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Journal articles on the topic 'Multivariate utility'

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Published: 9 March 2023
Last updated: 10 March 2023

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1

Scarsini, Marco. "Dominance Conditions for Multivariate Utility Functions." Management Science 34, no. 4 (April 1988): 454–60. http://dx.doi.org/10.1287/mnsc.34.4.454.

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2

Charpentier, Arthur, Alfred Galichon, and Marc Henry. "Local Utility and Multivariate Risk Aversion." Mathematics of Operations Research 41, no. 2 (May 2016): 466–76. http://dx.doi.org/10.1287/moor.2015.0736.

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3

Aichinger, Florian, and Sascha Desmettre. "Utility Maximization in Multivariate Volterra Models." SIAM Journal on Financial Mathematics 14, no. 1 (January 19, 2023): 52–98. http://dx.doi.org/10.1137/21m1464543.

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4

Dyckerhoff, Rainer. "Decomposition of multivariate utility functions in non-additive expected utility theory." Journal of Multi-Criteria Decision Analysis 3, no. 1 (April 1994): 41–58. http://dx.doi.org/10.1002/mcda.4020030106.

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5

Safra, Zvi, and Uzi Segal. "Dominance Axioms and Multivariate Nonexpected Utility Preferences." International Economic Review 34, no. 2 (May 1993): 321. http://dx.doi.org/10.2307/2526915.

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6

Campi, Luciano, and Mark P. Owen. "Multivariate utility maximization with proportional transaction costs." Finance and Stochastics 15, no. 3 (April 20, 2010): 461–99. http://dx.doi.org/10.1007/s00780-010-0125-9.

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7

Kritzman, Mark, and Don R. Rich. "Risk Containment for Investors with Multivariate Utility Functions." Journal of Derivatives 5, no. 3 (February 28, 1998): 28–44. http://dx.doi.org/10.3905/jod.1998.407996.

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8

Escobar-Anel, Marcos. "Multivariate risk aversion utility, application to ESG investments." North American Journal of Economics and Finance 63 (November 2022): 101790. http://dx.doi.org/10.1016/j.najef.2022.101790.

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9

Karni, Edi. "Generalized Expected Utility Analysis of Multivariate Risk Aversion." International Economic Review 30, no. 2 (May 1989): 297. http://dx.doi.org/10.2307/2526648.

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10

Li, Mingli, Xiaojing Li, Deng Wei, Yinfei Li, Liansheng Zhao, Xiaohong Ma, Yingcheng Wang, et al. "S179. PROGNOSTIC UTILITY OF MULTIVARIATE MORPHOMETRY IN SCHIZOPHRENIA." Schizophrenia Bulletin 44, suppl_1 (April 1, 2018): S394. http://dx.doi.org/10.1093/schbul/sby018.966.

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11

Wold, Svante, Mats Josefson, Johan Gottfries, and Anna Linusson. "The utility of multivariate design in PLS modeling." Journal of Chemometrics 18, no. 34 (March 2004): 156–65. http://dx.doi.org/10.1002/cem.861.

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12

Sreedharan, S., G. R. Poornima, Meena Nair, Genanew Bekele, Wathiq Mansoor, and Ananth Rao. "Users’ Satisfaction of Public Utility Services – Multivariate System Analysis." International Conference on Advances in Business, Management and Law (ICABML) 2017 1, no. 1 (December 24, 2017): 30–60. http://dx.doi.org/10.30585/icabml-cp.v1i1.12.

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This research develops a multivariate system framework for assessing user satisfaction of public water utility organization in a developing country and predicts quality, quantity and overall user satisfaction for policy initiatives. The model framework is applied to the data collected by Public Affairs Centre (PAC) based on the Citizen Report Card approach pioneered by it. Wald test confirms that there exits cross equation correlation across quality, quantity and overall users’ satisfaction dimensions. Based on the system model, the study identifies statistically significant factors that explain users’ loyalty to express satisfaction and voice to express dissatisfaction of users. Policy initiatives are proposed on key factors to reduce voice factors set so that the service provider could improve its service delivery. The system model correctly predicts 85% of satisfied customers across quality, quantity and overall satisfaction dimensions. Keywords: Multivariate, Logit, Discrete choice Model, Public Sector Utility service provider
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13

Rinks, Dan B., Jeffrey L. Ringuest, and Michael H. Peters. "A multivariate utility function approach to stochastic capacity planning." Engineering Costs and Production Economics 12, no. 1-4 (July 1987): 3–13. http://dx.doi.org/10.1016/0167-188x(87)90056-5.

