Academic literature on the topic 'Analyse statistique multiple'
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Journal articles on the topic "Analyse statistique multiple"
Guetsop Sateu, Fabrice Arnaud. "Décisions financières et performance des entreprises : une analyse exploratoire dans le contexte camerounais." Recherches en Sciences de Gestion N° 157, no. 4 (September 28, 2023): 149–71. http://dx.doi.org/10.3917/resg.157.0149.
Full textZingaretti, Laura M., Gilles Renand, Diego P. Morgavi, and Yuliaxis Ramayo-Caldas. "Link-HD: a versatile framework to explore and integrate heterogeneous microbial communities." Bioinformatics 36, no. 7 (November 18, 2019): 2298–99. http://dx.doi.org/10.1093/bioinformatics/btz862.
Full textRicher, Marie-Claude, Marie-Josée Letarte, and Sylvie Normandeau. "Caractéristiques familiales associées aux trois profils du trouble déficitaire de l’attention/hyperactivité chez les enfants âgés de 6 à 9 ans." Enfance en difficulté 1 (September 6, 2012): 145–66. http://dx.doi.org/10.7202/1012126ar.
Full textBec, Frédérique. "Impulsions dominantes et analyse des fluctuations de l’économie française." Articles 70, no. 1 (March 23, 2009): 5–26. http://dx.doi.org/10.7202/602127ar.
Full textCohen, Atika, Alain Lammé, Catherine Vermandele, and Mohamed Sraieb. "Les enjeux des supports de cours : cas d'un enseignement de statistique en sciences humaines." Statistique et Enseignement 8, no. 1 (2017): 21–44. https://doi.org/10.3406/staso.2017.1351.
Full textBaudot, Pierre-Yves, and Marie-Victoire Bouquet. "Expérience biographique du handicap et participation électorale." Alter 17-1 (2023): 45–68. http://dx.doi.org/10.4000/9ifj.
Full textIrwin, Julie R., and Gary H. McClelland. "Heuristiques trompeuses et modèles de régression multiple avec variable modératrice." Recherche et Applications en Marketing (French Edition) 17, no. 2 (June 2002): 87–101. http://dx.doi.org/10.1177/076737010201700205.
Full textOpoola, E., C. Z. Kahuwai, and T. S. Olugbemi. "Evaluation of the performance characteristics, nutrient digestibility and carcass quality of broiler chickens fed Lacto acidophilus®as a replacement for a commercial antibiotic." Nigerian Journal of Animal Production 48, no. 1 (February 28, 2021): 166–74. http://dx.doi.org/10.51791/njap.v48i1.2895.
Full textOlivier, Jean-Marc. "Prédiction et prévision en histoire économique : les succès suisses et scandinaves étaient-ils prévisibles?" Nouvelles perspectives en sciences sociales 6, no. 2 (September 13, 2011): 87–96. http://dx.doi.org/10.7202/1005771ar.
Full textAsselin, Christian, J. Pages, and René Morlat. "Typologie sensorielle du Cabernet franc et influence du terroir. Utilisation de méthodes statistiques multidimensionnelles." OENO One 26, no. 3 (September 30, 1992): 129. http://dx.doi.org/10.20870/oeno-one.1992.26.3.1192.
Full textDissertations / Theses on the topic "Analyse statistique multiple"
Zhang, Jian. "Bayesian multiple hypotheses testing with quadratic criterion." Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0016/document.
Full textThe anomaly detection and localization problem can be treated as a multiple hypotheses testing (MHT) problem in the Bayesian framework. The Bayesian test with the 0−1 loss function is a standard solution for this problem, but the alternative hypotheses have quite different importance in practice. The 0−1 loss function does not reflect this fact while the quadratic loss function is more appropriate. The objective of the thesis is the design of a Bayesian test with the quadratic loss function and its asymptotic study. The construction of the test is made in two steps. In the first step, a Bayesian test with the quadratic loss function for the MHT problem without the null hypothesis is designed and the lower and upper bounds of the misclassification probabilities are calculated. The second step constructs a Bayesian test for the MHT problem with the null hypothesis. The lower and upper bounds of the false alarm probabilities, the missed detection probabilities as well as the misclassification probabilities are calculated. From these bounds, the asymptotic equivalence between the proposed test and the standard one with the 0-1 loss function is studied. A lot of simulation and an acoustic experiment have illustrated the effectiveness of the new statistical test
Abdessemed, Lila. "Intégration de la contigui͏̈té en analyse factorielle discriminante et généralisation de l'analyse factorielle multiple aux tableaux de fréquence." Rennes 1, 1994. http://www.theses.fr/1994REN10029.
