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. 2016;111(515):936-942.
doi: 10.1080/01621459.2016.1200911. Epub 2016 Oct 18.

Comment

Qian Guan  1 , Eric B Laber  1 , Brian J Reich  1
Affiliations

Comment

Qian Guan et al. J Am Stat Assoc. 2016.
No abstract available

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Figures

Figure 1
Figure 1
Simulation results for single-stage trials under Settings 1 (left) and 2 (right). The boxplots show the differences between estimated and true causal effects over the 100 simulated datasets using the dependent Dirichlet process model (“DDP-GP”) and the semiparametric models with linear (“Ln”) and nonlinear (“NLn”) means and Gaussian (“Gs”) and mixture of Gaussians (“MGs”) residuals.
Figure 2
Figure 2
Simulation results for three-stage trials under Setting 3. The boxplots show the differences between estimated and true causal effects over the 100 simulated datasets using the Dependent Dirichlet Process model (“DDP-GP”) and the semiparametric models with linear (“Ln”) and nonlinear (“NLn”) means and Gaussian (“Gs”) and mixture of Gaussians (“MGs”) residuals.
Figure 3
Figure 3
Simulation results for three-stage trials under Setting 4. The boxplots show the differences between estimated and true causal effects over the 100 simulated datasets using the Dependent Dirichlet Process model (“DDP-GP”) and the semiparametric models with linear (“Ln”) and nonlinear (“NLn”) means and Gaussian (“Gs”) and mixture of Gaussians (“MGs”) residuals.
See this image and copyright information in PMC

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