jmv: propTest2 – R documentation

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propTest2

Proportion Test (2 Outcomes)

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

Value

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 or as.data.frame. For example:

results$table$asDF

as.data.frame(results$table)

Examples

## Not run: 
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
#

## End(Not run)

jmv

The 'jamovi' Analyses

v1.2.23

GPL (>= 2)

Authors

Ravi Selker, Jonathon Love, Damian Dropmann

Initial release

2020-06-26