<?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>0121-7488</journal-id>
<journal-title><![CDATA[Ciencia en Desarrollo]]></journal-title>
<abbrev-journal-title><![CDATA[Ciencia en Desarrollo]]></abbrev-journal-title>
<issn>0121-7488</issn>
<publisher>
<publisher-name><![CDATA[Universidad Pedagógica y Tecnológica de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-74882017000100021</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Estudio del efecto de la imputación de fallas en la estimación de la curva de supervivencia bajo censura a intervalo]]></article-title>
<article-title xml:lang="en"><![CDATA[Study of the effect of failure imputation in estimating the survival curve under interval censoring]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Jaramillo Elorza]]></surname>
<given-names><![CDATA[Mario César]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lopera Gómez]]></surname>
<given-names><![CDATA[Carlos Mario]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Colombia Escuela de Estadística ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional de Colombia Escuela de Estadística ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2017</year>
</pub-date>
<volume>8</volume>
<numero>1</numero>
<fpage>21</fpage>
<lpage>28</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-74882017000100021&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-74882017000100021&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-74882017000100021&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La mayoría de los análisis de supervivencia se basan en tiempos de falla exactos y observaciones censuradas a la derecha, utilizándose métodos ampliamente difundidos como el método de Kaplan-Meier (KM). Cuando los datos presentan censura a intervalo es necesario utilizar el método de Turnbull para estimar la función de supervivencia, sin embargo en la práctica se usa con frecuencia la imputación del tiempo de falla en este tipo de censura a través del punto medio del intervalo (PM), el extremo derecho del intervalo (ED) o generando un punto aleatorio dentro del mismo a través de la distribución uniforme. Este trabajo estudia a través de simulación el efecto de los tres tipos de imputación sobre la estimación de la curva de supervivencia en comparación al método desarrollado por Turnbull. Se analizaron diferentes escenarios de simulación basados en el tamaño de muestra y el tiempo entre visitas. En todos los escenarios de simulación las funciones estimadas usando imputación de datos difieren significativamente de la verdadera función de supervivencia S(t).]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Most survival analyzes are based on exact failure times and right censored observations, using methods widely known as the Kaplan-Meier (KM). When the data are interval censored is necessary to use the Turnbull's method to estimate the survival function, but in practice is often used the imputation of failure times in this kind of censorship through the midpoint of the interval, the right end of the interval or generating a random point within the interval using the uniform distribution. This paper studies through simulation the effect of three types of imputation on the estimates of the survival curve compared to the method developed by Turnbull. Different simulation scenarios based on the sample size and the time between visits were analyzed. In all scenarios simulation functions estimated using data imputation differ significantly from the true survival function S(t).]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Survival Analysis]]></kwd>
<kwd lng="en"><![CDATA[Interval Censoring]]></kwd>
<kwd lng="en"><![CDATA[Data Imputation]]></kwd>
<kwd lng="es"><![CDATA[Análisis de Supervivencia]]></kwd>
<kwd lng="es"><![CDATA[Censura de Intervalo]]></kwd>
<kwd lng="es"><![CDATA[Imputación de Datos]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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