Littérature scientifique sur le sujet « Survival data analysi »
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Articles de revues sur le sujet "Survival data analysi"
Tsaniya, Ulya, Triastuti Wuryandari et Dwi Ispriyanti. « ANALISIS SURVIVAL PADA DATA KEJADIAN BERULANG MENGGUNAKAN PENDEKATAN COUNTING PROCESS ». Jurnal Gaussian 11, no 3 (28 août 2022) : 377–85. http://dx.doi.org/10.14710/j.gauss.11.3.377-385.
Texte intégralN.Sundaram, N. Sundaram, et P. Venkatesan P.Venkatesan. « Modeling of Parametric Bayesian Cure Rate Survival for Pulmonary Tuberculosis Data Analysis ». International Journal of Scientific Research 3, no 6 (1 juin 2012) : 35–49. http://dx.doi.org/10.15373/22778179/june2014/171.
Texte intégralV. Vallinayagam, V. Vallinayagam, S. Parthasarathy S. Parthasarathy et P. Venkatesan P. Venkatesan. « A Comparative Study of Life Time Models in the Analysis of Survival Data ». Indian Journal of Applied Research 4, no 1 (1 octobre 2011) : 344–47. http://dx.doi.org/10.15373/2249555x/jan2014/101.
Texte intégralVissani, Francesco. « Joint analysis of Borexino and SNO solar neutrino data and reconstruction of the survival probability ». Nuclear Physics and Atomic Energy 18, no 4 (25 décembre 2017) : 303–12. http://dx.doi.org/10.15407/jnpae2017.04.303.
Texte intégralAsakura, Koko, et Toshimitsu Hamasaki. « Analysis of survival data ». Drug Delivery System 30, no 5 (2015) : 474–84. http://dx.doi.org/10.2745/dds.30.474.
Texte intégralBreslow, N., D. R. Cox et D. Oakes. « Analysis of Survival Data. » Biometrics 41, no 2 (juin 1985) : 593. http://dx.doi.org/10.2307/2530888.
Texte intégralJayet, H., et A. Moreau. « Analysis of survival data ». Journal of Econometrics 48, no 1-2 (avril 1991) : 263–85. http://dx.doi.org/10.1016/0304-4076(91)90041-b.
Texte intégralLagakos, S. « Analysis of survival data ». Controlled Clinical Trials 7, no 1 (mars 1986) : 85. http://dx.doi.org/10.1016/0197-2456(86)90009-7.
Texte intégralSchoenfeld, David, D. R. Cox et D. Oakes. « Analysis of Survival Data. » Journal of the American Statistical Association 81, no 394 (juin 1986) : 572. http://dx.doi.org/10.2307/2289259.
Texte intégralKenyon, James R. « Analysis of Multivariate Survival Data ». Technometrics 44, no 1 (février 2002) : 86–87. http://dx.doi.org/10.1198/tech.2002.s658.
Texte intégralThèses sur le sujet "Survival data analysi"
LIU, XIAOQIU. « Managing Cardiovascular Risk in Hypertension : Methodological Issues in Blood Pressure Data Analysis ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/154475.
Texte intégralTASSISTRO, ELENA. « Adverse events in survival data : from clinical questions to methods for statistical analysis ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/365520.
