Averaging Models have a large diffusion in several different areas of psychological and social research. They consist of a two parameters representation: a scale value for the subjective location of the stimulus on the response dimension and a weight for its importance in the integrated response. In the present paper we suggest a light but significant modification of the traditional formula used to represent the model in order to make clear some relevant properties of the model, which are essential to obtain unique and unbiased parameter estimations when a differential-weight averaging model is considered. This representation favors a superior understanding of the distinction between scale-values and importance-weights in order to realize what differences in weight could mean when we analyze empirical data coherent with an Averaging Model. © 2011 Springer Science+Business Media B.V.
Note on differential weight averaging models in functional measurement
VIDOTTO, GIULIO
2013
Abstract
Averaging Models have a large diffusion in several different areas of psychological and social research. They consist of a two parameters representation: a scale value for the subjective location of the stimulus on the response dimension and a weight for its importance in the integrated response. In the present paper we suggest a light but significant modification of the traditional formula used to represent the model in order to make clear some relevant properties of the model, which are essential to obtain unique and unbiased parameter estimations when a differential-weight averaging model is considered. This representation favors a superior understanding of the distinction between scale-values and importance-weights in order to realize what differences in weight could mean when we analyze empirical data coherent with an Averaging Model. © 2011 Springer Science+Business Media B.V.
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