R: Implement InSilicoVA methods with more flexible customization

insilico.fit {InSilicoVA}

R Documentation

Implement InSilicoVA methods with more flexible customization

Description

This function implements InSilicoVA model. This is the lower level core function of InSilicoVA with more flexibility in customized input. For more detail of model specification, see the paper on https://arxiv.org/abs/1411.3042 and the default function insilico.

Usage

insilico.fit(
  data,
  data.type = c("WHO2012", "WHO2016")[1],
  sci = NULL,
  isNumeric = FALSE,
  updateCondProb = TRUE,
  keepProbbase.level = TRUE,
  CondProb = NULL,
  CondProbNum = NULL,
  datacheck = TRUE,
  datacheck.missing = TRUE,
  warning.write = FALSE,
  directory = NULL,
  external.sep = TRUE,
  Nsim = 4000,
  thin = 10,
  burnin = 2000,
  auto.length = TRUE,
  conv.csmf = 0.02,
  jump.scale = 0.1,
  levels.prior = NULL,
  levels.strength = 1,
  trunc.min = 1e-04,
  trunc.max = 0.9999,
  subpop = NULL,
  java_option = "-Xmx1g",
  seed = 1,
  phy.code = NULL,
  phy.cat = NULL,
  phy.unknown = NULL,
  phy.external = NULL,
  phy.debias = NULL,
  exclude.impossible.cause = c("subset2", "subset", "all", "InterVA", "none")[1],
  impossible.combination = NULL,
  no.is.missing = FALSE,
  customization.dev = FALSE,
  Probbase_by_symp.dev = FALSE,
  probbase.dev = NULL,
  table.dev = NULL,
  table.num.dev = NULL,
  gstable.dev = NULL,
  nlevel.dev = NULL,
  indiv.CI = NULL,
  groupcode = FALSE,
  ...
)

Arguments

`data`	see `insilico`
`data.type`	see `insilico`
`sci`	see `insilico`
`isNumeric`	see `insilico`
`updateCondProb`	see `insilico`
`keepProbbase.level`	see `insilico`
`CondProb`	see `insilico`
`CondProbNum`	see `insilico`
`datacheck`	see `insilico`
`datacheck.missing`	see `insilico`
`warning.write`	see `insilico`
`directory`	see `insilico`
`external.sep`	see `insilico`
`Nsim`	see `insilico`
`thin`	see `insilico`
`burnin`	see `insilico`
`auto.length`	see `insilico`
`conv.csmf`	see `insilico`
`jump.scale`	see `insilico`
`levels.prior`	see `insilico`
`levels.strength`	see `insilico`
`trunc.min`	see `insilico`
`trunc.max`	see `insilico`
`subpop`	see `insilico`
`java_option`	see `insilico`
`seed`	see `insilico`
`phy.code`	see `insilico`
`phy.cat`	see `insilico`
`phy.unknown`	see `insilico`
`phy.external`	see `insilico`
`phy.debias`	see `insilico`
`exclude.impossible.cause`	see `insilico`
`impossible.combination`	see `insilico.train`
`no.is.missing`	see `insilico`
`customization.dev`	Logical indicator for customized variables
`Probbase_by_symp.dev`	Not tested yet.
`probbase.dev`	The customized conditional probabilities of symptoms given causes, which could be in a different format than InterVA default, but it should consist of `nlevel.dev` levels rather than numerical values.
`table.dev`	The table of level names in `probbase.dev`. Default to be NULL
`table.num.dev`	The corresponding prior numerical values for each level in `probbase.dev`, in the same order as `table.dev`. Default to be NULL
`gstable.dev`	Table of gold standard causes for each death. Default to be NULL
`nlevel.dev`	number of levels in `probbase.dev`. Default to be NULL
`indiv.CI`	credible interval for individual probabilities
`groupcode`	logical indicator of including the group code in the output causes
`...`	unused arguments

Value

a insilico fit object, see see insilico for more detail.

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(2014) Probabilistic cause-of-death assignment using verbal autopsies, https://arxiv.org/abs/1411.3042
Working paper no. 147, Center for Statistics and the Social Sciences, University of Washington