Learn R Programming

MAICtools (version 0.1.1)

unanchored_maic: Conduct non-Anchored Matching-Adjusted Indirect Comparison (MAIC).

Description

Conduct non-Anchored Matching-Adjusted Indirect Comparison (MAIC).

Value

A data frame containing the non-anchored matching-adjusted indirect comparison results.

Arguments

unds_wts

A combined data frame containing individual efficacy data from the intervention study and pseudo efficacy data from the comparator study.

unds.arm

The name of the grouping column in the combined data frame specified by unds_wts, e.g., comparator.arm = TRT. The default is TRT.

comparator.study

A character specifying or presenting the comparator study, e.g., comparator.study = "Study XX-1".

unds.param.var

The name of the column that specifies only a subset of the rows of the data to be used.

unds.param

A character specifying the subset of the rows to be used. This is the value of the column set by the unds.param.var.

time

The name of the survival or follow up time column in the combined data frame.

status

The status indicator, normally 0 = event, 1 = censored. Can be reseted using the event parameter.

event

A numeric value that represents the survival status, 0 = event, 1 = censored.

response

The name of the response status column in the unds_wts.

dtype

Two options are available: "HR" and "OR". The default is "HR".

wt.col

The name of the estimated weights column in the data frame specified by unds_wts. The default is wt.

CIw

The numeric value specifying the width of the confidence interval, with a default of 0.95.

digits

Specify the number of decimal places for the output results.

Examples

Run this code
# \donttest{
results3 <- unanchored_maic(
  unds_wts = unpts, unds.arm = ARM,
  comparator.study = "Study XX-1",
  unds.param.var = PARAMCD, unds.param = "OS",
  time = AVAL, status = CNSR, event = 0,
  dtype = "HR")

results3

results4 <- unanchored_maic(
  unds_wts = unpts, unds.arm = ARM,
  #' unds.param = "ORR",
  #' comparator.study = "Study XX-1",
  response = CNSR,
  dtype = "OR")

results4
# }

Run the code above in your browser using DataLab