Implementing CTA from Within Stata: Minimizing Imbalances on Patient Characteristics Between Treatment Groups in Randomized Trials (Invited)

Ariel Linden

Linden Consulting Group, LLC

Randomization ensures that treatment groups do not differ systematically in their characteristics, thereby reducing threats to validity that may otherwise explain differences in outcomes. Large observed imbalances in patient characteristics may indicate that selection bias is being introduced into the treatment allocation process. In this paper, I describe how the new Stata package for implementing CTA can be used for identifying potential imbalances in characteristics and their interactions when provisionally assigning each new participant to one or the other treatment group. The participant is then permanently assigned to the treatment group that elicits either no or less imbalance than if assigned to the alternate group.

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