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In our original papers1,2, we argued that a population-based study should attempt to remove the effect of stratification by experimental design and analysis, such as by matching cases and controls for ethnicity and environmental covariates.
It has been postulated that carefully matching cases and controls by geographical origin could minimize the problem of population stratification in human populations, but even modest levels of genetic structure within a population can lead to false positive and false negative results [11], [35].
Crude ORs will be adjusted for general practice and/or LSOA by matching cases and controls.
In our study, we attempted to control for some of these confounding factors when matching cases and controls.
Although compromised by the small sample size, Lucidarme and colleagues [ 1] have done their best to minimize the impact of confounding factors by matching cases and controls.
By matching cases and controls on racial/ethnic group as well as medical institution, the likelihood that population stratification may have biased our results is low.
Similar(44)
The case-crossover design controls for seasonal effects and secular trends by matching case and control days in relatively small time windows (e.g., calendar month).
Therefore, it cannot be excluded that after matching case and control subjects for HbA1c levels, a trend in the prevalence of these complications will not be found.
Before training the classifier, we matched cases and controls by age, gender, and length of record, in order to avoid trivial classification.
All studies matched cases and controls ethnically.
No attempt to match cases and controls was made.
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