This function is the summary method for class insilico.
Usage
## S3 method for class 'insilico'
summary(object, CI.csmf = 0.95, CI.cond = 0.95,
file = NULL, top = 10, id = NULL, ...)
Arguments
object
Fitted "insilico" object.
CI.csmf
Confidence interval for CSMF estimates.
CI.cond
Confidence interval for conditional probability estimates
file
Optional .csv file to write to. If it is specified, individual
cause of death distribution will be saved to the file.
top
Number of top causes to display on screen.
id
ID of specific death to display on screen.
...
Not used.
Details
summary.insilico formats some basic information about the InSilicoVA
fitted object on screen and show the several top CSMFs of user's choice. See
below for more detail.
Value
id.all
all IDs of the deaths.
indiv
individual Cause of Death distribution matrix.
csmf
CSMF distribution and confidence interval for each cause.
csmf.ordered
CSMF distribution and confidence interval for each cause, ordered by mean.
condprob
Conditional probability matrix and confidence intervals.
updateCondProb
Component of "insilico" object.
keepProbbase.level
Component of "insilico" object.
datacheck
Component of "insilico" object.
Nsim
Component of "insilico" object.
thin
Component of "insilico" object.
burnin
Component
of "insilico" object.
jump.scale
Component of "insilico" object.
levels.prior
Component of "insilico" object.
levels.strength
Component of "insilico" object.
trunc.min
Component of "insilico" object.
trunc.max
Component of "insilico" object.
subpop_counts
Component of "insilico" object.
showTop
Component of "insilico" object.
Author(s)
Zehang Li, Tyler McCormick, Sam Clark
Maintainer: Zehang Li <lizehang@uw.edu>
References
Tyler H. McCormick, Zehang R. Li, Clara Calvert, Amelia C.
Crampin, Kathleen Kahn and Samuel J. Clark Probabilistic cause-of-death
assignment using verbal autopsies, arXiv preprint arXiv:1411.3042http://arxiv.org/abs/1411.3042 (2014)
See Also
insilico, plot.insilico
Examples
## Not run:
# load sample data together with sub-population list
data(RandomVA1)
# extract InterVA style input data
data <- RandomVA1$data
# extract sub-population information.
# The groups are "HIV Positive", "HIV Negative" and "HIV status unknown".
subpop <- RandomVA1$subpop
# run without subpopulation
fit1<- insilico( data, subpop = NULL,
Nsim = 400, burnin = 200, thin = 10 , seed = 1,
external.sep = TRUE, keepProbbase.level = TRUE)
summary(fit1)
summary(fit1, top = 10)
# save individual COD distributions to files
summary(fit1, file = "results.csv")
## End(Not run)