Your overall goal at this stage is to determine what the factors represent by seeking out common themes in questions that load onto the same factors.You can combine questions that load onto the same factors, comparing them during your final analysis of data.If that is not the case, you may want to think about eliminating that respondent from the survey.Also double-check minimum and maximum values for your overall dataset.For instance, several questions may end up measuring the underlying component of employee loyalty, a factor not expressly asked about in your survey but one uncovered by PCA.Because PCA can be complex and needs to be precise, calling on a skilled expert for guidance during this step is a wise idea if you’re not familiar with the process.
If it does, you may want to consider deleting the question from the survey.
Unfortunately, validating a survey requires a lot more than that.
Dave Collingridge noticed the same phenomenon when he was a social sciences graduate student unable to find a professor or other faculty member who would or could help him with survey validation.
If you run across a question that doesn’t neatly load onto a factor, you can choose to delete it.
If the question is an important one you’d rather not delete, you can always retain it and analyze it separately.