Raw data and results for the paper "Full conditional non-parametric bootstrap - an evaluation with unbalanced designs and high residual variability"

This depot contains raw data and results for the paper "Full conditional non-parametric bootstrap - an evaluation with unbalanced designs and high residual variability"

Data

Original Emax and Hill model scenarios can be found in the archive comets_condBoot_data.zip located in the Zenodo depot: https://zenodo.org/records/4059718
Direct link to downloading the datasets: https://zenodo.org/records/4059718/files/comets_condBoot_data.zip?download=1

The data simulated for the other two scenarios are available in the present depot in the Zip file: newDesigns_simulatedData.zip
- Unbalanced designs 
    - comb_dropout: mix of patients receiving a full set of doses and others receving low doses
    - comb_end: mix of patients with rich and sparse designs, with all patients receiving the first and last dose
    - comb_latestart: mix of patients receiving a full set of doses and others receving high doses
    - comb_low: mix of patients receiving four or two doses
- Increased error
    - sigma30: 30% residual error
    - sigma50: 50% residual error

Results

- Original designs
    - results for full cNP
    - results for the other bootstraps can be downloaded from the previous depot: https://zenodo.org/records/4059718
- Unbalanced designs 
    - comb_dropout: mix of patients receiving a full set of doses and others receving low doses
    - comb_end: mix of patients with rich and sparse designs, with all patients receiving the first and last dose
    - comb_latestart: mix of patients receiving a full set of doses and others receving high doses
    - comb_low: mix of patients receiving four or two doses
- Increased error
    - sigma30: 30% residual error
    - sigma50: 50% residual error

Results include empirical SE, bias, RMSE (relative and absolute), parameter estimates, and coverage rates.

Running bootstrap with saemix

Finally, the Rstudio notebook shows how to run saemix and the different bootstraps on one of the demo datasets available in saemix. Packages (including saemix) needed to run this code are listed at the beginning of the notebook and the PDF shows the results of running the notebook.