<?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>0120-1751</journal-id>
<journal-title><![CDATA[Revista Colombiana de Estadística]]></journal-title>
<abbrev-journal-title><![CDATA[Rev.Colomb.Estad.]]></abbrev-journal-title>
<issn>0120-1751</issn>
<publisher>
<publisher-name><![CDATA[Departamento de Estadística - Universidad Nacional de Colombia.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0120-17512006000200007</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Precisiones en la teoría de los modelos logísticos]]></article-title>
<article-title xml:lang="en"><![CDATA[Accuracies in the Theory of the Logistic Models]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[LLINÁS]]></surname>
<given-names><![CDATA[HUMBERTO JESÚS]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Universidad del Norte  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
</aff>
<pub-date pub-type="pub">
<day>05</day>
<month>12</month>
<year>2006</year>
</pub-date>
<pub-date pub-type="epub">
<day>05</day>
<month>12</month>
<year>2006</year>
</pub-date>
<volume>29</volume>
<numero>2</numero>
<fpage>239</fpage>
<lpage>265</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-17512006000200007&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-17512006000200007&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-17512006000200007&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Se estudian los modelos logísticos, como una clase de modelos lineales generalizados (MLG). Se demuestra un teorema sobre la existencia y unicidad de las estimaciones de máxima verosimilitud (abreviadas por ML) de los parámetros logísticos y el método para calcularlas. Con base en una teoría asintótica para estas ML-estimaciones y el vector score, se encuentran aproximaciones para las diferentes desviaciones &sigma;2 log L, siendo L la función de verosimilitud. A partir de ellas se obtienen estadísticas para distintas pruebas de hipótesis, con distribución asintótica chi-cuadrada. La teoría asintótica se desarrolla para el caso de variables independientes y no idénticamente distribuidas, haciendo las modificaciones necesarias para la conocida situación de variables idénticamente distribuidas. Se hace siempre la distinción entre datos agrupados y no agrupados.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[The logistic models are studied, as a kind of generalized lineal models. A theorem is showed about existence and uniqueness of ML-estimates of the estimation of the logistic regression coefficients and the method in order to calculate it. According to an asymptotic theory for this ML-estimates and the score vector, it has been founded approaching for different deviations &sigma;2 log L (in this expression, L is the function of maximum likelihood). In consequence, we have gotten statistics for different hypotheses test which is asymptotically chi-square. The asymptotic theory is developed for the independent variables and no distributed identically variables. It is made the difference between ungrouped and grouped data.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[variable de respuesta binaria]]></kwd>
<kwd lng="es"><![CDATA[modelo lineal generalizado]]></kwd>
<kwd lng="es"><![CDATA[teoría asintótica]]></kwd>
<kwd lng="en"><![CDATA[Binary response]]></kwd>
<kwd lng="en"><![CDATA[Generalized linear model]]></kwd>
<kwd lng="en"><![CDATA[Asymptotic theory]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[   <font size="2" face="verdana">        <p>    <center><b><font size="4">Precisiones en la teor&iacute;a de los modelos log&iacute;sticos</font></b></center></p>        <p>    <center><b><font size="3">Accuracies in the Theory of the Logistic Models</font></b></center></p>        <p>    <center>HUMBERTO JES&Uacute;S LLIN&Aacute;S<sup>1</sup></center></p>        <p><sup>1</sup>Universidad del Norte, Barranquilla, Colombia, Profesor. E-mail: <a href="mailto:hllinas@uninorte.edu.co">hllinas@uninorte.edu.co</a></p>    <hr size="1">        <p>    <center><b>Resumen</b></center></p>        ]]></body>
