<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0103-6831</journal-id>
<journal-title><![CDATA[Estudos em Avaliação Educacional]]></journal-title>
<abbrev-journal-title><![CDATA[Est. Aval. Educ.]]></abbrev-journal-title>
<issn>0103-6831</issn>
<publisher>
<publisher-name><![CDATA[Fundação Carlos Chagas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0103-68312018000100156</article-id>
<article-id pub-id-type="doi">10.18222/eae.v0ix.3916</article-id>
<title-group>
<article-title xml:lang="pt"><![CDATA[Dados ausentes em avaliações educacionais: comparação de métodos de tratamento]]></article-title>
<article-title xml:lang="es"><![CDATA[Datos ausentes en evaluaciones educacionales: comparación de métodos de tratamiento]]></article-title>
<article-title xml:lang="en"><![CDATA[Missing data in educational assessment: a comparison of data treatment methods]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vinha]]></surname>
<given-names><![CDATA[Luis Gustavo do Amaral]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Laros]]></surname>
<given-names><![CDATA[Jacob Arie]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidade de Brasília Departamento de Estatística ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidade de Brasília Instituto de Psicologia ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2018</year>
</pub-date>
<volume>29</volume>
<numero>70</numero>
<fpage>156</fpage>
<lpage>187</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://educa.fcc.org.br/scielo.php?script=sci_arttext&amp;pid=S0103-68312018000100156&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://educa.fcc.org.br/scielo.php?script=sci_abstract&amp;pid=S0103-68312018000100156&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://educa.fcc.org.br/scielo.php?script=sci_pdf&amp;pid=S0103-68312018000100156&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="pt"><p><![CDATA[RESUMO Os dados ausentes s&#227;o comuns nas avalia&#231;&#245;es educacionais. Por isso, o uso de m&#233;todos adequados torna-se fundamental para reduzir o impacto da perda de informa&#231;&#227;o. O objetivo deste estudo &#233; comparar o desempenho de quatro m&#233;todos de tratamentos de dados ausentes (imputa&#231;&#227;o pela m&#233;dia, listwise deletion, m&#225;xima verossimilhan&#231;a e imputa&#231;&#227;o m&#250;ltipla), tendo como base o uso de modelos de regress&#227;o aplicados aos dados da avalia&#231;&#227;o educacional realizada no estado do Cear&#225;. Foram utilizadas informa&#231;&#245;es de 7.000 estudantes, simulando- -se diversos cen&#225;rios de acordo com o percentual e o tipo de aus&#234;ncia. A imputa&#231;&#227;o pela m&#233;dia apresentou o pior desempenho em todos os cen&#225;rios simulados e os demais m&#233;todos mostraram resultados semelhantes entre si. Verificou-se ainda que o uso de vari&#225;veis auxiliares na estima&#231;&#227;o por m&#225;xima verossimilhan&#231;a e imputa&#231;&#227;o m&#250;ltipla reduziu o vi&#233;s das estimativas de par&#226;metros importantes do modelo quando a aus&#234;ncia simulada n&#227;o &#233; ao acaso.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN: Los datos ausentes son comunes en las evaluaciones educacionales. Por ello el uso de m&#233;todos adecuados se hace fundamental para reducir el impacto de la p&#233;rdida de informaci&#243;n. El objetivo de este estudio es comparar el desempe&#241;o de cuatro m&#233;todos de tratamientos de datos ausentes (imputaci&#243;n por el promedio, listwise deletion, m&#225;xima verosimilitud e imputaci&#243;n m&#250;ltiple), en base al uso de modelos de regresi&#243;n aplicados a los datos de la evaluaci&#243;n educacional realizada en el estado de Cear&#225;. Se utilizaron informaciones de 7.000 estudiantes, simulando diversos escenarios de acuerdo al porcentual y al tipo de ausencia. La imputaci&#243;n por el promedio present&#243; el peor desempe&#241;o en todos los escenarios simulados y los dem&#225;s m&#233;todos mostraron resultados similares entre ellos. Tambi&#233;n se verific&#243; que el uso de variables auxiliares en la estimaci&#243;n por m&#225;xima verosimilitud e imputaci&#243;n m&#250;ltiple redujo el sesgo de las estimaciones de par&#225;metros importantes del modelo cuando la ausencia simulada no se debe a la casualidad.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Missing data are common in educational assessments. Using the appropriate methods has, therefore, become essential to reduce the impact of the loss of information. The present study aims to compare the performance of four methods for dealing with missing data (mean imputation, listwise deletion, maximum likelihood and multiple imputation), all based on regression models applied to the educational assessment of data collected in the State of Cear&#225;. Information about 7,000 students was used, simulating various scenarios according to the percentage and the type of the missing data. The mean imputation method showed the worst performance in all simulated scenarios and the other methods showed similar results among themselves. Moreover, the use of auxiliary variables in the estimation by maximum likelihood and multiple imputation proved to reduce the bias of estimates of some important parameters of the model, when the simulated missing data is not random.]]></p></abstract>
<kwd-group>
<kwd lng="pt"><![CDATA[Tratamento de Dados Ausentes]]></kwd>
<kwd lng="pt"><![CDATA[Avaliação da Educação]]></kwd>
<kwd lng="pt"><![CDATA[Desempenho Acadêmico]]></kwd>
<kwd lng="pt"><![CDATA[Simulação]]></kwd>
<kwd lng="es"><![CDATA[Tratamiento de Datos Ausentes]]></kwd>
<kwd lng="es"><![CDATA[Evaluación de la Educación]]></kwd>
<kwd lng="es"><![CDATA[Desempeño Académico]]></kwd>
<kwd lng="es"><![CDATA[Simulación]]></kwd>
<kwd lng="en"><![CDATA[Treatment of Missing Data]]></kwd>
<kwd lng="en"><![CDATA[Education Assessment]]></kwd>
<kwd lng="en"><![CDATA[Academic Performance]]></kwd>
<kwd lng="en"><![CDATA[Simulation]]></kwd>
</kwd-group>
</article-meta>
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