## Load libraries

    library(dplyr)

    ##
    ## Attaching package: 'dplyr'

    ## The following objects are masked from 'package:stats':
    ##
    ##     filter, lag

    ## The following objects are masked from 'package:base':
    ##
    ##     intersect, setdiff, setequal, union

    library(qpNCA)
    library(knitr)

## Define mutate_cond and locf functions

    mutate_cond <- function (.data, condition, ..., envir = parent.frame()){
      condition <- eval(substitute(condition), .data, envir)
      if(!any(condition))return(.data) # do nothing if nothing to do
      .data[condition, ] <- .data[condition, ] %>% mutate(...)
      .data
    }
    locf <- function(x){
      good <- !is.na(x)
      positions <- seq(length(x))
      good.positions <- good * positions
      last.good.position <- cummax(good.positions)
      last.good.position[last.good.position == 0] <- NA
      x[last.good.position]
    }

## Check out Theoph data and prepare data for NCA

We use the internal Theoph dataset as input file, modify the data and add necessary columns
Furthermore, we introduce some missing values, LOQ values and time deviations

    head(Theoph) %>% kable()

Subject | Wt | Dose | Time | conc
--- | --- | --- | --- | ---
1 | 79.6 | 4.02 | 0.00 | 0.74
1 | 79.6 | 4.02 | 0.25 | 2.84
1 | 79.6 | 4.02 | 0.57 | 6.57
1 | 79.6 | 4.02 | 1.12 | 10.50
1 | 79.6 | 4.02 | 2.02 | 9.66
1 | 79.6 | 4.02 | 3.82 | 8.58

    input.data <- Theoph

    #we need nominal time variable for some tasks.
    ntad <- data.frame(rn=c(1:11),ntad=c(0,0.25,0.5,1,2,4,5,7,9,12,24))

    input.data %<>%
               group_by(Subject) %>%
               mutate(subject=as.numeric(Subject),
                      rn=row_number(),
                      dose=Dose*Wt,
                      bloq=ifelse(conc==0,1,0),
                      loq=0.1,
                      excl_th=0
                      ) %>%
               left_join(ntad) %>%
               ungroup %>%
               arrange(subject,ntad) %>%
               select(subject,ntad,tad=Time,conc,dose,bloq,loq,excl_th)

    ## Joining, by = "rn"

    input.data %<>%
               mutate_cond(condition=subject==2&ntad%in%c(24),conc=NA) %>%
               mutate_cond(condition=subject==4&ntad%in%c(9),conc=NA) %>%
               mutate_cond(condition=subject==3&ntad==9,excl_th=1) %>%
               mutate_cond(condition=subject==6&ntad==24,conc=0,bloq=1) %>%
               filter(!(subject==5&ntad==12))

## Run full NCA analysis

    # Create a covariates file, containing at least the dose given

    cov = input.data %>%
          distinct(subject,dose)

    nca = qpNCA(
          input.data,
          by = "subject",
          nomtimevar = "ntad",
          timevar = "tad",
          depvar = "conc",
          bloqvar = "bloq",
          loqvar = "loq",
          loqrule = 1,
          includeCmax = "Y",
          exclvar = "excl_th",
          plotdir = NA,
          timelab = "Time (h)",
          deplab = "Conc (ng/mL)",
          tau = 24,
          tstart = 4,
          tend = 9,
          teval = 12,
          covariates = cov,
          dose = "dose",
          factor = 1,
          reg = "sd",
          ss = "n",
          route = "EV",
          method = 1
          )

    ##

    ## Checking function arguments...

    ## all OK!

    ## Applying LOQ rules...

    ## Performing Thalf estimation...

    ## Creating regression plots in standard output...

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    ## Calculating Cmax/Tmax...

    ## Applying time deviation corrections and missing concentration imputations...

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    ## Creating correction tables...

