Estimation is performed using penalized least squares methods to control for overfitting.
Our objective was to review methods to control for observed confounding, as well as unobserved confounding.
Third, we used panel data methods to control for the estimation bias associated with unobserved firm-level heterogeneity.
Using propensity score methods to control for selection, we do not find evidence of differential outcomes by admission to SU or other wards.
The considerations in designing this study were to use either design-based or analysis-based methods to control for characteristics that differed at baseline between treatment groups.
In practice, most analysts use econometric methods to control for an array of observable characteristics that vary across education levels, such as parental background and labor market experience.
Difficulty in finding appropriate data, as well as methods to control for selection and income inequality have hampered their efforts at answering this question.
For the main outcome measure, we analyzed longitudinal changes across visits for MADRS and YMRS sums using generalized estimating equation (GEE) methods to control for the correlation within the subjects at the five study time points.
We use matching methods to control for a rich set of adolescent and family characteristics by estimating the treatment effects, conditional on unconfoundedness, of multiple personality traits at the same time (Wooldridge, Econometric Analysis of Cross Section and Panel Data, 2010).
Finally, in contrast to the multiple-payers structure in the U.S. health care system, where most extant PID research was conducted, the universal health insurance and the single-payer system in Taiwan offer a favorable research setting that prevents the use of cumbersome methods to control for variation and change in health insurance coverage.
The remaining studies used multivariable methods to control for potential confounders associated with the outcomes.
