Wrapper for calling compute_dataset_simulation nruns time and computing summary statsitics of the simulations

compute_summary_statistics_of_simulations(
  data,
  fit,
  xdata_col,
  conf_int,
  nruns,
  nbins,
  type = 2
)

Arguments

data

A data frame containing C-QT analysis dataset

fit

An nlme::lme model object from model fitting

xdata_col

An unquoted column name for xdata

conf_int

Numeric confidence interval level (default: 0.9)

nruns

Integer number of simulations to run

nbins

Integer number of bins to break independent variable into - OR - a user specified vector for non-uniform binning

type

Algorithm for quantile. Default (2), is SAS quantile algorithm

Value

a tibble of summary statistics of nruns worth of dataset simulations for a VPC.

Examples

data_proc <- preprocess(cqtkit_data_verapamil)

fit <- nlme::lme(
  fixed = deltaQTCF ~ 1 + CONC,
  random = ~ 1 | ID,
  data = data_proc,
  method = "REML",
  na.action = "na.exclude"
)

compute_summary_statistics_of_simulations(
  data = data_proc,
  fit = fit,
  xdata_col = CONC,
  conf_int = 0.9,
  nruns = 50,
  nbins = 10,
  type = 2)
#> # A tibble: 250 × 15
#>    decile   sim_num med_xdata med_pred low_pred high_pred mean_med_pred
#>    <fct>      <int>     <dbl>    <dbl>    <dbl>     <dbl>         <dbl>
#>  1 [0,9.05]       1         0    -7.32    -19.4      3.35         -7.07
#>  2 [0,9.05]       2         0    -7.86    -20.7      3.98         -7.07
#>  3 [0,9.05]       3         0    -7.18    -20.3      5.10         -7.07
#>  4 [0,9.05]       4         0    -6.73    -20.1      4.82         -7.07
#>  5 [0,9.05]       5         0    -7.59    -19.4      3.61         -7.07
#>  6 [0,9.05]       6         0    -7.01    -18.6      3.72         -7.07
#>  7 [0,9.05]       7         0    -7.41    -19.4      5.76         -7.07
#>  8 [0,9.05]       8         0    -7.09    -17.7      4.85         -7.07
#>  9 [0,9.05]       9         0    -6.69    -19.2      6.19         -7.07
#> 10 [0,9.05]      10         0    -7.01    -19.3      3.22         -7.07
#> # ℹ 240 more rows
#> # ℹ 8 more variables: low_med_pred <dbl>, high_med_pred <dbl>,
#> #   mean_low_pred <dbl>, low_low_pred <dbl>, high_low_pred <dbl>,
#> #   mean_high_pred <dbl>, low_high_pred <dbl>, high_high_pred <dbl>