EnvStats: htestCensored.object – R documentation

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htestCensored.object

S3 Class "htestCensored"

Description

This class of objects is returned by EnvStats functions that perform hypothesis tests based on censored data. Objects of class "htestCensored" are lists that contain information about the null and alternative hypotheses, the censoring side, the censoring levels, the percentage of observations that are censored, the estimated distribution parameters (if applicable), the test statistic, the p-value, and (optionally, if applicable) confidence intervals for distribution parameters.

Details

Objects of S3 class "htestCensored" are returned by the functions listed in the section Hypothesis Tests in the help file EnvStats Functions for Censored Data. Currently, the only function listed is twoSampleLinearRankTestCensored.

Value

Required Components
The following components must be included in a legitimate list of class "htestCensored".

`statistic`	numeric scalar containing the value of the test statistic, with a `names` attribute indicating the null distribution.
`parameters`	numeric vector containing the parameter(s) associated with the null distribution of the test statistic. This vector has a `names` attribute describing its element(s).
`p.value`	numeric scalar containing the p-value for the test under the null hypothesis.
`null.value`	numeric vector containing the value(s) of the population parameter(s) specified by the null hypothesis. This vector has a `names` attribute describing its elements.
`alternative`	character string indicating the alternative hypothesis (the value of the input argument `alternative`). Possible values are `"greater"`, `"less"`, or `"two-sided"`.
`method`	character string giving the name of the test used.
`sample.size`	numeric scalar containing the number of non-missing observations in the sample used for the hypothesis test.
`data.name`	character string containing the actual name(s) of the input data.
`bad.obs`	the number of missing (`NA`), undefined (`NaN`) and/or infinite (`Inf`, `-Inf`) values that were removed from the data object prior to performing the hypothesis test.
`censoring.side`	character string indicating whether the data are left- or right-censored.
`censoring.name`	character string indicating the name of the data object used to identify which values are censored.
`censoring.levels`	numeric scalar or vector indicating the censoring level(s).
`percent.censored`	numeric scalar indicating the percent of non-missing observations that are censored.

Optional Components
The following component may optionally be included in an object of of class "htestCensored":

`estimate`	numeric vector containing the value(s) of the estimated population parameter(s) involved in the null hypothesis. This vector has a `names` attribute describing its element(s).
`estimation.method`	character string containing the method used to compute the estimated distribution parameter(s). The value of this component will depend on the available estimation methods (see `Distribution.df`).
`interval`	a list containing information about a confidence, prediction, or tolerance interval.

Methods

Generic functions that have methods for objects of class "htestCensored" include:
print.

Note

Since objects of class "htestCensored" are lists, you may extract their components with the $ and [[ operators.

Author(s)

Steven P. Millard (EnvStats@ProbStatInfo.com)

Examples

# Create an object of class "htestCensored", then print it out. 
  #--------------------------------------------------------------

  htestCensored.obj <-   with(EPA.09.Ex.16.5.PCE.df, 
    twoSampleLinearRankTestCensored(
      x = PCE.ppb[Well.type == "Compliance"], 
      x.censored = Censored[Well.type == "Compliance"], 
      y = PCE.ppb[Well.type == "Background"], 
      y.censored = Censored[Well.type == "Background"], 
      test = "tarone-ware", alternative = "greater"))

  mode(htestCensored.obj) 
  #[1] "list" 

  class(htestCensored.obj) 
  #[1] "htest" 

  names(htestCensored.obj) 
  # [1] "statistic"         "parameters"        "p.value"          
  # [4] "estimate"          "null.value"        "alternative"      
  # [7] "method"            "estimation.method" "sample.size"      
  #[10] "data.name"         "bad.obs"           "censoring.side"   
  #[13] "censoring.name"    "censoring.levels"  "percent.censored" 
 
  htestCensored.obj 
  
  #Results of Hypothesis Test
  #Based on Censored Data
  #--------------------------
  #
  #Null Hypothesis:                 Fy(t) = Fx(t)
  #
  #Alternative Hypothesis:          Fy(t) > Fx(t) for at least one t
  #
  #Test Name:                       Two-Sample Linear Rank Test:
  #                                 Tarone-Ware Test
  #                                 with Hypergeometric Variance
  #
  #Censoring Side:                  left
  #
  #Data:                            x = PCE.ppb[Well.type == "Compliance"]
  #                                 y = PCE.ppb[Well.type == "Background"]
  #
  #Censoring Variable:              x = Censored[Well.type == "Compliance"]
  #                                 y = Censored[Well.type == "Background"]
  #
  #Sample Sizes:                    nx = 8
  #                                 ny = 6
  #
  #Percent Censored:                x = 12.5%
  #                                 y = 50.0%
  #
  #Test Statistics:                 nu     =  8.458912
  #                                 var.nu = 20.912407
  #                                 z      =  1.849748
  #
  #P-value:                         0.03217495

  #==========

  # Extract the test statistics
  #----------------------------

  htestCensored.obj$statistic
  #       nu    var.nu         z 
  # 8.458912 20.912407  1.849748

  #==========

  # Clean up
  #---------
  rm(htestCensored.obj)

EnvStats

Package for Environmental Statistics, Including US EPA Guidance

v2.4.0

GPL (>= 3)

Authors

Steven P. Millard [aut], Alexander Kowarik [ctb, cre] (<https://orcid.org/0000-0001-8598-4130>)

Initial release

2020-10-20