I have longitudinal data with 2 follow ups at year 1 and 3. At baseline we have measure of endothelial function and we want to calculate the relation ship between endothelial function and diabetes type II. at follow up, the incidence of diabetes is recorded with self reported diagnosis or use of medication as the follow up was only done through interviews and questionnaire. we dont have the exact date of incidence of diabetes. which analysis method will be best to use for this type of data. survival analysis or mixed model? I understand for survival analysis I would need exact date of diagnosis of diabetes. but is there other assumptions that can make it possible to use it?

Edit: I have around 2000 participants. their endothelial function was measured with FHR ( continuous values). we have other information about their history of diabetes and other cardiovascular diseases etc. the participants were followed up at year 1 and than at year 3(after 3 yrs of baseline) through phone interviews and paper questionnaires. we asked their medical history, use of medication etc. we want to find an association between endothelial function and incidence of diabetes. so we exclude people who have diabetes at baseline so I am hypothesizing that :people who have bad endothelial function at baseline will get diabetes at follow up.

independent variable; endothelial function (continuous variable) dependent variable: diabetes type 2 incidence (dichotomous , calculated through weather participant get diagnosis for diabetes at follow up, or if they are using medication of diabetes.)

I want to find this association and show its significance using statistical analysis. but for the incidence of diabetes, we dont have exact dates, but only weather they have diabetes or not at one of the follow up.

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    $\begingroup$ You do not need the exact date for survival analysis. Look up interval censoring. As to which analysis, it depends on what you are trying to find out. $\endgroup$ – Peter Flom Jun 24 '19 at 10:53
  • $\begingroup$ I am trying to look at the association between these two (endothelial function and diabetes type 2). I look for interval censoring tough it still confusing that it will only condition the data and then that data can be use in any analysis including survival analysis? is this right ? $\endgroup$ – Maha Jamil Jul 3 '19 at 17:21
  • $\begingroup$ I don't understand your question in the comment. $\endgroup$ – Peter Flom Jul 4 '19 at 11:42

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