Burn-in testing is used to screen out units or systems with short lifetimes. Units or systems that survived a burn-in test may give rise to left truncated data that is either right or interval censored.

*Left truncated and right censored data*

Tobias and Trindade reported in their 2012 book *Applied Reliability* on field failure times of units that survived a burn-in test of 5000 hours (Example 4.6, p. 109). These field failure times represent an example of left truncation in combination with *right* censoring.

*Left truncated and interval censored data*

Meeker and Escobar described in their 1998 book *Statistical Methods for Reliability Data* a field-tracking study of units that survived a 1000 hours burn-in test (Example 11.11, pp. 269-270). The data in Meeker and Escobar’s study is an example of left truncation in combination with *interval* censoring.

Model fitting using maximum likelihood optimization

The R code fits a Weibull (or lognormal) model to left truncated data that is either right or interval censored. The fitting of these models is done by log-likelihood optimization (using the *optim* function in R).

Continue reading R code for modeling with left truncated and right/interval censored data