MHealthModeration

Numerical results for "Assessing time-varying causal effect moderation in mobile health"

Simulation studies

The simulation results for each scenario are generated by the following R scripts. Running a script in batch mode from your system command line with, say,

R CMD BATCH --vanilla sim-omit.R

will create R output and simulation data files by the same name; sim-omit.Rout and sim-omit.RData, respectively.

File | Description ---- | ---- sim-omit.R | Averaging over an underlying moderator sim-stable.R | Weight stabilization sim-ar1.R | Non-independence working correlation structure

Each of these scripts call routines defined in the files below.

File | Description ---- | ---- rsnmm.c | Data generator rsnmm.R | Data generator interface sim.R | Simulation routine init.R | Loads required packages and reads source files xgeepack.R | Extensions for the geepack R package; extract, from a geepack model object, elements (e.g. working covariance, estimating function) needed for variance calculations xzoo.R | Extensions for the zoo R package; apply lags, difference, rolling summaries to a sample of time series

Application to simulated data

Instead of the application presented in the paper (which considers sensitive data), we provide an example using simulated data---both with and without use of the geepack R package. The zoo R package is used to easily define variables, but is not needed for estimation.

File | Description ---- | ---- example_geepack.R | Loads geepack and zoo extensions, generates data and runs an analysis similar to the application presented in the paper example_geepack.Rout | Provides the output obtained by running the example in batch mode example.R | Loads zoo extensions, generates data and runs an analysis similar to the application presented in the paper example.Rout | Provides the output obtained by running the example in batch mode