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Abstract. Latent variable modelling has gradually become an integral part of mainstream statistics and is currently used for a multitude of applications in different subject areas. Examples of ‘traditional’ latent variable models include latent class models, item–response models, common factor models, structural equation models, mixed or random effects models and covariate measurement error models. Although latent variables have widely different interpretations in different settings, the models have a very similar mathematical structure. This has been the impetus for the formulation of general modelling frameworks which accommodate a wide range of models. Recent developments include multilevel structural equation models with both continuous and discrete latent variables, multiprocess models and nonlinear latent variable models. 相似文献
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Making Things Clearer by Making Them Fuzzy: Counseling Illustrations of a Fuzzy Graphic Rating Scale
ROBERT G. L. PRYOR BERYL HESKETH MELANIE GLEITZMAN 《The Career development quarterly》1989,38(2):136-147
The development and evaluation of a fuzzy graphic rating scale to measure work attitudes are outlined. Some examples of participants' fuzzy responses are included to illustrate the potential usefulness of this approach. 相似文献
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