By contrast, a considerable amount of missing data in background variables may lead to biased estimates of population parameters (Rutkowski [2011]).
Regarding exposure to at least one CART activity (potential yes/no response) there was a considerable amount of missing data on CART participation (226 missing out of 1034).
The ability to complete self-assessments was not a requirement for inclusion, which resulted in a considerable amount of missing data.
This might result from a sequencing strategy, for example, that induces a certain quantity of missing data, but for which those data are more or less randomly distributed.
There was a moderate quantity of missing data for 1st trimester genitourinary testing and this was predominately in the non-Indigenous women from the primary catchment area.
Second, there was a considerable proportion of missing data.
Due to changes in documentation patterns, systems and items during the investigated period, a considerable percentage of missing data in several variables occurred.
Although this criterion is best to minimize the quantity of missing data, selection according to evolutionary distances allows a more judicious choice of sequences (see below).
The quantity of missing data is the main limitation of our investigation.
The quantity of missing data among those 351 subjects occasionally involved only 1 missing response in the entire instrument, with the majority of respondents missing 4 or less items.
Because the quantity of missing data varied by outcome and predictor, the number of piglets or litters used in each analysis is reported on each table of results.
