Hi everyone, hope you're all well.

First post - so please let me know if I have missed anything from the posting FAQ,

I've got a question regarding the use of mixed effects ordinal logistic regression for repeated measures analysis where I have repeated measures of both the dependent variable at 5 time points (e.g. days 0, 28, 90, 180, 365) as well as multiple independent variables - where the independent variables may be measured at some/all of those time points e.g. only at Day 180 and Day 365. My dependent variable is a scale with categories from 0 - 6.

I am interested in utilising all of the repeated measures in my model, as well as being able to predict the outcome variable at different time points. However, if I include all repeated measures independent variables that are not measured at every time point, I've realised that naturally my model will omit the time variable (due to empty observations). It also has the curious effect of removing one of the cutoff points (e.g. should be 6 for a 7 point scale).

I was wondering if there was any way to utliise all the repeated measures variables and time variable? My first thought was imputation/some linear back extrapolation over time but I don't know if that would be particularly rigorous.

I have attached a sample of my code and corresponding output - my apologies if unclear. To simplify the code, I have included my repeated measures dependent variable (POS), the time variable (i.days) and 2 repeated measures independent variables: PHQ (measured at all 5 time points) and SF36 (measured only at 2 time points)

I've attempted to understand this by looking through the documentation and forum but to no avail. Hope you made it through the long post and I would be very grateful for any suggestions.

Code:
Code:
reshape long POS PHQ EQ5D5L, i(regono) j(days)
xtset regono days
meologit POS i.days PHQ
meologit POS i.days EQ5D5L
meologit POS i.days PHQ EQ5D5L
Output with independent variable measured at all 5 time points (PHQ):
Code:
 POS |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        days |
         28  |  -1.149115   .0740449   -15.52   0.000    -1.294241    -1.00399
         90  |  -1.836681   .0763513   -24.06   0.000    -1.986327   -1.687035
        180  |  -2.288859   .0789507   -28.99   0.000    -2.443599   -2.134118
        365  |  -2.433143   .0835774   -29.11   0.000    -2.596952   -2.269335
             |
         PHQ |    .105064   .0063705    16.49   0.000      .092578      .11755
-------------+----------------------------------------------------------------
       /cut1 |  -4.185908   .0825713                     -4.347745   -4.024071
       /cut2 |  -1.772225   .0666063                     -1.902771   -1.641679
       /cut3 |  -.8859034    .064558                     -1.012435   -.7593722
       /cut4 |   .3948111   .0623225                      .2726613    .5169609
       /cut5 |    2.54402   .0806856                      2.385879    2.702161
       /cut6 |   4.327243   .1559541                      4.021578    4.632907
Output with independent variable measured at only 2 time points (EQ5D5L):
Code:
        POS |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        days |
          0  |          0  (empty)
         28  |          0  (empty)
         90  |          0  (empty)
        180  |  -8.499786   .3015914   -28.18   0.000    -9.090894   -7.908677
        365  |          0  (omitted)
             |
      EQ5D5L |  -8.175158   .2752685   -29.70   0.000    -8.714675   -7.635642
-------------+----------------------------------------------------------------
       /cut1 |  -9.343137   .2739839                     -9.880135   -8.806138
       /cut2 |  -6.464956    .243897                     -6.942985   -5.986927
       /cut3 |  -5.132735   .2294906                     -5.582528   -4.682942
       /cut4 |  -2.003746   .1904413                     -2.377004   -1.630488
       /cut5 |   2.974826   .3917165                      2.207076    3.742576
------------------------------------------------------------------------------
Output with independent variable measured at only 2 time points (EQ5D5L) and at 5 time points (PHQ):
Code:
 POS |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        days |
          0  |          0  (empty)
         28  |          0  (empty)
         90  |          0  (empty)
        180  |  -8.465161   .3186536   -26.57   0.000    -9.089711   -7.840612
        365  |          0  (omitted)
             |
         PHQ |   .0048066   .0144241     0.33   0.739     -.023464    .0330773
      EQ5D5L |  -8.141514   .2928335   -27.80   0.000    -8.715457   -7.567571
-------------+----------------------------------------------------------------
       /cut1 |  -9.302017   .3001149                     -9.890231   -8.713803
       /cut2 |  -6.422326   .2750666                     -6.961447   -5.883206
       /cut3 |  -5.089812   .2628265                     -5.604942   -4.574681
       /cut4 |  -1.966184    .221139                     -2.399608   -1.532759
       /cut5 |   3.007101   .4038256                      2.215617    3.798584