Texte intégralWhen studying a novel treatment with a survival time outcome, failure can be defined to include a serious adverse event (AE) among the endpoints typically considered, for instance relapse or progression. These events act as competing risks, where the occurrence of relapse as first event and the subsequent treatment change exclude the possibility of observing AE related to the treatment itself. In principle, the analysis of AE could be tackled by two different approaches: 1. the description of the observed occurrence of AE as first event: treatment ability to protect from relapse has an impact on the chance of observing AE due to the competing risks action. 2. the assessment of the treatment impact on the development of AE in patients who are relapse free in time: one should consider the occurrence of AE as if relapse would not exclude the possibility of observing AE related to the treatment itself. In the first part of the thesis we reviewed the strategy of analysis for the two approaches starting from the type of clinical question of interest. Then we identified the suitable quantities and possible estimators (crude proportion, AE rate, crude incidence, Kaplan-Meier and Aalen-Nelson smoothed estimators of the cause-specific hazard) and judge them according to two features, usually needed in a survival context: (i) the estimator should address for the presence of right censoring (ii) the theoretical quantity and estimator should be functions of time. In the second part of the thesis we proposed alternative methods, such as regression models, stratified Kaplan-Meier curves and inverse probability of censoring weighting, to relax the assumption of independence between the potential time to AE and the potential time to relapse. We showed through simulations that these methods overcome the problems related to the use of standard competing risks estimators in the second approach. In particular, we simulated different scenarios setting the hazard of relapse independent from two binary covariates, dependent from X1 only, dependent from both covariates X1 and X2, also through their interaction. We showed that one can handle patients’ selection, and thus obtain conditional independence between the two potential times, adjusting for all the observed covariates. Of note, even adjusting only for few observed covariates as in the reality due to unmeasured covariates, gives less biased estimates with respect to the estimate obtained from the naive Kaplan-Meier censoring by relapse. In fact, we proved that the estimate obtained from the naive Kaplan-Meier is always biased unless the hazard of relapse is independent from the covariates values. In an hypothetical scenario where all the covariates are observed, the weighted average survival estimate obtained either non parametrically or by the Cox model and the survival estimate from the inverse probability of censoring weighting would be unbiased (methods applied adjusting for both covariates). In addition, we point out that with the inverse probability of censoring weighting method one could obtained biased estimates when all the possible interactions between the observed covariates are not included in the model to estimate the weights. However, the inclusion of the interaction is not needed when the weighted Cox model is used, since conditional on the observed covariates, this model is robust in estimating the average survival. Nevertheless, a limitation in the use of the weighted average survival method is given by the fact that it may be applied only in the presence of binary (or categorical) covariates, since if the covariate is continuous it is impossible to identify the subgroups in which the survival function is estimated.
Bruno, Rexanne Marie. « Statistical Analysis of Survival Data ». UNF Digital Commons, 1994. http://digitalcommons.unf.edu/etd/150.
Texte intégralFontenelle, OtÃvio Fernandes. « Survival Analysis ; Micro and Small Enterprises ; Modeling Survival Data, Data Characterization Survival ; parametric Estimator KAPLAN-MEIER ». Universidade Federal do CearÃ, 2009. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=4173.
Texte intégralThe main objective of this research is to explore economics issues that may induce impact on lifetime of small businesses during 2002 to 2006. The group of enterprises studied was selected from database of taxpayers recorded at fiscal authority of State of CearÃ. To do that, the methodology was focused on a branch of statistics which deals with survival analysis, called duration analysis or duration modeling in economics. It was applied non-linear model whose non-parametric estimator chosen was KAPLAN-MEIER. Through that methodology, it was developed sceneries based on the following attributes: county where the enterprises were established; economics activities based on national classification, fiscal version 1.0/1.1; and, finally, the relationship between State of Cearà â as fiscal authority â and enterprises. The counties were grouped applying two parameters of stratifications: gross domestic product(GDP) per capita and investment in education per capita. Before any stratification, only counties with thirty or more enterprises starting their activities in year 2002 were considered in sceneries to analysis.
