Hi everyone,

I have an unbalanced panel data per Stata as seen here:

Code:
. //Setting panel variables
. xtset household_key period
       panel variable:  household_key (unbalanced)
        time variable:  period, 1 to 34
                delta:  1 unit

.
. xtdescribe

household_key:  1, 2, ..., 2500                              n =       2500
  period:  1, 2, ..., 34                                     T =         34
           Delta(period) = 1 unit
           Span(period)  = 34 periods
           (household_key*period uniquely identifies each observation)

Distribution of T_i:   min      5%     25%       50%       75%     95%     max
                         1       1       1         5        11      19      34

     Freq.  Percent    Cum. |  Pattern
 ---------------------------+------------------------------------
      916     36.64   36.64 |  1.................................
      268     10.72   47.36 |  111...............................
      223      8.92   56.28 |  11111.............................
      211      8.44   64.72 |  1111111...........................
      163      6.52   71.24 |  111111111.........................
      157      6.28   77.52 |  11111111111.......................
      123      4.92   82.44 |  1111111111111.....................
       94      3.76   86.20 |  111111111111111...................
       70      2.80   89.00 |  11111111111111111.................
      275     11.00  100.00 | (other patterns)
 ---------------------------+------------------------------------
     2500    100.00         |  XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
However, this "unbalancedness" only results from unequal periods T attributed to households i. And the only reason this occurs is due to the lengths of various treatments assigned and its corresponding durations and how I aggregated this data based on said durations. Is this still prone to any type of "selection bias"? Is there anyway I can explicitly test for this?

Just to be clear, the entire row vector is for each cross section over period T contains NO missing values, but the unbalancedness again comes from the fact that treatment durations are wildly different. So each household/cross-section is observed for a total of 720 days, but some have 3 periods due to receiving 2 treatments, Some have 4 periods due to receiving 3 treatments etc. I'd really appreciate any guidance.