impute_dataframe.RdThis function uses the Amelia package to impute a given data frame and return the imputed values.
impute_dataframe(df, measurements_per_day, repetitions = 30)
| df | a data frame |
|---|---|
| measurements_per_day | The number of measurements per day in the diary study |
| repetitions | The amount of times the Amelia call should be averaged over. Defaults to 30. The actual number of imputations is five times the value for |
This function returns the modified data frame.
data <- generate_numerical_test_data(40) data#> id tijdstip something #> 1 1 NA NA #> 2 1 7.131129 391.71823 #> 3 1 29.582397 274.64996 #> 4 1 NA 144.06037 #> 5 1 3.482797 480.49675 #> 6 1 29.677464 1174.06622 #> 7 1 NA 783.72277 #> 8 1 NA 328.77809 #> 9 1 17.854679 305.21776 #> 10 1 NA 532.35094 #> 11 1 4.744942 1229.45761 #> 12 1 16.178128 103.86086 #> 13 1 20.251844 258.33473 #> 14 1 NA 387.53872 #> 15 1 14.093044 321.51461 #> 16 1 22.239532 285.32783 #> 17 1 NA 28.89721 #> 18 1 22.836601 NA #> 19 1 21.588764 137.81367 #> 20 1 36.880216 253.32342 #> 21 1 NA NA #> 22 1 NA 986.38742 #> 23 1 NA 70.14426 #> 24 1 32.421521 NA #> 25 1 9.518809 563.34356 #> 26 1 20.959861 NA #> 27 1 35.094032 1420.59144 #> 28 1 14.999714 612.11627 #> 29 1 23.108879 1282.78163 #> 30 1 NA 175.54598 #> 31 1 NA 924.33056 #> 32 1 22.542726 293.23382 #> 33 1 NA NA #> 34 1 NA NA #> 35 1 7.729795 NA #> 36 1 NA 372.25610 #> 37 1 28.293345 278.22997 #> 38 1 13.979191 206.93043 #> 39 1 38.940924 NA #> 40 1 23.673276 1143.65105impute_dataframe(data,measurements_per_day=1)#> id tijdstip something #> 1 1 14.002721 430.75827 #> 2 1 7.131129 391.71823 #> 3 1 29.582397 274.64996 #> 4 1 16.605677 144.06037 #> 5 1 3.482797 480.49675 #> 6 1 29.677464 1174.06622 #> 7 1 15.788297 783.72277 #> 8 1 15.542639 328.77809 #> 9 1 17.854679 305.21776 #> 10 1 20.626080 532.35094 #> 11 1 4.744942 1229.45761 #> 12 1 16.178128 103.86086 #> 13 1 20.251844 258.33473 #> 14 1 21.668926 387.53872 #> 15 1 14.093044 321.51461 #> 16 1 22.239532 285.32783 #> 17 1 21.062323 28.89721 #> 18 1 22.836601 451.19641 #> 19 1 21.588764 137.81367 #> 20 1 36.880216 253.32342 #> 21 1 21.408870 512.13946 #> 22 1 21.543851 986.38742 #> 23 1 17.744876 70.14426 #> 24 1 32.421521 533.52052 #> 25 1 9.518809 563.34356 #> 26 1 20.959861 602.35246 #> 27 1 35.094032 1420.59144 #> 28 1 14.999714 612.11627 #> 29 1 23.108879 1282.78163 #> 30 1 20.373802 175.54598 #> 31 1 25.882412 924.33056 #> 32 1 22.542726 293.23382 #> 33 1 26.524460 625.60976 #> 34 1 21.515369 600.35678 #> 35 1 7.729795 601.36885 #> 36 1 25.743455 372.25610 #> 37 1 28.293345 278.22997 #> 38 1 13.979191 206.93043 #> 39 1 38.940924 756.10249 #> 40 1 23.673276 1143.65105