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On the other hand, to date, most research providing population-based estimates [ 4- 7] relies on hospital data samples that are weighted to extrapolate to national-level estimates and are, therefore, particularly vulnerable to sampling bias [ 16].
The method is vulnerable to sampling error: by chance, related inversely to sample size, important characteristics of the sample such as gender or age distributions may not well reflect those of the whole population.
We have shown that Armitage's trend test [ 9], the most popular statistical strategy implemented in the current literature of GWAS with a case control setting, is highly vulnerable to sampling schemes and genetic structure embedded in the samples.
In addition MCOD data is not vulnerable to sampling bias.
These data are weighted to extrapolate to national-level estimates and are therefore particularly vulnerable to sampling bias.
Secondly, since this method uses only ten high power fields, the results are vulnerable to sampling bias.
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Third, the employer-sponsored health insurance question described here is only asked to workers and thus my findings may be vulnerable to sample-selection bias.
However, when using such complex samples, HPLC systems are vulnerable to sample carry-over.
However, this technique requires purification following each step and is therefore laborious and vulnerable to sample loss [ 19, 29].
Previous studies also revealed that some proteins are more vulnerable to sample handling than others [ 14, 15].
Cross-sectional data are vulnerable to sample bias, especially when respondents are not randomly selected, as was the case in 9 of 30 (30%) studies.
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