Optimal Individualized Treatments Under Limited Resources

  • Alexander R. Luedtke
  • Mark J. van der Laan
Part of the Springer Series in Statistics book series (SSS)


In this chapter, we consider a resource constraint under which there is a maximum proportion of the population that can be treated. Given this constraint, we develop a root-n rate estimator for the optimal resource-constrained (R-C) value and corresponding confidence intervals. We show that our estimator is efficient among all regular and asymptotically linear estimators in our nonparametric model \(\mathcal{M}\) under conditions. When the baseline covariates are continuous and the resource constraint is active, i.e., when the optimal R-C value is less than the optimal unconstrained value, these conditions are more reasonable than the nonexceptional law assumption needed for regular estimation of the optimal unconstrained value discussed in Chap.  22


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Vaccine and Infectious Disease DivisionFred Hutchinson Cancer Research CenterSeattleUSA
  2. 2.Division of Biostatistics and Department of StatisticsUniversity of California, BerkeleyBerkeleyUSA

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