On Restructurable Control System Theory

NASA Technical Reports Server (NTRS)

Athans, M.

1983-01-01

The state of stochastic system and control theory as it impacts restructurable control issues is addressed. The multivariable characteristics of the control problem are addressed. The failure detection/identification problem is discussed as a multi-hypothesis testing problem. Control strategy reconfiguration, static multivariable controls, static failure hypothesis testing, dynamic multivariable controls, fault-tolerant control theory, dynamic hypothesis testing, generalized likelihood ratio (GLR) methods, and adaptive control are discussed.

Various forms of indexing HDMR for modelling multivariate classification problems

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

Aksu, Çağrı; Tunga, M. Alper

2014-12-10

The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled.more » In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.« less

Approximate analysis for repeated eigenvalue problems with applications to controls-structure integrated design

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Hou, Gene J. W.

1994-01-01

A method for eigenvalue and eigenvector approximate analysis for the case of repeated eigenvalues with distinct first derivatives is presented. The approximate analysis method developed involves a reparameterization of the multivariable structural eigenvalue problem in terms of a single positive-valued parameter. The resulting equations yield first-order approximations to changes in the eigenvalues and the eigenvectors associated with the repeated eigenvalue problem. This work also presents a numerical technique that facilitates the definition of an eigenvector derivative for the case of repeated eigenvalues with repeated eigenvalue derivatives (of all orders). Examples are given which demonstrate the application of such equations for sensitivity and approximate analysis. Emphasis is placed on the application of sensitivity analysis to large-scale structural and controls-structures optimization problems.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, George

1993-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, Stanislav

1992-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.

Problems with Multivariate Normality: Can the Multivariate Bootstrap Help?

ERIC Educational Resources Information Center

Thompson, Bruce

Multivariate normality is required for some statistical tests. This paper explores the implications of violating the assumption of multivariate normality and illustrates a graphical procedure for evaluating multivariate normality. The logic for using the multivariate bootstrap is presented. The multivariate bootstrap can be used when distribution…

Predictors of future anabolic androgenic steroid use.

PubMed

Wichstrøm, Lars

2006-09-01

To prospectively study the stability of anabolic androgenic steroid (AAS) use and predictors of AAS use, and to investigate whether AAS use alters the risk of later emotional and behavioral problems. Survey of a national sample of Norwegian high school students (age 15-19) in 1994 followed up in 1999 (N = 2924). Measures of frequent alcohol intoxication (50+ times per 12 months), cannabis use (12 months), hard drug use (12 months), being offered cannabis, eating problems, conduct problems, sexual debut before age 15, BMI, involvement in power sports, perceived physical appearance, and satisfaction with body parts were obtained. Life-time prevalence of AAS use were 1.9 and 0.8% in the follow-up period. Multivariate logistic regression revealed that future AAS use was predicted by young age, male gender, previous AAS use, involvement in power sports, and frequent alcohol intoxication. AAS use did not predict future emotional or behavioral problems other than reducing the risk of future frequent alcohol intoxication. Frequent alcohol intoxication and involvement in power sports appear to predict future AAS use. At the population level there was little stability in individual AAS use from adolescence to early adulthood. No detrimental effects of AAS use could be detected in this study, but low statistical power limits this conclusion.

Who is afraid of math? Two sources of genetic variance for mathematical anxiety.

PubMed

Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W; Lyons, Ian M; Petrill, Stephen A

2014-09-01

Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem solving and achievement. This study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and nonfamilial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics and may extend to other areas of academic achievement. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

Who’s Afraid of Math? Two Sources of Genetic Variance for Mathematical Anxiety

PubMed Central

Wang, Zhe; Hart, Sara Ann; Kovas, Yulia; Lukowski, Sarah; Soden, Brooke; Thompson, Lee A.; Plomin, Robert; McLoughlin, Grainne; Bartlett, Christopher W.; Lyons, Ian M.; Petrill, Stephen A.

2015-01-01

Background Emerging work suggests that academic achievement may be influenced by the management of affect as well as through efficient information processing of task demands. In particular, mathematical anxiety has attracted recent attention because of its damaging psychological effects and potential associations with mathematical problem-solving and achievement. The present study investigated the genetic and environmental factors contributing to the observed differences in the anxiety people feel when confronted with mathematical tasks. In addition, the genetic and environmental mechanisms that link mathematical anxiety with math cognition and general anxiety were also explored. Methods Univariate and multivariate quantitative genetic models were conducted in a sample of 514 12-year-old twin siblings. Results Genetic factors accounted for roughly 40% of the variation in mathematical anxiety, with the remaining being accounted for by child-specific environmental factors. Multivariate genetic analyses suggested that mathematical anxiety was influenced by the genetic and non-familial environmental risk factors associated with general anxiety and additional independent genetic influences associated with math-based problem solving. Conclusions The development of mathematical anxiety may involve not only exposure to negative experiences with mathematics, but also likely involves genetic risks related to both anxiety and math cognition. These results suggest that integrating cognitive and affective domains may be particularly important for mathematics, and may extend to other areas of academic achievement. PMID:24611799

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

Scope of Gradient and Genetic Algorithms in Multivariable Function Optimization

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali; Sen, S. K.

2007-01-01

Global optimization of a multivariable function - constrained by bounds specified on each variable and also unconstrained - is an important problem with several real world applications. Deterministic methods such as the gradient algorithms as well as the randomized methods such as the genetic algorithms may be employed to solve these problems. In fact, there are optimization problems where a genetic algorithm/an evolutionary approach is preferable at least from the quality (accuracy) of the results point of view. From cost (complexity) point of view, both gradient and genetic approaches are usually polynomial-time; there are no serious differences in this regard, i.e., the computational complexity point of view. However, for certain types of problems, such as those with unacceptably erroneous numerical partial derivatives and those with physically amplified analytical partial derivatives whose numerical evaluation involves undesirable errors and/or is messy, a genetic (stochastic) approach should be a better choice. We have presented here the pros and cons of both the approaches so that the concerned reader/user can decide which approach is most suited for the problem at hand. Also for the function which is known in a tabular form, instead of an analytical form, as is often the case in an experimental environment, we attempt to provide an insight into the approaches focusing our attention toward accuracy. Such an insight will help one to decide which method, out of several available methods, should be employed to obtain the best (least error) output. *

Development of multivariate exposure and fatal accident involvement rates for 1977

DOT National Transportation Integrated Search

1985-10-01

The need for multivariate accident involvement rates is often encounted in : accident analysis. The FARS (Fatal Accident Reporting System) files contain : records of fatal involvements characterized by many variables while NPTS : (National Personal T...

Music Taste Groups and Problem Behavior.

PubMed

Mulder, Juul; Bogt, Tom Ter; Raaijmakers, Quinten; Vollebergh, Wilma

2007-04-01

Internalizing and externalizing problems differ by musical tastes. A high school-based sample of 4159 adolescents, representative of Dutch youth aged 12 to 16, reported on their personal and social characteristics, music preferences and social-psychological functioning, measured with the Youth Self-Report (YSR). Cluster analysis on their music preferences revealed six taste groups: Middle-of-the-road (MOR) listeners, Urban fans, Exclusive Rock fans, Rock-Pop fans, Elitists, and Omnivores. A seventh group of musically Low-Involved youth was added. Multivariate analyses revealed that when gender, age, parenting, school, and peer variables were controlled, Omnivores and fans within the Exclusive Rock groups showed relatively high scores on internalizing YSR measures, and social, thought and attention problems. Omnivores, Exclusive Rock, Rock-Pop and Urban fans reported more externalizing problem behavior. Belonging to the MOR group that highly appreciates the most popular, chart-based pop music appears to buffer problem behavior. Music taste group membership uniquely explains variance in both internalizing and externalizing problem behavior.

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

"Heart trouble" and religious involvement among older white men and women.

PubMed

Thompson, Edward H; Killgore, Leslie; Connors, Heather

2009-09-01

Objective Few studies examine how older adults' health status affects spiritual and religious involvement. This study examined the effects of gender and poor cardiac health on older adults' ends, means, and quest religious motivations and frequency of private devotion. Method Longitudinal data (12 months between the T1 and T2 interviews) with 182 older adults sampled from a Northeast city were used to examine in a multivariate analysis of covariance whether gender and the existence of cardiac health problems at T1 affected older adults' spiritual and religious involvement at T2. Findings A gender and cardiac health condition interaction showed older men with heart trouble had more changes in religious involvement-they engaged in more religious doubt, prayed less, and were not as intrinsically oriented at T2. Discussion The findings strongly suggest that older men with heart trouble may maintain a masculine style and shun seeking divine help.

Robust tests for multivariate factorial designs under heteroscedasticity.

PubMed

Vallejo, Guillermo; Ato, Manuel

2012-06-01

The question of how to analyze several multivariate normal mean vectors when normality and covariance homogeneity assumptions are violated is considered in this article. For the two-way MANOVA layout, we address this problem adapting results presented by Brunner, Dette, and Munk (BDM; 1997) and Vallejo and Ato (modified Brown-Forsythe [MBF]; 2006) in the context of univariate factorial and split-plot designs and a multivariate version of the linear model (MLM) to accommodate heterogeneous data. Furthermore, we compare these procedures with the Welch-James (WJ) approximate degrees of freedom multivariate statistics based on ordinary least squares via Monte Carlo simulation. Our numerical studies show that of the methods evaluated, only the modified versions of the BDM and MBF procedures were robust to violations of underlying assumptions. The MLM approach was only occasionally liberal, and then by only a small amount, whereas the WJ procedure was often liberal if the interactive effects were involved in the design, particularly when the number of dependent variables increased and total sample size was small. On the other hand, it was also found that the MLM procedure was uniformly more powerful than its most direct competitors. The overall success rate was 22.4% for the BDM, 36.3% for the MBF, and 45.0% for the MLM.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms.

PubMed

Matero, Sanni; van Den Berg, Frans; Poutiainen, Sami; Rantanen, Jukka; Pajander, Jari

2013-05-01

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed. Copyright © 2013 Wiley Periodicals, Inc.

Multiple Imputation for Multivariate Missing-Data Problems: A Data Analyst's Perspective.

ERIC Educational Resources Information Center

Schafer, Joseph L.; Olsen, Maren K.

1998-01-01

The key ideas of multiple imputation for multivariate missing data problems are reviewed. Software programs available for this analysis are described, and their use is illustrated with data from the Adolescent Alcohol Prevention Trial (W. Hansen and J. Graham, 1991). (SLD)

Multivariable Hermite polynomials and phase-space dynamics

NASA Technical Reports Server (NTRS)

Dattoli, G.; Torre, Amalia; Lorenzutta, S.; Maino, G.; Chiccoli, C.

1994-01-01

The phase-space approach to classical and quantum systems demands for advanced analytical tools. Such an approach characterizes the evolution of a physical system through a set of variables, reducing to the canonically conjugate variables in the classical limit. It often happens that phase-space distributions can be written in terms of quadratic forms involving the above quoted variables. A significant analytical tool to treat these problems may come from the generalized many-variables Hermite polynomials, defined on quadratic forms in R(exp n). They form an orthonormal system in many dimensions and seem the natural tool to treat the harmonic oscillator dynamics in phase-space. In this contribution we discuss the properties of these polynomials and present some applications to physical problems.

Multivariate Analysis, Retrieval, and Storage System (MARS). Volume 6: MARS System - A Sample Problem (Gross Weight of Subsonic Transports)

NASA Technical Reports Server (NTRS)

Hague, D. S.; Woodbury, N. W.

1975-01-01

The Mars system is a tool for rapid prediction of aircraft or engine characteristics based on correlation-regression analysis of past designs stored in the data bases. An example of output obtained from the MARS system, which involves derivation of an expression for gross weight of subsonic transport aircraft in terms of nine independent variables is given. The need is illustrated for careful selection of correlation variables and for continual review of the resulting estimation equations. For Vol. 1, see N76-10089.

Dangers in Using Analysis of Covariance Procedures.

ERIC Educational Resources Information Center

Campbell, Kathleen T.

Problems associated with the use of analysis of covariance (ANCOVA) as a statistical control technique are explained. Three problems relate to the use of "OVA" methods (analysis of variance, analysis of covariance, multivariate analysis of variance, and multivariate analysis of covariance) in general. These are: (1) the wasting of information when…

Predictors of criminal justice involvement in severe mania.

PubMed

McCabe, Patrick J; Christopher, Paul P; Pinals, Debra A; Fisher, William H

2013-07-01

Criminal justice problems among those with bipolar disorder lead to disruption in social functioning, treatment, and recovery. Understanding factors that contribute to arrest during episodes of illness can help inform approaches to risk management and improve clinical care. Data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a longitudinal, nationally representative survey conducted in two waves were used to identify factors that predicted inter-wave criminal justice involvement during bipolar I manic episodes. Over 10% of respondents experienced legal involvement during their most severe manic episode. Risk was found in a range of historical, clinical, and contextual factors. Multivariate analyses suggest risk is particularly high for those who are unemployed, non-white, have past juvenile detention, have a prior arrest (while using substances or when manic), used an illicit drug in the past year, and whose mania is characterized by both social and occupational impairment. Legal problems were particularly elevated among those who lacked health insurance while experiencing both social and occupational impairment. Respondents did not include prisoners and hospital inpatients; criminal justice problems were only assessed with regard to the most severe manic episode. The particular array of factors that elevate the risk of legal involvement during manic episodes offers guidance when identifying prevention strategies and evaluating patients in clinical and forensic settings. Reducing such involvement will require that these issues be dealt with in the broader context of mental health and other services, which in turn necessitates providing adequate access to healthcare. Copyright © 2013 Elsevier B.V. All rights reserved.

The PIT-trap-A "model-free" bootstrap procedure for inference about regression models with discrete, multivariate responses.

PubMed

Warton, David I; Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods.

The PIT-trap—A “model-free” bootstrap procedure for inference about regression models with discrete, multivariate responses

PubMed Central

Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)—common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of “model-free bootstrap”, adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods. PMID:28738071

Reciprocal Influences Between Maternal Parenting and Child Adjustment in a High-risk Population: A Five-Year Cross-Lagged Analysis of Bidirectional Effects

PubMed Central

Barbot, Baptiste; Crossman, Elizabeth; Hunter, Scott R.; Grigorenko, Elena L.; Luthar, Suniya S.

2014-01-01

This study examines longitudinally the bidirectional influences between maternal parenting (behaviors and parenting stress) and mothers' perceptions of their children's adjustment, in a multivariate approach. Data was gathered from 361 low-income mothers (many with psychiatric diagnoses) reporting on their parenting behavior, parenting stress and their child's adjustment, in a two-wave longitudinal study over 5 years. Measurement models were developed to derive four broad parenting constructs (Involvement, Control, Rejection, and Stress) and three child adjustment constructs (Internalizing problems, Externalizing problems, and Social competence). After measurement invariance of these constructs was confirmed across relevant groups and over time, both measurement models were integrated in a single crossed-lagged regression analysis of latent constructs. Multiple reciprocal influence were observed between parenting and perceived child adjustment over time: Externalizing and internalizing problems in children were predicted by baseline maternal parenting behaviors, while child social competence was found to reduce parental stress and increase parental involvement and appropriate monitoring. These findings on the motherhood experience are discussed in light of recent research efforts to understand mother-child bi-directional influences, and their potential for practical applications. PMID:25089759

Early Numeracy Intervention: Does Quantity Discrimination Really Work?

ERIC Educational Resources Information Center

Hansmann, Paul

2013-01-01

Scope and Method of Study: The current study demonstrates that a taped problem intervention is an effective tool for increasing the early numeracy skill of QD. A taped problems intervention was used with two variations of the quantity discrimination measure (triangle and traditional). A 3x2 doubly multivariate multivariate analysis of variance was…

Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms

ERIC Educational Resources Information Center

Anderson, John R.

2012-01-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…

Functional Path Analysis as a Multivariate Technique in Developing a Theory of Participation in Adult Education.

ERIC Educational Resources Information Center

Martin, James L.

This paper reports on attempts by the author to construct a theoretical framework of adult education participation using a theory development process and the corresponding multivariate statistical techniques. Two problems are identified: the lack of theoretical framework in studying problems, and the limiting of statistical analysis to univariate…

Multivariable feedback design - Concepts for a classical/modern synthesis

NASA Technical Reports Server (NTRS)

Doyle, J. C.; Stein, G.

1981-01-01

This paper presents a practical design perspective on multivariable feedback control problems. It reviews the basic issue - feedback design in the face of uncertainties - and generalizes known single-input, single-output (SISO) statements and constraints of the design problem to multiinput, multioutput (MIMO) cases. Two major MIMO design approaches are then evaluated in the context of these results.

Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm.

PubMed

de Almeida, Valber Elias; de Araújo Gomes, Adriano; de Sousa Fernandes, David Douglas; Goicoechea, Héctor Casimiro; Galvão, Roberto Kawakami Harrop; Araújo, Mario Cesar Ugulino

2018-05-01

This paper proposes a new variable selection method for nonlinear multivariate calibration, combining the Successive Projections Algorithm for interval selection (iSPA) with the Kernel Partial Least Squares (Kernel-PLS) modelling technique. The proposed iSPA-Kernel-PLS algorithm is employed in a case study involving a Vis-NIR spectrometric dataset with complex nonlinear features. The analytical problem consists of determining Brix and sucrose content in samples from a sugar production system, on the basis of transflectance spectra. As compared to full-spectrum Kernel-PLS, the iSPA-Kernel-PLS models involve a smaller number of variables and display statistically significant superiority in terms of accuracy and/or bias in the predictions. Published by Elsevier B.V.

Analysis techniques for multivariate root loci. [a tool in linear control systems

NASA Technical Reports Server (NTRS)

Thompson, P. M.; Stein, G.; Laub, A. J.

1980-01-01

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Methods for presentation and display of multivariate data

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

[Construction and validation of a socio-environmental vulnerability index for monitoring and management of natural disasters in the state of Rio de Janeiro, Brazil].

PubMed

Guimarães, Raphael Mendonça; Mazoto, Maíra Lopes; Martins, Raphael Nascimento; do Carmo, Cleber Nascimento; Asmus, Carmen Ildes Fróes

2014-10-01

Floods account for approximately 40% of natural disasters that occur around the world and they are therefore considered a major public health problem. While floods constitute a global problem, data from the International Strategy for Disaster Reduction showed that almost all of the deaths or individuals affected are concentrated in developing countries. It is assumed that, although they have natural causes, the consequences of floods also involve social issues. To try to predict such vulnerability in the occurrence of natural disasters, a social and environmental index that shows the degree of vulnerability of a location was developed in this paper. This index was developed using multivariate analysis involving factor analysis and demographic, social and environmental variables. The index was applied in the municipalities of the state of Rio de Janeiro and compared with the official figures of the Civil Defense Unit. The results found suggest that the proposed index meets the expectation of predicting the vulnerability of the local population.

A numerical approach to controller design for the ACES facility

NASA Technical Reports Server (NTRS)

Frazier, W. Garth; Irwin, R. Dennis

1993-01-01

In recent years the employment of active control techniques for improving the performance of systems involving highly flexible structures has become a topic of considerable research interest. Most of these systems are quite complicated, using multiple actuators and sensors, and possessing high order models. The majority of analytical controller synthesis procedures capable of handling multivariable systems in a systematic way require considerable insight into the underlying mathematical theory to achieve a successful design. This insight is needed in selecting the proper weighting matrices or weighting functions to cast what is naturally a multiple constraint satisfaction problem into an unconstrained optimization problem. Although designers possessing considerable experience with these techniques have a feel for the proper choice of weights, others may spend a significant amount of time attempting to find an acceptable solution. Another disadvantage of such procedures is that the resulting controller has an order greater than or equal to that of the model used for the design. Of course, the order of these controllers can often be reduced, but again this requires a good understanding of the theory involved.

Advances in industrial biopharmaceutical batch process monitoring: Machine-learning methods for small data problems.

PubMed

Tulsyan, Aditya; Garvin, Christopher; Ündey, Cenk

2018-04-06

Biopharmaceutical manufacturing comprises of multiple distinct processing steps that require effective and efficient monitoring of many variables simultaneously in real-time. The state-of-the-art real-time multivariate statistical batch process monitoring (BPM) platforms have been in use in recent years to ensure comprehensive monitoring is in place as a complementary tool for continued process verification to detect weak signals. This article addresses a longstanding, industry-wide problem in BPM, referred to as the "Low-N" problem, wherein a product has a limited production history. The current best industrial practice to address the Low-N problem is to switch from a multivariate to a univariate BPM, until sufficient product history is available to build and deploy a multivariate BPM platform. Every batch run without a robust multivariate BPM platform poses risk of not detecting potential weak signals developing in the process that might have an impact on process and product performance. In this article, we propose an approach to solve the Low-N problem by generating an arbitrarily large number of in silico batches through a combination of hardware exploitation and machine-learning methods. To the best of authors' knowledge, this is the first article to provide a solution to the Low-N problem in biopharmaceutical manufacturing using machine-learning methods. Several industrial case studies from bulk drug substance manufacturing are presented to demonstrate the efficacy of the proposed approach for BPM under various Low-N scenarios. © 2018 Wiley Periodicals, Inc.

DSM-based problem gambling: increasing the odds of heavy drinking in a national sample of U.S. college athletes?

PubMed

Huang, Jiun-Hau; Jacobs, Durand F; Derevensky, Jeffrey L

2011-03-01

Despite previously found co-occurrence of youth gambling and alcohol use, their relationship has not been systematically explored in a national sample using DSM-based gambling measures and multivariate modeling, adjusted for potential confounders. This study aimed to empirically examine the prevalence patterns and odds of at-least-weekly alcohol use and heavy episodic drinking (HED) in relation to various levels of gambling severity in college athletes. Multivariate logistic regression analyses were performed on data from a national sample of 20,739 U.S. college athletes from the first National Collegiate Athletic Association national survey of gambling and health-risk behaviors. Prevalence of at-least-weekly alcohol use significantly increased as DSM-IV-based gambling severity increased, from non-gambling (24.5%) to non-problem gambling (43.7%) to sub-clinical gambling (58.5%) to problem gambling (67.6%). Multivariate results indicated that all levels of gambling were associated with significantly elevated risk of at-least-weekly HED, from non-problem (OR = 1.25) to sub-clinical (OR = 1.75) to problem gambling (OR = 3.22); the steep increase in the relative risk also suggested a possible quadratic relationship between gambling level and HED risk. Notably, adjusted odds ratios showed problem gambling had the strongest association with at-least-weekly HED, followed by marijuana (OR = 3.08) and cigarette use (OR = 2.64). Gender interactions and differences were also identified and assessed. In conclusion, attention should be paid to college athletes exhibiting gambling problems, especially considering their empirical multivariate associations with high-risk drinking; accordingly, screening for problem gambling is recommended. More research is warranted to elucidate the etiologic mechanisms of these associations. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multivariable optimization of an auto-thermal ammonia synthesis reactor using genetic algorithm

NASA Astrophysics Data System (ADS)

Anh-Nga, Nguyen T.; Tuan-Anh, Nguyen; Tien-Dung, Vu; Kim-Trung, Nguyen

2017-09-01

The ammonia synthesis system is an important chemical process used in the manufacture of fertilizers, chemicals, explosives, fibers, plastics, refrigeration. In the literature, many works approaching the modeling, simulation and optimization of an auto-thermal ammonia synthesis reactor can be found. However, they just focus on the optimization of the reactor length while keeping the others parameters constant. In this study, the other parameters are also considered in the optimization problem such as the temperature of feed gas enters the catalyst zone. The optimal problem requires the maximization of a multivariable objective function which subjects to a number of equality constraints involving the solution of coupled differential equations and also inequality constraints. The solution of an optimization problem can be found through, among others, deterministic or stochastic approaches. The stochastic methods, such as evolutionary algorithm (EA), which is based on natural phenomenon, can overcome the drawbacks such as the requirement of the derivatives of the objective function and/or constraints, or being not efficient in non-differentiable or discontinuous problems. Genetic algorithm (GA) which is a class of EA, exceptionally simple, robust at numerical optimization and is more likely to find a true global optimum. In this study, the genetic algorithm is employed to find the optimum profit of the process. The inequality constraints were treated using penalty method. The coupled differential equations system was solved using Runge-Kutta 4th order method. The results showed that the presented numerical method could be applied to model the ammonia synthesis reactor. The optimum economic profit obtained from this study are also compared to the results from the literature. It suggests that the process should be operated at higher temperature of feed gas in catalyst zone and the reactor length is slightly longer.

Schizotypy and Performance on an Insight Problem-Solving Task: The Contribution of Persecutory Ideation.

PubMed

Cosgrave, Jan; Haines, Ross; Golodetz, Stuart; Claridge, Gordon; Wulff, Katharina; van Heugten-van der Kloet, Dalena

2018-01-01

Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01-1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving.

Oral health matters for the nutritional status of older persons-A population-based study.

PubMed

Lindmark, Ulrika; Jansson, Henrik; Lannering, Christina; Johansson, Linda

2018-03-01

To explore the association between oral health and nutritional status in the context of daily care for older people. Oral problems often increase with age and affect a person's ability to chew and swallow. They might also influence the ability to maintain a satisfactory nutritional status. Oral health awareness is therefore of great importance in nursing care for older people. A retrospective cross-sectional study. Data from the Swedish quality register, Senior Alert, were used, including structured assessments of both oral and nutritional status using the Revised Oral Assessment Guide-Jönköping and the Mini Nutritional Assessment. In total, 1,156 persons (mean age: 82.8 ± 7.9) had both oral and nutritional assessments registered by the nursing staff in daily care. Approximately 29% of participants had moderate oral health problems. Another 12% had severe problems. Over 60% of the persons were considered at risk of malnutrition or were malnourished. There was a weak correlation between poor nutritional status and poor oral health, and approximately one-third of the persons who were at risk or malnourished had simultaneous oral problems. A multivariate logistic regression revealed that when problems involving voice and swallowing were present, there was also a greater possibility of being assessed as at risk of malnourishment or being malnourished. There is a relationship between oral health problems and nutritional status, indicating the importance of evaluating oral health status in older persons with nutritional problems. Nursing staff involved in care for older people should be aware of the importance of including regular oral health check-ups in their work. There is also a need for nursing staff members and oral health professionals to exchange knowledge. © 2017 John Wiley & Sons Ltd.

The influence of television and video game use on attention and school problems: a multivariate analysis with other risk factors controlled.

PubMed

Ferguson, Christopher J

2011-06-01

Research on youth mental health has increasingly indicated the importance of multivariate analyses of multiple risk factors for negative outcomes. Television and video game use have often been posited as potential contributors to attention problems, but previous studies have not always been well-controlled or used well-validated outcome measures. The current study examines the multivariate nature of risk factors for attention problems symptomatic of attention deficit hyperactivity disorder and poor school performance. A predominantly Hispanic population of 603 children (ages 10-14) and their parents/guardians responded to multiple behavioral measures. Outcome measures included parent and child reported attention problem behaviors on the Child Behavior Checklist (CBCL) as well as poor school performance as measured by grade point average (GPA). Results found that internal factors such as male gender, antisocial traits, family environment and anxiety best predicted attention problems. School performance was best predicted by family income. Television and video game use, whether total time spent using, or exposure to violent content specifically, did not predict attention problems or GPA. Television and video game use do not appear to be significant predictors of childhood attention problems. Intervention and prevention efforts may be better spent on other risk factors. Copyright © 2010 Elsevier Ltd. All rights reserved.

Control strategies for systems with limited actuators

NASA Technical Reports Server (NTRS)

Marcopoli, Vincent R.; Phillips, Stephen M.

1994-01-01

This work investigates the effects of actuator saturation in multi-input, multi-output (MIMO) control systems. The adverse system behavior introduced by the saturation nonlinearity is viewed here as resulting from two mechanisms: controller windup - a problem caused by the discrepancy between the limited actuator commands and the corresponding control signals, and directionality - the problem of how to use nonlimited actuators when a limited condition exists. The tracking mode and Hanus methods are two common strategies for dealing with the windup problem. It is seen that while these methods alleviate windup, performance problems remain due to plant directionality. Though high gain conventional antiwindup as well as more general linear methods have the potential to address both windup and directionality, no systematic design method for these schemes has emerged; most approaches used in practice are application driven. An alternative method of addressing the directionality problem is presented which involves the introduction of a control direction preserving nonlinearity to the Hanus antiwindup system. A nonlinearity is subsequently proposed which reduces the conservation inherent in the former direction-preserving approach, improving performance. The concept of multivariable sensitivity is seen to play a key role in the success of the new method.

Stress state estimation in multilayer support of vertical shafts, considering off-design cross-sectional deformation

NASA Astrophysics Data System (ADS)

Antsiferov, SV; Sammal, AS; Deev, PV

2018-03-01

To determine the stress-strain state of multilayer support of vertical shafts, including cross-sectional deformation of the tubing rings as against the design, the authors propose an analytical method based on the provision of the mechanics of underground structures and surrounding rock mass as the elements of an integrated deformable system. The method involves a rigorous solution of the corresponding problem of elasticity, obtained using the mathematical apparatus of the theory of analytic functions of a complex variable. The design method is implemented as a software program allowing multivariate applied computation. Examples of the calculation are given.

A Multivariate Model for the Meta-Analysis of Study Level Survival Data at Multiple Times

ERIC Educational Resources Information Center

Jackson, Dan; Rollins, Katie; Coughlin, Patrick

2014-01-01

Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and…

Paternal psychosocial characteristics and corporal punishment of their 3-year-old children.

PubMed

Lee, Shawna J; Perron, Brian E; Taylor, Catherine A; Guterman, Neil B

2011-01-01

This study uses data from 2,309 biological fathers who participated in the Fragile Families and Child Well-Being Study (FFCWS) to examine associations between psychosocial characteristics and levels of corporal punishment (CP) toward their 3-year-old children over the past month. Results indicate that 61% of the fathers reported no CP over the past month, 23% reported using CP once or twice, and 16% reported using CP a few times in the past month or more. In multivariate models controlling for important sociodemographic factors as well as characteristics of the child, fathers' parenting stress, major depression, heavy alcohol use, and drug use were significantly associated with greater use of CP, whereas involvement with the child and generalized anxiety disorder were not. Girls were less likely to be the recipient of CP than were boys, and child externalizing behavior problems but not internalizing behavior problems were associated with more CP.

An Alternative Method for Computing Mean and Covariance Matrix of Some Multivariate Distributions

ERIC Educational Resources Information Center

Radhakrishnan, R.; Choudhury, Askar

2009-01-01

Computing the mean and covariance matrix of some multivariate distributions, in particular, multivariate normal distribution and Wishart distribution are considered in this article. It involves a matrix transformation of the normal random vector into a random vector whose components are independent normal random variables, and then integrating…

Personality and Gambling Involvement: A Person-Centered Approach

PubMed Central

Savage, Jeanne E.; Slutske, Wendy S.; Martin, Nicholas G.

2014-01-01

Individual differences in personality are likely to play an important role in explaining the propensity to gamble. One of the potential roadblocks to elucidating the relation between personality and gambling may be inadequately accounting for the diversity of gambling activities. The goal of the present study was to provide a comprehensive and nuanced portrait of the relation between personality and gambling by taking a multivariate approach to the co-use of multiple gambling activities and employing a broad inventory of potentially-relevant personality dimensions. Participants were 4,669 individuals from a national Australian twin registry. Structured interviews including an extensive assessment of gambling behaviors were conducted, and personality questionnaires that included the tidimensional Personality Questionnaire, the Sensation Seeking Scale, and the Magical Ideation Scale were completed. A latent class analysis of past-year involvement in 10 different gambling activities was performed to classify the participants into five groups. Unique personality configurations characterized the three more gambling-involved latent classes. Low behavioral control in the context of high negative emotionality and magical thinking typified extensive, versatile gamblers at high risk of gambling problems. Average behavioral control in the context of high negative emotionality and magical thinking typified those who primarily gambled on non-strategic games of chance. Low behavioral control in the context of high positive emotionality and low magical ideation typified those who primarily gambled on strategic games of skill. This study illustrates the value of using a multivariate person-centered approach for characterizing the personality correlates of the multi-faceted phenomenon that is gambling. PMID:25134059

Personality and gambling involvement: a person-centered approach.

PubMed

Savage, Jeanne E; Slutske, Wendy S; Martin, Nicholas G

2014-12-01

Individual differences in personality are likely to play an important role in explaining the propensity to gamble. One of the potential roadblocks to elucidating the relation between personality and gambling may be inadequately accounting for the diversity of gambling activities. The goal of the present study was to provide a comprehensive and nuanced portrait of the relation between personality and gambling by taking a multivariate approach to the co-use of multiple gambling activities and employing a broad inventory of potentially relevant personality dimensions. Participants were 4,669 individuals from a national Australian twin registry. Structured interviews including an extensive assessment of gambling behaviors were conducted, and personality questionnaires that included the Multidimensional Personality Questionnaire, the Sensation Seeking Scale, and the Magical Ideation Scale were completed. A latent class analysis of past-year involvement in 10 different gambling activities was performed to classify the participants into 5 groups. Unique personality configurations characterized the 3 more gambling-involved latent classes: (a) low behavioral control in the context of high negative emotionality and magical thinking typified extensive, versatile gamblers at high risk of gambling problems; (b) average behavioral control in the context of high negative emotionality and magical thinking typified those who primarily gambled on non-strategic games of chance; (c) low behavioral control in the context of high positive emotionality and low magical ideation typified those who primarily gambled on strategic games of skill. This study illustrates the value of using a multivariate person-centered approach for characterizing the personality correlates of the multifaceted phenomenon that is gambling.

Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

PubMed

Yu, Tao; Wang, Yongtao; Zhang, Huizhen; Johnson, Caroline H; Jiang, Yiming; Li, Xiangjun; Wu, Zeming; Liu, Tian; Krausz, Kristopher W; Yu, Aiming; Gonzalez, Frank J; Huang, Min; Bi, Huichang

2016-06-01

Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

Localization of genes involved in the metabolic syndrome using multivariate linkage analysis.

PubMed

Olswold, Curtis; de Andrade, Mariza

2003-12-31

There are no well accepted criteria for the diagnosis of the metabolic syndrome. However, the metabolic syndrome is identified clinically by the presence of three or more of these five variables: larger waist circumference, higher triglyceride levels, lower HDL-cholesterol concentrations, hypertension, and impaired fasting glucose. We use sets of two or three variables, which are available in the Framingham Heart Study data set, to localize genes responsible for this syndrome using multivariate quantitative linkage analysis. This analysis demonstrates the applicability of using multivariate linkage analysis and how its use increases the power to detect linkage when genes are involved in the same disease mechanism.

SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation.

PubMed

Bayar, Belhassen; Bouaynaya, Nidhal; Shterenberg, Roman

2017-03-01

We consider a high-dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. The system is underdetermined as there are more parameters than samples. We show that the maximum likelihood approach with covariance estimation is senseless because the likelihood diverges. We subsequently propose a normalization of the likelihood function that guarantees convergence. We call this method small-sample multivariate regression with covariance (SMURC) estimation. We derive an optimization problem and its convex approximation to compute SMURC. Simulation results show that the proposed algorithm outperforms the regularized likelihood estimator with known covariance matrix and the sparse conditional Gaussian graphical model. We also apply SMURC to the inference of the wing-muscle gene network of the Drosophila melanogaster (fruit fly).

Improved multivariate polynomial factoring algorithm

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

Wang, P.S.

1978-10-01

A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timingmore » are included.« less

Psychosocial factors associated with suicidal ideation among young men exempted from compulsory military or civil service.

PubMed

Appelqvist-Schmidlechner, Kaija; Henriksson, Markus; Joukamaa, Matti; Parkkola, Kai; Upanne, Maila; Stengård, Eija

2011-12-01

The aim of this study was to identify factors associated with suicidal ideation among young men exempted from compulsory military or civil service in Finland. The study involved a total of 356 men exempted from military or civil service. The research data were collected using questionnaires and register data. One third of the young men exempted from compulsory military or civil service reported serious suicidal ideation. Of the men with serious suicidal ideation, one third had attempted suicide. Various childhood adversities and current stressful life events and problems were associated with suicidal ideation. Multivariate logistic regression analysis showed that the following factors were independently associated with suicidal ideation: maternal alcohol-related problems, changes in the family, discord with the boss over the past 12 months, and lack of social support. Accumulation of problems predicted suicidal ideation. Men exempted from compulsory military or civil service comprise an important target group in the prevention of suicide. In order to prevent suicidal behaviour among young men at risk, it is important to address the significance of social support and relationships, and likewise to be aware of early risk indicators such as maternal alcohol-related problems.

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

Steed, Chad A

Interactive data visualization leverages human visual perception and cognition to improve the accuracy and effectiveness of data analysis. When combined with automated data analytics, data visualization systems orchestrate the strengths of humans with the computational power of machines to solve problems neither approach can manage in isolation. In the intelligent transportation system domain, such systems are necessary to support decision making in large and complex data streams. In this chapter, we provide an introduction to several key topics related to the design of data visualization systems. In addition to an overview of key techniques and strategies, we will describe practicalmore » design principles. The chapter is concluded with a detailed case study involving the design of a multivariate visualization tool.« less

Application of multivariable search techniques to the optimization of airfoils in a low speed nonlinear inviscid flow field

NASA Technical Reports Server (NTRS)

Hague, D. S.; Merz, A. W.

1975-01-01

Multivariable search techniques are applied to a particular class of airfoil optimization problems. These are the maximization of lift and the minimization of disturbance pressure magnitude in an inviscid nonlinear flow field. A variety of multivariable search techniques contained in an existing nonlinear optimization code, AESOP, are applied to this design problem. These techniques include elementary single parameter perturbation methods, organized search such as steepest-descent, quadratic, and Davidon methods, randomized procedures, and a generalized search acceleration technique. Airfoil design variables are seven in number and define perturbations to the profile of an existing NACA airfoil. The relative efficiency of the techniques are compared. It is shown that elementary one parameter at a time and random techniques compare favorably with organized searches in the class of problems considered. It is also shown that significant reductions in disturbance pressure magnitude can be made while retaining reasonable lift coefficient values at low free stream Mach numbers.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Multivariate Density Estimation and Remote Sensing

NASA Technical Reports Server (NTRS)

Scott, D. W.

1983-01-01

Current efforts to develop methods and computer algorithms to effectively represent multivariate data commonly encountered in remote sensing applications are described. While this may involve scatter diagrams, multivariate representations of nonparametric probability density estimates are emphasized. The density function provides a useful graphical tool for looking at data and a useful theoretical tool for classification. This approach is called a thunderstorm data analysis.

Atmospheric Tracer Inverse Modeling Using Markov Chain Monte Carlo (MCMC)

NASA Astrophysics Data System (ADS)

Kasibhatla, P.

2004-12-01

In recent years, there has been an increasing emphasis on the use of Bayesian statistical estimation techniques to characterize the temporal and spatial variability of atmospheric trace gas sources and sinks. The applications have been varied in terms of the particular species of interest, as well as in terms of the spatial and temporal resolution of the estimated fluxes. However, one common characteristic has been the use of relatively simple statistical models for describing the measurement and chemical transport model error statistics and prior source statistics. For example, multivariate normal probability distribution functions (pdfs) are commonly used to model these quantities and inverse source estimates are derived for fixed values of pdf paramaters. While the advantage of this approach is that closed form analytical solutions for the a posteriori pdfs of interest are available, it is worth exploring Bayesian analysis approaches which allow for a more general treatment of error and prior source statistics. Here, we present an application of the Markov Chain Monte Carlo (MCMC) methodology to an atmospheric tracer inversion problem to demonstrate how more gereral statistical models for errors can be incorporated into the analysis in a relatively straightforward manner. The MCMC approach to Bayesian analysis, which has found wide application in a variety of fields, is a statistical simulation approach that involves computing moments of interest of the a posteriori pdf by efficiently sampling this pdf. The specific inverse problem that we focus on is the annual mean CO2 source/sink estimation problem considered by the TransCom3 project. TransCom3 was a collaborative effort involving various modeling groups and followed a common modeling and analysis protocoal. As such, this problem provides a convenient case study to demonstrate the applicability of the MCMC methodology to atmospheric tracer source/sink estimation problems.

Multivariate Analysis of Schools and Educational Policy.

ERIC Educational Resources Information Center

Kiesling, Herbert J.

This report describes a multivariate analysis technique that approaches the problems of educational production function analysis by (1) using comparable measures of output across large experiments, (2) accounting systematically for differences in socioeconomic background, and (3) treating the school as a complete system in which different…

Intervention on early-onset conduct problems as indicated prevention for substance use: A seven-year follow up.

PubMed

Romero, Estrella; Rodríguez, Concepción; Villar, Paula; Gómez-Fraguela, X Antón

2017-06-28

The aim of this study is to evaluate the long-term effects of a manualised program which intervenes on children with early-onset conduct problems, their families and teachers. The program evaluation involved 14 primary schools which were randomly assigned to the intervention (45 participating families) and control (30 families) conditions during 2007-2008. After a screening process which identified children with significant conduct problems both at home with their family and at school, the program was implemented in eight schools. Seven years later, 58 families (37 from the intervention group and 21 from the control group), with characteristics equivalent to those of the study's entire initial group, were contacted again. With measures administered to the children and their parents, comparisons through multivariate analyses of variance between intervention and control groups supported the program's efficacy in reducing both conduct problems and relations with antisocial peers. Furthermore, the program fostered social and communication skills. As regards drug use, the intervention group showed less favourable attitudes towards drugs, lower intention of drug use, lower frequency of tobacco use and lower intensity of alcohol use. These results support the usefulness of multicomponent programs for conduct problems as a way to prevent, in the long term, unfavourable developmental trajectories, where drug use is a key element.

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Two-sample tests and one-way MANOVA for multivariate biomarker data with nondetects.

PubMed

Thulin, M

2016-09-10

Testing whether the mean vector of a multivariate set of biomarkers differs between several populations is an increasingly common problem in medical research. Biomarker data is often left censored because some measurements fall below the laboratory's detection limit. We investigate how such censoring affects multivariate two-sample and one-way multivariate analysis of variance tests. Type I error rates, power and robustness to increasing censoring are studied, under both normality and non-normality. Parametric tests are found to perform better than non-parametric alternatives, indicating that the current recommendations for analysis of censored multivariate data may have to be revised. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

MULTIVARIATE RECEPTOR MODELS-CURRENT PRACTICE AND FUTURE TRENDS. (R826238)

EPA Science Inventory

Multivariate receptor models have been applied to the analysis of air quality data for sometime. However, solving the general mixture problem is important in several other fields. This paper looks at the panoply of these models with a view of identifying common challenges and ...

Additive genetic variation and evolvability of a multivariate trait can be increased by epistatic gene action.

PubMed

Griswold, Cortland K

2015-12-21

Epistatic gene action occurs when mutations or alleles interact to produce a phenotype. Theoretically and empirically it is of interest to know whether gene interactions can facilitate the evolution of diversity. In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits. The analysis involves a sexually reproducing and recombining population. Our results indicate that under stabilizing selection conditions a population with a mixed additive and epistatic genetic architecture can have greater multivariate additive genetic variation and evolvability than a population with a purely additive genetic architecture. That greater multivariate additive genetic variation can occur with epistasis is in contrast to previous theory that indicated univariate additive genetic variation is decreased with epistasis under stabilizing selection conditions. In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability. Our analysis involves linking the combinatorial nature of epistatic genetic effects to the ancestral graph structure of a population to provide insight into the consequences of epistasis on multivariate trait variation and evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Multivariate Solution of the Multivariate Ranking and Selection Problem

DTIC Science & Technology

1980-02-01

Taneja (1972)), a ’a for a vector of constants c (Krishnaiah and Rizvi (1966)), the generalized variance ( Gnanadesikan and Gupta (1970)), iegier (1976...Olk-in, I. and Sobel, M. (1977). Selecting and Ordering Populations: A New Statistical Methodology, John Wiley & Sons, Inc., New York. Gnanadesikan

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition

PubMed Central

Lv, Yong; Song, Gangbing

2018-01-01

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal. PMID:29659510

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.

PubMed

Yuan, Rui; Lv, Yong; Song, Gangbing

2018-04-16

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal.

A Forward Glimpse into Inverse Problems through a Geology Example

ERIC Educational Resources Information Center

Winkel, Brian J.

2012-01-01

This paper describes a forward approach to an inverse problem related to detecting the nature of geological substrata which makes use of optimization techniques in a multivariable calculus setting. The true nature of the related inverse problem is highlighted. (Contains 2 figures.)

Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis

ERIC Educational Resources Information Center

Ansari, Asim; Iyengar, Raghuram

2006-01-01

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

Working parents: what factors are involved in their ability to take time off from work when their children are sick?

PubMed

Heymann, S J; Toomey, S; Furstenberg, F

1999-08-01

A series of studies has demonstrated that sick children fare better when their parents are present. To examine working conditions that determine whether parents can spend time with and become involved in the care of their children when they are sick. Survey with a multivariate analysis of factors influencing parental care of sick children. Mixed-income urban working parents aged 26 to 29 years participating in the Baltimore Parenthood Study. Only 42% of working parents in our sample cared for their young children when they became sick. A multivariate logistic regression analysis was conducted to predict which parents stayed at home when their children were sick. Those parents who had either paid sick or vacation leave were 5.2 times as likely to care for their children themselves when they were sick. Of parents with less than a high school education, 17% received paid leave, compared with 57% of parents with a general equivalency diploma, 76% of parents with a high school diploma, and 92% of parents with more than a high school education (P<.001). The finding that many parents were unable to care for their sick children themselves is important for pediatric care. While low-income children are more likely to face marked health problems and to be in need of parental care, they are more likely to live in households in which parents lack paid leave and cannot afford to take unpaid leave.

A Multivariate Model of Physics Problem Solving

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Farley, John

2013-01-01

A model of expertise in physics problem solving was tested on undergraduate science, physics, and engineering majors enrolled in an introductory-level physics course. Structural equation modeling was used to test hypothesized relationships among variables linked to expertise in physics problem solving including motivation, metacognitive planning,…

Independent Correlates of Reported Gambling Problems amongst Indigenous Australians

ERIC Educational Resources Information Center

Stevens, Matthew; Young, Martin

2010-01-01

To identify independent correlates of reported gambling problems amongst the Indigenous population of Australia. A cross-sectional design was applied to a nationally representative sample of the Indigenous population. Estimates of reported gambling problems are presented by remoteness and jurisdiction. Multivariable logistic regression was used to…

On the stabilizability of multivariable systems by minimum order compensation

NASA Technical Reports Server (NTRS)

Byrnes, C. I.; Anderson, B. D. O.

1983-01-01

In this paper, a derivation is provided of the necessary condition, mp equal to or greater than n, for stabilizability by constant gain feedback of the generic degree n, p x m system. This follows from another of the main results, which asserts that generic stabilizability is equivalent to generic solvability of a deadbeat control problem, provided mp equal to or less than n. Taken together, these conclusions make it possible to make some sharp statements concerning minimum order stabilization. The techniques are primarily drawn from decision algebra and classical algebraic geometry and have additional consequences for problems of stabilizability and pole-assignability. Among these are the decidability (by a Sturm test) of the equivalence of generic pole-assignability and generic stabilizability, the semi-algebraic nature of the minimum order, q, of a stabilizing compensator, and the nonexistence of formulae involving rational operations and extraction of square roots for pole-assigning gains when they exist, answering in the negative a question raised by Anderson, Bose, and Jury (1975).

The Multivariate Roles of Family Instability and Interparental Conflict in Predicting Children's Representations of Insecurity in the Family System and Early School Adjustment Problems.

PubMed

Coe, Jesse L; Davies, Patrick T; Sturge-Apple, Melissa L

2017-02-01

This study examined the moderating role of family instability in relations involving destructive interparental conflict, children's internal representations of insecurity in the family system, and their early school maladjustment. Two hundred forty-three preschool children (M age = 4.60 years; 56 % girls) and their families participated in this multi-method (i.e., observations, structured interview, surveys) multi-informant (i.e., observer, parent, teacher), longitudinal study. Findings indicated that the mediational role of children's insecure family representations in the pathway between destructive interparental conflict and children's adjustment problems varied significantly depending on the level of family instability. Interparental conflict was specifically associated with insecure family representations only under conditions of low family instability. In supporting the role of family instability as a vulnerable-stable risk factor, follow up analyses revealed that children's concerns about security in the family were uniformly high under conditions of heightened instability regardless of their level of exposure to interparental conflict.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Propulsion Controls, 1979. [air breathing engine control

NASA Technical Reports Server (NTRS)

1980-01-01

The state of the art of multivariable engine control is examined in order to determine future needs and problem areas and to establish the appropriate roles of government, industries, and universities in addressing these problems.

Integrating Supplementary Application-Based Tutorials in the Multivariable Calculus Course

ERIC Educational Resources Information Center

Verner, I. M.; Aroshas, S.; Berman, A.

2008-01-01

This article presents a study in which applications were integrated in the Multivariable Calculus course at the Technion in the framework of supplementary tutorials. The purpose of the study was to test the opportunity of extending the conventional curriculum by optional applied problem-solving activities and get initial evidence on the possible…

Enhancing Student Writing and Computer Programming with LATEX and MATLAB in Multivariable Calculus

ERIC Educational Resources Information Center

Sullivan, Eric; Melvin, Timothy

2016-01-01

Written communication and computer programming are foundational components of an undergraduate degree in the mathematical sciences. All lower-division mathematics courses at our institution are paired with computer-based writing, coding, and problem-solving activities. In multivariable calculus we utilize MATLAB and LATEX to have students explore…

Detection of Problem Gambler Subgroups Using Recursive Partitioning

ERIC Educational Resources Information Center

Markham, Francis; Young, Martin; Doran, Bruce

2013-01-01

The multivariate socio-demographic risk factors for problem gambling have been well documented. While this body of research is valuable in determining risk factors aggregated across various populations, the majority of studies tend not to specifically identify particular subgroups of problem gamblers based on the interaction between variables. The…

Anxiety, Sensory Over-Responsivity, and Gastrointestinal Problems in Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Mazurek, Micah O.; Vasa, Roma A.; Kalb, Luther G.; Kanne, Stephen M.; Rosenberg, Daniel; Keefer, Amy; Murray, Donna S.; Freedman, Brian; Lowery, Lea Ann

2013-01-01

Children with autism spectrum disorders (ASD) experience high rates of anxiety, sensory processing problems, and gastrointestinal (GI) problems; however, the associations among these symptoms in children with ASD have not been previously examined. The current study examined bivariate and multivariate relations among anxiety, sensory…

Temporal Trends and Changing Racial/ethnic Disparities in Alcohol Problems: Results from the 2000 to 2010 National Alcohol Surveys.

PubMed

Zemore, Sarah E; Karriker-Jaffe, Katherine J; Mulia, Nina

2013-09-28

Economic conditions and drinking norms have been in considerable flux over the past 10 years. Accordingly, research is needed to evaluate both overall trends in alcohol problems during this period and whether changes within racial/ethnic groups have affected racial/ethnic disparities. We used 3 cross-sectional waves of National Alcohol Survey data (2000, 2005, and 2010) to examine a) temporal trends in alcohol dependence and consequences overall and by race/ethnicity, and b) the effects of temporal changes on racial/ethnic disparities. Analyses involved bivariate tests and multivariate negative binomial regressions testing the effects of race/ethnicity, survey year, and their interaction on problem measures. Both women and men overall showed significant increases in dependence symptoms in 2010 (vs. 2000); women also reported increases in alcohol-related consequences in 2010 (vs. 2000). (Problem rates were equivalent across 2005 and 2000.) However, increases in problems were most dramatic among Whites, and dependence symptoms actually decreased among Latinos of both genders in 2010. Consequently, the long-standing disparity in dependence between Latino and White men was substantially reduced in 2010. Post-hoc analyses suggested that changes in drinking norms at least partially drove increased problem rates among Whites. Results constitute an important contribution to the literature on racial/ethnic disparities in alcohol problems. Findings are not inconsistent with the macroeconomic literature suggesting increases in alcohol problems during economic recession, but the pattern of effects across race/ethnicity and findings regarding norms together suggest, at the least, a revised understanding of how recessions affect drinking patterns and problems.

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

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

Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

The Neurodevelopmental Basis of Math Anxiety

PubMed Central

Young, Christina B.; Wu, Sarah S.; Menon, Vinod

2012-01-01

Math anxiety is a negative emotional reaction to situations involving mathematical problem solving. Math anxiety has a detrimental impact on an individual’s long-term professional success, but its neurodevelopmental origins are unknown. In a functional MRI study on 7- to 9-year-old children, we showed that math anxiety was associated with hyperactivity in right amygdala regions that are important for processing negative emotions. In addition, we found that math anxiety was associated with reduced activity in posterior parietal and dorsolateral prefrontal cortex regions involved in mathematical reasoning. Multivariate classification analysis revealed distinct multivoxel activity patterns, which were independent of overall activation levels in the right amygdala. Furthermore, effective connectivity between the amygdala and ventromedial prefrontal cortex regions that regulate negative emotions was elevated in children with math anxiety. These effects were specific to math anxiety and unrelated to general anxiety, intelligence, working memory, or reading ability. Our study identified the neural correlates of math anxiety for the first time, and our findings have significant implications for its early identification and treatment. PMID:22434239

The neurodevelopmental basis of math anxiety.

PubMed

Young, Christina B; Wu, Sarah S; Menon, Vinod

2012-05-01

Math anxiety is a negative emotional reaction to situations involving mathematical problem solving. Math anxiety has a detrimental impact on an individual's long-term professional success, but its neurodevelopmental origins are unknown. In a functional MRI study on 7- to 9-year-old children, we showed that math anxiety was associated with hyperactivity in right amygdala regions that are important for processing negative emotions. In addition, we found that math anxiety was associated with reduced activity in posterior parietal and dorsolateral prefrontal cortex regions involved in mathematical reasoning. Multivariate classification analysis revealed distinct multivoxel activity patterns, which were independent of overall activation levels in the right amygdala. Furthermore, effective connectivity between the amygdala and ventromedial prefrontal cortex regions that regulate negative emotions was elevated in children with math anxiety. These effects were specific to math anxiety and unrelated to general anxiety, intelligence, working memory, or reading ability. Our study identified the neural correlates of math anxiety for the first time, and our findings have significant implications for its early identification and treatment.

Calculus Student Descending a Staircase.

ERIC Educational Resources Information Center

Mueller, William

1999-01-01

Common student attitudes toward reform methods are conveyed through the thoughts of a student leaving a multivariable calculus exam and musings range over textbooks, homework, workload, group work, writing, noncomputational problems, instructional problems, instructional styles, and classroom activities. (Author/ASK)

Mental health problems in teens investigated by U.S. child welfare agencies.

