. It is found that q95 and Greenwald density fraction (n/nG) are the most relevant parameters for discriminating between DIII-D disruptive and non-disruptive discharges. A comparison with the Gradient Boosted Trees algorithm is shown and the first results coming from the application of regression algorithms are presented. Work supported by the US Department of Energy under DE-FC02-04ER54698, DE-SC0014264 and DE-FG02-95ER54309.

Evolutionary games combining two or three pair coordinations on a square lattice

NASA Astrophysics Data System (ADS)

Király, Balázs; Szabó, György

2017-10-01

We study multiagent logit-rule-driven evolutionary games on a square lattice whose pair interactions are composed of a maximal number of nonoverlapping elementary coordination games describing Ising-type interactions between just two of the available strategies. Using Monte Carlo simulations we investigate the macroscopic noise-level-dependent behavior of the two- and three-pair games and the critical properties of the continuous phase transtitions these systems exhibit. The four-strategy game is shown to be equivalent to a system that consists of two independent and identical Ising models.

Estimating preferences for local public services using migration data.

PubMed

Dahlberg, Matz; Eklöf, Matias; Fredriksson, Peter; Jofre-Monseny, Jordi

2012-01-01

Using Swedish micro data, the paper examines the impact of local public services on community choice. The choice of community is modelled as a choice between a discrete set of alternatives. It is found that, given taxes, high spending on child care attracts migrants. Less conclusive results are obtained with respect to the role of spending on education and elderly care. High local taxes deter migrants. Relaxing the independence of the irrelevant alternatives assumption, by estimating a mixed logit model, has a significant impact on the results.

Evolutionary games combining two or three pair coordinations on a square lattice.

PubMed

Király, Balázs; Szabó, György

2017-10-01

We study multiagent logit-rule-driven evolutionary games on a square lattice whose pair interactions are composed of a maximal number of nonoverlapping elementary coordination games describing Ising-type interactions between just two of the available strategies. Using Monte Carlo simulations we investigate the macroscopic noise-level-dependent behavior of the two- and three-pair games and the critical properties of the continuous phase transtitions these systems exhibit. The four-strategy game is shown to be equivalent to a system that consists of two independent and identical Ising models.

Categorical Data Analysis Using a Skewed Weibull Regression Model

NASA Astrophysics Data System (ADS)

Caron, Renault; Sinha, Debajyoti; Dey, Dipak; Polpo, Adriano

2018-03-01

In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as frequentist estimation procedures for binomial and multinomial data responses are presented in details. The analysis of two data sets to show the efficiency of the proposed model is performed.

Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self-assessed Health and an Efficient Discrete Choice Experiment.

PubMed

Jonker, Marcel F; Attema, Arthur E; Donkers, Bas; Stolk, Elly A; Versteegh, Matthijs M

2017-12-01

Health state valuations of patients and non-patients are not the same, whereas health state values obtained from general population samples are a weighted average of both. The latter constitutes an often-overlooked source of bias. This study investigates the resulting bias and tests for the impact of reference dependency on health state valuations using an efficient discrete choice experiment administered to a Dutch nationally representative sample of 788 respondents. A Bayesian discrete choice experiment design consisting of eight sets of 24 (matched pairwise) choice tasks was developed, with each set providing full identification of the included parameters. Mixed logit models were used to estimate health state preferences with respondents' own health included as an additional predictor. Our results indicate that respondents with impaired health worse than or equal to the health state levels under evaluation have approximately 30% smaller health state decrements. This confirms that reference dependency can be observed in general population samples and affirms the relevance of prospect theory in health state valuations. At the same time, the limited number of respondents with severe health impairments does not appear to bias social tariffs as obtained from general population samples. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A Bayesian ridge regression analysis of congestion's impact on urban expressway safety.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Lee, Jaeyoung

