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### Example of Section 4.1.
suppressMessages(library(psrwe, quietly = TRUE))
options(digits = 3)
data(ex_dta)
### First parts of Data.
head(ex_dta)
### Obtain PSs.
dta_ps_single <- psrwe_est(ex_dta,
v_covs = paste("V", 1:7, sep = ""),
v_grp = "Group", cur_grp_level = "current",
ps_method = "logistic", nstrata = 5)
### Balance assessment of PS stratification.
plot(dta_ps_single, "balance")
plot(dta_ps_single, "ps")
plot(dta_ps_single, "diff")
plot(dta_ps_single, "diff", metric = "astd", avg_only = TRUE)
### Obtain discounting parameters.
ps_bor_single <- psrwe_borrow(dta_ps_single, total_borrow = 30)
ps_bor_single
### PSPP, single arm study, binary outcome.
options(mc.cores = 1)
.msg <- capture.output({ suppressWarnings({
rst_pp <- psrwe_powerp(ps_bor_single,
outcome_type = "binary",
v_outcome = "Y_Bin",
seed = 1234)
}) })
rst_pp
### Plot PSPP results.
plot(rst_pp)
plot(rst_pp, add_stratum = TRUE)
### Outcome analysis.
oa_pp <- psrwe_outana(rst_pp, mu = 0.4)
oa_pp
### PSCL, single arm study, binary outcome.
rst_cl <- psrwe_compl(ps_bor_single,
outcome_type = "binary",
v_outcome = "Y_Bin")
rst_cl
### Outcome analysis.
oa_cl <- psrwe_outana(rst_cl, mu = 0.4)
oa_cl
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