summary.PSRWE_DTA: Summarize PS estimation and stratification results

In psrwe: PS-Integrated Methods for Incorporating RWE in Clinical Studies

Summarize PS estimation and stratification results

Description

Get number of subjects and the distances of PS distributions for each PS stratum.

Usage

## S3 method for class 'PSRWE_DTA'
summary(
  object,
  metric = c("ovl", "ksd", "std", "abd", "ley", "mhb", "omkss"),
  min_n0 = 10,
  ...
)

Arguments

object	A list of class PSRWE_DAT that is generated using the psrwe_est function.
metric	Metric to use for calculating the distance with options: ovl Overlapping area (default) ksd Kullback-Leibler distance astd Standardized absolute mean difference std Standardized mean difference abd Absolute difference in means ley Levy distance mhb Mahalanobis distance omkss One minus Kolmogorov-Smirnov statistic
min_n0	threshold for number of external subjects, below which the external data in the current stratum will be ignored by setting the PS distance to 0. Default value 10.
...	Additional parameters.

Value

A list with columns:

• SummaryA data frame with Stratum, number of subjects in RWD, current study, number of subjects in control and treatment arms for RCT studies, and distance in PS distributions.

• OverallA data frame with overall number of not-trimmed subjects in RWD, number of patients in current study, number of subjects in control and treatment arms for RCT studies, and distance in PS distributions.

• NVector of total number of total RWD patients, number of trimmed RWD patients, and total number of current study patients.

• ps_fmlPS model.

• Distance_metricMetric used for calculating the distance.

Examples

data(ex_dta)
dta_ps <- psrwe_est(ex_dta,
                     v_covs = paste("V", 1:7, sep = ""),
                     v_grp = "Group",
                     cur_grp_level = "current")
dta_ps

## With different similarity metric
print(dta_ps, metric = "omkss")
dta_ps_sum <- summary(dta_ps, metric = "omkss")

psrwe documentation built on March 18, 2022, 5:33 p.m.