The influence of data generation and imputation methods on the bias of factor analysis of rating scale data
Conference paper
Abstract
This paper focuses on the bias as a result of imputation methods applied to psychological questionnaire data. Multidimensional rating scale data were generated using three different models. A simulation was carried out with, among others, factors Method of Data Generation, and Imputation Method. It was found that imputation of the mean for each person separately had little bias whereas item mean imputation could result in severe underestimation of factor loadings.
Keywords
Factor analysis Imputation missing data multidimensional item response theory psychometricsPreview
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References
- Bernaards, C.A., and Sijtsma, K. (1999). Factor analysis of multidimensional polytomous item response data suffering from ignorable item nonresponse. Multivariate Behavioral Research, 34, 277–313.CrossRefGoogle Scholar
- Bernaards, C.A., and Sijtsma, K. (in press). Influence of imputation and EM methods on factor analysis when item monresponse in questionnaire data is nonignorable. Multivariate Behavioral Research. Google Scholar
- Harman, H.H. (1976). Modern Factor Analysis. Chicago: The University Chicago Press.Google Scholar
- Muthén, B. and Kaplan, D. (1985). A comparison of some methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical and Statistical Psychology, 38, 171–189.CrossRefGoogle Scholar
- Takane, Y, and de Leeuw, J. (1987). On the relationship between item response theory and factor analysis of discretized variables. Psychometrika, 52, 393–408.MathSciNetMATHCrossRefGoogle Scholar
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