Handling dv at time 0

Data read
1

When I convert with read_pumas and check the dataframe, the dv row comes always above the evid. I tried to convert back to df and sort the time and rerun the read_pumas but still having the same output.

A couple of work arounds:

  1. Remove observation at time 0
  2. Change time to 1e-5

Any suggestions for adding DV at time 0?

julia> dataset
162×8 DataFrame
 Row │ id      amt    time     dv            mdv    cmt    DOSE   evid
     │ String  Int64  Float64  Float64?      Int64  Int64  Int64  Int64
─────┼──────────────────────────────────────────────────────────────────
   1 │ 1          81      0.0  missing           1      1     81      1
   2 │ 1           0      0.0        0.0         0      2     81      0
   3 │ 1           0      0.5        0.4368      0      2     81      0
   4 │ 1           0      1.0        0.8433      0      2     81      0

DataFrame(population)

162×13 DataFrame
 Row │ id      time     evid   dv            amt       cmt      rate      duration  ss    ii        route       tad      dosenum
     │ String  Float64  Int64  Float64?      Float64?  Int64?   Float64?  Float64?  Int8  Float64?  NCA.Route?  Float64  Int64
─────┼───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │ 1           0.0      0        0.0          0.0  missing       0.0       0.0     0       0.0  NullRoute       0.0        1
   2 │ 1           0.0      1  missing           81.0        1       0.0       0.0     0       0.0  NullRoute       0.0        1
   3 │ 1           0.5      0        0.4368       0.0  missing       0.0       0.0     0       0.0  NullRoute       0.5        1