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14

Webster, Robert. "Group Think in Financial Analysis? A Multivariate Study." Journal of Finance Issues 6, no. 2 (December 31, 2008): 18–27. http://dx.doi.org/10.58886/jfi.v6i2.2414.

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This multivariate behavioral research investigates if financial assessments made by analysts may be affected by the professional employment group or sector in which the analyst works. Professional financial analysts from two separate groups were studied. The two groups were analysts for state public service commissions who regulate the public utilities industry and professional private sector analysts who specifically follow stocks and bonds of public utility companies. Members of both groups were asked by way of a mailed survey to analyze multiyear comparative financial statements of a publicly traded electric utility company using variables related to liquidity, long term debt, cash flow, dividends, profitability, as well as the overall financial condition of the firm. The paper describes the data collection process, statistical analysis, and results of the research.
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15

Benedetti, Giuseppe, and Luciano Campi. "Multivariate Utility Maximization with Proportional Transaction Costs and Random Endowment." SIAM Journal on Control and Optimization 50, no. 3 (January 2012): 1283–308. http://dx.doi.org/10.1137/110831064.

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16

Zaritsky, Joshua J., and Brian Y. Young. "The utility of multivariate analysis in the study of hepcidin." Kidney International 76, no. 8 (October 2009): 912. http://dx.doi.org/10.1038/ki.2009.272.

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17

Schlee, Edward E. "The preservation of multivariate comparative statics in nonexpected utility theory." Journal of Risk and Uncertainty 9, no. 3 (December 1994): 257–72. http://dx.doi.org/10.1007/bf01064203.

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18

Carbonell, Felix, Arnaud Charil, Alex P. Zijdenbos, Alan C. Evans, and Barry J. Bedell. "Hierarchical Multivariate Covariance Analysis of Metabolic Connectivity." Journal of Cerebral Blood Flow & Metabolism 34, no. 12 (October 8, 2014): 1936–43. http://dx.doi.org/10.1038/jcbfm.2014.165.

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Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).
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19

Soldatos, Gerasimos. "Marginal Utility and Cournot Stability Under Market Entry." Studies in Business and Economics 16, no. 1 (April 1, 2021): 187–97. http://dx.doi.org/10.2478/sbe-2021-0015.

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Abstract This paper introduces into the discussion of the stability of quantity-oligopoly equilibrium, the role that the slope of the marginal utility curve and of market entry in shaping the equilibrium and its stability. It does so by considering inverse multivariate linear demand functions and the notion of stability related to multivariate mean value theorem. The equilibrium cluster of Cournot sellers is determined by the stability dictated by this theorem and the rate of decline of the marginal utility of the product under consideration. Strategic complementarity is found to be the case under product heterogeneity, while the strategic substitutability associated with product homogeneity, induces a modification of Cournot limit theorem.
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20

Klyushin, Yaroslav G., Egor V. Pesterev, and Ilia A. Tetslav. "UTILITY ELASTICITY AS A MEASURE OF CORRELATION IN MULTIVARIATE DATA ANALYSIS." Proceedings of Irkutsk State Technical University 21, no. 1 (January 2017): 54–62. http://dx.doi.org/10.21285/1814-3520-2017-1-54-62.

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21

SASS, JÖRN, and DOROTHEE WESTPHAL. "ROBUST UTILITY MAXIMIZATION IN A MULTIVARIATE FINANCIAL MARKET WITH STOCHASTIC DRIFT." International Journal of Theoretical and Applied Finance 24, no. 04 (June 2021): 2150020. http://dx.doi.org/10.1142/s0219024921500205.

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We study a utility maximization problem in a financial market with a stochastic drift process, combining a worst-case approach with filtering techniques. Drift processes are difficult to estimate from asset prices, and at the same time optimal strategies in portfolio optimization problems depend crucially on the drift. We approach this problem by setting up a worst-case optimization problem with a time-dependent uncertainty set for the drift. Investors assume that the worst possible drift process with values in the uncertainty set will occur. This leads to local optimization problems, and the resulting optimal strategy needs to be updated continuously in time. We prove a minimax theorem for the local optimization problems and derive the optimal strategy. Further, we show how an ellipsoidal uncertainty set can be defined based on filtering techniques and demonstrate that investors need to choose a robust strategy to be able to profit from additional information.
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22

Bhat, Chandra R., Rajesh Paleti, and Marisol Castro. "A New Utility-Consistent Econometric Approach to Multivariate Count Data Modeling." Journal of Applied Econometrics 30, no. 5 (July 16, 2014): 806–25. http://dx.doi.org/10.1002/jae.2405.