PubMed

Heneghan, Amy; Stein, Ruth E K; Hurlburt, Michael S; Zhang, Jinjin; Rolls-Reutz, Jennifer; Fisher, Emily; Landsverk, John; Horwitz, Sarah McCue

2013-05-01

To examine prevalence and correlates of five mental health (MH) problems among 12-17.5 year olds investigated by child welfare. Data from the National Survey on Child and Adolescent Well-being (NSCAW II) were analyzed to examine depression, anxiety, substance use/abuse, suicidality, and attention deficit hyperactivity disorder (ADHD) as reported by teens and their caregivers. In a sample of 815 adolescents, prevalence for each MH problem and correlates (e.g., age, placement location) were identified using bivariate and multivariable logistic analyses. After investigation for maltreatment, 42.7% of teens reported at least one MH problem, regardless of placement. Nine percent reported depression, 13.9% reported suicidality, 23% had substance use/abuse, 13.5% reported anxiety, and 18.6% had ADHD. Of 332 teens with any MH problem, 52.1% reported only one problem, 28.3% had two problems, and 19.6% had ≥ three problems. Teens with prior out-of-home placement had odds 2.29 times higher of reporting a MH problem and odds 2.12 times higher of reporting substance use/abuse. Males were significantly less likely to report depression. Older teens were more likely to report substance use/abuse. Black teens were significantly less likely to report suicidality and ADHD and almost half as likely to report anxiety. Teens with a chronic health condition and teens whose caregiver reported depression had more than twice the odds of reporting anxiety. This study highlights high rates of MH problems in teens of all ages and placement locations and suggests that all teens involved with child welfare should be screened for MH problems, regardless of initial placement status. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

The Statistical Consulting Center for Astronomy (SCCA)

NASA Technical Reports Server (NTRS)

Akritas, Michael

2001-01-01

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to scientists both within and outside of astronomy. The most popular sections are multivariate techniques, image analysis, and time series analysis. Hundreds of copies of the ASURV, SLOPES and CENS-TAU codes developed by SCCA scientists were also downloaded from the StatCodes site. In addition to formal SCCA duties, SCCA scientists continued a variety of related activities in astrostatistics, including refereeing of statistically oriented papers submitted to the Astrophysical Journal, talks in meetings including Feigelson's talk to science journalists entitled "The reemergence of astrostatistics" at the American Association for the Advancement of Science meeting, and published papers of astrostatistical content.

Social capital in settings with a high concentration of road traffic injuries. The case of Cuernavaca, Mexico.

PubMed

Inclán, Cristina; Hijar, Martha; Tovar, Victor

2005-11-01

There exists a differential ability within local communities to maintain effective social controls to prevent road traffic injuries (RTIs) in high risks areas. In 2002 we conducted a cross-sectional study in Cuernavaca, Mexico which incorporated 339 adults living in three areas which were characterized by high RTI concentrations. Multivariate analyses demonstrated that even when participants perceived RTIs as a local problem, they expressed no expectations that community members would exert social control through their involvement in local issues and law adherence. The study revealed four key conclusions regarding the association between the low levels of social capital and RTIs: (a) public roads are used solely for transportation, are not viewed as a communal space, and consequently reciprocity is not viewed as a relevant way of controlling behaviors in public places; (b) "strong immediate personal networks" bring about a lack of reciprocity between those sharing the public space which generates uncooperative behavior; (c) high levels of residential instability hinders the identification of common problems; (d) when there exists a low level of civic commitment and a scarcity of social resources directed towards the problem, the possibilities of social control over RTIs are low.

The degree of circumferential tumour involvement as a prognostic factor in oesophageal cancer.

PubMed

Sillah, Karim; Pritchard, Susan A; Watkins, Gillian R; McShane, James; West, Catharine M; Page, Richard; Welch, Ian M

2009-08-01

Tumour length is an adverse prognostic factor in oesophageal cancer. However, the prognostic role of the degree of oesophageal circumference (DOC) involved by tumour with or without resection margin invasion is not clear. This work assessed the relationship between DOC involved by tumour, clinico-pathological variables and prognosis. The clinico-pathological details of 320 patients who underwent potentially curative oesophagogastrectomy for cancer between 1994 and 2007 were analysed. The DOC involved with tumour measured macroscopically on the resected specimen was classified as small (<2.5 cm, n = 115), large (> or = 2.5 cm, n = 144) or circumferential (i.e. involving the whole circumference, n = 61). Univariate and multivariate survival analyses were carried out. The DOC with tumour was higher in ulcerating tumours than stenosing or polypoidal types (p = 0.017). Tumour length, T-stage, neoadjuvant chemotherapy and vascular invasion were independently associated with DOC with tumour on multivariate analysis (p < 0.05 for all). DOC > or = 2.5 cm was an adverse prognostic factor in univariate analysis (p = 0.002) with a hazard ratio of 1.52 [95% CI 1.13-2.04] compared with those <2.5 cm. Circumferential tumours had a similar prognosis to tumours > or = 2.5 cm (p = 0.60). The prognostic significance of DOC with tumour was lost in multivariate analysis where the factors retaining independence were patient age, T-stage, lymph node metastasis, vascular invasion and positive resection margins. However, when patients were stratified by use of neoadjuvant chemotherapy (n = 121), the DOC with tumour retained prognostic significance on multivariate analysis in the 199 patients who did not undergo neoadjuvant chemotherapy (p = 0.04). The DOC with tumour appears to provide prognostic information in oesophageal cancer surgery, especially in patients who do not undergo preoperative chemotherapy.

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing disease resistance data

USDA-ARS?s Scientific Manuscript database

The mixed linear model (MLM) is currently among the most advanced and flexible statistical modeling techniques and its use in tackling problems in plant pathology has begun surfacing in the literature. The longitudinal MLM is a multivariate extension that handles repeatedly measured data, such as r...

Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance

ERIC Educational Resources Information Center

Finch, W. Holmes

2016-01-01

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…

Multivariate Generalizations of Student's t-Distribution. ONR Technical Report. [Biometric Lab Report No. 90-3.

ERIC Educational Resources Information Center

Gibbons, Robert D.; And Others

In the process of developing a conditionally-dependent item response theory (IRT) model, the problem arose of modeling an underlying multivariate normal (MVN) response process with general correlation among the items. Without the assumption of conditional independence, for which the underlying MVN cdf takes on comparatively simple forms and can be…

Epidemiology of pediatric burns and future prevention strategies-a study of 475 patients from a high-volume burn center in North India.

PubMed

Dhopte, Amol; Tiwari, V K; Patel, Pankaj; Bamal, Rahul

2017-01-01

Pediatric burns have a long-term social impact. This is more apparent in a developing country such as India, where their incidence and morbidity are high. The aim of this study was to provide recent prospective epidemiological data on pediatric burns in India and to suggest future preventive strategies. Children up to 18 years old admitted to the Department of Burns, Plastic & Maxillofacial Surgery, VMMC & Safdarjung Hospital, New Delhi, between January and December 2014 were included in the study. Data regarding age, sex, etiology, total body surface area (TBSA), circumstances of injury, and clinical assessment were collected. The Mann-Whitney test or Kruskal-Wallis test or ANOVA was used to compare involved TBSA among various cohort groups accordingly. Univariate and multivariate linear regression analyses were used to determine the predictors of TBSA. There were a total of 475 patients involved in the study, including seven suicidal burns, all of whom were females with a mean age greater than the cohort average. Age, type of burns, mode of injury, presence or absence of inhalation injury, gender, and time of year (quarter) for admission were found to independently affect the TBSA involved. Electrical burns also formed an important number of presenting burn patients, mainly involving teenagers. Several societal issues have come forth, e.g., child marriage, child labor, and likely psychological problems among female children as suggested by a high incidence of suicidal burns. This study also highlights several issues such as overcrowding, lack of awareness, dangerous cooking practices, and improper use of kerosene oil. There is an emergent need to recognize the problems, formulate strategies, spread awareness, and ban or replace hazardous substances responsible for most burn accidents.

Design Research on Inquiry-Based Multivariable Calculus: Focusing on Students' Argumentation and Instructional Design

ERIC Educational Resources Information Center

Kwon, Oh Nam; Bae, Younggon; Oh, Kuk Hwan

2015-01-01

In this study, researchers design and implement an inquiry based multivariable calculus course in a university which aims at enhancing students' argumentation in rich mathematical discussions. This research aims to understand the characteristics of students' argumentation in activities involving proof constructions through mathematical…

Child, caregiver, and family characteristics associated with emergency department use by children who remain at home after a child protective services investigation

PubMed Central

Hurlburt, Michael S.; Leslie, Laurel K.; Zhang, Jinjin; Horwitz, Sarah McCue

2012-01-01

Objectives To examine emergency department (ED) use among children involved with child protective services (CPS) in the U.S. but who remain at home, and to determine if ED use is related to child, caregiver and family characteristics as well as receipt of CPS services. Method We analyzed data on 4,001 children in the National Survey of Child and Adolescent Well-being. Multivariate models compared rates of ED use for whether the family received CPS services or did not receive CPS services as well as child characteristics, caregiver characteristics and caregiver/family psychological variables. Results ED use among children who remained at home receiving CPS services was similar to that of children who did not receive CPS services (35.6% and 37.4%, respectively). In multivariate modeling, children with families who received CPS services, children six years or older, and children without a chronic health problem were less likely to use the ED. Children who remained at home in families identified with numerous stressors and, therefore, likely at high risk for future abuse and neglect were 1.73 times (95% CI, 1.14–2.63) more likely to have repeat ED use than children in low risk families. Conclusion Children who remain at home after a CPS evaluation are at high risk for ED use. Future research should focus on the health problems that precipitate an ED visit as well as the relationship between primary care and ED use. PMID:22265905

Minimization of transmission cost in decentralized control systems

NASA Technical Reports Server (NTRS)

Wang, S.-H.; Davison, E. J.

1978-01-01

This paper considers the problem of stabilizing a linear time-invariant multivariable system by using local feedback controllers and some limited information exchange among local stations. The problem of achieving a given degree of stability with minimum transmission cost is solved.

Perceived Need and Receipt of Behavioral Health Services at Drop-In Centers among Homeless Youth.

PubMed

Pedersen, Eric R; Tucker, Joan S; Klein, David J; Parast, Layla

2018-06-03

Homeless youth are a population in need of housing assistance and case management, as well as services to address behavioral health problems. This study examines youth's perceived need for and receipt of services through drop-in centers. Surveys of 273 homeless youth. Cross-sectional. Descriptive analyses with bivariate and multivariable regression models. About one-third to half of the sample met criteria for behavioral health problems, yet half or less of those meeting criteria reported a need for services targeting the problems. Most youth who perceived a need for services received relevant services through a drop-in center, with the exception of care for substance use problems. Youth with behavioral health problems were more likely to perceive a need for services related to housing and case management than those addressing behavioral health problems more directly. Multivariable regression analyses indicated that the factors most strongly associated with perceived need for services were not behavioral health problems, but rather race/ethnicity, traveler status, trouble meeting basic needs, delinquency, abuse/victimization experiences, and trading sex. Findings can help to develop outreach and intervention efforts to reach homeless youth and help promote the use of behavioral health services. © Health Research and Educational Trust.

Association Between Perceived Discrimination and Racial/Ethnic Disparities in Problem Behaviors Among Preadolescent Youths

PubMed Central

Elliott, Marc N.; Kanouse, David E.; Klein, David J.; Davies, Susan L.; Cuccaro, Paula M.; Banspach, Stephen W.; Peskin, Melissa F.; Schuster, Mark A.

2013-01-01

Objectives. We examined the contribution of perceived racial/ethnic discrimination to disparities in problem behaviors among preadolescent Black, Latino, and White youths. Methods. We used cross-sectional data from Healthy Passages, a 3-community study of 5119 fifth graders and their parents from August 2004 through September 2006 in Birmingham, Alabama; Los Angeles County, California; and Houston, Texas. We used multivariate regressions to examine the relationships of perceived racial/ethnic discrimination and race/ethnicity to problem behaviors. We used values from these regressions to calculate the percentage of disparities in problem behaviors associated with the discrimination effect. Results. In multivariate models, perceived discrimination was associated with greater problem behaviors among Black and Latino youths. Compared with Whites, Blacks were significantly more likely to report problem behaviors, whereas Latinos were significantly less likely (a “reverse disparity”). When we set Blacks’ and Latinos’ discrimination experiences to zero, the adjusted disparity between Blacks and Whites was reduced by an estimated one third to two thirds; the reverse adjusted disparity favoring Latinos widened by about one fifth to one half. Conclusions. Eliminating discrimination could considerably reduce mental health issues, including problem behaviors, among Black and Latino youths. PMID:23597387

Input-output oriented computation algorithms for the control of large flexible structures

NASA Technical Reports Server (NTRS)

Minto, K. D.

1989-01-01

An overview is given of work in progress aimed at developing computational algorithms addressing two important aspects in the control of large flexible space structures; namely, the selection and placement of sensors and actuators, and the resulting multivariable control law design problem. The issue of sensor/actuator set selection is particularly crucial to obtaining a satisfactory control design, as clearly a poor choice will inherently limit the degree to which good control can be achieved. With regard to control law design, the researchers are driven by concerns stemming from the practical issues associated with eventual implementation of multivariable control laws, such as reliability, limit protection, multimode operation, sampling rate selection, processor throughput, etc. Naturally, the burden imposed by dealing with these aspects of the problem can be reduced by ensuring that the complexity of the compensator is minimized. Our approach to these problems is based on extensions to input/output oriented techniques that have proven useful in the design of multivariable control systems for aircraft engines. In particular, researchers are exploring the use of relative gain analysis and the condition number as a means of quantifying the process of sensor/actuator selection and placement for shape control of a large space platform.

G/SPLINES: A hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) algorithm with Holland's genetic algorithm

NASA Technical Reports Server (NTRS)

Rogers, David

1991-01-01

G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.

On Some Multiple Decision Problems

DTIC Science & Technology

1976-08-01

parameter space. Some recent results in the area of subset selection formulation are Gnanadesikan and Gupta [28], Gupta and Studden [43], Gupta and...York, pp. 363-376. [27) Gnanadesikan , M. (1966). Some Selection and Ranking Procedures for Multivariate Normal Populations. Ph.D. Thesis. Dept. of...Statist., Purdue Univ., West Lafayette, Indiana 47907. [28) Gnanadesikan , M. and Gupta, S. S. (1970). Selection procedures for multivariate normal

Confocal Raman imaging and chemometrics applied to solve forensic document examination involving crossed lines and obliteration cases by a depth profiling study.

PubMed

Borba, Flávia de Souza Lins; Jawhari, Tariq; Saldanha Honorato, Ricardo; de Juan, Anna

2017-03-27

This article describes a non-destructive analytical method developed to solve forensic document examination problems involving crossed lines and obliteration. Different strategies combining confocal Raman imaging and multivariate curve resolution-alternating least squares (MCR-ALS) are presented. Multilayer images were acquired at subsequent depth layers into the samples. It is the first time that MCR-ALS is applied to multilayer images for forensic purposes. In this context, this method provides a single set of pure spectral ink signatures and related distribution maps for all layers examined from the sole information in the raw measurement. Four cases were investigated, namely, two concerning crossed lines with different degrees of ink similarity and two related to obliteration, where previous or no knowledge about the identity of the obliterated ink was available. In the crossing line scenario, MCR-ALS analysis revealed the ink nature and the chronological order in which strokes were drawn. For obliteration cases, results making active use of information about the identity of the obliterated ink in the chemometric analysis were of similar quality as those where the identity of the obliterated ink was unknown. In all obliteration scenarios, the identity of inks and the obliterated text were satisfactorily recovered. The analytical methodology proposed is of general use for analytical forensic document examination problems, and considers different degrees of complexity and prior available information. Besides, the strategies of data analysis proposed can be applicable to any other kind of problem in which multilayer Raman images from multicomponent systems have to be interpreted.

A Simpli ed, General Approach to Simulating from Multivariate Copula Functions

Treesearch

Barry Goodwin

2012-01-01

Copulas have become an important analytic tool for characterizing multivariate distributions and dependence. One is often interested in simulating data from copula estimates. The process can be analytically and computationally complex and usually involves steps that are unique to a given parametric copula. We describe an alternative approach that uses \\probability{...

Model transformations for state-space self-tuning control of multivariable stochastic systems

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Bao, Yuan L.; Coleman, Norman P.

1988-01-01

The design of self-tuning controllers for multivariable stochastic systems is considered analytically. A long-division technique for finding the similarity transformation matrix and transforming the estimated left MFD to the right MFD is developed; the derivation is given in detail, and the procedures involved are briefly characterized.

Factors associated with disordered gambling in Finland

PubMed Central

2013-01-01

Background The purpose of this study was to compare the socio-demographic characteristics of non-problem gamblers, problem gamblers and pathological gamblers, to investigate the association between gambling related factors and perceived health and well-being among the three subgroups of gamblers, and to analyse simultaneously socio-demographic characteristics, gambling related factors and perceived health and well-being and the severity of disordered gambling (problem gamblers and pathological gamblers). Methods The data were collected through a nationwide telephone survey in 2011. Participants were selected through a random population sample of 15-74-year-old Finns. From that sample, persons with any past-year gambling involvement (N = 3451) were selected for a subsample for the descriptive and inferential analysis in the present paper. Gambling was assessed using the South Oaks Gambling Screen. Statistical significance was determined by chi-squared tests. The odds ratio and effect size were computed by using multivariate-adjusted multinomial logistic regression analysis. Results The most significant socio-demographic characteristics (male gender, young age, education ≤12 years), gambling related factors (slot machine gambling, internet gambling) and perceived health and well-being (feeling lonely, smoking daily, risky alcohol consumption, mental health problems) explained 22.9 per cent of the variation in the severity of disordered gambling. Conclusion Male gender and loneliness were found to be associated with problem gambling in particular, along with smoking and risky alcohol consumption. Mental health problems and risky alcohol consumption were associated with pathological gambling. These identified associations between disordered gambling, mental health problems and risky alcohol consumption should be taken into consideration when implementing screenings of disordered gambling. PMID:23816162

Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity.

PubMed

Lizier, Joseph T; Heinzle, Jakob; Horstmann, Annette; Haynes, John-Dylan; Prokopenko, Mikhail

2011-02-01

The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between brain regions, and how that structure changes according to behavioral conditions. This method is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only directional and non-linear relationships, but also collective interactions. Importantly, the method is able to estimate multivariate information measures with only relatively little data. We demonstrate the method to analyze functional magnetic resonance imaging time series to establish the directed information structure between brain regions involved in a visuo-motor tracking task. Importantly, this results in a tiered structure, with known movement planning regions driving visual and motor control regions. Also, we examine the changes in this structure as the difficulty of the tracking task is increased. We find that task difficulty modulates the coupling strength between regions of a cortical network involved in movement planning and between motor cortex and the cerebellum which is involved in the fine-tuning of motor control. It is likely these methods will find utility in identifying interregional structure (and experimentally induced changes in this structure) in other cognitive tasks and data modalities.

FBST for Cointegration Problems

NASA Astrophysics Data System (ADS)

Diniz, M.; Pereira, C. A. B.; Stern, J. M.

2008-11-01

In order to estimate causal relations, the time series econometrics has to be aware of spurious correlation, a problem first mentioned by Yule [21]. To solve the problem, one can work with differenced series or use multivariate models like VAR or VEC models. In this case, the analysed series are going to present a long run relation i.e. a cointegration relation. Even though the Bayesian literature about inference on VAR/VEC models is quite advanced, Bauwens et al. [2] highlight that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results." This paper presents the Full Bayesian Significance Test applied to cointegration rank selection tests in multivariate (VAR/VEC) time series models and shows how to implement it using available in the literature and simulated data sets. A standard non-informative prior is assumed.

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

Robust Multivariable Optimization and Performance Simulation for ASIC Design

NASA Technical Reports Server (NTRS)

DuMonthier, Jeffrey; Suarez, George

2013-01-01

Application-specific-integrated-circuit (ASIC) design for space applications involves multiple challenges of maximizing performance, minimizing power, and ensuring reliable operation in extreme environments. This is a complex multidimensional optimization problem, which must be solved early in the development cycle of a system due to the time required for testing and qualification severely limiting opportunities to modify and iterate. Manual design techniques, which generally involve simulation at one or a small number of corners with a very limited set of simultaneously variable parameters in order to make the problem tractable, are inefficient and not guaranteed to achieve the best possible results within the performance envelope defined by the process and environmental requirements. What is required is a means to automate design parameter variation, allow the designer to specify operational constraints and performance goals, and to analyze the results in a way that facilitates identifying the tradeoffs defining the performance envelope over the full set of process and environmental corner cases. The system developed by the Mixed Signal ASIC Group (MSAG) at the Goddard Space Flight Center is implemented as a framework of software modules, templates, and function libraries. It integrates CAD tools and a mathematical computing environment, and can be customized for new circuit designs with only a modest amount of effort as most common tasks are already encapsulated. Customization is required for simulation test benches to determine performance metrics and for cost function computation.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Detection of Equid herpesvirus type 2 and 5 DNA in uterine flushings of mares with reproductive disorders.

PubMed

Marenzoni, Maria Luisa; Sforna, Monica; Stefanetti, Valentina; Casagrande Proietti, Patrizia; Brignone, Luca; Del Sero, Andrea; Falcioni, Fabio; Orvieto, Simona; Tamantini, Cristina; Tiburzi, Alessandra; Valentini, Silvia; Coletti, Mauro; Timoney, Peter J; Passamonti, Fabrizio

2014-12-05

In recent years, there has been increasing evidence of the potential pathogenic significance of equine gammaherpesviruses in the horse. In humans, cattle and mice, gammaherpesviruses have already been associated with uterine infection. The aim of the present study was to investigate the presence of gammaherpesviruses in uterine flushings of mares with reproductive problems and to evaluate if there was a possible statistical association with clinical and laboratory findings in these cases. A total of 80 uterine flushings were collected from 61 mares with different reproductive problems and these were tested for equine herpesviruses (EHV) 1-5 by PCR. In the case of each mare in the study, the age, history of infertility, presence of anatomical defects in the reproductive tract, presence of systemic or local disease at time of sampling, phase in the oestrous cycle, post-partum interval, nature of uterine lavage performed (low versus large volume lavage), cytological and bacteriological examination results from the uterine flushing, and PCR herpesvirus results were recorded. Univariate analysis and multivariable logistic regression models were used to identify possible statistical associations and risk factors. Nine out of 61 mares (14.7%) had EHV-5 DNA in their uterine flushings. Co-infections with EHV-1 and EHV-2 were present in two cases. Of all the variables analyzed, only the cytological examination findings were associated with EHV-5 PCR positive results, both on univariate and multivariable analysis, especially in cases with an inflammation score of 3. It is postulated that presence of EHV-5 infection in the non-pregnant uterus may have a role to play in reproductive dysfunction and have a negative consequence on the pregnant uterus. Additional studies involving both healthy mares and mares with reproductive problems need to be performed, however, to elucidate whatever role equine gammaherpesviruses may play in the reproductive tract. This would be very worthwhile, since reproductive problems can have a significant impact on the equine breeding industry. Gaining a greater understanding of its causes could lead to new approaches for prevention and treatment. Copyright © 2014 Elsevier B.V. All rights reserved.

High Nrf2 expression in alveolar type I pneumocytes is associated with low recurrences in primary spontaneous pneumothorax.

PubMed

Chen, Yu-Wen; Chiu, Wen-Chin; Chou, Shah-Hwa; Su, Yu-Han; Huang, Ying-Fong; Lee, Yen-Lung; Yuan, Shyng-Shiou F; Lee, Yi-Chen

2017-10-01

Recurrent primary spontaneous pneumothorax (PSP) is a troublesome problem and a major concern for the patients. This study examined whether nuclear factor erythroid 2-related factor 2 (Nrf2) expression in alveolar type I pneumocytes was associated with the clinical manifestations of PSP patients including disease recurrence. Eighty-eight PSP patients who were managed with needlescopic video-assisted thoracoscopic surgery (NVATS) were included in this study. Immunohistochemistry (IHC) was assessed to determine Nrf2 expression in resected lung tissues and the results were correlated with clinicopathological characteristics by the chi-square or the Fisher's exact test. The prognostic value of Nrf2 for overall recurrence was evaluated by univariate and multivariable Cox regression model. The expression of Nrf2 was observed in type I pneumocytes of lung tissues from PSP patients by IHC. We found that low Nrf2 expression in PSP patients, especially in young (age ≤ 20, p = 0.033) and body mass index (BMI) ≥18 kg/m 2 (p = 0.019) groups, was significantly correlated with PSP recurrence. In the univariate and multivariate analyses, high Nrf2 expression was a significant protective factor for overall recurrence in PSP patients (univariate: p = 0.026; multivariate: p = 0.004). The expression level of Nrf2 in alveolar type I pneumocytes was a potential factor involved in PSP recurrence. Our findings suggest that elevated Nrf2 expression in PSP patients may be a promising way for reducing PSP recurrence. Copyright © 2017. Published by Elsevier Taiwan.

Equicontrollability and the model following problem

NASA Technical Reports Server (NTRS)

Curran, R. T.

1971-01-01

Equicontrollability and its application to the linear time-invariant model-following problem are discussed. The problem is presented in the form of two systems, the plant and the model. The requirement is to find a controller to apply to the plant so that the resultant compensated plant behaves, in an input-output sense, the same as the model. All systems are assumed to be linear and time-invariant. The basic approach is to find suitable equicontrollable realizations of the plant and model and to utilize feedback so as to produce a controller of minimal state dimension. The concept of equicontrollability is a generalization of control canonical (phase variable) form applied to multivariable systems. It allows one to visualize clearly the effects of feedback and to pinpoint the parameters of a multivariable system which are invariant under feedback. The basic contributions are the development of equicontrollable form; solution of the model-following problem in an entirely algorithmic way, suitable for computer programming; and resolution of questions on system decoupling.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Neural networks in chemistry

NASA Astrophysics Data System (ADS)

Zupan, Jure

1995-04-01

All problems that in some way are linked to handling of multi-variate experiments versus multi-variate responses can be approached by the group of methods that has recently became known as the artificial neural network (ANN) techniques. In this lecture, the types of the problems that can be solved by ANN techniques rather than the ANN techniques themselves will be addressed first. This issue is rather important due to the fact that the ANN techniques can be used for a very broad range of problems and choosing the wrong method can often result in either a failure to produce an effective solution or in a very time consuming and ineffective handling. Among the types of problems that can be solved by different ANN techniques the classification, mapping, look-up table, and modelling will be emphasized and discussed. Because all mentioned methods can be solved by different standard techniques, special emphasis will be paid to stress the advantages and drawbacks when employing different ANN techniques. Due to the fact that the range of possible use of ANN is so broad, even a very specific problem can be solved by many different ANN architectures or even using different learning strategies within ANN. In the second part the main learning strategies and corresponding choices of ANN architectures will be discussed. In this part the parameters and some guidelines how to select the method and the design of the ANNs will be shown on the examples of reported ANN applications in chemistry. The ANN learning strategies discussed will be back-propagation of errors, the Kohonen, and the counter propagation learning. The potential user of ANN should first, consider the problem, second, he must inspect the availability of data and the data themselves to decide for which ANN method they are best suited. In this respect, the amount of data, the dimensionality of the measurement space, the form of data (alphanumeric entries, binary, real, or even mixed forms of data) are crucial. After considering all this factors, the determination of the appropriate neural network architecture can be made. Additionally, the selection the optimal ANN involves the determination of specific internal parameters like the learning rate, the momentum term, the neighbourhood function, the time dependent decrease of corrections, etc. Even after all these decisions have been made the learning procedure itself is not a straightforward task. Here, the division of the entire ensemble of data into three data sets: training, controlling and the test set are crucial. This problem is addressed as well.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Linear, multivariable robust control with a mu perspective

NASA Technical Reports Server (NTRS)

Packard, Andy; Doyle, John; Balas, Gary

1993-01-01

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.

An Individualized Student Term Project for Multivariate Calculus

ERIC Educational Resources Information Center

Gordon, Sheldon P.

2004-01-01

In this article, the author describes an individualized term project that is designed to increase student understanding of some of the major concepts and methods in multivariate calculus. The project involves having each student conduct a complete max-min analysis of a third degree polynomial in x and y that is based on his or her social security…

Effects of cumulative risk on behavioral and psychological well-being in first grade: moderation by neighborhood context.

PubMed

Lima, Julie; Caughy, Margaret; Nettles, Saundra M; O'Campo, Patricia J

2010-10-01

This study builds upon existing research by examining whether risk indices for child psychological well-being behave in the same way in different types of neighborhoods. Specifically, we sought to determine if neighborhood characteristics acted to exacerbate or, alternatively, to buffer risk factors at the family and/or child level. Families with a child entering first grade in Fall 2002 were recruited from Baltimore City neighborhoods, defined as census block groups. This study included 405 children, and data came from an interview with the primary caregiver and an assessment of the first grader. The dependent variables were externalizing behavior and internalizing problems. A family risk index consisting of 13 measures, and a child risk index consisting of three measures were the main independent variables of interest. We examined the effects of these indices on child psychological well-being and behavior across two neighborhood characteristics: neighborhood potential for community involvement with children and neighborhood negative social climate. Results of multivariate analyses indicated that cumulative family risk was associated with an increase in both internalizing and externalizing behavior problems. Perceived negative social climate moderated the effect of family risks on behavior problems such that more risk was associated with a larger increment in both externalizing behavior problems and psychological problems for children living in high versus low risk neighborhoods. These findings further emphasize the importance of considering neighborhood context in the study of child psychological well-being. Copyright © 2010 Elsevier Ltd. All rights reserved.

Poor self-recognition of disordered eating among girls with bulimic-type eating disorders: cause for concern?

PubMed

Gratwick-Sarll, Kassandra; Bentley, Caroline; Harrison, Carmel; Mond, Jonathan

2016-08-01

Bulimic-type eating disorders are common among young women and associated with high levels of distress and disability and low uptake of mental health care. We examined self-recognition of disordered eating and factors associated with this among female adolescents with bulimic-type eating disorders (n = 139) recruited from a large, population-based sample. A vignette of a fictional character with bulimia nervosa was presented, followed by a series of questions addressing the nature and treatment of the problem described. One of these questions required participants to indicate whether they currently had a problem such as the one described. Self-report measures of eating disorder symptoms, general psychological distress and quality of life were also completed. More than half of participants (58%) did not believe that they currently had a problem with their eating. In multivariable analysis, impairment in emotional well-being and self-induced vomiting were the only variables independently associated with self-recognition. Participants who recognized a problem with their eating were more likely to have sought treatment for an eating problem than those who did not. Recognition of disordered eating among adolescents with bulimic-type eating disorders may be poor and this may be a factor in low uptake of mental health care. Health promotion efforts may need to address the misconception that only bulimic-type disorders involving self-induced vomiting are pathological. © 2014 Wiley Publishing Asia Pty Ltd.

Pedagogical alternatives for triple integrals: moving towards more inclusive and personalized learning

NASA Astrophysics Data System (ADS)

Tisdell, Christopher C.

2018-07-01

This paper is based on the presumption that teaching multiple ways to solve the same problem has academic and social value. In particular, we argue that such a multifaceted approach to pedagogy moves towards an environment of more inclusive and personalized learning. From a mathematics education perspective, our discussion is framed around pedagogical approaches to triple integrals seen in a standard multivariable calculus curriculum. We present some critical perspectives regarding the dominant and long-standing approach to the teaching of triple integrals currently seen in hegemonic calculus textbooks; and we illustrate the need for more diverse pedagogical methods. Finally, we take a constructive position by introducing a new and alternate pedagogical approach to solve some of the classical problems involving triple integrals from the literature through a simple application of integration by parts. This pedagogical alternative for triple integrals is designed to question the dominant one-size-fits-all approach of rearranging the order of integration and the privileging of graphical methods; and to enable a shift towards a more inclusive, enhanced and personalized learning experience.

The Multivariate Roles of Family Instability and Interparental Conflict in Predicting Children’s Representations of Insecurity in the Family System and Early School Adjustment Problems

PubMed Central

Coe, Jesse L.; Davies, Patrick T.; Sturge-Apple, Melissa L.

2016-01-01

This study examined the moderating role of family instability in relations involving destructive interparental conflict, children’s internal representations of insecurity in the family system, and their early school maladjustment. Two hundred forty-three preschool children (M age = 4.60 years; 56% girls) and their families participated in this multi-method (i.e., observations, structured interview, surveys) multi-informant (i.e., observer, parent, teacher), longitudinal study. Findings indicated that the mediational role of children’s insecure family representations in the pathway between destructive interparental conflict and children’s adjustment problems varied significantly depending on the level of family instability. Interparental conflict was specifically associated with insecure family representations only under conditions of low family instability. In supporting the role of family instability as a vulnerable-stable risk factor, follow up analyses revealed that children’s concerns about security in the family were uniformly high under conditions of heightened instability regardless of their level of exposure to interparental conflict. PMID:27146062

Trends in modern system theory

NASA Technical Reports Server (NTRS)

Athans, M.

1976-01-01

The topics considered are related to linear control system design, adaptive control, failure detection, control under failure, system reliability, and large-scale systems and decentralized control. It is pointed out that the design of a linear feedback control system which regulates a process about a desirable set point or steady-state condition in the presence of disturbances is a very important problem. The linearized dynamics of the process are used for design purposes. The typical linear-quadratic design involving the solution of the optimal control problem of a linear time-invariant system with respect to a quadratic performance criterion is considered along with gain reduction theorems and the multivariable phase margin theorem. The stumbling block in many adaptive design methodologies is associated with the amount of real time computation which is necessary. Attention is also given to the desperate need to develop good theories for large-scale systems, the beginning of a microprocessor revolution, the translation of the Wiener-Hopf theory into the time domain, and advances made in dynamic team theory, dynamic stochastic games, and finite memory stochastic control.

Design and evaluation of a robust dynamic neurocontroller for a multivariable aircraft control problem

NASA Technical Reports Server (NTRS)

Troudet, T.; Garg, S.; Merrill, W.

1992-01-01

The design of a dynamic neurocontroller with good robustness properties is presented for a multivariable aircraft control problem. The internal dynamics of the neurocontroller are synthesized by a state estimator feedback loop. The neurocontrol is generated by a multilayer feedforward neural network which is trained through backpropagation to minimize an objective function that is a weighted sum of tracking errors, and control input commands and rates. The neurocontroller exhibits good robustness through stability margins in phase and vehicle output gains. By maintaining performance and stability in the presence of sensor failures in the error loops, the structure of the neurocontroller is also consistent with the classical approach of flight control design.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

Anger Expression Types and Interpersonal Problems in Nurses.

PubMed

Han, Aekyung; Won, Jongsoon; Kim, Oksoo; Lee, Sang E

2015-06-01

The purpose of this study was to investigate the anger expression types in nurses and to analyze the differences between the anger expression types and interpersonal problems. The data were collected from 149 nurses working in general hospitals with 300 beds or more in Seoul or Gyeonggi province, Korea. For anger expression type, the anger expression scale from the Korean State-Trait Anger Expression Inventory was used. For interpersonal problems, the short form of the Korean Inventory of Interpersonal Problems Circumplex Scales was used. Data were analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance, and Duncan's multiple comparisons test. Three anger expression types in nurses were found: low-anger expression, anger-in, and anger-in/control type. From the results of multivariate analysis of variance, there were significant differences between anger expression types and interpersonal problems (Wilks lambda F = 3.52, p < .001). Additionally, anger-in/control type was found to have the most difficulty with interpersonal problems by Duncan's post hoc test (p < .050). Based on this research, the development of an anger expression intervention program for nurses is recommended to establish the means of expressing the suppressed emotions, which would help the nurses experience less interpersonal problems. Copyright © 2015. Published by Elsevier B.V.

A multivariate model of parent-adolescent relationship variables in early adolescence.

PubMed

McKinney, Cliff; Renk, Kimberly

2011-08-01

Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle school in a Southeastern state. The parents of a subset of these adolescents (i.e., 487 mother-father pairs) participated in this study as well. Correlational analyses indicate that authoritative and authoritarian parenting, family cohesion and adaptability, and conflict are significant predictors of early adolescents' internalizing and externalizing problems. Structural equation modeling analyses indicate that fathers' parenting may not predict directly externalizing problems in male and female adolescents but instead may act through conflict. More direct relationships exist when examining mothers' parenting. The impact of parenting, family environment, and conflict on early adolescents' internalizing and externalizing problems and the importance of both gender and cross-informant ratings are emphasized.

Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

USGS Publications Warehouse

Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

1997-01-01

One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

Theoretical constraints in the design of multivariable control systems

NASA Technical Reports Server (NTRS)

Rynaski, E. G.; Mook, D. Joseph; Depena, Juan

1991-01-01

The research being performed under NASA Grant NAG1-1361 involves a more clear understanding and definition of the constraints involved in the pole-zero placement or assignment process for multiple input, multiple output systems. Complete state feedback to more than a single controller under conditions of complete controllability and observability is redundant if pole placement alone is the design objective. The additional feedback gains, above and beyond those required for pole placement can be used for eignevalue assignment or zero placement of individual closed loop transfer functions. Because both poles and zeros of individual closed loop transfer functions strongly affect the dynamic response to a pilot command input, the pole-zero placement problem is important. When fewer controllers than degrees of freedom of motion are available, complete design freedom is not possible, the transmission zeros constrain the regions of possible pole-zero placement. The effect of transmission zero constraints on the design possibilities, selection of transmission zeros and the avoidance of producing non-minimum phase transfer functions is the subject of the research being performed under this grant.

A multivariate analysis of genetic constraints to life history evolution in a wild population of red deer.

PubMed

Walling, Craig A; Morrissey, Michael B; Foerster, Katharina; Clutton-Brock, Tim H; Pemberton, Josephine M; Kruuk, Loeske E B

2014-12-01

Evolutionary theory predicts that genetic constraints should be widespread, but empirical support for their existence is surprisingly rare. Commonly applied univariate and bivariate approaches to detecting genetic constraints can underestimate their prevalence, with important aspects potentially tractable only within a multivariate framework. However, multivariate genetic analyses of data from natural populations are challenging because of modest sample sizes, incomplete pedigrees, and missing data. Here we present results from a study of a comprehensive set of life history traits (juvenile survival, age at first breeding, annual fecundity, and longevity) for both males and females in a wild, pedigreed, population of red deer (Cervus elaphus). We use factor analytic modeling of the genetic variance-covariance matrix ( G: ) to reduce the dimensionality of the problem and take a multivariate approach to estimating genetic constraints. We consider a range of metrics designed to assess the effect of G: on the deflection of a predicted response to selection away from the direction of fastest adaptation and on the evolvability of the traits. We found limited support for genetic constraint through genetic covariances between traits, both within sex and between sexes. We discuss these results with respect to other recent findings and to the problems of estimating these parameters for natural populations. Copyright © 2014 Walling et al.

A Multivariate Analysis of Genetic Constraints to Life History Evolution in a Wild Population of Red Deer

PubMed Central

Walling, Craig A.; Morrissey, Michael B.; Foerster, Katharina; Clutton-Brock, Tim H.; Pemberton, Josephine M.; Kruuk, Loeske E. B.

2014-01-01

Evolutionary theory predicts that genetic constraints should be widespread, but empirical support for their existence is surprisingly rare. Commonly applied univariate and bivariate approaches to detecting genetic constraints can underestimate their prevalence, with important aspects potentially tractable only within a multivariate framework. However, multivariate genetic analyses of data from natural populations are challenging because of modest sample sizes, incomplete pedigrees, and missing data. Here we present results from a study of a comprehensive set of life history traits (juvenile survival, age at first breeding, annual fecundity, and longevity) for both males and females in a wild, pedigreed, population of red deer (Cervus elaphus). We use factor analytic modeling of the genetic variance–covariance matrix (G) to reduce the dimensionality of the problem and take a multivariate approach to estimating genetic constraints. We consider a range of metrics designed to assess the effect of G on the deflection of a predicted response to selection away from the direction of fastest adaptation and on the evolvability of the traits. We found limited support for genetic constraint through genetic covariances between traits, both within sex and between sexes. We discuss these results with respect to other recent findings and to the problems of estimating these parameters for natural populations. PMID:25278555

Localization of synchronous cortical neural sources.

PubMed

Zerouali, Younes; Herry, Christophe L; Jemel, Boutheina; Lina, Jean-Marc

2013-03-01

Neural synchronization is a key mechanism to a wide variety of brain functions, such as cognition, perception, or memory. High temporal resolution achieved by EEG recordings allows the study of the dynamical properties of synchronous patterns of activity at a very fine temporal scale but with very low spatial resolution. Spatial resolution can be improved by retrieving the neural sources of EEG signal, thus solving the so-called inverse problem. Although many methods have been proposed to solve the inverse problem and localize brain activity, few of them target the synchronous brain regions. In this paper, we propose a novel algorithm aimed at localizing specifically synchronous brain regions and reconstructing the time course of their activity. Using multivariate wavelet ridge analysis, we extract signals capturing the synchronous events buried in the EEG and then solve the inverse problem on these signals. Using simulated data, we compare results of source reconstruction accuracy achieved by our method to a standard source reconstruction approach. We show that the proposed method performs better across a wide range of noise levels and source configurations. In addition, we applied our method on real dataset and identified successfully cortical areas involved in the functional network underlying visual face perception. We conclude that the proposed approach allows an accurate localization of synchronous brain regions and a robust estimation of their activity.

A note on a simplified and general approach to simulating from multivariate copula functions

Treesearch

Barry K. Goodwin

2013-01-01

Copulas have become an important analytic tool for characterizing multivariate distributions and dependence. One is often interested in simulating data from copula estimates. The process can be analytically and computationally complex and usually involves steps that are unique to a given parametric copula. We describe an alternative approach that uses ‘Probability-...

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics

PubMed Central

Preisser, John S.; Sen, Pranab K.; Offenbacher, Steven

2011-01-01

Dental research often involves repeated multivariate outcomes on a small number of subjects for which there is interest in identifying outcomes that exhibit change in their levels over time as well as to characterize the nature of that change. In particular, periodontal research often involves the analysis of molecular mediators of inflammation for which multivariate parametric methods are highly sensitive to outliers and deviations from Gaussian assumptions. In such settings, nonparametric methods may be favored over parametric ones. Additionally, there is a need for statistical methods that control an overall error rate for multiple hypothesis testing. We review univariate and multivariate nonparametric hypothesis tests and apply them to longitudinal data to assess changes over time in 31 biomarkers measured from the gingival crevicular fluid in 22 subjects whereby gingivitis was induced by temporarily withholding tooth brushing. To identify biomarkers that can be induced to change, multivariate Wilcoxon signed rank tests for a set of four summary measures based upon area under the curve are applied for each biomarker and compared to their univariate counterparts. Multiple hypothesis testing methods with choice of control of the false discovery rate or strong control of the family-wise error rate are examined. PMID:21984957

Penalized regression procedures for variable selection in the potential outcomes framework

PubMed Central

Ghosh, Debashis; Zhu, Yeying; Coffman, Donna L.

2015-01-01

A recent topic of much interest in causal inference is model selection. In this article, we describe a framework in which to consider penalized regression approaches to variable selection for causal effects. The framework leads to a simple ‘impute, then select’ class of procedures that is agnostic to the type of imputation algorithm as well as penalized regression used. It also clarifies how model selection involves a multivariate regression model for causal inference problems, and that these methods can be applied for identifying subgroups in which treatment effects are homogeneous. Analogies and links with the literature on machine learning methods, missing data and imputation are drawn. A difference LASSO algorithm is defined, along with its multiple imputation analogues. The procedures are illustrated using a well-known right heart catheterization dataset. PMID:25628185

Frequent methamphetamine injection predicts emergency department utilization among street-involved youth

PubMed Central

Marshall, B.D.L.; Grafstein, E.; Buxton, J.A.; Qi, J.; Wood, E.; Shoveller, J.A.; Kerr, T.

2011-01-01

SUMMARY Objectives Methamphetamine (MA) use has been associated with health problems that commonly present in the emergency department (ED). This study sought to determine whether frequent MA injection was a risk factor for ED utilization among street-involved youth. Study design Prospective cohort study. Methods Data were derived from a street-involved youth cohort known as the ‘At Risk Youth Study’. Behavioural data including MA use were linked to ED records at a major inner-city hospital. Kaplan-Meier and Cox proportional hazards methods were used to determine the risk factors for ED utilization. Results Between September 2005 and January 2007, 427 eligible participants were enrolled, among whom the median age was 21 (interquartile range 19–23) years and 154 (36.1%) were female. Within 1 year, 163 (38.2%) visited the ED, resulting in an incidence density of 53.7 per 100 person-years. ED utilization was significantly higher among frequent (i.e. ≥daily) MA injectors (log-rank P=0.004). In multivariate analysis, frequent MA injection was associated with an increased hazard of ED utilization (adjusted hazard ratio=1.84, 95% confidence interval 1.04–3.25; P=0.036). Conclusions Street-involved youth who frequently inject MA appear to be at increased risk of ED utilization. The integration of MA-specific addiction treatment services within emergency care settings for high-risk youth is recommended. PMID:22133669

Non-fragile multivariable PID controller design via system augmentation

NASA Astrophysics Data System (ADS)

Liu, Jinrong; Lam, James; Shen, Mouquan; Shu, Zhan

2017-07-01

In this paper, the issue of designing non-fragile H∞ multivariable proportional-integral-derivative (PID) controllers with derivative filters is investigated. In order to obtain the controller gains, the original system is associated with an extended system such that the PID controller design can be formulated as a static output-feedback control problem. By taking the system augmentation approach, the conditions with slack matrices for solving the non-fragile H∞ multivariable PID controller gains are established. Based on the results, linear matrix inequality -based iterative algorithms are provided to compute the controller gains. Simulations are conducted to verify the effectiveness of the proposed approaches.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A Fundamental Mathematical Model of a Microbial Predenitrification System

NASA Technical Reports Server (NTRS)

Hoo, Karlene A.

2005-01-01

Space flight beyond Low Earth Orbit requires sophisticated systems to support all aspects of the mission (life support, real-time communications, etc.). A common concern that cuts across all these systems is the selection of information technology (IT) methodology, software and hardware architectures to provide robust monitoring, diagnosis, and control support. Another dimension of the problem space is that different systems must be integrated seamlessly so that communication speed and data handling appear as a continuum (un-interrupted). One such team investigating this problem is the Advanced Integration Matrix (AIM) team whose role is to define the critical requirements expected of software and hardware to support an integrated approach to the command and control of Advanced Life Support (ALS) for future long-duration human space missions, including permanent human presence on the Moon and Mars. A goal of the AIM team is to set the foundation for testing criteria that will assist in specifying tasks, control schemes and test scenarios to validate and verify systems capabilities. This project is to contribute to the goals of the AIM team by assisting with controls planning for ALS. Control for ALS is an enormous problem it involves air revitalization, water recovery, food production, solids processing and crew. In more general terms, these systems can be characterized as involving both continuous and discrete processes, dynamic interactions among the sub-systems, nonlinear behavior due to the complex operations, and a large number of multivariable interactions due to the dimension of the state space. It is imperative that a baseline approach from which to measure performance is established especially when the expectation for the control system is complete autonomous control.

Mathematical models for exploring different aspects of genotoxicity and carcinogenicity databases.

PubMed

Benigni, R; Giuliani, A

1991-12-01

One great obstacle to understanding and using the information contained in the genotoxicity and carcinogenicity databases is the very size of such databases. Their vastness makes them difficult to read; this leads to inadequate exploitation of the information, which becomes costly in terms of time, labor, and money. In its search for adequate approaches to the problem, the scientific community has, curiously, almost entirely neglected an existent series of very powerful methods of data analysis: the multivariate data analysis techniques. These methods were specifically designed for exploring large data sets. This paper presents the multivariate techniques and reports a number of applications to genotoxicity problems. These studies show how biology and mathematical modeling can be combined and how successful this combination is.

Multivariate geometry as an approach to algal community analysis

USGS Publications Warehouse

Allen, T.F.H.; Skagen, S.

1973-01-01

Multivariate analyses are put in the context of more usual approaches to phycological investigations. The intuitive common-sense involved in methods of ordination, classification and discrimination are emphasised by simple geometric accounts which avoid jargon and matrix algebra. Warnings are given that artifacts result from technique abuses by the naive or over-enthusiastic. An analysis of a simple periphyton data set is presented as an example of the approach. Suggestions are made as to situations in phycological investigations, where the techniques could be appropriate. The discipline is reprimanded for its neglect of the multivariate approach.

Deterministic annealing for density estimation by multivariate normal mixtures

NASA Astrophysics Data System (ADS)

Kloppenburg, Martin; Tavan, Paul

1997-03-01

An approach to maximum-likelihood density estimation by mixtures of multivariate normal distributions for large high-dimensional data sets is presented. Conventionally that problem is tackled by notoriously unstable expectation-maximization (EM) algorithms. We remove these instabilities by the introduction of soft constraints, enabling deterministic annealing. Our developments are motivated by the proof that algorithmically stable fuzzy clustering methods that are derived from statistical physics analogs are special cases of EM procedures.

A Note on Asymptotic Joint Distribution of the Eigenvalues of a Noncentral Multivariate F Matrix.

DTIC Science & Technology

1984-11-01

Krishnaiah (1982). Now, let us consider the samples drawn from the k multivariate normal popuiejons. Let (Xlt....Xpt) denote the mean vector of the t...to maltivariate problems. Sankh-ya, 4, 381-39(s. (71 KRISHNAIAH , P. R. (1982). Selection of variables in discrimlnant analysis. In Handbook of...Statistics, Volume 2 (P. R. Krishnaiah , editor), 805-820. North-Holland Publishing Company. 6. Unclassifie INSTRUCTIONS REPORT DOCUMENTATION PAGE

Causal diagrams and multivariate analysis I: a quiver full of arrows.

PubMed

Jupiter, Daniel C

2014-01-01

How do we know which variables we should include in our multivariate analyses? What role does each variable play in our understanding of the analysis? In this article I begin a discussion of these issues and describe 2 different types of studies for which this problem must be handled in different ways. Copyright © 2014 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Factors Affecting Female Teachers' Attitudes toward Help-Seeking or Help-Avoidance in Coping with Behavioral Problems

ERIC Educational Resources Information Center

Inbar-Furst, Hagit; Gumpel, Thomas P.

2015-01-01

Questionnaires were given to 392 elementary school teachers to examine help-seeking or help-avoidance in dealing with classroom behavioral problems. Scale validity was examined through a series of exploratory and confirmatory factor analyses. Using a series of multivariate regression analyses and structural equation modeling, we identified…

Adolescent Gender Differences in Alcohol Problem Behaviors and the Social Contexts of Drinking.

ERIC Educational Resources Information Center

Treiman, Katherine A.; Beck, Kenneth H.

1996-01-01

This study of over 1300 high school students examined gender differences in the social context of drinking associated with 4 alcohol problem behaviors (high intensity drinking, binge drinking, driving while intoxicated, and riding with an intoxicated driver). Student surveys revealed significant multivariate interaction effects between gender and…

Moore and Less!

ERIC Educational Resources Information Center

Asghari, Amir

2012-01-01

This article is the story of a very non-standard, absolutely student-centered multivariable calculus course. The course advocates the so-called problem method in which the problems used are a bridge between what the learners know and what they are about to know. The main feature of the course is a unique conceptual story that runs through the…

A Complementary Measure of Heterogeneity on Mathematical Skills

ERIC Educational Resources Information Center

Fedriani, Eugenio M.; Moyano, Rafael

2012-01-01

Finding educational truths is an inherently multivariate problem. There are many factors affecting each student and their performances. Because of this, both measuring of skills and assessing students are always complex processes. This is a well-known problem, and a number of solutions have been proposed by specialists. One of its ramifications is…

Fast computation of the multivariable stability margin for real interrelated uncertain parameters

NASA Technical Reports Server (NTRS)

Sideris, Athanasios; Sanchez Pena, Ricardo S.

1988-01-01

A novel algorithm for computing the multivariable stability margin for checking the robust stability of feedback systems with real parametric uncertainty is proposed. This method eliminates the need for the frequency search involved in another given algorithm by reducing it to checking a finite number of conditions. These conditions have a special structure, which allows a significant improvement on the speed of computations.

Antimicrobial resistance: the major contribution of poor governance and corruption to this growing problem.

PubMed

Collignon, Peter; Athukorala, Prema-Chandra; Senanayake, Sanjaya; Khan, Fahad

2015-01-01

To determine how important governmental, social, and economic factors are in driving antibiotic resistance compared to the factors usually considered the main driving factors-antibiotic usage and levels of economic development. A retrospective multivariate analysis of the variation of antibiotic resistance in Europe in terms of human antibiotic usage, private health care expenditure, tertiary education, the level of economic advancement (per capita GDP), and quality of governance (corruption). The model was estimated using a panel data set involving 7 common human bloodstream isolates and covering 28 European countries for the period 1998-2010. Only 28% of the total variation in antibiotic resistance among countries is attributable to variation in antibiotic usage. If time effects are included the explanatory power increases to 33%. However when the control of corruption indicator is included as an additional variable, 63% of the total variation in antibiotic resistance is now explained by the regression. The complete multivariate regression only accomplishes an additional 7% in terms of goodness of fit, indicating that corruption is the main socioeconomic factor that explains antibiotic resistance. The income level of a country appeared to have no effect on resistance rates in the multivariate analysis. The estimated impact of corruption was statistically significant (p< 0.01). The coefficient indicates that an improvement of one unit in the corruption indicator is associated with a reduction in antibiotic resistance by approximately 0.7 units. The estimated coefficient of private health expenditure showed that one unit reduction is associated with a 0.2 unit decrease in antibiotic resistance. These findings support the hypothesis that poor governance and corruption contributes to levels of antibiotic resistance and correlate better than antibiotic usage volumes with resistance rates. We conclude that addressing corruption and improving governance will lead to a reduction in antibiotic resistance.

Accuracy enhancement of a multivariate calibration for lead determination in soils by laser induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Zaytsev, Sergey M.; Krylov, Ivan N.; Popov, Andrey M.; Zorov, Nikita B.; Labutin, Timur A.