A dissertaÃÃo tem o objetivo de investigar fatores econÃmicos que possam influenciar na sobrevida de micros e pequenas empresas (MEPs) contribuintes do Imposto sobre OperaÃÃes relativas à CirculaÃÃo de Mercadorias e sobre PrestaÃÃes de ServiÃos de Transporte Interestadual e Intermunicipal e de ComunicaÃÃo (ICMS) do Estado do Cearà no perÃodo de 2002 à 2006. Para isso, aplicou-se uma tÃcnica estatÃstica denominada anÃlise de sobrevivÃncia a partir de modelos nÃo lineares cujo estimador nÃo-paramÃtrico escolhido foi o de KAPLAN-MEIER. Com os dados de sobrevivÃncia devidamente modelados, buscou-se estratificÃ-los focando os municÃpios dos logradouros das MEPs; dentro do que tange as operaÃÃes do ICMS, focando as atividades econÃmicas segundo a classificaÃÃo nacional de atividades econÃmicas (CNAE) versÃo fiscal 1.0/1.1; e, finalmente, observar a relaÃÃo do Estado â enquanto autoridade fiscal â com esses pequenos estabelecimentos, restringindo temporariamente seu faturamento ou mesmo baixando sua inscriÃÃo estadual, impossibilitando a continuidade de suas atividades. Dos municÃpios, utilizou-se como Ãndice de estratificaÃÃo entre as curvas de sobrevivÃncia o produto interno bruto (PIB) per capita e os investimentos mÃdio per capita em educaÃÃo daquelas empresas localizadas em municÃpios com 30 ou mais estabelecimentos ativados no ano de 2002. Dentre outras, duas importantes observaÃÃes foram identificar o municÃpio de Fortaleza como um âoutlinerâ frente aos outros municÃpios e a forte dominÃncia da curva de sobrevivÃncia das empresas que nÃo sofreram intervenÃÃo do fisco em suas atividades sobre aquelas que tiveram.
葉英傑 et Ying-Kit David Ip. « Analysis of clustered grouped survival data ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31226127.
Texte intégralIp, Ying-Kit David. « Analysis of clustered grouped survival data / ». Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B2353011x.
Texte intégralLee, Yau-wing. « Modelling multivariate survival data using semiparametric models ». Click to view the E-thesis via HKUTO, 2000. http://sunzi.lib.hku.hk/hkuto/record/B4257528X.
Texte intégralNhogue, Wabo Blanche Nadege. « Hedge Funds and Survival Analysis ». Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/26257.
Texte intégralKulich, Michal. « Additive hazards regression with incomplete covariate data / ». Thesis, Connect to this title online ; UW restricted, 1997. http://hdl.handle.net/1773/9562.
Texte intégral梁翠蓮 et Tsui-lin Leung. « Proportional odds model for survival data ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B42575011.
Texte intégralLivres sur le sujet "Survival data analysi"
Cox, D. R. Analysis of survival data. London : Chapman and Hall, 1990.
Trouver le texte intégralHougaard, Philip. Analysis of Multivariate Survival Data. New York, NY : Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1304-8.
Texte intégralElandt-Johnson, Regina C., et Norman L. Johnson. Survival Models and Data Analysis. Hoboken, NJ, USA : John Wiley & Sons, Inc., 1999. http://dx.doi.org/10.1002/9781119011040.
Texte intégralAnalysis of multivariate survival data. New York : Springer, 2000.
Trouver le texte intégralElandt-Johnson, Regina C. Survival models and data analysis. New York : Wiley, 1999.
Trouver le texte intégral1961-, Chen Ming-Hui, et Sinha Debajyoti, dir. Bayesian survival analysis. New York : Springer, 2001.
Trouver le texte intégralStatistical methods for survival data analysis. 2e éd. New York : Wiley, 1992.
Trouver le texte intégralLee, Elisa T., et John Wenyu Wang. Statistical Methods for Survival Data Analysis. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2003. http://dx.doi.org/10.1002/0471458546.
Texte intégralWenyu, Wang John, dir. Statistical methods for survival data analysis. 3e éd. New York : J. Wiley, 2003.
Trouver le texte intégralMurphy, Roberta. Survival analysis of nurse manpower data. [S.l : The Author], 1997.
Trouver le texte intégralChapitres de livres sur le sujet "Survival data analysi"
Nokeri, Tshepo Chris. « Survival Analysis ». Dans Data Science Revealed, 185–200. Berkeley, CA : Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6870-4_11.
Texte intégralTattar, Prabhanjan Narayanachar, et H. J. Vaman. « Lifetime Data and Concepts ». Dans Survival Analysis, 3–26. Boca Raton : Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003306979-1.
Texte intégralDeMaris, Alfred, et Steven H. Selman. « Survival Analysis ». Dans Converting Data into Evidence, 137–59. New York, NY : Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7792-1_8.
Texte intégralCollett, D. « Survival analysis ». Dans Modelling Survival Data in Medical Research, 1–13. Boston, MA : Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-3115-3_1.
