![[Stable]](figures/lifecycle-stable.svg)
Generates an observed vs. predicted data.frame from an NPAG or IT2B object
Value
The output of makeOP is a data frame of class PMop, which has a population and posterior
prediction object (also class PMop) for each output equation. Each of these has 13 columns:
- id
subject identification
- time
observation time in relative hours
- obs
observation
- pred
prediction
- pred.type
Population predictions based on Bayesian prior parameter value distribution, or individual predictions based on Bayesian posterior parameter value distributions
- icen
Predictions based on mean or median of Bayesian
pred.typeparameter values- outeq
output equation number
- block
dosing block number for each subject, as defined by dose resets (evid=4).
- obsSD
standard deviation of the observation based on the assay error polynomial
- d
prediction error,
pred-obs- ds
squared prediction error
- wd
weighted prediction error, which is the prediction error divided by the
obsSD- wds
weighted squared prediction error
A plot method exists in plot for PMop objects.
Details
makeOP will parse the output of NPparse or ITparse to generate a
data.frame suitable for analysis and plotting of observed vs. population or
or individual predicted outputs.
Examples
op <- makeOP(NPex$NPdata)
op
#> id time obs pred pred.type icen outeq block obsSD d
#> 1 1 120.00 10.44 3.663302 pop mean 1 1 1.2565350 -6.77669827
#> 2 1 121.00 12.89 3.479807 pop mean 1 1 1.5248181 -9.41019288
#> 3 1 122.00 14.98 6.326221 pop mean 1 1 1.7490961 -8.65377937
#> 4 1 125.99 16.69 8.846097 pop mean 1 1 1.9294571 -7.84390347
#> 5 1 129.00 20.15 7.868253 pop mean 1 1 2.2857564 -12.28174733
#> 6 1 132.00 14.97 6.787836 pop mean 1 1 1.7480330 -8.18216416
#> 7 1 143.98 12.57 3.672533 pop mean 1 1 1.4901063 -8.89746689
#> 8 2 120.00 3.56 3.663302 pop mean 1 1 0.4721422 0.10330173
#> 9 2 120.98 5.84 3.483385 pop mean 1 1 0.7371530 -2.35661463
#> 10 2 121.98 6.54 6.274216 pop mean 1 1 0.8175083 -0.26578435
#> 11 2 126.00 6.14 8.843913 pop mean 1 1 0.7716490 2.70391316
#> 12 2 129.02 6.56 7.860880 pop mean 1 1 0.8197972 1.30088042
#> 13 2 132.02 4.44 6.780971 pop mean 1 1 0.5750222 2.34097097
#> 14 2 144.00 3.76 3.668761 pop mean 1 1 0.4955897 -0.09123942
#> 15 3 120.08 4.06 3.648273 pop mean 1 1 0.5306885 -0.41172728
#> 16 3 121.07 3.24 3.467312 pop mean 1 1 0.4345457 0.22731214
#> 17 3 122.08 3.09 6.526507 pop mean 1 1 0.4168884 3.43650685
#> 18 3 126.08 7.98 8.825962 pop mean 1 1 0.9813218 0.84596248
#> 19 3 129.05 7.23 7.849820 pop mean 1 1 0.8962522 0.61981964
#> 20 3 132.10 4.71 6.753569 pop mean 1 1 0.6064377 2.04356863
#> 21 3 144.08 3.82 3.653709 pop mean 1 1 0.5026164 -0.16629083
#> 22 4 120.00 2.10 3.663302 pop mean 1 1 0.2998044 1.56330173
#> 23 4 121.00 3.05 3.479807 pop mean 1 1 0.4121760 0.42980712
#> 24 4 122.02 5.21 6.377442 pop mean 1 1 0.6644285 1.16744239
#> 25 4 126.00 5.09 8.843913 pop mean 1 1 0.6505328 3.75391316
#> 26 4 129.03 4.24 7.857194 pop mean 1 1 0.5517061 3.61719380
#> 27 4 132.00 3.69 6.787836 pop mean 1 1 0.4873875 3.09783584
#> 28 4 144.02 1.96 3.664992 pop mean 1 1 0.2831706 1.70499193
#> 29 5 120.00 2.93 3.663302 pop mean 1 1 0.3980298 0.73330173
