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Journal articles on the topic 'Extended multivariate analysis'

Author: Grafiati

Published: 9 October 2021

Last updated: 18 July 2025

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1

Ohlhausen, JA. "Advanced Multivariate Analysis Tools Applied to Surface Analysis." Microscopy and Microanalysis 16, S2 (2010): 382–83. http://dx.doi.org/10.1017/s1431927610055558.

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Keenan, Michael R., and Paul G. Kotula. "Multivariate Statistical Analysis of EEL-Spectral Images." Microscopy and Microanalysis 10, S02 (2004): 874–75. http://dx.doi.org/10.1017/s1431927604880620.

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3

Lavine, Barry K., Charles E. Davidson, Jason Ritter, David J. Westover, and Thomas Hancewicz. "Varimax extended rotation applied to multivariate spectroscopic image analysis." Microchemical Journal 76, no. 1-2 (2004): 173–80. http://dx.doi.org/10.1016/s0026-265x(03)00159-0.

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Keenan, MR, VS Smentkowski, RM Ulfig, E. Oltman, DJ Larson, and TF Kelly. "Multivariate Statistical Analysis of Atom Probe Tomography Data." Microscopy and Microanalysis 16, S2 (2010): 270–71. http://dx.doi.org/10.1017/s143192761005436x.

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Parish, C., C. Capdevila, and MK Miller. "Applying Multivariate Statistical Analysis to Atom Probe Tomography." Microscopy and Microanalysis 16, S2 (2010): 1858–59. http://dx.doi.org/10.1017/s1431927610056205.

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Van Benthem, M., P. Kotula, and P. Lu. "Multivariate Statistical Analysis Strategies of EELS Spectral Images." Microscopy and Microanalysis 17, S2 (2011): 784–85. http://dx.doi.org/10.1017/s143192761100479x.

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7

Sarahan, M., F. de la Peña, Q. Ramasse, and M. Walls. "Novel Multivariate Statistical Analysis Methods for STEM/EELS." Microscopy and Microanalysis 17, S2 (2011): 1306–7. http://dx.doi.org/10.1017/s1431927611007409.

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8

Hakim, H. A. Nazmul, ANM Nure Azam, Md Tuhin Talukder, et al. "Independent Predictors of Extended Hospitalization Following Cholecystectomy: A Multivariate Analysis." Scholars Journal of Applied Medical Sciences 12, no. 12 (2024): 1742–46. https://doi.org/10.36347/sjams.2024.v12i12.008.

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Introduction: Cholecystectomy, the surgical removal of the gallbladder, is one of the most commonly performed surgical procedures worldwide, particularly in patients with symptomatic cholelithiasis and cholecystitis. This study aimed to assess the independent predictors of extended hospitalization following cholecystectomy. Methods: This prospective observational study was conducted at the various surgical units of the inpatient Department of Surgery, Dhaka Medical College Hospital, Dhaka, from July 2018 to June 2019. Patients with cholecystitis attending in the outdoor or emergency, admitted with cholecystitis in Dhaka Medical College Hospital, Dhaka were considered as the study population. A total of 50 patients were selected as study subjects by purposive sampling technique. Statistical Package for Social Science (SPSS) version 21 for Windows was used to analyze the data. A p-value < 0.05 was considered to be significant. Result: The median length of stay (LOS) was 5.0 days (range: 1–21 days), with the 80th percentile at 6 days. Patients were classified into two groups: control (LOS <6 days) and prolonged LOS (≥6 days). Univariate analysis revealed that factors such as patient age (p <0.002), male gender (p =0.026), preoperative leukocyte count (p =0.002), preoperative NLR (p <0.002), and admission through the ED (p <0.002) were linked to prolonged LOS. Multivariate analysis identified three independent predictors of prolonged LOS: age ≥50 years (OR 2.212, 95% CI 1.372 – 3.530, p <0.002), preoperative NLR ≥3.0 (OR 1.776, 95% CI 1.146–2.725, p =0.004), and admission via the ED (OR 1.664, 95% CI 1.070–2.560, p =0.008). Conclusion: This study identifies key independent predictors of extended hospitalization (≥6 days) following cholecystectomy, highlighting the roles of advanced age (≥50 years), elevated neutrophil-lymphocyte ratio (NLR ≥3), and admission through the emergency department (ED). Through multivariate analysis, these factors were shown ...

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Kotula, P. G., та M. A. Rodriguez. "Multivariate Statistical Analysis Strategies of μ-XRF Spectral Images". Microscopy and Microanalysis 18, S2 (2012): 948–49. http://dx.doi.org/10.1017/s1431927612006599.

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10

Artyushkova, K., S. Pylypenko, J. Fenton, K. Archuleta, L. Williams, and J. Fulghum. "Multi-technique, Multivariate Analysis Methods for Enhanced Sample Characterization." Microscopy and Microanalysis 12, S02 (2006): 1402–3. http://dx.doi.org/10.1017/s1431927606069492.