2018-02-01

We have investigated matrix effects and spectral interferences on example of lead determination in different types of soils by laser induced breakdown spectroscopy (LIBS). Comparison between analytical performances of univariate and multivariate calibrations with the use of different laser wavelength for ablation (532, 355 and 266 nm) have been reported. A set of 17 soil samples (Ca-rich, Fe-rich, lean soils etc., 8.5-280 ppm of Pb) was involved into construction of the calibration models. Spectral interferences from main components (Ca, Fe, Ti, Mg) and trace components (Mn, Nb, Zr) were estimated by spectra modeling, and they were a reason for significant differences between the univariate calibration models obtained for a three different soil types (black, red, gray) separately. Implementation of 3rd harmonic of Nd:YAG laser in combination with multivariate calibration model based on PCR with 3 principal components provided the best analytical results: the RMSEC has been lowered down to 8 ppm. The sufficient improvement of the relative uncertainty (up to 5-10%) in comparison with univariate calibration was observed at the Pb concentration level > 50 ppm, while the problem of accuracy still remains for some samples with Pb concentration at the 20 ppm level. We have also discussed a few possible ways to estimate LOD without a blank sample. The most rigorous criterion has resulted in LOD of Pb in soils being 13 ppm. Finally, a good agreement between the values of lead content predicted by LIBS (46 ± 5 ppm) and XRF (42.1 ± 3.3 ppm) in the unknown soil sample from Lomonosov Moscow State University area was demonstrated.

Multivariate non-normally distributed random variables in climate research - introduction to the copula approach

NASA Astrophysics Data System (ADS)

Schölzel, C.; Friederichs, P.

2008-10-01

Probability distributions of multivariate random variables are generally more complex compared to their univariate counterparts which is due to a possible nonlinear dependence between the random variables. One approach to this problem is the use of copulas, which have become popular over recent years, especially in fields like econometrics, finance, risk management, or insurance. Since this newly emerging field includes various practices, a controversial discussion, and vast field of literature, it is difficult to get an overview. The aim of this paper is therefore to provide an brief overview of copulas for application in meteorology and climate research. We examine the advantages and disadvantages compared to alternative approaches like e.g. mixture models, summarize the current problem of goodness-of-fit (GOF) tests for copulas, and discuss the connection with multivariate extremes. An application to station data shows the simplicity and the capabilities as well as the limitations of this approach. Observations of daily precipitation and temperature are fitted to a bivariate model and demonstrate, that copulas are valuable complement to the commonly used methods.

SPReM: Sparse Projection Regression Model For High-dimensional Linear Regression *

PubMed Central

Sun, Qiang; Zhu, Hongtu; Liu, Yufeng; Ibrahim, Joseph G.

2014-01-01

The aim of this paper is to develop a sparse projection regression modeling (SPReM) framework to perform multivariate regression modeling with a large number of responses and a multivariate covariate of interest. We propose two novel heritability ratios to simultaneously perform dimension reduction, response selection, estimation, and testing, while explicitly accounting for correlations among multivariate responses. Our SPReM is devised to specifically address the low statistical power issue of many standard statistical approaches, such as the Hotelling’s T2 test statistic or a mass univariate analysis, for high-dimensional data. We formulate the estimation problem of SPREM as a novel sparse unit rank projection (SURP) problem and propose a fast optimization algorithm for SURP. Furthermore, we extend SURP to the sparse multi-rank projection (SMURP) by adopting a sequential SURP approximation. Theoretically, we have systematically investigated the convergence properties of SURP and the convergence rate of SURP estimates. Our simulation results and real data analysis have shown that SPReM out-performs other state-of-the-art methods. PMID:26527844

Contextual risk, maternal parenting and adolescent externalizing behaviour problems: the role of emotion regulation.

PubMed

Walton, A; Flouri, Eirini

2010-03-01

The objective of this study was to test if emotion regulation mediates the association between mothers' parenting and adolescents' externalizing behaviour problems (conduct problems and hyperactivity). The parenting dimensions were warmth, psychological control and behavioural control (measured with knowledge, monitoring and discipline). Adjustment was made for contextual risk (measured with the number of proximal adverse life events experienced), gender, age and English as an additional language. Data were from a UK community sample of adolescents aged 11-18 from a comprehensive school in a disadvantaged area. At the multivariate level, none of the parenting variables predicted hyperactivity, which was associated only with difficulties in emotion regulation, contextual risk and English as a first language. The parenting variables predicting conduct problems at the multivariate level were warmth and knowledge. Knowledge did not predict emotion regulation. However, warmth predicted emotion regulation, which was negatively associated with conduct problems. Contextual risk was a significant predictor of both difficulties in emotion regulation and externalizing behaviour problems. Its effect on conduct problems was independent of parenting and was not via its association with difficulties in emotion regulation. The findings add to the evidence for the importance of maternal warmth and contextual risk for both regulated emotion and regulated behaviour. The small maternal control effects on both emotion regulation and externalizing behaviour could suggest the importance of paternal control for adolescent outcomes.

Prevalence and predictors of thyroid functional abnormalities in newly diagnosed AL amyloidosis.

PubMed

Muchtar, E; Dean, D S; Dispenzieri, A; Dingli, D; Buadi, F K; Lacy, M Q; Hayman, S R; Kapoor, P; Leung, N; Russell, S; Lust, J A; Lin, Yi; Warsame, R; Gonsalves, W; Kourelis, T V; Go, R S; Chakraborty, R; Zeldenrust, S; Kyle, R A; Rajkumar, S Vincent; Kumar, S K; Gertz, M A

2017-06-01

Data on the effect of systemic immunoglobulin light chain amyloidosis (AL amyloidosis) on thyroid function are limited. To assess the prevalence of hypothyroidism in AL amyloidosis patients and determine its predictors. 1142 newly diagnosed AL amyloidosis patients were grouped based on the thyroid-stimulating hormone (TSH) measurement at diagnosis: hypothyroid group (TSH above upper normal reference; >5 mIU L -1 ; n = 217, 19% of study participants) and euthyroid group (n = 925, 81%). Predictors for hypothyroidism were assessed in a binary multivariate model. Survival between groups was compared using the log-rank test and a multivariate analysis. Patients with hypothyroidism were older, more likely to present with renal and hepatic involvement and had a higher light chain burden compared to patients in the euthyroid group. Higher proteinuria in patients with renal involvement and lower albumin in patients with hepatic involvement were associated with hypothyroidism. In a binary logistic regression model, age ≥65 years, female sex, renal involvement, hepatic involvement, kappa light chain restriction and amiodarone use were independently associated with hypothyroidism. Ninety-three per cent of patients in the hypothyroid group with free thyroxine measurement had normal values, consistent with subclinical hypothyroidism. Patients in the hypothyroid group had a shorter survival compared to patients in the euthyroid group (4-year survival 36% vs 43%; P = 0.008), a difference that was maintained in a multivariate analysis. A significant proportion of patients with AL amyloidosis present with hypothyroidism, predominantly subclinical, which carries a survival disadvantage. Routine assessment of TSH in these patients is warranted. © 2017 The Association for the Publication of the Journal of Internal Medicine.

Modeling the Drift Towards Sex Role Deviance.

ERIC Educational Resources Information Center

James, Jennifer; Vitaliano, Peter Paul

The interrelationships of deviant life experiences and current status, i.e., prostitution versus non-prostitution, were investigated by the application of multivariate analyses. Variables were studied involving early home life, pregnancy history, sexual history, and criminal involvement. Based on the analyses, three models were developed that…

Childhood internalizing and externalizing problems predict the onset of clinical panic attacks over adolescence: the TRAILS study.

PubMed

Mathyssek, Christina M; Olino, Thomas M; Verhulst, Frank C; van Oort, Floor V A

2012-01-01

Panic attacks are a source of individual suffering and are an independent risk factor for later psychopathology. However, much less is known about risk factors for the development of panic attacks, particularly during adolescence when the incidence of panic attacks increases dramatically. We examined whether internalizing and externalizing problems in childhood predict the onset of panic attacks in adolescence. This study is part of the TRacking Adolescents' Individual Lives Survey (TRAILS), a Dutch longitudinal population cohort study (N = 1,584). Internalizing and Externalizing Problems were collected using the Youth Self-Report (YSR) and the parent-report Child Behavior Checklist (CBCL) at baseline (age 10-12). At age 18-20, DSM-IV defined panic attacks since baseline were assessed with the Composite International Diagnostic Interview (CIDI). We investigated whether early adolescent Internalizing and Externalizing Problems predicted panic attacks between ages 10-20 years, using survival analysis in univariate and multivariate models. There were N = 314 (19.8%) cases who experienced at least one DSM-IV defined panic attack during adolescence and N = 18 (1.2%) who developed panic disorder during adolescence. In univariate analyses, CBCL Total Problems, Internalizing Problems and three of the eight syndrome scales predicted panic attack onset, while on the YSR all broad-band problem scales and each narrow-band syndrome scale predicted panic attack onset. In multivariate analyses, CBCL Social Problems (HR 1.19, p<.05), and YSR Thought Problems (HR 1.15, p<.05) and Social Problems (HR 1.26, p<.01) predicted panic attack onset. Risk indicators of panic attack include the wide range of internalizing and externalizing problems. Yet, when adjusted for co-occurring problem behaviors, Social Problems were the most consistent risk factor for panic attack onsets in adolescence.

Scenario generation for stochastic optimization problems via the sparse grid method

DOE PAGES

Chen, Michael; Mehrotra, Sanjay; Papp, David

2015-04-19

We study the use of sparse grids in the scenario generation (or discretization) problem in stochastic programming problems where the uncertainty is modeled using a continuous multivariate distribution. We show that, under a regularity assumption on the random function involved, the sequence of optimal objective function values of the sparse grid approximations converges to the true optimal objective function values as the number of scenarios increases. The rate of convergence is also established. We treat separately the special case when the underlying distribution is an affine transform of a product of univariate distributions, and show how the sparse grid methodmore » can be adapted to the distribution by the use of quadrature formulas tailored to the distribution. We numerically compare the performance of the sparse grid method using different quadrature rules with classic quasi-Monte Carlo (QMC) methods, optimal rank-one lattice rules, and Monte Carlo (MC) scenario generation, using a series of utility maximization problems with up to 160 random variables. The results show that the sparse grid method is very efficient, especially if the integrand is sufficiently smooth. In such problems the sparse grid scenario generation method is found to need several orders of magnitude fewer scenarios than MC and QMC scenario generation to achieve the same accuracy. As a result, it is indicated that the method scales well with the dimension of the distribution--especially when the underlying distribution is an affine transform of a product of univariate distributions, in which case the method appears scalable to thousands of random variables.« less

Quantum attack-resistent certificateless multi-receiver signcryption scheme.

PubMed

Li, Huixian; Chen, Xubao; Pang, Liaojun; Shi, Weisong

2013-01-01

The existing certificateless signcryption schemes were designed mainly based on the traditional public key cryptography, in which the security relies on the hard problems, such as factor decomposition and discrete logarithm. However, these problems will be easily solved by the quantum computing. So the existing certificateless signcryption schemes are vulnerable to the quantum attack. Multivariate public key cryptography (MPKC), which can resist the quantum attack, is one of the alternative solutions to guarantee the security of communications in the post-quantum age. Motivated by these concerns, we proposed a new construction of the certificateless multi-receiver signcryption scheme (CLMSC) based on MPKC. The new scheme inherits the security of MPKC, which can withstand the quantum attack. Multivariate quadratic polynomial operations, which have lower computation complexity than bilinear pairing operations, are employed in signcrypting a message for a certain number of receivers in our scheme. Security analysis shows that our scheme is a secure MPKC-based scheme. We proved its security under the hardness of the Multivariate Quadratic (MQ) problem and its unforgeability under the Isomorphism of Polynomials (IP) assumption in the random oracle model. The analysis results show that our scheme also has the security properties of non-repudiation, perfect forward secrecy, perfect backward secrecy and public verifiability. Compared with the existing schemes in terms of computation complexity and ciphertext length, our scheme is more efficient, which makes it suitable for terminals with low computation capacity like smart cards.

Multivariate missing data in hydrology - Review and applications

NASA Astrophysics Data System (ADS)

Ben Aissia, Mohamed-Aymen; Chebana, Fateh; Ouarda, Taha B. M. J.

2017-12-01

Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

Family and parenting characteristics associated with marijuana use by Chilean adolescents

PubMed Central

Bares, Cristina B; Delva, Jorge; Grogan-Kaylor, Andrew; Andrade, Fernando

2011-01-01

Objective Family involvement and several characteristics of parenting have been suggested to be protective factors for adolescent substance use. Some parenting behaviors may have stronger relationships with adolescent behavior while others may have associations with undesirable behavior among youth. Although it is generally acknowledged that families play an important role in the lives of Chilean adolescents, scant research exists on how different family and parenting factors may be associated with marijuana use and related problems in this population which has one of the highest rates of drug use in Latin America. Methods Using logistic regression and negative binomial regression, we examined whether a large number of family and parenting variables were associated with the possibility of Chilean adolescents ever using marijuana, and with marijuana-related problems. Analyses controlled for a number of demographic and peer-related variables. Results Controlling for other parenting and family variables, adolescent reports of parental marijuana use showed a significant and positive association with adolescent marijuana use. The multivariate models also revealed that harsh parenting by fathers was the only family variable associated with the number of marijuana-related problems youth experienced. Conclusion Of all the family and parenting variables studied, perceptions of parental use of marijuana and harsh parenting by fathers were predictors for marijuana use, and the experience of marijuana-related problems. Prevention interventions need to continue emphasizing the critical socializing role that parental behavior plays in their children’s development and potential use of marijuana. PMID:21660209

Perceived Devaluation and STI Testing Uptake among a Cohort of Street-Involved Youth in a Canadian Setting.

PubMed

Karamouzian, Mohammad; Shoveller, Jean; Dong, Huiru; Gilbert, Mark; Kerr, Thomas; DeBeck, Kora

2017-10-01

Perceived devaluation has been shown to have adverse effects on the mental and physical health outcomes of people who use drugs. However, the impact of perceived devaluation on sexually transmitted infections (STI) testing uptake among street-involved youth, who face multiple and intersecting stigmas due to their association with drug use and risky sexual practices, has not been fully characterized. Data were obtained between December 2013 and November 2014 from a cohort of street-involved youth who use illicit drugs aged 14-26 in Vancouver, British Columbia. Multivariable generalized estimating equations were constructed to assess the independent relationship between perceived devaluation and STI testing uptake. Among 300 street-involved youth, 87.0% reported a high perceived devaluation score at baseline. In the multivariable analysis, high perceived devaluation was negatively associated with STI testing uptake after adjustment for potential confounders (Adjusted Odds Ratio = 0.38, 95% Confidence Interval 0.15-0.98). Perceived devaluation was high among street-involved youth in our sample and appears to have adverse effects on STI testing uptake. HIV prevention and care programs should be examined and improved to better meet the special needs of street-involved youth in non-stigmatizing ways.

A Multivariate Examination of the Child-Abuse Potential of Parents with Children Aged 0-6

ERIC Educational Resources Information Center

Cetin, Zeynep; Ozozen Danaci, Miray

2016-01-01

Problem Statement: Child abuse, defined by the World Health Organization as "intentional or unintentional behavior by adults, society, or a country with negative consequences for the health and physical development of the child," is a social problem frequently encountered in all cultures and societies. It is need to this study because of…

Using Student-Developed, Inquiry-Based Experiments to Investigate the Contributions of Ca and Mg to Water Hardness

ERIC Educational Resources Information Center

Yang, Shui-Ping; Li, Chung-Chia

2009-01-01

This study provided a challenging opportunity for general chemistry students to mimic the scientific research process by solving a water-quality problem concerning individual calcium and magnesium concentrations. We found that general chemistry students were able to develop their own experiments to solve real-world, multivariable problems through…

Causal Inference and Omitted Variable Bias in Financial Aid Research: Assessing Solutions

ERIC Educational Resources Information Center

Riegg, Stephanie K.

2008-01-01

This article highlights the problem of omitted variable bias in research on the causal effect of financial aid on college-going. I first describe the problem of self-selection and the resulting bias from omitted variables. I then assess and explore the strengths and weaknesses of random assignment, multivariate regression, proxy variables, fixed…

Statistics Anxiety and Worry: The Roles of Worry Beliefs, Negative Problem Orientation, and Cognitive Avoidance

ERIC Educational Resources Information Center

Williams, Amanda S.

2015-01-01

Statistics anxiety is a common problem for graduate students. This study explores the multivariate relationship between a set of worry-related variables and six types of statistics anxiety. Canonical correlation analysis indicates a significant relationship between the two sets of variables. Findings suggest that students who are more intolerant…

Multivariate Epi-splines and Evolving Function Identification Problems

DTIC Science & Technology

2015-04-15

such extrinsic information as well as observed function and subgradient values often evolve in applications, we establish conditions under which the...previous study [30] dealt with compact intervals of IR. Splines are intimately tied to optimization problems through their variational theory pioneered...approxima- tion. Motivated by applications in curve fitting, regression, probability density estimation, variogram computation, financial curve construction

Moderation and Mediation in Structural Equation Modeling: Applications for Early Intervention Research

ERIC Educational Resources Information Center

Hopwood, Christopher J.

2007-01-01

Second-generation early intervention research typically involves the specification of multivariate relations between interventions, outcomes, and other variables. Moderation and mediation involve variables or sets of variables that influence relations between interventions and outcomes. Following the framework of Baron and Kenny's (1986) seminal…

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

A multivariate analysis of sex offender recidivism.

PubMed

Scalora, Mario J; Garbin, Calvin

2003-06-01

Sex offender recidivism risk is a multifaceted phenomenon requiring consideration across multiple risk factor domains. The impact of treatment involvement and subsequent recidivism is given limited attention in comparison to other forensic mental health issues. The present analysis is a retrospective study of sex offenders treated at a secure facility utilizing a cognitive-behavioral program matched with an untreated correctional sample. Variables studied included demographic, criminal history, offense related, and treatment progress. Recidivism was assessed through arrest data. Multivariate analysis suggests that recidivism is significantly related to quality of treatment involvement, offender demographics, offense characteristics, and criminal history. Successfully treated offenders were significantly less likely to subsequently reoffend. Recidivists were also significantly younger, less likely married, had engaged in more victim grooming or less violent offending behavior, and had significantly more prior property charges. The authors discuss the clinical and policy implications of the interrelationship between treatment involvement and recidivism.

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

PubMed Central

Galván-Tejada, Carlos E.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.

2017-01-01

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions. PMID:28216571

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

PubMed

Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

2017-02-14

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

Alcohol Use and Sexual Risks: Use of the Alcohol Use Disorders Identification Test (AUDIT) Among Female Sex Workers in China

PubMed Central

Chen, Yiyun; Li, Xiaoming; Zhang, Chen; Hong, Yan; Zhou, Yuejiao; Liu, Wei

2012-01-01

The association between alcohol use and sexual risks among female sex workers (FSWs) has been insufficiently studied. This article reports a cross-sectional study of the relationship between alcohol use risk, measured by the Alcohol Use Disorders Identification Test (AUDIT), and sexual risk behaviors among 1,022 FSWs in Guangxi, China. Bivariate analysis showed that FSWs at higher AUDIT levels tended to have earlier sexual initiation, younger age of involvement in the sex trade and were more vulnerable to sex under the influence of alcohol. Multivariate analysis revealed an independent association of problem drinking with both unprotected sex and a history of sexually transmitted diseases. Alcohol use in commercial sex shall be considered as an occupational hazard that requires immediate intervention. Future longitudinal studies are needed to confirm the association between alcohol use and sexual risks among this most-at-risk population. PMID:23311906

Foster care history and HIV infection among drug-using African American female sex workers.

PubMed

Surratt, Hilary L; Kurtz, Steven P

2012-05-01

Foster care has been associated with increased HIV risk behaviors among youth, yet long-term association with HIV infection has not been examined. This study explored the associations between foster placement, victimization, mental health, onset of sex work and HIV infection among highly vulnerable female sex workers. 562 drug-involved African American women were enrolled into an intervention study to increase health services utilization and reduce HIV risk. Seventeen percent reported a history of foster placement. Foster history was associated with significantly lower educational attainment, higher victimization, and more severe mental health problems. Women with foster histories reported significantly earlier entry into paid sex work, with some 62% active in the sex trade before age 18. Multivariate analyses found that foster care was independently associated with HIV seropositivity, and that early sex work partially mediated this association. The potential long-term health vulnerabilities associated with foster placement are understudied and warrant additional research.

Workplace responsibility, stress, alcohol availability and norms as predictors of alcohol consumption-related problems among employed workers.

PubMed

Hodgins, David C; Williams, Robert; Munro, Gordon

2009-01-01

The objectives of this study were to determine the prevalence of alcohol use and problems among employed individuals in Alberta, Canada (N = 1,890), and to conduct a multivariate examination of predictors of alcohol consumption-related problems. General alcohol problems were identified by 10%, although very few workers described any specific work-related alcohol problems (1%). Structural equation modeling revealed that, as hypothesized, workplace alcohol availability predicted general alcohol problems. Job responsibility and workplace norms also predicted alcohol problems but only for men. Perceived work stress did not predict alcohol problems. Results support the development of interventions that focus on re-shaping alcohol use norms.

A Review of Calibration Transfer Practices and Instrument Differences in Spectroscopy.

PubMed

Workman, Jerome J

2018-03-01

Calibration transfer for use with spectroscopic instruments, particularly for near-infrared, infrared, and Raman analysis, has been the subject of multiple articles, research papers, book chapters, and technical reviews. There has been a myriad of approaches published and claims made for resolving the problems associated with transferring calibrations; however, the capability of attaining identical results over time from two or more instruments using an identical calibration still eludes technologists. Calibration transfer, in a precise definition, refers to a series of analytical approaches or chemometric techniques used to attempt to apply a single spectral database, and the calibration model developed using that database, for two or more instruments, with statistically retained accuracy and precision. Ideally, one would develop a single calibration for any particular application, and move it indiscriminately across instruments and achieve identical analysis or prediction results. There are many technical aspects involved in such precision calibration transfer, related to the measuring instrument reproducibility and repeatability, the reference chemical values used for the calibration, the multivariate mathematics used for calibration, and sample presentation repeatability and reproducibility. Ideally, a multivariate model developed on a single instrument would provide a statistically identical analysis when used on other instruments following transfer. This paper reviews common calibration transfer techniques, mostly related to instrument differences, and the mathematics of the uncertainty between instruments when making spectroscopic measurements of identical samples. It does not specifically address calibration maintenance or reference laboratory differences.

Anger expression, violent behavior, and symptoms of depression among male college students in Ethiopia.

PubMed

Terasaki, Dale J; Gelaye, Bizu; Berhane, Yemane; Williams, Michelle A

2009-01-12

Depression is an important global public health problem. Given the scarcity of studies involving African youths, this study was conducted to evaluate the associations of anger expression and violent behavior with symptoms of depression among male college students. A self-administered questionnaire was used to collect information on socio-demographic and lifestyle characteristics and violent behavior among 1,176 college students in Awassa, Ethiopia in June, 2006. The questionnaire incorporated the Spielberger Anger-Out Expression (SAOE) scale and symptoms of depression were evaluated using the Patient Health Questionnaire (PHQ-9). Multivariable logistic regression procedures were used to calculate adjusted odds ratios (OR) and 95% confidence intervals (95%CI). Symptoms of depression were evident in 23.6% of participants. Some 54.3% of students reported committing at least one act of violence in the current academic year; and 29.3% of students reported high (SAOE score > or = 15) levels of anger-expression. In multivariate analysis, moderate (OR = 1.97; 95%CI 1.33-2.93) and high (OR = 3.23; 95%CI 2.14-4.88) outward anger were statistically significantly associated with increased risks of depressive symptoms. Violent behavior was noted to be associated with depressive symptoms (OR = 1.82; 95%CI 1.37-2.40). Further research should be conducted to better characterize community and individual level determinants of anger-expression, violent behavior and depression among youths.

Multivariate Analysis and Its Application.

DTIC Science & Technology

1987-09-01

26. Alzaid, Abdulhamid A., Rao, C. Radhakrishna and Shanbhag, D. N. An Application of the Perron - Frobenius Theorem to a Damage Model Problem...Technical Report #85-13. Center for Multivariate Analysis. April 1985. Using the Perron - Frobenius theorem, it is established that if (XY) is a random...C. Radhakrishna. Shanhhac, I).N. "An 45 A -. " Aplcto of’ ’~ th Perron -7’ 7rbn us’ Thoe oaDmgJoe Probem".Sanhva,48,pp 4-50 198. (Tchncal epot #8-13

On measures of association among genetic variables

PubMed Central

Gianola, Daniel; Manfredi, Eduardo; Simianer, Henner

2012-01-01

Summary Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart. PMID:22742500

Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia

PubMed Central

Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Tenison, Caitlin; Menon, Vinod

2015-01-01

Developmental dyscalculia (DD) is a disability that impacts math learning and skill acquisition in school-age children. Here we investigate arithmetic problem solving deficits in young children with DD using univariate and multivariate analysis of fMRI data. During fMRI scanning, 17 children with DD (ages 7–9, grades 2 and 3) and 17 IQ- and reading ability-matched typically developing (TD) children performed complex and simple addition problems which differed only in arithmetic complexity. While the TD group showed strong modulation of brain responses with increasing arithmetic complexity, children with DD failed to show such modulation. Children with DD showed significantly reduced activation compared to TD children in the intraparietal sulcus, superior parietal lobule, supramarginal gyrus and bilateral dorsolateral prefrontal cortex in relation to arithmetic complexity. Critically, multivariate representational similarity revealed that brain response patterns to complex and simple problems were less differentiated in the DD group in bilateral anterior IPS, independent of overall differences in signal level. Taken together, these results show that children with DD not only under-activate key brain regions implicated in mathematical cognition, but they also fail to generate distinct neural responses and representations for different arithmetic problems. Our findings provide novel insights into the neural basis of DD. PMID:22682904

Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia.

PubMed

Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Tenison, Caitlin; Menon, Vinod

2012-02-15

Developmental dyscalculia (DD) is a disability that impacts math learning and skill acquisition in school-age children. Here we investigate arithmetic problem solving deficits in young children with DD using univariate and multivariate analysis of fMRI data. During fMRI scanning, 17 children with DD (ages 7-9, grades 2 and 3) and 17 IQ- and reading ability-matched typically developing (TD) children performed complex and simple addition problems which differed only in arithmetic complexity. While the TD group showed strong modulation of brain responses with increasing arithmetic complexity, children with DD failed to show such modulation. Children with DD showed significantly reduced activation compared to TD children in the intraparietal sulcus, superior parietal lobule, supramarginal gyrus and bilateral dorsolateral prefrontal cortex in relation to arithmetic complexity. Critically, multivariate representational similarity revealed that brain response patterns to complex and simple problems were less differentiated in the DD group in bilateral anterior IPS, independent of overall differences in signal level. Taken together, these results show that children with DD not only under-activate key brain regions implicated in mathematical cognition, but they also fail to generate distinct neural responses and representations for different arithmetic problems. Our findings provide novel insights into the neural basis of DD. Copyright © 2011 Elsevier Ltd. All rights reserved.

Childhood adversity and behavioral health outcomes for youth: An investigation using state administrative data.

PubMed

Lucenko, Barbara A; Sharkova, Irina V; Huber, Alice; Jemelka, Ron; Mancuso, David

2015-09-01

This study aimed to measure the relative contribution of adverse experiences to adolescent behavioral health problems using administrative data. Specifically, we sought to understand the predictive value of adverse experiences on the presence of mental health and substance abuse problems for youth receiving publicly funded social and health services. Medicaid claims and other service records were analyzed for 125,123 youth age 12-17 and their biological parents. Measures from administrative records reflected presence of parental domestic violence, mental illness, substance abuse, criminal justice involvement, child abuse and/or neglect, homelessness, and death of a biological parent. Mental health and substance abuse status of adolescents were analyzed as functions of adverse experiences and other youth characteristics using logistic regression. In multivariate analyses, all predictors except parental domestic violence were statistically significant for substance abuse; parental death, parental mental illness, child abuse or neglect and homelessness were statistically significant for mental illness. Odds ratios for child abuse/neglect were particularly high in both models. The ability to identify risks during childhood using administrative data suggests the potential to target prevention and early intervention efforts for children with specific family risk factors who are at increased risk for developing behavioral health problems during adolescence. This study illustrates the utility of administrative data in understanding adverse experiences on children and the advantages and disadvantages of this approach. Copyright © 2015 Elsevier Ltd. All rights reserved.

Online Graph Completion: Multivariate Signal Recovery in Computer Vision.

PubMed

Kim, Won Hwa; Jalal, Mona; Hwang, Seongjae; Johnson, Sterling C; Singh, Vikas

2017-07-01

The adoption of "human-in-the-loop" paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e.g., human supervision) and the underlying inference algorithms are closely interwined. While classical work in active learning provides effective solutions when the learning module involves classification and regression tasks, many practical issues such as partially observed measurements, financial constraints and even additional distributional or structural aspects of the data typically fall outside the scope of this treatment. For instance, with sequential acquisition of partial measurements of data that manifest as a matrix (or tensor), novel strategies for completion (or collaborative filtering) of the remaining entries have only been studied recently. Motivated by vision problems where we seek to annotate a large dataset of images via a crowdsourced platform or alternatively, complement results from a state-of-the-art object detector using human feedback, we study the "completion" problem defined on graphs, where requests for additional measurements must be made sequentially. We design the optimization model in the Fourier domain of the graph describing how ideas based on adaptive submodularity provide algorithms that work well in practice. On a large set of images collected from Imgur, we see promising results on images that are otherwise difficult to categorize. We also show applications to an experimental design problem in neuroimaging.

On theoretical and experimental modeling of metabolism forming in prebiotic systems

NASA Astrophysics Data System (ADS)

Bartsev, S. I.; Mezhevikin, V. V.

Recently searching for extraterrestrial life attracts more and more attention However the searching hardly can be effective without sufficiently universal concept of life origin which incidentally tackles a problem of origin of life on the Earth A concept of initial stages of life origin including origin of prebiotic metabolism is stated in the paper Suggested concept eliminates key difficulties in the problem of life origin and allows experimental verification of it According to the concept the predecessor of living beings has to be sufficiently simple to provide non-zero probability of self-assembling during short in geological or cosmic scale time In addition the predecessor has to be capable of autocatalysis and further complication evolution A possible scenario of initial stage of life origin which can be realized both on other planets and inside experimental facility is considered In the scope of the scenario a theoretical model of multivariate oligomeric autocatalyst coupled with phase-separated particle is presented Results of computer simulation of possible initial stage of chemical evolution are shown Conducted estimations show the origin of autocatalytic oligomeric phase-separated system is possible at reasonable values of kinetic parameters of involved chemical reactions in a small-scale flow reactor Accepted statements allowing to eliminate key problems of life origin imply important consequence -- organisms emerged out of the Earth or inside a reactor have to be based on another different from terrestrial biochemical

Factors Predictive of Sentinel Lymph Node Involvement in Primary Breast Cancer.

PubMed

Malter, Wolfram; Hellmich, Martin; Badian, Mayhar; Kirn, Verena; Mallmann, Peter; Krämer, Stefan

2018-06-01

Sentinel lymph node biopsy (SLNB) has replaced axillary lymph node dissection (ALND) for axillary staging in patients with early-stage breast cancer. The need for therapeutic ALND is the subject of ongoing debate especially after the publication of the ACOSOG Z0011 trial. In a retrospective trial with univariate and multivariate analyses, factors predictive of sentinel lymph node involvement should be analyzed in order to define tumor characteristics of breast cancer patients, where SLNB should not be spared to receive important indicators for adjuvant treatment decisions (e.g. thoracic wall irradiation after mastectomy with or without reconstruction). Between 2006 and 2010, 1,360 patients with primary breast cancer underwent SLNB with/without ALND with evaluation of tumor localization, multicentricity and multifocality, histological subtype, tumor size, grading, lymphovascular invasion (LVI), and estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status. These characteristics were retrospectively analyzed in univariate and multivariate logistic regression models to define significant predictive factors for sentinel lymph node involvement. The multivariate analysis demonstrated that tumor size and LVI (p<0.001) were independent predictive factors for metastatic sentinel lymph node involvement in patients with early-stage breast cancer. Because of the increased risk for metastatic involvement of axillary sentinel nodes in cases with larger breast cancer or diagnosis of LVI, patients with these breast cancer characteristics should not be spared from SLNB in a clinically node-negative situation in order to avoid false-negative results with a high potential for wrong indication of primary breast reconstruction or wrong non-indication of necessary post-mastectomy radiation therapy. The prognostic impact of avoidance of axillary staging with SLNB is analyzed in the ongoing prospective INSEMA trial. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

The Hispanic Americans Baseline Alcohol Survey (HABLAS): Acculturation, Birthplace and Alcohol-Related Social Problems across Hispanic National Groups

ERIC Educational Resources Information Center

Caetano, Raul; Vaeth, Patrice A. C.; Rodriguez, Lori A.

2012-01-01

The purpose of this study was to examine the association between acculturation, birthplace, and alcohol-related social problems across Hispanic national groups. A total of 5,224 Hispanic adults (18+ years) were interviewed using a multistage cluster sample design in Miami, New York, Philadelphia, Houston, and Los Angeles. Multivariate analysis…

Development of a Test for an Experimental Research Program in Creative Problem Solving. Final Report.

ERIC Educational Resources Information Center

Miles, David T.

The purpose of this first phase of a continuing research program was the development of a test of creative problem solving in general design. A design class of 186 members was divided into an experimental and control group; a non-design control group (an educational psychology class) of 45 was also tested. Multivariate interpretation of creative…

Independent Predictors of Prognosis Based on Oral Cavity Squamous Cell Carcinoma Surgical Margins.

PubMed

Buchakjian, Marisa R; Ginader, Timothy; Tasche, Kendall K; Pagedar, Nitin A; Smith, Brian J; Sperry, Steven M

2018-05-01

Objective To conduct a multivariate analysis of a large cohort of oral cavity squamous cell carcinoma (OCSCC) cases for independent predictors of local recurrence (LR) and overall survival (OS), with emphasis on the relationship between (1) prognosis and (2) main specimen permanent margins and intraoperative tumor bed frozen margins. Study Design Retrospective cohort study. Setting Tertiary academic head and neck cancer program. Subjects and Methods This study included 426 patients treated with OCSCC resection between 2005 and 2014 at University of Iowa Hospitals and Clinics. Patients underwent excision of OCSCC with intraoperative tumor bed frozen margin sampling and main specimen permanent margin assessment. Multivariate analysis of the data set to predict LR and OS was performed. Results Independent predictors of LR included nodal involvement, histologic grade, and main specimen permanent margin status. Specifically, the presence of a positive margin (odds ratio, 6.21; 95% CI, 3.3-11.9) or <1-mm/carcinoma in situ margin (odds ratio, 2.41; 95% CI, 1.19-4.87) on the main specimen was an independent predictor of LR, whereas intraoperative tumor bed margins were not predictive of LR on multivariate analysis. Similarly, independent predictors of OS on multivariate analysis included nodal involvement, extracapsular extension, and a positive main specimen margin. Tumor bed margins did not independently predict OS. Conclusion The main specimen margin is a strong independent predictor of LR and OS on multivariate analysis. Intraoperative tumor bed frozen margins do not independently predict prognosis. We conclude that emphasis should be placed on evaluating the main specimen margins when estimating prognosis after OCSCC resection.

Metabonomics revealed xanthine oxidase-induced oxidative stress and inflammation in the pathogenesis of diabetic nephropathy.

PubMed

Liu, Jingping; Wang, Chengshi; Liu, Fang; Lu, Yanrong; Cheng, Jingqiu

2015-03-01

Diabetic nephropathy (DN) is a serious complication of diabetes mellitus (DM), which is a major public health problem in the world. To reveal the metabolic changes associated with DN, we analyzed the serum, urine, and renal extracts obtained from control and streptozotocin (STZ)-induced DN rats by (1)H NMR-based metabonomics and multivariate data analysis. A significant difference between control and DN rats was revealed in metabolic profiles, and we identified several important DN-related metabolites including increased levels of allantoin and uric acid (UA) in the DN rats, suggesting that disturbed purine metabolism may be involved in the DN. Combined with conventional histological and biological methods, we further demonstrated that xanthine oxidase (XO), a key enzyme for purine catabolism, was abnormally activated in the kidney of diabetic rats by hyperglycemia. The highly activated XO increased the level of intracellular ROS, which caused renal injury by direct oxidative damage to renal cells, and indirect inducing inflammatory responses via activating NF-κB signaling pathway. Our study highlighted that metabonomics is a promising tool to reveal the metabolic changes and the underlying mechanism involved in the pathogenesis of DN.

[Relations between problems on sleeping and suicidal behaviors in middle school students].

PubMed

Chen, Jing; Wan, Yuhui; Sun, Ying; Tao, Fangbiao

2014-02-01

To understand the epidemiological characteristics and possible associations between sleeping problems and suicidal behaviors among middle school students. A total of 13 817 middle school students were selected in Shenyang,Xinxiang, Chongqing and Guangzhou cities and cluster sampling method was used. Questionnaires would include information on demographics, quality of sleep, psychopathological status and suicidal behaviors. Pittsburgh Sleep Quality index (PSQI) and Adolescent Multidimensional Sub-health Questionnaire (MSQA) were used to assess the quality of sleep and psychosomatic symptoms, respectively. Rates on sleeping problems and suicidal behaviors were compared in students with specific characteristics. Effects related to sleeping problems and suicidal behaviors were analyzed, using the multivariate logistic regression model. The overall prevalence of problems related to sleeping among middle school students was 26.5%. 28.2% of the girls and 35.2% of senior students reported as having more sleeping problems. Rates on suicide related ideation, planning and attempts were 16.6%, 9.6% and 4.7% , respectively. Girls reported more suicide ideation than boys. However, no gender differences were found in suicide planning or attempted suicide. It also suggested that the incidence of the suicidal behavior among students with sleeping problems was significantly higher than students without sleeping problems. Data from Multivariable logistic regression analysis showed that sleeping problems appeared as independent risk factors on suicidal behavior. Higher PSQI scores seemed coincide with the increased risk of suicidal behaviors. Students having sleeping time less than 5 hours per day showed higher risk of suicidal behaviors. Problems on sleeping seemed a strong risk factor for suicidal behaviors among middle school students. Improvement on the quality of sleep and reasonable arrangement of sleeping time could help prevent related suicidal behaviors among middle school students.

Problem drinking is associated with increased prevalence of sexual risk behaviors among men who have sex with men (MSM) in Lima, Peru.

PubMed

Deiss, Robert G; Clark, Jesse L; Konda, Kelika A; Leon, Segundo R; Klausner, Jeffrey D; Caceres, Carlos F; Coates, Thomas J

2013-09-01

Alcohol use is an important but understudied HIV risk factor among men who have sex with men (MSM), particularly in Latin America. We studied the relationship between problem drinking and sexual risk among MSM in Lima, Peru. We recruited 718 participants from 24 neighborhoods for a study on sexually transmitted infections and community-building among MSM. Multivariate analysis was used to identify factors independently associated with problem drinking, which was defined via the CAGE Questionnaire. Of 718 participants, 58% met criteria for problem drinking. In univariate analysis, problem drinkers were significantly more likely to report failing to always use condoms, use alcohol or drugs prior to their most recent sexual encounter, report a history of sexual coercion and to engage in transactional sex. Problem drinkers also reported significantly higher numbers of recent and lifetime sexual partners. In multivariate analysis, factors independently associated with problem drinking included a history of sexual coercion [OR 1.8 95%, CI 1.2-2.6], having consumed alcohol prior to the most recent sexual encounter [OR 2.1 95%, CI 1.5-2.9], receiving compensation for sex in the last six months [OR 1.6, 95% CI 1.1-2.2] or having reported a prior HIV+ test [OR 0.5, 95% CI 0.2-0.9]. We found a high prevalence of problem drinking among MSM in Lima, Peru, which was associated with increased sexual risk in our study. Of note, individuals who were already HIV-infected were less likely to be problem drinkers. Further studies and targeted interventions to reduce problem drinking among MSM are warranted. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Visualization of diversity in large multivariate data sets.

PubMed

Pham, Tuan; Hess, Rob; Ju, Crystal; Zhang, Eugene; Metoyer, Ronald

2010-01-01

Understanding the diversity of a set of multivariate objects is an important problem in many domains, including ecology, college admissions, investing, machine learning, and others. However, to date, very little work has been done to help users achieve this kind of understanding. Visual representation is especially appealing for this task because it offers the potential to allow users to efficiently observe the objects of interest in a direct and holistic way. Thus, in this paper, we attempt to formalize the problem of visualizing the diversity of a large (more than 1000 objects), multivariate (more than 5 attributes) data set as one worth deeper investigation by the information visualization community. In doing so, we contribute a precise definition of diversity, a set of requirements for diversity visualizations based on this definition, and a formal user study design intended to evaluate the capacity of a visual representation for communicating diversity information. Our primary contribution, however, is a visual representation, called the Diversity Map, for visualizing diversity. An evaluation of the Diversity Map using our study design shows that users can judge elements of diversity consistently and as or more accurately than when using the only other representation specifically designed to visualize diversity.

Clustering Multivariate Time Series Using Hidden Markov Models

PubMed Central

Ghassempour, Shima; Girosi, Federico; Maeder, Anthony

2014-01-01

In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers. PMID:24662996

MEMD-enhanced multivariate fuzzy entropy for the evaluation of complexity in biomedical signals.

PubMed

Azami, Hamed; Smith, Keith; Escudero, Javier

2016-08-01

Multivariate multiscale entropy (mvMSE) has been proposed as a combination of the coarse-graining process and multivariate sample entropy (mvSE) to quantify the irregularity of multivariate signals. However, both the coarse-graining process and mvSE may not be reliable for short signals. Although the coarse-graining process can be replaced with multivariate empirical mode decomposition (MEMD), the relative instability of mvSE for short signals remains a problem. Here, we address this issue by proposing the multivariate fuzzy entropy (mvFE) with a new fuzzy membership function. The results using white Gaussian noise show that the mvFE leads to more reliable and stable results, especially for short signals, in comparison with mvSE. Accordingly, we propose MEMD-enhanced mvFE to quantify the complexity of signals. The characteristics of brain regions influenced by partial epilepsy are investigated by focal and non-focal electroencephalogram (EEG) time series. In this sense, the proposed MEMD-enhanced mvFE and mvSE are employed to discriminate focal EEG signals from non-focal ones. The results demonstrate the MEMD-enhanced mvFE values have a smaller coefficient of variation in comparison with those obtained by the MEMD-enhanced mvSE, even for long signals. The results also show that the MEMD-enhanced mvFE has better performance to quantify focal and non-focal signals compared with multivariate multiscale permutation entropy.

Quantum Attack-Resistent Certificateless Multi-Receiver Signcryption Scheme

PubMed Central

Li, Huixian; Chen, Xubao; Pang, Liaojun; Shi, Weisong

2013-01-01

The existing certificateless signcryption schemes were designed mainly based on the traditional public key cryptography, in which the security relies on the hard problems, such as factor decomposition and discrete logarithm. However, these problems will be easily solved by the quantum computing. So the existing certificateless signcryption schemes are vulnerable to the quantum attack. Multivariate public key cryptography (MPKC), which can resist the quantum attack, is one of the alternative solutions to guarantee the security of communications in the post-quantum age. Motivated by these concerns, we proposed a new construction of the certificateless multi-receiver signcryption scheme (CLMSC) based on MPKC. The new scheme inherits the security of MPKC, which can withstand the quantum attack. Multivariate quadratic polynomial operations, which have lower computation complexity than bilinear pairing operations, are employed in signcrypting a message for a certain number of receivers in our scheme. Security analysis shows that our scheme is a secure MPKC-based scheme. We proved its security under the hardness of the Multivariate Quadratic (MQ) problem and its unforgeability under the Isomorphism of Polynomials (IP) assumption in the random oracle model. The analysis results show that our scheme also has the security properties of non-repudiation, perfect forward secrecy, perfect backward secrecy and public verifiability. Compared with the existing schemes in terms of computation complexity and ciphertext length, our scheme is more efficient, which makes it suitable for terminals with low computation capacity like smart cards. PMID:23967037

Modeling of turbulent supersonic H2-air combustion with a multivariate beta PDF

NASA Technical Reports Server (NTRS)

Baurle, R. A.; Hassan, H. A.

1993-01-01

Recent calculations of turbulent supersonic reacting shear flows using an assumed multivariate beta PDF (probability density function) resulted in reduced production rates and a delay in the onset of combustion. This result is not consistent with available measurements. The present research explores two possible reasons for this behavior: use of PDF's that do not yield Favre averaged quantities, and the gradient diffusion assumption. A new multivariate beta PDF involving species densities is introduced which makes it possible to compute Favre averaged mass fractions. However, using this PDF did not improve comparisons with experiment. A countergradient diffusion model is then introduced. Preliminary calculations suggest this to be the cause of the discrepancy.

The Effects of Perceptions of Organizational Structure on Job Involvement, Job Satisfaction, and Organizational Commitment Among Indian Police Officers.

PubMed

Lambert, Eric G; Qureshi, Hanif; Klahm, Charles; Smith, Brad; Frank, James

2017-12-01

Successful police organizations rely on involved, satisfied, and committed workers. The concepts of job involvement (i.e., connection with the job), job satisfaction (i.e., affective feeling toward the job), and organizational commitment (i.e., bond with the employing organization) have been shown to significantly affect intentions and behaviors of employees. The current study used multivariate ordinary least squares (OLS) regression analysis on survey results from a sample of 827 Indian police officers to explore how perceptions of work environment factors affect officers' job involvement, job satisfaction, and organizational commitment. Organizational support, formalization (i.e., level of codified written rules and guidelines), promotional opportunities, institutional communication (i.e., salient work information is transmitted), and input into decision-making (i.e., having a voice in the process) significantly influenced the job involvement, job satisfaction, and organizational commitment of Indian police officers. Specifically, in the multivariate analysis, perceptions of formalization and instrumental communication had a positive relationship with job involvement; perceptions of organizational support, promotional opportunities, instrumental communication, and input into decision-making had positive associations with job satisfaction; and perceptions of organizational support, formalization, promotional opportunities, instrumental communication, and input into decision-making had positive relationships with organizational commitment.

A Multivariate Methodological Workflow for the Analysis of FTIR Chemical Mapping Applied on Historic Paint Stratigraphies

PubMed Central

Sciutto, Giorgia; Oliveri, Paolo; Catelli, Emilio; Bonacini, Irene

2017-01-01

In the field of applied researches in heritage science, the use of multivariate approach is still quite limited and often chemometric results obtained are often underinterpreted. Within this scenario, the present paper is aimed at disseminating the use of suitable multivariate methodologies and proposes a procedural workflow applied on a representative group of case studies, of considerable importance for conservation purposes, as a sort of guideline on the processing and on the interpretation of this FTIR data. Initially, principal component analysis (PCA) is performed and the score values are converted into chemical maps. Successively, the brushing approach is applied, demonstrating its usefulness for a deep understanding of the relationships between the multivariate map and PC score space, as well as for the identification of the spectral bands mainly involved in the definition of each area localised within the score maps. PMID:29333162

Quantitative investigation of inappropriate regression model construction and the importance of medical statistics experts in observational medical research: a cross-sectional study.

PubMed

Nojima, Masanori; Tokunaga, Mutsumi; Nagamura, Fumitaka

2018-05-05

To investigate under what circumstances inappropriate use of 'multivariate analysis' is likely to occur and to identify the population that needs more support with medical statistics. The frequency of inappropriate regression model construction in multivariate analysis and related factors were investigated in observational medical research publications. The inappropriate algorithm of using only variables that were significant in univariate analysis was estimated to occur at 6.4% (95% CI 4.8% to 8.5%). This was observed in 1.1% of the publications with a medical statistics expert (hereinafter 'expert') as the first author, 3.5% if an expert was included as coauthor and in 12.2% if experts were not involved. In the publications where the number of cases was 50 or less and the study did not include experts, inappropriate algorithm usage was observed with a high proportion of 20.2%. The OR of the involvement of experts for this outcome was 0.28 (95% CI 0.15 to 0.53). A further, nation-level, analysis showed that the involvement of experts and the implementation of unfavourable multivariate analysis are associated at the nation-level analysis (R=-0.652). Based on the results of this study, the benefit of participation of medical statistics experts is obvious. Experts should be involved for proper confounding adjustment and interpretation of statistical models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Weighty Problems: Predictors of Family Physicians Documenting Overweight and Obesity.

PubMed

Cyr, Peggy R; Haskins, Amy E; Holt, Christina; Hanifi, Jasmine

2016-03-01

Documenting obesity on the problem list has been shown to promote action about obesity and overweight, yet a majority of primary care providers do not record obesity on the medical problem list. With this in mind, our objectives were to determine the proportion of physicians' documentation of overweight (OW) or obesity on the problem list in our primary care teaching practice and to identify predictors of physician documentation of OW/obesity. De-identified health records of 6,195 adult patients with BMI ? 25 kg/m2 seen by a family physician over a 2-year period were included. Using multivariate logistic regression, patient age, BMI, gender, race, insurance, comorbidities, number of visits, physician gender or role, and practice site (suburban versus urban) were examined in relation to inclusion of OW/obesity on the medical problem list. Few (21.1%) patients had OW/obesity on their problem list. In the multivariate model, female PCPs were significantly more likely to document OW/obesity (OR=1.39, 95% CI=1.18--1.63) compared to male PCPs, and faculty were 26% more likely to document obesity (95% CI=1.07--1.48) compared to residents. Female patients, those with hypertension, diabetes, hyperlipidemia, and those with six or more visits were significantly more likely to have obesity on their problem lists, while patients with Medicaid were less likely to have obesity recorded. No significant difference was seen by race. Nearly 80% of OW and obese patients were not identified on the problem list. Patient gender, comorbidity, and number of visits were associated with documentation. Future research should examine automatic documentation of OW/obesity on the medical problem list.

Childhood Internalizing and Externalizing Problems Predict the Onset of Clinical Panic Attacks over Adolescence: The TRAILS Study

PubMed Central

Mathyssek, Christina M.; Olino, Thomas M.; Verhulst, Frank C.; van Oort, Floor V. A.

2012-01-01

Background Panic attacks are a source of individual suffering and are an independent risk factor for later psychopathology. However, much less is known about risk factors for the development of panic attacks, particularly during adolescence when the incidence of panic attacks increases dramatically. We examined whether internalizing and externalizing problems in childhood predict the onset of panic attacks in adolescence. Method This study is part of the TRacking Adolescents’ Individual Lives Survey (TRAILS), a Dutch longitudinal population cohort study (N = 1,584). Internalizing and Externalizing Problems were collected using the Youth Self-Report (YSR) and the parent-report Child Behavior Checklist (CBCL) at baseline (age 10–12). At age 18–20, DSM-IV defined panic attacks since baseline were assessed with the Composite International Diagnostic Interview (CIDI). We investigated whether early adolescent Internalizing and Externalizing Problems predicted panic attacks between ages 10–20 years, using survival analysis in univariate and multivariate models. Results There were N = 314 (19.8%) cases who experienced at least one DSM-IV defined panic attack during adolescence and N = 18 (1.2%) who developed panic disorder during adolescence. In univariate analyses, CBCL Total Problems, Internalizing Problems and three of the eight syndrome scales predicted panic attack onset, while on the YSR all broad-band problem scales and each narrow-band syndrome scale predicted panic attack onset. In multivariate analyses, CBCL Social Problems (HR 1.19, p<.05), and YSR Thought Problems (HR 1.15, p<.05) and Social Problems (HR 1.26, p<.01) predicted panic attack onset. Conclusion Risk indicators of panic attack include the wide range of internalizing and externalizing problems. Yet, when adjusted for co-occurring problem behaviors, Social Problems were the most consistent risk factor for panic attack onsets in adolescence. PMID:23251576

Prevalence and Psychosocial Correlates of Party-Drug Use and Associated Problems among University Students in the Netherlands.

PubMed

Kunst, Laura E; Gebhardt, Winifred A

2018-04-18

Recent developments in drug use patterns call for an investigation of current party-drug use and associated problems among college students, who appear to be an important target population for harm reduction interventions. In addition to reporting on party-drug use prevalence, we investigated whether initial use and continuation of party-drug use among students was associated with demographic, personality and psychosocial factors. An online questionnaire was administered to 446 students from a Dutch university, inquiring about party-drug use, demographic characteristics, social norms and personality (big five, impulsiveness, aggression). Univariate and multivariate bootstrapped linear regression analyses were used. Of all students, 22.9% indicated having used party-drugs at least once, with a notable sex difference (39.2% of men vs. 16.2% of women). In contrast to the reported trends in Dutch nightlife, GHB was used rarely (lifetime 1.6%) and new psychoactive substances (NPS; 6.7%) appeared almost equally popular as amphetamines (7.6%) and cocaine (7%). Mild health/psychosocial problems (e.g., doing embarrassing things, feeling unwell) were common (65%), whereas serious problems (e.g., being hospitalized) were rare. Neuroticism, extraversion, conscientiousness and impulsiveness were associated with lifetime but not regular party-drug use. Of all predictors, lifetime and regular party-drug use were most strongly related to lenient injunctive and descriptive norms in friends, and a low motivation to comply with parents. Our findings indicate that harm reduction/preventive interventions might profit from focusing on social norms, and targeting students who are highly involved in a pro-party-drug environment while experiencing less parental influence.

A multiresolution approach for the convergence acceleration of multivariate curve resolution methods.

PubMed

Sawall, Mathias; Kubis, Christoph; Börner, Armin; Selent, Detlef; Neymeyr, Klaus

2015-09-03

Modern computerized spectroscopic instrumentation can result in high volumes of spectroscopic data. Such accurate measurements rise special computational challenges for multivariate curve resolution techniques since pure component factorizations are often solved via constrained minimization problems. The computational costs for these calculations rapidly grow with an increased time or frequency resolution of the spectral measurements. The key idea of this paper is to define for the given high-dimensional spectroscopic data a sequence of coarsened subproblems with reduced resolutions. The multiresolution algorithm first computes a pure component factorization for the coarsest problem with the lowest resolution. Then the factorization results are used as initial values for the next problem with a higher resolution. Good initial values result in a fast solution on the next refined level. This procedure is repeated and finally a factorization is determined for the highest level of resolution. The described multiresolution approach allows a considerable convergence acceleration. The computational procedure is analyzed and is tested for experimental spectroscopic data from the rhodium-catalyzed hydroformylation together with various soft and hard models. Copyright © 2015 Elsevier B.V. All rights reserved.

Coping with post-war mental health problems among survivors of violence in Northern Uganda: Findings from the WAYS study.

