<?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>1409-2433</journal-id>
<journal-title><![CDATA[Revista de Matemática Teoría y Aplicaciones]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. Mat]]></abbrev-journal-title>
<issn>1409-2433</issn>
<publisher>
<publisher-name><![CDATA[Centro de Investigaciones en Matemática Pura y Aplicada (CIMPA) y Escuela de Matemática, San José, Costa Rica.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1409-24332020000200383</article-id>
<article-id pub-id-type="doi">10.15517/rmta.v27i2.33677</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Robustez de los índices de ajuste del análisis factorial confirmatorio a los valores extremos]]></article-title>
<article-title xml:lang="en"><![CDATA[Robustness of confirmatory factor analysis fit indices to outliers]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rojas-Torres]]></surname>
<given-names><![CDATA[Luis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Costa Rica Escuela de Matemática ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Costa Rica</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2020</year>
</pub-date>
<volume>27</volume>
<numero>2</numero>
<fpage>383</fpage>
<lpage>404</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_arttext&amp;pid=S1409-24332020000200383&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_abstract&amp;pid=S1409-24332020000200383&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_pdf&amp;pid=S1409-24332020000200383&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El objetivo de este trabajo es evaluar la robustez de varios índices de ajuste del Análisis Factorial Confirmatorio (SRMR, RMSEA, TLI, CFI y GFI) a la presencia de valores extremos. Para el alcance del objetivo se planteó un estudio de simulaciones con 3× 4 × 2 condiciones: tamaño de muestra (100, 200 y 500), porcentaje de valores extremos (0%, 1%, 5% y 10%) y número de variables con valores extremos (1 y 2). Los conjuntos de datos base (0% de valores extremos) por tamaño de muestra, fueron simulados a partir de una distribución que se ajustaba a un AFC con tres factores correlacionados. Los conjuntos de datos con valores extremos se crearon a partir de la sustitución de observaciones en los conjuntos de datos base. Luego, en cada conjunto de datos se estimó un AFC con tres factores correlacionados. Se obtuvo que con los puntos de corte clásicos de los índices de ajuste, todos estos fueron robustos a la presencia de datos extremos en conjuntos de datos de 200 y 500 observaciones. Con 100 observaciones se obtienen índices robustos pero considerando puntos de corte ajustados a la estructura factorial y el tamaño muestral trabajado.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The goal of this work is to evaluate the robustness of several Confirmatory Factor Analysis fit indices (SRMR, RMSEA, TLI, CFI and GFI) to the precense of outliers. For this purpose, it was planed a simulation study with 3 × 4 × 2 conditions: sample size (100, 200 and 500), outliers percentage (0%, 1%, 5% and 10%) and number of variables with outliers (1 and 2). The baseline data sets (0% of outliers) by sample size were simulated from a distribution which fit to a CFA with three factors correlated. Data bases with outliers were created from substitution of observations in baseline data sets. Later, in every data base was estimated a CFA with three factors correlated. It was obtained that all indices with classical cutoffs were robust to outliers with sample sizes of 200 and 500. With 100 observations, it was obtained that fit indexes were robust to outliers, but considering cutoffs adjusted by the factorial structure and the sample size.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[valores extremos]]></kwd>
<kwd lng="es"><![CDATA[análisis factorial confirmatorio]]></kwd>
<kwd lng="es"><![CDATA[robustez]]></kwd>
<kwd lng="es"><![CDATA[estudio de simulación]]></kwd>
<kwd lng="es"><![CDATA[error Monte Carlo.]]></kwd>
<kwd lng="en"><![CDATA[outliers]]></kwd>
<kwd lng="en"><![CDATA[confirmatory factor analysis]]></kwd>
<kwd lng="en"><![CDATA[robustness]]></kwd>
<kwd lng="en"><![CDATA[simulations study]]></kwd>
<kwd lng="en"><![CDATA[Monte Carlo error.]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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