<body><![CDATA[<p>Se estudian los modelos log&iacute;sticos, como una clase de modelos lineales  generalizados (MLG). Se demuestra un teorema sobre la existencia y unicidad  de las estimaciones de m&aacute;xima verosimilitud (abreviadas por ML) de los  par&aacute;metros log&iacute;sticos y el m&eacute;todo para calcularlas. Con base en una teor&iacute;a  asint&oacute;tica para estas ML-estimaciones y el vector score, se encuentran aproximaciones  para las diferentes desviaciones &sigma;2 log <i>L</i>, siendo <i>L</i> la funci&oacute;n de  verosimilitud. A partir de ellas se obtienen estad&iacute;sticas para distintas pruebas  de hip&oacute;tesis, con distribuci&oacute;n asint&oacute;tica chi-cuadrada. La teor&iacute;a asint&oacute;tica se  desarrolla para el caso de variables independientes y no id&eacute;nticamente distribuidas,  haciendo las modificaciones necesarias para la conocida situaci&oacute;n  de variables id&eacute;nticamente distribuidas. Se hace siempre la distinci&oacute;n entre  datos agrupados y no agrupados.</p>        <p><b><i>Palabras clave:</i></b> variable de respuesta binaria, modelo lineal generalizado,  teor&iacute;a asint&oacute;tica.</p>    <hr size="1">        <p>    <center><b>Abstract</b></center></p>        <p>The logistic models are studied, as a kind of generalized lineal models.  A theorem is showed about existence and uniqueness of ML-estimates of the  estimation of the logistic regression coefficients and the method in order to  calculate it. According to an asymptotic theory for this ML-estimates and  the score vector, it has been founded approaching for different deviations  &sigma;2 log <i>L</i> (in this expression, <i>L</i> is the function of maximum likelihood). In  consequence, we have gotten statistics for different hypotheses test which is  asymptotically chi-square. The asymptotic theory is developed for the independent  variables and no distributed identically variables. It is made the  difference between ungrouped and grouped data.</p>        <p><b><i>Key words:</i></b> Binary response, Generalized linear model, Asymptotic theory.</p>    <hr size="1">        <p>Texto completo disponible en <a href="pdf/rce/v29n2/v29n2a07.pdf">PDF</a></p>    <hr size="1">        <p><b><font size="3">Referencias</font></b></p>        <!-- ref --><p>1. Agresti, A. (1990),<i> Categorical Data Analysis</i>, 2nd edn, John Wiley and Sons, Inc.,  New York.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000021&pid=S0120-1751200600020000700001&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p>2. C.F,M. &amp; McFadden, D., eds (1974),&quot;Conditional logit analysis of qualitative choice behavior&quot;,<i>Frontiers in Econometrics Applications</i>, MA: MIT Press, Cambridge, pp. 105-142.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000022&pid=S0120-1751200600020000700002&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p>3. Dobson, A. J. (2002), <i>An Introduction to Generalized Linear Models</i>, 2 edn, Chapman  &amp; Hall, London.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000023&pid=S0120-1751200600020000700003&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font size="2" face="verdana">4. Goodman, L. (1971), &quot;The Analysis of Multidimensional Contingency Tables: Stepwise  Procedures and Direct Estimation Methods for Building Models for Multiple  Classifications&quot;, <i>Technometrics</i> (13), 33- 61.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000024&pid=S0120-1751200600020000700004&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font size="2" face="verdana">5. Mc Cullagh, P. (1983), &quot;Quasi-likelihood Functions&quot;, <i>Annals of Statistics</i> (11), 59-   67.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000025&pid=S0120-1751200600020000700005&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p>6. Mc Cullagh, P. & Nelder, J. (1983), <i>Generalized Linear Models</i>, 2 edn, Chapman  and Hall, London.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000026&pid=S0120-1751200600020000700006&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p>7. Rao, C. (1973), <i>Linear Statistical Inference and its Applications</i>, 2 edn, JohnWiley  and Sons, Inc., New York.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000027&pid=S0120-1751200600020000700007&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font size="2" face="verdana">8. Theil, H. (1970), &quot;On the Estimation of Relationships Involving Qualitative Variables&quot;,  <i>Amer. J. Sociol.</i> (76), 103- 154.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000028&pid=S0120-1751200600020000700008&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font size="2" face="verdana">9. Wedderburn, R. (1974), &quot;Quasi-likelihood Functions, Generalized linear models  and the Gauss-Newton Method&quot;, <i>Biometrika</i> (61), 439- 447.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000029&pid=S0120-1751200600020000700009&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font size="2" face="verdana">10. Wedderburn, R. (1976), &quot;On The Existence and Uniqueness of the Maximum  Likelihood Estimates for Certain Generalized Linear Models&quot;, <i>Biometrika</i>  (63), 27- 32.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000030&pid=S0120-1751200600020000700010&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p>11. Zacks, S. (1971), <i>The Theory of Statistical Inference</i>, 2nd edn, John Wiley and  Sons Inc., New York.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000031&pid=S0120-1751200600020000700011&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --> ]]></body><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Agresti]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<source><![CDATA[Categorical Data Analysis]]></source>
