Quickstart #

Assuming you’ve got the models-for-missing-data project code (see Installation) and have all of the dependencies (see Requirements), the last remaining pieces you’ll need to begin running models are the data and analysis config files. We’ve included examples of each in the “assets/” directory. See the guide for more information about each of these components of the models-for-missing-data workflow. You can find an example of the data here, and an analysis config file for these data here.

Usage #

There are two basic ways to call models-for-missing-data for analyses: interactively using RStudio or non-interactively via the command line.

Graphical user interface (RStudio) #

Start RStudio and set your working directory to the project directory. Open the template “analysis-pipeline.R”, which lives in “model-api/”. If you’d like to make changes to “analysis-pipeline.R”, or begin running models with your own data, create a copy of “analysis-pipeline.R” by appending “local” or your initials as a suffix. E.g., “analysis-pipeline-local.R”.

Command line interface (CLI) #

Run an analysis utilizing 2 CPUs with, for example:

./model-api/analysis-pipeline.R \
    assets/_config/M4MD/ELDO/counts.yml \
    --n-adapt 5000 --n-update 50000 --n-iter 15000 \
    --n-cores 2

See ./model-api/analysis-pipeline.R --help for more details on all CLI arguments, options, and flags.