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Abstract

Dans cet article, nous étudions le comportement du coefficient alpha de Cronbach et de son écart type. Nous analysons de façon systématique les effets de la taille de l'échantillon, de la longueur de l'échelle, de la force des corrélations entre les items, et des multiples dimensions de l'échelle. Nous démontrons les effets positifs de la taille de l'échantillon sur l'écart type d'alpha, ainsi que les effets de la longueur de l'échelle et des corrélations entre items (effets dont les bénéfices se compensent) à la fois sur alpha et sur son écart type. Nos résultats confirment également l'adage suivant: l'hétérogénéité dans les items d'une matrice de covariance (e.g. du fait de l'existence de plusieurs dimensions ou d'items pauvres) influence négativement la fiabilité en réduisant la précision de l'estimation. Nous avons également étudié la question de « l'équilibre » relatif à la longueur de l'échelle, et montré les conditions pour lesquelles il est optimal d'ajouter zéro, un, ou plusieurs items à une échelle. Concernant les « meilleures pratiques », nous recommandons que les chercheurs reportent l'intervalle de confiance ou l'écart type en même temps que l'estimation du coefficient alpha.

Keywords

Mesure enquête fiabilité

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Résultats sur l'écart type de l' alpha de Cronbach,indice de fiabilité

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