Multi-Group Latent Variable Models for Varying Numbers of Items and Factors with Cross-National and Longitudinal Applications

Varying sets of items and constructs are a problem frequently encountered in cross-national and longitudinal studies in marketing. We discuss the use of multi-group latent variable models in this situation and describe a method that can be used to handle unequal sets of items and constructs across groups in such models. A simulation study based on cross-national marketing data from Belgium and Great Britain revealed that accurate estimates of differences between latent means can be obtained with this procedure with as few as two common items, although a fairly large sample size is required to obtain small standard errors of the estimates of latent mean differences. A substantive example involving a confirmatory factor model as well as a structural model is also provided, using longitudinal data concerning the quality image of a food product in the Netherlands.

[1]  Knowlton W. Johnson Structural Equation Modeling in Practice: Testing a Theory for Research Use , 1998 .

[2]  John W. Berry,et al.  ON CROSS‐CULTURAL COMPARABILITY , 1969 .

[3]  W. Meredith Measurement invariance, factor analysis and factorial invariance , 1993 .

[4]  J. Steenkamp,et al.  Assessing Measurement Invariance in Cross-National Consumer Research , 1998 .

[5]  W. Garlington,et al.  The Change Seeker Index: A Measure of the Need for Variable Stimulus Input , 1964 .

[6]  T. Madsen,et al.  Market Orientation in Food and Agriculture , 1995, Springer US.

[7]  K. Jöreskog Simultaneous factor analysis in several populations , 1971 .

[8]  L. Harlow,et al.  Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices , 1995 .

[9]  J. Steenkamp,et al.  The Role of Optimum Stimulation Level in Exploratory Consumer Behavior , 1992 .

[10]  Jan-Benedict E. M. Steenkamp,et al.  Development and cross-cultural validation of a short form of CSI as a measure of optimum stimulation level. , 1995 .

[11]  R. Green,et al.  A Cross-National Comparison of Consumer Habits and Innovator Characteristics , 1975 .

[12]  Kenneth A. Bollen,et al.  Structural Equations with Latent Variables , 1989 .

[13]  B. Byrne,et al.  Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. , 1989 .

[14]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[15]  D. Sörbom A GENERAL METHOD FOR STUDYING DIFFERENCES IN FACTOR MEANS AND FACTOR STRUCTURE BETWEEN GROUPS , 1974 .

[16]  Karl G. Jöreskog,et al.  Lisrel 8: User's Reference Guide , 1997 .

[17]  Christian Homburg,et al.  Applications of structural equation modeling in marketing and consumer research: A review , 1996 .

[18]  Leslie A. Hayduk,et al.  LISREL Issues, Debates and Strategies , 1996 .

[19]  P. Allison Estimation of Linear Models with Incomplete Data , 1987 .