    ## Calculating parameters that do not need lambda_z...

    ## Calculating parameters that DO need lambda_z...

    ## Joining, by = c("subject", "route")

    ## Combining all parameters...

    ##
    ## Writing results...

    ##
    ## Done!

## Print results

    # Covariates:

    nca$covariates %>% kable()

subject | dose
--- | ---
1 | 320.000
2 | 319.770
3 | 319.365
4 | 319.800
5 | 319.365
6 | 318.560
7 | 319.880
8 | 267.840
9 | 320.650
10 | 320.100
11 | 319.992
12 | 319.956

    # Corrections applied:

    nca$corrections %>% kable()

subject | ntad | applies.to | rule.nr | rule.txt
--- | --- | --- | --- | ---
1 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
1 | 4 | TSTART | SDT-2 | Concentration ( 5.53 ) at deviating time ( t=3.57 instead of 4 ) corrected to 5.353 by interpolation (sample taken too early)
1 | 9 | TEND | SDT-2 | Concentration ( 3.46 ) at deviating time ( t=9.22 instead of 9 ) corrected to 3.515 by interpolation (sample taken too late)
1 | 12 | TEVAL | SDT-2 | Concentration ( 2.78 ) at deviating time ( t=12.1 instead of 12 ) corrected to 2.804 by interpolation (sample taken too late)
1 | 24 | TAU | SDT-3 | Concentration ( 0.92 ) at deviating time ( t=23.85 instead of 24 ) corrected to 0.907 by extrapolation (sample taken too early)
2 | 0 | PREDOSE | SDC-1 | Missing or measurable concentration at (SD) PREDOSE set to 0
2 | 4 | TSTART | SDT-2 | Concentration ( 7.09 ) at deviating time ( t=3.48 instead of 4 ) corrected to 6.943 by interpolation (sample taken too early)
2 | 12 | TEVAL | SDT-2 | Concentration ( 3.53 ) at deviating time ( t=12.05 instead of 12 ) corrected to 3.544 by interpolation (sample taken too late)
2 | 24 | TAU | SDT-2 | Concentration ( NA ) at deviating time ( t=24.22 instead of 24 ) corrected to NA by interpolation (sample taken too late)
2 | 24 | TAU | SDC-3 | Missing concentration at t=24 corrected to 1.394 by extrapolation
3 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
3 | 4 | TSTART | SDT-2 | Concentration ( 6.59 ) at deviating time ( t=3.53 instead of 4 ) corrected to 6.37 by interpolation (sample taken too early)
3 | 9 | TEND | SDT-2 | Concentration ( 4.57 ) at deviating time ( t=9.07 instead of 9 ) corrected to 4.576 by interpolation (sample taken too late)
3 | 12 | TEVAL | SDT-2 | Concentration ( 3 ) at deviating time ( t=12.1 instead of 12 ) corrected to 3.052 by interpolation (sample taken too late)
3 | 24 | TAU | SDT-2 | Concentration ( 1.25 ) at deviating time ( t=24.12 instead of 24 ) corrected to 1.267 by interpolation (sample taken too late)
4 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
4 | 4 | TSTART | SDT-2 | Concentration ( 5.87 ) at deviating time ( t=3.6 instead of 4 ) corrected to 5.687 by interpolation (sample taken too early)
4 | 9 | TEND | SDT-2 | Concentration ( NA ) at deviating time ( t=9.03 instead of 9 ) corrected to NA by interpolation (sample taken too late)
4 | 9 | TEND | SDC-2 | Missing concentration at t=9 corrected to 3.769 by interpolation
4 | 12 | TEVAL | SDT-2 | Concentration ( 2.69 ) at deviating time ( t=12.12 instead of 12 ) corrected to 2.731 by interpolation (sample taken too late)
4 | 24 | TAU | SDT-2 | Concentration ( 0.86 ) at deviating time ( t=24.08 instead of 24 ) corrected to 0.872 by interpolation (sample taken too late)
5 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
5 | 4 | TSTART | SDT-2 | Concentration ( 7.5 ) at deviating time ( t=3.62 instead of 4 ) corrected to 7.162 by interpolation (sample taken too early)
5 | 12 | NA | - | Missing record at t=12 added
5 | 12 | TEVAL | SDC-2 | Missing concentration at t=12 corrected to 4.139 by interpolation
5 | 24 | TAU | SDT-2 | Concentration ( 1.05 ) at deviating time ( t=24.17 instead of 24 ) corrected to 1.093 by interpolation (sample taken too late)
6 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
6 | 4 | TSTART | SDT-2 | Concentration ( 6.85 ) at deviating time ( t=3.5 instead of 4 ) corrected to 6.597 by interpolation (sample taken too early)
6 | 24 | NA | LOQ1 | BLOQ values after first measurable concentration set to missing
