This function will perform phase II of the multilevel propensity score analysis.

The ci.adjust provides a Bonferroni-Sidak adjusted confidence intervals based on the number of levels/clusters.

Usage

mlpsa(
  response,
  treatment = NULL,
  strata = NULL,
  level2 = NULL,
  minN = 5,
  reverse = FALSE,
  ci.level = 0.05
)

Arguments

response

vector containing the response values

treatment

vector containing the treatment conditions

strata

vector containing the strata for each response

level2

vector containing the level 2 specifications

minN

the minimum number of subjects per strata for that strata to be included in the analysis.

reverse

reverse the order of treatment and control for the difference calculation.

ci.level

the confidence level to use for confidence intervals. Defaults to a 95% confidence level.

Value

a mlpsa class

See also

[mlpsa.ctree()], [mlpsa.logistic()]

Examples

if (FALSE) { # \dontrun{
require(multilevelPSA)
require(party)
data(pisana)
data(pisa.colnames)
data(pisa.psa.cols)
mlctree = mlpsa.ctree(pisana[,c('CNT','PUBPRIV',pisa.psa.cols)], formula=PUBPRIV ~ ., level2='CNT')
student.party = getStrata(mlctree, pisana, level2='CNT')
student.party$mathscore = apply(student.party[,paste0('PV', 1:5, 'MATH')], 1, sum) / 5
results.psa.math = mlpsa(response=student.party$mathscore, 
       treatment=student.party$PUBPRIV, 
       strata=student.party$strata, 
       level2=student.party$CNT, minN=5)
results.psa.math
summary(results.psa.math)
} # }