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Fulghum, JE, and K. Artyushkova. "Multivariate Analysis of XPS Data for Enhanced Chemical Information." Microscopy and Microanalysis 14, S2 (2008): 776–77. http://dx.doi.org/10.1017/s1431927608088922.

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12

Wise, BM. "An Overview of Chemometric Methods for Analysis of Multivariate Images." Microscopy and Microanalysis 16, S2 (2010): 374–75. http://dx.doi.org/10.1017/s1431927610063130.

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Parish, C., P. Edmondson, and M. Miller. "Multivariate Statistical Analysis of STEM-EDS at the Noise Floor." Microscopy and Microanalysis 17, S2 (2011): 594–95. http://dx.doi.org/10.1017/s1431927611003849.

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Sugar, J., and P. Kotula. "Imaging Li Using EFTEM Spectrum Imaging and Multivariate Statistical Analysis." Microscopy and Microanalysis 17, S2 (2011): 1588–89. http://dx.doi.org/10.1017/s1431927611008816.

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15

Towhidi, M., and J. Behboodian. "Bayesian multivariate normal analysis under the extended reflected normal loss function." Statistics 35, no. 3 (2001): 215–23. http://dx.doi.org/10.1080/02331880108802732.

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16

Pedersen, F., E. Bengtsson, and B. Nordin. "An extended strategy for exploratory multivariate image analysis including noise considerations." Journal of Chemometrics 9, no. 5 (1995): 389–409. http://dx.doi.org/10.1002/cem.1180090506.

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17

Sunanta, Owat. "Generalized Point Estimators for Fuzzy Multivariate Data." Austrian Journal of Statistics 47, no. 1 (2018): 33–44. http://dx.doi.org/10.17713/ajs.v47i1.391.

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Data analysis methods are necessary tools in evaluating and better understanding the information of interest. However, there are limitations in applying standard statistical methods to specific data analyses. The data obtained from different sources are often clouded by imprecision and uncertainty. To overcome this problem, data analysis methods have to be generalized to capture the data uncertainty through statististical methods for fuzzy data. The existing methods are based on the extension principle or require other generalized procedures, such as the calculation of statistics, the extimation of parameters, and the construction of fuzzy confidence regions. The development of these methods to evaluate univariate data has been flourished. However, to solve complex real-world problems, these methods have to be extended and generalized to handle multivariate fuzzy data. In this research, the methods of generalized point estimators, i.e. sample mean, variance-covariance, and correlation coefficient, are extended for the multivariate case through concepts of fuzzy vector and combined fuzzy sample.

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Kotula, Paul G., Michael R. Keenan, Joseph R. Michael, and Paul Carpenter. "Spectral Imaging and Automated Multivariate Statistical Analysis of the Ourique Meteorite." Microscopy and Microanalysis 10, S02 (2004): 892–93. http://dx.doi.org/10.1017/s1431927604880590.

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Edwards, PR, RW Martin, and MR Lee. "Multivariate Statistical Analysis of Combined Hyperspectral Cathodoluminescence and X-Ray Datasets." Microscopy and Microanalysis 12, S02 (2006): 1522–23. http://dx.doi.org/10.1017/s1431927606066682.

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Sehdev, Amikar, Donna Niedzwiecki, Alan P. Venook, et al. "Association of RAS mutations with race in metastatic colorectal cancer: CALGB/SWOG 80405 (ALLIANCE)." Journal of Clinical Oncology 36, no. 4_suppl (2018): 638. http://dx.doi.org/10.1200/jco.2018.36.4_suppl.638.

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638 Background: Colorectal cancer (CRC) is a heterogeneous disease with distinct molecular subtypes in part based on RAS mutational status. It is plausible that RAS mutations are differentially distributed between CC and AA and may contribute to poor outcomes in AAs with CRC. Methods: We did a retrospective analysis of CALGB/SWOG 80405 trial patients. We divided the entire cohort into 2 groups: a) Common RAS: mutation in KRAS exon 2, codon 12 or 13; b) Extended RAS: any NRAS mutations or mutation in KRAS except those listed above. We then analyzed these two subgroups for association between RAS mutations and race (3 categories: Caucasian, AA, Others) using chi-square test for univariate analyses and logistic regression for multivariate analysis. We also analyzed the effect of extended RAS testing on prognosis of metastatic CRC by estimating the overall survival (OS) using Kaplan-Meier method and 95% confidence interval (CI). Cox proportional-hazard model was used for multivariate analyses. Results: There were 1729 CRC patients in common RAS group of which 357 (20.6%) had mutations present. Extended RAS group had 621 patients of which 95 (15.5%) had mutations present. There was no significant difference in the rate of common RAS mutations between CC and AA (20.5% vs. 24%, p=0.22). However, extended RAS mutations were significantly more in AA as compared to CC (25% vs. 14%, p=0.02). Multivariate analysis adjusted for age, gender, prior adjuvant chemotherapy and pelvic radiation confirmed higher odds of extended RAS mutation in AA compared to CC (adjusted OR 1.12; 95% CI 1.01-1.23; p=0.02). The median OS in patients with an extended RAS mutation was shorter as compared to those without extended RAS mutation (25.3 vs. 31.9 months; HR 1.26; 95% CI 0.99-1.62; p=0.05). Multivariate analyses adjusted for age, gender, race, prior adjuvant chemotherapy and pelvic radiation showed a trend towards longer OS in patients without extended RAS mutation as compared those with extended RAS mutation (adjusted HR= 1.24, 95% CI, 0.97-0.1.58, p=0.08). Conclusions: Extended RAS mutations are significantly more common in AA as compared to CC. Additionally, presence of extended RAS mutation may confer a poor prognosis in CRC patients.