2016-03-01

With the rapid growth of traffic in urban areas, concerns about congestion and traffic safety have been heightened. This study leveraged both Automatic Vehicle Identification (AVI) system and Microwave Vehicle Detection System (MVDS) installed on an expressway in Central Florida to explore how congestion impacts the crash occurrence in urban areas. Multiple congestion measures from the two systems were developed. To ensure more precise estimates of the congestion's effects, the traffic data were aggregated into peak and non-peak hours. Multicollinearity among traffic parameters was examined. The results showed the presence of multicollinearity especially during peak hours. As a response, ridge regression was introduced to cope with this issue. Poisson models with uncorrelated random effects, correlated random effects, and both correlated random effects and random parameters were constructed within the Bayesian framework. It was proven that correlated random effects could significantly enhance model performance. The random parameters model has similar goodness-of-fit compared with the model with only correlated random effects. However, by accounting for the unobserved heterogeneity, more variables were found to be significantly related to crash frequency. The models indicated that congestion increased crash frequency during peak hours while during non-peak hours it was not a major crash contributing factor. Using the random parameter model, the three congestion measures were compared. It was found that all congestion indicators had similar effects while Congestion Index (CI) derived from MVDS data was a better congestion indicator for safety analysis. Also, analyses showed that the segments with higher congestion intensity could not only increase property damage only (PDO) crashes, but also more severe crashes. In addition, the issues regarding the necessity to incorporate specific congestion indicator for congestion's effects on safety and to take care of the multicollinearity between explanatory variables were also discussed. By including a specific congestion indicator, the model performance significantly improved. When comparing models with and without ridge regression, the magnitude of the coefficients was altered in the existence of multicollinearity. These conclusions suggest that the use of appropriate congestion measure and consideration of multicolilnearity among the variables would improve the models and our understanding about the effects of congestion on traffic safety. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Harrison, Xavier A

2015-01-01

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

Sunspot random walk and 22-year variation

USGS Publications Warehouse

Love, Jeffrey J.; Rigler, E. Joshua

2012-01-01

We examine two stochastic models for consistency with observed long-term secular trends in sunspot number and a faint, but semi-persistent, 22-yr signal: (1) a null hypothesis, a simple one-parameter random-walk model of sunspot-number cycle-to-cycle change, and, (2) an alternative hypothesis, a two-parameter random-walk model with an imposed 22-yr alternating amplitude. The observed secular trend in sunspots, seen from solar cycle 5 to 23, would not be an unlikely result of the accumulation of multiple random-walk steps. Statistical tests show that a 22-yr signal can be resolved in historical sunspot data; that is, the probability is low that it would be realized from random data. On the other hand, the 22-yr signal has a small amplitude compared to random variation, and so it has a relatively small effect on sunspot predictions. Many published predictions for cycle 24 sunspots fall within the dispersion of previous cycle-to-cycle sunspot differences. The probability is low that the Sun will, with the accumulation of random steps over the next few cycles, walk down to a Dalton-like minimum. Our models support published interpretations of sunspot secular variation and 22-yr variation resulting from cycle-to-cycle accumulation of dynamo-generated magnetic energy.

Random analysis of bearing capacity of square footing using the LAS procedure

NASA Astrophysics Data System (ADS)

Kawa, Marek; Puła, Wojciech; Suska, Michał

2016-09-01

In the present paper, a three-dimensional problem of bearing capacity of square footing on random soil medium is analyzed. The random fields of strength parameters c and φ are generated using LAS procedure (Local Average Subdivision, Fenton and Vanmarcke 1990). The procedure used is re-implemented by the authors in Mathematica environment in order to combine it with commercial program. Since the procedure is still tested the random filed has been assumed as one-dimensional: the strength properties of soil are random in vertical direction only. Individual realizations of bearing capacity boundary-problem with strength parameters of medium defined the above procedure are solved using FLAC3D Software. The analysis is performed for two qualitatively different cases, namely for the purely cohesive and cohesive-frictional soils. For the latter case the friction angle and cohesion have been assumed as independent random variables. For these two cases the random square footing bearing capacity results have been obtained for the range of fluctuation scales from 0.5 m to 10 m. Each time 1000 Monte Carlo realizations have been performed. The obtained results allow not only the mean and variance but also the probability density function to be estimated. An example of application of this function for reliability calculation has been presented in the final part of the paper.

