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  • English  (4)
  • Temme, Dirk  (4)
  • Open access  (4)
  • 1
    Online Resource
    Online Resource
    Structural Equation Models for Finite Mixtures : Simulation Results and Empirical Applications (2005)
    Berlin : Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
    Details
    UID:
    edochu_18452_4133
    Format: 1 Online-Ressource (7 Seiten)
    ISSN: 1436-1086
    Series Statement: Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes 2002,2005,33
    Content: Unobserved heterogeneity is a serious but often neglected problem in structural equation modelling (SEM) challenging the validity of many empirical results. Recently, a finite mixture approach to SEM has been proposed to resolve this problem but until now only a few studies analyse the performance of the relevant software. The contribution of this paper is twofold: First, results from a Monte Carlo study into the properties of the program system MECOSA are presented. Second, an empirical application to data from a large-scale consumer survey in the fast moving consumer goods industry is described.
    Language: English
    DOI: 10.18452/3481
    URN: urn:nbn:de:kobv:11-10048911
    URL: Volltext  (kostenfrei)
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    HU Berlin
  • 2
    Online Resource
    Online Resource
    A Monte Carlo Study of Structural Equation Modelsfor Finite Mixtures (2002)
    Berlin : Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
    Details
    UID:
    edochu_18452_4146
    Format: 1 Online-Ressource (24 Seiten)
    ISSN: 1436-1086
    Series Statement: Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes 2002,2002,48
    Content: Empirical applications of structural equation modeling (SEM) typically rest on the assumption that the analysed sample is homogenous with respect to the underlying structural model or that homogenous subsamples have been formed based on a priori knowledge. However, researchers often are ignorant about the true causes of heterogeneity and thus risk to produce misleading results. Using a sequential procedure of cluster analysis in combination with multi-group SEM has been shown to be inappropriate to solve the problem of unobserved heterogeneity. Recently, two encouraging approaches have been developed in this regard: (1) Finite mixtures of structural equation models and (2) hierarchical Bayesian estimation. In this paper, we focus exclusively on the MECOSA approach to finite normal mixtures subject to conditional mean and covariance structures. Since not much is known about the performance of MECOSA, which is both a specific odel and a software, we present the results of an extensive Monte Carlo simulation. It was found that MECOSA performed best where homogenous groups were present in the data in equal proportions and in conjunction with rather large differences in parameters across the groups. MECOSA performed worse when the proportions were unequal and parameters were relatively close together across groups. Of the three estimation methods available in MECOSA the two-stage minimum distance estimation (MDE) in general performed worse than the alternative EM algorithms (EM and EMG). This effect was especially pronounced under conditions of close parameters and unequal group proportions. Above that, for these conditions the modified likelihood ratio test turned out to be inappropriate in the three groups case.
    Language: English
    DOI: 10.18452/3494
    URN: urn:nbn:de:kobv:11-10049067
    URL: Volltext  (kostenfrei)
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    HU Berlin
  • 3
    Online Resource
    Online Resource
    PLS Path Modeling : A Software Review (2006)
    Berlin : Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
    Details
    UID:
    edochu_18452_4666
    Format: 1 Online-Ressource (27 Seiten)
    ISSN: 1860-5664
    Series Statement: 2006,84
    Content: After years of stagnancy, PLS path modeling has recently attracted renewed interest from applied researchers in marketing. At the same time, the availability of software alternatives to Lohmöller´s LVPLS package has considerably increased (PLS-Graph, PLS-GUI, SPAD-PLS, SmartPLS). To help the user to make an informed decision, the existing programs are reviewed; their strengths and weaknesses are identified. Furthermore, analyzing simulated data reveals that the signs of weights/factor loadings and path coefficients can vary considerably across the different programs. Thus, applied researchers should treat the interpretation of their results with caution. Compared to programs for analysis of covariance structure models (LISREL approach), PLS path modeling software is on equal footing regarding ease of use, but clearly lags behind in terms of methodological capabilities.
    Language: English
    DOI: 10.18452/4014
    URN: urn:nbn:de:kobv:11-10072206
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    HU Berlin
  • 4
    Online Resource
    Online Resource
    Formative Measurement Models in Covariance Structure Analysis : Specification and Identification (2006)
    Berlin : Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
    Details
    UID:
    edochu_18452_4665
    Format: 1 Online-Ressource (18 Seiten)
    ISSN: 1860-5664
    Series Statement: 2006,83
    Content: Many researchers seem to be unsure about how to specify formative measurement models in software programs like LISREL or AMOS and to establish identification of the corresponding structural equation model. In order to make identification easier, a new, mainly graphically orientedapproach is presented for a specific class of recursive models with formativeindicators. Using this procedure it is shown that some models have erroneously beenconsidered underidentified. Furthermore, it is shown that specifying formative indicators asexogenous variables rises serious conceptual and substantial issues in the case that theformative construct is truly endogenous (i. e. influenced by more remote causes). Anempirical study on the effects and causes of brand competence illustrates this point.
    Language: English
    DOI: 10.18452/4013
    URN: urn:nbn:de:kobv:11-10071705
    URL: Volltext  (kostenfrei)
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    HU Berlin
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