propTestN: Proportion Test (N Outcomes)

Description

The X<U+00B2> Goodness of fit test (not to be confused with the X<U+00B2> test of independence), tests the Null hypothesis that the proportions of observations match some expected proportions. If the p-value is low, this suggests that the Null hypothesis is false, and that the true proportions are different to those tested.

Usage

propTestN(data, var, counts = NULL, expected = FALSE, ratio = NULL,
  formula)

Arguments

data

the data as a data frame

var

the variable of interest in data (not necessary when using a formula, see the examples)

counts

the counts in data

expected

TRUE or FALSE (default), whether expected counts should be displayed

ratio

a vector of numbers: the expected proportions

formula

(optional) the formula to use, see the examples

Value

A results object containing:

`results$props`					a table of the proportions
`results$tests`					a table of the test results

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$props$asDF

as.data.frame(results$props)

Examples

Run this code

# NOT RUN {
data('HairEyeColor')
dat <- as.data.frame(HairEyeColor)

propTestN(formula = Freq ~ Eye, data = dat, ratio = c(1,1,1,1))

#
#  PROPORTION TEST (N OUTCOMES)
#
#  Proportions
#  --------------------------------
#    Level    Count    Proportion
#  --------------------------------
#    Brown      220         0.372
#    Blue       215         0.363
#    Hazel       93         0.157
#    Green       64         0.108
#  --------------------------------
#
#
#  X<U+00B2> Goodness of Fit
#  -----------------------
#    X<U+00B2>     df    p
#  -----------------------
#    133     3    < .001
#  -----------------------
#

# }

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