Book contents
- Frontmatter
- Contents
- Contributors
- Cross-Cultural Research Methods in Psychology
- 1 Introduction to the Methodological Issues Associated With Cross-Cultural Research
- PART I Conceptual Issues and Design
- Part II Data Analysis and Interpretation
- 7 Methods for Investigating Structural Equivalence
- 8 Evaluating Test and Survey Items for Bias Across Languages and Cultures
- Appendix Statistical Software for Differential Item Functioning Analysis
- 9 Effect Sizes in Cross-Cultural Research
- 10 Data Analytic Approaches for Investigating Isomorphism Between the Individual-Level and the Cultural-Level Internal Structure
- 11 Multilevel Modeling and Cross-Cultural Research
- Appendix Sample Data Sets
- 12 Cross-Cultural Meta-Analysis
- Name index
- Subject index
- References
7 - Methods for Investigating Structural Equivalence
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Contributors
- Cross-Cultural Research Methods in Psychology
- 1 Introduction to the Methodological Issues Associated With Cross-Cultural Research
- PART I Conceptual Issues and Design
- Part II Data Analysis and Interpretation
- 7 Methods for Investigating Structural Equivalence
- 8 Evaluating Test and Survey Items for Bias Across Languages and Cultures
- Appendix Statistical Software for Differential Item Functioning Analysis
- 9 Effect Sizes in Cross-Cultural Research
- 10 Data Analytic Approaches for Investigating Isomorphism Between the Individual-Level and the Cultural-Level Internal Structure
- 11 Multilevel Modeling and Cross-Cultural Research
- Appendix Sample Data Sets
- 12 Cross-Cultural Meta-Analysis
- Name index
- Subject index
- References
Summary
This chapter focuses on data analytic methods to investigate whether the internal structures of measurement instruments are equivalent between cultural groups. For example, is the structure of values that guide individuals’ lives similar between Western and Far Eastern countries? Do employees use the same dimensions to evaluate their organization and their supervisors in different cultural groups? Is the structure of personality between the United States and China the same, or are there culture-specific personality dimensions? This chapter introduces the four most commonly used data analytic methods to investigate the equivalence of the internal structure between cultural groups – namely, multidimensional scaling (MDS), principal component analysis (PCA), exploratory factor analysis (EFA), and confirmatory factor analysis. Before presenting these four data analytic methods, the concept of structural equivalence is explained and situated within the equivalence framework. Moreover, at the end of this chapter two general issues about sample size and data transformation before the analyses are discussed.
The concept of structural equivalence
The investigation of the internal structure forms a key element in the validation process of a measurement instrument within a cultural group (e.g., Messick, 1989). The question is whether the item responses adequately capture the underlying dimensions or factors of the domain one wants to assess. For instance, the responses to the items of a Big Five personality instrument should be captured by five underlying factors, and each of the items has to contribute to the assessment of the specific personality factor it has been constructed for. Thus, the investigation of the internal structure answers two questions: (a) what are the underlying dimensions or factors that capture the interrelationships between the observed item responses and (b) how does each item relate to these underlying dimensions or factors? The more the expected underlying dimensions emerge from the observed item–response relationships and the more each item relates to the expected underlying dimension, the more evidence there is for the construct validity of the instrument.
- Type
- Chapter
- Information
- Cross-Cultural Research Methods in Psychology , pp. 179 - 215Publisher: Cambridge University PressPrint publication year: 2010
References
- 18
- Cited by