6 | 24 | TAU | SDT-2 | Concentration ( NA ) at deviating time ( t=24.3 instead of 24 ) corrected to NA by interpolation (sample taken too late)
6 | 24 | TAU | SDC-3 | Missing concentration at t=24 corrected to 0.72 by extrapolation
7 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
7 | 4 | TSTART | SDT-2 | Concentration ( 7.54 ) at deviating time ( t=3.5 instead of 4 ) corrected to 7.323 by interpolation (sample taken too early)
7 | 9 | TEND | SDT-2 | Concentration ( 5.33 ) at deviating time ( t=9.02 instead of 9 ) corrected to 5.335 by interpolation (sample taken too late)
7 | 12 | TEVAL | SDT-2 | Concentration ( 4.19 ) at deviating time ( t=11.98 instead of 12 ) corrected to 4.185 by interpolation (sample taken too early)
7 | 24 | TAU | SDT-2 | Concentration ( 1.15 ) at deviating time ( t=24.65 instead of 24 ) corrected to 1.306 by interpolation (sample taken too late)
8 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
8 | 4 | TSTART | SDT-2 | Concentration ( 5.66 ) at deviating time ( t=3.53 instead of 4 ) corrected to 5.663 by interpolation (sample taken too early)
8 | 9 | TEND | SDT-2 | Concentration ( 4.11 ) at deviating time ( t=8.8 instead of 9 ) corrected to 4.042 by interpolation (sample taken too early)
8 | 12 | TEVAL | SDT-2 | Concentration ( 3.16 ) at deviating time ( t=11.6 instead of 12 ) corrected to 3.096 by interpolation (sample taken too early)
8 | 24 | TAU | SDT-2 | Concentration ( 1.12 ) at deviating time ( t=24.43 instead of 24 ) corrected to 1.188 by interpolation (sample taken too late)
9 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
9 | 4 | TSTART | SDT-2 | Concentration ( 9.75 ) at deviating time ( t=3.52 instead of 4 ) corrected to 9.385 by interpolation (sample taken too early)
9 | 9 | TEND | SDT-2 | Concentration ( 6.11 ) at deviating time ( t=9.03 instead of 9 ) corrected to 6.117 by interpolation (sample taken too late)
9 | 12 | TEVAL | SDT-2 | Concentration ( 4.57 ) at deviating time ( t=12.05 instead of 12 ) corrected to 4.595 by interpolation (sample taken too late)
9 | 24 | TAU | SDT-2 | Concentration ( 1.17 ) at deviating time ( t=24.15 instead of 24 ) corrected to 1.212 by interpolation (sample taken too late)
10 | 0 | PREDOSE | SDC-1 | Missing or measurable concentration at (SD) PREDOSE set to 0
10 | 4 | TSTART | SDT-2 | Concentration ( 10.21 ) at deviating time ( t=3.55 instead of 4 ) corrected to 9.901 by interpolation (sample taken too early)
10 | 9 | TEND | SDT-2 | Concentration ( 7.14 ) at deviating time ( t=9.38 instead of 9 ) corrected to 7.285 by interpolation (sample taken too late)
10 | 12 | TEVAL | SDT-2 | Concentration ( 5.68 ) at deviating time ( t=12.1 instead of 12 ) corrected to 5.734 by interpolation (sample taken too late)
10 | 24 | TAU | SDT-3 | Concentration ( 2.42 ) at deviating time ( t=23.7 instead of 24 ) corrected to 2.366 by extrapolation (sample taken too early)
11 | 0 | PREDOSE | SDC-1 | Missing or measurable concentration at (SD) PREDOSE set to 0
11 | 4 | TSTART | SDT-2 | Concentration ( 8.58 ) at deviating time ( t=3.82 instead of 4 ) corrected to 8.549 by interpolation (sample taken too early)
11 | 9 | TEND | SDT-2 | Concentration ( 6.89 ) at deviating time ( t=9.05 instead of 9 ) corrected to 6.904 by interpolation (sample taken too late)
11 | 12 | TEVAL | SDT-2 | Concentration ( 5.94 ) at deviating time ( t=12.12 instead of 12 ) corrected to 5.977 by interpolation (sample taken too late)
11 | 24 | TAU | SDT-2 | Concentration ( 3.28 ) at deviating time ( t=24.37 instead of 24 ) corrected to 3.36 by interpolation (sample taken too late)
12 | 0 | NA | LOQ1 | BLOQ values before first measurable concentration set to 0
12 | 4 | TSTART | SDT-2 | Concentration ( 8.74 ) at deviating time ( t=3.5 instead of 4 ) corrected to 8.352 by interpolation (sample taken too early)
12 | 9 | TEND | SDT-2 | Concentration ( 5.9 ) at deviating time ( t=9.1 instead of 9 ) corrected to 5.957 by interpolation (sample taken too late)
12 | 24 | TAU | SDT-2 | Concentration ( 1.57 ) at deviating time ( t=24.35 instead of 24 ) corrected to 1.649 by interpolation (sample taken too late)

