MEIO - Summer School - Statistical Methods for Lifetime Data

Títol del curs: Statistical Methods for Lifetime Data

Impartit per: Luís A. Escobar. Department of Experimental Statistics, Louisiana State University. luis@lsu.edu

Llengua del curs: Castellà

Dates i horaris del curs: 9, 10, 11, 14, 15 de juny, de 3 a 7.

Aules FME: 003 / PC2

Tipus d'activitat i càrrega lectiva: Curs de 20 hores

Reconeixement acadèmic: 2,5 crèdits

Data de matrícula: del 10 al 30 de maig 2010

Temari: This is an applied course covering advanced statistical methods for lifetime data analysis; in particular, as they apply to Reliability and Survival analysis studies.
After completing this course, you will be able to:

• Recognize and properly deal with different kinds of reliability/survival data and properly interpret important reliability/survival metrics.
• Use nonparametric estimation to make inferences from multiply censored data with minimal assumptions.
• Use probability plots to identify appropriate parametric models and diagnose anomalies in failure-time data.
• Fit simple semi-parametric models including the standard techniques required when using proportional hazard models.
• Fit simple models to life data, and make inferences on important quantities like distribution quantiles, failure probabilities, and hazard functions.
• Use appropriate methods for computing confidence intervals from censored data.
• Identify and analyze data with multiple failure modes.
• Use regression analysis methods for the analysis of nonnormal-censored data that arise in field studies and in controlled life studies.
• Understand the relationship and tradeoffs between traditional failure-time data and degradation data.
• Conduct comparative studies using lifetime data.

Pla del curs:Part 1 (6 hours):

• Appropriate Time Scales for Life Data/Degradation Data.
• Lifetime Metrics: Failure Probability, Quantiles, Hazard.
• Simple Nonparametric Estimation, the Kaplan Meier Estimator.
• Introduction to Software (JMP/R).
• Weibull/Lognormal Distributions.

Part 2 (6 hours):

• Probability Plots, Detecting Multiple Modes of Failure.
• Parametric Modeling with Single Distribution.
• Multiple Failure Modes and Data Analysis.
• Semi-parametric Regression Analysis.
• Fitting the Proportional Hazard Regression Model.

Part 3 (5 hours):

• Failure Time Regression Analysis.
• rinciples of Acceleration Models and Acceleration Factors.
• Regression Life Test Data Analysis--One Variable.
• Regression Life Test Data Analysis--More than One Variable.
• Pitfalls in Accelerated/Regression Test Models.

Part 4 (3 hours):

• Accelerated Repeated Measures Degradation.
• Comparisons.
• Accelerated Destructive Degradation Test Data Analysis.