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Valid measurement is fundamental to the generation of knowledge, and summated rating scales are the dominant measurement format in I/O psychology and organisational behaviour. Users of these scales have traditionally been advised to include both positively and negatively keyed items, but this practice can give rise to an artifactual wording factor. With increasing use of confirmatory factor analysis and structural equation modelling, this problem has assumed greater significance. The presence of such factors can destroy model fit, and seriously mislead researchers. I demonstrate the ongoing relevance of this problem by showing how it affects a recently published unidimensional scale. Judge et al.'s (2003) Core Self-Evaluations Scale (CSES). Using four diverse samples from different countries, I show that a one factor model cannot be fitted to CSES data unless wording effects are accounted for. Having identified the presence of an item wording factor in the CSES samples, I use these data to identify patterns of responding consistent with carelessness. Carelessness has been identified as an important possible explanation for the emergence of item wording effects, but past simulations of careless responding have unrealistically assumed that careless respondents are careless when answering all negatively worded items. Using the patterns identified in empirical data. I create a realistic model of careless responding by varying both the number of careless respondents, and the proportion of items each such respondent answers carelessly. I then use this Monte Carlo simulation to identify the effect of careless responding on factor structure and model fit in a CFA framework, varying item skew, inter-item correlation, and the number of item rating points. A wording factor emerges at relatively low levels of \ ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library

Careless responding and wording factors in Likert-type scales : modelling and fixing the problem