PubMed

Amone-P'Olak, Kennedy; Omech, Bernard

2018-05-01

Cognitive emotion regulation strategies and mental health problems were assessed in a sample of war-affected youth in Northern Uganda. Univariable and multivariable regression models were fitted to assess the influence of CERS on mental health problems. Maladaptive cognitive emotion regulation strategies (e.g., rumination) were significantly associated with more mental health problems while adaptive cognitive emotion regulation strategies (e.g., putting into perspective) were associated with reporting fewer symptoms of mental health problems. The youth with significant scores on mental health problems (scores ≥ 85th percentile) reported more frequent use of maladaptive than adaptive strategies. Interventions to reduce mental health problems should focus on enhancing the use of adaptive strategies.

Solution of nonlinear multivariable constrained systems using a gradient projection digital algorithm that is insensitive to the initial state

NASA Technical Reports Server (NTRS)

Hargrove, A.

1982-01-01

Optimal digital control of nonlinear multivariable constrained systems was studied. The optimal controller in the form of an algorithm was improved and refined by reducing running time and storage requirements. A particularly difficult system of nine nonlinear state variable equations was chosen as a test problem for analyzing and improving the controller. Lengthy analysis, modeling, computing and optimization were accomplished. A remote interactive teletype terminal was installed. Analysis requiring computer usage of short duration was accomplished using Tuskegee's VAX 11/750 system.

Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery.

PubMed

Liu, Han; Wang, Lie; Zhao, Tuo

2015-08-01

We propose a calibrated multivariate regression method named CMR for fitting high dimensional multivariate regression models. Compared with existing methods, CMR calibrates regularization for each regression task with respect to its noise level so that it simultaneously attains improved finite-sample performance and tuning insensitiveness. Theoretically, we provide sufficient conditions under which CMR achieves the optimal rate of convergence in parameter estimation. Computationally, we propose an efficient smoothed proximal gradient algorithm with a worst-case numerical rate of convergence O (1/ ϵ ), where ϵ is a pre-specified accuracy of the objective function value. We conduct thorough numerical simulations to illustrate that CMR consistently outperforms other high dimensional multivariate regression methods. We also apply CMR to solve a brain activity prediction problem and find that it is as competitive as a handcrafted model created by human experts. The R package camel implementing the proposed method is available on the Comprehensive R Archive Network http://cran.r-project.org/web/packages/camel/.

Approximating Multilinear Monomial Coefficients and Maximum Multilinear Monomials in Multivariate Polynomials

NASA Astrophysics Data System (ADS)

Chen, Zhixiang; Fu, Bin

This paper is our third step towards developing a theory of testing monomials in multivariate polynomials and concentrates on two problems: (1) How to compute the coefficients of multilinear monomials; and (2) how to find a maximum multilinear monomial when the input is a ΠΣΠ polynomial. We first prove that the first problem is #P-hard and then devise a O *(3 n s(n)) upper bound for this problem for any polynomial represented by an arithmetic circuit of size s(n). Later, this upper bound is improved to O *(2 n ) for ΠΣΠ polynomials. We then design fully polynomial-time randomized approximation schemes for this problem for ΠΣ polynomials. On the negative side, we prove that, even for ΠΣΠ polynomials with terms of degree ≤ 2, the first problem cannot be approximated at all for any approximation factor ≥ 1, nor "weakly approximated" in a much relaxed setting, unless P=NP. For the second problem, we first give a polynomial time λ-approximation algorithm for ΠΣΠ polynomials with terms of degrees no more a constant λ ≥ 2. On the inapproximability side, we give a n (1 - ɛ)/2 lower bound, for any ɛ> 0, on the approximation factor for ΠΣΠ polynomials. When the degrees of the terms in these polynomials are constrained as ≤ 2, we prove a 1.0476 lower bound, assuming Pnot=NP; and a higher 1.0604 lower bound, assuming the Unique Games Conjecture.

Testing Mean Differences among Groups: Multivariate and Repeated Measures Analysis with Minimal Assumptions

PubMed Central

Bathke, Arne C.; Friedrich, Sarah; Pauly, Markus; Konietschke, Frank; Staffen, Wolfgang; Strobl, Nicolas; Höller, Yvonne

2018-01-01

ABSTRACT To date, there is a lack of satisfactory inferential techniques for the analysis of multivariate data in factorial designs, when only minimal assumptions on the data can be made. Presently available methods are limited to very particular study designs or assume either multivariate normality or equal covariance matrices across groups, or they do not allow for an assessment of the interaction effects across within-subjects and between-subjects variables. We propose and methodologically validate a parametric bootstrap approach that does not suffer from any of the above limitations, and thus provides a rather general and comprehensive methodological route to inference for multivariate and repeated measures data. As an example application, we consider data from two different Alzheimer’s disease (AD) examination modalities that may be used for precise and early diagnosis, namely, single-photon emission computed tomography (SPECT) and electroencephalogram (EEG). These data violate the assumptions of classical multivariate methods, and indeed classical methods would not have yielded the same conclusions with regards to some of the factors involved. PMID:29565679

Sexual initiation and emotional/behavioral problems in Taiwanese adolescents: a multivariate response profile analysis.

PubMed

Chan, Chia-Hua; Ting, Te-Tien; Chen, Yen-Tyng; Chen, Chuan-Yu; Chen, Wei J

2015-04-01

This study aimed to investigate the relations of adolescent sexual experiences (particularly early initiation) to a spectrum of emotional/behavioral problems and to probe possible gender difference in such relationships. The 10th (N = 8,842) and 12th (N = 10,083) grade students, aged 16-19 years, participating in national surveys in 2005 and 2006 in Taiwan were included for this study. A self-administered web-based questionnaire was designed to collect information on sociodemographic characteristics, sexual experience, substance use, and the Youth Self-Report Form. For the sexually experienced adolescents, their sexual initiation was classified as early initiation (<16 years) or non-early initiation (16-19 years). Gender-specific multivariate response profile regression was used to examine the relationship between sexual experience and the behavioral syndromes. Externalizing problems, including Rule-breaking Behavior and Aggressive Behavior, were strongly associated with sexual initiation in adolescence; the magnitude of the association increased for earlier sexual initiation, especially for females. As to internalizing problems, the connection was rather heterogeneous. The scores on some syndromes, such as Somatic Complaints and Anxious/Depressed, were higher only for females with early or non-early sexual initiation whereas the score on Withdrawn, along with Social Problems that is neither internalizing nor externalizing, was lower for the sexually experienced adolescents than for the sexually inexperienced ones. We concluded that earlier sexual initiation was associated with a wider range of behavioral problems in adolescents for both genders, yet the increased risk with emotional problems was predominately found in females.

Preserving sparseness in multivariate polynominal factorization

NASA Technical Reports Server (NTRS)

Wang, P. S.

1977-01-01

Attempts were made to factor these ten polynomials on MACSYMA. However it did not get very far with any of the larger polynomials. At that time, MACSYMA used an algorithm created by Wang and Rothschild. This factoring algorithm was also implemented for the symbolic manipulation system, SCRATCHPAD of IBM. A closer look at this old factoring algorithm revealed three problem areas, each of which contribute to losing sparseness and intermediate expression growth. This study led to effective ways of avoiding these problems and actually to a new factoring algorithm. The three problems are known as the extraneous factor problem, the leading coefficient problem, and the bad zero problem. These problems are examined separately. Their causes and effects are set forth in detail; the ways to avoid or lessen these problems are described.

Indonesian couple’s pregnancy ambivalence and contraceptive use

PubMed Central

Barden-O'Fallon, Janine L.; Speizer, Ilene S.

2013-01-01

CONTEXT: Recognizing pregnancy ambivalence is important for family planning policy and programming efforts. Most studies on pregnancy ambivalence are based on data from women; using partner’s perceived pregnancy intentions whenever partners are considered. This study examines couple’s pregnancy ambivalence and the association with contraceptive use in Indonesia. METHOD: Matched couple data from the 2002-2003 Indonesia Demographic and Health Survey are used to examine contraceptive use, fertility desires, and responses to whether a pregnancy in the next few weeks would be a big problem, small problem or no problem. Inconsistent fertility desires and responses to the problem question are used to define ambivalence. Response patterns and concordance between partners is evaluated. Multivariate logistic regression analyses are used to assess whether couple’s pregnancy ambivalence is associated with contraceptive use. RESULTS: 71% of husbands and 54% of wives report that a pregnancy in the next few weeks would be “no problem.” Couple’s concordance on the problem question is 63% (kappa statistic = 0.26) among contraceptive users and 61% (0.24) among non-users. In the multivariate analysis, couples who were discordant on the problem question were 24% less likely to use contraception than were couples in which both partners agreed a pregnancy would be a big or small problem. Results were not statistically significant at p≥0.05 in a model with a disaggregated variable on couple’s discordance that identified which partner was ambivalent; this might be related to small cell sizes. Contraceptive use was also less likely for couples with discordant fertility desires. CONCLUSION: Husbands and wives influence each other’s fertility attitudes and family planning use. To improve effective contraceptive use and/or continuation, couple’s pregnancy attitudes should be taken into account at the time of screening and method selection. PMID:20403804

Analysis of Family Functioning and Parent-Child Relationship between Adolescents with Depression and their Parents.

PubMed

Chen, Qing; DU, Wenyong; Gao, Yan; Ma, Changlin; Ban, Chunxia; Meng, Fu

2017-12-25

Drug therapy combined with family therapy is currently the best treatment for adolescent depression. Nevertheless, family therapy requires an exploration of unresolved problems in the family system, which in practice presents certain difficulties. Previous studies have found that the perceptual differences of family function between parents and children reflect the problems in the family system. To explore the characteristics and role of family functioning and parent-child relationship between adolescents with depressive disorder and their parents. The general information and clinical data of the 93 adolescents with depression were collected. The Family Functioning Assessment Scale and Parent-child Relationship Scale were used to assess adolescents with depressive disorder and their parents. a) The dimensions of family functioning in adolescents with depressive disorder were more negative in communication, emotional response, emotional involvement, roles, and overall functioning than their parents. The differences were statistically significant. Parent-child relationship dimensions: the closeness and parent-child total scores were more negative compared with the parents and the differences were statistically significant. b) All dimensions of parent-child relationship and family functioning in adolescents with depression except the time spent together were negatively correlated or significantly negatively correlated. c) The results of multivariate regression analysis showed: the characteristics of family functioning, emotional involvement, emotional response, family structure, and income of the adolescents with depressive disorder mainly affected the parent-child relationship. There were perceptual differences in partial family functioning and parent-child relationship between adolescents with depressive disorder and their parents. Unclear roles between family members, mutual entanglement, too much or too little emotional investment, negligence of inner feelings, parental divorce, and low average monthly family income were the main factors causing adverse parent-child relationship. These perceptual differences have a relatively good predictive effect on family problems, and can be used as an important guide for exploring the family relationship in family therapy.

Analysis of Family Functioning and Parent-Child Relationship between Adolescents with Depression and their Parents

PubMed Central

CHEN, Qing; DU, Wenyong; GAO, Yan; MA, Changlin; BAN, Chunxia; MENG, Fu

2017-01-01

Background Drug therapy combined with family therapy is currently the best treatment for adolescent depression. Nevertheless, family therapy requires an exploration of unresolved problems in the family system, which in practice presents certain difficulties. Previous studies have found that the perceptual differences of family function between parents and children reflect the problems in the family system. Aims To explore the characteristics and role of family functioning and parent-child relationship between adolescents with depressive disorder and their parents. Methods The general information and clinical data of the 93 adolescents with depression were collected. The Family Functioning Assessment Scale and Parent-child Relationship Scale were used to assess adolescents with depressive disorder and their parents. Results a) The dimensions of family functioning in adolescents with depressive disorder were more negative in communication, emotional response, emotional involvement, roles, and overall functioning than their parents. The differences were statistically significant. Parent-child relationship dimensions: the closeness and parent-child total scores were more negative compared with the parents and the differences were statistically significant. b) All dimensions of parent-child relationship and family functioning in adolescents with depression except the time spent together were negatively correlated or significantly negatively correlated. c) The results of multivariate regression analysis showed: the characteristics of family functioning, emotional involvement, emotional response, family structure, and income of the adolescents with depressive disorder mainly affected the parent-child relationship. Conclusions There were perceptual differences in partial family functioning and parent-child relationship between adolescents with depressive disorder and their parents. Unclear roles between family members, mutual entanglement, too much or too little emotional investment, negligence of inner feelings, parental divorce, and low average monthly family income were the main factors causing adverse parent-child relationship. These perceptual differences have a relatively good predictive effect on family problems, and can be used as an important guide for exploring the family relationship in family therapy. PMID:29719348

Dental avoidance behaviour in parent and child as risk indicators for caries in 5-year-old children.

PubMed

Wigen, Tove I; Skaret, Erik; Wang, Nina J

2009-11-01

The aim of this study was to explore associations between avoidance behaviour and dental anxiety in both parents and children and caries experience in 5-year-old children. It was hypothesised that parents' dental avoidance behaviour and dental anxiety were related to dental caries in 5-year-old children. Data were collected from dental records and by clinical and radiographic examination of 523 children. The parents completed a questionnaire regarding education, national background, dental anxiety, dental attendance, and behaviour management problems. Bivariate and multivariate logistic regression was conducted. Children having one or more missed dental appointments (OR = 4.7), child behaviour management problems (OR = 3.3), child dental anxiety (OR = 3.1), and parents avoiding dental care (OR = 2.1) were bivariately associated with caries experience at the age of 5 years. In multivariate logistic regression, having one or more missed dental appointments (OR = 4.0) and child behaviour management problems (OR = 2.4) were indicators for dental caries in 5-year-old children, when controlling for parents education and national origin. Parents that avoid bringing their child to scheduled dental appointments and previous experiences of behaviour management problems for the child indicated risk for dental caries in 5-year-old children.

The Prognostic Value of Varying Definitions of Positive Resection Margin in Patients with Colorectal Cancer Liver Metastases.

PubMed

Wang, Jane; Margonis, Georgios Antonios; Amini, Neda; Andreatos, Nikolaos; Yuan, Chunhui; Damaskos, Christos; Antoniou, Efstathios; Garmpis, Nikolaos; Buettner, Stefan; Barbon, Carlotta; Deshwar, Amar; He, Jin; Burkhart, Richard; Pawlik, Timothy M; Wolfgang, Christopher L; Weiss, Matthew J

2018-04-09

Varying definitions of resection margin clearance are currently employed among patients with colorectal cancer liver metastases (CRLM). Specifically, a microscopically positive margin (R1) has alternatively been equated with an involved margin (margin width = 0 mm) or a margin width < 1 mm. Consequently, patients with a margin width of 0-1 mm (sub-mm) are inconsistently classified in either the R0 or R1 categories, thus obscuring the prognostic implications of sub-mm margins. Six hundred thirty-three patients who underwent resection of CRLM were identified. Both R1 definitions were alternatively employed and multivariable analysis was used to determine the predictive power of each definition, as well as the prognostic implications of a sub-mm margin. Five hundred thirty-nine (85.2%) patients had a margin width ≥ 1 mm, 42 had a sub-mm margin width, and 52 had an involved margin (0 mm). A margin width ≥ 1 mm was associated with improved survival vs. a sub-mm margin (65 vs. 36 months; P = 0.03) or an involved margin (65 vs. 33 months; P < 0.001). No significant difference in survival was detected between patients with involved vs. sub-mm margins (P = 0.31). A sub-mm margin and an involved margin were both independent predictors of worse OS (HR 1.66, 1.04-2.67; P = 0.04, and HR 2.14, 1.46-3.16; P < 0.001, respectively) in multivariable analysis. Importantly, after combining the two definitions, patients with either an involved margin or a sub-mm margin were associated with worse OS in multivariable analysis (HR 1.94, 1.41-2.65; P < 0.001). Patients with involved or sub-mm margins demonstrated a similar inferior OS vs. patients with a margin width > 1 mm. Consequently, a uniform definition of R1 as a margin width < 1 mm should perhaps be employed by future studies.

Cognitive Development of Toddlers: Does Parental Stimulation Matter?

PubMed

Malhi, Prahbhjot; Menon, Jagadeesh; Bharti, Bhavneet; Sidhu, Manjit

2018-02-01

To examine the impact of quality of early stimulation on cognitive functioning of toddlers living in a developing country. The developmental functioning of 150 toddlers in the age range of 12-30 mo (53% boys; Mean = 1.76 y, SD = 0.48) was assessed by the mental developmental index of the Developmental Assessment Scale for Indian Infants (DASII). The StimQ questionnaire- toddler version was used to measure cognitive stimulation at home. The questionnaire consists of four subscales including availability of learning materials (ALM), reading activities (READ), parent involvement in developmental activities (PIDA), and parent verbal responsivity (PVR). Multivariate regression analysis was used to predict cognitive scores using demographic (age of child), socio-economic status (SES) (income, parental education), and home environment (subscale scores of StimQ) as independent variables. Mean Mental Development Index (MDI) score was 91.5 (SD = 13.41), nearly one-fifth (17.3%) of the toddlers had MDI scores less than 80 (cognitive delay). Children with cognitive delay, relative to typically developing (TD, MDI score ≥ 80) cohort of toddlers, had significantly lower scores on all the subscales of StimQ and the total StimQ score. Despite the overall paucity of learning materials available to toddlers, typical developing toddlers were significantly more likely to have access to symbolic toys (P = 0.004), art materials (P = 0.032), adaptive/fine motor toys (P = 0.018), and life size toys (P = 0.036). Multivariate regression analysis results indicated that controlling for confounding socio-economic status variables, higher parental involvement in developmental activities (PIDA score) and higher parental verbal responsivity (PVR score) emerged as significant predictors of higher MDI scores and explained 34% of variance in MDI scores (F = 23.66, P = 0.001). Disparities in child development emerge fairly early and these differences are not all linked to economic disparities. There is a need to develop evidence-based parenting interventions for primary prevention of developmental problems, especially in resource poor countries.

Adolescent Bullying Involvement and Perceived Family, Peer and School Relations: Commonalities and Differences Across Race/Ethnicity

PubMed Central

Spriggs, Aubrey L.; Iannotti, Ronald J.; Nansel, Tonja R.; Haynie, Denise L.

2007-01-01

Purpose Although bullying is recognized as a serious problem in the U.S., little is known about racial/ethnic differences in bullying risk. This study examined associations between bullying and family, peer, and school relations for White, Black and Hispanic adolescents. Methods A nationally-representative sample (n=11,033) of adolescents in grades six to ten participated in the 2001 Health Behaviors in School-Aged Children survey, self-reporting bullying involvement and information on family, peer and school relations. Descriptive statistics and multinomial logistic regression analyses controlling for gender, age and affluence were stratified by race/ethnicity. Results Nine percent of respondents were victims of bullying, 9% were bullies, and 3% were bully-victims. Black adolescents reported a significantly lower prevalence of victimization than White and Hispanic students. Multivariate results indicated modest racial/ethnic variation in associations between bullying and family, peer and school factors. Parental communication, social isolation, and classmate relationships were similarly related to bullying across racial/ethnic groups. Living with two biological parents was protective against bullying involvement for White students only. Further, although school satisfaction and performance were negatively associated with bullying involvement for White and Hispanic students, school factors were largely unrelated to bullying among Black students. Conclusions Although school attachment and performance were inconsistently related to bullying behavior across race/ethnicity, bullying behaviors are consistently related to peer relationships across Black, White and Hispanic adolescents. Negative associations between family communication and bullying behaviors for White, Black and Hispanic adolescents suggest the importance of addressing family interactions in future bullying prevention efforts. PMID:17707299

Adolescent bullying involvement and perceived family, peer and school relations: commonalities and differences across race/ethnicity.

PubMed

Spriggs, Aubrey L; Iannotti, Ronald J; Nansel, Tonja R; Haynie, Denise L

2007-09-01

Although bullying is recognized as a serious problem in the United States, little is known about racial/ethnic differences in bullying risk. This study examined associations between bullying and family, peer, and school relations for white, black and Hispanic adolescents. A nationally representative sample (n = 11,033) of adolescents in grades six to ten participated in the 2001 Health Behaviors in School-Aged Children survey, self-reporting bullying involvement and information on family, peer and school relations. Descriptive statistics and multinomial logistic regression analyses controlling for gender, age and affluence were stratified by race/ethnicity. Nine percent of respondents were victims of bullying, 9% were bullies, and 3% were bully-victims. Black adolescents reported a significantly lower prevalence of victimization than white and Hispanic students. Multivariate results indicated modest racial/ethnic variation in associations between bullying and family, peer, and school factors. Parental communication, social isolation, and classmate relationships were similarly related to bullying across racial/ethnic groups. Living with two biological parents was protective against bullying involvement for white students only. Furthermore, although school satisfaction and performance were negatively associated with bullying involvement for white and Hispanic students, school factors were largely unrelated to bullying among black students. Although school attachment and performance were inconsistently related to bullying behavior across race/ethnicity, bullying behaviors are consistently related to peer relationships across black, white, and Hispanic adolescents. Negative associations between family communication and bullying behaviors for white, black, and Hispanic adolescents suggest the importance of addressing family interactions in future bullying prevention efforts.

Anger expression, violent behavior, and symptoms of depression among male college students in Ethiopia

PubMed Central

Terasaki, Dale J; Gelaye, Bizu; Berhane, Yemane; Williams, Michelle A

2009-01-01

Background Depression is an important global public health problem. Given the scarcity of studies involving African youths, this study was conducted to evaluate the associations of anger expression and violent behavior with symptoms of depression among male college students. Methods A self-administered questionnaire was used to collect information on socio-demographic and lifestyle characteristics and violent behavior among 1,176 college students in Awassa, Ethiopia in June, 2006. The questionnaire incorporated the Spielberger Anger-Out Expression (SAOE) scale and symptoms of depression were evaluated using the Patient Health Questionnaire (PHQ-9). Multivariable logistic regression procedures were used to calculate adjusted odds ratios (OR) and 95% confidence intervals (95%CI). Results Symptoms of depression were evident in 23.6% of participants. Some 54.3% of students reported committing at least one act of violence in the current academic year; and 29.3% of students reported high (SAOE score ≥ 15) levels of anger-expression. In multivariate analysis, moderate (OR = 1.97; 95%CI 1.33–2.93) and high (OR = 3.23; 95%CI 2.14–4.88) outward anger were statistically significantly associated with increased risks of depressive symptoms. Violent behavior was noted to be associated with depressive symptoms (OR = 1.82; 95%CI 1.37–2.40). Conclusion Further research should be conducted to better characterize community and individual level determinants of anger-expression, violent behavior and depression among youths. PMID:19138431

Aboriginal Street-involved Youth Experience Elevated Risk of Incarceration

PubMed Central

Barker, Brittany; Alfred, Gerald Taiaiake; Fleming, Kim; Nguyen, Paul; Wood, Evan; Kerr, Thomas; DeBeck, Kora

2015-01-01

Objectives Past research has identified risk factors associated with incarceration among adult Aboriginal populations; however, less is known about incarceration among street-involved Aboriginal youth. Therefore, we undertook this study to longitudinally investigate recent reports of incarceration among a prospective cohort of street-involved youth in Vancouver, Canada. Study Design Prospective cohort study. Methods Data were collected from a cohort of street-involved, drug-using youth from September 2005 to May 2013. Multivariate generalized estimating equation analyses were employed to examine the potential relationship between Aboriginal ancestry and recent incarceration. Results Among our sample of 1050 youth, 248 (24%) reported being of aboriginal ancestry, and 378 (36%) reported being incarcerated in the previous six months at some point during the study period. In multivariate analysis controlling for a range of potential confounders including drug use patterns and other risk factors, Aboriginal ancestry remained significantly associated with recent incarceration (adjusted odds ratio [AOR]=1.44; 95% confidence interval [CI]: 1.12–1.86). Conclusions Even after adjusting for drug use patterns and other risk factors associated with incarceration, this study found that Aboriginal street-involved youth were still significantly more likely to be incarcerated than their non-Aboriginal peers. Given the established harms associated with incarceration these findings underscore the pressing need for systematic reform including culturally appropriate interventions to prevent Aboriginal youth from becoming involved with the criminal justice system. PMID:26390949

Antimicrobial Resistance: The Major Contribution of Poor Governance and Corruption to This Growing Problem

PubMed Central

Collignon, Peter; Athukorala, Prema-chandra; Senanayake, Sanjaya; Khan, Fahad

2015-01-01

Objectives To determine how important governmental, social, and economic factors are in driving antibiotic resistance compared to the factors usually considered the main driving factors—antibiotic usage and levels of economic development. Design A retrospective multivariate analysis of the variation of antibiotic resistance in Europe in terms of human antibiotic usage, private health care expenditure, tertiary education, the level of economic advancement (per capita GDP), and quality of governance (corruption). The model was estimated using a panel data set involving 7 common human bloodstream isolates and covering 28 European countries for the period 1998–2010. Results Only 28% of the total variation in antibiotic resistance among countries is attributable to variation in antibiotic usage. If time effects are included the explanatory power increases to 33%. However when the control of corruption indicator is included as an additional variable, 63% of the total variation in antibiotic resistance is now explained by the regression. The complete multivariate regression only accomplishes an additional 7% in terms of goodness of fit, indicating that corruption is the main socioeconomic factor that explains antibiotic resistance. The income level of a country appeared to have no effect on resistance rates in the multivariate analysis. The estimated impact of corruption was statistically significant (p< 0.01). The coefficient indicates that an improvement of one unit in the corruption indicator is associated with a reduction in antibiotic resistance by approximately 0.7 units. The estimated coefficient of private health expenditure showed that one unit reduction is associated with a 0.2 unit decrease in antibiotic resistance. Conclusions These findings support the hypothesis that poor governance and corruption contributes to levels of antibiotic resistance and correlate better than antibiotic usage volumes with resistance rates. We conclude that addressing corruption and improving governance will lead to a reduction in antibiotic resistance. PMID:25786027

The importance of building construction materials relative to other factors affecting structure survival during wildfire

USGS Publications Warehouse

Syphard, Alexandra D.; Brennan, Teresa J.; Keeley, Jon E.

2017-01-01

Structure loss to wildfire is a serious problem in wildland-urban interface areas across the world. Laboratory experiments suggest that fire-resistant building construction and design could be important for reducing structure destruction, but these need to be evaluated under real wildfire conditions, especially relative to other factors. Using empirical data from destroyed and surviving structures from large wildfires in southern California, we evaluated the relative importance of building construction and structure age compared to other local and landscape-scale variables associated with structure survival. The local-scale analysis showed that window preparation was especially important but, in general, creating defensible space adjacent to the home was as important as building construction. At the landscape scale, structure density and structure age were the two most important factors affecting structure survival, but there was a significant interaction between them. That is, young structure age was most important in higher-density areas where structure survival overall was more likely. On the other hand, newer-construction structures were less likely to survive wildfires at lower density. Here, appropriate defensible space near the structure and accessibility to major roads were important factors. In conclusion, community safety is a multivariate problem that will require a comprehensive solution involving land use planning, fire-safe construction, and property maintenance.

Selection of Sustainable Processes using Sustainability ...

EPA Pesticide Factsheets

Chemical products can be obtained by process pathways involving varying amounts and types of resources, utilities, and byproduct formation. When such competing process options such as six processes for making methanol as are considered in this study, it is necessary to identify the most sustainable option. Sustainability of a chemical process is generally evaluated with indicators that require process and chemical property data. These indicators individually reflect the impacts of the process on areas of sustainability, such as the environment or society. In order to choose among several alternative processes an overall comparative analysis is essential. Generally net profit will show the most economic process. A mixed integer optimization problem can also be solved to identify the most economic among competing processes. This method uses economic optimization and leaves aside the environmental and societal impacts. To make a decision on the most sustainable process, the method presented here rationally aggregates the sustainability indicators into a single index called sustainability footprint (De). Process flow and economic data were used to compute the indicator values. Results from sustainability footprint (De) are compared with those from solving a mixed integer optimization problem. In order to identify the rank order of importance of the indicators, a multivariate analysis is performed using partial least square variable importance in projection (PLS-VIP)

A complementary measure of heterogeneity on mathematical skills

NASA Astrophysics Data System (ADS)

Fedriani, Eugenio M.; Moyano, Rafael

2012-06-01

Finding educational truths is an inherently multivariate problem. There are many factors affecting each student and their performances. Because of this, both measuring of skills and assessing students are always complex processes. This is a well-known problem, and a number of solutions have been proposed by specialists. One of its ramifications is that the variety of progress levels of students in the Mathematics classroom makes teaching more difficult. We think that a measure of the heterogeneity of the different student groups could be interesting in order to prepare some strategies to deal with these kinds of difficulties. The major aim of this study is to develop new tools, complementary to the statistical ones that are commonly used for these purposes, to study situations related to education (mainly to the detection of levels of mathematical education) in which several variables are involved. These tools are thought to simplify these educational analyses and, through a better comprehension of the topic, to improve our teaching. Several authors in our research group have developed some mathematical, theoretical tools, to deal with multidimensional phenomena, and have applied them to measure poverty and also to other business models. These tools are based on multidigraphs. In this article, we implement these tools using symbolic computational software and apply them to study a specific situation related to mathematical education.

Robust Nonlinear Causality Analysis of Nonstationary Multivariate Physiological Time Series.

PubMed

Schack, Tim; Muma, Michael; Feng, Mengling; Guan, Cuntai; Zoubir, Abdelhak M

2018-06-01

An important research area in biomedical signal processing is that of quantifying the relationship between simultaneously observed time series and to reveal interactions between the signals. Since biomedical signals are potentially nonstationary and the measurements may contain outliers and artifacts, we introduce a robust time-varying generalized partial directed coherence (rTV-gPDC) function. The proposed method, which is based on a robust estimator of the time-varying autoregressive (TVAR) parameters, is capable of revealing directed interactions between signals. By definition, the rTV-gPDC only displays the linear relationships between the signals. We therefore suggest to approximate the residuals of the TVAR process, which potentially carry information about the nonlinear causality by a piece-wise linear time-varying moving-average model. The performance of the proposed method is assessed via extensive simulations. To illustrate the method's applicability to real-world problems, it is applied to a neurophysiological study that involves intracranial pressure, arterial blood pressure, and brain tissue oxygenation level (PtiO2) measurements. The rTV-gPDC reveals causal patterns that are in accordance with expected cardiosudoral meachanisms and potentially provides new insights regarding traumatic brain injuries. The rTV-gPDC is not restricted to the above problem but can be useful in revealing interactions in a broad range of applications.

Relationship between sickness presenteeism and awareness and presence or absence of systems for return to work among workers with mental health problems in Japan: an Internet-based cross-sectional study.

PubMed

Doki, Shotaro; Sasahara, Shinichiro; Suzuki, Shun; Hirai, Yasuhito; Oi, Yuichi; Usami, Kazuya; Matsuzaki, Ichiyo

2015-01-01

The objective of this study was to clarify the relationship between sickness presenteeism and the degree of awareness of company regulations regarding financial compensation for absenteeism. An Internet-based survey of 258 full-time workers who had more than 28 days of sickness absence due to mental health problems was conducted. Workers were categorized as having either low or high sickness presenteeism, and awareness and presence or absence of systems for return to work and duration of financial compensation were compared between groups. The following factors were significantly related to high sickness presenteeism based on logistic regression analyses: working for a private company (odds ratio [OR]=2.57; 95% confidence interval [CI]=1.10-5.99); recognition of a gradual resumption system (OR=3.89, 95% CI=1.02-14.81); and awareness regarding the duration of financial compensation (OR=1.04, 95% CI=1.01-1.07). No relationship was found between mental sickness presenteeism and presence or absence of systems for return to work in our multivariate analysis; however, a relationship was apparent between sickness presenteeism and characteristics of the workers' companies. These results are expected to contribute to research involving human resources and occupational health.

Interpersonal violence among women seeking welfare: unraveling lives.

PubMed

Lown, E Anne; Schmidt, Laura A; Wiley, James

2006-08-01

Exposure to violence is a widespread problem among women who receive welfare benefits. Research has focused on partner violence among women with children on Temporary Assistance for Needy Families (TANF), ignoring low-income women without dependent children who are eligible for General Assistance (GA). We report findings from a survey of 1235 women seeking TANF (N=1095) and GA (N=140) throughout a California county. Estimates of recent physical, sexual, and severe violence were high in both populations. However, the highest rates occurred among women without children seeking GA, suggesting that they are at higher risk for sexual violence and more severe forms of physical violence, especially from intimate partners. This increased risk is partly accounted for by the co-occurrence of other serious health and social problems. In multivariate analyses, past-year violence was associated with substance use (adjusted odds ratio [AOR]=2.0, 95% confidence interval [CI] = 1.5, 2.9), recent homelessness (AOR = 1.9, 95% CI = 1.4, 2.6), family fragmentation including divorce or separation (AOR=3.1, 95% CI 1.8, 5.2), or foster care involvement (AOR=2.2, 95% CI=1.1, 4.5) Welfare reform created TANF programs to address domestic violence. Women seeking GA may need similar services because of the high prevalence of violence.

Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record

NASA Astrophysics Data System (ADS)

Relan, Rishi; Tiels, Koen; Marconato, Anna; Dreesen, Philippe; Schoukens, Johan

2018-05-01

Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. In this paper, a methodology to identify a parsimonious discrete-time nonlinear state space model (NLSS) for the nonlinear dynamical system with relatively short data record is proposed. The capability of the NLSS model structure is demonstrated by introducing two different initialisation schemes, one of them using multivariate polynomials. In addition, a method using first-order information of the multivariate polynomials and tensor decomposition is employed to obtain the parsimonious decoupled representation of the set of multivariate real polynomials estimated during the identification of NLSS model. Finally, the experimental verification of the model structure is done on the cascaded water-benchmark identification problem.

Multivariable bio-inspired photonic sensors for non-condensable gases

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Karker, Nicholas; Carpenter, Michael A.; Minnick, Andrew

2018-02-01

Existing gas sensors often lose their measurement accuracy in practical field applications. To mitigate this significant problem, here, we report a demonstration of fabricated multivariable photonic sensors inspired by a known nanostructure of Morpho butterfly scales for detection of exemplary non-condensable gases such as H2, CO, and CO2. We fabricated bio-inspired nanostructures using conventional photolithography and chemical etching and detected individual gases that were difficult or unrealistic to detect using natural Morpho nanostructures. Such bio-inspired gas sensors are the critical step in the development of new sensors with improved accuracy for diverse operational scenarios. While this report is our initial demonstration of responses of fabricated multivariable sensors to individual gases in pristine laboratory conditions, it is a significant milestone in understanding the next steps toward field tests and practical applications of these sensors.

Expression of Tissue Factor in Epithelial Ovarian Carcinoma Is Involved in the Development of Venous Thromboembolism.

PubMed

Sakurai, Manabu; Matsumoto, Koji; Gosho, Masahiko; Sakata, Akiko; Hosokawa, Yoshihiko; Tenjimbayashi, Yuri; Katoh, Takashi; Shikama, Ayumi; Komiya, Haruna; Michikami, Hiroo; Tasaka, Nobutaka; Akiyama-Abe, Azusa; Nakao, Sari; Ochi, Hiroyuki; Onuki, Mamiko; Minaguchi, Takeo; Yoshikawa, Hiroyuki; Satoh, Toyomi

2017-01-01

Our 2007 study of 32 patients with ovarian cancer reported the possible involvement of tissue factor (TF) in the development of venous thromboembolism (VTE) before treatment, especially in clear cell carcinoma (CCC). This follow-up study further investigated this possibility in a larger cohort. We investigated the intensity of TF expression (ITFE) and other variables for associations with VTE using univariate and multivariate analyses in 128 patients with epithelial ovarian cancer initially treated between November 2004 and December 2010, none of whom had received neoadjuvant chemotherapy. Before starting treatment, all patients were ultrasonographically screened for VTE. The ITFE was graded based on immunostaining of surgical specimens. Histological types were serous carcinoma (n = 42), CCC (n = 12), endometrioid carcinoma (n = 15), mucinous carcinoma (n = 53), and undifferentiated carcinoma (n = 6). The prevalence of VTE was significantly higher in CCC (34%) than in non-CCC (17%, P = 0.03). As ITFE increased, the frequencies of CCC and VTE increased significantly (P < 0.001 and P = 0.014, respectively). Multivariate analysis identified TF expression and pretreatment dimerized plasmin fragment D level as significant independent risk factors for VTE development. These factors showed particularly strong impacts on advanced-stage disease (P = 0.021). The 2007 cohort was small, preventing multivariate analysis. This study of a larger cohort yielded stronger evidence that the development of VTE in epithelial ovarian cancer may involve TF expression in cancer tissues.

Escaping the snare of chronological growth and launching a free curve alternative: general deviance as latent growth model.

PubMed

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating "protective" or "launch" factors or as "developmental snares." These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of "general deviance" over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the "general deviance" model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of "general deviance" can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the "snares" alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control.

Escaping the snare of chronological growth and launching a free curve alternative: General deviance as latent growth model

PubMed Central

WOOD, PHILLIP KARL; JACKSON, KRISTINA M.

2014-01-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating “protective” or “launch” factors or as “developmental snares.” These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of “general deviance” over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the “general deviance” model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of “general deviance” can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the “snares” alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control. PMID:23880389

Child Involvement in Interparental Conflict and Child Adjustment Problems: A Longitudinal Study of Violent Families

PubMed Central

Jouriles, Ernest N.; Rosenfield, David; McDonald, Renee; Mueller, Victoria

2014-01-01

This study examined whether child involvement in interparental conflict predicts child externalizing and internalizing problems in violent families. Participants were 119 families (mothers and children) recruited from domestic violence shelters. One child between the ages of 7 and 10 years in each family (50 female, 69 male) completed measures of involvement in their parents’ conflicts, externalizing problems, and internalizing problems. Mothers completed measures of child externalizing and internalizing problems, and physical intimate partner violence. Measures were completed at three assessments, spaced 6 months apart. Results indicated that children’s involvement in their parents’ conflicts was positively associated with child adjustment problems. These associations emerged in between-subjects and within-subjects analyses, and for child externalizing as well as internalizing problems, even after controlling for the influence of physical intimate partner violence. In addition, child involvement in parental conflicts predicted later child reports of externalizing problems, but child reports of externalizing problems did not predict later involvement in parental conflicts. These findings highlight the importance of considering children’s involvement in their parents’ conflicts in theory and clinical work pertaining to high-conflict families. PMID:24249486

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

Lindorff, D. P.; Carroll, R. L.

1973-01-01

A survey of the literature in which Liapunov's second method is used in determining the control law is presented, with emphasis placed on the model-tracking adaptive control problem. Forty references are listed. Following a brief tutorial exposition of the adaptive control problem, the techniques for treating reduction of order, disturbance and time-varying parameters, multivariable systems, identification, and adaptive observers are discussed. The method is critically evaluated, particularly with respect to possibilities for application.

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

PubMed

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

2015-09-01

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

Association between school bullying levels/types and mental health problems among Taiwanese adolescents.

PubMed

Yen, Cheng-Fang; Yang, Pinchen; Wang, Peng-Wei; Lin, Huang-Chi; Liu, Tai-Ling; Wu, Yu-Yu; Tang, Tze-Chun

2014-04-01

Few studies have compared the risks of mental health problems among the adolescents with different levels and different types of bullying involvement experiences. Bullying involvement in 6,406 adolescents was determined through use of the Chinese version of the School Bullying Experience Questionnaire. Data were collected regarding the mental health problems, including depression, suicidality, insomnia, general anxiety, social phobia, alcohol abuse, inattention, and hyperactivity/impulsivity. The association between experiences of bullying involvement and mental health problems was examined. The risk of mental health problems was compared among those with different levels/types of bullying involvement. The results found that being a victim of any type of bullying and being a perpetrator of passive bullying were significantly associated with all kinds of mental health problems, and being a perpetrator of active bullying was significantly associated with all kinds of mental health problems except for general anxiety. Victims or perpetrators of both passive and active bullying had a greater risk of some dimensions of mental health problems than those involved in only passive or active bullying. Differences in the risk of mental health problems were also found among adolescents involved in different types of bullying. This difference in comorbid mental health problems should be taken into consideration when assessing adolescents involved in different levels/types of bullying. © 2014.

The Relationship Between Father Involvement and Child Problem Behaviour in Intact Families: A 7-Year Cross-Lagged Study.

PubMed

Flouri, Eirini; Midouhas, Emily; Narayanan, Martina K

2016-07-01

This study investigated the cross-lagged relationship between father involvement and child problem behaviour across early-to-middle childhood, and tested whether temperament modulated any cross-lagged child behaviour effects on father involvement. It used data from the first four waves of the UK's Millennium Cohort Study, when children (50.3 % male) were aged 9 months, and 3, 5 and 7 years. The sample was 8302 families where both biological parents were co-resident across the four waves. Father involvement (participation in play and physical and educational activities with the child) was measured at ages 3, 5 and 7, as was child problem behaviour (assessed with the Strengths and Difficulties Questionnaire). Key child and family covariates related to father involvement and child problem behaviour were controlled. Little evidence was found that more father involvement predicted less child problem behaviour two years later, with the exception of father involvement at child's age 5 having a significant, but small, effect on peer problems at age 7. There were two child effects. More hyperactive children at age 3 had more involved fathers at age 5, and children with more conduct problems at age 3 had more involved fathers at age 5. Child temperament did not moderate any child behaviour effects on father involvement. Thus, in young, intact UK families, child adjustment appears to predict, rather than be predicted by, father involvement in early childhood. When children showed more problematic behaviours, fathers did not become less involved. In fact, early hyperactivity and conduct problems in children seemed to elicit more involvement from fathers. At school age, father involvement appeared to affect children's social adjustment rather than vice versa.

Uncertainty Modeling for Robustness Analysis of Control Upset Prevention and Recovery Systems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.; Khong, Thuan H.; Shin, Jong-Yeob; Kwatny, Harry; Chang, Bor-Chin; Balas, Gary J.

2005-01-01

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems (developed for failure detection, identification, and reconfiguration, as well as upset recovery) need to be evaluated over broad regions of the flight envelope and under extreme flight conditions, and should include various sources of uncertainty. However, formulation of linear fractional transformation (LFT) models for representing system uncertainty can be very difficult for complex parameter-dependent systems. This paper describes a preliminary LFT modeling software tool which uses a matrix-based computational approach that can be directly applied to parametric uncertainty problems involving multivariate matrix polynomial dependencies. Several examples are presented (including an F-16 at an extreme flight condition, a missile model, and a generic example with numerous crossproduct terms), and comparisons are given with other LFT modeling tools that are currently available. The LFT modeling method and preliminary software tool presented in this paper are shown to compare favorably with these methods.

Analysis of the procedures used to evaluate suicide crime scenes in Brazil: a statistical approach to interpret reports.

PubMed

Bruni, Aline Thaís; Velho, Jesus Antonio; Ferreira, Arthur Serra Lopes; Tasso, Maria Júlia; Ferrari, Raíssa Santos; Yoshida, Ricardo Luís; Dias, Marcos Salvador; Leite, Vitor Barbanti Pereira

2014-08-01

This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences. Copyright © 2014 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Personal and Workplace Environmental Factors Associated With Reduced Worker Productivity Among Older Workers With Chronic Knee Pain: A Cross-Sectional Survey.

PubMed

Agaliotis, Maria; Mackey, Martin G; Heard, Robert; Jan, Stephen; Fransen, Marlene

2017-04-01

The aim of this study was to explore personal and workplace environmental factors as predictors of reduced worker productivity among older workers with chronic knee pain. A questionnaire-based survey was conducted among 129 older workers who had participated in a randomized clinical trial evaluating dietary supplements. Multivariable analyses were used to explore predictors of reduced work productivity among older workers with chronic knee pain. The likelihood of presenteeism was higher in those reporting knee pain (≥3/10) or problems with other joints, and lower in those reporting job insecurity. The likelihood of work transitions was higher in people reporting knee pain (≥3/10), a high comorbidity score or low coworker support, and lower in those having an occupation involving sitting more than 30% of the day. Allowing access to sitting and promoting positive affiliations between coworkers are likely to provide an enabling workplace environment for older workers with chronic knee pain.

A dynamic factor model of the evaluation of the financial crisis in Turkey.

PubMed

Sezgin, F; Kinay, B

2010-01-01

Factor analysis has been widely used in economics and finance in situations where a relatively large number of variables are believed to be driven by few common causes of variation. Dynamic factor analysis (DFA) which is a combination of factor and time series analysis, involves autocorrelation matrices calculated from multivariate time series. Dynamic factor models were traditionally used to construct economic indicators, macroeconomic analysis, business cycles and forecasting. In recent years, dynamic factor models have become more popular in empirical macroeconomics. They have more advantages than other methods in various respects. Factor models can for instance cope with many variables without running into scarce degrees of freedom problems often faced in regression-based analysis. In this study, a model which determines the effect of the global crisis on Turkey is proposed. The main aim of the paper is to analyze how several macroeconomic quantities show an alteration before the evolution of the crisis and to decide if a crisis can be forecasted or not.

The prevalence of obesity documentation in Primary Care Electronic Medical Records. Are we acknowledging the problem?

PubMed

Mattar, Ahmed; Carlston, David; Sariol, Glen; Yu, Tongle; Almustafa, Ahmad; Melton, Genevieve B; Ahmed, Adil

2017-01-25

Although obesity is a growing problem, primary care physicians often inadequately address it. The objective of this study is to examine the prevalence of obesity documentation in the patient's problem list for patients with eligible body mass indexes (BMI) as contained in the patients' electronic medical record (EMR). Additionally, we examined the prevalence of selected chronic conditions across BMI levels. This study is a retrospective study using EMR data for adult patients visiting an outpatient clinic between June 2012 and June 2015. International Classification of Diseases, Ninth Revision, (ICD-9) codes were used to identify obesity documentation in the EMR problem list. Univariate and multivariate logistic regression analyses were used. Out of 10,540, a total of 3,868 patients were included in the study. 2,003 (52%) patients met the criteria for obesity (BMI ≥ 30.0); however, only 112 (5.6%) patient records included obesity in the problem list. Moreover, in a multivariate analysis, in addition to age and gender, morbid obesity and cumulative number of comorbidities were significantly associated with obesity documentation, OR=1.6 and OR=1.3, respectively, with 95% CI [1.4, 1.9] and [1.0, 1.7], respectively. For those with obesity documentation, exercise counseling was provided more often than diet counselling. Based on EHR documentation, obesity is under coded and generally not identified as a significant problem in primary care. Physicians are more likely to document obesity in the patient record for those with higher BMI scores who are morbidly obese. Moreover, physicians more frequently provide exercise than diet counseling for the documented obese.

Sexual functioning among early post-treatment breast cancer survivors.

PubMed

Avis, Nancy E; Johnson, Aimee; Canzona, Mollie Rose; Levine, Beverly J

2018-02-17

This study aims (1) to estimate percentages of partnered women who are sexually active over the first 2 years post-breast cancer diagnosis; (2) to identify factors related to sexual inactivity; and (3) to evaluate separately, among both sexually active and inactive survivors, the relation between sexual problems and treatment-related variables, symptoms, and psychosocial factors. Longitudinal observational study of breast cancer survivors recruited within 8 months of cancer diagnosis and followed for 18 months. The main outcome measures were (1) being sexually active/inactive in the past month and (2) sexual problems assessed with the four-item sexual problem domain of the Quality of Life in Adult Cancer Survivors (QLACS) scale. At baseline, 52.4% of women reported being sexually active in the past month. This percentage increased to 60.7% 18 months later. In multivariable repeated-measures analyses, age, past chemotherapy, depressive symptoms, and lower perceived attractiveness were related to inactivity. Sexually inactive women reported more problems on the QLACS than sexually active women. In stratified multivariable analyses, depressive symptoms were related to greater sexual problems for both sexually active and inactive women, as was vaginal dryness. Among the sexually active women, younger age at diagnosis, less illness intrusiveness, and lower perceived attractiveness were related to more problems. Research has shown that sexual functioning/sexual health are key aspects of quality of life for many cancer survivors, and are often not addressed by health care providers. Future studies should examine how such topics are handled by clinicians in their interactions with survivors.

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

Discordance between net analyte signal theory and practical multivariate calibration.

PubMed

Brown, Christopher D

2004-08-01

Lorber's concept of net analyte signal is reviewed in the context of classical and inverse least-squares approaches to multivariate calibration. It is shown that, in the presence of device measurement error, the classical and inverse calibration procedures have radically different theoretical prediction objectives, and the assertion that the popular inverse least-squares procedures (including partial least squares, principal components regression) approximate Lorber's net analyte signal vector in the limit is disproved. Exact theoretical expressions for the prediction error bias, variance, and mean-squared error are given under general measurement error conditions, which reinforce the very discrepant behavior between these two predictive approaches, and Lorber's net analyte signal theory. Implications for multivariate figures of merit and numerous recently proposed preprocessing treatments involving orthogonal projections are also discussed.

Reduced Circumferential Resection Margin Involvement in Rectal Cancer Surgery: Results of the Dutch Surgical Colorectal Audit.

PubMed

Gietelink, Lieke; Wouters, Michel W J M; Tanis, Pieter J; Deken, Marion M; Ten Berge, Martijn G; Tollenaar, Rob A E M; van Krieken, J Han; de Noo, Mirre E

2015-09-01

The circumferential resection margin (CRM) is a significant prognostic factor for local recurrence, distant metastasis, and survival after rectal cancer surgery. Therefore, availability of this parameter is essential. Although the Dutch total mesorectal excision trial raised awareness about CRM in the late 1990s, quality assurance on pathologic reporting was not available until the Dutch Surgical Colorectal Audit (DSCA) started in 2009. The present study describes the rates of CRM reporting and involvement since the start of the DSCA and analyzes whether improvement of these parameters can be attributed to the audit. Data from the DSCA (2009-2013) were analyzed. Reporting of CRM and CRM involvement was plotted for successive years, and variations of these parameters were analyzed in a funnelplot. Predictors of CRM involvement were determined in univariable analysis and the independent influence of year of registration on CRM involvement was analyzed in multivariable analysis. A total of 12,669 patients were included for analysis. The mean percentage of patients with a reported CRM increased from 52.7% to 94.2% (2009-2013) and interhospital variation decreased. The percentage of patients with CRM involvement decreased from 14.2% to 5.6%. In multivariable analysis, the year of DSCA registration remained a significant predictor of CRM involvement. After the introduction of the DSCA, a dramatic improvement in CRM reporting and a major decrease of CRM involvement after rectal cancer surgery have occurred. This study suggests that a national quality assurance program has been the driving force behind these achievements. Copyright © 2015 by the National Comprehensive Cancer Network.

Corporal punishment and youth externalizing behavior in Santiago, Chile.

PubMed

Ma, Julie; Han, Yoonsun; Grogan-Kaylor, Andrew; Delva, Jorge; Castillo, Marcela

2012-06-01

Corporal punishment is still widely practiced around the globe, despite the large body of child development research that substantiates its short- and long-term consequences. Within this context, this paper examined the relationship between parental use of corporal punishment and youth externalizing behavior with a Chilean sample to add to the growing empirical evidence concerning the potential relationship between increased corporal punishment and undesirable youth outcomes across cultures. Analysis was based on 919 adolescents in Santiago, Chile. Descriptive and multivariate analyses were conducted to examine the extent to which parents' use of corporal punishment and positive family measures were associated with youth externalizing behavior. Furthermore, the associations between self-reported externalizing behavior and infrequent, as well as frequent, use of corporal punishment were investigated to understand how varying levels of parental use of corporal punishment were differently related to youth outcomes. Both mothers' and fathers' use of corporal punishment were associated with greater youth externalizing behavior. Additionally, increases in positive parenting practices, such as parental warmth and family involvement, were met with decreases in youth externalizing behavior when controlling for youth demographics, family socioeconomic status, and parents' use of corporal punishment. Finally, both infrequent and frequent use of corporal punishment were positively associated with higher youth problem behaviors, though frequent corporal punishment had a stronger relationship with externalizing behavior than did infrequent corporal punishment. Parental use of corporal punishment, even on an occasional basis, is associated with greater externalizing behavior for youth while a warm and involving family environment may protect youth from serious problem behaviors. Therefore, findings of this study add to the growing evidence concerning the negative consequences of corporal punishment for youth outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Corporal Punishment and Youth Externalizing Behavior in Santiago, Chile

PubMed Central

Ma, Julie; Han, Yoonsun; Grogan-Kaylor, Andrew; Delva, Jorge; Castillo, Marcela

2012-01-01

Objectives Corporal punishment is still widely practiced around the globe, despite the large body of child development research that substantiates its short- and long-term consequences. Within this context, this paper examined the relationship between parental use of corporal punishment and youth externalizing behavior with a Chilean sample to add to the growing empirical evidence concerning the potential relationship between increased corporal punishment and undesirable youth outcomes across cultures. Methods Analysis was based on 919 adolescents in Santiago, Chile. Descriptive and multivariate analyses were conducted to examine the extent to which parents’ use of corporal punishment and positive family measures were associated with youth externalizing behavior. Furthermore, the associations between self-reported externalizing behavior and infrequent, as well as frequent, use of corporal punishment were investigated to contribute to understanding how varying levels of parental use of corporal punishment were differently related to youth outcomes. Results Both mother’s and father’s use of corporal punishment were associated with greater youth externalizing behavior. Additionally, increases in positive parenting practices, such as parental warmth and family involvement, were met with decreases in youth externalizing behavior when controlling for youth demographics, family socioeconomic status, and parents’ use of corporal punishment. Finally, both infrequent and frequent use of corporal punishment were positively associated with higher youth problem behaviors, though frequent corporal punishment had a stronger relationship with externalizing behavior than did infrequent corporal punishment. Conclusions Parental use of corporal punishment, even on an occasional basis, is associated with greater externalizing behavior for youth while a warm and involving family environment may protect youth from serious problem behaviors. Therefore, findings of this study add to the growing evidence concerning the negative consequences of corporal punishment for youth outcomes. PMID:22766372

Factors associated with perceived health among 12-year-old school children. Relevance of physical exercise and sense of coherence.

PubMed

Honkinen, Päivi-Leena K; Suominen, Sakari B; Välimaa, Raili S; Helenius, Hans Y; Rautava, Päivi T

2005-01-01

Poor perceived health during childhood may affect an individual's well-being throughout life. In adult studies, sense of coherence (SOC) has been shown to be associated with perceived health. The aim of this study was to determine which factors with an emphasis on SOC and physical exercise were associated with perceived health among 12-year-old children. A total of 1,231 12-year-old school children (83%) completed a questionnaire. Most of the 37 questions had multiple-choice types of response. The questions were largely based on those used in the Health Behaviour in School-aged Children (HBSC) study coordinated by the WHO. SOC was determined using the 13-item scale developed by Antonovsky. Factors used in calculating performance at school were marks (given by the teachers, range 4-10, 10 being the best) in mathematics, native language, and first foreign language. Statistical analysis involved the use of logistic regression models and the so-called generalized estimation technique because of the multi-level study design. In a multivariate model adjusted for reported psychosomatic symptoms, insufficient physical exercise was clearly (OR 4.6) associated with poor perceived health. Other variables with significant associations (OR 1.4-1.7) were a mark below 9 in mathematics, belonging to the weakest SOC tertile, reporting of problems of perceived support from teachers, and reporting of various problems involving the class climate. Among the studied variables physical exercise was the most strongly associated with perceived health, even when several social and psychological risk factors were included in the analysis. SOC and variables of social support were also of importance.