    # half-life estimation:

    nca$half_life %>% kable()

subject | no.points | intercept | lambda_z | r.squared | adj.r.squared | start_th | end_th | thalf | includeCmax | points_excluded
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | 3 | 8.212078 | 0.0915758 | 0.9989638 | 0.9979276 | 9.22 | 23.85 | 7.569107 | Y | N
2 | 3 | 8.959057 | 0.0777431 | 0.9964163 | 0.9928325 | 6.98 | 12.05 | 8.915865 | Y | N
3 | 6 | 8.688001 | 0.0818231 | 0.9962482 | 0.9953103 | 2.02 | 24.12 | 8.471285 | Y | Y
4 | 3 | 8.703249 | 0.0962171 | 0.9999286 | 0.9998572 | 7.03 | 24.08 | 7.203989 | Y | N
5 | 5 | 10.568234 | 0.0948933 | 0.9957650 | 0.9943534 | 3.62 | 24.17 | 7.304489 | Y | N
6 | 3 | 12.790536 | 0.1192526 | 0.9867217 | 0.9734435 | 7.03 | 12.00 | 5.812428 | Y | N
7 | 3 | 13.366552 | 0.0992870 | 0.9989241 | 0.9978483 | 9.02 | 24.65 | 6.981247 | Y | N
8 | 3 | 8.369952 | 0.0824586 | 0.9994437 | 0.9988873 | 8.80 | 24.43 | 8.405999 | Y | N
9 | 3 | 16.852407 | 0.1102595 | 0.9993968 | 0.9987936 | 9.03 | 24.15 | 6.286508 | Y | N
10 | 3 | 14.263523 | 0.0749598 | 0.9995087 | 0.9990174 | 9.38 | 23.70 | 9.246916 | Y | N
11 | 3 | 10.684404 | 0.0484570 | 0.9999997 | 0.9999995 | 9.05 | 24.37 | 14.304378 | Y | N
12 | 4 | 12.821101 | 0.0866189 | 0.9986472 | 0.9979708 | 7.02 | 24.35 | 8.002264 | Y | N