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21

Mathai, Arak M. "An Extended Zeta Function with Applications in Model Building and Bayesian Analysis." Mathematics 11, no. 19 (2023): 4076. http://dx.doi.org/10.3390/math11194076.

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In certain problems in model building and Bayesian analysis, the results end up in forms connected with generalized zeta functions. This necessitates the introduction of an extended form of the generalized zeta function. Such an extended form of the zeta function is introduced in this paper. In model building situations and in various types of applications in physical, biological and social sciences and engineering, a basic model taken is the Gaussian model in the univariate, multivariate and matrix-variate situations. A real scalar variable logistic model behaves like a Gaussian model but with a thicker tail. Hence, for many of industrial applications, a logistic model is preferred to a Gaussian model. When we study the properties of a logistic model in the multivariate and matrix-variate cases, in the real and complex domains, invariably the problem ends up in the extended zeta function defined in this paper. Several such extended logistic models are considered. It is also found that certain Bayesian considerations also end up in the extended zeta function introduced in this paper. Several such Bayesian models in the multivariate and matrix-variate cases in the real and complex domains are discussed. It is stated in a recent paper that “Quantum Mechanics is just the Bayesian theory generalized to the complex Hilbert space”. Hence, the models developed in this paper are expected to have applications in quantum mechanics, communication theory, physics, statistics and related areas.

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22

Kotula, Paul G., Michael R. Keenan, Richard P. Grant, and Paul F. Hlava. "Multivariate Statistical Analysis of Wavelength and Energy-Dispersive X-ray Spectral Images." Microscopy and Microanalysis 10, S02 (2004): 118–19. http://dx.doi.org/10.1017/s1431927604880607.

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23

Watanabe, M. "Practical Processing of Spectrum Images by Multivariate Statistical Analysis: Advantages and Disadvantages." Microscopy and Microanalysis 19, S2 (2013): 2028–29. http://dx.doi.org/10.1017/s1431927613012130.

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24

Qi, Feng, Da-Wei Niu, Dongkyu Lim, and Bai-Ni Guo. "Some logarithmically completely monotonic functions and inequalities for multinomial coefficients and multivariate beta functions." Applicable Analysis and Discrete Mathematics, no. 00 (2020): 33. http://dx.doi.org/10.2298/aadm191111033q.

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In the paper, the authors extend a function arising from the Bernoulli trials in probability and involving the gamma function to its largest ranges, find logarithmically complete monotonicity of these extended functions, and, in light of logarithmically complete monotonicity of these extended functions, derive some inequalities for multinomial coefficients and multivariate beta functions. These results recover, extend, and generalize some known conclusions.

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25

Azen, Razia, and David V. Budescu. "Comparing Predictors in Multivariate Regression Models: An Extension of Dominance Analysis." Journal of Educational and Behavioral Statistics 31, no. 2 (2006): 157–80. http://dx.doi.org/10.3102/10769986031002157.

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Dominance analysis (DA) is a method used to compare the relative importance of predictors in multiple regression. DA determines the dominance of one predictor over another by comparing their additional R2 contributions across all subset models. In this article DA is extended to multivariate models by identifying a minimal set of criteria for an appropriate generalization of R2 to the case of multiple response variables. The DA results obtained by univariate regression (with each criterion separately) are analytically compared with results obtained by multivariate DA and illustrated with an example. It is shown that univariate dominance does not necessarily imply multivariate dominance (and vice versa), and it is recommended that researchers who wish to account for the correlation among the response variables use multivariate DA to determine the relative importance of predictors.

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El-Ragehy, Nariman A., Ali M. Yehia, Nagiba Y. Hassan, Mahmoud A. Tantawy, and Mohamed Abdelkawy. "Chemometrics Tools in Detection and Quantitation of the Main Impurities Present in Aspirin/Dipyridamole Extended-Release Capsules." Journal of AOAC INTERNATIONAL 99, no. 4 (2016): 948–56. http://dx.doi.org/10.5740/jaoacint.16-0082.

