incr_effect function

Incremental treatment effect

Computes incremental effect for all treatment strategies on outcome variables from a probabilistic sensitivity analysis relative to a comparator.

incr_effect(x, comparator, sample, strategy, grp = NULL, outcomes)

Arguments

• x: A data.frame or data.table containing simulation output with information on outcome variables for each randomly sampled parameter set from a PSA. Each row should denote a randomly sampled parameter set and treatment strategy.
• comparator: The comparator strategy. If the strategy column is a character variable, then must be a character; if the strategy column is an integer variable, then must be an integer.
• sample: Character name of column denoting a randomly sampled parameter set.
• strategy: Character name of column denoting treatment strategy.
• grp: Character name of column denoting subgroup. If NULL, then it is assumed that there is only one group.
• outcomes: Name of columns to compute incremental changes for.

Returns

A data.table containing the differences in the values of each variable specified in outcomes between each treatment strategy and the comparator.

Examples

# simulation output
n_samples <- 100
sim <- data.frame(sample = rep(seq(n_samples), 4),
             c = c(rlnorm(n_samples, 5, .1), rlnorm(n_samples, 5, .1),
                    rlnorm(n_samples, 11, .1), rlnorm(n_samples, 11, .1)),
             e = c(rnorm(n_samples, 8, .2), rnorm(n_samples, 8.5, .1),
                   rnorm(n_samples, 11, .6), rnorm(n_samples, 11.5, .6)),
             strategy = rep(paste0("Strategy ", seq(1, 2)),
                           each = n_samples * 2),
             grp = rep(rep(c("Group 1", "Group 2"),
                           each = n_samples), 2)
)
# calculate incremental effect of Strategy 2 relative to Strategy 1 by group
ie <- incr_effect(sim, comparator = "Strategy 1", sample = "sample",
                        strategy = "strategy", grp = "grp", outcomes = c("c", "e"))
head(ie)