    # PK parameters:

    nca$pkpar %>% kable()

subject | cmax | tmax | method | tlast | clast.obs | tlast.ok | t0.ok | aucall | auclast | aumcall | aumclast | mrtall | mrtlast | calc.tau | auctau | aumctau | tau | calc.teval | auc12 | teval | calc.part | auc4_9 | tstart | tend | c0 | area.back.extr | loqrule | no.points | intercept | lambda_z | r.squared | adj.r.squared | start_th | end_th | thalf | includeCmax | points_excluded | dose | factor | reg | ss | route | clast.pred | aucinf.obs | aucinf.pred | aumcinf.obs | aumcinf.pred | cl.f.obs | cl.f.pred | mrtinf.obs | mrtinf.pred | vz.f.obs | vz.f.pred | vss.obs | vss.pred | pctextr.obs | pctextr.pred | pctback.obs | pctback.pred | cl.obs | cl.pred | vz.obs | vz.pred | cl.f.ss | cl.ss
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | 6.44 | 1.15 | 1 | 23.85 | 0.92 | 1 | 1 | 73.77555 | 73.77555 | 609.1524 | 609.1524 | 8.256833 | 8.256833 | 1 | 73.97837 | 612.3497 | 24 | 1 | 51.75887 | 12 | 1 | 21.64179 | 4 | 9 | NA | NA | 1 | 3 | 8.212078 | 0.0915758 | 0.9989638 | 0.9979276 | 9.22 | 23.85 | 7.569107 | Y | N | 320.000 | 1 | sd | n | ev | 0.9245229 | 83.82187 | 83.87126 | 958.4620 | 960.1793 | 3.817620 | 3.815371 | 11.434510 | 11.448252 | 41.68807 | 41.66352 | NA | NA | 11.985320 | 12.037150 | NA | NA | NA | NA | NA | NA | NA | NA
2 | 7.09 | 3.48 | 1 | 12.05 | 3.53 | 1 | 1 | 62.25685 | 62.25685 | 354.0998 | 354.0998 | 5.687724 | 5.687724 | 1 | 91.67850 | 808.1730 | 24 | 1 | 62.08000 | 12 | 1 | 28.32875 | 4 | 9 | NA | NA | 1 | 3 | 8.959057 | 0.0777431 | 0.9964163 | 0.9928325 | 6.98 | 12.05 | 8.915865 | Y | N | 319.770 | 1 | sd | n | ev | 3.5108576 | 107.66280 | 107.41657 | 1485.2925 | 1479.1583 | 2.970107 | 2.976915 | 13.795782 | 13.770299 | 38.20411 | 38.29168 | NA | NA | 42.174223 | 42.041671 | NA | NA | NA | NA | NA | NA | NA | NA
3 | 7.56 | 2.02 | 1 | 24.12 | 1.25 | 1 | 1 | 88.55995 | 88.55995 | 739.5346 | 739.5346 | 8.350666 | 8.350666 | 1 | 88.40890 | 737.1499 | 24 | 1 | 62.71486 | 12 | 1 | 26.17989 | 4 | 9 | NA | NA | 1 | 6 | 8.688001 | 0.0818231 | 0.9962482 | 0.9953103 | 2.02 | 24.12 | 8.471285 | Y | Y | 319.365 | 1 | sd | n | ev | 1.2072785 | 103.83680 | 103.31468 | 1294.7180 | 1275.7434 | 3.075644 | 3.091187 | 12.468778 | 12.348132 | 37.58892 | 37.77888 | NA | NA | 14.712367 | 14.281349 | NA | NA | NA | NA | NA | NA | NA | NA