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Abstract Aspirin (ASP) and dipyridamole (DIP) in combination is widely used in the prevention of secondary events after stroke and transient ischemic attack. Salicylic acid is a well-known impurity of ASP, and the DIP extended-release formulation may contain ester impurities originating from the reaction with tartaric acid. UV spectral data analysis of the active ingredients in the presence of their main impurities is presented using multivariate approaches. Four chemometric-assisted spectrophotometric methods, namely, partial least-squares, concentration residuals augmented classical least-squares (CRACLS), multivariate curve resolution (MCR) alternating least-squares (ALS), and artificial neural networks, were developed and validated. The quantitative analyses of all the proposed calibrations were compared by percentage recoveries, root mean square error of prediction, and standard error of prediction. In addition, r2 values between the pure and estimated spectral profiles were used to evaluate the qualitative analysis of CRACLS and MCR-ALS. The lowest error was obtained by the CRACLS model, whereas the best correlation was achieved using MCR-ALS. The four multivariate calibration methods could successfully be applied for the extended-release formulation analysis. The application results were also validated by analysis of the stored dosage-form solution, which showed a susceptibility of DIP esterification in the extended-release formulation. Statistical comparison between the proposed and official methods showed no significant difference.

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Smentkowski, V., and M. Keenan. "A Complete Characterization of Samples Using Multivariate Statistical Analysis of 3Dimensional MCs+ ToF-SIMS Data." Microscopy and Microanalysis 17, S2 (2011): 1462–63. http://dx.doi.org/10.1017/s143192761100818x.

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28

Nagar, Daya K., Raúl Alejandro Morán-Vásquez, and Arjun K. Gupta. "Extended Matrix Variate Hypergeometric Functions and Matrix Variate Distributions." International Journal of Mathematics and Mathematical Sciences 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/190723.

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Hypergeometric functions of matrix arguments occur frequently in multivariate statistical analysis. In this paper, we define and study extended forms of Gauss and confluent hypergeometric functions of matrix arguments and show that they occur naturally in statistical distribution theory.

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Gottfries, J., J. Ahlbom, V. Harang, et al. "Validation of an extended release tablet dissolution testing system using design and multivariate analysis." International Journal of Pharmaceutics 106, no. 2 (1994): 141–48. http://dx.doi.org/10.1016/0378-5173(94)90312-3.

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Müller, Rasmus, Stefan Larsson, and Johan Spross. "Multivariate stability assessment during staged construction." Canadian Geotechnical Journal 53, no. 4 (2016): 603–18. http://dx.doi.org/10.1139/cgj-2015-0037.

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For staging the construction of embankments on soft clay, an important aspect in deterministic or probabilistic stability analyses is the assessment of the representative average values and associated uncertainties for the undrained shear strength as the height of the embankment is sequentially increased. Assessments made prior to construction can be verified by performing observations during the construction phase. All relevant available information should be incorporated into an analysis to increase the level of confidence and the objectivity of the assessment. To this end, we apply an extended multivariate approach to assess the undrained shear strength using different indirect measurement methods during the staged construction of the Veda embankment (Sweden). This multivariate approach implies that uncertainties associated with the assessments are reduced, and objectively weighted averages are obtained. The resulting implications on the calculated deterministic safety factors and the probabilistically retrieved reliability indices of the embankment are thoroughly discussed in this work.

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Sasongko, S. B., K. A. Ibrahim, and A. Ahmad. "Fault Analysis Of Process System Using Multi Block Principal Component Analysis." REAKTOR 7, no. 02 (2017): 61. http://dx.doi.org/10.14710/reaktor.7.02.61-65.

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This research looks into the issues of the quality improvement based on process control instead of product control using multivariate statistical process contro. A deterministic model of a proton exchange membrane fuel cell (PEM-FC) power plant was used as a case study to represent a multi variable or mukti equipment system. A three-step approach is proposed which can be classified into fault detection, fault isolation, and faulr diagnosis. The fault detection and the isolation utilize the multivariate analysis and yhe contro chart method , which uses the series multi-block principal component analysis of extended of PCA method. The series block principal component abalysis is solved using the non linear iteration partial least squares (NIPALS) algorithm. The SB-PCA can advangeouly incorporate the control chart, namely, T2 Hotelling control chart. In the fault diagnosis chart, the normalized variable method was successfully applied in this study with promising results. As a conclution, the result of this study demonstrated the potentials of multivariate statistical process control in solving fault detection and diagnosis problem for multi variable and multi equipment system.Keywords : statistical process control, principal component, fault analysis

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32

Boomsma, D. I., and P. C. M. Molenaar. "Constrained Maximum Likelihood Analysis of Familial Resemblance of Twins and Their Parents." Acta geneticae medicae et gemellologiae: twin research 36, no. 1 (1987): 29–39. http://dx.doi.org/10.1017/s0001566000004566.