MToS: A Tree of Shapes for Multivariate Images.

PubMed

Carlinet, Edwin; Géraud, Thierry

2015-12-01

The topographic map of a gray-level image, also called tree of shapes, provides a high-level hierarchical representation of the image contents. This representation, invariant to contrast changes and to contrast inversion, has been proved very useful to achieve many image processing and pattern recognition tasks. Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images. Common workarounds, such as marginal processing, or imposing a total order on data, are not satisfactory and yield many problems. This paper presents a method to build a tree-based representation of multivariate images, which features marginally the same properties of the gray-level tree of shapes. Briefly put, we do not impose an arbitrary ordering on values, but we only rely on the inclusion relationship between shapes in the image definition domain. The interest of having a contrast invariant and self-dual representation of multivariate image is illustrated through several applications (filtering, segmentation, and object recognition) on different types of data: color natural images, document images, satellite hyperspectral imaging, multimodal medical imaging, and videos.

Hypersonic vehicle model and control law development using H(infinity) and micron synthesis

NASA Astrophysics Data System (ADS)

Gregory, Irene M.; Chowdhry, Rajiv S.; McMinn, John D.; Shaughnessy, John D.

1994-10-01

The control system design for a Single Stage To Orbit (SSTO) air breathing vehicle will be central to a successful mission because a precise ascent trajectory will preserve narrow payload margins. The air breathing propulsion system requires the vehicle to fly roughly halfway around the Earth through atmospheric turbulence. The turbulence, the high sensitivity of the propulsion system to inlet flow conditions, the relatively large uncertainty of the parameters characterizing the vehicle, and continuous acceleration make the problem especially challenging. Adequate stability margins must be provided without sacrificing payload mass since payload margins are critical. Therefore, a multivariable control theory capable of explicitly including both uncertainty and performance is needed. The H(infinity) controller in general provides good robustness but can result in conservative solutions for practical problems involving structured uncertainty. Structured singular value mu framework for analysis and synthesis is potentially much less conservative and hence more appropriate for problems with tight margins. An SSTO control system requires: highly accurate tracking of velocity and altitude commands while limiting angle-of-attack oscillations, minimized control power usage, and a stabilized vehicle when atmospheric turbulence and system uncertainty are present. The controller designs using H(infinity) and mu-synthesis procedures were compared. An integrated flight/propulsion dynamic mathematical model of a conical accelerator vehicle was linearized as the vehicle accelerated through Mach 8. Vehicle acceleration through the selected flight condition gives rise to parametric variation that was modeled as a structured uncertainty. The mu-analysis approach was used in the frequency domain to conduct controller analysis and was confirmed by time history plots. Results demonstrate the inherent advantages of the mu framework for this class of problems.

Hypersonic vehicle model and control law development using H(infinity) and micron synthesis

NASA Technical Reports Server (NTRS)

Gregory, Irene M.; Chowdhry, Rajiv S.; Mcminn, John D.; Shaughnessy, John D.

1994-01-01

The control system design for a Single Stage To Orbit (SSTO) air breathing vehicle will be central to a successful mission because a precise ascent trajectory will preserve narrow payload margins. The air breathing propulsion system requires the vehicle to fly roughly halfway around the Earth through atmospheric turbulence. The turbulence, the high sensitivity of the propulsion system to inlet flow conditions, the relatively large uncertainty of the parameters characterizing the vehicle, and continuous acceleration make the problem especially challenging. Adequate stability margins must be provided without sacrificing payload mass since payload margins are critical. Therefore, a multivariable control theory capable of explicitly including both uncertainty and performance is needed. The H(infinity) controller in general provides good robustness but can result in conservative solutions for practical problems involving structured uncertainty. Structured singular value mu framework for analysis and synthesis is potentially much less conservative and hence more appropriate for problems with tight margins. An SSTO control system requires: highly accurate tracking of velocity and altitude commands while limiting angle-of-attack oscillations, minimized control power usage, and a stabilized vehicle when atmospheric turbulence and system uncertainty are present. The controller designs using H(infinity) and mu-synthesis procedures were compared. An integrated flight/propulsion dynamic mathematical model of a conical accelerator vehicle was linearized as the vehicle accelerated through Mach 8. Vehicle acceleration through the selected flight condition gives rise to parametric variation that was modeled as a structured uncertainty. The mu-analysis approach was used in the frequency domain to conduct controller analysis and was confirmed by time history plots. Results demonstrate the inherent advantages of the mu framework for this class of problems.

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes.

PubMed

Motegi, Hiromi; Tsuboi, Yuuri; Saga, Ayako; Kagami, Tomoko; Inoue, Maki; Toki, Hideaki; Minowa, Osamu; Noda, Tetsuo; Kikuchi, Jun

2015-11-04

There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.

Anxiety after completion of treatment for early-stage breast cancer: a systematic review to identify candidate predictors and evaluate multivariable model development.

PubMed

Harris, Jenny; Cornelius, Victoria; Ream, Emma; Cheevers, Katy; Armes, Jo

2017-07-01

The purpose of this review was to identify potential candidate predictors of anxiety in women with early-stage breast cancer (BC) after adjuvant treatments and evaluate methodological development of existing multivariable models to inform the future development of a predictive risk stratification model (PRSM). Databases (MEDLINE, Web of Science, CINAHL, CENTRAL and PsycINFO) were searched from inception to November 2015. Eligible studies were prospective, recruited women with stage 0-3 BC, used a validated anxiety outcome ≥3 months post-treatment completion and used multivariable prediction models. Internationally accepted quality standards were used to assess predictive risk of bias and strength of evidence. Seven studies were identified: five were observational cohorts and two secondary analyses of RCTs. Variability of measurement and selective reporting precluded meta-analysis. Twenty-one candidate predictors were identified in total. Younger age and previous mental health problems were identified as risk factors in ≥3 studies. Clinical variables (e.g. treatment, tumour grade) were not identified as predictors in any studies. No studies adhered to all quality standards. Pre-existing vulnerability to mental health problems and younger age increased the risk of anxiety after completion of treatment for BC survivors, but there was no evidence that chemotherapy was a predictor. Multiple predictors were identified but many lacked reproducibility or were not measured across studies, and inadequate reporting did not allow full evaluation of the multivariable models. The use of quality standards in the development of PRSM within supportive cancer care would improve model quality and performance, thereby allowing professionals to better target support for patients.

Obstructive urination problems after high-dose-rate brachytherapy boost treatment for prostate cancer are avoidable.

PubMed

Kragelj, Borut

2016-03-01

Aiming at improving treatment individualization in patients with prostate cancer treated with combination of external beam radiotherapy and high-dose-rate brachytherapy to boost the dose to prostate (HDRB-B), the objective was to evaluate factors that have potential impact on obstructive urination problems (OUP) after HDRB-B. In the follow-up study 88 patients consecutively treated with HDRB-B at the Institute of Oncology Ljubljana in the period 2006-2011 were included. The observed outcome was deterioration of OUP (DOUP) during the follow-up period longer than 1 year. Univariate and multivariate relationship analysis between DOUP and potential risk factors (treatment factors, patients' characteristics) was carried out by using binary logistic regression. ROC curve was constructed on predicted values and the area under the curve (AUC) calculated to assess the performance of the multivariate model. Analysis was carried out on 71 patients who completed 3 years of follow-up. DOUP was noted in 13/71 (18.3%) of them. The results of multivariate analysis showed statistically significant relationship between DOUP and anti-coagulation treatment (OR 4.86, 95% C.I. limits: 1.21-19.61, p = 0.026). Also minimal dose received by 90% of the urethra volume was close to statistical significance (OR = 1.23; 95% C.I. limits: 0.98-1.07, p = 0.099). The value of AUC was 0.755. The study emphasized the relationship between DOUP and anticoagulation treatment, and suggested the multivariate model with fair predictive performance. This model potentially enables a reduction of DOUP after HDRB-B. It supports the belief that further research should be focused on urethral sphincter as a critical structure for OUP.

Mental health and social competencies of 10- to 12-year-old children born at 23 to 25 weeks of gestation in the 1990s: a Swedish national prospective follow-up study.

PubMed

Farooqi, Aijaz; Hägglöf, Bruno; Sedin, Gunnar; Gothefors, Leif; Serenius, Fredrik

2007-07-01

We investigated a national cohort of extremely immature children with respect to behavioral and emotional problems and social competencies, from the perspectives of parents, teachers, and children themselves. We examined 11-year-old children who were born before 26 completed weeks of gestation in Sweden between 1990 and 1992. All had been evaluated at a corrected age of 36 months. At 11 years of age, 86 of 89 survivors were studied and compared with an equal number of control subjects, matched with respect to age and gender. Behavioral and emotional problems, social competencies, and adaptive functioning at school were evaluated with standardized, well-validated instruments, including parent and teacher report questionnaires and a child self-report, administered by mail. Compared with control subjects, parents of extremely immature children reported significantly more problems with internalizing behaviors (anxiety/depression, withdrawn, and somatic problems) and attention, thought, and social problems. Teachers reported a similar pattern. Reports from children showed a trend toward increased depression symptoms compared with control subjects. Multivariate analysis of covariance of parent-reported behavioral problems revealed no interactions, but significant main effects emerged for group status (extremely immature versus control), family function, social risk, and presence of a chronic medical condition, with all effect sizes being medium and accounting for 8% to 12% of the variance. Multivariate analysis of covariance of teacher-reported behavioral problems showed significant effects for group status and gender but not for the covariates mentioned above. According to the teachers' ratings, extremely immature children were less well adjusted to the school environment than were control subjects. However, a majority of extremely immature children (85%) were functioning in mainstream schools without major adjustment problems. Despite favorable outcomes for many children born at the limit of viability, these children are at risk for mental health problems, with poorer school results.

Dimensions of Problem Drinking among Young Adult Restaurant Workers

PubMed Central

Moore, Roland S.; Cunradi, Carol B.; Duke, Michael R.; Ames, Genevieve M.

2009-01-01

Background Nationwide surveys identify food service workers as heavy alcohol users. Objectives This article analyzes dimensions and correlates of problem drinking among young adult food service workers. Methods A telephone survey of national restaurant chain employees yielded 1294 completed surveys. Results Hazardous alcohol consumption patterns were seen in 80% of men and 64% of women. Multivariate analysis showed that different dimensions of problem drinking measured by the AUDIT were associated with workers' demographic characteristics, smoking behavior and job category. Conclusions & Scientific Significance These findings offer evidence of extremely high rates of alcohol misuse among young adult restaurant workers. PMID:20180660

Farming systems and sanitary problems in mountain cattle farms.

PubMed

Bernúes, A; Manrique, E; Maza, M T

1994-01-01

On the basis of concepts established by ecopathology and the systems theory, certain aspects of the 'Ecosanitary System', which forms part of the 'Farming System', were studied. Multivariant statistical methods were used to analyze and classify 69 mountain cattle farms into different types and to establish relationships between variables relating to pathological problems and others relating to aspects of production and farm structure. Stable mastitis characterized farms with a higher milk production, more intensive farming and greater hygiene measures. The pattern of diarrhoea in the calves was similar. Problems relating to reproduction and calving were more characteristic of traditional, small farms.

The relationship between violence and engagement in drug dealing and sex work among street-involved youth.

PubMed

Hayashi, Kanna; Daly-Grafstein, Ben; Dong, Huiru; Wood, Evan; Kerr, Thomas; DeBeck, Kora

2016-06-27

Street-involved youth are highly vulnerable to violence. While involvement in income-generating activities within illicit drug scenes is recognized as shaping youths' vulnerability to violence, the relative contributions of different income-generating activities remain understudied. We sought to examine the independent effects of drug dealing and sex work on experiencing violence among street-involved youth. Data were derived from a prospective cohort of street-involved youth aged 14-26 who used drugs in Vancouver, British Columbia, between September 2005 and May 2014. Multivariable generalized estimating equations were used to examine the impact of involvement in drug dealing and sex work on experiencing violence. Among 1,152 participants, including 364 (31.6%) women, 740 (64.2%) reported having experienced violence at some point during the study period. In multivariable analysis, involvement in drug dealing but not sex work remained independently associated with experiencing violence among females (adjusted odds ratio [AOR]: 1.43; 95% confidence interval [CI]: 1.08-1.90) and males (AOR: 1.50; 95% CI: 1.25-1.80), while involvement in sex work only was not associated with violence among females (AOR: 1.15; 95% CI: 0.76-1.74) or males (AOR: 1.42; 95% CI: 0.81-2.48). Findings indicate that involvement in drug dealing is a major factor associated with experiencing violence among our sample. In addition to conventional interventions, such as addiction treatment, novel approaches are needed to reduce the risk of violence for drug-using youth who are actively engaged in drug dealing. The potential for low-threshold employment and decriminalization of drug use to mitigate violence warrants further study.

The relationship between violence and engagement in drug dealing and sex work among street-involved youth

PubMed Central

Hayashi, Kanna; Daly-Grafstein, Ben; Dong, Huiru; Wood, Evan; Kerr, Thomas; DeBeck, Kora

2016-01-01

OBJECTIVES Street-involved youth are highly vulnerable to violence. While involvement in income-generating activities within illicit drug scenes are recognized as shaping youths’ vulnerability to violence, the relative contributions of different income-generating activities remain understudied. We sought to examine the independent effects of drug dealing and sex work on experiencing violence among street-involved youth. METHODS Data were derived from a prospective cohort of street-involved youth aged 14–26 who use drugs in Vancouver, Canada, between September 2005 and May 2014. Multivariable generalized estimating equations were used to examine the impact of involvement in drug dealing and sex work on experiencing violence. RESULTS Among 1,152 participants, including 364 (31.6%) women, 740 (64.2%) reported having experienced violence at some point during the study period. In multivariable analysis, involvement in drug dealing but not sex work remained independently associated with experiencing violence among females (adjusted odds ratio [AOR]: 1.43; 95% confidence interval [CI]: 1.08 – 1.90) and males (AOR: 1.50; 95% CI: 1.25 – 1.80), while involvement in sex work only was not associated with violence among females (AOR: 1.15; 95% CI: 0.76 – 1.74) or males (AOR: 1.42; 95% CI: 0.81 – 2.48). CONCLUSION Findings indicate that involvement in drug dealing is a major factor associated with experiencing violence among our sample. In addition to conventional interventions, such as addiction treatment, novel approaches are needed to reduce the risk of violence for drug-using youth who are actively engaged in drug dealing. The potential for low-threshold employment and decriminalization of drug use to mitigate violence warrants further study. PMID:27348116

Applications of numerical optimization methods to helicopter design problems: A survey

NASA Technical Reports Server (NTRS)

Miura, H.

1984-01-01

A survey of applications of mathematical programming methods is used to improve the design of helicopters and their components. Applications of multivariable search techniques in the finite dimensional space are considered. Five categories of helicopter design problems are considered: (1) conceptual and preliminary design, (2) rotor-system design, (3) airframe structures design, (4) control system design, and (5) flight trajectory planning. Key technical progress in numerical optimization methods relevant to rotorcraft applications are summarized.

Applications of numerical optimization methods to helicopter design problems - A survey

NASA Technical Reports Server (NTRS)

Miura, H.

1985-01-01

A survey of applications of mathematical programming methods is used to improve the design of helicopters and their components. Applications of multivariable search techniques in the finite dimensional space are considered. Five categories of helicopter design problems are considered: (1) conceptual and preliminary design, (2) rotor-system design, (3) airframe structures design, (4) control system design, and (5) flight trajectory planning. Key technical progress in numerical optimization methods relevant to rotorcraft applications are summarized.

Applications of numerical optimization methods to helicopter design problems - A survey

NASA Technical Reports Server (NTRS)

Miura, H.

1984-01-01

A survey of applications of mathematical programming methods is used to improve the design of helicopters and their components. Applications of multivariable search techniques in the finite dimensional space are considered. Five categories of helicopter design problems are considered: (1) conceptual and preliminary design, (2) rotor-system design, (3) airframe structures design, (4) control system design, and (5) flight trajectory planning. Key technical progress in numerical optimization methods relevant to rotorcraft applications are summarized.

A computer program to find the kernel of a polynomial operator

NASA Technical Reports Server (NTRS)

Gejji, R. R.

1976-01-01

This paper presents a FORTRAN program written to solve for the kernel of a matrix of polynomials with real coefficients. It is an implementation of Sain's free modular algorithm for solving the minimal design problem of linear multivariable systems. The structure of the program is discussed, together with some features as they relate to questions of implementing the above method. An example of the use of the program to solve a design problem is included.

Critical elements on fitting the Bayesian multivariate Poisson Lognormal model

NASA Astrophysics Data System (ADS)

Zamzuri, Zamira Hasanah binti

2015-10-01

Motivated by a problem on fitting multivariate models to traffic accident data, a detailed discussion of the Multivariate Poisson Lognormal (MPL) model is presented. This paper reveals three critical elements on fitting the MPL model: the setting of initial estimates, hyperparameters and tuning parameters. These issues have not been highlighted in the literature. Based on simulation studies conducted, we have shown that to use the Univariate Poisson Model (UPM) estimates as starting values, at least 20,000 iterations are needed to obtain reliable final estimates. We also illustrated the sensitivity of the specific hyperparameter, which if it is not given extra attention, may affect the final estimates. The last issue is regarding the tuning parameters where they depend on the acceptance rate. Finally, a heuristic algorithm to fit the MPL model is presented. This acts as a guide to ensure that the model works satisfactorily given any data set.

Housing instability and alcohol problems during the 2007-2009 US recession: the moderating role of perceived family support.

PubMed

Murphy, Ryan D; Zemore, Sarah E; Mulia, Nina

2014-02-01

The 2007-2009 US economic recession was marked by unprecedented rates of housing instability and relatively little is known about how this instability impacted alcohol problems. While previous studies have linked homelessness to increased rates of alcohol use and abuse, housing instability during a recession impacts a much larger segment of the population and usually does not result in homelessness. Using a nationally representative sample of US adults, this study examines the association between housing instability during the recession and alcohol outcomes. Additionally, we assess whether this association is moderated by perceived family support. In multivariate negative binomial regressions, both trouble paying the rent/mortgage (vs. stable housing) and lost (vs. stable) housing were associated with experiencing more negative drinking consequences and alcohol dependence symptoms. However, these associations were moderated by perceived family support. In contrast to those with low perceived family support, participants with high perceived family support reported relatively few alcohol problems, irrespective of housing instability. Furthermore, while job loss was strongly associated with alcohol problems in univariate models, no significant associations between job loss and alcohol outcomes were observed in multivariate models that included indicators of housing instability. Findings point to the importance of the informal safety net and suggest that alcohol screening and abuse prevention efforts should be intensified during periods of recession, particularly among those who experience housing instability.

Paternal ADHD symptoms and child conduct problems: is father involvement always beneficial?

PubMed

Romirowsky, A M; Chronis-Tuscano, A

2014-09-01

Maternal psychopathology robustly predicts poor developmental and treatment outcomes for children with attention-deficit/hyperactivity disorder (ADHD). Despite the high heritability of ADHD, few studies have examined associations between paternal ADHD symptoms and child adjustment, and none have also considered degree of paternal involvement in childrearing. Identification of modifiable risk factors for child conduct problems is particularly important in this population given the serious adverse outcomes resulting from this comorbidity. This cross-sectional study examined the extent to which paternal involvement in childrearing moderated the association between paternal ADHD symptoms and child conduct problems among 37 children with ADHD and their biological fathers. Neither paternal ADHD symptoms nor involvement was independently associated with child conduct problems. However, the interaction between paternal ADHD symptoms and involvement was significant, such that paternal ADHD symptoms were positively associated with child conduct problems only when fathers were highly involved in childrearing. The presence of adult ADHD symptoms may determine whether father involvement in childrearing has a positive or detrimental influence on comorbid child conduct problems.

Central nervous system relapse in peripheral T-cell lymphomas: a Swedish Lymphoma Registry study.

PubMed

Ellin, Fredrik; Landström, Jenny; Jerkeman, Mats; Relander, Thomas

2015-07-02

Central nervous system (CNS) relapse in non-Hodgkin lymphoma (NHL) carries a very poor prognosis. Risk factors and outcome have been studied in aggressive B-cell lymphomas, but very little is known about the risk in peripheral T-cell lymphoma (PTCL). We aimed at analyzing risk factors for CNS involvement at first relapse or progression, as well as the outcome of these patients, in a large population-based cohort of patients with PTCL. Twenty-eight out of 625 patients (4.5%) developed CNS disease over time. In multivariable analysis, disease characteristics at diagnosis independently associated with an increased risk for later CNS involvement were involvement of more than 1 extranodal site (hazard ratio [HR], 2.60; 95% confidence interval [CI], 1.07-6.29; P = .035) and skin (HR, 3.51; 95% CI, 1.26-9.74; P = .016) and gastrointestinal involvement (HR, 3.06; 95% CI, 1.30-7.18; P = .010). The outcome of relapsed/refractory patients was very poor, and CNS involvement was not associated with a significantly worse outcome compared with relapsed/refractory patients without CNS involvement in multivariable analysis (HR, 1.6; 95% CI, 0.96-2.6; P = .074). The results from the present study indicate that CNS relapse in PTCL occurs at a frequency similar to what is seen in aggressive B-cell lymphomas, but the poor outcomes in relapse are largely driven by systemic rather than CNS disease. © 2015 by The American Society of Hematology.

The relationship between gambling attitudes, involvement, and problems in adolescence: Examining the moderating role of coping strategies and parenting styles.

PubMed

Dixon, Ramsay W; Youssef, George J; Hasking, Penelope; Yücel, Murat; Jackson, Alun C; Dowling, Nicki A

2016-07-01

Several factors are associated with an increased risk of adolescent problem gambling, including positive gambling attitudes, higher levels of gambling involvement, ineffective coping strategies and unhelpful parenting practices. It is less clear, however, how these factors interact or influence each other in the development of problem gambling behavior during adolescence. The aim of the current study was to simultaneously explore these predictors, with a particular focus on the extent to which coping skills and parenting styles may moderate the expected association between gambling involvement and gambling problems. Participants were 612 high school students. The data were analyzed using a zero-inflated Poisson (ZIP) regression model, controlling for gender. Although several variables predicted the number of symptoms associated with problem gambling, none of them predicted the probability of displaying any problem gambling. Gambling involvement fully mediated the relationship between positive gambling attitudes and gambling problem severity. There was a significant relationship between gambling involvement and problems at any level of problem focused coping, reference to others and inconsistent discipline. However, adaptive coping styles employed by adolescents and consistent disciplinary practices by parents were buffers of gambling problems at low levels of adolescent gambling involvement, but failed to protect adolescents when their gambling involvement was high. These findings indicate that research exploring the development of gambling problems is required and imply that coping and parenting interventions may have particular utility for adolescents who are at risk of development gambling problems but who are not gambling frequently. Copyright © 2016 Elsevier Ltd. All rights reserved.

Self-Regulated Learning Strategies in Relation with Statistics Anxiety

ERIC Educational Resources Information Center

Kesici, Sahin; Baloglu, Mustafa; Deniz, M. Engin

2011-01-01

Dealing with students' attitudinal problems related to statistics is an important aspect of statistics instruction. Employing the appropriate learning strategies may have a relationship with anxiety during the process of statistics learning. Thus, the present study investigated multivariate relationships between self-regulated learning strategies…

Examining substance use and affective processes as multivariate risk factors associated with overweight body mass among treatment-seeking smokers.

PubMed

Farris, Samantha G; Zvolensky, Michael J; Robles, Zuzuky; Schmidt, Norman B

2015-01-01

Cigarette smoking and obesity are two major public health problems. However, factors related to the underlying risk for being overweight are not well established. Certain demographic, smoking, and psychological factors have been linked to overweight/obese body mass. The current study examined a multivariate risk model, stratified by gender, in order to better explicate the nature of overweight body mass among daily smokers. In a sample of treatment-seeking smokers (n = 395), among males and females, (1) older age, (2) stronger expectancies about the weight/appetite control effects of smoking, (3) greater smoking-based inflexibility/avoidance due to smoking-related sensations, and (4) less problematic alcohol use, were associated with being overweight. Additionally, among males, having a tobacco-related medical problem and higher tolerance for physical discomfort aided in the discriminant function model for classifying smokers as overweight. Together, numerous cognitive-affective vulnerabilities and smoking processes may be targetable and potentially inform weight-related prevention programs among smokers.

Robust Multivariable Estimation of the Relevant Information Coming from a Wheel Speed Sensor and an Accelerometer Embedded in a Car under Performance Tests

PubMed Central

Hernandez, Wilmar

2005-01-01

In the present paper, in order to estimate the response of both a wheel speed sensor and an accelerometer placed in a car under performance tests, robust and optimal multivariable estimation techniques are used. In this case, the disturbances and noises corrupting the relevant information coming from the sensors' outputs are so dangerous that their negative influence on the electrical systems impoverish the general performance of the car. In short, the solution to this problem is a safety related problem that deserves our full attention. Therefore, in order to diminish the negative effects of the disturbances and noises on the car's electrical and electromechanical systems, an optimum observer is used. The experimental results show a satisfactory improvement in the signal-to-noise ratio of the relevant signals and demonstrate the importance of the fusion of several intelligent sensor design techniques when designing the intelligent sensors that today's cars need.

The impact on social relationships of moving from congregated settings to personalized accommodation.

PubMed

McConkey, Roy; Bunting, Brendan; Keogh, Fiona; Garcia Iriarte, Edurne

2017-01-01

A natural experiment contrasted the social relationships of people with intellectual disabilities ( n = 110) before and after they moved from congregated settings to either personalized accommodation or group homes. Contrasts could also be drawn with individuals who had enduring mental health problems ( n = 46) and who experienced similar moves. Face-to-face interviews were conducted in each person's residence on two occasions approximately 24 months apart. Multivariate statistical analyses were used to determine significant effects. Greater proportions of people living in personalized settings scored higher on the five chosen indicators of social relationships than did persons living in grouped accommodation. However, multivariate statistical analyses identified that only one in five persons increased their social relationships as a result of changes in their accommodation, particularly persons with an intellectual disability and high support needs. These findings reinforce the extent of social isolation experienced by people with disabilities and mental health problems that changes in their accommodation only partially counter.

Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distribution

PubMed Central

Dinov, Ivo D.; Kamino, Scott; Bhakhrani, Bilal; Christou, Nicolas

2014-01-01

Summary Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students’ understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models. We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference. PMID:25419016

Technology-enhanced Interactive Teaching of Marginal, Joint and Conditional Probabilities: The Special Case of Bivariate Normal Distribution.

PubMed

Dinov, Ivo D; Kamino, Scott; Bhakhrani, Bilal; Christou, Nicolas

2013-01-01

Data analysis requires subtle probability reasoning to answer questions like What is the chance of event A occurring, given that event B was observed? This generic question arises in discussions of many intriguing scientific questions such as What is the probability that an adolescent weighs between 120 and 140 pounds given that they are of average height? and What is the probability of (monetary) inflation exceeding 4% and housing price index below 110? To address such problems, learning some applied, theoretical or cross-disciplinary probability concepts is necessary. Teaching such courses can be improved by utilizing modern information technology resources. Students' understanding of multivariate distributions, conditional probabilities, correlation and causation can be significantly strengthened by employing interactive web-based science educational resources. Independent of the type of a probability course (e.g. majors, minors or service probability course, rigorous measure-theoretic, applied or statistics course) student motivation, learning experiences and knowledge retention may be enhanced by blending modern technological tools within the classical conceptual pedagogical models. We have designed, implemented and disseminated a portable open-source web-application for teaching multivariate distributions, marginal, joint and conditional probabilities using the special case of bivariate Normal distribution. A real adolescent height and weight dataset is used to demonstrate the classroom utilization of the new web-application to address problems of parameter estimation, univariate and multivariate inference.

Interventions aimed at reducing obesity in early childhood: a meta-analysis of programs that involve parents.

PubMed

Yavuz, H Melis; van Ijzendoorn, Marinus H; Mesman, Judi; van der Veek, Shelley

2015-06-01

Obesity is a growing problem even in very young childhood, resulting in high costs for individuals and society. As a response, numerous obesity prevention and intervention programs have been developed. Previous research has shown that early intervention programs are more effective when parents are involved, but the effectiveness of specific aspects of programs with parental involvement has not been investigated. This meta-analysis aims to investigate the features related to the effectiveness of different types of obesity intervention programs involving parents and targeting young children (0-6-year-olds). The Web of Science, PubMed, PsycInfo, CINAHL, and ERIC databases were searched for childhood obesity prevention and intervention programs involving parents. Data were analyzed using the Comprehensive Meta-analysis (CMA) software. Fifty studies with effect sizes measured at short-term follow-up (within 3 months from the end of the intervention) and 26 studies with effect sizes measured at long-term follow-up (all reported in a total of 49 publications) were identified. The combined effect size of interventions was small but significant at short-term follow-up (d = .08, p < .01). The results suggested the presence of a potential publication bias in studies providing results at long-term follow-up, with a nonsignificant adjusted effect size (d = .02), which indicated that obesity interventions were not effective at long-term follow-up. Multivariate meta-regression analyses showed that interventions were more effective when including either interactive sessions or educational materials as opposed to those including both interactive sessions and noninteractive educational materials. No other moderators regarding sample characteristics, study design, or methodological quality were significant. Interventions targeting young children that require parental involvement are effective at short-term follow-up, specifically when interventions include one mode of intervention rather than two. However, results were not retained in the long run. © 2014 Association for Child and Adolescent Mental Health.

Applications of multivariate modeling to neuroimaging group analysis: A comprehensive alternative to univariate general linear model

PubMed Central

Chen, Gang; Adleman, Nancy E.; Saad, Ziad S.; Leibenluft, Ellen; Cox, RobertW.

2014-01-01

All neuroimaging packages can handle group analysis with t-tests or general linear modeling (GLM). However, they are quite hamstrung when there are multiple within-subject factors or when quantitative covariates are involved in the presence of a within-subject factor. In addition, sphericity is typically assumed for the variance–covariance structure when there are more than two levels in a within-subject factor. To overcome such limitations in the traditional AN(C)OVA and GLM, we adopt a multivariate modeling (MVM) approach to analyzing neuroimaging data at the group level with the following advantages: a) there is no limit on the number of factors as long as sample sizes are deemed appropriate; b) quantitative covariates can be analyzed together with within- subject factors; c) when a within-subject factor is involved, three testing methodologies are provided: traditional univariate testing (UVT)with sphericity assumption (UVT-UC) and with correction when the assumption is violated (UVT-SC), and within-subject multivariate testing (MVT-WS); d) to correct for sphericity violation at the voxel level, we propose a hybrid testing (HT) approach that achieves equal or higher power via combining traditional sphericity correction methods (Greenhouse–Geisser and Huynh–Feldt) with MVT-WS. PMID:24954281

Characterizing the Associative Content of Brain Structures Involved in Habitual and Goal-Directed Actions in Humans: A Multivariate fMRI Study

PubMed Central

Liljeholm, Mimi; Zika, Ondrej; O'Doherty, John P.

2015-01-01

While there is accumulating evidence for the existence of distinct neural systems supporting goal-directed and habitual action selection in the mammalian brain, much less is known about the nature of the information being processed in these different brain regions. Associative learning theory predicts that brain systems involved in habitual control, such as the dorsolateral striatum, should contain stimulus and response information only, but not outcome information, while regions involved in goal-directed action, such as ventromedial and dorsolateral prefrontal cortex and dorsomedial striatum, should be involved in processing information about outcomes as well as stimuli and responses. To test this prediction, human participants underwent fMRI while engaging in a binary choice task designed to enable the separate identification of these different representations with a multivariate classification analysis approach. Consistent with our predictions, the dorsolateral striatum contained information about responses but not outcomes at the time of an initial stimulus, while the regions implicated in goal-directed action selection contained information about both responses and outcomes. These findings suggest that differential contributions of these regions to habitual and goal-directed behavioral control may depend in part on basic differences in the type of information that these regions have access to at the time of decision making. PMID:25740507

Sleep and Nutritional Deprivation and Performance of House Officers.

ERIC Educational Resources Information Center

Hawkins, Michael R.; And Others

1985-01-01

A study to compare cognitive functioning in acutely and chronically sleep-deprived house officers is described. A multivariate analysis of variance revealed significant deficits in primary mental tasks involving basic rote memory, language, and numeric skills. (Author/MLW)

Simulation Modeling to Compare High-Throughput, Low-Iteration Optimization Strategies for Metabolic Engineering

PubMed Central

Heinsch, Stephen C.; Das, Siba R.; Smanski, Michael J.

2018-01-01

Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems. PMID:29535690

Mining Recent Temporal Patterns for Event Detection in Multivariate Time Series Data

PubMed Central

Batal, Iyad; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

Improving the performance of classifiers using pattern mining techniques has been an active topic of data mining research. In this work we introduce the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data. This framework first converts time series into time-interval sequences of temporal abstractions. It then constructs more complex temporal patterns backwards in time using temporal operators. We apply our framework to health care data of 13,558 diabetic patients and show its benefits by efficiently finding useful patterns for detecting and diagnosing adverse medical conditions that are associated with diabetes. PMID:25937993

An information-based network approach for protein classification

PubMed Central

Wan, Xiaogeng; Zhao, Xin; Yau, Stephen S. T.

2017-01-01

Protein classification is one of the critical problems in bioinformatics. Early studies used geometric distances and polygenetic-tree to classify proteins. These methods use binary trees to present protein classification. In this paper, we propose a new protein classification method, whereby theories of information and networks are used to classify the multivariate relationships of proteins. In this study, protein universe is modeled as an undirected network, where proteins are classified according to their connections. Our method is unsupervised, multivariate, and alignment-free. It can be applied to the classification of both protein sequences and structures. Nine examples are used to demonstrate the efficiency of our new method. PMID:28350835

Impact of financial burden of cancer on survivors' quality of life.

PubMed

Fenn, Kathleen M; Evans, Suzanne B; McCorkle, Ruth; DiGiovanna, Michael P; Pusztai, Lajos; Sanft, Tara; Hofstatter, Erin W; Killelea, Brigid K; Knobf, M Tish; Lannin, Donald R; Abu-Khalaf, Maysa; Horowitz, Nina R; Chagpar, Anees B

2014-09-01

Little is known about the relationship between the financial burden of cancer and the physical and emotional health of cancer survivors. We examined the association between financial problems caused by cancer and reported quality of life in a population-based sample of patients with cancer. Data from the 2010 National Health Interview Survey (NHIS) were analyzed. A multivariable regression model was used to examine the relationship between the degree to which cancer caused financial problems and the patients' reported quality of life. Of 2,108 patients who answered the survey question, "To what degree has cancer caused financial problems for you and your family?," 8.6% reported "a lot," whereas 69.6% reported "not at all." Patients who reported "a lot" of financial problems as a result of cancer care costs were more likely to rate their physical health (18.6% v 4.3%, P < .001), mental health (8.3% v 1.8%, P < .001), and satisfaction with social activities and relationships (11.8% v 3.6%, P < .001) as poor compared to those with no financial hardship. On multivariable analysis controlling for all of the significant covariates on bivariate analysis, the degree to which cancer caused financial problems was the strongest independent predictor of quality of life. Patients who reported that cancer caused "a lot" of financial problems were four times less likely to rate their quality of life as "excellent," "very good," or "good" (odds ratio = 0.24; 95% CI, 0.14 to 0.40; P < .001). Increased financial burden asa result of cancer care costs is the strongest independent predictor of poor quality of life among cancer survivors. Copyright © 2014 by American Society of Clinical Oncology.

A longitudinal study of the comparative efficacy of Women for Sobriety, LifeRing, SMART Recovery, and 12-step groups for those with AUD.

PubMed

Zemore, Sarah E; Lui, Camillia; Mericle, Amy; Hemberg, Jordana; Kaskutas, Lee Ann

2018-05-01

Despite the effectiveness of 12-step groups, most people reporting a prior alcohol use disorder (AUD) do not sustain involvement in such groups at beneficial levels. This highlights the need for research on other mutual help groups that address alcohol problems and may attract those who avoid 12-step groups. The current study addresses this need, offering outcome data from the first longitudinal, comparative study of 12-step groups and their alternatives: The Peer ALlternatives for Addiction (PAL) Study. Adults with a lifetime AUD were surveyed at baseline (N=647), 6months (81% response rate) and 12months (83% response rate). Members of the largest known secular mutual help alternatives, namely Women for Sobriety (WFS), LifeRing, and SMART, were recruited in collaboration with group directors; current 12-step attendees were recruited from an online meeting hub. Online surveys assessed demographic and clinical variables; mutual help involvement; and alcohol and drug use and severity. Analyses involved multivariate logistic GEEs separately modelling alcohol abstinence, alcohol problems, and total abstinence across 6 and 12months. Key predictors were baseline primary group affiliation (PGA); primary group involvement (PGI) at both baseline and 6months; and the interaction between baseline PGA and 6-month PGI. The critical effects of interest were the interactions, expressing whether associations between changes in PGI from baseline to 6months and substance use outcomes differed by primary group. None of the interactions between baseline PGA and 6-month PGI were significant, suggesting no differences in the efficacy of WFS, LifeRing, or SMART, vs. 12-step groups. Nevertheless, some PGA main effects emerged. Compared to 12-step members, those identifying SMART as their primary group at baseline fared worse across outcomes, and those affiliating with LifeRing showed lower odds of total abstinence. Still, these effects became nonsignificant when controlling for baseline alcohol recovery goal, suggesting that any group differences may be explained by selection of those with weaker abstinence motivation into LifeRing and (especially) SMART. This study makes a valuable contribution in view of the extremely limited evidence on mutual help alternatives. Results tentatively suggest that WFS, LifeRing, and SMART are as effective as 12-step groups for those with AUDs, and that this population has the best odds of success when committing to lifetime total abstinence. An optimal care plan may thus involve facilitating involvement in a broad array of mutual help groups and supporting abstinence motivation. Copyright © 2018 Elsevier Inc. All rights reserved.

Posterior Beta and Anterior Gamma Oscillations Predict Cognitive Insight

ERIC Educational Resources Information Center

Sheth, Bhavin R.; Sandkuhler, Simone; Bhattacharya, Joydeep

2009-01-01

Pioneering neuroimaging studies on insight have revealed neural correlates of the emotional "Aha!" component of the insight process, but neural substrates of the cognitive component, such as problem restructuring (a key to transformative reasoning), remain a mystery. Here, multivariate electroencephalogram signals were recorded from human…

Parent Influences on Early Childhood Internalizing Difficulties

ERIC Educational Resources Information Center

Bayer, Jordana, K.; Sanson, Ann, V.; Hemphill, Sheryl A.

2006-01-01

Children's internalizing problems are a concerning mental health issue, due to significant prevalence and continuity over time. This study tested a multivariate model predicting young children's internalizing behaviors from parenting practices, parents' anxiety-depression and family stressors. A community sample of 2 year old children (N=112) was…

Partial Least Square Analyses of Landscape and Surface Water Biota Associations in the Savannah River Basin

EPA Science Inventory

Ecologists are often faced with problem of small sample size, correlated and large number of predictors, and high noise-to-signal relationships. This necessitates excluding important variables from the model when applying standard multiple or multivariate regression analyses. In ...

Association between a syndemic of psychosocial problems and unprotected anal intercourse among men who have sex with men in Shanghai, China.

PubMed

Wang, Ying; Wang, Zezhou; Jia, Mengmeng; Liang, Ajuan; Yuan, Dong; Sun, Zhe; Gan, Feng; Wang, Yichen; Cai, Yong; Zhang, Zhiruo

2017-01-07

Previous studies have discussed the overlapping and reinforcing effects (defined as a syndemic) of psychosocial problems on high-risk sexual behaviors among men who have sex with men (MSM). The present study aimed to apply the syndemic theory to verify the reinforcing effects of psychosocial problems on unprotected anal intercourse (UAI) among MSM in Shanghai, and determine if other important psychosocial factors fit into the syndemic theory. Data were collected from 547 MSM in Shanghai, China, through face-to-face interviews. The measures for psychosocial problems included the Rosenberg Self-Esteem Scale; the Generalized Anxiety Disorder-7; the Center for Epidemiological Studies Depression Scale; the University of California, Los Angeles Loneliness Scale; and the Sexual Compulsivity Scale. We used multivariate analysis and binary logistic regression to investigate the associations between psychosocial problems and high-risk sexual behaviors. The prevalence of UAI among MSM in the past 6 months was 54.5%. Education (graduate from college vs. high school) served as a protective factor against UAI (OR 0.59, 95% CI: 0.38-0.94). There was a high prevalence of psychosocial problems, and at least one-third of participants reported experiencing more than two psychosocial symptoms. Of these psychosocial factors that we investigated, lower self-esteem was associated with UAI in both univariate and multivariate regression model (P = 0.009). Result suggests that overlapping and reinforcing effects of psychosocial problems may increase high risk sexual behaviors among MSM in Shanghai, China (OR 1.65, 95% CI: 1.09-2.50; P = 0.018). We found further evidence for a syndemic of psychosocial problems among MSM in Shanghai, China. This syndemic may also increase high risk sexual behaviors among MSM. Most HIV prevention interventions are focused on behavior change and only have moderate effects; our findings suggest that a shift from behavior-focused interventions to a more comprehensive strategy that addresses psychosocial factors may be necessary.

Application of advanced control techniques to aircraft propulsion systems

NASA Technical Reports Server (NTRS)

Lehtinen, B.

1984-01-01

Two programs are described which involve the application of advanced control techniques to the design of engine control algorithms. Multivariable control theory is used in the F100 MVCS (multivariable control synthesis) program to design controls which coordinate the control inputs for improved engine performance. A systematic method for handling a complex control design task is given. Methods of analytical redundancy are aimed at increasing the control system reliability. The F100 DIA (detection, isolation, and accommodation) program, which investigates the uses of software to replace or augment hardware redundancy for certain critical engine sensor, is described.

Intimate partner violence among economically disadvantaged young adult women: associations with adolescent risk-taking and pregnancy experiences.

PubMed

O'Donnell, Lydia; Agronick, Gail; Duran, Richard; Myint-U, Athi; Stueve, Ann

2009-06-01

Intimate partner violence negatively impacts the health of substantial proportions of young women in economically disadvantaged communities, where sexual initiation, aggressive behaviors, unintended pregnancies and childbearing are common among adolescents. It is therefore important to assess how adolescent risk behaviors and pregnancy experiences are linked to such violence during young adulthood. Data from 526 participants in the Reach for Health Longitudinal Study who were surveyed during middle school (in 1995-1996 and 1996-1997) and at ages 22-25 (in 2005-2007) provided information on adolescent risk behaviors and pregnancy experiences, as well as experiences of intimate partner violence during young adulthood. Bivariate and multivariate analyses were conducted to identify correlates of intimate partner violence involvement. As young adults, 29% of women reported having been victims of intimate partner violence in the past 12 months; 21% reported having perpetrated such violence. In multivariate analyses, victimization and perpetration in the last year are positively associated with aggressive behavior in middle school (odds ratios, 1.9 and 2.5, respectively), lifetime number of sex partners (1.3 for both) and having a history of unintended pregnancy or pregnancy problems (1.3 for both). Perpetration also is associated with early sexual initiation (0.5) and living with a partner (1.8). It is important to consider women's pregnancy histories in programs aimed at preventing the adverse outcomes of relationship violence and in screening for partner violence in sexual and reproductive health services. Early intervention may help women develop the skills needed for resolving conflicts with peers and partners.

Patterns of and Motivations for Concurrent Use of Video Games and Substances

PubMed Central

Ream, Geoffrey L.; Elliott, Luther C.; Dunlap, Eloise

2011-01-01

“Behavioral addictions” share biological mechanisms with substance dependence, and “drug interactions” have been observed between certain substances and self-reinforcing behaviors. This study examines correlates of patterns of and motivations for playing video games while using or feeling the effects of a substance (concurrent use). Data were drawn from a nationally-representative survey of adult Americans who “regularly” or “occasionally” played video games and had played for at least one hour in the past seven days (n = 3,380). Only recent concurrent users’ data were included in analyses (n = 1,196). Independent variables included demographics, substance use frequency and problems, game genre of concurrent use (identified by looking titles up in an industry database), and general game playing variables including problem video game play (PVP), consumer involvement, enjoyment, duration, and frequency of play. Exploratory factor analysis identified the following dimensions underlying patterns of and motivations for concurrent use: pass time or regulate negative emotion, enhance an already enjoyable or positive experience, and use of video games and substances to remediate each other’s undesirable effects. Multivariate regression analyses indicated PVP and hours/day of video game play were associated with most patterns/motivations, as were caffeine, tobacco, alcohol, marijuana, and painkiller use problems. This suggests that concurrent use with some regular situational pattern or effect-seeking motivation is part of the addictive process underlying both PVP and substance dependence. Various demographic, game playing, game genre of concurrent use, and substance use variables were associated with specific motivations/patterns, indicating that all are important in understanding concurrent use. PMID:22073024

Depression and HIV risk behavior practices among at risk women.

PubMed

Klein, Hugh; Elifson, Kirk W; Sterk, Claire E

2008-01-01

In this study, we examined the relationship between depression and HIV-related risk behavior practices in a sample of 250 at risk, predominantly African American women living in the Atlanta, Georgia metropolitan area. Interviews were conducted between August 1997 and August 2000. Street outreach efforts were used to identify potential study participants, with further expansion of the sample via targeted sampling and ethnographic mapping procedures. Our conceptual model hypothesized a relationship between depression and HIV risk in which depression and condom-related attitudes were construed as intervening (or mediating) variables. A multivariate analysis was used to determine the relationship between depression and women's risk behaviors. The results showed that depression was a key-mediating variable, having its primary influence on women's risky practices through its impact upon their attitudes toward using condoms. Factors associated with depression, included religiosity, closeness of family relationships, financial problems, childhood maltreatment experiences, and drug-related problems. The implications of these findings for prevention and intervention efforts are: (1) heightening faith community involvement and religious participation to decrease depression; (2) working with women whose familial bonds are in need of strengthening to combat depression; (3) providing mental health and counseling services to women who were emotionally and/or sexually abused during their formative years seems to help these women to recover from unresolved issues that may be fueling depression; (4) assisting at risk women who need training in money management issues to minimize their risk for depression; and (5) helping women drug abusers to receive treatment for their drug problems to combat their depression and lower their HIV risk.

Interpretation of FTIR spectra of polymers and Raman spectra of car paints by means of likelihood ratio approach supported by wavelet transform for reducing data dimensionality.

PubMed

Martyna, Agnieszka; Michalska, Aleksandra; Zadora, Grzegorz

2015-05-01

The problem of interpretation of common provenance of the samples within the infrared spectra database of polypropylene samples from car body parts and plastic containers as well as Raman spectra databases of blue solid and metallic automotive paints was under investigation. The research involved statistical tools such as likelihood ratio (LR) approach for expressing the evidential value of observed similarities and differences in the recorded spectra. Since the LR models can be easily proposed for databases described by a few variables, research focused on the problem of spectra dimensionality reduction characterised by more than a thousand variables. The objective of the studies was to combine the chemometric tools easily dealing with multidimensionality with an LR approach. The final variables used for LR models' construction were derived from the discrete wavelet transform (DWT) as a data dimensionality reduction technique supported by methods for variance analysis and corresponded with chemical information, i.e. typical absorption bands for polypropylene and peaks associated with pigments present in the car paints. Univariate and multivariate LR models were proposed, aiming at obtaining more information about the chemical structure of the samples. Their performance was controlled by estimating the levels of false positive and false negative answers and using the empirical cross entropy approach. The results for most of the LR models were satisfactory and enabled solving the stated comparison problems. The results prove that the variables generated from DWT preserve signal characteristic, being a sparse representation of the original signal by keeping its shape and relevant chemical information.

Patterns of and motivations for concurrent use of video games and substances.

PubMed

Ream, Geoffrey L; Elliott, Luther C; Dunlap, Eloise

2011-10-01

"Behavioral addictions" share biological mechanisms with substance dependence, and "drug interactions" have been observed between certain substances and self-reinforcing behaviors. This study examines correlates of patterns of and motivations for playing video games while using or feeling the effects of a substance (concurrent use). Data were drawn from a nationally-representative survey of adult Americans who "regularly" or "occasionally" played video games and had played for at least one hour in the past seven days (n = 3,380). Only recent concurrent users' data were included in analyses (n = 1,196). Independent variables included demographics, substance use frequency and problems, game genre of concurrent use (identified by looking titles up in an industry database), and general game playing variables including problem video game play (PVP), consumer involvement, enjoyment, duration, and frequency of play. Exploratory factor analysis identified the following dimensions underlying patterns of and motivations for concurrent use: pass time or regulate negative emotion, enhance an already enjoyable or positive experience, and use of video games and substances to remediate each other's undesirable effects. Multivariate regression analyses indicated PVP and hours/day of video game play were associated with most patterns/motivations, as were caffeine, tobacco, alcohol, marijuana, and painkiller use problems. This suggests that concurrent use with some regular situational pattern or effect-seeking motivation is part of the addictive process underlying both PVP and substance dependence. Various demographic, game playing, game genre of concurrent use, and substance use variables were associated with specific motivations/patterns, indicating that all are important in understanding concurrent use.

Paternal ADHD Symptoms and Child Conduct Problems: Is Father Involvement Always Beneficial?

PubMed Central

Romirowsky, Abigail Mintz; Chronis-Tuscano, Andrea

2013-01-01

Background Maternal psychopathology robustly predicts poor developmental and treatment outcomes for children with attention-deficit/hyperactivity disorder (ADHD). Despite the high heritability of ADHD, few studies have examined associations between paternal ADHD symptoms and child adjustment, and none have also considered degree of paternal involvement in childrearing. Identification of modifiable risk factors for child conduct problems is particularly important in this population given the serious adverse outcomes resulting from this comorbidity. Methods This cross-sectional study examined the extent to which paternal involvement in childrearing moderated the association between paternal ADHD symptoms and child conduct problems among 37 children with ADHD and their biological fathers. Results Neither paternal ADHD symptoms nor involvement was independently associated with child conduct problems. However, the interaction between paternal ADHD symptoms and involvement was significant, such that paternal ADHD symptoms were positively associated with child conduct problems only when fathers were highly involved in childrearing. Conclusions The presence of adult ADHD symptoms may determine whether father involvement in childrearing has a positive or detrimental influence on comorbid child conduct problems. PMID:25250402

Problem drinking and the dimension of involvement with drugs: a Guttman scalogram analysis of adolescent drug use.

PubMed Central

Donovan, J E; Jessor, R

1983-01-01

Analyses of data from two nationwide surveys of high school students, one carried out in 1974 and the other in 1978, suggest that problem drinking may be seen as yet another step along an underlying dimension of involvement with both licit and illicit drugs. The dimension of involvement with drugs consists of the following levels: nonuse of alcohol or illicit drugs; nonproblem use of alcohol; marijuana use; problem drinking; use of pills (amphetamines, barbiturates, hallucinogenic drugs); and the use of "hard drugs" such as cocaine or heroin. The dimension possesses excellent Guttman-scale properties in both national samples as well as in subsamples differing in gender and ethnic background. The ordering of the levels of involvement was confirmed by the ordering of the alcohol-drug involvement groups based on their mean scores on measures of psychosocial proneness for involvement in problem behavior. The excessive use of a licit drug, i.e., problem drinking, appears to indicate greater involvement in drug use than does the use of an illicit drug, marijuana. This finding points to the importance of distinguishing between use and problem use of drugs in efforts to understand adolescent drug involvement. PMID:6837819

An improved algorithm for the determination of the system paramters of a visual binary by least squares

NASA Astrophysics Data System (ADS)

Xu, Yu-Lin

The problem of computing the orbit of a visual binary from a set of observed positions is reconsidered. It is a least squares adjustment problem, if the observational errors follow a bias-free multivariate Gaussian distribution and the covariance matrix of the observations is assumed to be known. The condition equations are constructed to satisfy both the conic section equation and the area theorem, which are nonlinear in both the observations and the adjustment parameters. The traditional least squares algorithm, which employs condition equations that are solved with respect to the uncorrelated observations and either linear in the adjustment parameters or linearized by developing them in Taylor series by first-order approximation, is inadequate in our orbit problem. D.C. Brown proposed an algorithm solving a more general least squares adjustment problem in which the scalar residual function, however, is still constructed by first-order approximation. Not long ago, a completely general solution was published by W.H Jefferys, who proposed a rigorous adjustment algorithm for models in which the observations appear nonlinearly in the condition equations and may be correlated, and in which construction of the normal equations and the residual function involves no approximation. This method was successfully applied in our problem. The normal equations were first solved by Newton's scheme. Practical examples show that this converges fast if the observational errors are sufficiently small and the initial approximate solution is sufficiently accurate, and that it fails otherwise. Newton's method was modified to yield a definitive solution in the case the normal approach fails, by combination with the method of steepest descent and other sophisticated algorithms. Practical examples show that the modified Newton scheme can always lead to a final solution. The weighting of observations, the orthogonal parameters and the efficiency of a set of adjustment parameters are also considered. The definition of efficiency is revised.

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

NASA Astrophysics Data System (ADS)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin, particularly for annual maxima of the FWI distribution and spatiotemporal autocorrelation of precipitation fields.

Fresh Biomass Estimation in Heterogeneous Grassland Using Hyperspectral Measurements and Multivariate Statistical Analysis

NASA Astrophysics Data System (ADS)

Darvishzadeh, R.; Skidmore, A. K.; Mirzaie, M.; Atzberger, C.; Schlerf, M.

2014-12-01

Accurate estimation of grassland biomass at their peak productivity can provide crucial information regarding the functioning and productivity of the rangelands. Hyperspectral remote sensing has proved to be valuable for estimation of vegetation biophysical parameters such as biomass using different statistical techniques. However, in statistical analysis of hyperspectral data, multicollinearity is a common problem due to large amount of correlated hyper-spectral reflectance measurements. The aim of this study was to examine the prospect of above ground biomass estimation in a heterogeneous Mediterranean rangeland employing multivariate calibration methods. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of above ground biomass for 170 sample plots. Multivariate calibrations including partial least squares regression (PLSR), principal component regression (PCR), and Least-Squared Support Vector Machine (LS-SVM) were used to estimate the above ground biomass. The prediction accuracy of the multivariate calibration methods were assessed using cross validated R2 and RMSE. The best model performance was obtained using LS_SVM and then PLSR both calibrated with first derivative reflectance dataset with R2cv = 0.88 & 0.86 and RMSEcv= 1.15 & 1.07 respectively. The weakest prediction accuracy was appeared when PCR were used (R2cv = 0.31 and RMSEcv= 2.48). The obtained results highlight the importance of multivariate calibration methods for biomass estimation when hyperspectral data are used.

