节作者:Ravi Selker, Jonathon Love, Damian Dropmann
Proportion Test (2 Outcomes; propTest2
)¶
Description¶
The Binomial test is used to test the Null hypothesis that the proportion of observations match some expected value. If the p-value is low, this suggests that the Null hypothesis is false, and that the true proportion must be some other value.
Usage¶
propTest2(
data,
vars,
areCounts = FALSE,
testValue = 0.5,
hypothesis = "notequal",
ci = FALSE,
ciWidth = 95,
bf = FALSE,
priorA = 1,
priorB = 1,
ciBayes = FALSE,
ciBayesWidth = 95,
postPlots = FALSE
)
Arguments¶
data |
the data as a data frame |
vars |
a vector of strings naming the variables of interest in data |
areCounts |
TRUE or FALSE (default), the variables are counts |
testValue |
a number (default: 0.5), the value for the null hypothesis |
hypothesis |
'notequal' (default), 'greater' or 'less' , the alternative hypothesis |
ci |
TRUE or FALSE (default), provide confidence intervals |
ciWidth |
a number between 50 and 99.9 (default: 95), the confidence interval width |
bf |
TRUE or FALSE (default), provide Bayes factors |
priorA |
a number (default: 1), the beta prior ‘a’ parameter |
priorB |
a number (default: 1), the beta prior ‘b’ parameter |
ciBayes |
TRUE or FALSE (default), provide Bayesian credible intervals |
ciBayesWidth |
a number between 50 and 99.9 (default: 95), the credible interval width |
postPlots |
TRUE or FALSE (default), provide posterior plots |
Output¶
A results object containing:
results$table |
a table of the proportions and test results |
results$postPlots |
an array of the posterior plots |
Tables can be converted to data frames with
asDF
oras.data.frame()
. For example:
results$table$asDF
as.data.frame(results$table)
Examples¶
dat <- data.frame(x=c(8, 15))
propTest2(dat, vars = x, areCounts = TRUE)
#
# PROPORTION TEST (2 OUTCOMES)
#
# Binomial Test
# -------------------------------------------------------
# Level Count Total Proportion p
# -------------------------------------------------------
# x 1 8 23 0.348 0.210
# 2 15 23 0.652 0.210
# -------------------------------------------------------
# Note. Ha is proportion != 0.5
#