Mixing rates and limit theorems for random intermittent maps

NASA Astrophysics Data System (ADS)

Bahsoun, Wael; Bose, Christopher

2016-04-01

We study random transformations built from intermittent maps on the unit interval that share a common neutral fixed point. We focus mainly on random selections of Pomeu-Manneville-type maps {{T}α} using the full parameter range 0<α <∞ , in general. We derive a number of results around a common theme that illustrates in detail how the constituent map that is fastest mixing (i.e. smallest α) combined with details of the randomizing process, determines the asymptotic properties of the random transformation. Our key result (theorem 1.1) establishes sharp estimates on the position of return time intervals for the quenched dynamics. The main applications of this estimate are to limit laws (in particular, CLT and stable laws, depending on the parameters chosen in the range 0<α <1 ) for the associated skew product; these are detailed in theorem 3.2. Since our estimates in theorem 1.1 also hold for 1≤slant α <∞ we study a second class of random transformations derived from piecewise affine Gaspard-Wang maps, prove existence of an infinite (σ-finite) invariant measure and study the corresponding correlation asymptotics. To the best of our knowledge, this latter kind of result is completely new in the setting of random transformations.

A New Metamodeling Approach for Time-dependent Reliability of Dynamic Systems with Random Parameters Excited by Input Random Processes

DTIC Science & Technology

2014-04-09

Excited by Input Random Processes Igor Baseski1,2, Dorin Drignei3, Zissimos P. Mourelatos1, Monica Majcher1 Oakland University, Rochester MI 48309 1...CONTRACT NUMBER W56HZV-04-2-0001 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Igor Baseski; Dorin Drignei; Zissimos Mourelatos; Monica

Effects of data structure on the estimation of covariance functions to describe genotype by environment interactions in a reaction norm model

PubMed Central

Calus, Mario PL; Bijma, Piter; Veerkamp, Roel F

2004-01-01

Covariance functions have been proposed to predict breeding values and genetic (co)variances as a function of phenotypic within herd-year averages (environmental parameters) to include genotype by environment interaction. The objective of this paper was to investigate the influence of definition of environmental parameters and non-random use of sires on expected breeding values and estimated genetic variances across environments. Breeding values were simulated as a linear function of simulated herd effects. The definition of environmental parameters hardly influenced the results. In situations with random use of sires, estimated genetic correlations between the trait expressed in different environments were 0.93, 0.93 and 0.97 while simulated at 0.89 and estimated genetic variances deviated up to 30% from the simulated values. Non random use of sires, poor genetic connectedness and small herd size had a large impact on the estimated covariance functions, expected breeding values and calculated environmental parameters. Estimated genetic correlations between a trait expressed in different environments were biased upwards and breeding values were more biased when genetic connectedness became poorer and herd composition more diverse. The best possible solution at this stage is to use environmental parameters combining large numbers of animals per herd, while losing some information on genotype by environment interaction in the data. PMID:15339629

Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

PubMed Central

Shah, Anoop D.; Bartlett, Jonathan W.; Carpenter, James; Nicholas, Owen; Hemingway, Harry

2014-01-01

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The “true” imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001–2010) with complete data on all covariates. Variables were artificially made “missing at random,” and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data. PMID:24589914

Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study.

PubMed

Shah, Anoop D; Bartlett, Jonathan W; Carpenter, James; Nicholas, Owen; Hemingway, Harry

2014-03-15

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001-2010) with complete data on all covariates. Variables were artificially made "missing at random," and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data.

Design of state-feedback controllers including sensitivity reduction, with applications to precision pointing

NASA Technical Reports Server (NTRS)

Hadass, Z.

1974-01-01

The design procedure of feedback controllers was described and the considerations for the selection of the design parameters were given. The frequency domain properties of single-input single-output systems using state feedback controllers are analyzed, and desirable phase and gain margin properties are demonstrated. Special consideration is given to the design of controllers for tracking systems, especially those designed to track polynomial commands. As an example, a controller was designed for a tracking telescope with a polynomial tracking requirement and some special features such as actuator saturation and multiple measurements, one of which is sampled. The resulting system has a tracking performance comparing favorably with a much more complicated digital aided tracker. The parameter sensitivity reduction was treated by considering the variable parameters as random variables. A performance index is defined as a weighted sum of the state and control convariances that sum from both the random system disturbances and the parameter uncertainties, and is minimized numerically by adjusting a set of free parameters.