Pre-Intervention Multivariate and Univariate Analyses
Univariate and multivariate Pareto models
... for multivariate Pareto data. Creative Bayesian analyses involving informative priors, in multivariate settings and in cases involving covariates, are also notable for their ...
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P< 0.001). Univariate and multivariate survival analyses further showed that miR-182 expression was
... diagnosis of primary CRC and then underwent elective surgery in Nanfang Hospital, Southern Medical University (Guangzhou, China). The use of tissues for this study has been approved by the ethics committee of Nanfang ...
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Effects of wheat cultivar and harvest year on technological quality studied by univariate and multivariate analyses
... Bread volumes of the cultivar Bezostaja are in correspondence with the protein contents in each harvest year, but bread volumes from the cultivar Jagger were mutually comparable rega[r] ...
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How to Classify, Detect, and Manage Univariate and Multivariate Outliers, With Emphasis on Pre-Registration
... Conclusion In this paper, we stressed the importance of outliers in several ways: to detect error outliers; to gain theoretical insights by identifying new moderators that can cause outlying values; and to improve the ...
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Multivariate analyses
... Partitioning multivariate variance Reporting multivariate outcome When we have run the MANOVA analysis in SPSS, we are presented with several lines of multivar- iate ...
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Shapelet Transforms for Univariate and Multivariate Time Series Classification
... scale analyses of multivariate datasets, where most studies had focused on a handful of ...decisive multivariate shapelet transform that outperformed all other approaches, however, this was not the ...
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Essays on univariate and multivariate modeling of financial market risks
... (yielding multivariate models of even higher flexibility), we construct C- and D-vines with mixture pair-copulas to minimize the possibility of misspecifying a vine ...from pre-specified sets of para- ...
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The effect of univariate bias adjustment on multivariate hazard estimates
... of univariate bias- adjustment methods for multivariate ...our analyses are of a rather conceptual na- ture and thus also apply to other climate model outputs, for instance from regional climate ...
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The effect of univariate bias adjustment on multivariate hazard estimates
... Assessing the appropriateness of bias adjustment for im- pact modeling is not an easy task (Papadimitriou et al., 2017). While the quality of bias adjustment on climate variables can be evaluated against observed ...
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A comparison of multivariate and univariate models for pre test post test data concerning accuracy in the presence of missing data
... a MV method offers various benefits and more reliable results in significance testing over the univariate methods. This study only compared the immediate results concerning accuracy, bias and pre- diction. ...
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Multivariate models for pretest posttest data and a comparison to univariate models
... is the error that is present but not specifically controlled for. As with the regressor variable approach, researchers need to deal with some issues when using this approach. First, the change score method is known to be ...
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Comparison of univariate and multivariate linkage analysis of traits related to hypertension
... the multivariate analysis of TG, LDL, and HDL would be more powerful for detecting HTN genes via linkage analysis compared with univariate analysis of ...in univariate Haseman-Elston regression and ...
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Value Added Methods: Moving from Univariate to Multivariate Criteria
... Franco (2006) analyzed VAS from Ohio (TVAAS model) to study their relationships among school/non-school factors. Correlation tables quantified relationships that exist between the independent variables (school/non-school ...
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Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study
... In addition to the increased ALFF in the thalamus, more widespread increases were found in the pre- and post-central gyrus. Similar primary damage and secondary disease effects may explain these results. Preterm ...
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Predictive factors for infertility of women: an univariate and multivariate logistic regression analysis
... regression analyses were used to indicate the association between the dependent (infertility compared to no fertility) and independent ...statistical analyses were performed by SPSS software ...
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Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments
... with univariate bias correction, for example, the question of stationarity (re- garding biases in marginal ...the multivariate distribution to evolve in the projection ...are pre- served by MBCn has ...
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Stochastic Volatility: Univariate and Multivariate Extensions
... Corresponding Author: Éric Jacquier, Finance Department, Fulton Hall 224B, Boston College, Chestnut Hill, MA 02167, USA Tel: 617 552-2943 Fax: 617 552-0431 email: [email protected][r] ...
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Bias in Estimating Multivariate and Univariate Diffusions
... Abstract Multivariate continuous time models are now widely used in economics and ...linear multivariate continuous time systems that includes the commonly used Euler and trapezoidal approximations as ...
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Univariate and Multivariate Time Series Manifold Learning
... Time series analysis aims to extract meaningful information from data that has been generated in sequence by a dynamic process. The modelling of the non-linear dynamics of a signal is often performed using a linear space ...
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A Univariate, Bivariate and Multivariate Extensions for the Inverse Rayleigh Model with Properties and Applications to the Univariate Version
... A new univariate extension of the Inverse Rayleigh distribution is proposed and studied. Some of its fundamental statistical properties such as some stochastic properties, ordinary and incomplete moments, moments ...
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