Texte intégralIbrahim, Joseph G., Ming-Hui Chen et Debajyoti Sinha. « Missing Covariate Data ». Dans Bayesian Survival Analysis, 290–319. New York, NY : Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3447-8_8.
Texte intégralBhattacharjee, Atanu. « Survival Analysis ». Dans Big Data Analytics in Oncology with R, 1–24. Boca Raton : Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003185598-1.
Texte intégralEveritt, Brian, et Sophia Rabe-Hesketh. « Survival Analysis I ». Dans Analyzing Medical Data Using S-PLUS, 345–59. New York, NY : Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3285-6_17.
Texte intégralIbrahim, Joseph G., Ming-Hui Chen et Debajyoti Sinha. « Joint Models for Longitudinal and Survival Data ». Dans Bayesian Survival Analysis, 262–89. New York, NY : Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3447-8_7.
Texte intégralBhattacharjee, Atanu. « Parametric Survival Analysis ». Dans Big Data Analytics in Oncology with R, 39–48. Boca Raton : Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003185598-3.
Texte intégralShoukri, Mohamed M. « Analysis of Survival Data ». Dans Analysis of Correlated Data with SAS and R, 335–82. Fourth edition. | Boca Raton : CRC Press, 2018. | Previous edition : Analysis of correlated data with SAS and R / Mohamed M. Shoukri (Boca Raton : Chapman & Hall/CRC, 2007). : Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315277738-9.
Texte intégralActes de conférences sur le sujet "Survival data analysi"
Mosquéra, Júlia Milhomem, Amanda Ribeiro Alves, Gianna Carolina Pereira Cavalli, Larissa Feitosa de Albuquerque Lima Ramos et Flávio Lúcio Vasconcelos. « GLOBAL SURVIVAL BASED ON CLINICAL, HISTOLOGICAL, AND BIOLOGICAL TUMOR CRITERIA IN A SECONDARY PUBLIC BRAZILIAN HOSPITAL ». Dans Abstracts from the Brazilian Breast Cancer Symposium - BBCS 2021. Mastology, 2021. http://dx.doi.org/10.29289/259453942021v31s2045.
Texte intégralWang, Lu, Yan Li, Jiayu Zhou, Dongxiao Zhu et Jieping Ye. « Multi-task Survival Analysis ». Dans 2017 IEEE International Conference on Data Mining (ICDM). IEEE, 2017. http://dx.doi.org/10.1109/icdm.2017.58.
Texte intégralBagkavos, Dimitrios I., Aglaia Kalamatianou et Dimitrios Ioannides. « Kernel based confidence intervals for survival function estimation ». Dans Recent Advances in Stochastic Modeling and Data Analysis. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812709691_0040.
Texte intégralLord, Laurel, John Sell, Feyzi Bagirov et Mark Newman. « Survival Analysis within Stack Overflow : Python and R ». Dans 2018 4th International Conference on Big Data Innovations and Applications (Innovate-Data). IEEE, 2018. http://dx.doi.org/10.1109/innovate-data.2018.00015.
Texte intégralXuan Tran, Ha, Thuc Duy Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao et Tony Waters. « Decision Support for Disability Employment using Counterfactual Survival Analysis ». Dans 2022 IEEE International Conference on Big Data (Big Data). IEEE, 2022. http://dx.doi.org/10.1109/bigdata55660.2022.10021126.
Texte intégralYang, Wanshan, Ting Huang, Junlin Zeng, Yan Tang, Lijun Chen, Shivakant Mishra et Youjian Eugene Liu. « Purchase Prediction in Free Online Games via Survival Analysis ». Dans 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006031.
Texte intégralYadav, Pranjul, Michael Steinbach, Lisiane Pruinelli, Bonnie Westra, Connie Delaney, Vipin Kumar et Gyorgy Simon. « Forensic Style Analysis with Survival Trajectories ». Dans 2015 IEEE International Conference on Data Mining (ICDM). IEEE, 2015. http://dx.doi.org/10.1109/icdm.2015.152.