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23

TODOROVA, Tamara. "Diminishing Marginal Utility and the Teaching of Economics: A Note." Journal of Research in Educational Sciences 12, no. 14 (December 31, 2021): 25. http://dx.doi.org/10.14505/jres.v12.14.02.

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This paper discusses how utility can be taught in undergraduate courses in microeconomics so that to illustrate total and marginal utility, the law of diminishing marginal utility, and consumer rationality. Diminishing marginal utility is essential in describing rational consumer behavior, overconsumption, and oversaturation to students of economics. We demonstrate a quadratic and a logarithmic total utility with the subsequent forms and shapes of marginal utility. From what it seems there is no contradiction between diminishing marginal utility in the univariate context of consuming one good and the indifference curve as the multivariate case of two goods consumed.
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24

Kamphuis, Jan H., Paul A. Arbisi, Yossef S. Ben-Porath, and John L. McNulty. "Detecting Comorbid Axis-II Status Among Inpatients Using the MMPI-2 Restructured Clinical Scales." European Journal of Psychological Assessment 24, no. 3 (January 2008): 157–64. http://dx.doi.org/10.1027/1015-5759.24.3.157.

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This study examined the differential diagnostic utility of the MMPI-2 Restructured Clinical Scales (RCS) and Clinical Scales (CS) in detecting a complex multivariate clinical phenomenon: that is, comorbid Axis-II status in two matched samples of inpatients. Psychiatric inpatients diagnosed with either substance use disorder (n = 43) or major depression (n = 49) were matched on age, sex, and clinical setting, and compared with patients with the same Axis-I disorder and a comorbid personality disorder. Presence or absence of a comorbid personality disorder was chosen to provide a potent test of the differential diagnostic utility of the RCS versus CS when using a highly complex, multivariate criterion variable. Using hierarchical logistic regression analyses, the RCS consistently demonstrated higher diagnostic utility. Moreover, the RCS profiles were significantly more focused and more readily interpretable, relative to the CS profiles that were remarkably similar across disorders. These findings provide further support for the diagnostic and clinical utility of the RCS.
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25

Trzęsiok, Michał. "Measuring the Quality of Multivariate Statistical Models." Acta Universitatis Lodziensis. Folia Oeconomica 6, no. 339 (February 13, 2019): 99–100. http://dx.doi.org/10.18778/0208-6018.339.06.

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Assessing the quality of a statistical model is very important, since it is crucial for the utility of the modelling process’ outcome. There are many different ways of measuring statistical models’ quality. Some of the measures represent a “goodness of fit” approach, some are “prediction ability” orientated. Among them there are absolute and relative measures. It is a researcher’s decision, which model quality measure is the most adequate for the given task. In the paper we present an overview of statistical models’ quality measures and a suggestion of using different ones during the model type selection stage and the stage of assessing the quality of the final model.
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26

Raymond, Mark R., and Zhehan Jiang. "Indices of Subscore Utility for Individuals and Subgroups Based on Multivariate Generalizability Theory." Educational and Psychological Measurement 80, no. 1 (May 16, 2019): 67–90. http://dx.doi.org/10.1177/0013164419846936.

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Conventional methods for evaluating the utility of subscores rely on traditional indices of reliability and on correlations among subscores. One limitation of correlational methods is that they do not explicitly consider variation in subtest means. An exception is an index of score profile reliability designated as [Formula: see text], which quantifies the ratio of true score profile variance to observed score profile variance. [Formula: see text] has been shown to be more sensitive than correlational methods to group differences in score profile utility. However, it is a group average, representing the expected value over a population of examinees. Just as score reliability varies across individuals and subgroups, one can expect that the reliability of score profiles will vary across examinees. This article proposes two conditional indices of score profile utility grounded in multivariate generalizability theory. The first is based on the ratio of observed profile variance to the profile variance that can be attributed to random error. The second quantifies the proportion of observed variability in a score profile that can be attributed to true score profile variance. The article describes the indices, illustrates their use with two empirical examples, and evaluates their properties with simulated data. The results suggest that the proposed estimators of profile error variance are consistent with the known error in simulated score profiles and that they provide information beyond that provided by traditional measures of subscore utility. The simulation study suggests that artificially large values of the indices could occur for about 5% to 8% of examinees. The article concludes by suggesting possible applications of the indices and discusses avenues for further research.
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27

Ashby, Damien R., Daniel P. Gale, Mark Busbridge, Patrick H. Maxwell, and Peter Choi. "Response to ‘The utility of multivariate analysis in the study of hepcidin’." Kidney International 76, no. 8 (October 2009): 912–13. http://dx.doi.org/10.1038/ki.2009.277.

