<div dir="ltr"><div>Ecacarva,</div><div><br></div><div>Boa noite.</div><div><br></div><div>Ecacarva,</div><div><br></div><div>Tudo depende dos seus dados. Uma vez fiz uns teste para os pacotes Amelia, VIM e mi (Imputação múltipla), e observei que amelia tinha os melhores ajustes, achei interessante pois esperava que o mi tivesse os melhores ajustes. Entretanto, acabei usando os dados desbalanceados mesmo, como tinha dados longitudinais fiz a análise como um modelo misto. Isso é fácil de você testar. Crie um banco de dados exclua alguns valores e teste qual desse métodos te da os melhores ajustes. Segue alguns artigos falando sobre dados faltantes.</div><div><br></div><div><a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016756/">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016756/</a><br></div><a href="http://www.statisticalhorizons.com/wp-content/uploads/MissingDataByML.pdf">http://www.statisticalhorizons.com/wp-content/uploads/MissingDataByML.pdf</a><br><div><br></div><div>Att.,</div><div><br></div><div>Alisson</div></div><div class="gmail_extra"><br><div class="gmail_quote">2016-04-14 21:39 GMT-03:00 ecacarva [via R-br] <span dir="ltr"><<a href="mailto:ml-node+s2285057n4665950h86@n4.nabble.com" target="_blank">ml-node+s2285057n4665950h86@n4.nabble.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div dir="ltr">Valeu pessoal ! Vou analisar e testar o máximo nos meus dados.<div><br></div><div>Alisson, fiquei especialmente interessado em tratar missing com <span style="font-size:12.8px"> </span><span style="font-size:12.8px">modelos mistos generalizados, já que você disse que é um método mais moderno.</span></div><div><span style="font-size:12.8px"><br></span></div><div><span style="font-size:12.8px">Você tem algum exemplo reprodutível ou literatura com exemplos ?</span></div><div><span style="font-size:12.8px"><br></span></div><div><span style="font-size:12.8px">Obrigado</span></div></div><div class="gmail_extra"><br><div class="gmail_quote">Em 14 de abril de 2016 13:07, Jônatan [via R-br] <span dir="ltr"><<a href="http:///user/SendEmail.jtp?type=node&node=4665950&i=0" rel="nofollow" link="external" target="_blank">[hidden email]</a>></span> escreveu:<br><blockquote style="border-left:2px solid #cccccc;padding:0 1em" class="gmail_quote">
<div dir="ltr">no link abaixo há uma lista de Pacotes do R relacionados a MI, organizada pelo autor do livro Flexible Imputation of Missing Data:<div><a href="http://www.stefvanbuuren.nl/mi/Software.html" rel="nofollow" link="external" target="_blank">http://www.stefvanbuuren.nl/mi/Software.html</a><br></div><div><br></div><div>Att.</div></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div>2016-04-11 11:11 GMT-03:00 Elias Carvalho <span dir="ltr"><<a href="http:///user/SendEmail.jtp?type=node&node=4665948&i=0" rel="nofollow" link="external" target="_blank">[hidden email]</a>></span>:<br></div></div><blockquote style="border-left:2px solid #cccccc;padding:0 1em" class="gmail_quote"><div><div><div dir="ltr">Alguém da lista poderia me da uma dica de como tratar dados missing ?<div><br></div><div>Multiple Imputation seria a técnica mais moderna ?</div><div><br></div><div>Obrigado<span><font color="#888888"><br clear="all"><div><br></div><div><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div>Elias</div></div></div></div></div></div>
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