pval_func: Outcome analysis.
In matchMulti: Optimal Multilevel Matching using a Network Algorithm
View source: R/matchMulti-internal.R
pval_func R Documentation
Outcome analysis.
Description
Calcualtes p-values for test of sharp null for treatment effect.
Usage
pval_func(
obj,
out.name = NULL,
schl_id_name = NULL,
treat.name = NULL,
wt = TRUE
)
Arguments
obj
A multiMatch object
out.name
Name of outcome covariate
schl_id_name
Name of school (group) identifier
treat.name
Name of treatment indicator
wt
Logical flag for whether p-value should weight strata by size.
Value
A p-value for constant-additive treatment effect.
Author(s)
Luke Keele, Penn State University, ljk20@psu.edu
Sam Pimentel, University of Pennsylvania, spi@wharton.upenn.edu
References
Rosenbaum, Paul R. (2002). Observational Studies.
Springer-Verlag.
Rosenbaum, Paul R. (2010). Design of Observational Studies.
Springer-Verlag.
matchMulti documentation built on May 31, 2023, 9:13 p.m.
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View source: R/matchMulti-internal.R
| pval_func | R Documentation |
Outcome analysis.
Description
Calcualtes p-values for test of sharp null for treatment effect.
Usage
pval_func(
obj,
out.name = NULL,
schl_id_name = NULL,
treat.name = NULL,
wt = TRUE
)
Arguments
obj |
A multiMatch object |
out.name |
Name of outcome covariate |
schl_id_name |
Name of school (group) identifier |
treat.name |
Name of treatment indicator |
wt |
Logical flag for whether p-value should weight strata by size. |
Value
A p-value for constant-additive treatment effect.
Author(s)
Luke Keele, Penn State University, ljk20@psu.edu
Sam Pimentel, University of Pennsylvania, spi@wharton.upenn.edu
References
Rosenbaum, Paul R. (2002). Observational Studies. Springer-Verlag.
Rosenbaum, Paul R. (2010). Design of Observational Studies. Springer-Verlag.
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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