Extends LAGO theory with fixed center effects to control confounding by indication, establishing consistency, asymptotic normality, and optimal intervention selection for continuous GLM and binary logistic outcomes even with few centers.
29 Figure 2: Total (top) and marginal (bottom) costs of the cubic cost function for each intervention component, component 1 (left) and component 2 (right)
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Addressing Confounding by Indication Through (Un)Measured Centre Characteristics in Learn-As-you-GO(LAGO) Trials
Extends LAGO theory with fixed center effects to control confounding by indication, establishing consistency, asymptotic normality, and optimal intervention selection for continuous GLM and binary logistic outcomes even with few centers.