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        "resumen" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Age-period-cohort models are usually used in descriptive epidemiological studies to analyze time trends in incidence or mortality&#46; The exact linear relationship between the three effects of these models has the effect of making the parameters of the full model impossible to estimate&#44; which is called <span class="elsevierStyleItalic">non-identifiability</span>&#46; In these notes two of the most frequently used methods to analyze age-period-cohort models will be explained&#46; One is based on penalty functions and the other on estimable functions &#40;drift and curvatures or deviation from linearity&#41;&#46; Both methods will be illustrated with two examples in wich temporal trends of breast and lung cancer mortality in women from Catalonia in Spain will be studied&#46; These examples show how the methods based on penalty functions tend to attribute the trend exclusively to a cohort effect&#46; Consequently&#44; the use of methods based on estimate functions is recommended&#46;</p>"
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Algunos aspectos metodológicos sobre los modelos edad-período-cohorte. Aplicación a las tendencias de mortalidad por cáncer
Some methodological aspects of age-period-cohort models. Application to cancer mortality trends
J.R. Gonzáleza, F.J. Llorcab, V. Morenoc,
Autor para correspondencia
v.moreno@ico.scs.es

Correspondencia: Dr. V. Moreno. Servei d'Epidemiologia i Registre del Càncer. Institut Català d'Oncologia. Avda. Gran Via, s/n. km 2,7. 08907 L'Hospitalet de Llobregat. Barcelona.
a Servicio de Prevención y Control del Cáncer. Institut Català d'Oncologia
b Departamento de Medicina Preventiva y Salud Pública. Facultad de Medicina de la Universidad de Cantabria
c Servicio de Epidemiología y Registro del Cáncer. Institut Català d'Oncologia
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            "correspondencia" => "<span class="elsevierStyleItalic">Correspondencia&#58;</span> Dr&#46; V&#46; Moreno&#46; Servei d&#39;Epidemiologia i Registre del C&#224;ncer&#46; Institut Catal&#224; d&#39;Oncologia&#46; Avda&#46; Gran Via&#44; s&#47;n&#46; km 2&#44;7&#46; 08907 L&#39;Hospitalet de Llobregat&#46; Barcelona&#46;"
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      "en" => array:1 [
        "titulo" => "Some methodological aspects of age-period-cohort models&#46; Application to cancer mortality trends"
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    "fechaRecibido" => "2001-12-28"
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          "palabras" => array:4 [
            0 => "Tendencias temporales"
            1 => "Modelos edad-per&#237;odo-cohorte"
            2 => "Epidemiolog&#237;a descriptiva"
            3 => "Mortalidad por c&#225;ncer"
          ]
        ]
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            0 => "Time trends"
            1 => "Age-period-cohort models"
            2 => "Descriptive epidemiology"
            3 => "Cancer mortality"
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      "es" => array:2 [
        "titulo" => "Resumen"
        "resumen" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Los modelos edad-per&#237;odo-cohorte suelen utilizarse en estudios de epidemiolog&#237;a descriptiva para analizar las tendencias de la incidencia y de la mortalidad para valorar el efecto temporal de la ocurrencia de un evento&#46; La relaci&#243;n lineal exacta existente entre estos tres efectos hace que los par&#225;metros del modelo completo no puedan estimarse&#44; lo que se denomina <span class="elsevierStyleItalic">no identificabilidad</span>&#46; En estas notas se explicar&#225;n dos de los m&#233;todos m&#225;s usados para analizar modelos edad-per&#237;odo-cohorte&#58; uno se basa en funciones de penalizaci&#243;n y otro en funciones estimables &#40;tendencia lineal y curvaturas o desviaciones&#41;&#46; Ambos m&#233;todos se ilustrar&#225;n con dos ejemplos en el que se analizan la tendencia temporal de la mortalidad por c&#225;ncer de pulm&#243;n y mama en las mujeres de Catalu&#241;a&#46; Estos ejemplos ilustran que los m&#233;todos basados en funciones de penalizaci&#243;n tienden a atribuir la tendencia a un efecto cohorte exclusivo&#44; por lo que se aconseja utilizar los m&#233;todos basados en funciones estimables&#46;</p>"
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      "en" => array:2 [
        "titulo" => "Abstract"
        "resumen" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Age-period-cohort models are usually used in descriptive epidemiological studies to analyze time trends in incidence or mortality&#46; The exact linear relationship between the three effects of these models has the effect of making the parameters of the full model impossible to estimate&#44; which is called <span class="elsevierStyleItalic">non-identifiability</span>&#46; In these notes two of the most frequently used methods to analyze age-period-cohort models will be explained&#46; One is based on penalty functions and the other on estimable functions &#40;drift and curvatures or deviation from linearity&#41;&#46; Both methods will be illustrated with two examples in wich temporal trends of breast and lung cancer mortality in women from Catalonia in Spain will be studied&#46; These examples show how the methods based on penalty functions tend to attribute the trend exclusively to a cohort effect&#46; Consequently&#44; the use of methods based on estimate functions is recommended&#46;</p>"
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Información del artículo
ISSN: 02139111
Idioma original: Español
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