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

Developing the Fundamental Theorem of Calculus. Applications of Calculus to Work, Area, and Distance Problems. [and] Atmospheric Pressure in Relation to Height and Temperature. Applications of Calculus to Atmospheric Pressure. [and] The Gradient and Some of Its Applications. Applications of Multivariate Calculus to Physics. [and] Kepler's Laws and the Inverse Square Law. Applications of Calculus to Physics. UMAP Units 323, 426, 431, 473.

ERIC Educational Resources Information Center

Lindstrom, Peter A.; And Others

This document consists of four units. The first of these views calculus applications to work, area, and distance problems. It is designed to help students gain experience in: 1) computing limits of Riemann sums; 2) computing definite integrals; and 3) solving elementary area, distance, and work problems by integration. The second module views…

Cognitive Correlates of Math Skills in Third-Grade Students

ERIC Educational Resources Information Center

Mannamaa, Mairi; Kikas, Eve; Peets, Katlin; Palu, Anu

2012-01-01

Math achievement is not a unidimensional construct but includes different skills that require different cognitive abilities. The focus of this study was to examine associations between a number of cognitive abilities and three domains of math skills (knowing, applying and problem solving) simultaneously in a multivariate framework. Participants…

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

PubMed

Hurtado Rúa, Sandra M; Mazumdar, Madhu; Strawderman, Robert L

2015-12-30

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Assessing the hydrogeochemical processes affecting groundwater pollution in arid areas using an integration of geochemical equilibrium and multivariate statistical techniques.

PubMed

El Alfy, Mohamed; Lashin, Aref; Abdalla, Fathy; Al-Bassam, Abdulaziz

2017-10-01

Rapid economic expansion poses serious problems for groundwater resources in arid areas, which typically have high rates of groundwater depletion. In this study, integration of hydrochemical investigations involving chemical and statistical analyses are conducted to assess the factors controlling hydrochemistry and potential pollution in an arid region. Fifty-four groundwater samples were collected from the Dhurma aquifer in Saudi Arabia, and twenty-one physicochemical variables were examined for each sample. Spatial patterns of salinity and nitrate were mapped using fitted variograms. The nitrate spatial distribution shows that nitrate pollution is a persistent problem affecting a wide area of the aquifer. The hydrochemical investigations and cluster analysis reveal four significant clusters of groundwater zones. Five main factors were extracted, which explain >77% of the total data variance. These factors indicated that the chemical characteristics of the groundwater were influenced by rock-water interactions and anthropogenic factors. The identified clusters and factors were validated with hydrochemical investigations. The geogenic factors include the dissolution of various minerals (calcite, aragonite, gypsum, anhydrite, halite and fluorite) and ion exchange processes. The anthropogenic factors include the impact of irrigation return flows and the application of potassium, nitrate, and phosphate fertilizers. Over time, these anthropogenic factors will most likely contribute to further declines in groundwater quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stochastic optimization of GeantV code by use of genetic algorithms

DOE PAGES

Amadio, G.; Apostolakis, J.; Bandieramonte, M.; ...

2017-10-01

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) andmore » handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. Here, the goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.« less

Stochastic optimization of GeantV code by use of genetic algorithms

NASA Astrophysics Data System (ADS)

Amadio, G.; Apostolakis, J.; Bandieramonte, M.; Behera, S. P.; Brun, R.; Canal, P.; Carminati, F.; Cosmo, G.; Duhem, L.; Elvira, D.; Folger, G.; Gheata, A.; Gheata, M.; Goulas, I.; Hariri, F.; Jun, S. Y.; Konstantinov, D.; Kumawat, H.; Ivantchenko, V.; Lima, G.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.

2017-10-01

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) and handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. The goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.

Stochastic optimization of GeantV code by use of genetic algorithms

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

Amadio, G.; Apostolakis, J.; Bandieramonte, M.

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) andmore » handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. Here, the goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.« less

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Perception of control, coping and psychological stress of infertile women undergoing IVF.

PubMed

Gourounti, Kleanthi; Anagnostopoulos, Fotios; Potamianos, Grigorios; Lykeridou, Katerina; Schmidt, Lone; Vaslamatzis, Grigorios

2012-06-01

The study aimed to examine: (i) the association between perception of infertility controllability and coping strategies; and (ii) the association between perception of infertility controllability and coping strategies to psychological distress, applying multivariate statistical techniques to control for the effects of demographic variables. This cross-sectional study included 137 women with fertility problems undergoing IVF in a public hospital. All participants completed questionnaires that measured fertility-related stress, state anxiety, depressive symptomatology, perception of control and coping strategies. Pearson's correlation coefficients were calculated between all study variables, followed by hierarchical multiple linear regression. Low perception of personal and treatment controllability was associated with frequent use of avoidance coping and high perception of treatment controllability was positively associated with problem-focused coping. Multivariate analysis showed that, when controlling for demographic factors, low perception of personal control and avoidance coping were positively associated with fertility-related stress and state anxiety, and problem-appraisal coping was negatively and significantly associated with fertility-related stress and depressive symptomatology scores. The findings of this study merit the understanding of the role of control perception and coping in psychological stress of infertile women to identify beforehand those women who might be at risk of experiencing high stress and in need of support. Copyright © 2012 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Data mining for water resource management part 2 - methods and approaches to solving contemporary problems

USGS Publications Warehouse

Roehl, Edwin A.; Conrads, Paul

2010-01-01

This is the second of two papers that describe how data mining can aid natural-resource managers with the difficult problem of controlling the interactions between hydrologic and man-made systems. Data mining is a new science that assists scientists in converting large databases into knowledge, and is uniquely able to leverage the large amounts of real-time, multivariate data now being collected for hydrologic systems. Part 1 gives a high-level overview of data mining, and describes several applications that have addressed major water resource issues in South Carolina. This Part 2 paper describes how various data mining methods are integrated to produce predictive models for controlling surface- and groundwater hydraulics and quality. The methods include: - signal processing to remove noise and decompose complex signals into simpler components; - time series clustering that optimally groups hundreds of signals into "classes" that behave similarly for data reduction and (or) divide-and-conquer problem solving; - classification which optimally matches new data to behavioral classes; - artificial neural networks which optimally fit multivariate data to create predictive models; - model response surface visualization that greatly aids in understanding data and physical processes; and, - decision support systems that integrate data, models, and graphics into a single package that is easy to use.

MGAS: a powerful tool for multivariate gene-based genome-wide association analysis.

PubMed

Van der Sluis, Sophie; Dolan, Conor V; Li, Jiang; Song, Youqiang; Sham, Pak; Posthuma, Danielle; Li, Miao-Xin

2015-04-01

Standard genome-wide association studies, testing the association between one phenotype and a large number of single nucleotide polymorphisms (SNPs), are limited in two ways: (i) traits are often multivariate, and analysis of composite scores entails loss in statistical power and (ii) gene-based analyses may be preferred, e.g. to decrease the multiple testing problem. Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals. Through extensive simulation, we show that under most trait-generating genotype-phenotype models MGAS has superior statistical power to detect associated genes compared with gene-based analyses of univariate phenotypic composite scores (i.e. GATES, multiple regression), and multivariate analysis of variance (MANOVA). Re-analysis of metabolic data revealed 32 False Discovery Rate controlled genome-wide significant genes, and 12 regions harboring multiple genes; of these 44 regions, 30 were not reported in the original analysis. MGAS allows researchers to conduct their multivariate gene-based analyses efficiently, and without the loss of power that is often associated with an incorrectly specified genotype-phenotype models. MGAS is freely available in KGG v3.0 (http://statgenpro.psychiatry.hku.hk/limx/kgg/download.php). Access to the metabolic dataset can be requested at dbGaP (https://dbgap.ncbi.nlm.nih.gov/). The R-simulation code is available from http://ctglab.nl/people/sophie_van_der_sluis. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Measuring Family Problem Solving: The Family Problem Solving Diary.

ERIC Educational Resources Information Center

Kieren, Dianne K.

The development and use of the family problem-solving diary are described. The diary is one of several indicators and measures of family problem-solving behavior. It provides a record of each person's perception of day-to-day family problems (what the problem concerns, what happened, who got involved, what those involved did, how the problem…

Multivariate analysis of progressive thermal desorption coupled gas chromatography-mass spectrometry.

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

Van Benthem, Mark Hilary; Mowry, Curtis Dale; Kotula, Paul Gabriel

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that varymore » as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.« less

Parents' and Adolescents' Attitudes about Parental Involvement in Clinical Research.

PubMed

Rosenthal, Susan L; de Roche, Ariel M; Catallozzi, Marina; Breitkopf, Carmen Radecki; Ipp, Lisa S; Chang, Jane; Francis, Jenny K R; Hu, Mei-Chen

2016-08-01

To understand parent and adolescent attitudes toward parental involvement during clinical trials and factors related to those attitudes. As part of a study on willingness to participate in a hypothetical microbicide study, adolescents and their parents were interviewed separately. Adolescent medicine clinics in New York City. There were 301 dyads of adolescents (ages 14-17 years; 62% female; 72% Hispanic) and their parents. None. The interview included questions on demographic characteristics, sexual history, and family environment (subscales of the Family Environment Scale) that were associated with attitudes about parental involvement. Factor analysis of the parental involvement scale yielded 2 factors: LEARN, reflecting gaining knowledge about study test results and behaviors (4 items) and PROCEDURE, reflecting enrollment and permissions (4 items). Adolescents endorsed significantly fewer items on the LEARN scale and the PROCEDURE scale indicating that adolescents believed in less parental involvement. There was no significant concordance between adolescents and their own parents on the LEARN scale and the PROCEDURE scale. In final multivariate models predicting attitudes, adolescents who were female and had sexual contact beyond kissing, and non-Hispanic parents had lower LEARN scores. Adolescents who were older, had previous research experience, and reported less moral or religious emphasis in their family had lower PROCEDURE scores; there were no significant predictors for parents in the multivariate analyses. Parents wanted greater involvement in the research process than adolescents. Recruitment and retention might be enhanced by managing these differing expectations. Copyright © 2016 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

Depression and associated factors in older adults in South Africa.

PubMed

Peltzer, Karl; Phaswana-Mafuya, Nancy

2013-01-18

Late-life depression is an important public health problem because of its devastating consequences. The study aims to investigate the prevalence and associated factors of self-reported symptom-based depression in a national sample of older South Africans who participated in the Study of Global Ageing and Adult Health (SAGE wave 1) in 2008. We conducted a national population-based cross-sectional study with a probability sample of 3,840 individuals aged 50 years or above in South Africa in 2008. The questionnaire included socio-demographic characteristics, health variables, anthropometric and blood pressure measurements as well as questions on depression symptoms in the past 12 months. Multivariable regression analysis was performed to assess the association of socio-demographic factors, health variables, and depression. The overall prevalence of symptom-based depression in the past 12 months was 4.0%. In multivariable analysis, functional disability, lack of quality of life, and chronic conditions (angina, asthma, arthritis, and nocturnal sleep problems) were associated with self-reported depression symptoms in the past 12 months. Self-reported depression in older South Africans seems to be a public health problem calling for appropriate interventions to reduce occurrence. Factors identified to be associated with depression, including functional disability, lack of quality of life, and chronic conditions (angina, asthma, arthritis, and nocturnal sleep problems), can be used to guide interventions. The identified protective and risk factors can help in formulating public health care policies to improve quality of life among older adults.

Compressed Secret Key Agreement:Maximizing Multivariate Mutual Information per Bit

NASA Astrophysics Data System (ADS)

Chan, Chung

2017-10-01

The multiterminal secret key agreement problem by public discussion is formulated with an additional source compression step where, prior to the public discussion phase, users independently compress their private sources to filter out strongly correlated components for generating a common secret key. The objective is to maximize the achievable key rate as a function of the joint entropy of the compressed sources. Since the maximum achievable key rate captures the total amount of information mutual to the compressed sources, an optimal compression scheme essentially maximizes the multivariate mutual information per bit of randomness of the private sources, and can therefore be viewed more generally as a dimension reduction technique. Single-letter lower and upper bounds on the maximum achievable key rate are derived for the general source model, and an explicit polynomial-time computable formula is obtained for the pairwise independent network model. In particular, the converse results and the upper bounds are obtained from those of the related secret key agreement problem with rate-limited discussion. A precise duality is shown for the two-user case with one-way discussion, and such duality is extended to obtain the desired converse results in the multi-user case. In addition to posing new challenges in information processing and dimension reduction, the compressed secret key agreement problem helps shed new light on resolving the difficult problem of secret key agreement with rate-limited discussion, by offering a more structured achieving scheme and some simpler conjectures to prove.

Surrogate model approach for improving the performance of reactive transport simulations

NASA Astrophysics Data System (ADS)

Jatnieks, Janis; De Lucia, Marco; Sips, Mike; Dransch, Doris

2016-04-01

Reactive transport models can serve a large number of important geoscientific applications involving underground resources in industry and scientific research. It is common for simulation of reactive transport to consist of at least two coupled simulation models. First is a hydrodynamics simulator that is responsible for simulating the flow of groundwaters and transport of solutes. Hydrodynamics simulators are well established technology and can be very efficient. When hydrodynamics simulations are performed without coupled geochemistry, their spatial geometries can span millions of elements even when running on desktop workstations. Second is a geochemical simulation model that is coupled to the hydrodynamics simulator. Geochemical simulation models are much more computationally costly. This is a problem that makes reactive transport simulations spanning millions of spatial elements very difficult to achieve. To address this problem we propose to replace the coupled geochemical simulation model with a surrogate model. A surrogate is a statistical model created to include only the necessary subset of simulator complexity for a particular scenario. To demonstrate the viability of such an approach we tested it on a popular reactive transport benchmark problem that involves 1D Calcite transport. This is a published benchmark problem (Kolditz, 2012) for simulation models and for this reason we use it to test the surrogate model approach. To do this we tried a number of statistical models available through the caret and DiceEval packages for R, to be used as surrogate models. These were trained on randomly sampled subset of the input-output data from the geochemical simulation model used in the original reactive transport simulation. For validation we use the surrogate model to predict the simulator output using the part of sampled input data that was not used for training the statistical model. For this scenario we find that the multivariate adaptive regression splines (MARS) method provides the best trade-off between speed and accuracy. This proof-of-concept forms an essential step towards building an interactive visual analytics system to enable user-driven systematic creation of geochemical surrogate models. Such a system shall enable reactive transport simulations with unprecedented spatial and temporal detail to become possible. References: Kolditz, O., Görke, U.J., Shao, H. and Wang, W., 2012. Thermo-hydro-mechanical-chemical processes in porous media: benchmarks and examples (Vol. 86). Springer Science & Business Media.

Applied statistics in agricultural, biological, and environmental sciences.

USDA-ARS?s Scientific Manuscript database

Agronomic research often involves measurement and collection of multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate statistical methods encompass the simultaneous analysis of all random variables measured on each experimental or s...

Prognostic significance of interventricular septal thickness in patients with AL amyloidosis.

PubMed

Cho, Hyunsoo; Kim, Soo-Jeong; Shim, Chi Young; Hong, Geu-Ru; Ha, Jong-Won; Kim, Yu Ri; Yang, Woo Ick; Chung, Haerim; Jang, Ji Eun; Cheong, June-Won; Min, Yoo Hong; Kim, Jin Seok

2017-09-01

The major prognostic determinant of immunoglobulin light chain (AL) amyloidosis is cardiac involvement. However, the role of interventricular septal thickness (IVST), which reflects the extent of cardiac involvement, remains unclear. Therefore, we analyzed 77 patients with newly diagnosed AL amyloidosis and evaluated the prognostic role of IVST. Fifty patients (64.9%) had cardiac involvement and 17 patients (22.1%) showed IVST >15mm. Among all patients, the revised Mayo Clinic Stage III-IV and IVST >15mm were independently associated with inferior overall survival (OS) in a multivariable analysis. IVST >15mm was also adversely prognostic for OS in a subgroup of advanced-stage (revised Mayo Clinic stage III-IV) patients in a multivariable analysis (P<0.001). Furthermore, advanced-stage patients with IVST >15mm did not show survival benefit from treatment with bortezomib-based regimens and/or autologous stem-cell transplantation (ASCT). Our study demonstrated that IVST >15mm is adversely prognostic independent of the revised Mayo Clinic staging system in patients with AL amyloidosis. In addition, the degree of IVST might be used as a useful prognostic indicator that can guide the management of patients with AL amyloidosis especially at an advanced stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Psychiatric and neurological disorders in late adolescence and risk of convictions for violent crime in men.

PubMed

Moberg, Tomas; Stenbacka, Marlene; Tengström, Anders; Jönsson, Erik G; Nordström, Peter; Jokinen, Jussi

2015-11-23

The relationship between mental illness and violent crime is complex because of the involvement of many other confounding risk factors. In the present study, we analysed psychiatric and neurological disorders in relation to the risk of convictions for violent crime, taking into account early behavioural and socio-economic risk factors. The study population consisted of 49,398 Swedish men, who were thoroughly assessed at conscription for compulsory military service during the years 1969-1970 and followed in national crime registers up to 2006. Five diagnostic groups were analysed: anxiety-depression/neuroses, personality disorders, substance-related disorders, mental retardation and neurological conditions. In addition, eight confounders measured at conscription and based on the literature on violence risk assessment, were added to the analyses. The relative risks of convictions for violent crime during 35 years after conscription were examined in relation to psychiatric diagnoses and other risk factors at conscription, as measured by odds ratios (ORs) and confidence intervals (CIs) from bivariate and multivariate logistic regression analyses. In the bivariate analyses there was a significant association between receiving a psychiatric diagnosis at conscription and a future conviction for violent crime (OR = 3.83, 95 % CI = 3.47-4.22), whereas no significant association between neurological conditions and future violent crime (OR = 1.03, 95 % CI = 0.48-2.21) was found. In the fully adjusted multivariate logistic regression model, mental retardation had the strongest association with future violent crime (OR = 3.60, 95 % CI = 2.73-4.75), followed by substance-related disorders (OR = 2.81, 95 % CI = 2.18-3.62), personality disorders (OR = 2.66, 95 % CI = 2.21-3.19) and anxiety-depression (OR = 1.29, 95 % CI = 1.07-1.55). Among the other risk factors, early behavioural problem had the strongest association with convictions for violent crime. Mental retardation, substance-related disorders, personality disorders and early behavioural problems are important predictors of convictions for violent crime in men.

How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information.

PubMed

Tuarob, Suppawong; Tucker, Conrad S; Kumara, Soundar; Giles, C Lee; Pincus, Aaron L; Conroy, David E; Ram, Nilam

2017-04-01

It is believed that anomalous mental states such as stress and anxiety not only cause suffering for the individuals, but also lead to tragedies in some extreme cases. The ability to predict the mental state of an individual at both current and future time periods could prove critical to healthcare practitioners. Currently, the practical way to predict an individual's mental state is through mental examinations that involve psychological experts performing the evaluations. However, such methods can be time and resource consuming, mitigating their broad applicability to a wide population. Furthermore, some individuals may also be unaware of their mental states or may feel uncomfortable to express themselves during the evaluations. Hence, their anomalous mental states could remain undetected for a prolonged period of time. The objective of this work is to demonstrate the ability of using advanced machine learning based approaches to generate mathematical models that predict current and future mental states of an individual. The problem of mental state prediction is transformed into the time series forecasting problem, where an individual is represented as a multivariate time series stream of monitored physical and behavioral attributes. A personalized mathematical model is then automatically generated to capture the dependencies among these attributes, which is used for prediction of mental states for each individual. In particular, we first illustrate the drawbacks of traditional multivariate time series forecasting methodologies such as vector autoregression. Then, we show that such issues could be mitigated by using machine learning regression techniques which are modified for capturing temporal dependencies in time series data. A case study using the data from 150 human participants illustrates that the proposed machine learning based forecasting methods are more suitable for high-dimensional psychological data than the traditional vector autoregressive model in terms of both magnitude of error and directional accuracy. These results not only present a successful usage of machine learning techniques in psychological studies, but also serve as a building block for multiple medical applications that could rely on an automated system to gauge individuals' mental states. Copyright © 2017 Elsevier Inc. All rights reserved.

Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions

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

Konakli, Katerina, E-mail: konakli@ibk.baug.ethz.ch; Sudret, Bruno

2016-09-15

The growing need for uncertainty analysis of complex computational models has led to an expanding use of meta-models across engineering and sciences. The efficiency of meta-modeling techniques relies on their ability to provide statistically-equivalent analytical representations based on relatively few evaluations of the original model. Polynomial chaos expansions (PCE) have proven a powerful tool for developing meta-models in a wide range of applications; the key idea thereof is to expand the model response onto a basis made of multivariate polynomials obtained as tensor products of appropriate univariate polynomials. The classical PCE approach nevertheless faces the “curse of dimensionality”, namely themore » exponential increase of the basis size with increasing input dimension. To address this limitation, the sparse PCE technique has been proposed, in which the expansion is carried out on only a few relevant basis terms that are automatically selected by a suitable algorithm. An alternative for developing meta-models with polynomial functions in high-dimensional problems is offered by the newly emerged low-rank approximations (LRA) approach. By exploiting the tensor–product structure of the multivariate basis, LRA can provide polynomial representations in highly compressed formats. Through extensive numerical investigations, we herein first shed light on issues relating to the construction of canonical LRA with a particular greedy algorithm involving a sequential updating of the polynomial coefficients along separate dimensions. Specifically, we examine the selection of optimal rank, stopping criteria in the updating of the polynomial coefficients and error estimation. In the sequel, we confront canonical LRA to sparse PCE in structural-mechanics and heat-conduction applications based on finite-element solutions. Canonical LRA exhibit smaller errors than sparse PCE in cases when the number of available model evaluations is small with respect to the input dimension, a situation that is often encountered in real-life problems. By introducing the conditional generalization error, we further demonstrate that canonical LRA tend to outperform sparse PCE in the prediction of extreme model responses, which is critical in reliability analysis.« less

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

Epidemiological profile of hospitalised injuries among electric bicycle riders admitted to a rural hospital in Suzhou: a cross-sectional study.

PubMed

Du, Wei; Yang, Jie; Powis, Brent; Zheng, Xiaoying; Ozanne-Smith, Joan; Bilston, Lynne; He, JingLin; Ma, Ting; Wang, Xiaofei; Wu, Ming

2014-04-01

Police reports indicate an increasing burden of electric bike (E-bike) casualties in China; however, hospitalised injury data have not been reported. The aim of the present work was to describe hospitalised injury patterns for E-bikers involved in road crashes and explore injury risk disparities among them. For the period October 2010 to April 2011, this cross-sectional study retrospectively collected information for hospitalised E-bikers involved in road crashes from hospital records, in Suzhou China, using the International Classification of Diseases, 10th revision (ICD-10) injury diagnosis codes. Injury nature and body region were further categorised using ICD-10 codes. Multivariate logistic regression was used to assess the risk of specific injury types. We found that hospitalised E-biker injuries (n=323) accounted for 57.2% of road traffic hospitalisations over the 6-month study period. The average age, length of stay and hospitalisation cost were 43.8 years, 10.0 days and ¥8229 (US$1286), respectively. Fractures and head injuries were common. The odds of traumatic brain injuries were significantly elevated for night-time E-bike crashes and incidents other than colliding with motor vehicles. These findings confirm E-bike injuries as an important population health problem and identify elevated injury odds in different E-biker groups. Future injury prevention initiatives should include encouraging helmet use among E-bikers.

Father Involvement and Behavior Problems among Preadolescents at Risk of Maltreatment

PubMed Central

Yoon, Susan; Bellamy, Jennifer L.; Kim, Wonhee; Yoon, Dalhee

2018-01-01

Although there is a well-established connection between father involvement and children’s positive behavioral development in general, this relation has been understudied in more vulnerable and high-risk populations. The aims of this study were to examine how the quantity (i.e., the amount of shared activities) and quality (i.e., perceived quality of the father-child relationship) of father involvement are differently related to internalizing and externalizing behavior problems among preadolescents at risk of maltreatment and test if these associations are moderated by father type and child maltreatment. A secondary data analysis was conducted using data from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN). Generalized estimating equations analysis was performed on a sample of 499 preadolescents aged 12 years. The results indicated that higher quality of father involvement was associated with lower levels of internalizing and externalizing behavior problems whereas greater quantity of father involvement was associated with higher levels of internalizing and externalizing behavior problems. The positive association between the quantity of father involvement and behavior problems was stronger in adolescents who were physically abused by their father. The association between father involvement and behavior problems did not differ by the type of father co-residing in the home. The findings suggest that policies and interventions aimed at improving the quality of fathers’ relationships and involvement with their children may be helpful in reducing behavior problems in adolescents at risk of maltreatment. PMID:29491703

A Method for Exploiting Redundancy to Accommodate Actuator Limits in Multivariable Systems

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Roulette, Greg

1995-01-01

This paper introduces a new method for accommodating actuator saturation in a multivariable system with actuator redundancy. Actuator saturation can cause significant deterioration in control system performance because unmet demand may result in sluggish transients and oscillations in response to setpoint changes. To help compensate for this problem, a technique has been developed which takes advantage of redundancy in multivariable systems to redistribute the unmet control demand over the remaining useful effectors. This method is not a redesign procedure, rather it modifies commands to the unlimited effectors to compensate for those which are limited, thereby exploiting the built-in redundancy. The original commands are modified by the increments due to unmet demand, but when a saturated effector comes off its limit, the incremental commands disappear and the original unmodified controller remains intact. This scheme provides a smooth transition between saturated and unsaturated modes as it divides up the unmet requirement over any available actuators. This way, if there is sufficiently redundant control authority, performance can be maintained.

The association of 83 plasma proteins with CHD mortality, BMI, HDL-, and total-cholesterol in men: applying multivariate statistics to identify proteins with prognostic value and biological relevance.

PubMed

Heidema, A Geert; Thissen, Uwe; Boer, Jolanda M A; Bouwman, Freek G; Feskens, Edith J M; Mariman, Edwin C M

2009-06-01

In this study, we applied the multivariate statistical tool Partial Least Squares (PLS) to analyze the relative importance of 83 plasma proteins in relation to coronary heart disease (CHD) mortality and the intermediate end points body mass index, HDL-cholesterol and total cholesterol. From a Dutch monitoring project for cardiovascular disease risk factors, men who died of CHD between initial participation (1987-1991) and end of follow-up (January 1, 2000) (N = 44) and matched controls (N = 44) were selected. Baseline plasma concentrations of proteins were measured by a multiplex immunoassay. With the use of PLS, we identified 15 proteins with prognostic value for CHD mortality and sets of proteins associated with the intermediate end points. Subsequently, sets of proteins and intermediate end points were analyzed together by Principal Components Analysis, indicating that proteins involved in inflammation explained most of the variance, followed by proteins involved in metabolism and proteins associated with total-C. This study is one of the first in which the association of a large number of plasma proteins with CHD mortality and intermediate end points is investigated by applying multivariate statistics, providing insight in the relationships among proteins, intermediate end points and CHD mortality, and a set of proteins with prognostic value.

Involvement of family members in life with type 2 diabetes: Six interconnected problem domains of significance for family health identity and healthcare authenticity

PubMed Central

Grabowski, Dan; Andersen, Tue Helms; Varming, Annemarie; Ommundsen, Christine; Willaing, Ingrid

2017-01-01

Objectives: Family involvement plays a key role in diabetes management. Problems and challenges related to type 2-diabetes often affect the whole family, and relatives are at increased risk of developing diabetes themselves. We highlight these issues in our objectives: (1) to uncover specific family problems associated with mutual involvement in life with type 2-diabetes and (2) to analytically look at ways of approaching these problems in healthcare settings. Methods: Qualitative data were gathered in participatory problem assessment workshops. The data were analysed in three rounds using radical hermeneutics. Results: Problems were categorized in six domains: knowledge, communication, support, everyday life, roles and worries. The final cross-analysis focusing on the link between family identity and healthcare authenticity provided information on how the six domains can be approached in healthcare settings. Conclusion: The study generated important knowledge about problems associated with family involvement in life with type 2 diabetes and about how family involvement can be supported in healthcare practice. PMID:28839943

A Multivariate Magnitude Robust Control Chart for Mean Shift Detection and Change Point Estimation

DTIC Science & Technology

2007-03-01

data like scratches on a desk to the width of lumber at a mill and intangible data like heart rate and microprocessor switching frequency. These...of historical data . The preferred method involves a series of designed experiments to understand what factors affect the process, and their...outcome. Since the QE is involved in every step of data collection, he/she receives exactly the data required, and possesses in-depth knowledge of the

On-line evaluation of multiloop digital controller performance

NASA Technical Reports Server (NTRS)

Wieseman, Carol D.

1993-01-01

The purpose of this presentation is to inform the Guidance and Control community of capabilities which were developed by the Aeroservoelasticity Branch to evaluate the performance of multivariable control laws, on-line, during wind-tunnel testing. The capabilities are generic enough to be useful for all kinds of on-line analyses involving multivariable control in experimental testing. Consequently, it was decided to present this material at this workshop even though it has been presented elsewhere. Topics covered include: essential on-line analysis requirements; on-line analysis capabilities; on-line analysis software; frequency domain procedures; controller performance evaluation frequency-domain flutter suppression; and plant determination.

Characterizing the associative content of brain structures involved in habitual and goal-directed actions in humans: a multivariate FMRI study.

PubMed

McNamee, Daniel; Liljeholm, Mimi; Zika, Ondrej; O'Doherty, John P

2015-03-04

While there is accumulating evidence for the existence of distinct neural systems supporting goal-directed and habitual action selection in the mammalian brain, much less is known about the nature of the information being processed in these different brain regions. Associative learning theory predicts that brain systems involved in habitual control, such as the dorsolateral striatum, should contain stimulus and response information only, but not outcome information, while regions involved in goal-directed action, such as ventromedial and dorsolateral prefrontal cortex and dorsomedial striatum, should be involved in processing information about outcomes as well as stimuli and responses. To test this prediction, human participants underwent fMRI while engaging in a binary choice task designed to enable the separate identification of these different representations with a multivariate classification analysis approach. Consistent with our predictions, the dorsolateral striatum contained information about responses but not outcomes at the time of an initial stimulus, while the regions implicated in goal-directed action selection contained information about both responses and outcomes. These findings suggest that differential contributions of these regions to habitual and goal-directed behavioral control may depend in part on basic differences in the type of information that these regions have access to at the time of decision making. Copyright © 2015 the authors 0270-6474/15/353764-08$15.00/0.

Factors influencing common diagnoses made during first-opinion small-animal consultations in the United Kingdom.

PubMed

Robinson, N J; Dean, R S; Cobb, M; Brennan, M L

2016-09-01

It is currently unclear how frequently a diagnosis is made during small-animal consultations or how much of a role making a diagnosis plays in veterinary decision-making. Understanding more about the diagnostic process will help direct future research towards areas relevant to practicing veterinary surgeons. The aim of this study was to determine the frequency with which a diagnosis was made, classify the types of diagnosis made (and the factors influencing these) and determine which specific diagnoses were made for health problems discussed during small-animal consultations. Data were gathered during real-time direct observation of small-animal consultations in eight practices in the United Kingdom. Data collected included characteristics of the consultation (e.g. consultation type), patient (e.g. breed), and each problem discussed (e.g. new or pre-existing problem). Each problem discussed was classified into one of the following diagnosis types: definitive; working; presumed; open; previous. A three-level multivariable logistic-regression model was developed, with problem (Level 1) nested within patient (Level 2) nested within consulting veterinary surgeon (Level 3). Problems without a previous diagnosis, in cats and dogs only, were included in the model, which had a binary outcome variable of definitive diagnosis versus no definitive diagnosis. Data were recorded for 1901 animals presented, and data on diagnosis were gathered for 3192 health problems. Previous diagnoses were the most common diagnosis type (n=1116/3192; 35.0%), followed by open (n=868/3192; 27.2%) then definitive (n=660/3192; 20.7%). The variables remaining in the final model were patient age, problem history, consultation type, who raised the problem, and body system affected. New problems, problems in younger animals, and problems raised by the veterinary surgeon were more likely to result in a definitive diagnosis than pre-existing problems, problems in older animals, and problems raised by the owner. The most common diagnoses made were overweight/obese and periodontal disease (both n=210; 6.6%). Definitive diagnoses are rarely made during small-animal consultations, with much of the veterinary caseload involving management of ongoing problems or making decisions around new problems prior to a diagnosis being made. This needs to be taken into account when considering future research priorities, and it may be necessary to conduct research focused on the approach to common clinical presentations, rather than purely on the common diagnoses made. Examining how making a diagnosis affects the actions taken during the consultation may shed further light on the role of diagnosis in the clinical decision-making process. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Anabolic-androgenic steroid use and involvement in violent behavior in a nationally representative sample of young adult males in the United States.

PubMed

Beaver, Kevin M; Vaughn, Michael G; Delisi, Matt; Wright, John Paul

2008-12-01

We examined the effects of anabolic-androgenic steroid use on serious violent behavior. Multivariate models based on data from the National Longitudinal Study of Adolescent Health (N = 6823) were used to examine the association between lifetime and past-year self-reported anabolic-androgenic steroid use and involvement in violent acts. Compared with individuals who did not use steroids, young adult males who used anabolic-androgenic steroids reported greater involvement in violent behaviors after we controlled for the effects of key demographic variables, previous violent behavior, and polydrug use.

Synthesis of linear regression coefficients by recovering the within-study covariance matrix from summary statistics.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-06-01

Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

State-Space Analysis of Granger-Geweke Causality Measures with Application to fMRI.

PubMed

Solo, Victor

2016-05-01

The recent interest in the dynamics of networks and the advent, across a range of applications, of measuring modalities that operate on different temporal scales have put the spotlight on some significant gaps in the theory of multivariate time series. Fundamental to the description of network dynamics is the direction of interaction between nodes, accompanied by a measure of the strength of such interactions. Granger causality and its associated frequency domain strength measures (GEMs) (due to Geweke) provide a framework for the formulation and analysis of these issues. In pursuing this setup, three significant unresolved issues emerge. First, computing GEMs involves computing submodels of vector time series models, for which reliable methods do not exist. Second, the impact of filtering on GEMs has never been definitively established. Third, the impact of downsampling on GEMs has never been established. In this work, using state-space methods, we resolve all these issues and illustrate the results with some simulations. Our analysis is motivated by some problems in (fMRI) brain imaging, to which we apply it, but it is of general applicability.

State-Space Analysis of Granger-Geweke Causality Measures with Application to fMRI

PubMed Central

Solo, Victor

2017-01-01

The recent interest in the dynamics of networks and the advent, across a range of applications, of measuring modalities that operate on different temporal scales have put the spotlight on some significant gaps in the theory of multivariate time series. Fundamental to the description of network dynamics is the direction of interaction between nodes, accompanied by a measure of the strength of such interactions. Granger causality and its associated frequency domain strength measures (GEMs) (due to Geweke) provide a framework for the formulation and analysis of these issues. In pursuing this setup, three significant unresolved issues emerge. First, computing GEMs involves computing submodels of vector time series models, for which reliable methods do not exist. Second, the impact of filtering on GEMs has never been definitively established. Third, the impact of downsampling on GEMs has never been established. In this work, using state-space methods, we resolve all these issues and illustrate the results with some simulations. Our analysis is motivated by some problems in (fMRI) brain imaging, to which we apply it, but it is of general applicability. PMID:26942749

The prevalence of obesity documentation in Primary Care Electronic Medical Records

PubMed Central

Mattar, Ahmed; Carlston, David; Sariol, Glen; Yu, Tongle; Almustafa, Ahmad; Melton, Genevieve B.

2017-01-01

Summary Background Although obesity is a growing problem, primary care physicians often inadequately address it. The objective of this study is to examine the prevalence of obesity documentation in the patient’s problem list for patients with eligible body mass indexes (BMI) as contained in the patients’ electronic medical record (EMR). Additionally, we examined the prevalence of selected chronic conditions across BMI levels. Method This study is a retrospective study using EMR data for adult patients visiting an outpatient clinic between June 2012 and June 2015. International Classification of Diseases, Ninth Revision, (ICD-9) codes were used to identify obesity documentation in the EMR problem list. Univariate and multivariate logistic regression analyses were used. Results Out of 10,540, a total of 3,868 patients were included in the study. 2,003 (52%) patients met the criteria for obesity (BMI ≥ 30.0); however, only 112 (5.6%) patient records included obesity in the problem list. Moreover, in a multivariate analysis, in addition to age and gender, morbid obesity and cumulative number of comorbidities were significantly associated with obesity documentation, OR=1.6 and OR=1.3, respectively, with 95% CI [1.4, 1.9] and [1.0, 1.7], respectively. For those with obesity documentation, exercise counseling was provided more often than diet counselling. Conclusion Based on EHR documentation, obesity is under coded and generally not identified as a significant problem in primary care. Physicians are more likely to document obesity in the patient record for those with higher BMI scores who are morbidly obese. Moreover, physicians more frequently provide exercise than diet counseling for the documented obese. PMID:28119990

Estimating Peer Effects in Sexual Behavior among Adolescents

ERIC Educational Resources Information Center

Ali, Mir M.; Dwyer, Debra S.

2011-01-01

In this paper we seek to empirically quantify the role of peer social networks in influencing sexual behavior among adolescents. Using data of a nationally representative sample of adolescents we utilize a multivariate structural model with school-level fixed effects to account for the problems of contextual effects, correlated effects and peer…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

Changes in Loneliness during Middle Childhood Predict Risk for Adolescent Suicidality Indirectly through Mental Health Problems

ERIC Educational Resources Information Center

Jones, Angela C.; Schinka, Katherine C.; van Dulmen, Manfred H. M.; Bossarte, Robert M.; Swahn, Monica H.

2011-01-01

We investigated whether changes in loneliness during middle childhood as well as from middle childhood into adolescence were associated with adolescent self-harm behaviors and suicidal thoughts using a community sample of 889 participants. Multivariate logistic regressions indicate that the relationship between changes in loneliness and…

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

ERIC Educational Resources Information Center

Duvvuri, Sri Devi; Gruca, Thomas S.

2010-01-01

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

AAHPER Research Consortium Symposium Papers: Socio-Psychological Dimensions, Research Design and Safety. Volume II, Book 3.

ERIC Educational Resources Information Center

Cox, Richard H., Ed.

This collection focuses on research topics in physical education and athletics and includes the following papers: Methodological Problems in the Assessment of Personality from the Psychoanalytic, Behavioral and Cognitive Positions; Some Factors Affecting the Performance of Women in Sports and Activity; Multivariate Considerations in Children's…

Interpretable Early Classification of Multivariate Time Series

ERIC Educational Resources Information Center

Ghalwash, Mohamed F.

2013-01-01

Recent advances in technology have led to an explosion in data collection over time rather than in a single snapshot. For example, microarray technology allows us to measure gene expression levels in different conditions over time. Such temporal data grants the opportunity for data miners to develop algorithms to address domain-related problems,…

A Lesson in Vectors "Plain" and Simple

ERIC Educational Resources Information Center

Bradshaw, David M.

2004-01-01

The United States Military Academy (USMA) has a four course core mathematics curriculum that is studied by all students. The third course is MA205, Calculus II; a multivariate calculus course filled with practical applications. During a Problem Solving Lab (PSL), students participated in a hands-on exercise with multiple vector operations,…

Conceptual and statistical problems associated with the use of diversity indices in ecology.

PubMed

Barrantes, Gilbert; Sandoval, Luis

2009-09-01

Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing patterns of diversity at different geographic and ecological scales. These indices have serious conceptual and statistical problems which make comparisons of species richness or species abundances across communities nearly impossible. There is often no a single statistical method that retains all information needed to answer even a simple question. However, multivariate analyses could be used instead of diversity indices, such as cluster analyses or multiple regressions. More complex multivariate analyses, such as Canonical Correspondence Analysis, provide very valuable information on environmental variables associated to the presence and abundance of the species in a community. In addition, particular hypotheses associated to changes in species richness across localities, or change in abundance of one, or a group of species can be tested using univariate, bivariate, and/or rarefaction statistical tests. The rarefaction method has proved to be robust to standardize all samples to a common size. Even the simplest method as reporting the number of species per taxonomic category possibly provides more information than a diversity index value.

Application of multivariable search techniques to structural design optimization

NASA Technical Reports Server (NTRS)

Jones, R. T.; Hague, D. S.

1972-01-01

Multivariable optimization techniques are applied to a particular class of minimum weight structural design problems: the design of an axially loaded, pressurized, stiffened cylinder. Minimum weight designs are obtained by a variety of search algorithms: first- and second-order, elemental perturbation, and randomized techniques. An exterior penalty function approach to constrained minimization is employed. Some comparisons are made with solutions obtained by an interior penalty function procedure. In general, it would appear that an interior penalty function approach may not be as well suited to the class of design problems considered as the exterior penalty function approach. It is also shown that a combination of search algorithms will tend to arrive at an extremal design in a more reliable manner than a single algorithm. The effect of incorporating realistic geometrical constraints on stiffener cross-sections is investigated. A limited comparison is made between minimum weight cylinders designed on the basis of a linear stability analysis and cylinders designed on the basis of empirical buckling data. Finally, a technique for locating more than one extremal is demonstrated.

Examining Middle School Pre-Service Teachers' Knowledge of Fraction Division Interpretations

ERIC Educational Resources Information Center

Alenazi, Ali

2016-01-01

This study investigated 11 pre-service middle school teachers' solution strategies for exploring their knowledge of fraction division interpretations. Each participant solved six fraction division problems. The problems were organized into two sets: symbolic problems (involving numbers only) and contextual problems (involving measurement…

Service use by Australian children for emotional and behavioural problems: Findings from the second Australian Child and Adolescent Survey of Mental Health and Wellbeing.

PubMed

Johnson, Sarah E; Lawrence, David; Hafekost, Jennifer; Saw, Suzy; Buckingham, William J; Sawyer, Michael; Ainley, John; Zubrick, Stephen R

2016-09-01

To identify the proportion of children and adolescents in Australia and the proportion of those with mental disorders who used services for emotional and behavioural problems, the type of services used and what characteristics were associated with service use. During 2013-2014, a national face-to-face household survey of mental health and wellbeing (Young Minds Matter) was conducted, involving 6310 parents and carers of 4- to 17-year-olds (55% of eligible households) and self-report surveys from 2967 11- to 17-year-olds in these households (89% of eligible youth). The survey identified 12-month mental disorders based on the Diagnostic Interview Schedule for Children-Version IV and asked about service use for emotional or behavioural problems in the previous 12 months. Overall, 17.0% of all 4- to 17-year-olds used services for emotional or behavioural problems in the previous 12 months. Of those with mental disorders, 56.0% used services (48.9% of 4- to 11-year-olds; 65.1% of 12- to 17-year-olds). Service use was highest among 4- to 17-year-olds with major depressive disorder (79.6%) and lowest for those with attention-deficit/hyperactivity disorder (52.7%). Two-fifths (41.2%), 72.5% and 87.6% of those with mild, moderate and severe disorders used services. General practitioners, psychologists, paediatricians and counsellors/family therapists were the most commonly accessed health service providers. Two-fifths with mental disorders had attended school services. About 5% of adolescents reported use of online personal support or counselling for help with their problems. From multivariate models, service use was higher in sole carer families, but also among those living in the least socially and economically disadvantaged compared to the most disadvantaged areas. Rates of service use for mental disorders in Australia's children and adolescents appear to have increased substantially. Health services and schools are the major providers of services for emotional and behavioural problems, but telephone counselling and online services have become well-established parts of the service environment. © The Royal Australian and New Zealand College of Psychiatrists 2016.

Introduction to multivariate discrimination

NASA Astrophysics Data System (ADS)

Kégl, Balázs

2013-07-01

Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either relevant to or even motivated by certain unorthodox applications of multivariate discrimination in experimental physics.

On the Directional Dependence and Null Space Freedom in Uncertainty Bound Identification

NASA Technical Reports Server (NTRS)

Lim, K. B.; Giesy, D. P.

1997-01-01

In previous work, the determination of uncertainty models via minimum norm model validation is based on a single set of input and output measurement data. Since uncertainty bounds at each frequency is directionally dependent for multivariable systems, this will lead to optimistic uncertainty levels. In addition, the design freedom in the uncertainty model has not been utilized to further reduce uncertainty levels. The above issues are addressed by formulating a min- max problem. An analytical solution to the min-max problem is given to within a generalized eigenvalue problem, thus avoiding a direct numerical approach. This result will lead to less conservative and more realistic uncertainty models for use in robust control.

Parameter estimation of multivariate multiple regression model using bayesian with non-informative Jeffreys’ prior distribution

NASA Astrophysics Data System (ADS)

Saputro, D. R. S.; Amalia, F.; Widyaningsih, P.; Affan, R. C.

2018-05-01

Bayesian method is a method that can be used to estimate the parameters of multivariate multiple regression model. Bayesian method has two distributions, there are prior and posterior distributions. Posterior distribution is influenced by the selection of prior distribution. Jeffreys’ prior distribution is a kind of Non-informative prior distribution. This prior is used when the information about parameter not available. Non-informative Jeffreys’ prior distribution is combined with the sample information resulting the posterior distribution. Posterior distribution is used to estimate the parameter. The purposes of this research is to estimate the parameters of multivariate regression model using Bayesian method with Non-informative Jeffreys’ prior distribution. Based on the results and discussion, parameter estimation of β and Σ which were obtained from expected value of random variable of marginal posterior distribution function. The marginal posterior distributions for β and Σ are multivariate normal and inverse Wishart. However, in calculation of the expected value involving integral of a function which difficult to determine the value. Therefore, approach is needed by generating of random samples according to the posterior distribution characteristics of each parameter using Markov chain Monte Carlo (MCMC) Gibbs sampling algorithm.

Field applications of stand-off sensing using visible/NIR multivariate optical computing

NASA Astrophysics Data System (ADS)

Eastwood, DeLyle; Soyemi, Olusola O.; Karunamuni, Jeevanandra; Zhang, Lixia; Li, Hongli; Myrick, Michael L.

2001-02-01

12 A novel multivariate visible/NIR optical computing approach applicable to standoff sensing will be demonstrated with porphyrin mixtures as examples. The ultimate goal is to develop environmental or counter-terrorism sensors for chemicals such as organophosphorus (OP) pesticides or chemical warfare simulants in the near infrared spectral region. The mathematical operation that characterizes prediction of properties via regression from optical spectra is a calculation of inner products between the spectrum and the pre-determined regression vector. The result is scaled appropriately and offset to correspond to the basis from which the regression vector is derived. The process involves collecting spectroscopic data and synthesizing a multivariate vector using a pattern recognition method. Then, an interference coating is designed that reproduces the pattern of the multivariate vector in its transmission or reflection spectrum, and appropriate interference filters are fabricated. High and low refractive index materials such as Nb2O5 and SiO2 are excellent choices for the visible and near infrared regions. The proof of concept has now been established for this system in the visible and will later be extended to chemicals such as OP compounds in the near and mid-infrared.

Arrowheaded enhanced multivariance products representation for matrices (AEMPRM): Specifically focusing on infinite matrices and converting arrowheadedness to tridiagonality

NASA Astrophysics Data System (ADS)

Özdemir, Gizem; Demiralp, Metin

2015-12-01

In this work, Enhanced Multivariance Products Representation (EMPR) approach which is a Demiralp-and-his- group extension to the Sobol's High Dimensional Model Representation (HDMR) has been used as the basic tool. Their discrete form have also been developed and used in practice by Demiralp and his group in addition to some other authors for the decomposition of the arrays like vectors, matrices, or multiway arrays. This work specifically focuses on the decomposition of infinite matrices involving denumerable infinitely many rows and columns. To this end the target matrix is first decomposed to the sum of certain outer products and then each outer product is treated by Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) which has been developed by Demiralp and his group. The result is a three-matrix- factor-product whose kernel (the middle factor) is an arrowheaded matrix while the pre and post factors are invertable matrices decomposed of the support vectors of TMEMPR. This new method is called as Arrowheaded Enhanced Multivariance Products Representation for Matrices. The general purpose is approximation of denumerably infinite matrices with the new method.

Applying Sociocultural Theory to Teaching Statistics for Doctoral Social Work Students

ERIC Educational Resources Information Center

Mogro-Wilson, Cristina; Reeves, Michael G.; Charter, Mollie Lazar

2015-01-01

This article describes the development of two doctoral-level multivariate statistics courses utilizing sociocultural theory, an integrative pedagogical framework. In the first course, the implementation of sociocultural theory helps to support the students through a rigorous introduction to statistics. The second course involves students…

Mean Comparison: Manifest Variable versus Latent Variable

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Bentler, Peter M.

2006-01-01

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

Connectedness, social support and internalising emotional and behavioural problems in adolescents displaced by the Chechen conflict

PubMed Central

Betancourt, Theresa S.; Salhi, Carmel; Buka, Stephen; Leaning, Jennifer; Dunn, Gillian; Earls, Felton

2013-01-01

The study investigated factors associated with internalising emotional and behavioural problems among adolescents displaced during the most recent Chechen conflict. A cross-sectional survey (N=183) examined relationships between social support and connectedness with family, peers and community in relation to internalising problems. Levels of internalising were higher in displaced Chechen youth compared to published norms among non-referred youth in the United States and among Russian children not affected by conflict. Girls demonstrated higher problem scores compared to boys. Significant inverse correlations were observed between family, peer and community connectedness and internalising problems. In multivariate analyses, family connectedness was indicated as a significant predictor of internalising problems, independent of age, gender, housing status and other forms of support evaluated. Sub-analyses by gender indicated stronger protective relationships between family connectedness and internalising problems in boys. Results indicate that family connectedness is an important protective factor requiring further exploration by gender in war-affected adolescents. PMID:22443099

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. Availability The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana. PMID:24564704

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana.

The intergenerational transmission of at-risk/problem gambling: The moderating role of parenting practices.

PubMed

Dowling, Nicki A; Shandley, Kerrie A; Oldenhof, Erin; Affleck, Julia M; Youssef, George J; Frydenberg, Erica; Thomas, Shane A; Jackson, Alun C

2017-10-01

Although parenting practices are articulated as underlying mechanisms or protective factors in several theoretical models, their role in the intergenerational transmission of gambling problems has received limited research attention. This study therefore examined the degree to which parenting practices (positive parenting, parental involvement, and inconsistent discipline) moderated the intergenerational transmission of paternal and maternal problem gambling. Students aged 12-18 years (N = 612) recruited from 17 Australian secondary schools completed a survey measuring parental problem gambling, problem gambling severity, and parenting practices. Participants endorsing paternal problem gambling (23.3%) were 4.3 times more likely to be classified as at-risk/problem gamblers than their peers (5.4%). Participants endorsing maternal problem gambling (6.9%) were no more likely than their peers (4.0%) to be classified as at-risk/problem gamblers. Paternal problem gambling was a significant predictor of offspring at-risk/problem gambling after controlling for maternal problem gambling and participant demographic characteristics. The relationship between maternal problem gambling and offspring at-risk/problem gambling was buffered by parental involvement. Paternal problem gambling may be important in the development of adolescent at-risk/problem gambling behaviours and higher levels of parental involvement buffers the influence of maternal problem gambling in the development of offspring gambling problems. Further research is therefore required to identify factors that attenuate the seemingly greater risk of transmission associated with paternal gambling problems. Parental involvement is a potential candidate for prevention and intervention efforts designed to reduce the intergenerational transmission of gambling problems. (Am J Addict 2017;26:707-712). © 2017 American Academy of Addiction Psychiatry.

A 2-year longitudinal study of prospective predictors of pathological Internet use in adolescents.

PubMed

Strittmatter, Esther; Parzer, Peter; Brunner, Romuald; Fischer, Gloria; Durkee, Tony; Carli, Vladimir; Hoven, Christina W; Wasserman, Camilla; Sarchiapone, Marco; Wasserman, Danuta; Resch, Franz; Kaess, Michael

2016-07-01

Longitudinal studies of prospective predictors for pathological Internet use (PIU) in adolescents as well as its course are lacking. This three-wave longitudinal study was conducted within the framework of the European Union-funded project "Saving and Empowering Young Lives in Europe" over a 2-year period. The sample consisted of 1444 students at the baseline investigation (T0); 1202 students after 1 year (T1); and 515 students after 2 years (T2). Structured self-report questionnaires were administered at all three time points. PIU was assessed using the Young Diagnostic Questionnaire (YDQ). In addition, demographic (i.e., gender), social (i.e., parental involvement), psychological (i.e., emotional problems), and Internet use-related factors (i.e., online activities) were assessed as prospective predictors. The prevalence of PIU was 4.3 % at T0, 2.7 % at T1 and 3.1 % at T2. However, only 3 students (0.58 %) had persistent categorical PIU (YDQ score of ≥5) over the 2-year period. In univariate models, a variety of variables that have been previously identified in cross-sectional investigations predicted PIU at T2. However, multivariate regression demonstrated that only previous PIU symptoms and emotional problems were significant predictors of PIU 2 years later (adjusted R (2) 0.23). The stability of categorical PIU in adolescents over 2 years was lower than previously reported. However, current PIU symptoms were the best predictor of later PIU; emotional symptoms also predicted PIU over and above the influence of previous problematic Internet use. Both PIU symptoms and emotional problems may contribute to the vicious cycle that supports the perpetuation of PIU.

The Association of Health and Employment in Mature Women: A Longitudinal Study

PubMed Central

Byles, Julie

2012-01-01

Abstract Background Despite a reduction in income inequalities between men and women, there is still a large gap between income and retirement savings of Australian men and women. This is especially true for women who have health or disability problems. Mature age women are closest to retirement and, therefore, have less chance than younger women to build up enough retirement savings and may need to continue working to fund their older age. Continued workforce participation may be particularly difficult for women who are less healthy. Understanding which health problems lead to a decrease in workforce participation among mature age women is crucial. Therefore, this longitudinal study sought to identify which health problems are associated with employment among midage women over time. Methods Data were analyzed from the midage cohort of the Australian Longitudinal Study on Women's Health (ALSWH), which involved 14,200 midage women (aged 45–50 years in 1996). The women have been surveyed four additional times, in 1998, 2001, 2004, and 2007. Generalized estimating equations (GEE) were used to conduct nested multivariate longitudinal analyses. Results The percentages of women who were employed in the years 2001, 2004, and 2007 were 77%, 72%, and 68%, respectively. Results were adjusted for sociodemographic variables. Being employed decreased as physical and mental health deteriorated and with self-reported conditions: diabetes, high blood pressure, depression, anxiety, and other psychiatric conditions. Back pain, arthritis, cancer, obesity, and being a current smoker are associated with employment but not when quality of life is added to the model. Conclusions There were significant associations between health and employment. Understanding these relationships could inform policies and guidelines for preventing declines in employment in mature age women. PMID:22060315

Predictors of parenting stress in a diverse sample of parents of early adolescents in high-risk communities.

