assess_recurrence: assess_recurrence
In lendle/hdps: High-dimensional propensity score algorithm

Description Usage Arguments Details Value Author(s) References

Expands covarites to up to three binary columns for at least one, sporadic, or frequent occrence of each covariate.

1	assess_recurrence(covars, debug = FALSE)

`covars`	a matrix or something that can be coerced with `as.matrix` of covariates
`debug`	Enables some debuging checks which slow things down, but may yield useful warnings or errors.

Each column x of covars is expanded to three binary columns. The first column indicates that the value of x is non-zero. The second indicates that the value of x ≥ the median of non-zero values of x. The third indicates that the value of x ≥ the 75th percentile of non-zero values of x. Non-unique columns per covariate are dropped.

Groups of columns of the returned matrix are in the same order of columns in covars.

If covars has column names, the returned matrix will have the same column names with suffexes "_once", "_sporadic", and "_frequent" for the first, second, and third expanded columns, respectively.

Expanded covars matrix.

Sam Lendle

Schneeweiss, S., Rassen, J. A., Glynn, R. J., Avorn, J., Mogun, H., & Brookhart, M. A. (2009). High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology (Cambridge, Mass.), 20(4), 512.

lendle/hdps documentation built on May 9, 2019, 8:34 a.m.