Description Usage Arguments Details Value Author(s) References
View source: R/prioritize_covariates.R
Returns the indexes of columns covars
ordered by the possible amount of counfounding each column could adjust for.
1 2  prioritize_covariates(outcome, treatment, covars, return_bias = FALSE,
keep_NaNs = FALSE)

outcome 
binary vector of outcomes 
treatment 
binary vector of treatments 
covars 

return_bias 
Should the calculated multiplitive biases be returned with the ordered indexes? Defaults to 
keep_NaNs 
If the calculated multiplicitive bias for a covariate is 
For each covariate in covars
, the potential multiplicitive bias is calculated as described in Schneeweiss et al. (2009).
The column indexes are then put in descending order of the absolute value of the log of the multiplicitive bias.
If return_bias==TRUE
, the returned vector of indexes includes the multiplicitive biases sorted in the same order and stored in an attribute called "bias_m"
.
If outcome
has no variation for a particular value of a covariate, then the multiplicitive bias is calculated as NaN
.
If keep_NaNs==FALSE
, then the column indexes of such covariates are not included in the returned vector.
Vector of column indexes of covars
.
Sam Lendle
Schneeweiss, S., Rassen, J. A., Glynn, R. J., Avorn, J., Mogun, H., & Brookhart, M. A. (2009). Highdimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology (Cambridge, Mass.), 20(4), 512.
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