<div dir="ltr"><p style="margin-bottom:0cm;line-height:100%"> <font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Prezados,</font></font></font></p> <p style="margin-bottom:0cm;line-height:100%"> <br> </p> <p style="margin-bottom:0cm;line-height:100%"> <font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Boa noite. Tenho o prazer de anunciar (abaixo) o próximo seminário do ciclo de palestras do programa de Pós-Graduação em Estatística do IMECC-Unicamp.</font></font></font></p> <p style="margin-bottom:0cm;line-height:100%"> <br> </p> <p style="margin-bottom:0cm;line-height:100%"> <font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Todos estão convidados.</font></font></font></p> <p style="margin-bottom:0cm;line-height:100%"> <br> </p> <p style="margin-bottom:0cm;line-height:100%"> <font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Cordialmente,</font></font></font></p> <p style="margin-bottom:0cm;line-height:100%"> <br> </p> <p style="margin-bottom:0cm;line-height:100%"> <font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Caio Azevedo (em nome da Comissão de Pós-Graduação)</font></font></font></p> <p align="justify" style="margin-bottom:0cm;line-height:100%"> <br> </p> <pre class="gmail-western" style="text-align:justify"><font color="#000000"><font face="Arial, sans-serif"><font style="font-size:11pt"><b>Local e data: </b>sala 225 no dia 01/09/17 as 14h00.</font></font></font></pre><p align="justify"> <br> <br> </p> <p align="justify"> <font color="#000000"><font face="Arial, sans-serif"><font style="font-size:11pt"><b>Apresentador:</b> Prof. Dr. Julio M. Stern</font></font></font></p> <p align="justify"> <br> <br> </p> <p align="justify"> <font color="#000000"><font face="Arial, sans-serif"><font style="font-size:11pt"><b>Título: </b>Haphazard Intentional Allocation and Rerandomization to Improve Covariate Balance in Experiments </font></font></font></p> <p align="justify"><br> <br> </p> <p align="justify"> <font color="#000000"><font face="Arial, sans-serif"><font style="font-size:11pt"><b>Autores:</b> by Marcelo S. Lauretto, Rafael B. Stern, Kari L. Morgan, Margaret H. Clark, Julio M. Stern </font></font></font></p> <p align="justify" style="margin-bottom:0cm"> <br> </p> <p align="justify" style="margin-bottom:0cm"> <br> </p> <p align="justify" style="margin-bottom:0cm"><font face="Arial, sans-serif"><font style="font-size:11pt"><font color="#000000"><b>Abstract:</b></font><font color="#000000"> In randomized experiments, a single random allocation can yield groups that differ meaningfully with respect to a given covariate. Furthermore, it is only feasible to use classical control procedures of allocation for a very modest number of covariates. As a response to this problem, Morgan and Rubin [11, 12] proposed an approach based on rerandomization (repeated randomization) to ensure that the final allocation obtained is balanced. However, despite the benefits of the rerandomization method, it has an exponential computational cost in the number of covariates, for fixed balance constraints. Here, we propose the use of haphazard intentional allocation, an alternative allocation method based on optimal balance of the covariates extended by random noise, see Lauretto et al. [7]. Our proposed method can be divided into a randomization and an optimization step. The randomization step consists of creating new (artificial) covariates according a specified distribution. The optimization step consists of finding the allocation that minimizes a linear combination of the imbalance in the original covariates and the imbalance in the artificial covariates. Numerical experiments on real and simulated data show a remarkable superiority of haphazard intentional allocation over the rerandomization method, both in terms of balance between groups and in terms of inference power. </font></font></font></p> <p align="justify" style="margin-bottom:0cm"><br> </p><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div><br></div><div>===================================================</div><div>Assistant Professor,</div><div>Department of Statistics, Institute of Mathematics,</div><div>Statistics and Scientific Computing,</div><div>University of Campinas, Brazil.</div><div><br></div><div>Office Phone : 55 - 19 - 35216060</div><div>Fax : 55 - 19 - 3521-6094</div><div><br></div><div>home-page : <a href="http://www.ime.unicamp.br/~cnaber/" target="_blank">http://www.ime.unicamp.br/~cnaber/</a></div><div>===================================================</div><div><br></div><div><div style="font-size:12.8px">"<span style="color:rgb(0,19,32);font-family:Trebuchet,Arial,Helvetica,sans-serif;font-size:14px;line-height:20px;text-align:justify;background-color:rgb(253,254,255)">Pois desde a criação do mundo os atributos invisíveis de Deus, seu eterno poder e sua natureza divina, têm sido observados claramente, podendo ser compreendidos por intermédio de tudo o que foi criado, de maneira que tais pessoas são indesculpáveis.</span><span style="color:rgb(0,19,32);font-family:Trebuchet,Arial,Helvetica,sans-serif;font-size:14px;line-height:20px;text-align:justify;background-color:rgb(253,254,255)"> </span><span style="font-size:12.8px">"</span></div><div style="font-size:12.8px"><span style="font-size:12.8px">Romanos 1:20</span></div></div></div></div></div></div></div> </div>