Next, we recommend best practices in assessing reliability, convergent and discriminant validity based on multiple criteria and taking sampling errors into consideration. In this best practice paper, we first critically review the most frequently-used approaches in empirical studies to evaluate the quality of measurement scales when using structural equation modeling. Moreover, researchers rarely consider sampling errors for these psychometric quality measures. However, these results are usually inadequate and sometimes inappropriate. ![]() Researchers commonly report the quality of these measurement scales based on Cronbach’s alpha and confirmatory factor analysis results. When the scales are used in a different population, the items are translated into other languages or revised to adapt to other populations, it is essential for researchers to report the quality of measurement scales before using them to test hypotheses. Typically, empirical studies measure such constructs using established scales with multiple indicators. Many constructs in management studies, such as perceptions, personalities, attitudes, and behavioral intentions, are not directly observable.
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