'Midwest biopharmaceutical statistics workshop' diaporamas de présentation

Statistical Considerations for Defining Cut Points and Titers in Anti-Drug Antibody (ADA) Assays

Statistical Considerations for Defining Cut Points and Titers in Anti-Drug Antibody (ADA) Assays. Ken Goldberg, Non-Clinical Statistics Johnson & Johnson Pharmaceutical Research & Development, LLC, Chesterbrook, PA. Outline. Introduction Why are ADA and IR assays important? Two case studies

1.54k views • 44 slides

By Brenda Crowe

Comparison of Bayesian and Frequentist Meta-Analytical Approaches for Analyzing Time to Event Data. By Brenda Crowe (Joint work with Monica Bennett, Karen Price, James Stamey and John Seaman Jr ) Midwest Biopharmaceutical Statistics Workshop 2014. Outline. Background/motivation

541 views • 41 slides

Applying Change Point Detection in Vaccine Manufacturing

Applying Change Point Detection in Vaccine Manufacturing. Hesham Fahmy, Ph.D. Merck & Co., Inc. West Point, PA 19486 hesham_fahmy@merck.com. Midwest Biopharmaceutical Statistics Workshop (MBSW) - MAY 23 - 25, 2011. Outline. Definitions Detection methods CUSUM and EWMA estimators

701 views • 40 slides

In-Vitro Screening for Combination Drug Discovery

492 views • 25 slides

Propensity Scoring and Beyond: Why? and How?

Propensity Scoring and Beyond: Why? and How?. Midwest Biopharmaceutical Statistics Workshop, 2009. Notation for Variables. y = observed outcome variable(s) x = observed baseline covariate(s) t = observed treatment assignment (usually non-random) z = unobserved explanatory variable(s).

400 views • 8 slides

Propensity Scoring and Beyond: Why? and How?

Propensity Scoring and Beyond: Why? and How?. Midwest Biopharmaceutical Statistics Workshop, 2009. Notation for Variables. y = observed outcome variable(s) x = observed baseline covariate(s) t = observed treatment assignment (usually non-random) z = unobserved explanatory variable(s).

308 views • 8 slides