4 | 8.00 | 0.98 | 1 | 24.08 | 0.86 | 1 | 1 | 80.44595 | 80.44595 | 614.9855 | 614.9855 | 7.644705 | 7.644705 | 1 | 80.37666 | 614.1894 | 24 | 1 | 58.89166 | 12 | 1 | 23.37641 | 4 | 9 | NA | NA | 1 | 3 | 8.703249 | 0.0962171 | 0.9999286 | 0.9998572 | 7.03 | 24.08 | 7.203989 | Y | N | 319.800 | 1 | sd | n | ev | 0.8579476 | 89.38407 | 89.36274 | 923.1107 | 922.3753 | 3.577819 | 3.578673 | 10.327463 | 10.321700 | 37.18484 | 37.19372 | NA | NA | 9.999676 | 9.978193 | NA | NA | NA | NA | NA | NA | NA | NA
5 | 8.20 | 1.02 | 1 | 24.17 | 1.05 | 1 | 1 | 102.32475 | 102.32475 | 767.2143 | 767.2143 | 7.497837 | 7.497837 | 1 | 102.14258 | 767.7359 | 24 | 1 | 70.75194 | 12 | 1 | 28.50079 | 4 | 9 | NA | NA | 1 | 5 | 10.568234 | 0.0948933 | 0.9957650 | 0.9943534 | 3.62 | 24.17 | 7.304489 | Y | N | 319.365 | 1 | sd | n | ev | 1.0663923 | 113.38981 | 113.56255 | 1151.2620 | 1157.2576 | 2.816523 | 2.812239 | 10.153135 | 10.190486 | 29.68094 | 29.63579 | NA | NA | 9.758423 | 9.895693 | NA | NA | NA | NA | NA | NA | NA | NA
6 | 8.33 | 1.92 | 1 | 12.00 | 3.01 | 1 | 1 | 67.48030 | 67.48030 | 349.9481 | 349.9481 | 5.185929 | 5.185929 | 1 | 89.85776 | 670.2872 | 24 | 1 | 67.48030 | 12 | 1 | 27.80327 | 4 | 9 | NA | NA | 1 | 3 | 12.790536 | 0.1192526 | 0.9867217 | 0.9734435 | 7.03 | 12.00 | 5.812428 | Y | N | 318.560 | 1 | sd | n | ev | 3.0577347 | 92.72084 | 93.12112 | 864.4906 | 872.6506 | 3.435689 | 3.420921 | 9.323585 | 9.371135 | 28.81018 | 28.68634 | NA | NA | 27.222078 | 27.534915 | NA | NA | NA | NA | NA | NA | NA | NA
7 | 8.60 | 1.07 | 1 | 24.65 | 1.15 | 1 | 1 | 106.79630 | 106.79630 | 901.0842 | 901.0842 | 8.437410 | 8.437410 | 1 | 105.99811 | 893.5606 | 24 | 1 | 73.05545 | 12 | 1 | 30.90683 | 4 | 9 | NA | NA | 1 | 3 | 13.366552 | 0.0992870 | 0.9989241 | 0.9978483 | 9.02 | 24.65 | 6.981247 | Y | N | 319.880 | 1 | sd | n | ev | 1.1564216 | 118.37888 | 118.44356 | 1303.2524 | 1305.4981 | 2.702171 | 2.700696 | 11.009163 | 11.022111 | 27.21575 | 27.20089 | NA | NA | 9.784331 | 9.833594 | NA | NA | NA | NA | NA | NA | NA | NA
8 | 9.03 | 0.63 | 1 | 24.43 | 1.12 | 1 | 1 | 86.32615 | 86.32615 | 705.2296 | 705.2296 | 8.169363 | 8.169363 | 1 | 85.82985 | 698.6535 | 24 | 1 | 60.22219 | 12 | 1 | 24.01132 | 4 | 9 | NA | NA | 1 | 3 | 8.369952 | 0.0824586 | 0.9994437 | 0.9988873 | 8.80 | 24.43 | 8.405999 | Y | N | 267.840 | 1 | sd | n | ev | 1.1164831 | 99.90872 | 99.86607 | 1201.7715 | 1200.2124 | 2.680847 | 2.681992 | 12.028695 | 12.018220 | 32.51142 | 32.52530 | NA | NA | 13.594978 | 13.558076 | NA | NA | NA | NA | NA | NA | NA | NA