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28

Simpson, E. S., J. L. Wadsworth, and J. A. Tawn. "Determining the dependence structure of multivariate extremes." Biometrika 107, no. 3 (May 7, 2020): 513–32. http://dx.doi.org/10.1093/biomet/asaa018.

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Summary In multivariate extreme value analysis, the nature of the extremal dependence between variables should be considered when selecting appropriate statistical models. Interest often lies in determining which subsets of variables can take their largest values simultaneously while the others are of smaller order. Our approach to this problem exploits hidden regular variation properties on a collection of nonstandard cones, and provides a new set of indices that reveal aspects of the extremal dependence structure not available through existing measures of dependence. We derive theoretical properties of these indices, demonstrate their utility through a series of examples, and develop methods of inference that also estimate the proportion of extremal mass associated with each cone. We apply the methods to river flows in the U.K., estimating the probabilities of different subsets of sites being large simultaneously.
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29

Mohajan, Devajit, and Haradhan Kumar Mohajan. "Utility Maximization Analysis of an Organization: A Mathematical Economic Procedure." Law and Economy 2, no. 1 (January 2023): 1–15. http://dx.doi.org/10.56397/le.2023.01.01.

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In the society utility is the vital concept, especially in mathematical economics. It is considered as the tendency of an object or action that increases or decreases overall happiness. In social sciences, the property of a commodity that enables to satisfy human wants is called utility. This paper has tried to operate utility maximization policy of an organization by considering two constraints: budget constraint and coupon constraint. To develop the maximization policy of utility function, the techniques of multivariate calculus are used. In this study four commodity variables are used to operate the mathematical analysis efficiently. In this article Lagrange multiplier technique is applied to achieve optimal result throughout the study.
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30

SASS, JÖRN, DOROTHEE WESTPHAL, and RALF WUNDERLICH. "EXPERT OPINIONS AND LOGARITHMIC UTILITY MAXIMIZATION FOR MULTIVARIATE STOCK RETURNS WITH GAUSSIAN DRIFT." International Journal of Theoretical and Applied Finance 20, no. 04 (April 2, 2017): 1750022. http://dx.doi.org/10.1142/s0219024917500224.

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This paper investigates optimal trading strategies in a financial market with multidimensional stock returns, where the drift is an unobservable multivariate Ornstein–Uhlenbeck process. Information about the drift is obtained by observing stock returns and expert opinions which provide unbiased estimates on the current state of the drift. The optimal trading strategy of investors maximizing expected logarithmic utility of terminal wealth depends on the filter which is the conditional expectation of the drift given the available information. We state filtering equations to describe its dynamics for different information settings. At information dates, the expert opinions lead to an update of the filter which causes a decrease in the conditional covariance matrix. We investigate properties of these conditional covariance matrices. First, we consider the asymptotic behavior of the covariance matrices for an increasing number of expert opinions on a finite time horizon. Second, we state conditions for convergence in infinite time with regularly-arriving expert opinions. Finally, we derive the optimal trading strategy of an investor. The optimal expected logarithmic utility of terminal wealth, the value function, is a functional of the conditional covariance matrices. Hence, our analysis of the covariance matrices allows us to deduce properties of the value function.
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31

El Emam, Khaled, Lucy Mosquera, Xi Fang, and Alaa El-Hussuna. "Utility Metrics for Evaluating Synthetic Health Data Generation Methods: Validation Study." JMIR Medical Informatics 10, no. 4 (April 7, 2022): e35734. http://dx.doi.org/10.2196/35734.

