Although we attempted to control for this difference by including baseline smoking status in the regression models, residual confounding by smoking status cannot be excluded.
Residual confounding is possibly related to study design (non-randomized), although we attempted to control for several important variables.
Furthermore, although we attempted to control for major confounders in this study, residual confounding could not be ruled out.
Although we attempted to control for as many biases as possible, the retrospective design of our study presents inherent limitations.
Although we attempted to control for such effects, we cannot exclude that residual confounding is ultimately responsible for the associations we found between PFCs and depression.
Although we attempted to control for this by the inclusion of other health related variables in the model, we cannot exclude the possibility of residual confounding.
Although we attempted to control for a number of factors involved in cognitive function (e.g. age, education, computer experience, etc)., like any other epidemiological study, we cannot exclude the role of other potential confounders.
In addition, although we attempted to control for potential population stratification by restricting our sample to white women using principal components analysis, it is possible our analyses were subject to uncontrolled confounding from admixture.
Although we attempted to control for some of these variables through the use of multivariable models that included some of these factors (substance abuse and psychiatric diagnoses), residual confounding may remain.
Finally, a larger proportion of case-patients were of White race compared to controls, and PCOS patients were younger and had significantly higher BMI than controls, although we attempted to control for these parameters known to be associated with case-status in the logistic regression models.