PubMed

Anderson, Lori S

2008-01-01

Parenting stress is associated with negative parenting practices, which have been linked to increased youth health risk behaviors. It is important, therefore, to understand the most salient contributors to parenting stress in families who live in communities considered at high risk of the development of youth problem behaviors. On the basis of a model derived from the model of parenting stress of R. R. Abidin (1995), the contributions to parenting stress of child factors (age, social skills, and problem behaviors), parent factors (gender, health, and race or ethnicity), and contextual factors (family structure, conflict, social support, education, and income) were explored. A secondary data analysis using bivariate correlations and multiple and hierarchical regression was conducted to identify the relative influence of these factors on parenting stress in a national sample of 824 parents (primarily mothers, those from racial or ethnic minorities, and those who have low income) of adolescents aged 10-18 years. Analyses indicated strong associations between child behavior and parenting stress (p < .001). There was a positive association between youth age and parenting stress. Single parents and parents in poor health reported significantly high levels of parenting stress; families with high levels of involvement and cohesion reported significantly less stress. The data support the multivariate model of parenting stress of R. R. Abidin (1995). Parents of adolescents experience a high level of parenting stress that can compromise their ability to parent effectively. Identification of child, parent, and contextual characteristics that are associated with parenting stress may facilitate our understanding of how healthcare, social service, and education providers can prepare and support parents to reduce the risk of problem behavior.

Follow-up care of young childhood cancer survivors: attendance and parental involvement.

PubMed

Vetsch, Janine; Rueegg, Corina S; Mader, Luzius; Bergstraesser, Eva; Rischewski, Johannes; Kuehni, Claudia E; Michel, Gisela

2016-07-01

Despite recommendations, only a proportion of long-term childhood cancer survivors attend follow-up care. We aimed to (1) describe the follow-up attendance of young survivors aged 11-17 years; (2) describe the parental involvement in follow-up, and (3) investigate predictors of follow-up attendance and parental involvement. As part of the Swiss Childhood Cancer Survivor Study, a follow-up questionnaire was sent to parents of childhood cancer survivors aged 11-17 years. We assessed follow-up attendance of the child, parents' involvement in follow-up, illness perception (Brief IPQ), and sociodemographic data. Clinical data was available from the Swiss Childhood Cancer Registry. Of 309 eligible parents, 189 responded (67 %; mean time since diagnosis 11.3 years, range 6.8-17.2) and 75 % (n = 141) reported that their child still attended follow-up. Of these, 83 % (n = 117) reported ≥1 visit per year and 17 % (n = 23) reported <1 visit every year. Most survivors saw pediatric oncologists (n = 111; 79 % of 141), followed by endocrinologists (n = 24, 17 %) and general practitioners (n = 22, 16 %). Most parents (92 %) reported being involved in follow-up (n = 130). In multivariable and Cox regression analyses, longer time since diagnosis (p = 0.025) and lower perceived treatment control (assessed by IPQ4: how much parents thought follow-up can help with late effects; p = 0.009) were associated with non-attendance. Parents' overall information needs was significantly associated with parental involvement in the multivariable model (p = 0.041). Educating survivors and their parents on the importance and effectiveness of follow-up care might increase attendance in the longer term.

Maternal Depressive Symptoms and Child Behavior Problems among Latina Adolescent Mothers: The Buffering Effect of Mother-reported Partner Child Care Involvement

PubMed Central

Smith, Erin N.; Grau, Josefina M.; Duran, Petra A.; Castellanos, Patricia

2013-01-01

We examined the relations between maternal depressive symptoms and child internalizing and externalizing problems in a sample of 125 adolescent Latina mothers (primarily Puerto Rican) and their toddlers. We also tested the influence of mother-reported partner child care involvement on child behavior problems and explored mother-reported partner characteristics that related to this involvement. Results suggested that maternal depressive symptoms related to child internalizing and externalizing problems when accounting for contextual risk factors. Importantly, these symptoms mediated the link between life stress and child behavior problems. Mother-reported partner child care interacted with maternal depressive symptoms for internalizing, not externalizing, problems. Specifically, depressive symptoms related less strongly to internalizing problems at higher levels of partner child care than at lower levels. Participants with younger partners, co-residing partners, and in longer romantic relationships reported higher partner child care involvement. Results are discussed considering implications for future research and interventions for mothers, their children, and their partners. PMID:24339474

Quantitative methods for analysing cumulative effects on fish migration success: a review.

PubMed

Johnson, J E; Patterson, D A; Martins, E G; Cooke, S J; Hinch, S G

2012-07-01

It is often recognized, but seldom addressed, that a quantitative assessment of the cumulative effects, both additive and non-additive, of multiple stressors on fish survival would provide a more realistic representation of the factors that influence fish migration. This review presents a compilation of analytical methods applied to a well-studied fish migration, a more general review of quantitative multivariable methods, and a synthesis on how to apply new analytical techniques in fish migration studies. A compilation of adult migration papers from Fraser River sockeye salmon Oncorhynchus nerka revealed a limited number of multivariable methods being applied and the sub-optimal reliance on univariable methods for multivariable problems. The literature review of fisheries science, general biology and medicine identified a large number of alternative methods for dealing with cumulative effects, with a limited number of techniques being used in fish migration studies. An evaluation of the different methods revealed that certain classes of multivariable analyses will probably prove useful in future assessments of cumulative effects on fish migration. This overview and evaluation of quantitative methods gathered from the disparate fields should serve as a primer for anyone seeking to quantify cumulative effects on fish migration survival. © 2012 The Authors. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.

Multivariate moment closure techniques for stochastic kinetic models

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

Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.

2015-09-07

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporallymore » evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.« less

Physical dating violence among adolescents and young adults with alcohol misuse.

PubMed

Singh, Vijay; Epstein-Ngo, Quyen; Cunningham, Rebecca M; Stoddard, Sarah A; Chermack, Stephen T; Walton, Maureen A

2015-08-01

This study determined prevalence and correlates of physical dating violence (victimization or aggression) among male and female youth with alcohol misuse and seeking emergency department (ED) care. Patients age 14-20 seeking care at a single large university-based ED completed a computerized, self-administered, cross-sectional survey. Measures included demographics, alcohol and substance use, mental health problems, health service use, peer influences, parent support, and community involvement. Bivariate and multivariate regression assessed physical dating violence correlates. Among 842 male and female youth seeking ED care who screened positive for alcohol misuse, 22.3% (n=188) reported dating violence in the past year. Multivariate analyses showed variables associated with dating violence were female gender (AOR 2.17, CI 1.46-3.22), Caucasian race (AOR 0.59, CI 0.37-0.93), receipt of public assistance (AOR 1.82, CI 1.16-2.87), AUDIT Score (AOR 1.06, CI 1.02-1.10), older age of drinking onset (AOR 0.86, CI 0.77-0.96), suicidal ideation or attempt (AOR 1.95, CI 1.13-3.37), frequency of ED visits (AOR 1.22, CI 1.05-1.46), negative peer influences (AOR 1.05, CI 1.01-1.10), and positive peer influences (AOR 0.86, CI 0.80-0.93). Nearly 1 in 4 youth with alcohol misuse seeking ED care report dating violence. Key correlates of dating violence included alcohol use severity, suicidal ideation, ED services, and peer influences. Evidence-based dating violence interventions addressing these correlates are needed for youth with alcohol misuse seeking ED care. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Coping Styles, Well-Being and Self-Care Behaviors Among African Americans With Type 2 Diabetes

PubMed Central

Samuel-Hodge, Carmen D.; Watkins, Daphne C.; Rowell, Kyrel L.; Hooten, Elizabeth G.

2009-01-01

Purpose The purpose of this study was to describe how coping styles among African Americans with type 2 diabetes relate to diabetes appraisals, self-care behaviors, and health-related quality of life or well-being. Methods This cross-sectional analysis of baseline measures from 185 African Americans with type 2 diabetes enrolled in a church-based randomized controlled trial uses the theoretical framework of the transactional model of stress and coping to describe bivariate and multivariate associations among coping styles, psychosocial factors, self-care behaviors, and well-being, as measured by validated questionnaires. Results Among participants who were on average 59 years of age with 9 years of diagnosed diabetes, passive and emotive styles of coping were used most frequently, with older and less educated participants using more often passive forms of coping. Emotive styles of coping were significantly associated with greater perceived stress, problem areas in diabetes, and negative appraisals of diabetes control. Both passive and active styles of coping were associated with better diabetes self-efficacy and competence in bivariate analysis. In multivariate analysis, significant proportions of the variance in dietary behaviors and mental well-being outcomes (general and diabetes specific) were explained, with coping styles among the independent predictors. A positive role for church involvement in the psychological adaptation to living with diabetes was also observed. Conclusions In this sample of older African Americans with diabetes, coping styles were important factors in diabetes appraisals, self-care behaviors, and psychological outcomes. These findings suggest potential benefits in emphasizing cognitive and behavioral strategies to promote healthy coping outcomes in persons living with diabetes. PMID:18535323

Extensive countrywide field investigation of subclinical mastitis in sheep in Greece.

PubMed

Vasileiou, N G C; Cripps, P J; Ioannidi, K S; Chatzopoulos, D C; Gougoulis, D A; Sarrou, S; Orfanou, D C; Politis, A P; Gonzalez-Valerio, T Calvo; Argyros, S; Mavrogianni, V S; Petinaki, E; Fthenakis, G C

2018-05-30

The objectives of this work were (1) to investigate prevalence of subclinical mastitis, (2) to identify etiological agents involved, and (3) to study factors potentially predisposing ewes to subclinical mastitis. Milk samples were collected from 2,198 ewes in 111 farms with a total population of 35,925 ewes, in all 13 administrative regions of Greece, for bacteriological and cytological examination. Prevalence of subclinical mastitis was 0.260. Main etiological agents were staphylococci (Staphylococcus aureus and coagulase-negative species), which accounted for 0.699 of all isolates recovered; prevalence of staphylococcal mastitis was 0.191. In a multivariable mixed-effects analysis, the primary factor found to be associated with increased prevalence of subclinical mastitis was the management system practiced in flocks (flocks under a semi-intensive system had the highest prevalence). Other factors that were included in the multivariable model were the stage of lactation period (ewes in the 2nd month postpartum showed the highest prevalence) and application of postmilking teat dipping. In contrast, measures taken at the end of a lactation period (e.g., intramammary administration of antimicrobial agents) were not found to have an effect on prevalence of subclinical mastitis. The results confirmed the significance of subclinical mastitis as a frequent problem of ewes, with staphylococci as the primary etiological agent. The findings confirm the multifactorial nature of subclinical mastitis and indicate that its control should rely on many approaches. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Use of dental services by immigration status in the United States.

PubMed

Wilson, Fernando A; Wang, Yang; Stimpson, Jim P; McFarland, Kimberly K; Singh, Karan P

2016-03-01

There is limited research with mixed findings comparing differences in oral health outcomes and the use of dental services by immigration status. The authors conducted a study by reviewing nationally representative data to describe differences in dental care among noncitizens, naturalized citizens, and US-born citizens in the United States. The authors used nationally representative data from the 2008-2012 Medical Expenditure Panel Survey to examine dental care for US-born citizens, naturalized citizens, and noncitizens 18 years and older. Total analytical sample size was 98,107 adults. They used multivariate logistic regression to model dental service use adjusting for confounding factors. Naturalized citizens and noncitizens were significantly less likely to have at least 1 dental visit within 12 months (39.5% and 23.1%, respectively) compared with US-born citizens (43.6%; P < .001). Among users, a smaller proportion of comprehensive examination visits were for naturalized citizens and noncitizens (75.9% and 71.4%, respectively) compared with US-born citizens (82.8%; P < .01). Noncitizen visits to dentists were also more likely to involve tooth extraction compared with those of US-born citizens (11.3% versus 8.8%; P < .01). Multivariate logistic regression suggests both non- and naturalized citizens had lower adjusted odds of having a comprehensive examination compared with US-born citizens during a visit (P < .01). Noncitizens and naturalized citizens had a lower rate of dental service use, and noncitizens were more likely to have had tooth extraction compared with US-born citizens. Increased outreach efforts tailored to noncitizens and naturalized citizens who are at high risk of experiencing dental problems are needed, particularly to address misperceptions on the necessity of preventive dental visits. Copyright © 2016 American Dental Association. Published by Elsevier Inc. All rights reserved.

Problem Solving and Computational Skill: Are They Shared or Distinct Aspects of Mathematical Cognition?

PubMed Central

Fuchs, Lynn S.; Fuchs, Douglas; Hamlett, Carol L.; Lambert, Warren; Stuebing, Karla; Fletcher, Jack M.

2009-01-01

The purpose of this study was to explore patterns of difficulty in 2 domains of mathematical cognition: computation and problem solving. Third graders (n = 924; 47.3% male) were representatively sampled from 89 classrooms; assessed on computation and problem solving; classified as having difficulty with computation, problem solving, both domains, or neither domain; and measured on 9 cognitive dimensions. Difficulty occurred across domains with the same prevalence as difficulty with a single domain; specific difficulty was distributed similarly across domains. Multivariate profile analysis on cognitive dimensions and chi-square tests on demographics showed that specific computational difficulty was associated with strength in language and weaknesses in attentive behavior and processing speed; problem-solving difficulty was associated with deficient language as well as race and poverty. Implications for understanding mathematics competence and for the identification and treatment of mathematics difficulties are discussed. PMID:20057912

The longitudinal relationship between behavior and emotional disturbance in young people with intellectual disability and maternal mental health

PubMed Central

Gray, Kylie M; Piccinin, Andrea M; Hofer, Scott M; Mackinnon, Andrew; Bontempo, Daniel E; Einfeld, Stewart L; Parmenter, Trevor; Tonge, Bruce J

2011-01-01

Although elevated rates of parent psychosocial distress have been associated with child behavior and emotional problems, little is known about the nature of this relationship over time. This study followed an epidemiological cohort of children and adolescents over 11 years with 4 waves of data collection. Within this cohort, complete data were available on 238 mothers and their children. Behavior and emotional problems were assessed using the DBC, maternal mental health with the GHQ. Multivariate growth curve modelling was used to evaluate the commonality of individual change patterns. High levels of mental health problems were reported, which were stable over time. Higher scores on the DBC were associated with higher rates of mental health problems. Increases in child social relating problems were associated with increases mental health symptoms, particularly depression and anxiety. PMID:21295442

Behavioral correlation with television watching and videogame playing among children in the United Arab Emirates.

PubMed

Yousef, Said; Eapen, Valsamma; Zoubeidi, Taoufik; Mabrouk, Abdelazim

2014-08-01

Television viewing and videogame use (TV/VG) appear to be associated with some childhood behavioral problems. There are no studies addressing this problem in the United Arab Emirates. One hundred ninety-seven school children (mean age, 8.7 ± 2.1 years) were assessed. Child Behavior Checklist (CBCL) subscale scores and socio-demographic characteristics were compared between children who were involved with TV/VG more than 2 hours/day and those involved less than 2 hours/day (the recommended upper limit by The American Academy of Pediatrics). Thirty-seven percent of children who were involved with TV/VG time of more than 2 hours/day scored significantly higher on CBCL syndrome scales of withdrawn, social problems, attention problems, delinquent behavior, aggressive behavior, internalizing problems, externalizing problems and the CBCL total scores compared with their counterparts. Moreover, these children were younger in birth order and had fewer siblings. After controlling for these confounders using logistic regression, we found that TV/VG time more than 2 hours/day was positively associated with withdrawn (p = 0.008), attention problem (p = 0.037), externalizing problems (p = 0.007), and CBCL total (p = 0.014). Involvement with TV/VG for more than 2 hours/day is associated with more childhood behavioral problems. Counteracting negative effects of the over-involvement with TV/VG in children requires increased parental awareness.

Childhood adversity in association with personality disorder dimensions: new findings in an old debate.

PubMed

Hengartner, M P; Ajdacic-Gross, V; Rodgers, S; Müller, M; Rössler, W

2013-10-01

Various studies have reported a positive relationship between child maltreatment and personality disorders (PDs). However, few studies included all DSM-IV PDs and even fewer adjusted for other forms of childhood adversity, e.g. bullying or family problems. We analyzed questionnaires completed by 512 participants of the ZInEP epidemiology survey, a comprehensive psychiatric survey of the general population in Zurich, Switzerland. Associations between childhood adversity and PDs were analyzed bivariately via simple regression analyses and multivariately via multiple path analysis. The bivariate analyses revealed that all PD dimensions were significantly related to various forms of family and school problems as well as child abuse. In contrast, according to the multivariate analysis only school problems and emotional abuse were associated with various PDs. Poverty was uniquely associated with schizotypal PD, conflicts with parents with obsessive-compulsive PD, physical abuse with antisocial PD, and physical neglect with narcissistic PD. Sexual abuse was statistically significantly associated with schizotypal and borderline PD, but corresponding effect sizes were small. Childhood adversity has a serious impact on PDs. Bullying and violence in schools and emotional abuse appear to be more salient markers of general personality pathology than other forms of childhood adversity. Associations with sexual abuse were negligible when adjusted for other forms of adversity. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Adverse Childhood Experiences, Coping Resources, and Mental Health Problems among Court-Involved Youth

ERIC Educational Resources Information Center

Logan-Greene, Patricia; Tennyson, Robert L.; Nurius, Paula S.; Borja, Sharon

2017-01-01

Background: Mental health problems are gaining attention among court-involved youth with emphasis on the role of childhood adversity, but assessment lags. Objective: The present study uses a commonly delivered assessment tool to examine mental health problems (current mental health problem, mental health interfered with probation goals, and…

Childhood Risk Factors for Early-Onset Drinking*

PubMed Central

Donovan, John E.; Molina, Brooke S. G.

2011-01-01

Objective: There is relatively little research on the childhood antecedent predictors of early-onset alcohol use. This study examined an array of psychosocial variables assessed at age 10 and reflecting Problem Behavior Theory as potential antecedent risk factors for the initiation of alcohol use at age 14 or younger. Method: A sample of 452 children (238 girls) ages 8 or 10 and their families was drawn from Allegheny County, PA, using targeted-age directory sampling and random-digit dialing procedures. Children and parents were interviewed using computer-assisted interviews. Logistic regression analyses were used to examine the age-10 univariate and multivariate predictors of the initiation of alcohol use by age 14 or younger. Results: Twenty-five percent of the sample reported having more than a sip or a taste of alcohol in their life by age 14. Sex, race, and age cohort did not relate to early drinking status. Children with two parents were less likely to initiate drinking early. Early initiation of drinking related significantly to an array of antecedent risk factors (personality, social environment, and behavioral) assessed at age 10 that reflect psychosocial proneness for problem behavior. In the multivariate model, the variables most predictive of early-onset drinking were having a single parent, sipping or tasting alcohol by age 10, having parents who also started drinking at an early age, and parental drinking frequency. Conclusions: Initiation of alcohol use by age 14 reflects childhood psychosocial proneness to engage in problem behavior as measured by Problem Behavior Theory and having a family environment conducive to alcohol use. PMID:21906502

Factors affecting breastfeeding adherence among Chinese mothers

PubMed Central

Huang, Pan; Ren, Jianhua; Liu, Yi; Luo, Biru; Zhao, Xiufang

2017-01-01

Abstract Breastfeeding is beneficial for both infant and mother, but discontinuation of breastfeeding is very common. To investigate maternal breastfeeding intention and the rate of breastfeeding based on the theory of reasoned action, and analyze the predominant factors associated with breastfeeding and breastfeeding problems. This observational study was conducted in 3 hospitals. Three researchers recruited women at 3 time points in the hospitals: initial documentation of pregnancy at the outpatient department, prenatal admission, and postpartum discharge. SPSS version 21 was used for statistical analyses. Significance was set at P < .05. In the multivariate analysis, binary logistic regression was used and odds ratios (ORs) with 95% confidence intervals (CI) were calculated. We recruited 1260 women, with 420 pregnant women at each time point. 55.1% of the infants were exclusively breastfed, 40.6% were mixed fed, and 4.3% were formula fed when discharged from hospital. A total of 53.8% of the mothers declared having breastfeeding problems. The multivariate analysis showed that nonsuccessful breastfeeding was associated with neonatal birth length, food intake before breastfeeding, infrequent sucking, the intention of breastfeeding, understanding level of the benefits of breastfeeding and that breastfeeding problems were related with the understanding level of the benefits of breastfeeding, neonatal birth length, normal vaginal delivery, breast size, the experience of breastfeeding, use of pacifier and the needs of family member's support in breastfeeding. Most mothers who intended to practice exclusive breastfeeding initially chose to add formula and had breastfeeding problems when discharged from hospital. Successful breastfeeding depends on antenatal and postnatal breastfeeding education and on support provided by healthcare professionals. PMID:28930818

CT-assessed large airway involvement and lung function decline in eosinophilic asthma: The association between induced sputum eosinophil differential counts and airway remodeling.

PubMed

Inoue, Hideki; Ito, Isao; Niimi, Akio; Matsumoto, Hisako; Matsuoka, Hirofumi; Jinnai, Makiko; Takeda, Tomoshi; Oguma, Tsuyoshi; Otsuka, Kojiro; Nakaji, Hitoshi; Tajiri, Tomoko; Iwata, Toshiyuki; Nagasaki, Tadao; Kanemitsu, Yoshihiro; Mishima, Michiaki

2016-11-01

Eosinophilic asthma (EA) is a distinct clinical phenotype characterized by eosinophilic airway inflammation and airway remodeling. Few studies have used computed tomography (CT) scanning to assess the association between sputum eosinophil differential counts and airway involvement. We aimed to investigate the clinical characteristics and airway involvement of EA, and to examine the correlation between induced sputum eosinophil differential counts and CT-assessed airway remodeling. We retrospectively divided 63 patients with stable asthma receiving inhaled corticosteroids into 2 groups: 26 patients with EA (sputum eosinophil >3%) and 37 patients with non-eosinophilic asthma (NEA). Clinical measurements such as spirometry, fractional exhaled nitric oxide levels (FeNO), and CT-assessed indices of airway involvement were compared between the groups. Multivariate analysis was performed to identify determinants of the percentage of wall area (WA%). The EA group had significantly longer asthma duration, lower pulmonary function, and higher FeNO than the NEA group. Also, the EA group had higher WA% and smaller airway luminal area than the NEA group. Sputum eosinophil differential counts and WA% were positively correlated. The multivariate linear regression analysis showed that the factors associated with WA% included sputum eosinophil differential counts, age, and body mass index. However, asthma duration was not associated with WA%. Our CT-assessed findings demonstrated large airway involvement in EA, and we observed a positive association between induced sputum eosinophil differential counts and WA%. The findings indicate that induced sputum eosinophil differential counts may be associated with airway remodeling in patients with stable asthma.

Predicting the preferences for involvement in medical decision making among patients with mental disorders

PubMed Central

Michaelis, Svea; Kriston, Levente; Härter, Martin; Watzke, Birgit; Schulz, Holger; Melchior, Hanne

2017-01-01

Background The involvement of patients in medical decision making has been investigated widely in somatic diseases. However, little is known about the preferences for involvement and variables that could predict these preferences in patients with mental disorders. Objective This study aims to determine what roles mentally ill patients actually want to assume when making medical decisions and to identify the variables that could predict this role, including patients’ self-efficacy. Method Demographic and clinical data of 798 patients with mental disorders from three psychotherapeutic units in Germany were elicited using self-report questionnaires. Control preference was measured using the Control Preferences Scale, and patients’ perceived self-efficacy was assessed using the Self-Efficacy Scale. Bivariate and multivariate regression analyses were conducted to investigate the associations between patient variables and control preference. Results Most patients preferred a collaborative role (57.5%), followed by a semi passive (21.2%), a partly autonomous (16.2%), an autonomous (2.8%) and a fully passive (2.3%) role when making medical decisions. Age, sex, diagnosis, employment status, medical pretreatment and perceived self-efficacy were associated with the preference for involvement in the multivariate logistic model. Conclusion Our results confirm the preferences for involvement in medical decisions of mentally ill patients. We reconfirmed previous findings that older patients prefer a shared role over an autonomous role and that subjects with a high qualification prefer a more autonomous role over a shared role. The knowledge about predictors may help strengthen treatment effectiveness because matching the preferred and actual role preferences has been shown to improve clinical outcome. PMID:28837621

Predicting the preferences for involvement in medical decision making among patients with mental disorders.

PubMed

Michaelis, Svea; Kriston, Levente; Härter, Martin; Watzke, Birgit; Schulz, Holger; Melchior, Hanne

2017-01-01

The involvement of patients in medical decision making has been investigated widely in somatic diseases. However, little is known about the preferences for involvement and variables that could predict these preferences in patients with mental disorders. This study aims to determine what roles mentally ill patients actually want to assume when making medical decisions and to identify the variables that could predict this role, including patients' self-efficacy. Demographic and clinical data of 798 patients with mental disorders from three psychotherapeutic units in Germany were elicited using self-report questionnaires. Control preference was measured using the Control Preferences Scale, and patients' perceived self-efficacy was assessed using the Self-Efficacy Scale. Bivariate and multivariate regression analyses were conducted to investigate the associations between patient variables and control preference. Most patients preferred a collaborative role (57.5%), followed by a semi passive (21.2%), a partly autonomous (16.2%), an autonomous (2.8%) and a fully passive (2.3%) role when making medical decisions. Age, sex, diagnosis, employment status, medical pretreatment and perceived self-efficacy were associated with the preference for involvement in the multivariate logistic model. Our results confirm the preferences for involvement in medical decisions of mentally ill patients. We reconfirmed previous findings that older patients prefer a shared role over an autonomous role and that subjects with a high qualification prefer a more autonomous role over a shared role. The knowledge about predictors may help strengthen treatment effectiveness because matching the preferred and actual role preferences has been shown to improve clinical outcome.

Understanding the Discipline Gap from an Ecological Perspective

ERIC Educational Resources Information Center

McElderry, Cathy G.; Cheng, Tyrone C.

2014-01-01

This study investigated school exclusion's relationships with student characteristics, mother characteristics, parental involvement, school location, and service provision. The researchers examined data from 4,837 students in seventh to 12th grade extracted from a national data set. Multivariate results showed that student's age, gender,…

An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents

ERIC Educational Resources Information Center

Hwang, Heungsun; Montreal, Hec; Dillon, William R.; Takane, Yoshio

2006-01-01

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

The Impact of Bullying and Victimization on Students' Relationships

ERIC Educational Resources Information Center

Demanet, Jannick; Van Houtte, Mieke

2012-01-01

Grschool, in Flemish secondary schools. Methods: We use data from the Flemish Educational Assessment (FlEA), consisting of 11,872 students in 85 schools. Multivariate analyses of variance (ANOVA) were performed. Results: Non-involved students felt most attached to peers, parents, teachers, and school. Bullies matched the level of parental…

Multivariate Longitudinal Methods for Studying Developmental Relationships between Depression and Academic Achievement

ERIC Educational Resources Information Center

Grimm, Kevin J.

2007-01-01

Recent advances in methods and computer software for longitudinal data analysis have pushed researchers to more critically examine developmental theories. In turn, researchers have also begun to push longitudinal methods by asking more complex developmental questions. One such question involves the relationships between two developmental…

Religious Influences on the Risk of Marital Dissolution

ERIC Educational Resources Information Center

Vaaler, Margaret L.; Ellison, Christopher G.; Powers, Daniel A.

2009-01-01

This study examined multiple dimensions of religious involvement and the risk of divorce among a nationwide sample of 2,979 first-time married couples. Multivariate proportional hazards modeling was used to analyze two waves of the National Survey of Families and Households. Results indicated that although each partner's religious attendance bore…

Improving multivariate Horner schemes with Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Kuipers, J.; Plaat, A.; Vermaseren, J. A. M.; van den Herik, H. J.

2013-11-01

Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.

A Multivariate Analysis of Termination Status in a Rural Community Mental Health Center.

ERIC Educational Resources Information Center

Tutin, Judith; Kessler, Marc

It has been estimated that the most pressing problem in community mental health care clinics is dropout, defined as unilateral termination by the client without therapist approval. To clarify the nature of dropout patients, 133 outpatient records at a rural community mental health center were examined over a one year period. Variables expected to…

Bellman Continuum (3rd) International Workshop (13-14 June 1988)

DTIC Science & Technology

1988-06-01

Modelling Uncertain Problem ................. 53 David Bensoussan ,---,>Asymptotic Linearization of Uncertain Multivariable Systems by Sliding Modes...K. Ghosh .-. Robust Model Tracking for a Class of Singularly Perturbed Nonlinear Systems via Composite Control ....... 93 F. Garofalo and L. Glielmo...MODELISATION ET COMMANDE EN ECONOMIE MODELS AND CONTROL POLICIES IN ECONOMICS Qualitative Differential Games : A Viability Approach ............. 117

Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient

ERIC Educational Resources Information Center

Krishnamoorthy, K.; Xia, Yanping

2008-01-01

The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…

How Does a Child Solve 7 + 8? Decoding Brain Activity Patterns Associated with Counting and Retrieval Strategies

ERIC Educational Resources Information Center

Cho, Soohyun; Ryali, Srikanth; Geary, David C.; Menon, Vinod

2011-01-01

Cognitive development and learning are characterized by diminished reliance on effortful procedures and increased use of memory-based problem solving. Here we identify the neural correlates of this strategy shift in 7-9-year-old children at an important developmental period for arithmetic skill acquisition. Univariate and multivariate approaches…

SPSS Syntax for Missing Value Imputation in Test and Questionnaire Data

ERIC Educational Resources Information Center

van Ginkel, Joost R.; van der Ark, L. Andries

2005-01-01

A well-known problem in the analysis of test and questionnaire data is that some item scores may be missing. Advanced methods for the imputation of missing data are available, such as multiple imputation under the multivariate normal model and imputation under the saturated logistic model (Schafer, 1997). Accompanying software was made available…

What is a good index? Problems with statistically based indicators and the Malmquist index as alternative

USDA-ARS?s Scientific Manuscript database

Conventional multivariate statistical methods have been used for decades to calculate environmental indicators. These methods generally work fine if they are used in a situation where the method can be tailored to the data. But there is some skepticism that the methods might fail in the context of s...

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

A Survey on Transport Management Practices Associated with Injuries and Health Problems in Horses

PubMed Central

Padalino, Barbara; Raidal, Sharanne L.; Hall, Evelyn; Knight, Peter; Celi, Pietro; Jeffcott, Leo; Muscatello, Gary

2016-01-01

An online survey was conducted to determine associations between transport management and transport-related injuries and diseases in horses in Australia. The survey was composed of three sections: respondents’ demographic information, transport management strategies or procedures (before, during and after transportation) and transport diseases experienced in the previous two year period. Univariate and multivariate modelling was performed exploring associations between variables (respondents’ details and transport management strategies) and the following transport-related diseases as outcomes: traumatic injuries, diarrhoea, heat stroke, muscular problems, laminitis, transport pneumonia and colic. The survey generated 797 responses. Traumatic injuries were the most common transport-related problem, with a reported incidence of 45.0%. Younger respondents (<40 years old) caring for large numbers of horses (>30 in a week) were more likely to report transport-related injuries. Injury risk was also linked to the use of protections and tranquilizers prior to transport, and checking horses after the journey. Diarrhoea (20.0%) and heat stroke (10.5%) were reported more by amateur than professional horse carers. Increased risk of heat stroke was linked to the restriction of hay and water prior to transportation. Muscular problems (13.0%) appeared to be exacerbated when horse health was not assessed before journey; whilst the risk of laminitis (2.9%) was around three fold greater when post transport recovery strategies were not applied. Associations were made between transport pneumonia (9.2%) and duration of journey, and with activity (horses involved in racing at greater risk). No associations were seen between the incidence of colic (10.3%) and the variables examined. Study findings should be interpreted with caution as they represent participant perceptions and recall. Nevertheless, results support many current recommendations for safe transportation of horses. They also highlight the need to further investigate many of identified management factors to refine existing policies and practices in equine transportation. PMID:27588689

Peer rejection in childhood, involvement with antisocial peers in early adolescence, and the development of externalizing behavior problems

PubMed Central

Laird, Robert D.; Jordan, Kristi Y.; Dodge, Kenneth A.; Pettit, Gregory S.; Bates, John E.

2009-01-01

A longitudinal, prospective design was used to examine the roles of peer rejection in middle childhood and antisocial peer involvement in early adolescence in the development of adolescent externalizing behavior problems. Both early starter and late starter pathways were considered. Classroom sociometric interviews from ages 6 through 9 years, adolescent reports of peers' behavior at age 13 years, and parent, teacher, and adolescent self-reports of externalizing behavior problems from age 5 through 14 years were available for 400 adolescents. Results indicate that experiencing peer rejection in elementary school and greater involvement with antisocial peers in early adolescence are correlated but that these peer relationship experiences may represent two different pathways to adolescent externalizing behavior problems. Peer rejection experiences, but not involvement with antisocial peers, predict later externalizing behavior problems when controlling for stability in externalizing behavior. Externalizing problems were most common when rejection was experienced repeatedly. Early externalizing problems did not appear to moderate the relation between peer rejection and later problem behavior. Discussion highlights multiple pathways connecting externalizing behavior problems from early childhood through adolescence with peer relationship experiences in middle childhood and early adolescence. PMID:11393650

Association between Parental Involvement in School and Child Conduct, Social, and Internalizing Problems: Teacher Report

ERIC Educational Resources Information Center

Kirkhaug, Bente; Drugli, May Britt; Klockner, Christian A.; Morch, Willy-Tore

2013-01-01

The present study examined the factor structure of the Teacher Involvement Questionnaire (Involve-T) by means of exploratory factor analysis and examined the association between children's socio-emotional and behavioural problems and teacher-reported parental involvement in school, using structural equation modelling. The study was conducted with…

SEM-PLS Analysis of Inhibiting Factors of Cost Performance for Large Construction Projects in Malaysia: Perspective of Clients and Consultants

PubMed Central

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R 2 value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun. PMID:24693227

SEM-PLS analysis of inhibiting factors of cost performance for large construction projects in Malaysia: perspective of clients and consultants.

PubMed

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R(2) value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

USGS Publications Warehouse

Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

2013-01-01

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

Simulation of multivariate stationary stochastic processes using dimension-reduction representation methods

NASA Astrophysics Data System (ADS)

Liu, Zhangjun; Liu, Zenghui; Peng, Yongbo

2018-03-01

In view of the Fourier-Stieltjes integral formula of multivariate stationary stochastic processes, a unified formulation accommodating spectral representation method (SRM) and proper orthogonal decomposition (POD) is deduced. By introducing random functions as constraints correlating the orthogonal random variables involved in the unified formulation, the dimension-reduction spectral representation method (DR-SRM) and the dimension-reduction proper orthogonal decomposition (DR-POD) are addressed. The proposed schemes are capable of representing the multivariate stationary stochastic process with a few elementary random variables, bypassing the challenges of high-dimensional random variables inherent in the conventional Monte Carlo methods. In order to accelerate the numerical simulation, the technique of Fast Fourier Transform (FFT) is integrated with the proposed schemes. For illustrative purposes, the simulation of horizontal wind velocity field along the deck of a large-span bridge is proceeded using the proposed methods containing 2 and 3 elementary random variables. Numerical simulation reveals the usefulness of the dimension-reduction representation methods.

Liquid chromatography with diode array detection and multivariate curve resolution for the selective and sensitive quantification of estrogens in natural waters.

PubMed

Pérez, Rocío L; Escandar, Graciela M

2014-07-04

Following the green analytical chemistry principles, an efficient strategy involving second-order data provided by liquid chromatography (LC) with diode array detection (DAD) was applied for the simultaneous determination of estriol, 17β-estradiol, 17α-ethinylestradiol and estrone in natural water samples. After a simple pre-concentration step, LC-DAD matrix data were rapidly obtained (in less than 5 min) with a chromatographic system operating isocratically. Applying a second-order calibration algorithm based on multivariate curve resolution with alternating least-squares (MCR-ALS), successful resolution was achieved in the presence of sample constituents that strongly coelute with the analytes. The flexibility of this multivariate model allowed the quantification of the four estrogens in tap, mineral, underground and river water samples. Limits of detection in the range between 3 and 13 ng L(-1), and relative prediction errors from 2 to 11% were achieved. Copyright © 2014 Elsevier B.V. All rights reserved.

A Novel Approach to Detect Accelerated Aged and Surface-Mediated Degradation in Explosives by UPLC-ESI-MS.

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

Beppler, Christina L

2015-12-01

A new approach was created for studying energetic material degradation. This approach involved detecting and tentatively identifying non-volatile chemical species by liquid chromatography-mass spectrometry (LC-MS) with multivariate statistical data analysis that form as the CL-20 energetic material thermally degraded. Multivariate data analysis showed clear separation and clustering of samples based on sample group: either pristine or aged material. Further analysis showed counter-clockwise trends in the principal components analysis (PCA), a type of multivariate data analysis, Scores plots. These trends may indicate that there was a discrete shift in the chemical markers as the went from pristine to aged material, andmore » then again when the aged CL-20 mixed with a potentially incompatible material was thermally aged for 4, 6, or 9 months. This new approach to studying energetic material degradation should provide greater knowledge of potential degradation markers in these materials.« less

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

Multivariable Sensors for Ubiquitous Monitoring of Gases in the Era of Internet of Things and Industrial Internet.

PubMed

Potyrailo, Radislav A

2016-10-12

Modern gas monitoring scenarios for medical diagnostics, environmental surveillance, industrial safety, and other applications demand new sensing capabilities. This Review provides analysis of development of new generation of gas sensors based on the multivariable response principles. Design criteria of these individual sensors involve a sensing material with multiresponse mechanisms to different gases and a multivariable transducer with independent outputs to recognize these different gas responses. These new sensors quantify individual components in mixtures, reject interferences, and offer more stable response over sensor arrays. Such performance is attractive when selectivity advantages of classic gas chromatography, ion mobility, and mass spectrometry instruments are canceled by requirements for no consumables, low power, low cost, and unobtrusive form factors for Internet of Things, Industrial Internet, and other applications. This Review is concluded with a perspective for future needs in fundamental and applied aspects of gas sensing and with the 2025 roadmap for ubiquitous gas monitoring.

Characterization and dynamics of air pollutants in the Lower Rio Grande Valley

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

Mejia-Velazquez, G.M.; Sheya, S.A.; Dworzanski, J.

1999-07-01

The Lower Rio Grande Valley (LRGV) has become a region of increasing interest because of its rapid economic development and the increased international border crossing traffic, as well as for its extensive agricultural activities. Over the past few years air pollution problems in the region have been reported by the population. However, very few air quality studies have been performed in the area. In this paper some results of a study to demonstrate the feasibility of a comprehensive (criteria pollutant + VOC/SVOC + PM{sub FINE}) air pollutant dynamics characterization and modeling study in the LRGV are presented and discussed. Themore » study involved both sides of the US/Mexican border and used. A highly mobile monitoring station equipped with a broad array of physical and chemical samplers and sensors was used in the study in two periods in December, 1995 and March,1998. PM10/PM2.5 and NO{sub x} (the latter only in the March 1998 study) concentrations were measured in Reynosa, Rio Bravo and Matamoros, Mexico, as well as Hidalgo, Brownsville and along the Freeway between Brownsville and McAllen on Texas. The photochemical model predicted peak ozone concentrations that reached, and on some days exceeded, air quality standards. The concurrent PM10/PM2.5 study involved both physical (size distributed counting) and time-resolved (2-hourly) organic chemical (VOC/SVOC type PM{sub FINE} adsorbates) characterization methods. Recently completed multivariate data analysis results from a December 1995 study at one of the sites (Hidalgo international bridge) are being presented to illustrate the capabilities of the time-resolved PM{sub FINE} characterization approach. The results of this work show that the LRGV region does not appear to have grave air pollution problems yet. However, with the increase in traffic activities over the next few years, air quality is likely to deteriorate.« less

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

A neuromorphic network for generic multivariate data classification

PubMed Central

Schmuker, Michael; Pfeil, Thomas; Nawrot, Martin Paul

2014-01-01

Computational neuroscience has uncovered a number of computational principles used by nervous systems. At the same time, neuromorphic hardware has matured to a state where fast silicon implementations of complex neural networks have become feasible. En route to future technical applications of neuromorphic computing the current challenge lies in the identification and implementation of functional brain algorithms. Taking inspiration from the olfactory system of insects, we constructed a spiking neural network for the classification of multivariate data, a common problem in signal and data analysis. In this model, real-valued multivariate data are converted into spike trains using “virtual receptors” (VRs). Their output is processed by lateral inhibition and drives a winner-take-all circuit that supports supervised learning. VRs are conveniently implemented in software, whereas the lateral inhibition and classification stages run on accelerated neuromorphic hardware. When trained and tested on real-world datasets, we find that the classification performance is on par with a naïve Bayes classifier. An analysis of the network dynamics shows that stable decisions in output neuron populations are reached within less than 100 ms of biological time, matching the time-to-decision reported for the insect nervous system. Through leveraging a population code, the network tolerates the variability of neuronal transfer functions and trial-to-trial variation that is inevitably present on the hardware system. Our work provides a proof of principle for the successful implementation of a functional spiking neural network on a configurable neuromorphic hardware system that can readily be applied to real-world computing problems. PMID:24469794

The Roles of Internal Representation and Processing in Problem Solving Involving Insight: A Computational Complexity Perspective

ERIC Educational Resources Information Center

Wareham, Todd

2017-01-01

In human problem solving, there is a wide variation between individuals in problem solution time and success rate, regardless of whether or not this problem solving involves insight. In this paper, we apply computational and parameterized analysis to a plausible formalization of extended representation change theory (eRCT), an integration of…

The Total Synthesis Problem of linear multivariable control. II - Unity feedback and the design morphism

NASA Technical Reports Server (NTRS)

Sain, M. K.; Antsaklis, P. J.; Gejji, R. R.; Wyman, B. F.; Peczkowski, J. L.

1981-01-01

Zames (1981) has observed that there is, in general, no 'separation principle' to guarantee optimality of a division between control law design and filtering of plant uncertainty. Peczkowski and Sain (1978) have solved a model matching problem using transfer functions. Taking into consideration this investigation, Peczkowski et al. (1979) proposed the Total Synthesis Problem (TSP), wherein both the command/output-response and command/control-response are to be synthesized, subject to the plant constraint. The TSP concept can be subdivided into a Nominal Design Problem (NDP), which is not dependent upon specific controller structures, and a Feedback Synthesis Problem (FSP), which is. Gejji (1980) found that NDP was characterized in terms of the plant structural matrices and a single, 'good' transfer function matrix. Sain et al. (1981) have extended this NDP work. The present investigation is concerned with a study of FSP for the unity feedback case. NDP, together with feedback synthesis, is understood as a Total Synthesis Problem.

Suicidal behaviors and associated factors among university students in six countries in the Association of Southeast Asian Nations (ASEAN).

PubMed

Peltzer, Karl; Yi, Siyan; Pengpid, Supa

2017-04-01

A large data gap remains on suicidal behaviors among youth in the Association of Southeast Asian Nations (ASEAN) countries, despite the increasing rates of suicide in Asian cultures that may be related to rapid economic changes and the loss of social stability. This study was therefore conducted to explore the prevalence of and factors associated with suicidal ideation and suicide attempts among university students in six ASEAN member states. Data were collected in a cross-sectional survey of 4675 undergraduate university students, mean age 20.6 years (SD=2.7), range of 18-30 years, from Cambodia, Indonesia, Malaysia, Myanmar, Thailand and Vietnam. The overall prevalence of ever suicidal ideation and ever suicide attempt among students in this study was 11.7% and 2.4%, respectively. Different rates of these suicidal behaviors were observed across the countries. In multivariable logistic regression models, suicidal ideation was significantly associated with psychosocial factors including childhood sexual abuse, depressive symptoms, involvement in physical fights, and poor academic performance as well as socio-environmental factors including living with parents or guardians and low involvement in organized religious activity. Suicide attempt was significantly associated with childhood sexual abuse, depressive symptoms, low involvement in organized religious activity and being underweight or overweight. Our findings suggest that individual-level strategies for suicide prevention should be targeted toward students with poor academic performance, mental health problems and a history of adverse childhood experiences. Particular attention should be paid to the role of families that could be a potential stressor in the lives of university students. Copyright © 2017 Elsevier B.V. All rights reserved.

Aberrant Gene Expression in Humans

PubMed Central

Yang, Ence; Ji, Guoli; Brinkmeyer-Langford, Candice L.; Cai, James J.

2015-01-01

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions. PMID:25617623

Problem solving therapy - use and effectiveness in general practice.

PubMed

Pierce, David

2012-09-01

Problem solving therapy (PST) is one of the focused psychological strategies supported by Medicare for use by appropriately trained general practitioners. This article reviews the evidence base for PST and its use in the general practice setting. Problem solving therapy involves patients learning or reactivating problem solving skills. These skills can then be applied to specific life problems associated with psychological and somatic symptoms. Problem solving therapy is suitable for use in general practice for patients experiencing common mental health conditions and has been shown to be as effective in the treatment of depression as antidepressants. Problem solving therapy involves a series of sequential stages. The clinician assists the patient to develop new empowering skills, and then supports them to work through the stages of therapy to determine and implement the solution selected by the patient. Many experienced GPs will identify their own existing problem solving skills. Learning about PST may involve refining and focusing these skills.

On the stabilization of decentralized control systems.

NASA Technical Reports Server (NTRS)

Wang, S.-H.; Davison, E. J.

1973-01-01

This paper considers the problem of stabilizing a linear time-variant multivariable system by using several local feedback control laws. Each local feedback control law depends only on partial system outputs. A necessary and sufficient condition for the existence of local control laws with dynamic compensation to stabilize a given system is derived. This condition is stated in terms of a new notion, called fixed modes, which is a natural generalization of the well-known concept of uncontrollable modes and unobservable modes that occur in centralized control system problems. A procedure that constructs a set of stabilizing feedback control laws is given.

Elimination of RF inhomogeneity effects in segmentation.

PubMed

Agus, Onur; Ozkan, Mehmed; Aydin, Kubilay

2007-01-01

There are various methods proposed for the segmentation and analysis of MR images. However the efficiency of these techniques is effected by various artifacts that occur in the imaging system. One of the most encountered problems is the intensity variation across an image. To overcome this problem different methods are used. In this paper we propose a method for the elimination of intensity artifacts in segmentation of MRI images. Inter imager variations are also minimized to produce the same tissue segmentation for the same patient. A well-known multivariate classification algorithm, maximum likelihood is employed to illustrate the enhancement in segmentation.

Parent Beliefs about the Causes of Learning and Developmental Problems among Children with Autism Spectrum Disorder: Results from a National Survey

PubMed Central

Lindly, Olivia J.; Sinche, Brianna

2017-01-01

This study aimed to assess variation in parent beliefs about causes of learning and developmental problems in U.S. children with autism spectrum disorder, using data from a nationally-representative survey. Results showed that beliefs about a genetic/hereditary cause of learning/developmental problems were most common, but nearly as many parents believed in exposure causes. 40% of parents had no definite causal beliefs. On multivariate analysis, parents who were non-white, publicly-insured or poor were more likely than other parents to endorse exposure causes, or less likely to endorse genetic causes, compared to other parents. Further research should assess how these beliefs modify health care quality or services utilization. PMID:27611353

Mediating effects of depression and anxiety on the relationship between bullying involvement and pain problems among adolescents in Taiwan.

PubMed

Yen, Cheng-Fang; Lin, I-Mei; Liu, Tai-Ling; Hu, Huei-Fan; Cheng, Chung-Ping

2014-08-01

This study aimed to examine the mediating effects of depression and anxiety on the relationships of bullying victimization and perpetration with pain among adolescents in Taiwan. A total of 4976 students of junior and senior high schools completed the questionnaires. Bullying victimization and perpetration, pain problems, depression, and anxiety were assessed. The mediating effects of depression and anxiety on the relationship between bullying involvement and pain problems and the moderating effects of sex on the medicating roles of depression and anxiety were examined by structural equation model. Both depression and anxiety were significant mediators of the relationship between bullying victimization and pain problems among adolescents. Depression was also a significant mediator of the relationship between bullying perpetration and pain problems among adolescents. Sex had no moderating effect on the mediating role of depression/anxiety on the association between bullying involvement and pain problems. Medical and educational professionals should survey and intervene in depression and anxiety when managing pain problems among adolescents involved in bullying. Copyright © 2014 Elsevier Inc. All rights reserved.

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study

PubMed Central

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance. PMID:26196398

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

PubMed

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance.

Problem Gambling Among Ontario Students: Associations with Substance Abuse, Mental Health Problems, Suicide Attempts, and Delinquent Behaviours.

PubMed

Cook, Steven; Turner, Nigel E; Ballon, Bruce; Paglia-Boak, Angela; Murray, Robert; Adlaf, Edward M; Ilie, Gabriela; den Dunnen, Wendy; Mann, Robert E

2015-12-01

This paper describes gambling problems among Ontario students in 2009 and examines the relationship between gambling problems and substance use problems, mental health problem indicators, and delinquent behaviors. Data were derived from the Ontario Student Drug Use and Health Survey of Ontario students in grades 7-12. Gambling problems were measured as 2 or more of 6 indicators of problem gambling. In total 2.8% of the students surveyed endorsed two or more of the problem gambling items. The odds of problem gamblers reporting mental distress was 4.2 times higher than the rest of the sample and the odds of problem gamblers reporting a suicide attempt were 17.8 times greater than the rest of the sample. In addition compared to the rest of the students, delinquent behaviors were also more common among problem gamblers, including theft (OR = 14.5), selling marijuana (OR = 19.6), gang fights (OR = 11.3) and carrying a handgun (OR = 11.2). In a multivariate analysis, substance-use problems, mental health problems, and the participation in a variety of delinquent behaviors remained significantly associated with youth problem gambling behavior. Students who report problem gambling behaviors show increased substance abuse, mental health, and delinquency/criminal problems that are similar to those seen among adult problem gamblers. The association between these problems suggests that these problems could be addressed in a unified manner.

Negative Events in Childhood Predict Trajectories of Internalizing Symptoms Up to Young Adulthood: An 18-Year Longitudinal Study

PubMed Central

Melchior, Maria; Touchette, Évelyne; Prokofyeva, Elena; Chollet, Aude; Fombonne, Eric; Elidemir, Gulizar; Galéra, Cédric

2014-01-01

Background Common negative events can precipitate the onset of internalizing symptoms. We studied whether their occurrence in childhood is associated with mental health trajectories over the course of development. Methods Using data from the TEMPO study, a French community-based cohort study of youths, we studied the association between negative events in 1991 (when participants were aged 4–16 years) and internalizing symptoms, assessed by the ASEBA family of instruments in 1991, 1999, and 2009 (n = 1503). Participants' trajectories of internalizing symptoms were estimated with semi-parametric regression methods (PROC TRAJ). Data were analyzed using multinomial regression models controlled for participants' sex, age, parental family status, socio-economic position, and parental history of depression. Results Negative childhood events were associated with an increased likelihood of concurrent internalizing symptoms which sometimes persisted into adulthood (multivariate ORs associated with > = 3 negative events respectively: high and decreasing internalizing symptoms: 5.54, 95% CI: 3.20–9.58; persistently high internalizing symptoms: 8.94, 95% CI: 2.82–28.31). Specific negative events most strongly associated with youths' persistent internalizing symptoms included: school difficulties (multivariate OR: 5.31, 95% CI: 2.24–12.59), parental stress (multivariate OR: 4.69, 95% CI: 2.02–10.87), serious illness/health problems (multivariate OR: 4.13, 95% CI: 1.76–9.70), and social isolation (multivariate OR: 2.24, 95% CI: 1.00–5.08). Conclusions Common negative events can contribute to the onset of children's lasting psychological difficulties. PMID:25485875

MULTIVARIATE ANALYSIS OF DRINKING BEHAVIOUR IN A RURAL POPULATION

PubMed Central

Mathrubootham, N.; Bashyam, V.S.P.; Shahjahan

1997-01-01

This study was carried out to find out the drinking pattern in a rural population, using multivariate techniques. 386 current users identified in a community were assessed with regard to their drinking behaviours using a structured interview. For purposes of the study the questions were condensed into 46 meaningful variables. In bivariate analysis, 14 variables including dependent variables such as dependence, MAST & CAGE (measuring alcoholic status), Q.F. Index and troubled drinking were found to be significant. Taking these variables and other multivariate techniques too such as ANOVA, correlation, regression analysis and factor analysis were done using both SPSS PC + and HCL magnum mainframe computer with FOCUS package and UNIX systems. Results revealed that number of factors such as drinking style, duration of drinking, pattern of abuse, Q.F. Index and various problems influenced drinking and some of them set up a vicious circle. Factor analysis revealed mainly 3 factors, abuse, dependence and social drinking factors. Dependence could be divided into low/moderate dependence. The implications and practical applications of these tests are also discussed. PMID:21584077

Multivariate hydrological frequency analysis for extreme events using Archimedean copula. Case study: Lower Tunjuelo River basin (Colombia)

NASA Astrophysics Data System (ADS)

Gómez, Wilmar

2017-04-01

By analyzing the spatial and temporal variability of extreme precipitation events we can prevent or reduce the threat and risk. Many water resources projects require joint probability distributions of random variables such as precipitation intensity and duration, which can not be independent with each other. The problem of defining a probability model for observations of several dependent variables is greatly simplified by the joint distribution in terms of their marginal by taking copulas. This document presents a general framework set frequency analysis bivariate and multivariate using Archimedean copulas for extreme events of hydroclimatological nature such as severe storms. This analysis was conducted in the lower Tunjuelo River basin in Colombia for precipitation events. The results obtained show that for a joint study of the intensity-duration-frequency, IDF curves can be obtained through copulas and thus establish more accurate and reliable information from design storms and associated risks. It shows how the use of copulas greatly simplifies the study of multivariate distributions that introduce the concept of joint return period used to represent the needs of hydrological designs properly in frequency analysis.

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Predictors of continued problem drinking and substance use following military discharge.

