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Papers by francesca bassi

International Journal of Market Research, 2011

Measurement scales are a crucial instrument for research in marketing in order to measure unobser... more Measurement scales are a crucial instrument for research in marketing in order to measure unobservable variables as attitudes, opinions, beliefs. In using, evaluating, or developing multi-item scales, a number of guidelines and procedures are recommended to ensure that the measure is psychometrically robust. These procedures have been outlined in the psychometric literature since the late seventies and are composed of steps which refer to construct definition, domain and scale validity, reliability, dimensionality, and generalizability. Various statistical instruments are used in the scale developing process, these almost always refer to metric variables (interval or ratio scales). Items forming scales are instead rarely measured on an metric level, frequently items are ordinal, in some rare cases, nominal. In this paper, it is shown how the implementation of latent class analysis may improve the process of measurement scale development since it explicitly considers that items generate ordinal or even nominal variables. Specifically, applying appropriate latent class models allows to assess scale validity and reliability more soundly than the methods traditionally used.

International Journal of Market Research, 2011

Measurement scales are a crucial instrument for research in marketing in order to measure unobser... more Measurement scales are a crucial instrument for research in marketing in order to measure unobservable variables as attitudes, opinions, beliefs. In using, evaluating, or developing multi-item scales, a number of guidelines and procedures are recommended to ensure that the measure is psychometrically robust. These procedures have been outlined in the psychometric literature since the late seventies and are composed of steps which refer to construct definition, domain and scale validity, reliability, dimensionality, and generalizability. Various statistical instruments are used in the scale developing process, these almost always refer to metric variables (interval or ratio scales). Items forming scales are instead rarely measured on an metric level, frequently items are ordinal, in some rare cases, nominal. In this paper, it is shown how the implementation of latent class analysis may improve the process of measurement scale development since it explicitly considers that items generate ordinal or even nominal variables. Specifically, applying appropriate latent class models allows to assess scale validity and reliability more soundly than the methods traditionally used.