MIXTURE MODEL ANALYSIS OF COMPLEX SAMPLES

We investigate the effects of a complex sampling design on the estimat ion of mixture models. An approximate or pseudo likelihood approach is proposed to obtain consistent estimates of class-specific parameters when the sample arises from such a complex design. The effects of igno ring the sample design are demonstrated empirically in the context of an international value segmentation study in which a multinomial mixtu re model is applied to identify segment-level value rankings. The anal ysis reveals that ignoring the sample design results in both an incorr ect number of segments as identified by information criteria and biase d estimates of segment-level parameters.