Texte intégralLi, Yan, Kevin S. Xu et Chandan K. Reddy. « Regularized Parametric Regression for High-dimensional Survival Analysis ». Dans Proceedings of the 2016 SIAM International Conference on Data Mining. Philadelphia, PA : Society for Industrial and Applied Mathematics, 2016. http://dx.doi.org/10.1137/1.9781611974348.86.
Texte intégralMoat, Genevieve, et Shirley Coleman. « Survival Analysis and Predictive Maintenance Models for non-sensored Assets in Facilities Management ». Dans 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671625.
Texte intégralRahman, Md Mahmudur, et Sanjay Purushotham. « Fair and Interpretable Models for Survival Analysis ». Dans KDD '22 : The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA : ACM, 2022. http://dx.doi.org/10.1145/3534678.3539259.
Texte intégralRapports d'organisations sur le sujet "Survival data analysi"
McKeague, Ian W., et Mei-Jie Zhang. On the Analysis of Grouped Survival Data Using Cumulative Occurrence/Exposure Rates. Fort Belvoir, VA : Defense Technical Information Center, mars 1991. http://dx.doi.org/10.21236/ada238219.
Texte intégralSmith, Steven G., John R. Skalski et J. Warren Schelechte. Statistical Survival Analysis of Fish and Wildlife Tagging Studies ; SURPH.1 Manual - Analysis of Release-Recapture Data for Survival Studies, 1994 Technical Manual. Office of Scientific and Technical Information (OSTI), décembre 1994. http://dx.doi.org/10.2172/654053.
Texte intégralKimura, Fukunari, et Takamune Fujii. Globalizing Activities and the Rate of Survival : Panel Data Analysis on Japanese Firms. Cambridge, MA : National Bureau of Economic Research, novembre 2003. http://dx.doi.org/10.3386/w10067.
Texte intégralZhang, Dan, Jingting Liu, Mengxia zheng, Chunyan Meng et Jianhua Liao. Prognostic and Clinicopathological significance of CD155 Expression in Cancer Patients : A Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, septembre 2022. http://dx.doi.org/10.37766/inplasy2022.9.0087.
Texte intégralZhu, Yi-Bing, Yan Yao, Yuan Xu et Hui-Bin Huang. Nitrogen balance and Outcomes in Critically Ill Patients : A Systematic Review and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, mai 2022. http://dx.doi.org/10.37766/inplasy2022.5.0134.
Texte intégralChen, Xiaole, Peng Wang, Yunquan Luo, Yi-Yu Lu, Wenjun Zhou, Mengdie Yang, Jian Chen, Zhi-Qiang Meng et Shi-Bing Su. Therapeutic Efficacy Evaluation and Underlying Mechanisms Prediction of Jianpi Liqi Decoction for Hepatocellular Carcinoma. Science Repository, septembre 2021. http://dx.doi.org/10.31487/j.jso.2021.02.04.sup.
Texte intégralZhao, Binghao, Yu Wang et Wenbin Ma. Comparative Efficacy and Safety of Therapeutics for Elderly Glioblastoma : a Bayesian Network Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, mars 2022. http://dx.doi.org/10.37766/inplasy2022.3.0094.
Texte intégralKuo, Meng-Hsuan, Chih-Wei Tseng, Ching-Sheng Hsu, Yen-Chun Chen, I.-Ting Kao et Chen-Yi Wu. Protocol for systematic review and meta-analysis of prognostic value of sarcopenia in advanced HCC patients treating with systemic therapy. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, février 2023. http://dx.doi.org/10.37766/inplasy2023.2.0011.
Texte intégralZheng, Jiaxi, et Haihua Yang. Clinical Benefits of Immune Checkpoint Inhibitors and Predictive Value of Tumor Mutation Burden in Hepatocellular Carcinoma : A Systematic Review and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, janvier 2022. http://dx.doi.org/10.37766/inplasy2022.1.0008.
Texte intégralWang, Qing, Zi-Xu Wang, Nasu M. Otomi et Shinji Mine. Association between cutoffs for classifying high- and low-volume hospitals and long-term survival after eophagectomy : A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, juillet 2022. http://dx.doi.org/10.37766/inplasy2022.7.0023.
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