Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/166031 
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Title: 

Treatment allocation for linear models with covariate information

The document was removed on behalf of the author(s)/ the editor(s).

Year of Publication: 
2017
Series/Report no.: 
FAU Discussion Papers in Economics No. 14/2017
Publisher: 
Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute for Economics, Nürnberg
Abstract: 
This paper analyses optimal treatment allocation of experimental units to treatment and control group. 'Optimal' means that the allocation of treatments should balance covariates across treatment and control group in a way that minimizes the variance of the treatment estimator in a given linear model. This paper shows the benefits as well as the limits of this approach. In particular, it presents a sample size formula as well as several simulations to give some intuition on the minimum as well as the maximum benefits of this approach compared to random allocation as well as to alternative methods of treatment allocation.
Subjects: 
experiment design
treatment allocation
JEL: 
C90
C61
Document Type: 
Working Paper

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The document was removed on behalf of the author(s)/ the editor(s) on: September 28, 2017


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