adj_val: Adjusted Value Calculation

In WARDEN: Workflows for Health Technology Assessments in R using Discrete EveNts

Adjusted Value Calculation

Description

This function calculates an adjusted value over a time interval with optional discounting. This is useful for instances when adding cycles may not be desirable, so one can perform "cycle-like" calculations without needing cycles, offering performance speeds. See the vignette on avoiding cycles for an example in a model.

Usage

adj_val(curtime, nexttime, by, expression, discount = NULL)

Arguments

curtime	Numeric. The current time point.
nexttime	Numeric. The next time point. Must be greater than or equal to curtime.
by	Numeric. The step size for evaluation within the interval.
expression	An expression evaluated at each step. Use time as the variable within the expression.
discount	Numeric or NULL. The discount rate to apply, or NULL for no discounting.

Details

The user can use the .time variable to select the corresponding time of the sequence being evaluated. For example, in c⁠urtime = 0, nexttime = 4, by = 1⁠, time would correspond to ⁠0, 1, 2, 3⁠. If using nexttime = 4.2, ⁠0, 1, 2, 3, 4⁠

Value

Numeric. The calculated adjusted value.

Examples

# Define a function or vector to evaluate
bs_age <- 1
vec <- 1:8/10

# Calculate adjusted value without discounting
adj_val(0, 4, by = 1, expression = vec[floor(.time + bs_age)])
adj_val(0, 4, by = 1, expression = .time * 1.1)

# Calculate adjusted value with discounting
adj_val(0, 4, by = 1, expression = vec[floor(.time + bs_age)], discount = 0.03)

WARDEN documentation built on Aug. 8, 2025, 7:50 p.m.