Regression Models and Life-Tables. Features As of today, 63344 citations listed on Google Scholar Published in 1972 Author: Sir David Roxbee Cox, a British Statistician Ideas ? The present paper…
Nonparametric Estimation from Incomplete Observations. Kaplan-Meier Survival Curve Estimation Copyright @Statistical.Solutions Features One of the most cited statistical papers of all time As of today, 66638 citations listed on Google…
Metagenomic data have specific characteristics that require adapted statistical methods. Discover the most commonly used statistical tools in this field. The training begins with a reminder of hypothesis testing, associated risks, multiplicity and how to control them. Then learn what are the specificities and problems of genomic data. The training reviews classic tests for comparing groups (ANOVA, MANOVA) and their extension to tests adapted to genomic data (ANOSIM and PERMANOVA). Data visualization tools and choice of a distance metric are also discussed.
Shelf-life data possess specific features so that their design and analysis require adapted statistical tools. This workshop uses a variety of case studies to present the most important aspects to consider for a sound determination of product shelf life. Starting from the assessment of the differences between shelf-life and stability studies, participants learn for each type of study how to design efficient experiments to determine the failure time of products accurately. The issues discussed include the timepoint selection, how to handle destructive testing, the experiment size and the choice of samples. The workshop also emphasizes the appropriate ways to analyze life data and to adequately interpret and communicate the results obtained. The principle of accelerated shelf-life testing (ASLT) along with the conditions for a successful use are discussed.
Lifetime data possess specific features so that their design and analysis require adapted statistical tools.This workshop uses a variety of case studies to present the most important aspects to consider for a sound determination of survival curves. Participants learn for each type of study how to design efficient experiments to determine the survival time of patients. The issues discussed include the timepoint selection, how to handle censoring (incomplete observations), competing risks, and the experiment size. The workshop also emphasizes the appropriate ways to analyze life data, how to compare curves, how to account for time-varying covariates and to adequately interpret and communicate the results obtained.