#> 30 5 121.00 2.64 3.479807 pop mean 1 1 0.3637857 0.83980712
#> 31 5 122.00 4.80 6.326221 pop mean 1 1 0.6168939 1.52622063
#> 32 5 126.00 3.70 8.843913 pop mean 1 1 0.4885595 5.14391316
#> 33 5 129.02 4.13 7.860880 pop mean 1 1 0.5388658 3.73088042
#> 34 5 132.00 2.81 6.787836 pop mean 1 1 0.3838697 3.97783584
#> 35 5 144.00 2.21 3.668761 pop mean 1 1 0.3128605 1.45876058
#> 36 6 120.00 6.92 3.663302 pop mean 1 1 0.8609314 -3.25669827
#> 37 6 121.00 6.89 3.479807 pop mean 1 1 0.8575083 -3.41019288
#> 38 6 121.98 6.64 6.274216 pop mean 1 1 0.8289489 -0.36578435
#> 39 6 126.00 13.72 8.843913 pop mean 1 1 1.6143907 -4.87608684
#> 40 6 129.00 12.69 7.868253 pop mean 1 1 1.5031348 -4.82174733
#> 41 6 131.98 10.58 6.794706 pop mean 1 1 1.2720217 -3.78529359
#> 42 6 144.98 6.62 3.488576 pop mean 1 1 0.8266616 -3.13142389
#> 43 7 120.00 5.41 3.663302 pop mean 1 1 0.6875572 -1.74669827
#> 44 7 121.03 4.46 3.474447 pop mean 1 1 0.5773517 -0.98555338
#> 45 7 122.03 4.54 6.402763 pop mean 1 1 0.5866658 1.86276266
#> 46 7 126.02 12.19 8.839506 pop mean 1 1 1.4487576 -3.35049448
#> 47 7 129.08 12.10 7.838756 pop mean 1 1 1.4389440 -4.26124367
#> 48 7 132.03 8.61 6.777541 pop mean 1 1 1.0523602 -1.83245933
#> 49 7 144.03 6.37 3.663109 pop mean 1 1 0.7980369 -2.70689095
#> 50 8 120.00 6.19 3.663302 pop mean 1 1 0.7773898 -2.52669827
#> 51 8 121.03 6.33 3.474447 pop mean 1 1 0.7934514 -2.85555338
#> 52 8 122.00 6.24 6.326221 pop mean 1 1 0.7831283 0.08622063
#> 53 8 125.98 13.03 8.848266 pop mean 1 1 1.5399734 -4.18173386
#> 54 8 128.98 11.86 7.875624 pop mean 1 1 1.4127363 -3.98437649
#> 55 8 132.00 11.45 6.787836 pop mean 1 1 1.3678360 -4.66216416
#> 56 8 143.98 7.83 3.672533 pop mean 1 1 0.9643513 -4.15746689
#> 57 9 120.00 2.85 3.663302 pop mean 1 1 0.3885913 0.81330173
#> 58 9 120.97 3.70 3.485176 pop mean 1 1 0.4885595 -0.21482412
#> 59 9 122.00 6.65 6.326221 pop mean 1 1 0.8300925 -0.32377937
#> 60 9 125.98 6.81 8.848266 pop mean 1 1 0.8483759 2.03826614
#> 61 9 128.98 6.51 7.875624 pop mean 1 1 0.8140742 1.36562351
#> 62 9 132.00 7.48 6.787836 pop mean 1 1 0.9246691 -0.69216416
#> 63 9 143.98 4.51 3.672533 pop mean 1 1 0.5831738 -0.83746689
#> 64 10 120.00 2.93 3.663302 pop mean 1 1 0.3980298 0.73330173
#> 65 10 121.00 4.36 3.479807 pop mean 1 1 0.5657004 -0.88019288
#> 66 10 122.02 7.79 6.377442 pop mean 1 1 0.9598222 -1.41255761
#> 67 10 126.00 11.02 8.843913 pop mean 1 1 1.3205709 -2.17608684
#> 68 10 129.00 8.86 7.868253 pop mean 1 1 1.0804437 -0.99174733
#> 69 10 131.97 6.09 6.798144 pop mean 1 1 0.7659057 0.70814382
#> 70 10 144.00 4.15 3.668761 pop mean 1 1 0.5412012 -0.48123942
#> 71 11 120.00 2.09 3.663302 pop mean 1 1 0.2986169 1.57330173
#> 72 11 121.03 2.68 3.474447 pop mean 1 1 0.3685139 0.79444662
#> 73 11 122.00 4.71 6.326221 pop mean 1 1 0.6064377 1.61622063
#> 74 11 125.98 7.71 8.848266 pop mean 1 1 0.9507593 1.13826614
#> 75 11 129.00 6.31 7.868253 pop mean 1 1 0.7911580 1.55825267
#> 76 11 132.00 5.82 6.787836 pop mean 1 1 0.7348502 0.96783584
#> ds wd wds
#> 1 4.592364e+01 -5.3931631 29.08620853
#> 2 8.855173e+01 -6.1713544 38.08561523
#> 3 7.488790e+01 -4.9475723 24.47847148