<year>1990</year>
<edition>2nd</edition>
<publisher-loc><![CDATA[New York ]]></publisher-loc>
<publisher-name><![CDATA[John Wiley and Sons, Inc]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[C.F]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[McFadden]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang="en"><![CDATA["Conditional logit analysis of qualitative choice behavior"]]></article-title>
<source><![CDATA[Frontiers in Econometrics Applications]]></source>
<year>1974</year>
<page-range>105-142</page-range><publisher-loc><![CDATA[Cambridge ]]></publisher-loc>
<publisher-name><![CDATA[MA: MIT Press]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Dobson]]></surname>
<given-names><![CDATA[A. J]]></given-names>
</name>
</person-group>
<source><![CDATA[An Introduction to Generalized Linear Models]]></source>
<year>2002</year>
<edition>2</edition>
<publisher-loc><![CDATA[London ]]></publisher-loc>
<publisher-name><![CDATA[Chapman & Hall]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Goodman]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</person-group>
<article-title xml:lang="en"><![CDATA[" The Analysis of Multidimensional Contingency Tables: Stepwise Procedures and Direct Estimation Methods for Building Models for Multiple Classifications"]]></article-title>
<source><![CDATA[Technometrics]]></source>
<year>1971</year>
<volume>13</volume>
<page-range>33-61</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mc Cullagh]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
</person-group>
<article-title xml:lang="en"><![CDATA[" Quasi-likelihood Functions"]]></article-title>
<source><![CDATA[Annals of Statistics]]></source>
<year>1983</year>
<numero>11</numero>
<issue>11</issue>
<page-range>59- 67</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mc Cullagh]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Nelder]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<source><![CDATA[Generalized Linear Models]]></source>
<year>1983</year>
<edition>2</edition>
<publisher-loc><![CDATA[London ]]></publisher-loc>
<publisher-name><![CDATA[Chapman and Hall]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rao]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
</person-group>
<source><![CDATA[Linear Statistical Inference and its Applications]]></source>
<year>1973</year>
<edition>2</edition>
<publisher-loc><![CDATA[New York ]]></publisher-loc>
<publisher-name><![CDATA[JohnWiley and Sons, Inc]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Theil]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang="en"><![CDATA[" On the Estimation of Relationships Involving Qualitative Variables"]]></article-title>
<source><![CDATA[Amer. J. Sociol]]></source>
<year>1970</year>
<numero>76</numero>
<issue>76</issue>
<page-range>103-154</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wedderburn]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
</person-group>
<article-title xml:lang="en"><![CDATA[" Quasi-likelihood Functions, Generalized linear models and the Gauss-Newton Method"]]></article-title>
<source><![CDATA[Biometrika]]></source>
<year>1974</year>
<numero>61</numero>
<issue>61</issue>
<page-range>439-447</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wedderburn]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
</person-group>
<article-title xml:lang="en"><![CDATA[" On The Existence and Uniqueness of the Maximum Likelihood Estimates for Certain Generalized Linear Models"]]></article-title>
<source><![CDATA[Biometrika]]></source>
<year>1976</year>
<numero>63</numero>
<issue>63</issue>
<page-range>27-32</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zacks]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<source><![CDATA[The Theory of Statistical Inference]]></source>
<year>1971</year>
<edition>2</edition>
<publisher-loc><![CDATA[New York ]]></publisher-loc>
<publisher-name><![CDATA[John Wiley and Sons Inc]]></publisher-name>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