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Background A regular task by developers and users of synthetic data generation (SDG) methods is to evaluate and compare the utility of these methods. Multiple utility metrics have been proposed and used to evaluate synthetic data. However, they have not been validated in general or for comparing SDG methods. Objective This study evaluates the ability of common utility metrics to rank SDG methods according to performance on a specific analytic workload. The workload of interest is the use of synthetic data for logistic regression prediction models, which is a very frequent workload in health research. Methods We evaluated 6 utility metrics on 30 different health data sets and 3 different SDG methods (a Bayesian network, a Generative Adversarial Network, and sequential tree synthesis). These metrics were computed by averaging across 20 synthetic data sets from the same generative model. The metrics were then tested on their ability to rank the SDG methods based on prediction performance. Prediction performance was defined as the difference between each of the area under the receiver operating characteristic curve and area under the precision-recall curve values on synthetic data logistic regression prediction models versus real data models. Results The utility metric best able to rank SDG methods was the multivariate Hellinger distance based on a Gaussian copula representation of real and synthetic joint distributions. Conclusions This study has validated a generative model utility metric, the multivariate Hellinger distance, which can be used to reliably rank competing SDG methods on the same data set. The Hellinger distance metric can be used to evaluate and compare alternate SDG methods.
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32

Batista, Acsa Santos, Thinara de Freitas Oliveira, Ivan de Oliveira Pereira, and Leandro Soares Santos. "Identification of cocoa bean quality by near infrared spectroscopy and multivariate modeling." Research, Society and Development 10, no. 15 (November 20, 2021): e641101522732. http://dx.doi.org/10.33448/rsd-v10i15.22732.

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Cocoa is a commodity responsible for the income of millions of people and the manufacture of several important products for the food, pharmaceutical, and cosmetic industries. Its quality is associated with several factors involved in the processing steps, mainly in fermentation and drying. The objective of this study was to evaluate the application of near-infrared spectroscopic data associated with multivariate analysis to classify cocoa beans according to their quality and predict attributes such as pH and total acidity by PLS-DA and PLS, respectively. The pH values (4.4-6.7) and total acidity (6.12-29.9) were determined by conventional methods. The PLS-DA proved to be effective in differentiating the classes of cocoa samples with superior and inferior quality, presenting in the validation 100% and 71.43% correct cocoa bean classification with inferior Quality and Higher Quality, respectively. The models obtained by PLS presented satisfactory parameters, being classified as having moderate practical utility and excellent predictive capacity for pH and moderate practical utility and reasonable predictive capacity for total acidity. Thus, the potential of the NIRS technology associated with chemometrics was found and showed efficiency in the classification and prediction of attributes in cocoa beans.
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33

Lestander, Torbjörn A., Magnus Rudolfsson, Linda Pommer, and Anders Nordin. "NIR provides excellent predictions of properties of biocoal from torrefaction and pyrolysis of biomass." Green Chem. 16, no. 12 (2014): 4906–13. http://dx.doi.org/10.1039/c3gc42479k.

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NIR spectrometry combined with multivariate calibration modeling has potential utility as a standardized method for rapidly characterising thermotreated biomass predictions with respect of its energy, carbon, oxygen, hydrogen, ash, volatile matter and fixed carbon contents.
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34

NIN, JORDI, JAVIER HERRANZ, and VICENÇ TORRA. "HOW TO GROUP ATTRIBUTES IN MULTIVARIATE MICROAGGREGATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 16, supp01 (April 2008): 121–38. http://dx.doi.org/10.1142/s0218488508005285.

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Microaggregation is one of the most employed microdata protection methods. It builds clusters of at least k original records, and then replaces these records with the centroid of the cluster. When the number of attributes of the dataset is large, one usually splits the dataset into smaller blocks of attributes, and then applies microaggregation to each block, successively and independently. In this way, the effect of the noise introduced by microaggregation is reduced, at the cost of losing the k-anonymity property.In this work we show that, besides the specific microaggregation method, the value of the parameter k and the number of blocks in which the dataset is split, there exists another factor which influences the quality of the microaggregation: the way in which the attributes are grouped to form the blocks. When correlated attributes are grouped in the same block, the statistical utility of the protected dataset is higher. In contrast, when correlated attributes are dispersed into different blocks, the achieved anonymity is higher, and so, the disclosure risk is lower. We present quantitative evaluations of such statements based on different experiments on real datasets.
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35

Flynn, David M., and Esther Solomon. "Organizational Commitment: A Multivariate Test within the Banking Industry." Psychological Reports 57, no. 1 (August 1985): 119–30. http://dx.doi.org/10.2466/pr0.1985.57.1.119.