Full textCollignon, Olivier. "Recherche statistique de biomarqueurs du cancer et de l'allergie à l'arachide." Phd thesis, Nancy 1, 2009. http://tel.archives-ouvertes.fr/tel-00430177.
Full textDupuy, Mariette. "Analyse des caractéristiques électriques pour la détection des sujets à risque de mort subite cardiaque." Electronic Thesis or Diss., Bordeaux, 2025. http://www.theses.fr/2025BORD0002.
Full textSudden cardiac death (SCD) accounts for 30% of adult mortality in industrialized countries. The majority of SCD cases are the result of an arrhythmia called ventricular fibrillation, which itself results from structural abnormalities in the heart muscle. Despite the existence of effective therapies, most individuals at risk for SCD are not identified preventively due to the lack of available testing. Developing specific markers on electrocardiographic recordings would enable the identification and stratification of SCD risk. Over the past six years, the Liryc Institute has recorded surface electrical signals from over 800 individuals (both healthy and pathological) using a high-resolution 128-electrode device. Features were calculated from these signals (signal duration per electrode, frequency, amplitude fractionation, etc.). In total, more than 1,500 electrical features are available per patient. During the acquisition process using the 128-electrode system in a hospital setting, noise or poor positioning of specific electrodes sometimes prevents calculating the intended features, leading to an incomplete database. This thesis is organized around two main axes. First, we developed a method for imputing missing data to address the problem of faulty electrodes. Then, we developed a risk score for the sudden death risk stratification. The most commonly used family of methods for handling missing data is imputation, ranging from simple completion by averaging to local aggregation methods, local regressions, optimal transport, or even modifications of generative models. Recently, Autoencoders (AE) and, more specifically, Denoising AutoEncoders (DAE) have performed well in this task. AEs are neural networks used to learn a representation of data in a reduced-dimensional space. DAEs are AEs that have been proposed to reconstruct original data from noisy data. In this work, we propose a new methodology based on DAEs called the modified Denoising AutoEncoder (mDAE) to allow for the imputation of missing data. The second research axis of the thesis focused on developing a risk score for sudden cardiac death. DAEs can model and reconstruct complex data. We trained DAEs to model the distribution of healthy individuals based on a selected subset of electrical features. Then, we used these DAEs to discriminate pathological patients from healthy individuals by analyzing the imputation quality of the DAE on partially masked features. We also compared different classification methods to establish a risk score for sudden death
Girka, Fabien. "Development of new statistical/ML methods for identifying multimodal factors related to the evolution of Multiple Sclerosis." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG075.
Full textStudying a given phenomenon under multiple views can reveal a more significant part of the mechanisms at stake rather than considering each view separately. In order to design a study under such a paradigm, measurements are usually acquired through different modalities resulting in multimodal/multiblock/multi-source data. One statistical framework suited explicitly for the joint analysis of such multi-source data is Regularized Generalized Canonical Correlation Analysis (RGCCA). RGCCA extracts canonical vectors and components that summarize the different views and their interactions. The contributions of this thesis are fourfold. (i) Improve and enrich the RGCCA R package to democratize its use. (ii) Extend the RGCCA framework to better handle tensor data by imposing a low-rank tensor factorization to the extracted canonical vectors. (iii) Propose and investigate simultaneous versions of RGCCA to get all canonical components at once. The proposed methods pave the way for new extensions of RGCCA. (iv) Use the developed tools and expertise to analyze multiple sclerosis and leukodystrophy data. A focus is made on identifying biomarkers differentiating between patients and healthy controls or between groups of patients
Kumar, Vandhna. "Descente d'échelle statistique du niveau de la mer pour les îles du Pacifique Sud-Ouest : une approche de régression linéaire multiple." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30234.
