Interpretation summary for Regression with Life Data

Regression with life data performs regression with one or more predictors to help you understand how different factors and covariates affect the lifetime of your product or part. Regression with life data allows the use of censored data and different distributions. You can also estimate other percentiles besides the 50th percentile.

Regression with life data includes the following results:

A regression table, which describes the model that predicts product lifetime.
Goodness-of-fit measures, which help you assess the fit of different models.
Tables of percentiles and survival probabilities, which help you assess the reliability of the product.
Probability plots of the residuals (standardized and Cox-Snell), which help you assess whether the distribution and the equal shape/scale assumption are appropriate.

Data Description

Engineers want to assess the reliability of a redesigned compressor case of jet engines. To test the design, the engineers use a machine to throw a single projectile into each compressor case. After the projectile impact, engineers inspect the compressor every twelve hours for failure.

The engineers perform regression with life data to evaluate the relationship between the case design, the projectile weight, and the failure time. They also want to estimate the failure times at which they can expect 1% and 5% of the engines to fail. The engineers use a Weibull distribution to model the data.

The model includes Design as a categorical factor and Weight as a continuous factor.

Data: JetEngineReliability.MTW