How can researchers determine if data are missing not at random?

Determining if data are missing not at random (MNAR) is a complex task, as this situation occurs when the reason for missingness is related to the unobserved data itself. The correct approach involves comparing the characteristics of respondents with missing data against those without missing data, as this can provide insights into potential biases and help identify if missingness may be related to the outcomes in question.

Analyzing missing data patterns over time can also reveal trends, but it may not directly indicate whether the data are MNAR. Conducting follow-up interviews with participants can help gather more information, but it does not conclusively determine the nature of the missing data either. Thus, option C is not a valid conclusion, as researchers have methods to investigate and assess the nature of missing data, particularly through direct comparisons between groups.