Full textSea level rise is a growing concern in the islands of the western Pacific. Over the altimetry era (1993-present), sea level rise rates in the western tropical Pacific were amongst the highest recorded across the world ocean, reaching up to 3-4 times the global mean. As more and more affected communities relocate to higher grounds to escape the rising seas, there is a compelling need for information on local scales to ease the adaptation and planning process. This is not a straightforward process as sea level varies regionally, driven by wind and ocean circulation patterns, and the prevailing climate modes (e.g. ENSO, PDO/IPO). On local scales, substantial sea level changes can result from natural or anthropogenic induced vertical ground motion. Motivated by such concerns, this thesis focuses on developing a statistical downscaling technique, namely a multiple linear regression (MLR) model, to simulate island sea levels at selected sites in the southwest Pacific - Suva and Lautoka in Fiji, and Nouméa in New Caledonia. The model is based on the knowledge that sea level variations in the tropical Pacific are mainly thermosteric in nature (temperature-related changes in ocean water density) and that these thermosteric variations are dominated by wind-forced, westward propagating Rossby waves. The MLR experiments are conducted over the 1988-2014 study period, with a focus on interannual-to-decadal sea level variability and trend. Island sea levels are first expressed a sum of steric and mass changes. Then, a more dynamical approach using wind stress curl as a proxy for the thermosteric component is undertaken to construct the MLR model. In the latter case, island sea levels are perceived as a composite of global, regional and local components, where the second is dominant. The MLR model takes wind stress curl as the dominant regional regressor (via a Rossby wave model), and the local halosteric component (salinity-related changes in ocean water density), local wind stress, and local sea surface temperature as minor regressors. A stepwise regression function is used to isolate statistically significant regressors before calibrating the MLR model. The modeled sea level shows high agreement with observations, capturing 80% of the variance on average. Stationarity tests on the MLR model indicate that it can be applied skillfully to projections of future sea level. The statistical downscaling approach overall provides insights on key drivers of sea level variability at the selected sites, showing that while local dynamics and the global signal modulate sea level to a given extent, most of the variance is driven by regional factors. [...]
Jmel, Saïd. "Applications des modèles graphiques au choix de variables et à l'analyse des interactions dans une table de contingence multiple." Toulouse 3, 1992. http://www.theses.fr/1992TOU30091.
Full textPluntz, Matthieu. "Sélection de variables en grande dimension par le Lasso et tests statistiques - application à la pharmacovigilance." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASR002.
Full textVariable selection in high-dimensional regressions is a classic problem in health data analysis. It aims to identify a limited number of factors associated with a given health event among a large number of candidate variables such as genetic factors or environmental or drug exposures.The Lasso regression (Tibshirani, 1996) provides a series of sparse models where variables appear one after another depending on the regularization parameter's value. It requires a procedure for choosing this parameter and thus the associated model. In this thesis, we propose procedures for selecting one of the models of the Lasso path, which belong to or are inspired by the statistical testing paradigm. Thus, we aim to control the risk of selecting at least one false positive (Family-Wise Error Rate, FWER) unlike most existing post-processing methods of the Lasso, which accept false positives more easily.Our first proposal is a generalization of the Akaike Information Criterion (AIC) which we call the Extended AIC (EAIC). We penalize the log-likelihood of the model under consideration by its number of parameters weighted by a function of the total number of candidate variables and the targeted level of FWER but not the number of observations. We obtain this function by observing the relationship between comparing the information criteria of nested sub-models of a high-dimensional regression, and performing multiple likelihood ratio test, about which we prove an asymptotic property.Our second proposal is a test of the significance of a variable appearing on the Lasso path. Its null hypothesis depends on a set A of already selected variables and states that it contains all the active variables. As the test statistic, we aim to use the regularization parameter value from which a first variable outside A is selected by Lasso. This choice faces the fact that the null hypothesis is not specific enough to define the distribution of this statistic and thus its p-value. We solve this by replacing the statistic with its conditional p-value, which we define conditional on the non-penalized estimated coefficients of the model restricted to A. We estimate the conditional p-value with an algorithm that we call simulation-calibration, where we simulate outcome vectors and then calibrate them on the observed outcome‘s estimated coefficients. We adapt the calibration heuristically to the case of generalized linear models (binary and Poisson) in which it turns into an iterative and stochastic procedure. We prove that using our test controls the risk of selecting a false positive in linear models, both when the null hypothesis is verified and, under a correlation condition, when the set A does not contain all active variables.We evaluate the performance of both procedures through extensive simulation studies, which cover both the potential selection of a variable under the null hypothesis (or its equivalent for EAIC) and on the overall model selection procedure. We observe that our proposals compare well to their closest existing counterparts, the BIC and its extended versions for the EAIC, and Lockhart et al.'s (2014) covariance test for the simulation-calibration test. We also illustrate both procedures in the detection of exposures associated with drug-induced liver injuries (DILI) in the French national pharmacovigilance database (BNPV) by measuring their performance using the DILIrank reference set of known associations
Tran, Xuan Quang. "Les modèles de régression dynamique et leurs applications en analyse de survie et fiabilité." Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0147/document.