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AbstractWhen the univariate twin design is extended by including parents of twins, it is possible to assess additive genetic effects in the presence of assortative mating and genotype-environment correlation, the effects of parental influence, as well as the extent of residual shared environmental influences. The analysis of data obtained in such an extended twin design can be carried out by means of constrained maximum likelihood confirmatory factor analysis. Specifically, the structural model underlying this design can be represented as a LISREL model with nonlinear constraints. This representation offers the possibility to consider extended multivariate twin designs involving common genetic and environmental factors. The proposed method will be illustrated with applications to simulated and real data.

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Keenan, M., V. Smentkowski, R. Ulfig, E. Oltman, D. Larson, and T. Kelly. "Phase Composition at the Atomic-Size Scale through Multivariate Statistical Analysis of Atom Probe Tomography Data." Microscopy and Microanalysis 17, S2 (2011): 720–21. http://dx.doi.org/10.1017/s1431927611004478.

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Hengartner, Astrid, Sumaiya Sayeed, Paul Serrato, et al. "296 Associated Risk Factors for Extended Length of Stay following Pediatric Tethered Cord Release: An Analysis of 2012 – 2021 NSQIP-Pediatric Database." Neurosurgery 71, Supplement_1 (2025): 73. https://doi.org/10.1227/neu.0000000000003360_296.

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INTRODUCTION: The factors associated with prolonged hospitalization following surgical release of tethered spinal cord in pediatric patients are relatively unknown. METHODS: A retrospective cohort study was performed using the 2012-2021 ACS NSQIP-Pediatric database. Patients undergoing laminectomy with release of a tethered spinal cord were identified using CPT and ICD-9/10 codes. Patients were dichotomized into two cohorts based on whether they experienced an extended postoperative hospital LOS, defined as a LOS greater than the 75th percentile for the entire cohort (3 days). Patient demographics, comorbidities, adverse events, and healthcare resource utilization were assessed. Predictors of extended LOS were identified using multivariate logistic regression analysis. RESULTS: Among the 10,196 studied patients undergoing laminectomy with tethered cord release, 2,077 experienced an extended LOS. The extended LOS-cohort was significantly older than the normal LOS cohort (Normal LOS: 5.44 ± 4.70 years vs. Extended LOS: 7.11 ± 5.27, p<0.001) and more frequently Hispanic, Asian, or of “other or unknown” racial identity (p<0.001). Overall, complications, unplanned readmission, and reoperation rates were higher among the extended LOS cohort (p<0.001). On multivariate logistic regression, independent associations of extended LOS included age, race and ethnicity, ASA classification, impaired cognitive status, cardiac risk factors, neuromuscular disorders, and tracheostomies. CONCLUSIONS: Our study reveals that age, race, comorbidities, and perioperative complications contribute to prolonged LOS after surgical release of tethered spinal cord among pediatric patients. Additional investigations to further understand the risk factors of extended LOS are warranted to improve patient outcomes.

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Dolgiy, Aleksandr, and Sergey Kovalev. "Automatic transportation process control systems with an extended data analytics circuit." Transport automation research 10, no. 4 (2024): 337–59. https://doi.org/10.20295/2412-9186-2024-10-04-337-359.

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A new hybrid approach has been proposed to automate the management of complex technological processes at railway stations of industrial transport using intelligent monitoring technologies. This approach is based on the concept of predictive modeling combined with methods of statistical analysis, including a modification of the principal components analysis method for multivariate statistical analysis and the identification of violations in technological processes using a combination of well-known methods such as contribution analysis and fuzzy dynamic analysis. The principal feature of the hybrid approach is mapping the initial space of numerical parameters of the technological process onto a new space formed by fuzzy rules of an evolving system model. Applying multivariate analysis to new system variables using the principal component method allows for the formation of a few intermediate variables with different degrees of granularity and interpretability, describing the behavior of the controlled process, which makes it possible to develop mathematical models and algorithms for solving various monitoring tasks An example of using this approach for post-processing monitoring data to identify performance discrepancies in a marshalling yard and anomalies in the controlled process is considered.

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36

Reza, Widya, Vitri Aprilla Handayani, and Eko Sulistyono. "Analyze breaking palm oil dormancy through chemical processes using multivariate analysis of variance." Jurnal Pijar Mipa 17, no. 3 (2022): 314–18. http://dx.doi.org/10.29303/jpm.v17i3.3449.

