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In summary, there may be some evidence to support the view that LIPA influences some CVD risk factors in certain populations, but more well-designed experiments with greater control of confounding factors are required to confirm this.
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A potential limitation of observational studies is inadequate control of confounding.
However, we show that including nonconfounding ancestry components in a matching criterion can lead to inaccurate matches, and hence to an improper control of confounding.
Control of confounding variables = region, HIV testing rate, and age.
The integration of diagnosis-based models with medication-based predictive models is expected to result in greater predictive power and more exhaustive control of confounding, by modelling the complex relationships between diagnosed comorbidities and the presence of any pharmacological therapy, taking into account its benefit and harms.
Proper control of confounding due to population stratification is crucial for valid analysis of case-control association studies.
Incomplete control of confounding may have influenced our findings.
We chose to use a videotaped lecture instead of a face-to-face lecture because we could have greater control over a variety of confounds such as tone of voice, speech content, and facial expression.
To control the effect of confounding variables, stepwise logistic regression was done.
A change in the HR estimates of 15% or greater would provide evidence of confounding.
To control for the effect of confounding variables, a stepwise logistic regression was done.
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