nca_follow_policy: NCA follow policy (internal; increasing monotonicity)
In aihuman: Experimental Evaluation of Algorithm-Assisted Human Decision-Making
nca_follow_policy R Documentation
NCA follow policy (internal; increasing monotonicity)
Description
Optimal policy whether to follow PSA recommendation for NCA as an outcome
and policy class with an increasing monotonicity constraint.
Used for the replication in the vignette.
Usage
nca_follow_policy
Format
A data frame with 41 rows and 6 variables:
- FTAScore
FTA score
- NCAScore
NCA score
- NVCAFlag
NVCA flag
- wts
Weight for each observation
- n
Number of such cases
- policy
Optimal policy
aihuman documentation built on April 12, 2025, 1:47 a.m.
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| nca_follow_policy | R Documentation |
NCA follow policy (internal; increasing monotonicity)
Description
Optimal policy whether to follow PSA recommendation for NCA as an outcome and policy class with an increasing monotonicity constraint. Used for the replication in the vignette.
Usage
nca_follow_policy
Format
A data frame with 41 rows and 6 variables:
- FTAScore
FTA score
- NCAScore
NCA score
- NVCAFlag
NVCA flag
- wts
Weight for each observation
- n
Number of such cases
- policy
Optimal policy
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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