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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Raw data and results for the paper "Full conditional non-parametric bootstrap - an evaluation with unbalanced designs and high residual variability"

Authors: Comets, Emmanuelle;

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

Abstract

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/4059718Direct 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.

Related Organizations
Keywords

Pharmacodynamics, Simulation, Bootstrap

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average