I have approximately 1000 run-life examples (time to fail data) for equipment. However, the number of failures is quite low relative to the number of units that are censored (95% are right - censored, majority are unobserved failures, a small proportion are failures from a competing risk).
I am interested in some time-varying covariates that are quite computationally expensive to calculate for the run-life length. I am doing this retrospectively with sensor data. To reduce the computational effort, it was proposed that we could downsample those with right censoring, however this to me would bias the hazard calculation (#no. of units working / total units available). Am I right, or is this an acceptable practice under certain assumptions? And what other choices do I have with such highly censored data.