Risk Modelling and Survival Analysis - Actuarial Science
Explore stochastic processes, Markov chains, risk modeling, and survival analysis in actuarial science. Learn key concepts and tackle past exam questions using R for practical applications.
Study Design Part 1: Survival Analysis - Lecture 2C
Explore survival analysis techniques for clinical research, covering key concepts and applications in study design and data interpretation.
Clinical Genomics and Biomarker Discovery 2010
Explore survival analysis and clinical omics for personalized medicine, delving into cutting-edge approaches in genomics and biomarker discovery.
Survival Analyses
Learn to generate censored exponential data, derive density and likelihood for censored data, and understand the Kaplan-Meier estimator as a maximum likelihood estimator in R.
Actuarial Science
Comprehensive exploration of actuarial concepts, covering statistics, economics, and mathematical modeling for risk assessment in insurance and finance.
Essentials of Epidemiology
Explore clinical trial studies, cohort research models, and survival analysis techniques including Kaplan Meier method in epidemiological research.
R Tutorials
Comprehensive R tutorials covering bioinformatics, statistics, and data visualization. Learn to analyze gene expression, perform regression, create plots, and conduct survival analysis using R programming.
Bioinformatics
Comprehensive bioinformatics tutorials covering RNA-seq analysis, data visualization, statistical methods, and cancer genomics using R and other tools.
Biostatistics and Epidemiology Lecture Series
Comprehensive lecture series covering essential biostatistics and epidemiology concepts, from basics to advanced topics like probability, statistical inference, and survival analysis.
The Attack of the Clones - A Study of the Impact of Shared Code on Vulnerability Patching
Explores impact of shared code on vulnerability patching, revealing delays between patch releases and novel exploitation techniques. Analyzes patch deployment data from millions of hosts to improve cybersecurity strategies.
Survival Analysis
Learn key concepts and techniques in survival analysis, including censoring, truncation, life tables, and Kaplan-Meier curves, with practical examples and applications.
Conceptual Overviews of Statistical and Data-Analytic Tools and Techniques
Explore key statistical and data analysis methods, from hierarchical regression to survival analysis, with conceptual overviews of advanced techniques and tools.
Survival Analysis with TCGA Data in R - Create Kaplan-Meier Curves
Learn survival analysis using TCGA data in R, including Kaplan-Meier curves. Covers key concepts, data preparation, and practical implementation using survival and survminer packages.
Statistical Rethinking 2023 - Modeling Events
Explore statistical modeling for events, covering discrimination, mediation, generative models, and generalized linear models. Learn to analyze and compute interventions, with a bonus on survival analysis.
Survival Analysis of Cancer Patients Using Machine Learning Technique by Shakuntala Baichoo
Explore machine learning techniques for survival analysis of cancer patients, focusing on predicting outcomes and analyzing clinical data to enhance patient care and treatment strategies.
Empirical Likelihood with Censored Data
Explore advanced statistical techniques for analyzing censored data using empirical likelihood methods, enhancing your ability to handle incomplete datasets effectively.
Bayesian Quantile Joint Modeling of Multivariate Longitudinal and Time-to-Event Data
Explore Bayesian quantile joint modeling for multivariate longitudinal and time-to-event data, focusing on non-Gaussian outcomes and time-varying covariates in medical research applications.
臨床研究者のための生物統計学 - 生存時間解析の基礎 - チャプター3
臨床研究における生存時間解析の基礎概念と手法を学び、医療統計学の実践的な応用方法を習得する19分間の講義。
臨床研究者のための生物統計学 - 生存時間解析の基礎 - チャプター4
臨床研究における生存時間解析の基礎概念と手法を学び、医療統計学の実践的な応用方法を習得する医学統計学レクチャー。
R Tutorials
Comprehensive R tutorials covering data management, analysis, and visualization, with hands-on exercises using real datasets and practical applications in statistics and data science.
Cancer Somatic Mutation Analysis - MAFTOOLS R Package
Learn to analyze cancer somatic mutations using MAFtools R package. Covers importing data, visualization techniques, driver detection, survival analysis, and comparing cancer cohorts for comprehensive mutation insights.