#> 4 6.152682e+01 -4.0653422 16.52700721
#> 5 1.508413e+02 -5.3731654 28.87090620
#> 6 6.694781e+01 -4.6807835 21.90973378
#> 7 7.916492e+01 -5.9710282 35.65317812
#> 8 1.067125e-02 0.2187937 0.04787068
#> 9 5.553633e+00 -3.1969137 10.22025748
#> 10 7.064132e-02 -0.3251152 0.10569988
#> 11 7.311146e+00 3.5040716 12.27851756
#> 12 1.692290e+00 1.5868320 2.51803592
#> 13 5.480145e+00 4.0710964 16.57382577
#> 14 8.324632e-03 -0.1841027 0.03389382
#> 15 1.695194e-01 -0.7758360 0.60192150
#> 16 5.167081e-02 0.5231029 0.27363666
#> 17 1.180958e+01 8.2432307 67.95085210
#> 18 7.156525e-01 0.8620643 0.74315489
#> 19 3.841764e-01 0.6915683 0.47826673
#> 20 4.176173e+00 3.3697915 11.35549450
#> 21 2.765264e-02 -0.3308504 0.10946196
#> 22 2.443912e+00 5.2144063 27.19003265
#> 23 1.847342e-01 1.0427756 1.08738093
#> 24 1.362922e+00 1.7570624 3.08726838
#> 25 1.409186e+01 5.7705214 33.29891673
#> 26 1.308409e+01 6.5563780 42.98609233
#> 27 9.596587e+00 6.3560022 40.39876362
#> 28 2.906997e+00 6.0210767 36.25336503
#> 29 5.377314e-01 1.8423285 3.39417441
#> 30 7.052760e-01 2.3085212 5.32927018
#> 31 2.329349e+00 2.4740408 6.12087784
#> 32 2.645984e+01 10.5287340 110.85424038
#> 33 1.391947e+01 6.9235803 47.93596476
#> 34 1.582318e+01 10.3624630 107.38063931
#> 35 2.127982e+00 4.6626557 21.74035787
#> 36 1.060608e+01 -3.7827616 14.30928501
#> 37 1.162942e+01 -3.9768626 15.81543630
#> 38 1.337982e-01 -0.4412628 0.19471288
#> 39 2.377622e+01 -3.0203884 9.12274617
#> 40 2.324925e+01 -3.2077943 10.28994425
#> 41 1.432845e+01 -2.9758090 8.85543903
#> 42 9.805816e+00 -3.7880361 14.34921753
#> 43 3.050955e+00 -2.5404406 6.45383855
#> 44 9.713155e-01 -1.7070242 2.91393164
#> 45 3.469885e+00 3.1751682 10.08169340
#> 46 1.122581e+01 -2.3126674 5.34843070
#> 47 1.815820e+01 -2.9613686 8.76970410
#> 48 3.357907e+00 -1.7412853 3.03207465
#> 49 7.327259e+00 -3.3919369 11.50523582
#> 50 6.384204e+00 -3.2502333 10.56401634
#> 51 8.154185e+00 -3.5989014 12.95209145
#> 52 7.433998e-03 0.1100977 0.01212151
#> 53 1.748690e+01 -2.7154585 7.37371497
#> 54 1.587526e+01 -2.8203258 7.95423737
#> 55 2.173577e+01 -3.4084235 11.61735047
#> 56 1.728453e+01 -4.3111538 18.58604677
#> 57 6.614597e-01 2.0929488 4.38043484
#> 58 4.614940e-02 -0.4397092 0.19334420
#> 59 1.048331e-01 -0.3900522 0.15214069
#> 60 4.154529e+00 2.4025507 5.77224997
#> 61 1.864928e+00 1.6775173 2.81406426
#> 62 4.790912e-01 -0.7485533 0.56033209
#> 63 7.013508e-01 -1.4360504 2.06224068
#> 64 5.377314e-01 1.8423285 3.39417441
#> 65 7.747395e-01 -1.5559346 2.42093258
#> 66 1.995319e+00 -1.4716867 2.16586180
#> 67 4.735354e+00 -1.6478380 2.71536994
#> 68 9.835628e-01 -0.9179074 0.84255407
#> 69 5.014677e-01 0.9245836 0.85485484
#> 70 2.315914e-01 -0.8892061 0.79068740
#> 71 2.475278e+00 5.2686299 27.75846108
#> 72 6.311454e-01 2.1558118 4.64752457
#> 73 2.612169e+00 2.6651057 7.10278864
#> 74 1.295650e+00 1.1972179 1.43333080
#> 75 2.428151e+00 1.9695845 3.87926328
#> 76 9.367062e-01 1.3170519 1.73462566
#> [ reached 'max' / getOption("max.print") -- omitted 480 rows ]
names(op)
#> [1] "id" "time" "obs" "pred" "pred.type" "icen"
#> [7] "outeq" "block" "obsSD" "d" "ds" "wd"
#> [13] "wds"