View source: R/plotIncidence.R
plotIncidence | R Documentation |
Calculates and plots the cervical cancer incidence for one or several prevention strategies.
plotIncidence(..., current=NULL, labels=NULL)
... |
one or several microsimulated cohort corresponding to one or several microsimulated cohorts. |
current |
real cervical cancer incidence in the population of interest. |
labels |
labels to be used in the plot. |
Returns a list with cervical cancer incidence for each age group.
David Moriña (Universitat de Barcelona), Pedro Puig (Universitat Autònoma de Barcelona) and Mireia Diaz (Institut Català d'Oncologia)
Georgalis L, de Sanjosé S, Esnaola M, Bosch F X, Diaz M. Present and future of cervical cancer prevention in Spain: a cost-effectiveness analysis. European Journal of Cancer Prevention 2016;25(5):430-439.
Moriña D, de Sanjosé S, Diaz M. Impact of model calibration on cost-effectiveness analysis of cervical cancer prevention 2017;7.
mSimCC-package
, microsim
, costs
, le
,
bCohort
, plotCIN2Incidence
, plotCIN1Incidence
,
plotCIN3Incidence
, plotMortality
, plotPrevalence
,
qalys
, yls
data(probs)
nsim <- 3
p.men <- 0
size <- 20
min.age <- 10
max.age <- 84
#### Natural history
hn <- microsim(seed=1234, nsim, probs, abs_states=c(10, 11), sympt_states=c(5, 6, 7, 8),
prob_sympt=c(0.11, 0.23, 0.66, 0.9),
size, p.men, min.age, max.age,
utilityCoefs = c(1, 1, 0.987, 0.87, 0.87, 0.76, 0.67, 0.67, 0.67, 0.938, 0, 0),
costCoefs.md = c(0, 0, 254.1, 1495.9, 1495.9, 5546.8, 12426.4, 23123.4,
34016.6, 0, 0, 0),
costCoefs.nmd = c(0, 0, 81.4, 194.1, 194.1, 219.1, 219.1, 219.1, 219.1, 0, 0, 0),
costCoefs.i = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), disc=3,
treatProbs=c(0,0,1,1,1,0.9894,0.9422,0.8262,0.5507,0,0,0),
nCores=1) ### individual level
hn_c <- bCohort(hn)
plotIncidence(hn_c) ### Aggregated level
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