boot.dr_scores: Bootstrap average effects
In bonander/CEAforests: Tree-based heterogenous cost-effectiveness and policy learning with individual-level data (beta)
Description
Usage
Arguments
Value
Description
boot.dr_scores Bootstraps doubly robust scores and obtains accelerated bootstrap confidence intervals (BCa).
Usage
1
boot.dr_scores(dc, dy, R, WTP, alpha)
Arguments
dc
delta_cost
dy
delta_y
alpha
Desired confidence level.
Value
Returns a matrix with estimated standard errors and BCa confidence intervals.
bonander/CEAforests documentation built on April 1, 2021, 10:57 a.m.
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Description Usage Arguments Value
Description
boot.dr_scores Bootstraps doubly robust scores and obtains accelerated bootstrap confidence intervals (BCa).
Usage
1 | boot.dr_scores(dc, dy, R, WTP, alpha)
|
Arguments
dc |
delta_cost |
dy |
delta_y |
alpha |
Desired confidence level. |
Value
Returns a matrix with estimated standard errors and BCa confidence intervals.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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