9 | 9.75 | 3.52 | 1 | 24.15 | 1.17 | 1 | 1 | 119.97750 | 119.97750 | 977.8807 | 977.8807 | 8.150534 | 8.150534 | 1 | 119.79884 | 976.6269 | 24 | 1 | 85.02136 | 12 | 1 | 37.02829 | 4 | 9 | NA | NA | 1 | 3 | 16.852407 | 0.1102595 | 0.9993968 | 0.9987936 | 9.03 | 24.15 | 6.286508 | Y | N | 320.650 | 1 | sd | n | ev | 1.1755390 | 130.58883 | 130.63907 | 1330.3840 | 1332.0528 | 2.455417 | 2.454473 | 10.187579 | 10.196435 | 22.26944 | 22.26087 | NA | NA | 8.125757 | 8.161087 | NA | NA | NA | NA | NA | NA | NA | NA
10 | 10.21 | 3.55 | 1 | 23.70 | 2.42 | 1 | 1 | 138.32370 | 138.32370 | 1278.1800 | 1278.1800 | 9.240499 | 9.240499 | 1 | 139.21851 | 1293.7275 | 24 | 1 | 90.77302 | 12 | 1 | 42.16870 | 4 | 9 | NA | NA | 1 | 3 | 14.263523 | 0.0749598 | 0.9995087 | 0.9990174 | 9.38 | 23.70 | 9.246916 | Y | N | 320.100 | 1 | sd | n | ev | 2.4136923 | 170.60766 | 170.52351 | 2473.9934 | 2470.8765 | 1.876235 | 1.877161 | 14.501069 | 14.489946 | 25.02987 | 25.04222 | NA | NA | 18.922926 | 18.882917 | NA | NA | NA | NA | NA | NA | NA | NA
11 | 10.50 | 1.12 | 1 | 24.37 | 3.28 | 1 | 1 | 148.83055 | 148.83055 | 1459.0711 | 1459.0711 | 9.803573 | 9.803573 | 1 | 147.60209 | 1435.2096 | 24 | 1 | 91.64302 | 12 | 1 | 38.73468 | 4 | 9 | NA | NA | 1 | 3 | 10.684404 | 0.0484570 | 0.9999997 | 0.9999995 | 9.05 | 24.37 | 14.304378 | Y | N | 319.992 | 1 | sd | n | ev | 3.2801465 | 216.51943 | 216.52246 | 4505.5348 | 4505.6709 | 1.477890 | 1.477870 | 20.808917 | 20.809254 | 30.49901 | 30.49858 | NA | NA | 31.262267 | 31.263226 | NA | NA | NA | NA | NA | NA | NA | NA
12 | 11.40 | 1.00 | 1 | 24.35 | 1.57 | 1 | 1 | 121.29440 | 121.29440 | 1017.1143 | 1017.1143 | 8.385501 | 8.385501 | 1 | 120.73101 | 1009.3769 | 24 | 1 | 84.61490 | 12 | 1 | 35.68178 | 4 | 9 | NA | NA | 1 | 4 | 12.821101 | 0.0866189 | 0.9986472 | 0.9979708 | 7.02 | 24.35 | 8.002264 | Y | N | 319.956 | 1 | sd | n | ev | 1.5556951 | 139.41978 | 139.25463 | 1667.7216 | 1661.7937 | 2.294911 | 2.297633 | 11.961873 | 11.933490 | 26.49435 | 26.52577 | NA | NA | 13.000579 | 12.897403 | NA | NA | NA | NA | NA | NA | NA | NA

    # Regression plots:

    nca$plots

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