Comparison of Rasch Model Logits and Likert Mean Score in Testing the Normality Assumption

The lack of empirical evidence about Rasch model logits as a potential score in normality testing boost the motivations on how this type of data can replace the Likert mean score. The research also would like to see how these logits will be variant by fixing the diversity of zones selected for Adversity Quotient (AQ) measurement. The AQ was tested using IKBAR (Instrumen Kecerdasan Menghadapi Cabaran) with CORE model (Control, Ownership, Reach and Endurance) on 1845 polytechnic students from five different zones in Malaysia using a proportionate stratified multistage cluster sampling. The findings revealed that the skewness and kurtosis pattern for all zones showed that Rasch model logits are greater than the Likert mean score. The gaps pattern showed that Borneo dominated the largest gap for Control and AQ for both skewness and kurtosis. In terms of skewness, North region dominated the Endurance gap and the West dominated the Reach gaps. The East dominated the kurtosis gaps for Reach and Endurance. The Rasch model logits for all zones generally had a probability of failing to meet the normality acceptance range. A paired-samples t-test revealed that there was a significant difference for both scores. There was a significant average difference between both score. Rasch model logits were higher than Likert mean score. Based on the results, it is clear that the patterns of the Rasch model logits applicability exposed a great potential and alternative to be used by the researchers as normality data testing besides the Likert mean score. Further studies are proposed to be carried out to explore the potential of using logits for different settings and to ensure applicability to the other normality testing for educational research.