Full textThis thesis was designed to explore the dynamic regression models, assessing the sta-tistical inference for the survival and reliability data analysis. These dynamic regressionmodels that we have been considered including the parametric proportional hazards andaccelerated failure time models contain the possibly time-dependent covariates. We dis-cussed the following problems in this thesis.At first, we presented a generalized chi-squared test statisticsY2nthat is a convenient tofit the survival and reliability data analysis in presence of three cases: complete, censoredand censored with covariates. We described in detail the theory and the mechanism to usedofY2ntest statistic in the survival and reliability data analysis. Next, we considered theflexible parametric models, evaluating the statistical significance of them by usingY2nandlog-likelihood test statistics. These parametric models include the accelerated failure time(AFT) and a proportional hazards (PH) models based on the Hypertabastic distribution.These two models are proposed to investigate the distribution of the survival and reliabilitydata in comparison with some other parametric models. The simulation studies were de-signed, to demonstrate the asymptotically normally distributed of the maximum likelihood estimators of Hypertabastic’s parameter, to validate of the asymptotically property of Y2n test statistic for Hypertabastic distribution when the right censoring probability equal 0% and 20%.n the last chapter, we applied those two parametric models above to three scenes ofthe real-life data. The first one was done the data set given by Freireich et al. on thecomparison of two treatment groups with additional information about log white blood cellcount, to test the ability of a therapy to prolong the remission times of the acute leukemiapatients. It showed that Hypertabastic AFT model is an accurate model for this dataset.The second one was done on the brain tumour study with malignant glioma patients, givenby Sauerbrei & Schumacher. It showed that the best model is Hypertabastic PH onadding five significance covariates. The third application was done on the data set given by Semenova & Bitukov on the survival times of the multiple myeloma patients. We did not propose an exactly model for this dataset. Because of that was an existing oneintersection of survival times. We, therefore, suggest fitting other dynamic model as SimpleCross-Effect model for this dataset
Héraud, Bousquet Vanina. "Traitement des données manquantes en épidémiologie : application de l’imputation multiple à des données de surveillance et d’enquêtes." Thesis, Paris 11, 2012. http://www.theses.fr/2012PA11T017/document.
Full textThe management of missing values is a common and widespread problem in epidemiology. The most common technique used restricts the data analysis to subjects with complete information on variables of interest, which can reducesubstantially statistical power and precision and may also result in biased estimates.This thesis investigates the application of multiple imputation methods to manage missing values in epidemiological studies and surveillance systems for infectious diseases. Study designs to which multiple imputation was applied were diverse: a risk analysis of HIV transmission through blood transfusion, a case-control study on risk factors for ampylobacter infection, and a capture-recapture study to estimate the number of new HIV diagnoses among children. We then performed multiple imputation analysis on data of a surveillance system for chronic hepatitis C (HCV) to assess risk factors of severe liver disease among HCV infected patients who reported drug use. Within this study on HCV, we proposedguidelines to apply a sensitivity analysis in order to test the multiple imputation underlying hypotheses. Finally, we describe how we elaborated and applied an ongoing multiple imputation process of the French national HIV surveillance database, evaluated and attempted to validate multiple imputation procedures.Based on these practical applications, we worked out a strategy to handle missing data in surveillance data base, including the thorough examination of the incomplete database, the building of the imputation model, and the procedure to validate imputation models and examine underlying multiple imputation hypotheses
Books on the topic "Analyse statistique multiple"
J, Greenacre Michael, and Blasius Jörg 1957-, eds. Multiple correspondence analysis and related methods. Boca Raton: Chapman & Hall/CRC, 2006.
Find full textPaul, Reise Steven, and Duan Naihua 1949-, eds. Multilevel modeling: Methodological advances, issues, and applications. Mahwah, N.J: Lawrence Erlbaum Associates, 2003.
Find full textBechhofer, Robert E. Design and analysis of experiments for statistical selection, screening, and multiple comparisons. New York: Wiley, 1995.
Find full textJaccard, James. Interaction effects in multiple regression. 2nd ed. Thousand Oaks, Calif: Sage Publications, 2003.
Find full textRobert, Turrisi, and Wan Choi K, eds. Interaction effects in multiple regression. Newbury Park: Sage Publications, 1990.
Find full textK, Wan Choi, ed. LISREL approaches to interaction effects in multiple regression. Thousand Oaks, Calif: Sage Publications, 1996.
Find full textHsu, Jason. Multiple Comparisons: Theory and Methods. Taylor & Francis Group, 1996.
Find full textHsu, Jason. Multiple Comparisons: Theory and Methods. Taylor & Francis Group, 1996.
Find full textMultiple Comparisons: Theory and Methods. Chapman & Hall/CRC, 1996.
Find full textMultiple Comparisons: Theory and Methods. Taylor & Francis Group, 2023.
Find full textReports on the topic "Analyse statistique multiple"
Battams, Nathan. Coup d’œil sur la diversité familiale au Canada (février 2018). L’Institut Vanier de la famille, 2018. http://dx.doi.org/10.61959/zgcs6217f.
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