Description Usage Arguments Value Examples
Takes treatments from a paired scenario with no early detection and updates treatments only for those advanced-stage cases who were stage-shifted in the early detection scenario
1 | update_treat_stageshift(policies, shifts, treats)
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policies |
Data frame specifying policies - see ex1$pol. If 'pairnum' = NA, no treatments are updated. If 'pairnum' is numeric, treatments from that number scenario will be the starting point, with early-detected cases shifted according to the next input |
shifts |
List of treatment-shift indicators (see shifttreatment_indicator) |
treats |
List of original treatment matrices (see treatments_by_policy) |
List of updated treatment matrices
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | library(bcimodel)
data(ex1)
# ex1$nh shows that there are 4 stage-subgroups. Use a fake random distribution of groups 1:4 for the population before stage-shifting.
popdistr <- matrix(sample.int(4, size=40, replace=TRUE), nrow=20, ncol=2)
# Create stageshift indicator matrices for all 3 scenarios: no stage shifts for #1 and #2, but 30% stageshift for #3. Use a small population of size 20, and 2 sims
stageshifts <- list(base=matrix(0, nrow=20, ncol=2),
tam=matrix(0, nrow=20, ncol=2),
tamshift=stageshift_indicator(0.85, 20, 2))
# Get the actual stages - only policy #3 has stage-shifting
stages <- lapply(stageshifts, shift_stages, original=popdistr, map=ex1$map)
# First 2 scenarios have no shifting, same treatment. Randomly distribute treatment
# Scenario 3 has shifting. NAs indicate that treatments will be same as the scenario
# with no early detection but same treatments
treats <- treatments_by_policy(policies=ex1$pol,
treat_chars=ex1$tx,
stagegroups=stages,
map=ex1$map,
pop_size=20, nsim=2)
# Indicators of treatment shifting
treatshifts <- lapply(ex1$pol$num,
shifttreatment_indicator,
type=ex1$pol$pairnum,
shifts=stageshifts,
basecase=popdistr,
map=ex1$map)
newtreat <- update_treat_stageshift(ex1$pol, treatshifts, treats)
# Two cases have been shifted in #3 compared to #2
lapply(treatshifts, table)
lapply(newtreat, table)
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