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Palm oil is a dormant plant. The main cause of oil palm seed dormancy is the hard and thick seed coat or shell, inhibiting the effective absorption of water and gases. The presence of a seed coat barrier causes the germination process of oil palm seeds to be hampered. This study aims to determine the effect of chemical treatment on breaking palm oil dormancy by immersion in a solution of strong acids, namely H2SO4, KNO3, and HCl. This study used a completely random design (CRD) with three treatments, four observations, and five replications. The results of the following study were analyzed using MANOVA with the parameters observed were germination rate, germination rate, seedling height, and most extended root length. Based on the analysis results, it was found that immersion with a solution of a strong acid, namely H2SO4, KNO3, and HCl, had different effects on breaking palm oil dormancy. The highest average germination rate was through immersion with HCl, which produced an average of 65.24. The highest average germination was through immersion in H2SO4 with an average of 8.52. In contrast, the average seedling height and most extended root length were soaked in HCl with an average of 35.28, and 15, respectively. Based on the results obtained, the best chemical treatment for breaking palm oil dormancy is through soaking with HCl.

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37

Yan, Enshuo, Huachuan Wang, and Weihao Xia. "Temporal Streaming Batch Principal Component Analysis for Time Series Classification (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 28 (2025): 29543–44. https://doi.org/10.1609/aaai.v39i28.35319.

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In multivariate time series classification, although current sequence analysis models have excellent classification capabilities, they show significant shortcomings when dealing with long sequence multivariate data. This paper focuses on optimizing model performance for long-sequence multivariate data by mitigating the impact of extended time series and multiple variables on the model. We propose a principal component analysis (PCA)-based temporal streaming compression and dimensionality reduction algorithm for time series data (temporal streaming batch PCA, TSBPCA), which continuously updates the compact representation of the entire sequence through streaming PCA time estimation with time block updates, enhancing the data representation capability of a range of sequence analysis models.We evaluated this method using various models on five datasets, and the experimental results show that our method demonstrates outstanding performance in both classification accuracy and time efficiency.

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38

Lu, P., LN Brewer, PG Kotula, M. Rodriguez, E. Webb, and J. Hsu. "Electron Diffraction Spectral Imaging and Multivariate Statistical Analysis for Structural Mapping of Amorphous and Nano-crystalline Composites." Microscopy and Microanalysis 16, S2 (2010): 272–73. http://dx.doi.org/10.1017/s1431927610053766.

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39

Hayashida, Shingo, Nobuhiko Nagano, Tamaki Morohashi, et al. "Clinical factors associated with extended hospitalization in pediatric patients ≥3 years of age with respiratory syncytial virus or human metapneumovirus infection: A Japanese single-center, retrospective study." Medicine 102, no. 42 (2023): e35565. http://dx.doi.org/10.1097/md.0000000000035565.

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Respiratory syncytial virus (RSV) and human metapneumovirus (hMPV) infections are common in children worldwide. However, the clinical factors related to extended hospitalization in Japanese patients aged ≥3 years remain elusive. We aimed to elucidate the clinical risk factors contributing to hospital stays ≥7 days in patients with RSV and hMPV infections. Patients ≥3 years of age who were hospitalized due to RSV or hMPV infection between 2014 to 2020 were included. Twenty-one RSV- and 27 hMPV-infected patients were enrolled. Patients were divided into 2 groups: hospitalization for ≥ and <7 days. Univariate and multivariate analyses determined the clinical risk factors contributing to hospital stay ≥7 days. The RSV- and hMPV-infected patients had similar clinical characteristics. The clinical risk factors contributing to extended hospitalization were analyzed in the 48 infected patients of the 2 groups. The presence of prophylactic antibiotics usage, co-bacterial colonization, and underlying diseases were extracted by univariate analysis (P < .05). In multivariate analysis, underlying diseases were determined as an independent clinical risk factor (odds ratio 8.09, P = .005). Underlying diseases contributed to extended hospitalization in RSV- or hMPV-infected patients ≥3 years of age.

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40

Ahmed, M. U., N. Rehman, D. Looney, T. M. Rutkowski, and D. P. Mandic. "Dynamical complexity of human responses: a multivariate data-adaptive framework." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 3 (2012): 433–45. http://dx.doi.org/10.2478/v10175-012-0055-0.

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Abstract Established complexity measures typically operate at a single scale and thus fail to quantify inherent long-range correlations in real-world data, a key feature of complex systems. The recently introduced multiscale entropy (MSE) method has the ability to detect fractal correlations and has been used successfully to assess the complexity of univariate data. However, multivariate observations are common in many real-world scenarios and a simultaneous analysis of their structural complexity is a prerequisite for the understanding of the underlying signal-generating mechanism. For this purpose, based on the notion of multivariate sample entropy, the standard MSE method is extended to the multivariate case, whereby for rigor, the intrinsic multivariate scales of the input data are generated adaptively via the multivariate empirical mode decomposition (MEMD) algorithm. This allows us to gain better understanding of the complexity of the underlying multivariate real-world process, together with more degrees of freedom and physical interpretation in the analysis. Simulations on both synthetic and real-world biological multivariate data sets support the analysis.

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Gomes Gonsalez, Maria Angeles. "A Corpus-based Analysis of Extended Multiple Themes in PresE." International Journal of Corpus Linguistics 3, no. 1 (1998): 81–113. http://dx.doi.org/10.1075/ijcl.3.1.05gom.