PubMed

Norman, Sonya B; Schmied, Emily; Larson, Gerald E

2014-07-01

The goals of the present study were to (a) examine change in rates of problem alcohol/substance use among a sample of veterans between their last year of military service and their first year following separation, (b) identify predictors of continued problem use in the first year after separation, and (c) evaluate the hypothesis that avoidant coping, posttraumatic stress disorder (PTSD) symptoms, and chronic stress place individuals at particularly high risk for continued problem use. Participants (N = 1,599) completed self-report measures before and during the year following separation. Participants who endorsed either having used more than intended or wanting or needing to cut down during the past year were considered to have problem use. Of 742 participants reporting problem substance use at baseline, 42% reported continued problem substance use at follow-up ("persistors"). Persistors reported more trouble adjusting to civilian life, had a greater likelihood of driving while intoxicated, and had a greater likelihood of aggression. Multivariate analyses showed that avoidant coping score at baseline and higher PTSD symptom score and greater sensation seeking at follow up predicted continued problem use. Understanding risk factors for continued problem use is a prerequisite for targeted prevention of chronic problems and associated negative life consequences.

Responding to Family Problems, Alcohol and Substance Misuse. A Survey of Service Provision in the Glasgow Area.

ERIC Educational Resources Information Center

McKellar, Susan; Coggans, Niall

1997-01-01

Surveyed social agencies' awareness of possible developmental problems of alcohol and substance abusers' children, extent to which agency felt it could deal with the problem involving the family, and development of services for children of substance abusers. Found that many agency workers considered involvement in family problems to be part of…

Determination of optimal self-drive tourism route using the orienteering problem method

NASA Astrophysics Data System (ADS)

Hashim, Zakiah; Ismail, Wan Rosmanira; Ahmad, Norfaieqah

2013-04-01

This paper was conducted to determine the optimal travel routes for self-drive tourism based on the allocation of time and expense by maximizing the amount of attraction scores assigned to each city involved. Self-drive tourism represents a type of tourism where tourists hire or travel by their own vehicle. It only involves a tourist destination which can be linked with a network of roads. Normally, the traveling salesman problem (TSP) and multiple traveling salesman problems (MTSP) method were used in the minimization problem such as determination the shortest time or distance traveled. This paper involved an alternative approach for maximization method which is maximize the attraction scores and tested on tourism data for ten cities in Kedah. A set of priority scores are used to set the attraction score at each city. The classical approach of the orienteering problem was used to determine the optimal travel route. This approach is extended to the team orienteering problem and the two methods were compared. These two models have been solved by using LINGO12.0 software. The results indicate that the model involving the team orienteering problem provides a more appropriate solution compared to the orienteering problem model.

A hybrid computer program for rapidly solving flowing or static chemical kinetic problems involving many chemical species

NASA Technical Reports Server (NTRS)

Mclain, A. G.; Rao, C. S. R.

1976-01-01

A hybrid chemical kinetic computer program was assembled which provides a rapid solution to problems involving flowing or static, chemically reacting, gas mixtures. The computer program uses existing subroutines for problem setup, initialization, and preliminary calculations and incorporates a stiff ordinary differential equation solution technique. A number of check cases were recomputed with the hybrid program and the results were almost identical to those previously obtained. The computational time saving was demonstrated with a propane-oxygen-argon shock tube combustion problem involving 31 chemical species and 64 reactions. Information is presented to enable potential users to prepare an input data deck for the calculation of a problem.

Games and gambling involvement among casino patrons.

PubMed

LaPlante, Debi A; Afifi, Tracie O; Shaffer, Howard J

2013-06-01

A growing literature is addressing the nature of the relationships among gambling activity, gambling involvement, and gambling-related problems. This research suggests that among the general population, compared to playing any specific game, gambling involvement is a better predictor of gambling-related problems. To date, researchers have not examined these relationships among casino patrons, a population that differs from the general population in a variety of important ways. A survey of 1160 casino patrons at two Las Vegas resort casinos allowed us to determine relationships between the games that patrons played during the 12 months before their casino visit, the games that patrons played during their casino visit, and patrons' self-perceived history of gambling-related problems. Results indicate that playing specific gambling games onsite predicted (i.e., statistically significant odds ratios ranging from .5 to 4.51) self-perceived gambling-related problems. However, after controlling for involvement, operationally defined as the number of games played during the current casino visit and self-reported gambling frequency during the past 12 months, the relationships between games and gambling-related problems disappeared or were attenuated (i.e., odds ratios no longer statistically significant). These results extend the burgeoning literature related to gambling involvement and its relationship to gambling-related problems.

Criminal justice involvement, trauma, and negative affect in Iraq and Afghanistan war era veterans.

PubMed

Elbogen, Eric B; Johnson, Sally C; Newton, Virginia M; Straits-Troster, Kristy; Vasterling, Jennifer J; Wagner, H Ryan; Beckham, Jean C

2012-12-01

Although criminal behavior in veterans has been cited as a growing problem, little is known about why some veterans are at increased risk for arrest. Theories of criminal behavior postulate that people who have been exposed to stressful environments or traumatic events and who report negative affect such as anger and irritability are at increased risk of antisocial conduct. We hypothesized veterans with posttraumatic stress disorder (PTSD) or traumatic brain injury (TBI) who report anger/irritability would show higher rates of criminal arrests. To test this, we examined data in a national survey of N = 1,388 Iraq and Afghanistan war era veterans. We found that 9% of respondents reported arrests since returning home from military service. Most arrests were associated with nonviolent criminal behavior resulting in incarceration for less than 2 weeks. Unadjusted bivariate analyses revealed that veterans with probable PTSD or TBI who reported anger/irritability were more likely to be arrested than were other veterans. In multivariate analyses, arrests were found to be significantly related to younger age, male gender, having witnessed family violence, prior history of arrest, alcohol/drug misuse, and PTSD with high anger/irritability but were not significantly related to combat exposure or TBI. Findings show that a subset of veterans with PTSD and negative affect may be at increased risk of criminal arrest. Because arrests were more strongly linked to substance abuse and criminal history, clinicians should also consider non-PTSD factors when evaluating and treating veterans with criminal justice involvement.

Criminal Justice Involvement, Trauma, and Negative Affect in Iraq and Afghanistan War Era Veterans

PubMed Central

Elbogen, Eric B.; Johnson, Sally C.; Newton, Virginia M.; Straits-Troster, Kristy; Vasterling, Jennifer J.; Wagner, H. Ryan; Beckham, Jean C.

2012-01-01

Although criminal behavior in veterans has been cited as a growing problem, little is known about why some veterans are at increased risk for arrest. Theories of criminal behavior postulate that people who have been exposed to stressful environments or traumatic events and who report negative affect such as anger and irritability are at increased risk of antisocial conduct. We thus hypothesized that veterans with posttraumatic stress disorder (PTSD) or traumatic brain injury (TBI) who report anger/irritability would show higher rates of criminal arrests. To test this, we examined data in a national survey of N=1388 Iraq and Afghanistan War Era Veterans. We found that 9% of respondents reported arrests since returning home from military service. Most arrests were associated with nonviolent criminal behavior resulting in incarceration for less than two weeks. Unadjusted bivariate analyses revealed that veterans with probable PTSD or TBI who reported anger/irritability were most likely to be arrested. In multivariate analyses, arrests were found to be significantly related to younger age, male gender, having witnessed family violence, prior history of arrest, alcohol/drug misuse, and PTSD with high anger/irritability but were not significantly related to combat exposure or TBI. Findings show that a subset of veterans with PTSD and negative affect may be at increased risk of criminal arrest. Since arrests are more strongly linked to substance abuse and criminal history, clinicians should also consider non-PTSD factors when evaluating and treating veterans with criminal justice involvement. PMID:23025247

Condom use self-efficacy and HIV risk practices among men who use the internet to find male partners for unprotected sex.

PubMed

Klein, Hugh

2014-05-01

This research examines the levels of condom use self-efficacy in a population of men who have sex with men who are at great risk for contracting/transmitting HIV. It focuses on the relationship between condom use self-efficacy and risk involvement, and examines the factors associated with greater/lower levels of condom use self-efficacy. The data come from a national sample of men, randomly chosen, who used any of 16 websites specifically to identify other men with whom they could engage in unprotected sex. Data were collected between January 2008 and May 2009 from 332 men, via telephone interviews. Multivariate analyses and structural equation modeling were used to test a conceptual model based on syndemics theory. Overall levels of condom use self-efficacy were fairly high, and self-efficacy was related inversely to involvement in HIV risk practices. Six factors were found to be indicative of levels of condom use self-efficacy: the number of drug problems experienced, sexual role identity as a "bottom," not caring about the HIV serostatus of potential sex partners, experiencing childhood maltreatment, having confidence in HIV-related information provided in other men's online profiles, and level of HIV knowledge. Condom use self-efficacy plays an integral role in HIV risk practices among high-risk men who have sex with men. This is true despite the fact that, overall, condom use self-efficacy levels were fairly high in this population.

Child wasting is a severe public health problem in the predominantly rural population of Ethiopia: A community based cross-sectional study.

PubMed

Tariku, Amare; Bikis, Gashaw Andargie; Woldie, Haile; Wassie, Molla Mesele; Worku, Abebaw Gebeyehu

2017-01-01

In Ethiopia, child wasting has remained a public health problem for a decade's, suggesting the need to further monitoring of the problem. Hence, this study aimed at assessing the prevalence of wasting and associated factors among children aged 6-59 months at Dabat District, northwest Ethiopia. A Community based cross-sectional study was undertaken from May to June, 2015, in Dabat District, northwest Ethiopia. A total of 1184 children aged under five years and their mothers/caretakers were included in the study. An interviewer-administered, pre-tested, and structured questionnaire was used to collect data. Standardized anthropometric body measurements were employed to assess the height and weight of the participants. Anthropometric body measurements were analyzed by the WHO Anthro Plus software version 1.0.4. Wasting was defined as having a weight-for-height of Z-score lower than two standard deviations (WHZ < -2 SD) compared to the WHO reference population of the same age and sex group. In the binary logistic regression, both bivariate and multivariate analyses were done to list out factors associated with wasting. All variables with P-values of < 0.2 in the bivariate analysis were earmarked for the multivariate analysis. Both Crude Odds Ratio (COR) and Adjusted Odds Ratio (AOR) at 95% Confidence Interval (CI) were computed to determine the strength of association. In the multivariate analysis, variables at P -values of < 0.05 were identified as determinants of wasting. The overall prevalence of wasting was 18.2%; 10.3% and 7.9% of the children were moderately and severely wasted, respectively. Poor dietary diversity [AOR = 2.08, 95% CI: 1.53, 4.46], late initiation of breastfeeding [AOR = 1.43, 95% CI: 1.04, 1.95], no postnatal vitamin-A supplementation [AOR = 1.55, 95% CI: 1.04, 2.30], and maternal occupational status [AOR = 2.31, 95% CI: 1.56, 3.42] were independently associated with wasting in the study area. Wasting is a severe public health problem in Dabat District. Therefore, there is a need to strengthen the implementation of optimal breastfeeding practice and dietary diversity. In addition, improving the coverage of mothers ' postnatal vitamin-A supplementation is essential to address the burden of child wasting.

Statistical Knowledge for Teaching: Exploring it in the Classroom

ERIC Educational Resources Information Center

Burgess, Tim

2009-01-01

This paper first reports on the methodology of a study of teacher knowledge for statistics, conducted in a classroom at the primary school level. The methodology included videotaping of a sequence of lessons that involved students in investigating multivariate data sets, followed up by audiotaped interviews with each teacher. These stimulated…

Bootstrapping Cox’s Regression Model.

DTIC Science & Technology

1985-11-01

crucial points a multivariate martingale central limit theorem. Involved in this is a p x p covariance matrix Z with elements T j2= f {2(s8 ) - s(l)( s ,8o...1980). The statistical analaysis of failure time data. Wiley, New York. Meyer, P.-A. (1971). Square integrable martingales, a survey. Lecture Notes

School-Related Predictors of Smoking, Drinking and Drug Use: Evidence from the Belfast Youth Development Study

ERIC Educational Resources Information Center

Perra, Oliver; Fletcher, Adam; Bonell, Chris; Higgins, Kathryn; McCrystal, Patrick

2012-01-01

Objective: To examine whether students' school engagement, relationships with teachers, educational aspirations and involvement in fights at school are associated with various measures of subsequent substance use. Methods: Data were drawn from the Belfast Youth Development Study (n = 2968). Multivariate logistic models examined associations…

Better Crunching: Recommendations for Multivariate Data Analysis Approaches for Program Impact Evaluations

ERIC Educational Resources Information Center

Braverman, Marc T.

2016-01-01

Extension program evaluations often present opportunities to analyze data in multiple ways. This article suggests that program evaluations can involve more sophisticated data analysis approaches than are often used. On the basis of a hypothetical program scenario and corresponding data set, two approaches to testing for evidence of program impact…

Multivariate Limits and Continuity: A Survey of Calculus Textbooks.

ERIC Educational Resources Information Center

Thompson, Thomas M.; Wiggins, Kenneth L.

There has been much recent discussion concerning the content of the standard calculus course for students majoring in mathematics and the sciences. Some of this discussion has focused on the available textbooks. One weakness noted in some of these books involves the definitions of limit and continuity for functions of several variables. A…

Multivariate analysis of variance of designed chromatographic data. A case study involving fermentation of rooibos tea.

PubMed

Marini, Federico; de Beer, Dalene; Walters, Nico A; de Villiers, André; Joubert, Elizabeth; Walczak, Beata

2017-03-17

An ultimate goal of investigations of rooibos plant material subjected to different stages of fermentation is to identify the chemical changes taking place in the phenolic composition, using an untargeted approach and chromatographic fingerprints. Realization of this goal requires, among others, identification of the main components of the plant material involved in chemical reactions during the fermentation process. Quantitative chromatographic data for the compounds for extracts of green, semi-fermented and fermented rooibos form the basis of preliminary study following a targeted approach. The aim is to estimate whether treatment has a significant effect based on all quantified compounds and to identify the compounds, which contribute significantly to it. Analysis of variance is performed using modern multivariate methods such as ANOVA-Simultaneous Component Analysis, ANOVA - Target Projection and regularized MANOVA. This study is the first one in which all three approaches are compared and evaluated. For the data studied, all tree methods reveal the same significance of the fermentation effect on the extract compositions, but they lead to its different interpretation. Copyright © 2017 Elsevier B.V. All rights reserved.

A Cognitive Model for Problem Solving in Computer Science

ERIC Educational Resources Information Center

Parham, Jennifer R.

2009-01-01

According to industry representatives, computer science education needs to emphasize the processes involved in solving computing problems rather than their solutions. Most of the current assessment tools used by universities and computer science departments analyze student answers to problems rather than investigating the processes involved in…

Problem Solving through Paper Folding

ERIC Educational Resources Information Center

Wares, Arsalan

2014-01-01

The purpose of this article is to describe a couple of challenging mathematical problems that involve paper folding. These problem-solving tasks can be used to foster geometric and algebraic thinking among students. The context of paper folding makes some of the abstract mathematical ideas involved relatively concrete. When implemented…

Preoperative magnetic resonance imaging assessment of circumferential resection margin predicts disease-free survival and local recurrence: 5-year follow-up results of the MERCURY study.

PubMed

Taylor, Fiona G M; Quirke, Philip; Heald, Richard J; Moran, Brendan J; Blomqvist, Lennart; Swift, Ian R; Sebag-Montefiore, David; Tekkis, Paris; Brown, Gina

2014-01-01

The prognostic relevance of preoperative high-resolution magnetic resonance imaging (MRI) assessment of circumferential resection margin (CRM) involvement is unknown. This follow-up study of 374 patients with rectal cancer reports the relationship between preoperative MRI assessment of CRM staging, American Joint Committee on Cancer (AJCC) TNM stage, and clinical variables with overall survival (OS), disease-free survival (DFS), and time to local recurrence (LR). Patients underwent protocol high-resolution pelvic MRI. Tumor distance to the mesorectal fascia of ≤ 1 mm was recorded as an MRI-involved CRM. A Cox proportional hazards model was used in multivariate analysis to determine the relationship of MRI assessment of CRM to survivorship after adjusting for preoperative covariates. Surviving patients were followed for a median of 62 months. The 5-year OS was 62.2% in patients with MRI-clear CRM compared with 42.2% in patients with MRI-involved CRM with a hazard ratio (HR) of 1.97 (95% CI, 1.27 to 3.04; P < .01). The 5-year DFS was 67.2% (95% CI, 61.4% to 73%) for MRI-clear CRM compared with 47.3% (95% CI, 33.7% to 60.9%) for MRI-involved CRM with an HR of 1.65 (95% CI, 1.01 to 2.69; P < .05). Local recurrence HR for MRI-involved CRM was 3.50 (95% CI, 1.53 to 8.00; P < .05). MRI-involved CRM was the only preoperative staging parameter that remained significant for OS, DFS, and LR on multivariate analysis. High-resolution MRI preoperative assessment of CRM status is superior to AJCC TNM-based criteria for assessing risk of LR, DFS, and OS. Furthermore, MRI CRM involvement is significantly associated with distant metastatic disease; therefore, colorectal cancer teams could intensify treatment and follow-up accordingly to improve survival outcomes.

Angiotensin-converting enzyme inhibitors delay the occurrence of renal involvement and are associated with a decreased risk of disease activity in patients with systemic lupus erythematosus--results from LUMINA (LIX): a multiethnic US cohort.

PubMed

Durán-Barragán, S; McGwin, G; Vilá, L M; Reveille, J D; Alarcón, G S

2008-07-01

To examine if angiotensin-converting enzyme (ACE) inhibitor use delays the occurrence of renal involvement and decreases the risk of disease activity in SLE patients. SLE patients (Hispanics, African Americans and Caucasians) from the lupus in minorities: nature vs nurture (LUMINA) cohort were studied. Renal involvement was defined as ACR criterion and/or biopsy-proven lupus nephritis. Time-to-renal involvement was examined by univariable and multivariable Cox proportional hazards regression analyses. Disease activity was examined with a case-crossover design and a conditional logistic regression model; in the case intervals, a decrease in the SLAM-R score >or=4 points occurred but not in the control intervals. Eighty of 378 patients (21%) were ACE inhibitor users; 298 (79%) were not. The probability of renal involvement free-survival at 10 yrs was 88.1% for users and 75.4% for non-users (P = 0.0099, log rank test). Users developed persistent proteinuria and/or biopsy-proven lupus nephritis (7.1%) less frequently than non-users (22.9%), P = 0.016. By multivariable Cox proportional hazards regression analyses, ACE inhibitors use [hazard ratio (HR) 0.27; 95% CI 0.09, 0.78] was associated with a longer time-to-renal involvement occurrence whereas African American ethnicity (HR 3.31; 95% CI 1.44, 7.61) was with a shorter time. ACE inhibitor use (54/288 case and 254/1148 control intervals) was also associated with a decreased risk of disease activity (HR 0.56; 95% CI 0.34, 0.94). ACE inhibitor use delays the development of renal involvement and associates with a decreased risk of disease activity in SLE; corroboration of these findings in other lupus cohorts is desirable before practice recommendations are formulated.

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

PubMed

Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

2017-02-01

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Gaussian Mixture Models of Between-Source Variation for Likelihood Ratio Computation from Multivariate Data

PubMed Central

Franco-Pedroso, Javier; Ramos, Daniel; Gonzalez-Rodriguez, Joaquin

2016-01-01

In forensic science, trace evidence found at a crime scene and on suspect has to be evaluated from the measurements performed on them, usually in the form of multivariate data (for example, several chemical compound or physical characteristics). In order to assess the strength of that evidence, the likelihood ratio framework is being increasingly adopted. Several methods have been derived in order to obtain likelihood ratios directly from univariate or multivariate data by modelling both the variation appearing between observations (or features) coming from the same source (within-source variation) and that appearing between observations coming from different sources (between-source variation). In the widely used multivariate kernel likelihood-ratio, the within-source distribution is assumed to be normally distributed and constant among different sources and the between-source variation is modelled through a kernel density function (KDF). In order to better fit the observed distribution of the between-source variation, this paper presents a different approach in which a Gaussian mixture model (GMM) is used instead of a KDF. As it will be shown, this approach provides better-calibrated likelihood ratios as measured by the log-likelihood ratio cost (Cllr) in experiments performed on freely available forensic datasets involving different trace evidences: inks, glass fragments and car paints. PMID:26901680

Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil.

PubMed

Souza, Iara da Costa; Morozesk, Mariana; Duarte, Ian Drumond; Bonomo, Marina Marques; Rocha, Lívia Dorsch; Furlan, Larissa Maria; Arrivabene, Hiulana Pereira; Monferrán, Magdalena Victoria; Matsumoto, Silvia Tamie; Milanez, Camilla Rozindo Dias; Wunderlin, Daniel Alberto; Fernandes, Marisa Narciso

2014-08-01

Roots of mangrove trees have an important role in depurating water and sediments by retaining metals that may accumulate in different plant tissues, affecting physiological processes and anatomy. The present study aimed to evaluate adaptive changes in root of Rhizophora mangle in response to different levels of chemical elements (metals/metalloids) in interstitial water and sediments from four neotropical mangroves in Brazil. What sets this study apart from other studies is that we not only investigate adaptive modifications in R. mangle but also changes in environments where this plant grows, evaluating correspondence between physical, chemical and biological issues by a combined set of multivariate statistical methods (pattern recognition). Thus, we looked to match changes in the environment with adaptations in plants. Multivariate statistics highlighted that the lignified periderm and the air gaps are directly related to the environmental contamination. Current results provide new evidences of root anatomical strategies to deal with contaminated environments. Multivariate statistics greatly contributes to extrapolate results from complex data matrixes obtained when analyzing environmental issues, pointing out parameters involved in environmental changes and also evidencing the adaptive response of the exposed biota. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cognitive, behaviour, and academic functioning in adolescent and young adult survivors of childhood acute lymphoblastic leukaemia: a report from the Childhood Cancer Survivor Study.

PubMed

Jacola, Lisa M; Edelstein, Kim; Liu, Wei; Pui, Ching-Hon; Hayashi, Robert; Kadan-Lottick, Nina S; Srivastava, Deokumar; Henderson, Tara; Leisenring, Wendy; Robison, Leslie L; Armstrong, Gregory T; Krull, Kevin R

2016-10-01

Survivors of childhood acute lymphoblastic leukaemia (ALL) are at risk for neurocognitive deficits that affect development in adolescence and young adulthood, and influence educational attainment and future independence. We examined a large and diverse cohort of survivors to identify risk predictors and modifiers of these outcomes. In this cohort study, cognitive and behaviour symptoms were assessed via a standardised parent questionnaire for 1560 adolescent survivors of ALL diagnosed between 1970 and 1999. Clinically significant symptoms (≥90th percentile) and learning problems were compared between survivors and a sibling cohort. Multivariable regression models were used to examine associations with demographic and treatment characteristics. Models were adjusted for inverse probability of sampling weights to reflect undersampling of ALL survivors in the expansion cohort. In a subset of survivors with longitudinal data (n=925), we examined associations between adolescent symptoms or problems and adult educational attainment. Compared with siblings, survivors treated with chemotherapy only were more likely to demonstrate headstrong behaviour (155 [19%] of 752 survivors vs 88 [14%] of 610 siblings, p=0·010), inattention-hyperactivity (15 [19%] vs 86 [14%], p<0·0001), social withdrawal (142 [18%] vs 75 [12%], p=0·002), and had higher rates of learning problems (191 [28%] vs 76 [14%], p<0·0001). In multivariable models among survivors, increased cumulative dose of intravenous methotrexate (ie, >4·3 g/m 2 ) conferred increased risk of inattention-hyperactivity (relative risk [RR] 1·53, 95% CI 1·13-2·08). Adolescent survivors with cognitive or behaviour problems and those with learning problems were less likely to graduate from college as young adults than adolescent survivors without cognitive or behaviour problems. Although modern therapy for childhood ALL has eliminated the use of cranial radiation therapy, adolescent survivors treated with chemotherapy only remain at increased risk for cognitive, behaviour, and academic problems that adversely affect adult education outcomes. National Cancer Institute, American Lebanese-Syrian Associated Charities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Educational Level, Underachievement, and General Mental Health Problems in 10,866 Adolescents.

PubMed

Tempelaar, Wanda M; de Vos, Nelleke; Plevier, Carolien M; van Gastel, Willemijn A; Termorshuizen, Fabian; MacCabe, James H; Boks, Marco P M

2017-08-01

Previous research suggests that cognitive functioning is associated with the risk of several adult psychiatric disorders. In this study we investigated whether adolescents who perform worse than expected at secondary school are at a higher risk for general mental health problems. In a cross-sectional survey comprising 10,866 Dutch adolescents aged 13 to 16 years, underachievement at secondary school was defined as the discrepancy between predicted school grade and actual grade 1 or 3 years later. Mental health problems were assessed using the Strengths and Difficulties Questionnaire. We investigated the association of underachievement with mental health problems using logistic regression, adjusting for potential confounders. Underachievement was associated with general psychopathology in pupils aged 13 to 14 years (odds ratio [OR], 1.86; 95% confidence interval [CI], 1.47-2.37) and in pupils aged 15 to 16 years (OR, 2.05; 95% CI, 1.67-2.52) in a multivariate analysis including sociodemographic factors. The association between underachievement and mental health problems was attenuated when school factors such as teacher advice and interaction between underachievement and teacher advice were added, but underachievement remained significantly associated with mental health problems in adolescents in the higher educational tracks (pupils aged 13-14 years: OR, 2.22; 95% CI, 1.07-4.60 and OR, 2.41; 95% CI, 1.10-5.30, age 15-16 years: OR, 2.63; 95% CI, 1.38-5.03). In the multivariate analysis including the interaction between underachievement and teacher advice, a significant interaction effect occurs between underachievement and teacher advice in the higher tracks. Values of OR and CI are given for each significant interaction term. In the younger age group (pupils aged 13-14 years) this results in 2 sets of OR and CI. This association was most pronounced for the hyperactivity subscale of the Strengths and Difficulties Questionnaire. Underachievement at secondary school is associated with general mental health problems, especially with hyperactivity symptoms, in pupils who started at high educational tracks. Copyright © 2017 Academic Pediatric Association. All rights reserved.

The link between drinking and gambling among undergraduate university students.

PubMed

Hodgins, David C; Racicot, Stephanie

2013-09-01

The purpose of this research was to explore different aspects of the link between alcohol use and gambling among undergraduate university students (N = 121). Potential aspects of the link examined included level of involvement in each behavior, consequences, motives for involvement, and impaired control over involvement. Results confirmed that drinking and gambling among university students are associated, consistent with the expectations of a problem syndrome model. The strongest link was between general dimensions of problematic involvement for both behaviors. Students who drink to cope and have other indicators of alcohol problems are more likely to gamble to cope, gamble to win money, and have higher gambling involvement and gambling-related problems. However, the salience of drinking and gambling to cope in this relationship is an interesting finding that needs further exploration and extension to other problem behaviors. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Breadth and depth involvement: Understanding Internet gambling involvement and its relationship to gambling problems.

PubMed

LaPlante, Debi A; Nelson, Sarah E; Gray, Heather M

2014-06-01

The "involvement effect" refers to the finding that controlling for gambling involvement often reduces or eliminates frequently observed game-specific associations with problem gambling. In other words, broader patterns of gambling behavior, particularly the number of types of games played over a defined period, contribute more to problem gambling than playing specific games (e.g., lottery, casino, Internet gambling). This study extends this burgeoning area of inquiry in three primary ways. First, it tests independently and simultaneously the predictive power of two gambling patterns: breadth involvement (i.e., the number of games an individual plays) and depth involvement (i.e., the number of days an individual plays). Second, it includes the first involvement analyses of actual betting activity records that are associated with clinical screening information. Third, it evaluates and compares the linearity of breadth and depth effects. We conducted analyses of the actual gambling activity of 1,440 subscribers to the bwin.party gambling service who completed an online gambling disorder screen. In all, 11 of the 16 games we examined had a significant univariate association with a positive screen for gambling disorder. However, after controlling for breadth involvement, only Live Action Internet sports betting retained a significant relationship with potential gambling-related problems. Depth involvement, though significantly related to potential problems, did not impact game-based gambling disorder associations as much as breadth involvement. Finally, breadth effects appeared steeply linear, with a slight quadratic component manifesting beyond four games played, but depth effects appeared to have a strong linear component and a slight cubic component.

Cast Iron Versus Creativity: Fostering Balanced Thinking in Military Professionals

DTIC Science & Technology

2015-06-01

CREATIVITY: FOSTERING BALANCED THINKING IN MILITARY PROFESSIONALS by Michael H. Laplante June 2015 Thesis Advisor: Leo Blanken Co...AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE CAST IRON VERSUS CREATIVITY: FOSTERING BALANCED THINKING IN MILITARY PROFESSIONALS 5...utilizes multivariant experimentation with military officers. The research analyzes the impact of how a commander frames a problem to a subordinate. More

Housing Instability Among Current and Former Welfare Recipients

PubMed Central

Phinney, Robin; Danziger, Sheldon; Pollack, Harold A.; Seefeldt, Kristin

2007-01-01

Objectives. We examined correlates of eviction and homelessness among current and former welfare recipients from 1997 to 2003 in an urban Michigan community. Methods. Longitudinal cohort data were drawn from the Women’s Employment Study, a representative panel study of mothers who were receiving cash welfare in February 1997. We used logistic regression analysis to identify risk factors for both eviction and homelessness over the survey period. Results. Twenty percent (95% confidence interval [CI]=16%, 23%) of respondents were evicted and 12% (95% CI=10%, 15%) experienced homelessness at least once between fall 1997 and fall 2003. Multivariate analyses indicated 2 consistent risk factors: having less than a high school education and having used illicit drugs other than marijuana. Mental and physical health problems were significantly associated with homelessness but not evictions. A multivariate screening algorithm achieved 75% sensitivity and 67% specificity in identifying individuals at risk for homelessness. A corresponding algorithm for eviction achieved 75% sensitivity and 50% specificity. Conclusions. The high prevalence of housing instability among our respondents suggests the need to better target housing assistance and other social services to current and former welfare recipients with identifiable personal problems. PMID:17267717

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

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

Development of adolescents' peer crowd identification in relation to changes in problem behaviors.

PubMed

Doornwaard, Suzan M; Branje, Susan; Meeus, Wim H J; ter Bogt, Tom F M

2012-09-01

This 5-wave longitudinal study, which included 1,313 Dutch adolescents, examined the development of peer crowd identification in relation to changes in problem behaviors. Adolescents from 2 age cohorts annually reported their identification with 7 peer crowds and their levels of internalizing and externalizing problem behaviors. Univariate latent growth curve analyses revealed declines (i.e., "Hip Hoppers" and "Metal Heads") or declines followed by stabilization (i.e., "Nonconformists") in identification with nonconventional crowds and increases (i.e., "Elites" and "Brains") or declines followed by stabilization (i.e., "Normals" and "Jocks") in identification with conventional crowds. Multivariate latent growth curve analyses indicated that stronger and more persistent identifications with nonconventional crowds were generally associated with more problem behaviors throughout adolescence. In contrast, stronger and more persistent identifications with conventional crowds were generally associated with fewer problem behaviors throughout adolescence with the notable exception of Brains, who showed a mixed pattern. Though characterized by fewer externalizing problems, this group did report more anxiety problems. These findings and their implications are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Adjustment Problems and Multiple Intelligences among Gifted Students in Hong Kong: The Development of the Revised Student Adjustment Problems Inventory.

ERIC Educational Resources Information Center

Chan, David W.

2003-01-01

A study involving 639 Chinese gifted students (grades 4-12) found that intense emotional involvement, perfectionism, unchallenging schoolwork, multipotentiality, and parental expectations were relatively common adjustment problems. Poor interpersonal relationships were not. Results also indicated that conventional intelligence increased…

Rocks in a Box: A Three-Point Problem.

ERIC Educational Resources Information Center

Leyden, Michael B.

1981-01-01

Describes a simulation drilling core activity involving the use of a physical model from which students gather data and solve a three-point problem to determine the strike and dip of a buried stratum. Includes descriptions of model making, data plots, and additional problems involving strike and dip. (DS)

Proportional Reasoning in the Learning of Chemistry: Levels of Complexity

ERIC Educational Resources Information Center

Ramful, Ajay; Narod, Fawzia Bibi

2014-01-01

This interdisciplinary study sketches the ways in which proportional reasoning is involved in the solution of chemistry problems, more specifically, problems involving quantities in chemical reactions (commonly referred to as stoichiometry problems). By building on the expertise of both mathematics and chemistry education research, the present…

An Action-Research Program for Increasing Employee Involvement in Problem Solving.

ERIC Educational Resources Information Center

Pasmore, William; Friedlander, Frank

1982-01-01

Describes the use of participative action research to solve problems of work-related employee injuries in a rural midwestern electronics plant by increasing employee involvement. The researchers established an employee problem-solving group that interviewed and surveyed workers, analyzed the results, and suggested new work arrangements. (Author/RW)

Predictors of obesity in Michigan Operating Engineers.

PubMed

Duffy, Sonia A; Cohen, Kathleen A; Choi, Seung Hee; McCullagh, Marjorie C; Noonan, Devon

2012-06-01

Blue collar workers are at risk for obesity. Little is known about obesity in Operating Engineers, a group of blue collar workers, who operate heavy earth-moving equipment in road building and construction. Therefore, 498 Operating Engineers in Michigan were recruited to participate in a cross-sectional survey to determine variables related to obesity in this group. Bivariate and multivariate analyses were conducted to determine personal, psychological, and behavioral factors predicting obesity. Approximately 45% of the Operating Engineers screened positive for obesity, and another 40% were overweight. Multivariate analysis revealed that younger age, male sex, higher numbers of self-reported co-morbidities, not smoking, and low physical activity levels were significantly associated with obesity among Operating Engineers. Operating Engineers are significantly at risk for obesity, and workplace interventions are needed to address this problem.

Operationalizing Proneness to Externalizing Psychopathology as a Multivariate Psychophysiological Phenotype

PubMed Central

Nelson, Lindsay D.; Patrick, Christopher J.; Bernat, Edward M.

2010-01-01

The externalizing dimension is viewed as a broad dispositional factor underlying risk for numerous disinhibitory disorders. Prior work has documented deficits in event-related brain potential (ERP) responses in individuals prone to externalizing problems. Here, we constructed a direct physiological index of externalizing vulnerability from three ERP indicators and evaluated its validity in relation to criterion measures in two distinct domains: psychometric and physiological. The index was derived from three ERP measures that covaried in their relations with externalizing proneness the error-related negativity and two variants of the P3. Scores on this ERP composite predicted psychometric criterion variables and accounted for externalizing-related variance in P3 response from a separate task. These findings illustrate how a diagnostic construct can be operationalized as a composite (multivariate) psychophysiological variable (phenotype). PMID:20573054

Depressive symptoms in nonresident african american fathers and involvement with their sons.

PubMed

Davis, R Neal; Caldwell, Cleopatra Howard; Clark, Sarah J; Davis, Matthew M

2009-12-01

Our objective was to determine whether paternal depressive symptoms were associated with less father involvement among African American fathers not living with their children (ie, nonresident fathers). We analyzed survey data for 345 fathers enrolled in a program for nonresident African American fathers and their preteen sons. Father involvement included measures of contact, closeness, monitoring, communication, and conflict. We used bivariate analyses and multivariate logistic regression analysis to examine associations between father involvement and depressive symptoms. Thirty-six percent of fathers reported moderate depressive symptoms, and 11% reported severe depressive symptoms. In bivariate analyses, depressive symptoms were associated with less contact, less closeness, low monitoring, and increased conflict. In multivariate analyses controlling for basic demographic features, fathers with moderate depressive symptoms were more likely to have less contact (adjusted odds ratio: 1.7 [95% confidence interval: 1.1-2.8]), less closeness (adjusted odds ratio: 2.1 [95% confidence interval: 1.3-3.5]), low monitoring (adjusted odds ratio: 2.7 [95% confidence interval: 1.4-5.2]), and high conflict (adjusted odds ratio: 2.1 [95% confidence interval: 1.2-3.6]). Fathers with severe depressive symptoms also were more likely to have less contact (adjusted odds ratio: 3.1 [95% confidence interval: 1.4-7.2]), less closeness (adjusted odds ratio: 2.6 [95% confidence interval: 1.2-5.7]), low monitoring (adjusted odds ratio: 2.8 [95% confidence interval: 1.1-7.1]), and high conflict (adjusted odds ratio: 2.6 [95% confidence interval: 1.1-5.9]). Paternal depressive symptoms may be an important, but modifiable, barrier for nonresident African American fathers willing to be more involved with their children.

Factors associated with severe dry eye in primary Sjögren's syndrome diagnosed patients.

PubMed

Fernandez Castro, Mónica; Sánchez-Piedra, Carlos; Andreu, Jose Luis; Martínez Taboada, Víctor; Olivé, Alejandro; Rosas, Jose

2018-06-01

Primary Sjögren's syndrome (pSS) is an autoimmune disease, characterized by lymphocytic infiltration of exocrine glands and other organs, resulting in dry eye, dry mouth and extraglandular systemic findings. To explore the association of severe or very severe dry eye with extraocular involvement in patients diagnosed with primary Sjögren's syndrome. SJOGRENSER registry is a multicenter cross-sectional study of pSS patients. For the construction of our main variable, severe/very severe dry eye, we used those variables that represented a degree 3-4 of severity according to the 2007 Dry Eye Workshop classification. First, bivariate logistic regression models were used to identify the effect of each independent variable on severe/very severe dry eye. Secondly, multivariate analysis using regression model was used to establish the independent effect of patient characteristics. Four hundred and thirty-seven patients were included in SJOGRENSER registry; 94% of the patients complained of dry eye and 16% developed corneal ulcer. Schirmer's test was pathological in 92% of the patients; 378 patients presented severe/very severe dry eye. Inflammatory articular involvement was significantly more frequent in patients with severe/very severe dry eye than in those without severe/very severe dry eye (82.5 vs 69.5%, p = 0,028). Inflammatory joint involvement was associated with severe/very severe dry eye in the multivariate analysis, OR 2.079 (95% CI 1.096-3.941). Severe or very severe dry eye is associated with the presence of inflammatory joint involvement in patients with pSS. These results suggest that a directed anamnesis including systemic comorbidities, such as the presence of inflammatory joint involvement or dry mouth in patients with dry eye, would be useful to suspect a pSS.

The paradox of public holidays: Hospital-treated self-harm and associated factors.

PubMed

Griffin, Eve; Dillon, Christina B; O'Regan, Grace; Corcoran, Paul; Perry, Ivan J; Arensman, Ella

2017-08-15

Recent research on the patterns of self-harm around public holidays is lacking. This study used national data to examine the patterns of hospital-treated self-harm during public holidays, and to examine associated factors. Data on self-harm presentations to all emergency departments were obtained from the National Self-Harm Registry Ireland. The association between self-harm presentations and public holidays was examined using univariate and multivariate Poisson regression analyses. A total of 104,371 presentations of self-harm were recorded between 2007 and 2015. The mean number of self-harm presentations was 32 on public holidays. St. Patrick's Day had the highest number of presentations compared to all other public holidays, with a daily mean of 44 presentations. Across all years, self-harm presentations during public holidays had a 24% increased risk of involving alcohol consumption compared to all other days and this effect was most pronounced during the Christmas period. The association with alcohol remained significant at a multivariate level. Presentations on public holidays were more likely to attend out of normal working hours. An increase in male presentations involving self-cutting was observed on public holidays and there was an over-representation of males presenting for the first time. It is likely that extent of alcohol involvement in self-harm presentations reported here is an underestimate, as it was dependent on the information being recorded by the attending clinician. Public holidays are associated with an elevated number of self-harm presentations to hospital, with presentations to hospital involving alcohol significantly increased on these days. Hospital resources should be targeted to address increases during public holidays, including during out-of-hours. Involvement of alcohol may delay delivery of care to these patients in emergency settings. Copyright © 2017 Elsevier B.V. All rights reserved.

Factors associated with physicians' choice of a career in research: a retrospective report 15 years after medical school graduation.

PubMed

Krupat, Edward; Camargo, Carlos A; Strewler, Gordon J; Espinola, Janice A; Fleenor, Thomas J; Dienstag, Jules L

2017-03-01

Relatively little is known regarding factors associated with the choice of a research career among practicing physicians, and most investigations of this issue have been conducted in the absence of a theoretical/conceptual model. Therefore we designed a survey to identify the determinants of decisions to pursue a biomedical research career based upon the Theory of Planned Behavior and the concept of stereotype threat. From October 2012 through January 2014 electronic surveys were sent to four consecutive Harvard Medical School graduating classes, 1996-1999. Respondents provided demographic information, indicated their current research involvement, and provided retrospective reports of their experiences and attitudes when they were making career choices as they completed medical school. Multivariable ordinal regression was used to identify factors independently associated with current research involvement. Completed questionnaires were received from 358 respondents (response rate 65 %). In unadjusted analyses, variables associated with more extensive research involvement included non-minority status, male gender, lower debt at graduation, strong attitudes toward research at time of graduation, and greater social pressures to pursue research (all P < .001). These associations remained significant in multivariable regression analysis (all P < 0.01). However, an interaction between sex and prior research publications was also detected, indicating that more extensive research involvement during medical school doubled the likelihood of a research career for women (OR 2.53, 95 % CI 1.00-6.40; P = 0.05). Most of the factors predicting research career choice involve factors that are potentially modifiable, suggesting that appropriately designed behavioral interventions may help to expand the size and diversity of the biomedical research community.

Expert Involvement Predicts mHealth App Downloads: Multivariate Regression Analysis of Urology Apps

PubMed Central

Osório, Luís; Cavadas, Vitor; Fraga, Avelino; Carrasquinho, Eduardo; Cardoso de Oliveira, Eduardo; Castelo-Branco, Miguel; Roobol, Monique J

2016-01-01

Background Urological mobile medical (mHealth) apps are gaining popularity with both clinicians and patients. mHealth is a rapidly evolving and heterogeneous field, with some urology apps being downloaded over 10,000 times and others not at all. The factors that contribute to medical app downloads have yet to be identified, including the hypothetical influence of expert involvement in app development. Objective The objective of our study was to identify predictors of the number of urology app downloads. Methods We reviewed urology apps available in the Google Play Store and collected publicly available data. Multivariate ordinal logistic regression evaluated the effect of publicly available app variables on the number of apps being downloaded. Results Of 129 urology apps eligible for study, only 2 (1.6%) had >10,000 downloads, with half having ≤100 downloads and 4 (3.1%) having none at all. Apps developed with expert urologist involvement (P=.003), optional in-app purchases (P=.01), higher user rating (P<.001), and more user reviews (P<.001) were more likely to be installed. App cost was inversely related to the number of downloads (P<.001). Only data from the Google Play Store and the developers’ websites, but not other platforms, were publicly available for analysis, and the level and nature of expert involvement was not documented. Conclusions The explicit participation of urologists in app development is likely to enhance its chances to have a higher number of downloads. This finding should help in the design of better apps and further promote urologist involvement in mHealth. Official certification processes are required to ensure app quality and user safety. PMID:27421338

Factors associated with physicians’ choice of a career in research: A retrospective report 15 years after medical school graduation

PubMed Central

Krupat, Edward; Camargo, Carlos A.; Strewler, Gordon J.; Espinola, Janice A.; Fleenor, Thomas J.; Dienstag, Jules L.

2016-01-01

Relatively little is known regarding factors associated with the choice of a research career among practicing physicians, and most investigations of this issue have been conducted in the absence of a theoretical/conceptual model. Therefore we designed a survey to identify the determinants of decisions to pursue a biomedical research career based upon the Theory of Planned Behavior and the concept of stereotype threat. From October 2012 through January 2014 electronic surveys were sent to four consecutive Harvard Medical School graduating classes, 1996-1999. Respondents provided demographic information, indicated their current research involvement, and provided retrospective reports of their experiences and attitudes when they were making career choices as they completed medical school. Multivariable ordinal regression was used to identify factors independently associated with current research involvement. Completed questionnaires were received from 358 respondents (response rate 65%). In unadjusted analyses, variables associated with more extensive research involvement included non-minority status, male gender, lower debt at graduation, strong attitudes toward research at time of graduation, and greater social pressures to pursue research (all P<.001). These associations remained significant in multivariable regression analysis (all P<0.01). However, an interaction between sex and prior research publications was also detected, indicating that more extensive research involvement during medical school doubled the likelihood of a research career for women (OR 2.53, 95%CI 1.00-6.40; P=0.05). Most of the factors predicting research career choice involve factors that are potentially modifiable, suggesting that appropriately designed behavioral interventions may help to expand the size and diversity of the biomedical research community. PMID:27112959

Maternal Characteristics Associated With Social Support in At-Risk Mothers of Premature Infants.

PubMed

White-Traut, Rosemary; Rankin, Kristin; Fabiyi, Camille; Liu, Li; Cheung, Irene; Norr, Kathleen

To identify maternal characteristics associated with social support among new mothers of premature infants who are at social-environmental risk. Cross-sectional analysis of intake interview data from a larger randomized controlled trial of a mother-premature infant developmentally based intervention. Two urban community-based hospitals. One hundred ninety-four women (50% Black, 50% Hispanic) who recently gave birth to otherwise healthy, premature (29-34 weeks gestational age) infants. Participants had at least 2 of 10 social-environmental risks (e.g., poverty). In-hospital interviews were conducted to obtain data on sociodemographic characteristics, prior mental health problems, and social support through the use of the Personal Resources Questionnaire 2000. Bivariate and multivariable linear regression analyses were performed to identify factors associated with social support. Mean Personal Resources Questionnaire 2000 scores were significantly lower for Hispanic than Black participants (92.0 vs. 96.0, respectively), those interviewed in Spanish versus English (89.8 vs. 96.1), those with low versus age-appropriate education levels (89.7 vs. 95.3), multiparous versus primiparous women (92.7 vs. 96.0), and those reporting versus not reporting histories of mental health problems (84.7 vs. 94.8). After multivariable adjustment, only younger age, Spanish language preference, multiparity, and a history of mental health problems were associated with significantly lower levels of social support (R 2  = 0.18). More programs should be made available to provide social support to at-risk mothers, especially younger mothers, and those with limited English ability, other children at home, or histories of mental health problems. Nurses should target these mothers for additional support during their premature infants' NICU stay. Copyright © 2017 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

The multiplicative effect of combining alcohol with energy drinks on adolescent gambling.

PubMed

Vieno, Alessio; Canale, Natale; Potente, Roberta; Scalese, Marco; Griffiths, Mark D; Molinaro, Sabrina

2018-07-01

There has been increased concern about the negative effects of adolescents consuming a combination of alcohol mixed with energy drinks (AmED). To date, few studies have focused on AmED use and gambling. The present study analyzed the multiplicative effect of AmED consumption, compared to alcohol alone, on the likelihood of at-risk or problem gambling during adolescence. Data from the ESPAD®Italia 2015 study, a cross-sectional survey conducted in a nationally representative sample of students (ages 15 to 19years) were used to examine the association between self-reported AmED use (≥6 times,≥10 times, and ≥20 times during the last month) and self-reported gambling severity. Multivariate models were used to calculate adjusted prevalence ratios to evaluate the association between alcohol use, AmED use, and gambling among a representative sample of adolescents who reported gambling in the last year and completed a gambling severity scale (n=4495). Among the 19% students classed as at-risk and problem gamblers, 43.9% were classed as AmED consumers, while 23.6% were classed as alcohol consumers (i.e. did not mix alcohol with energy drinks). In multivariate analyses that controlled for covariates, AmED consumers were three times more likely to be at-risk and problem gamblers (OR=3.05) compared to non-consuming adolescents, while the effect became less pronounced with considering those who consumed alcohol without the addition of energy drinks (OR=1.37). The present study clearly established that consuming AmED might pose a significantly greater risk of experiencing gambling-related problems among adolescents. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Association of Combat Exposure With Postdeployment Behavioral Health Problems Among U.S. Army Enlisted Women Returning From Afghanistan or Iraq.

PubMed

Adams, Rachel Sayko; Nikitin, Ruslan V; Wooten, Nikki R; Williams, Thomas V; Larson, Mary Jo

2016-08-01

An association between combat exposure and postdeployment behavioral health problems has been demonstrated among U.S. military service members returning from Afghanistan or Iraq in predominantly male samples, yet few studies have focused on the experiences of women. Using data from the longitudinal, observational Substance Use and Psychological Injury Combat (SUPIC) Study, we explored the self-report of 4 combat exposure items and postdeployment behavioral health screening results for 42,397 Army enlisted women who had returned from Afghanistan or Iraq from fiscal years 2008 through 2011. We ran multivariate logistic regression models to examine how a constructed composite combat exposure score (0, 1, 2, 3+) was associated with screening positive postdeployment for posttraumatic stress disorder (PTSD), depression, and at-risk drinking among active duty (AD) and National Guard/Reserve (NG/R) women. AD and NG/R women commonly reported being wounded, injured, assaulted, or hurt (17.3% and 29.0%, respectively). In all 6 multivariate models, Army women with any report of combat exposure had increased odds of the behavioral health problem (i.e., PTSD, depression, or at-risk drinking). The magnitude of the association between combat exposure and PTSD was most striking, indicating increased odds of PTSD as combat exposure score increased. AD and NG/R women with a combat exposure score of 3+ had increased odds of PTSD, 20.7, 95% confidence interval (CI) [17.0, 25.1] and 27.8, 95% CI [21.0, 36.9], respectively. Women who report combat exposure may benefit from early prevention and confidential intervention to promote postdeployment health and reduce long-term behavioral health problems. Copyright © 2016 International Society for Traumatic Stress Studies.

The Association of Combat Exposure With Postdeployment Behavioral Health Problems Among U.S. Army Enlisted Women Returning From Afghanistan or Iraq

PubMed Central

Adams, Rachel Sayko; Nikitin, Ruslan V.; Wooten, Nikki R.; Williams, Thomas V.; Larson, Mary Jo

2016-01-01

An association between combat exposure and postdeployment behavioral health problems has been demonstrated among U.S. military service members returning from Afghanistan or Iraq in predominantly male samples, yet few studies have focused on the experiences of women. Using data from the longitudinal, observational Substance Use and Psychological Injury Combat (SUPIC) study, this study explored the self-report of 4 combat exposure items and postdeployment behavioral health screening results for 42,397 Army enlisted women who returned from Afghanistan or Iraq from fiscal years 2008 through 2011. We ran multivariate logistic regression models to examine how a constructed composite combat exposure score (0, 1, 2, 3+) was associated with screening positive postdeployment for posttraumatic stress disorder (PTSD), depression, or at-risk drinking among active duty (AD) and National Guard/Reserve (NG/R) women. AD and NG/R women commonly reported being wounded, injured, assaulted, or hurt (17.3% and 29.0%, respectively). In all 6 multivariate models, Army women with any report of combat exposure had increased odds of the behavioral health problem (i.e., PTSD, depression, or at-risk drinking). The magnitude of the association between combat exposure and PTSD was most striking, indicating increased odds of PTSD as combat exposure score increased. AD and NG/R women with a combat exposure score of 3+ had increased odds of PTSD, 20.7, 95% CI [17.0, 25.1] and 27.8, 95% CI [21.0, 36.9], respectively. Women who reported combat exposure may benefit from early prevention and confidential intervention to promote postdeployment health and reduce long-term behavioral health problems. PMID:27476700

How does maternal oxytocin influence children's mental health problem and maternal mental health problem?

PubMed

Tse, Wai S; Siu, Angela F Y; Wong, Tracy K Y

2017-12-01

This study aims to explore the interrelationship among maternal oxytocin (OT) responsiveness, maternal mental health, maternal parenting behavior, and mental health of children under a free-play interaction. 61 mother-child dyads were recruited for the study. Maternal mental health problem and parenting self-efficacy were measured using self-reported questionnaires. The mental health problems of children were also evaluated using a mother-reported questionnaire. Furthermore, salivary OT was collected before and after a standardized 10min free-play interaction. Parenting behaviors, including eye gaze and touch, were measured during the free-play interaction. Maternal OT responsiveness was significantly associated with less maternal mental health problem, touch frequency, and mental health problem of children but not with parenting self-efficacy. In the multivariate linear regression analysis that considers maternal OT responsiveness and maternal and children's mental health problems, maternal OT responsiveness was not associated with the mental health problems of children. This result suggested that maternal mental health problem played a mediational role between maternal OT responsiveness and the mental health problem of children. Results supported the assertion that maternal OT responsiveness contributed to the increased risk of maternal mental health problems and, subsequently, the risk of mental health problems of their children. Copyright © 2017 Elsevier B.V. All rights reserved.

Differential Effects of Counselor Self-Disclosure, Self-Involving Statements, and Interpretation.

ERIC Educational Resources Information Center

Dowd, E. Thomas; Boroto, Daniel R.

1982-01-01

College students (N=217) rated counselor characteristics after viewing a simulated counseling session ending with the counselor summarizing the session, disclosing a past personal problem, disclosing a present personal problem, engaging in self-involving statements, or offering dynamic interpretations. Self-disclosure and self-involving statements…

Presence of Ureaplasma diversum in the genital tracts of female dairy cattle in Mato Grosso State, Brazil.

PubMed

Azevedo, Jaqueline B; Silva, Gustavo S; Rocha, Priscylla S; Pitchenin, Letícia C; Dutra, Valéria; Nakazato, Luciano; de Oliveira, Anderson Castro Soares; Pescador, Caroline A

2017-02-01

Ureaplasma diversum infection in bovine females may result in various reproductive problems, including granular vulvovaginitis, abortion, weak calves, salpingitis, and spontaneous abortion. The presence of U. diversum in a dairy bovine population from midwestern Brazil has not been established. The aim of this study was to determine whether U. diversum was present in dairy cattle from midwestern Brazil using polymerase chain reaction (PCR). Vulvovaginal mucus was analyzed from 203 cows located in six municipalities in the north region of Mato Grosso State, Brazil. A total of 25% of dairy cows with vulvovaginitis were positive for U. diversum. The factors evaluated were included in a multivariable logistic regression model with the presence of at least one positive cow in the herd serving as the dependent variable. Three variables were significantly associated with a U. diversum-positive PCR and were included in the final multivariable model: number of parities, vulvar lesions, and reproductive problems. For each new parity, the chance of U. diversum infection decreased 0.03-fold, indicating that cows with the highest number of parities were more protected. The presence of vulvar lesions was increased 17.6-fold in females positive for U. diversum, suggesting that this bacterium could be related to the red granular lesions in the vulvar mucosa, whereas reproductive problems were increased 7.6-fold. However, further investigations should be conducted to ascertain the effects of U. diversum in association with other mycoplasma species in the herds studied.