this is actually the first time I'm working on a big dataset and I really hope someone can give me some advice on how to handle missing data. I tried to find information regarding my problem but can't find any blog with the same issue.
I'm working on a dataset including different questionnaires. Some questionnaires measure the participants level of anxiety, depression etc and some questionnaires measure the same participants perception of compassion within their organisation. The questionnaires are ProQOL, SSPS, COQ etc and are likert type scale. The questionnaires were filled in by the same participants which is the workforce in the organisation but on different days. I have incomplete data due to different working days/hours. For example participant 1 filled in questionnaire 1, 4, 5 but not 3 and 2. Participant 2 filled in 2, 3, 4, 5 but not one and so forth. The items within the questionnaires are completely missing so no respondent responded to item several items within one questionnaire. Some questionnaires aren't responded by 51% of participants. Can anyone help me what would be the best approach in this situation?
I read a lot about MCAR, MAR and MNAR and would say the data is MCAR as far as I understand. Please correct me if I'm wrong. I also calculated the randomness in SPSS. I therefore went to Analyze -> Missing values analysis and opted t-tests with groups formed by indicator variables under the descriptives option and clicked EM. I thought that might be a good idea. As I said, I'm completely new to this and would really appreciate some help. Thank you in advance.