For evaluating monitoring and parent-adolescent communication, a set of scales addressing parental knowledge, control and solicitation, and adolescent disclosure was proposed by Kerr and Stattin (2000). Although these scales have been widely disseminated, their psychometric proprieties have often been found to be unsatisfactory, raising questions about their validity. The current study examines whether their poor psychometric properties, which are mainly attributed to the relatively poor conceptual quality of the items, could have been caused by the use of less-than-optimal analytical estimation methods. A cross-validation approach is used on a sample of 1071 adolescents. Maximum likelihood (ML) is compared with the diagonal weighted least squares (DWLS) method, which is suitable for Likert scales. The results of the DWLS approach lead to a more optimal fit than that obtained using ML estimation. The DWLS methodology may represent a useful option for researchers using these scales because it corrects for their unreliability.

Evidence of factorial validity of parental knowledge, control and solicitation, and adolescent disclosure scales: When the ordered nature of likert scales matters

Lionetti Francesca;
2016-01-01

Abstract

For evaluating monitoring and parent-adolescent communication, a set of scales addressing parental knowledge, control and solicitation, and adolescent disclosure was proposed by Kerr and Stattin (2000). Although these scales have been widely disseminated, their psychometric proprieties have often been found to be unsatisfactory, raising questions about their validity. The current study examines whether their poor psychometric properties, which are mainly attributed to the relatively poor conceptual quality of the items, could have been caused by the use of less-than-optimal analytical estimation methods. A cross-validation approach is used on a sample of 1071 adolescents. Maximum likelihood (ML) is compared with the diagonal weighted least squares (DWLS) method, which is suitable for Likert scales. The results of the DWLS approach lead to a more optimal fit than that obtained using ML estimation. The DWLS methodology may represent a useful option for researchers using these scales because it corrects for their unreliability.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/711299
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