nbc4va (version 1.2)

ova2nbc: Translate open verbal autopsy arguments to train a NBC model

Description

A wrapper function for creating an nbc object with the parameters specified by the openVA package.

Usage

ova2nbc(symps.train, symps.test, causes.train, causes.table = NULL, ...)

Arguments

symps.train

Dataframe of verbal autopsy train data.

• Columns (in order): ID, Cause, Symptom-1 to Symptom-n..

• ID (vectorof char): case identifiers

• Cause (vectorof char): observed causes for each case

• Symptom-n.. (vectorsof char): "Y" for presence, "" for absence, "." for missing

Example:

ID	Cause	S1	S2	S3
"a1"	"HIV"	"Y"	""	"."
"b2"	"Stroke"	"."	""	"Y"

symps.test

Dataframe of verbal autopsy test data in the same format as symps.train.

• If (causes.train is (vectorof char)): symps.test is assumed to not have a cause column

causes.train

The train vector or column for the causes of death to use.

• If (vectorof char): cause of death values with number of values equal to nrow(symps.train); it is assumed that symps.test has no causes of death column

• If (char): name of cause of death column from symps.train

causes.table

Character list of unique causes to learn.

• If (NULL): set to unique causes of death in symps.train

...

Additional arguments to be passed to avoid errors if necessary.

Value

nbc An nbc object with the following modifications:

• $id (vectorof char): set to test data ids

• $prob (matrixof numeric): set to a matrix of likelihood for each cause of death for the test cases

• $CSMF (vectorof char): set to the predicted CSMFs with names for the corresponding causes

References

• Li Z, McCormick T, Clark S. openVA: Automated Method for Verbal Autopsy [Internet]. 2016. [cited 2016 Apr 29]. Available from: https://cran.r-project.org/package=openVA

Examples

# NOT RUN {
library(openVA)  # install.packages("openVA")
library(nbc4va)

# Obtain some openVA formatted data
data(RandomVA3) # cols: deathId, cause, symptoms..
train <- RandomVA3[1:100, ]
test <- RandomVA3[101:200, ]

# Run naive bayes classifier on openVA data
results <- ova2nbc(train, test, "cause")

# Obtain the probabilities and predictions
prob <- results$prob.causes
pred <- results$pred.causes
# }
# NOT RUN {
# }