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)

x | A |
---|---|

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 |

outcomes | Name of columns to compute incremental changes for. |

A `data.table`

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

# 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)#> sample strategy grp ic ie #> 1: 1 Strategy 2 Group 1 65827.82 2.516667 #> 2: 1 Strategy 2 Group 2 58907.17 2.247874 #> 3: 2 Strategy 2 Group 1 57389.52 2.139747 #> 4: 2 Strategy 2 Group 2 63251.77 2.711067 #> 5: 3 Strategy 2 Group 1 68718.28 3.708635 #> 6: 3 Strategy 2 Group 2 59492.99 2.150093