Calculate present value for a payoff in a single cohort with dynamic pricing across multiple timepoints

Source: R/future.R

Present value of a series of payoffs for a single given cohort, entering at given future time, allowing for dynamic pricing. This function is a wrapper for dynpv() restricted to evaluation of a single cohort.

futurepv(tzero = 0, payoffs, prices, discrate)

Arguments

tzero

Time at the date of calculation, to be used in lookup in prices vector

payoffs

Vector of payoffs of interest (numeric vector)

prices

Vector of price indices through the time horizon of interest

discrate

Discount rate per timestep, corresponding to price index

Value

A list inputs, results and pv. The inputs list contains a list of the following parameters called with the function: uptakes, payoffs, horizon, tzero, prices, and discrate. The results output is a class_dynpv() S7 object that contains the following elements:

  • name: Name given to the object

  • df: Tibble of calculation results

  • ncoh: Number of cohorts of uptaking patients (always 1)

  • ntimes: Number of times (unique values of tzero) at which calculations are performed

  • uptake: Total number of uptaking patients (always 1)

  • total: Total present value

  • mean: Average present value per uptaking patient (=total/uptake)

  • sum_by_coh: Tibble of summarized calculation results for each uptake cohort

  • inputs: list contains a list of the following parameters called with the function: uptakes, payoffs, horizon, tzero, prices, and discrate. The pv output is numeric, a convenience value equal to $results$mean.

See also

dynpv()

Examples

# Obtain dataset
democe <- get_dynfields(
   heemodel = oncpsm,
   payoffs = c("cost_daq_new", "cost_total", "qaly"),
   discount = "disc"
   )

# Obtain discount rate
discrate <- get_param_value(oncpsm, "disc")

# Obtain payoff vector of interest
payoffs <- democe |>
   dplyr::filter(int=="new") |>
   dplyr::mutate(cost_oth_rup = cost_total_rup - cost_daq_new_rup)
Nt <- nrow(payoffs)

# Run calculation for times 0-9
fpv <- futurepv(
  tzero = (0:9)*52,
  payoffs = payoffs$cost_oth_rup,
  prices = 1.001^(1:(2*Nt)-1), # Approx 5.3% every 52 steps
  discrate = 0.001 + discrate
)
fpv$results
#> This is a dynamicpv::class_dynpv S7 object, named NA . 
#>      Number of cohorts:             1044 
#>      Number of times:               10 
#> 
#>  Uptake, total and mean present values by timepoint: 
#> # A tibble: 10 × 4
#>    tzero uptake  total   mean
#>    <dbl>  <dbl>  <dbl>  <dbl>
#>  1     0      1 52165. 52165.
#>  2    52      1 54948. 54948.
#>  3   104      1 57880. 57880.
#>  4   156      1 60967. 60967.
#>  5   208      1 64220. 64220.
#>  6   260      1 67646. 67646.
#>  7   312      1 71255. 71255.
#>  8   364      1 75056. 75056.
#>  9   416      1 79060. 79060.
#> 10   468      1 83278. 83278.
#> 
#>  The full dataset is available using @df. 
fpv$pv
#> # A tibble: 10 × 2
#>    tzero   mean
#>    <dbl>  <dbl>
#>  1     0 52165.
#>  2    52 54948.
#>  3   104 57880.
#>  4   156 60967.
#>  5   208 64220.
#>  6   260 67646.
#>  7   312 71255.
#>  8   364 75056.
#>  9   416 79060.
#> 10   468 83278.