Search results for "Multivariate Analysi"
showing 10 items of 1084 documents
A discrete mathematical model for addictive buying: Predicting the affected population evolution
2011
This paper deals with the construction of a discrete mathematical model for addictive buying. Firstly, identifications of consumers buying behavior are performed by using multivariate statistical techniques based on real data bases and sociological approaches. Then the population is divided into appropriate groups according to the level of overbuying and a discrete compartmental model is constructed. The future short term addicted population is computed assuming several future economic scenarios. © 2010 Elsevier Ltd.
Association between odontoma size, age and gender: Multivariate analysis of retrospective data
2019
Background The variety of characteristics related to odontoma research, including an unexplored one such as size, merits a multivariate approach that allows the adequate drawing of inferences with pertinent conclusions. The objective of this study is to establish the possible association between some characteristics related to the odontoma, tumor size among them. Material and methods The sociodemographic characteristics of 60 patients were evaluated. Diagnosis, size, location, type of treatment performed, and prognosis were determined. These data were analyzed descriptively and through multivariate models. Results Thirty-four compound and 26 complex odontomas in 32 men and 28 women were obs…
T-patterns in the study of movement and behavioral disorders
2020
Aim of the present review is to offer an outline of the application of T-pattern analysis (TPA) in the study of neurological disorders characterized by anomalies of movement and, more in general, of behavior. TPA is a multivariate technique to detect real time patterns of behavior on the basis of statistically significant constraints among the events in sequence. TPA is particularly suitable to analyse the structure of behavior. The application of TPA to study movement and behavioral disorders is able to offer, with a high level of detail, hidden characteristics of behavior otherwise impossible to detect. For its intrinsic features, TPA is completely different not only from quantitative eva…
Multivariate approach to reveal relationships between sensory perception of cheeses and aroma profile obtained with different extraction methods
2014
A new and original statistical approach was used to compare the effectiveness of 4 different methods to analyse aroma compounds of seven different commercial semi-hard cheeses with regard to their orthonasal sensory perception. Four extraction methods were evaluated: Purge and Trap, Artificial Mouth, Solid-Phase Microextraction (SPME) and Solvent-Assisted Flavour Evaporation (SAFE). Among the headspace methods, Artificial Mouth gave the closest representation of the studied product space to the sensory perception one. The SAFE method was complementary to the dynamic headspace methods, as it was very efficient in extracting the heavy molecules but less efficient for extracting the most volat…
Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series
2012
The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respira…
Detecting nonlinear causal interactions between dynamical systems by non-uniform embedding of multiple time series.
2010
This study introduces a new approach for the detection of nonlinear Granger causality between dynamical systems. The approach is based on embedding the multivariate (MV) time series measured from the systems X and Y by means of a sequential, non-uniform procedure, and on using the corrected conditional entropy (CCE) as unpredictability measure. The causal coupling from X to Y is quantified as the relative decrease of CCE measured after allowing the series of X to enter the embedding procedure for the description of Y. The ability of the approach to quantify nonlinear causality is assessed on MV time series measured from simulated dynamical systems with unidirectional coupling (the Rössler-…
A multivariate statistical approach of X-ray fluorescence characterization of a large collection of reverse glass paintings
2019
We present an X-ray fluorescence spectroscopy (XRF) study combined with a multivariate approach that allow to detect compositional differences and similarities among the glass supports of a large set of reverse glass paintings belonging to the collection of the Mistretta museum. Reverse painting on glass is an old decorative technique used since the Roman time consisting in applying a cold paint layer on the reverse side of a glass support. The collection shows a large spreading of provenience and dating of the items. In consideration of the current classification solely based on stylistic criteria, we applied a multivariate analysis on the XRF measurements data set to find a more objective…
Adaptive independent vector analysis for multi-subject complex-valued fMRI data.
2017
Abstract Background Complex-valued fMRI data can provide additional insights beyond magnitude-only data. However, independent vector analysis (IVA), which has exhibited great potential for group analysis of magnitude-only fMRI data, has rarely been applied to complex-valued fMRI data. The main challenges in this application include the extremely noisy nature and large variability of the source component vector (SCV) distribution. New method To address these challenges, we propose an adaptive fixed-point IVA algorithm for analyzing multiple-subject complex-valued fMRI data. We exploited a multivariate generalized Gaussian distribution (MGGD)- based nonlinear function to match varying SCV dis…
253 PFS of elderly ovarian cancer patients might be predicted by G-8 geriatric screening tool – results of a retrospective cohort study
2021
Introduction/Background* The aim of this study was to evaluate the impact of the preoperative global health status on the prognosis of patients with ovarian cancer (OC) older than 60 years, who received cytoreductive surgery. Methodology G-8 geriatric screening tool (G-8 score), Lee Schonberg prognostic index, Eastern Cooperative Oncology Group (ECOG) performance status and Charlson Comorbidity Index (CCI) were determined retrospectively in a consecutive cohort of elderly patients with OC. Univariate and multivariate Cox regression analyses and Kaplan-Meier method were performed to analyze the impact of the preoperative global health status on survival. Result(s)* 116 patients entered the s…
Prognostic factors of overall survival for patients with FIGO stage IIIc or IVa ovarian cancer treated with neo-adjuvant chemotherapy followed by int…
2020
International audience; Introduction The aim of this study was to identify prognostic factors of overall survival in patients with FIGO stage IIIc or IVa ovarian cancer (OC) treated by neo-adjuvant chemotherapy (NAC) followed by interval debulking surgery.Materials and methods Data from 483 patients with ovarian cancer were retrospectively collected, from January 1, 2000 to December 31, 2016, from the FRANCOGYN database, regrouping data from 11 centers specialized in ovarian cancer treatment. Median overall survival was determined using the Kaplan-Meier method. Univariate and multivariate analysis were performed to define prognostic factors of overall survival.Results The median overall sur…