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Average hazard ratio under non-proportional hazards (test version)

Source: R/AHR.R
AHR.Rd

AHR() provides a geometric average hazard ratio under various non-proportional hazards assumptions for either single or multiple strata studies. The piecewise exponential distribution allows a simple method to specify a distribution and enrollment pattern where the enrollment, failure and dropout rates changes over time.

Usage

AHR(
  enrollRates = tibble::tibble(Stratum = "All", duration = c(2, 2, 10), rate = c(3, 6,
    9)),
  failRates = tibble::tibble(Stratum = "All", duration = c(3, 100), failRate =
    log(2)/c(9, 18), hr = c(0.9, 0.6), dropoutRate = rep(0.001, 2)),
  totalDuration = 30,
  ratio = 1,
  simple = TRUE
)

Arguments

enrollRates

Piecewise constant enrollment rates by stratum and time period.

failRates

Piecewise constant control group failure rates, duration for each piecewise constant period, hazard ratio for experimental vs control, and dropout rates by stratum and time period.

totalDuration

Total follow-up from start of enrollment to data cutoff; this can be a single value or a vector of positive numbers.

ratio

ratio of experimental to control randomization.

simple

logical; if TRUE (default), for each value in input totalDuration overall event count, statistical information and average hazard ratio are given; if FALSE, hazard ratio, expected events and statistical information are produced by stratum and underlying hazard ratio.

Value

A tibble with Time (from totalDuration), AHR (average hazard ratio), Events (expected number of events), info (information under given scenarios), and info0 (information under related null hypothesis) for each value of totalDuration input; if simple=FALSE, Stratum and t (beginning of each constant HR period) are also returned and HR is returned instead of AHR

Specification

The contents of this section are shown in PDF user manual only.

Examples

# Example: default
AHR()
#> # A tibble: 1 × 5
#>    Time   AHR Events  info info0
#>   <dbl> <dbl>  <dbl> <dbl> <dbl>
#> 1    30 0.695   58.5  14.3  14.6

# Example: default with multiple analysis times (varying totalDuration)

AHR(totalDuration = c(15, 30))
#> # A tibble: 2 × 5
#>    Time   AHR Events  info info0
#>   <dbl> <dbl>  <dbl> <dbl> <dbl>
#> 1    15 0.786   30.3  7.44  7.57
#> 2    30 0.695   58.5 14.3  14.6 

# Stratified population
enrollRates <- tibble::tibble(Stratum = c(rep("Low", 2), rep("High", 3)),
                              duration = c(2, 10, 4, 4, 8),
                              rate = c(5, 10, 0, 3, 6))
failRates <- tibble::tibble(Stratum = c(rep("Low", 2), rep("High", 2)),
                            duration = 1,
                            failRate = c(.1, .2, .3, .4),
                            hr = c(.9, .75, .8, .6),
                            dropoutRate = .001)
AHR(enrollRates = enrollRates, failRates = failRates, totalDuration = c(15, 30))
#> # A tibble: 2 × 5
#>    Time   AHR Events  info info0
#>   <dbl> <dbl>  <dbl> <dbl> <dbl>
#> 1    15 0.733   113.  28.1  28.3
#> 2    30 0.718   166.  41.3  41.5

# Same example, give results by strata and time period
AHR(enrollRates = enrollRates, failRates = failRates, totalDuration = c(15, 30), simple = FALSE)
#> # A tibble: 8 × 7
#>    Time Stratum     t    HR Events  info info0
#>   <dbl> <chr>   <dbl> <dbl>  <dbl> <dbl> <dbl>
#> 1    15 High        0  0.8   12.1   2.99  3.02
#> 2    15 High        1  0.6   23.1   5.72  5.78
#> 3    15 Low         0  0.9    9.96  2.48  2.49
#> 4    15 Low         1  0.75  68.1  16.9  17.0 
#> 5    30 High        0  0.8   14.2   3.51  3.54
#> 6    30 High        1  0.6   45.2  11.2  11.3 
#> 7    30 Low         0  0.9    9.96  2.48  2.49
#> 8    30 Low         1  0.75  96.8  24.1  24.2