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The concept of organizational commitment as an important contributor to behavior in organizations has been increasingly researched. This study seeks to distinguish the significant antecedents of organizational commitment within the banking industry. Analysis of data from the sample of 118 bank vice presidents of 713 contacted suggest a reduced set of antecedent variables. Specifically, personal characteristics, job characteristics, and perceived work experiences significantly contributed to the organizational commitment construct. These results support previously proposed multivariate models. However, the model proposed here may provide a more effective basis for organizational design and research as a reduced model, including seven antecedent variables. The analyses introduced from cross-cultural research a measure of uncertainty of validity within a single culture. Its utility for cross-cultural work is further enriched. Replication is needed.
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Horała, Agnieszka, Agata Swiatly, Jakub Lorek, Zenon J. Kokot, Jan Matysiak, and Ewa Nowak-Markwitz. "Assessment of diagnostic utility of multivariate diagnostic models in differential diagnosis of ovarian tumors." Ginekologia Polska 89, no. 10 (October 31, 2018): 568–72. http://dx.doi.org/10.5603/gp.a2018.0097.

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37

Reghunath, R. "The utility of multivariate statistical techniques in hydrogeochemical studies: an example from Karnataka, India." Water Research 36, no. 10 (May 2002): 2437–42. http://dx.doi.org/10.1016/s0043-1354(01)00490-0.

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38

Fernández, Inés Álvarez, and Gonzalo Nieto Feliner. "A multivariate approach to assess the taxonomic utility of morphometric characters inDoronicum (Asteraceae, Senecioneae)." Folia Geobotanica 36, no. 4 (December 2001): 423–44. http://dx.doi.org/10.1007/bf02899989.

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39

Miyake, Makito, Steve Goodison, Myron Chang, Yunfeng Dai, Virginia Urquidi, and Charles Joel Rosser. "A multi-analyte assay for the noninvasive detection of bladder cancer." Journal of Clinical Oncology 31, no. 6_suppl (February 20, 2013): 306. http://dx.doi.org/10.1200/jco.2013.31.6_suppl.306.

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306 Background: Accurate urinary assays for bladder cancer (BCa) detection would benefit both patients and healthcare systems. Through genomic and proteomic profiling of urine components, we have previously identified a panel of biomarkers that can outperform current urine-based biomarkers for the non-invasive detection of BCa. Herein, we report the diagnostic utility of various multivariate combinations of these biomarkers. Methods: We performed a case-controlled validation study in which voided urines from 550 patients (220 tumor bearing subjects) were analyzed. The urinary concentrations of 14 biomarkers (IL-8, MMP-9,MMP-10, SDC1,CCL18, PAI-1, CD44, VEGF, ANG, CA9,A1AT, OPN, PTX3, and APOE) were assessed by enzyme-linked immunosorbent assay (ELISA). Diagnostic performance of each biomarker and multivariate models were compared using receiver operating characteristic curves and the chi-square test. Results: An 3-biomarker model (CA9, PAI-1 and IL-8) achieved the most accurate BCa diagnosis (sensitivity 90%, specificity 88%). These data show that a multivariate urine-based assay can markedly improve the accuracy of non-invasive BCa detection. Conclusions: Further validation studies are under way to investigate the clinical utility of this panel of biomarkers for BCa diagnosis and disease monitoring.
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Soo Yi, Ji, Rachel Melton, John Stasko, and Julie A. Jacko. "Dust & Magnet: Multivariate Information Visualization Using a Magnet Metaphor." Information Visualization 4, no. 4 (June 23, 2005): 239–56. http://dx.doi.org/10.1057/palgrave.ivs.9500099.

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The use of multivariate information visualization techniques is intrinsically difficult because the multidimensional nature of data cannot be effectively presented and understood on real-world displays, which have limited dimensionalities. However, the necessity to use these techniques in daily life is increasing as the amount and complexity of data grows explosively in the information age. Thus, multivariate information visualization techniques that are easier to understand and more accessible are needed for the general population. In order to meet this need, the present paper proposes Dust & Magnet, a multivariate information visualization technique using a magnet metaphor and various interactive techniques. The intuitive magnet metaphor and subsequent interactions facilitate the ease of learning this multivariate information visualization technique. A visualization tool such as Dust & Magnet has the potential to increase the acceptance of and utility for multivariate information by a broader population of users who are not necessarily knowledgeable about multivariate information visualization techniques.
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Yao, Christopher, Alyssa Kahane, Eric Monteiro, Fred Gentili, Gelareh Zadeh, and John de Almeida. "Preferences and Utilities for Health States after Treatment of Olfactory Groove Meningioma: Endoscopic versus Open." Journal of Neurological Surgery Part B: Skull Base 78, no. 04 (February 17, 2017): 315–23. http://dx.doi.org/10.1055/s-0037-1598197.

