We have attempted to account for this by controlling for trial group assignment in our multivariable regression models, by the possibility of residual confounding remains.
Each male received a life-time score of directed song rate by taking the random effect estimates (BLUPs) of song rate from a linear mixed effect model, controlling for trial batch, cohort effects and whether birds were reared in unisexual or mixed sex groups (all focal males were raised in unisexual groups) as fixed effects.
In the basic models we controlled for trial arm, maternal and paternal age and child's sex and age.
The regression models will be controlled for trial arm (intervention vs control group), patient group (high risk or established CVD), and several personal characteristics: age, sex, ethnicity, marital status, SES, patient activation, therapy adherence, and depressive symptoms.
Fully adjusted models controlled for trial membership (E vs. E + P), a within-trial indicator for treatment arm (active vs. placebo), time on study (days), continuous temperature (degrees centigrade), as well as the participant and neighborhood characteristics that we defined previously.
Surprisingly, while many fMRI researchers routinely take pains to eliminate response accuracy differences as a potential confound (e.g., by only analyzing trials with correct responses), relatively few studies have systematically controlled for trial-by-trial RT differences [e.g.], [5], [7,47]; a recent survey of 170 fMRI studies found that only 9% had explicitly modeled RT [3].
Therefore, controlling for in-trial changes in the covariates analyzed was not possible.
Results are also controlled for different trial lengths.
We attribute this component of trial-over-trial-depression to CS-linked plasticity that occurs during trial-over-trial behavioral learning, because it persists after we control for same-trial facilitation.
One way to decrease this unavoidable confound is to intermix trials controlling for circumference and surface.
Well-designed and conducted studies, controlling for the complexities of surgical trials are needed.
