Question on statistical methodology

[Luis Mijares Castaneda]

Hello, I posted a similar question before, but I will repost it here. I have a dataset and I am interested in ascertaining which variables are associated with increased AI usage. I have two variables, ai_useY2 and ai_use_Y4, and their frequency distributions are listed below. I was wondering if I should restructure the dataset from wide to long and perhaps use a repeated-measures logistic regression, or if I should use a fixed-effects (FE) logistic regression instead. I was also wondering whether I should subset the dataset to participants who were present in both waves. Another potential issue to note, as shown below, is that many participants did not provide consistent answers across survey periods; 11 people answered “Yes” to previously using AI in wave 1 and then switched to “No” in wave 2. Any advice would be appreciated.

tab ai_use_Y2 ai_use_Y4

           |       ai_use_Y4
 ai_use_Y2 |      0.No      1.Yes |     Total
-----------+----------------------+----------
      0.No |       639         25 |       664 
     1.Yes |        11          4 |        15 
-----------+----------------------+----------
     Total |       650         29 |       679 

. tab1 ai_use_*

-> tabulation of ai_use_Y4  

  ai_use_Y4 |      Freq.     Percent        Cum.
------------+-----------------------------------
       0.No |      1,259       94.52       94.52
      1.Yes |         73        5.48      100.00
------------+-----------------------------------
      Total |      1,332      100.00

-> tabulation of ai_use_Y2  

  ai_use_Y2 |      Freq.     Percent        Cum.
------------+-----------------------------------
       0.No |        982       97.71       97.71
      1.Yes |         23        2.29      100.00
------------+-----------------------------------
      Total |      1,005      100.00

[Carlo Lazzaro]

Luis:
if the study measures the same partipants during two waves of data, you may wabt to consider a (conditional) ficed effect panel logistic regression (-xtlogit,fe-).
As an aside, two predictors only are not expected to give you back infornative results.