In previously
reported work a method for applying a lower bound to the variation induced by
the Monte Carlo effect was trialled.
This is implemented in the widely used probabilistic genotyping system,
STRmix™. The approach did not give the
desired 99% coverage.
However, the method for assigning the lower
bound to the MCMC variability is only one of a number of layers of
conservativism applied in a typical application. We tested all but one of these sources of
variability collectively and term the result the near global coverage. The near global coverage for all tested
samples was greater than 99.5% for inclusionary average LRs of known
donors. This suggests that when included
in the probability interval method the other layers of conservativism are more
than adequate to compensate for the intermittent underperformance of the MCMC
variability component. Running for
extended MCMC accepts was also shown to result in improved precision.
Funding
US National Institute of Justice - Grant No. 2020-DQ-BX-0022