Differences between open-interval estimation and standard methods lie mainly in the construction of the data sets, not in the application of statistical methods. The second message is that use of DLB data can make a critical difference to the quality of statistical results. This is particularly true when analyzing populations at highly disaggregated levels. In fertility estimates from small samples of women, sampling noise can drown out signal. This is a familiar problem, of course, but using more of the information inherent in DLB data can greatly improve the precision of statistical estimators.
More precise estimators make for better analysis and stronger conclusions.
DLB data are often available to researchers, but they are seldom used to their full potential.