The Impact of Extreme Response Style on the Mean Comparison of Two Independent Samples

Abstract

Extreme response style (ERS) is prevalent in survey research using rating scales. It may cause biased results in group comparisons. This research conducted two sets of simulation studies to explore the magnitude of the ERS impact on mean comparisons between two independent samples. Data were generated from a multidimensional nominal response model. Study 1 examined the influence of ERS on the estimate of group differences in the variable of interest. The results indicated that ERS led to biased estimates, especially when these groups differed significantly in ERS. The correlation between ERS and the variable of interest also moderated the ERS impact. The results were illustrated with an empirical example. Study 2 investigated the impact of ERS on the type I error and type II error in the independent t-test based on scale scores. When the variable of interest had no true difference between groups, ERS inflated the type I error rate. When the difference existed, ERS inflated the type II error rate. Two groups’ true difference in ERS and the variable of interest, unequal ERS variances, the correlation between ERS and the variable of interest, and the number of items moderated the impact of ERS on type I and II error rates. The implications for practices and further research are discussed.