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This corpus-based study reformulates Halliday's (1994: 55) notion of Multiple Theme, i.e., textual and/or interpersonal items occurring before a simple Topical Theme (or clause initial transitivity/mood element) (e.g., Well, but then, Ann, surely, wouldn't the best idea be to join the group?) (cf. Berry 1982, 1995; Lautamatti 1978; Young 1980; Vasconcellos 1992). Firstly, the label Extended Multiple Theme is here proposed as a cover-term for Topical Themes co-occurring with pre-topical and/or post-topical textual and/or interpersonal elements. And secondly, Extended Multiple Themes are suggested to: (i) allow for recursiveness within the three functional slots; (ii) tend to abide by Dik's (1989: 342) Principle of Centripetal Organisation; and (iii) substantiate the layering hypothesis posited for example in Dik 's Functional Grammar or in Role and Reference Grammar (cf. Hengeveld 1989; Van Valin Jr. 1993). These claims were deduced from the application of three multivariate statistical tests, namely, the Logistic Regression Technique, the Fisher's Exact Test, and the x2 Test, to the tokens of Extended Multiple Themes found in real Present-day English texts, that is to say, in the Lancaster Spoken English Corpus.

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Lucas, G., P. Burdet, M. Cantoni, and C. Hébert. "Multivariate Statistical Analysis tool for the interpretation and the quantification of hyperspectral data: application to 3D EDX/FIB images." Microscopy and Microanalysis 18, S2 (2012): 1014–15. http://dx.doi.org/10.1017/s1431927612006927.

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Kotula, PG, and JR Michael. "Spectral Imaging and Multivariate Statistical Analysis from Thin Specimens in the SEM with a Four-Channel Silicon Drift Detector." Microscopy and Microanalysis 12, S02 (2006): 1390–91. http://dx.doi.org/10.1017/s1431927606066955.

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Golriz, Mohammad, Omid Ghamarnejad, Elias Khajeh, et al. "Preoperative Thrombocytopenia May Predict Poor Surgical Outcome after Extended Hepatectomy." Canadian Journal of Gastroenterology and Hepatology 2018 (November 1, 2018): 1–11. http://dx.doi.org/10.1155/2018/1275720.

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Background. It is a novel idea that platelet counts may be associated with postoperative outcome following liver surgery. This may help in planning an extended hepatectomy (EH), which is a surgical procedure with high morbidity and mortality. Aim. The aim of this study was to evaluate the predictive potential of platelet counts on the outcome of EH in patients without portal hypertension, splenomegaly, or cirrhosis. Methods. A series of 213 consecutive patients underwent EH (resection of ≥ five liver segments) between 2001 and 2016. The association of preoperative platelet counts with posthepatectomy liver failure (PHLF), morbidity (based on Clavien-Dindo classification), and 30-day mortality was evaluated using multivariate analysis. Results. PHLF was detected in 26.3% of patients, major complications in 26.8%, and 30-day mortality in 11.3% of patients. Multivariate analysis revealed that the preoperative platelet count is an independent predictor of PHLF (odds ratio [OR] 4.4, 95% confidence interval [CI] 1.3–15.0, p=0.020) and 30-day mortality (OR 4.4, 95% CI 1.1–18.8, p=0.043). Conclusions. Preoperative platelet count is associated with PHLF and mortality following extended liver resection. This association was independent of other related parameters. Prospective studies are needed to evaluate the predictive role and to determine the impact of preoperative correction of platelet count on postoperative outcomes after EH.

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Palleschi, A., and V. Palleschi. "An Extended Kalman Filter approach to non-linear multivariate analysis of Laser-Induced Breakdown Spectroscopy spectra." Spectrochimica Acta Part B: Atomic Spectroscopy 149 (November 2018): 271–75. http://dx.doi.org/10.1016/j.sab.2018.09.003.

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Faes, Matthias, and David Moens. "Multivariate dependent interval finite element analysis via convex hull pair constructions and the Extended Transformation Method." Computer Methods in Applied Mechanics and Engineering 347 (April 2019): 85–102. http://dx.doi.org/10.1016/j.cma.2018.12.021.

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Stephen, Aina, Omeje Nkiru, Onoja Joseph, et al. "A multivariate analysis of veterinary preferences for NSAIDs in Nigeria." International Journal of Veterinary Science and Research 8, no. 1 (2022): 034–38. http://dx.doi.org/10.17352/ijvsr.000109.