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Objectives The purpose of this study is to report health utility scores for patients with olfactory groove meningiomas (OGM) treated with either the standard transcranial approach, or the expanded endonasal endoscopic approach. Design The time trade-off technique was used to derive health utility scores. Setting Healthy individuals without skull base tumors were surveyed. Main Outcome Measures Participants reviewed and rated scenarios describing treatment (endoscopic, open, stereotactic radiation, watchful waiting), remission, recurrence, and complications associated with the management of OGMs. Results There were 51 participants. The endoscopic approach was associated with higher utility scores compared with an open craniotomy approach (0.88 vs. 0.74; p < 0.001) and watchful waiting (0.88 vs.0.74; p = 0.002). If recurrence occurred, revision endoscopic resection continued to have a higher utility score compared with revision open craniotomy (0.68; p = 0.008). On multivariate analysis, older individuals were more likely to opt for watchful waiting (p = 0.001), whereas participants from higher income brackets were more likely to rate stereotactic radiosurgery with higher utility scores (p = 0.017). Conclusion The endoscopic approach was associated with higher utility scores than craniotomy for primary and revision cases. The present utilities can be used for future cost-utility analyses.
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Forsell, Camilla, Stefan Seipel, and Mats Lind. "Surface Glyphs for Efficient Visualization of Spatial Multivariate Data." Information Visualization 5, no. 2 (May 25, 2006): 112–24. http://dx.doi.org/10.1057/palgrave.ivs.9500119.

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We present a first effort to evaluate the possible utility of a new type of surface glyphs intended for visualizations of multivariate spatial data. The glyphs are based on results from vision research suggesting that our perception of metric 3D structure is distorted and imprecise relative to the actual scene before us; only a class of qualitative properties of the scene is perceived with accuracy. These properties are best characterized as being invariant over affine but not Euclidean transformations. A large number of possible 3D glyphs for the visualization of spatial data can be constructed using such properties. One group of such glyphs is based on the local sign of surface curvature. We investigated this group in two visualization experiments. The results show that available sources of 3D structural information were sufficient for our subjects to make fast and accurate judgments. Some implications for visualization are also discussed.
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KLEBANOV, LEV, GALINA GLAZKO, PETER SALZMAN, ANDREI YAKOVLEV, and YUANHUI XIAO. "A MULTIVARIATE EXTENSION OF THE GENE SET ENRICHMENT ANALYSIS." Journal of Bioinformatics and Computational Biology 05, no. 05 (October 2007): 1139–53. http://dx.doi.org/10.1142/s0219720007003041.

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A test-statistic typically employed in the gene set enrichment analysis (GSEA) prevents this method from being genuinely multivariate. In particular, this statistic is insensitive to changes in the correlation structure of the gene sets of interest. The present paper considers the utility of an alternative test-statistic in designing the confirmatory component of the GSEA. This statistic is based on a pertinent distance between joint distributions of expression levels of genes included in the set of interest. The null distribution of the proposed test-statistic, known as the multivariate N-statistic, is obtained by permuting group labels. Our simulation studies and analysis of biological data confirm the conjecture that the N-statistic is a much better choice for multivariate significance testing within the framework of the GSEA. We also discuss some other aspects of the GSEA paradigm and suggest new avenues for future research.
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44

Shah, Nauman, and Stephen J. Roberts. "Dynamically Measuring Statistical Dependencies in Multivariate Financial Time Series Using Independent Component Analysis." ISRN Signal Processing 2013 (June 2, 2013): 1–14. http://dx.doi.org/10.1155/2013/434832.

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We present a computationally tractable approach to dynamically measure statistical dependencies in multivariate non-Gaussian signals. The approach makes use of extensions of independent component analysis to calculate information coupling, as a proxy measure for mutual information, between multiple signals and can be used to estimate uncertainty associated with the information coupling measure in a straightforward way. We empirically validate relative accuracy of the information coupling measure using a set of synthetic data examples and showcase practical utility of using the measure when analysing multivariate financial time series.
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Pitcher, Austin, Christopher Langhammer, and Brian T. Feeley. "Utility of MRI in the Evaluation of Acute Greater Tuberosity Proximal Humeral Fractures." Orthopaedic Journal of Sports Medicine 7, no. 6 (June 1, 2019): 232596711985147. http://dx.doi.org/10.1177/2325967119851472.