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Vultures are obligate scavengers known to accomplish incredible ecological feats unmatched by other birds of prey. However, the role of animal health specialists in vulture conservation is under-emphasized in Nigeria, despite vulture’s explicit dependence on the carcasses of domesticated livestock under the regime of veterinary caregivers. In our research, we evaluate the perception of animal health specialists on vultures and the veterinary use of Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) for livestock treatment in the study location. Data collated from a semi-structured questionnaire were analyzed using correspondence analysis to produce a simple visual display of the complex count data matrix. The prevalence of 10 NSAIDs was analyzed along 3 column attributes namely; Not-in-Use (NU), Rarely-Used (RU), and Frequently-Used (FU). The NSAIDs were statistically under the significant influence by the column attributes at 0.05 alpha-level (X2≤64.35;P<0.0000), with the principal axis accounting for 74.33% of the total inertia. Ketoprofen aggregated close to the centroid, while diclofenac and Ibuprofen were strongly associated with FU. Aspirin and Indomethacin inclined significantly towards the NU and RU axes, respectively. Despite the global consensus on the toxic influence of some NSAIDs on the vultures, about 90% of the research respondents were unaware of the hazards toxic NSAIDs are likely to impose on the vultures. Diclofenac has received less than enough focus, despite its extended use for livestock treatment in Nigeria. Future conservation interventions should therefore be designed to involve, engage and educate the veterinary practitioners in Nigeria.

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Msilini, A., P. Masselot, and T. B. M. J. Ouarda. "Regional Frequency Analysis at Ungauged Sites with Multivariate Adaptive Regression Splines." Journal of Hydrometeorology 21, no. 12 (2020): 2777–92. http://dx.doi.org/10.1175/jhm-d-19-0213.1.

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AbstractHydrological systems are naturally complex and nonlinear. A large number of variables, many of which not yet well considered in regional frequency analysis (RFA), have a significant impact on hydrological dynamics and consequently on flood quantile estimates. Despite the increasing number of statistical tools used to estimate flood quantiles at ungauged sites, little attention has been dedicated to the development of new regional estimation (RE) models accounting for both nonlinear links and interactions between hydrological and physio-meteorological variables. The aim of this paper is to simultaneously take into account nonlinearity and interactions between variables by introducing the multivariate adaptive regression splines (MARS) approach in RFA. The predictive performances of MARS are compared with those obtained by one of the most robust RE models: the generalized additive model (GAM). Both approaches are applied to two datasets covering 151 hydrometric stations in the province of Quebec (Canada): a standard dataset (STA) containing commonly used variables and an extended dataset (EXTD) combining STA with additional variables dealing with drainage network characteristics. Results indicate that RE models using MARS with the EXTD outperform slightly RE models using GAM. Thus, MARS seems to allow for a better representation of the hydrological process and an increased predictive power in RFA.

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Lainscsek, Claudia, Manuel E. Hernandez, Howard Poizner, and Terrence J. Sejnowski. "Delay Differential Analysis of Electroencephalographic Data." Neural Computation 27, no. 3 (2015): 615–27. http://dx.doi.org/10.1162/neco_a_00656.

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We propose a time-domain approach to detect frequencies, frequency couplings, and phases using nonlinear correlation functions. For frequency analysis, this approach is a multivariate extension of discrete Fourier transform, and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short and sparse time series and can be extended to cross-trial and cross-channel spectra (CTS) for electroencephalography data where multiple short data segments from multiple trials of the same experiment are available. There are two versions of CTS. The first one assumes some phase coherency across the trials, while the second one is independent of phase coherency. We demonstrate that the phase-dependent version is more consistent with event-related spectral perturbation analysis and traditional Morlet wavelet analysis. We show that CTS can be applied to short data windows and yields higher temporal resolution than traditional Morlet wavelet analysis. Furthermore, the CTS can be used to reconstruct the event-related potential using all linear components of the CTS.

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Salem, Rany M., Daniel T. O'Connor, and Nicholas J. Schork. "Curve-based multivariate distance matrix regression analysis: application to genetic association analyses involving repeated measures." Physiological Genomics 42, no. 2 (2010): 236–47. http://dx.doi.org/10.1152/physiolgenomics.00118.2009.

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Most, if not all, human phenotypes exhibit a temporal, dosage-dependent, or age effect. Despite this fact, it is rare that data are collected over time or in sequence in relevant studies of the determinants of these phenotypes. The costs and organizational sophistication necessary to collect repeated measurements or longitudinal data for a given phenotype are clearly impediments to this, but greater efforts in this area are needed if insights into human phenotypic expression are to be obtained. Appropriate data analysis methods for genetic association studies involving repeated or longitudinal measures are also needed. We consider the use of longitudinal profiles obtained from fitted functions on repeated data collections from a set of individuals whose similarities are contrasted between sets of individuals with different genotypes to test hypotheses about genetic influences on time-dependent phenotype expression. The proposed approach can accommodate uncertainty of the fitted functions, as well as weighting factors across the time points, and is easily extended to a wide variety of complex analysis settings. We showcase the proposed approach with data from a clinical study investigating human blood vessel response to tyramine. We also compare the proposed approach with standard analytic procedures and investigate its robustness and power via simulation studies. The proposed approach is found to be quite flexible and performs either as well or better than traditional statistical methods.

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