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Background: Understanding soft tissue injury patterns associated with greater tuberosity (GT) fractures may help clinicians provide guidance to patients. Hypothesis: Evaluating magnetic resonance imaging (MRI) findings in patients with suspected isolated GT fractures will help elucidate the role of MRI in the diagnosis and treatment of these patients. Study Design: Case series; Level of evidence, 4. Methods: We performed a retrospective review of medical records from 2010 to 2014 for patients presenting with acute isolated GT fractures and MRI. Uncomplicated and delayed recovery groups were established according to the need for delayed procedural intervention or persistent symptoms past last recorded follow-up. Multivariate regression analysis was used to analyze the relationships between MRI findings and delayed recovery. Results: A total of 32 patients met the inclusion criteria (mean age, 47 years [range, 24-88 years]; mean follow-up, 30 weeks [range, 33 days–4 years]). There was no significant difference in the estimation of fracture displacement as measured on radiography and compared with MRI (radiography, 2.8 mm; MRI, 3.5 mm; P = .16). There was a high incidence of full-thickness rotator cuff tears (9%), partial-thickness rotator cuff tears (72%), partial biceps tendon tears (41%), and labral tears (50%). Presence of biceps pathology or partial-thickness rotator cuff tear was predictive of delayed recovery in a multivariate model. Conclusion: There is a high incidence of soft tissue injury found by MRI following GT fracture. MRI did not appreciably change the measure of displacement of the fracture fragment. In the multivariate analysis, presence of a partial-thickness rotator cuff tear or biceps tendon injury was associated with delayed recovery.
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S., Sreedharan, Poornima G.R., Meena Nair, Genanew Bekele Worku, Wathiq Mansoor, and Ananth Rao. "Predicting Users’ Responses of Public Utility Services - Multivariate and Neural Network Analysis - A Case Study." International Review of Advances in Business, Management and Law 1, no. 1 (April 8, 2018): 13–33. http://dx.doi.org/10.30585/irabml.v1i1.53.

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This research addresses the problem of predicting the user’s responses through multivariate choice (MVC) and neural network (NN) frameworks for predicting quality, quantity and overall User satisfaction of public water supply organization, BWSSB (Bangalore Water Supply and Sewerage Board) in Bangalore - India for policy initiatives. The MVC study identifies statistically significant factors that explain users’ loyalty to express satisfaction and voice to express dissatisfaction. The MVC model correctly predicts 85% of satisfied customers across satisfaction dimensions. Wald test on 1940 responses confirms that there exits cross equation correlation across quality, quantity and overall Users’ satisfaction dimensions and thus appropriateness of MVC framework over traditional logit for predicting the user responses. NN framework outperforms the econometric model with 94% correct classification of user responses. The study opens up potential research opportunities for applying the advanced analytical frameworks for predicting user responses in various public and private settings for Policy initiatives so that the service providers could improve their service delivery.
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Eskander, Ramez N., Brian A. Carpenter, Howard G. Wu, and Judith K. Wolf. "The clinical utility of an elevated-risk multivariate index assay score in ovarian cancer patients." Current Medical Research and Opinion 32, no. 6 (April 20, 2016): 1161–65. http://dx.doi.org/10.1080/03007995.2016.1176014.

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Bennani, Kawtar, Imane Thami Alami, Najib Bendaou, Nezha Saidi, Fatima Gaboun, and Chawki Al Faiz. "Conservation and multivariate analysis utility in characterization of ecogegraphical relationships of Trifolium and Lotus species." African Journal of Ecology 49, no. 1 (February 8, 2011): 1–9. http://dx.doi.org/10.1111/j.1365-2028.2010.01220.x.

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Currie, Craig J., Christopher Ll Morgan, Chris D. Poole, Peter Sharplin, Morten Lammert, and Phil McEwan. "Multivariate models of health-related utility and the fear of hypoglycaemia in people with diabetes." Current Medical Research and Opinion 22, no. 8 (June 28, 2006): 1523–34. http://dx.doi.org/10.1185/030079906x115757.

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Fujihara, Yuki, Hideyuki Ota, and Kentaro Watanabe. "Utility of early active motion for flexor tendon repair with concomitant injuries: A multivariate analysis." Injury 49, no. 12 (December 2018): 2248–51. http://dx.doi.org/10.1016/j.injury.2018.10.022.

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