cat.analysis: Categorical Data Analysis for Probability Survey Data
In mhweber/spsurvey: Spatial Survey Design and Analysis

Description Usage Arguments Value Other Functions Required Author(s) References See Also Examples

This function organizes input and output for analysis of categorical data generated by a probability survey. Input can be either an object of class spsurvey.analysis (see the documentation for function spsurvey.analysis) or through use of the other arguments to this function.

cat.analysis(sites = NULL, subpop = NULL, design = NULL,
  data.cat = NULL, popsize = NULL, popcorrect = FALSE,
  pcfsize = NULL, N.cluster = NULL, stage1size = NULL,
  sizeweight = FALSE, vartype = "Local", conf = 95,
  spsurvey.obj = NULL)

`sites`	Data frame consisting of two variables: the first variable is site IDs, and the second variable is a logical vector indicating which sites to use in the analysis. If spsurvey.obj is not provided, then this argument is required. The default is NULL.
`subpop`	Data frame describing sets of populations and subpopulations for which estimates will be calculated. The first variable is site IDs. Each subsequent variable identifies a Type of population, where the variable name is used to identify Type. A Type variable identifies each site with one of the subpopulations of that Type. If spsurvey.obj is not provided, then this argument is required. The default is NULL.
`design`	Data frame consisting of design variables. If spsurvey.obj is not provided, then this argument is required. The default is NULL. Variables should be named as follows: siteID Vector of site IDs wgt Vector of weights, which are either the weights for a single-stage sample or the stage two weights for a two-stage sample xcoord Vector of x-coordinates for location, which are either the x-coordinates for a single-stage sample or the stage two x-coordinates for a two-stage sample ycoord Vector of y-coordinates for location, which are either the y-coordinates for a single-stage sample or the stage two y-coordinates for a two-stage sample stratum Vector of the stratum codes for each site cluster Vector of the stage one sampling unit (primary sampling unit or cluster) codes for each site wgt1 Vector of stage one weights in a two-stage design xcoord1 Vector of the stage one x-coordinates for location in a two-stage design ycoord1 Vector of the stage one y-coordinates for location in a two-stage design support Vector of support values - for a finite resource, the value one (1) for a for site. For an extensive resource, the measure of the sampling unit associated with a site. Required for calculation of finite and continuous population correction factors. swgt Vector of size-weights, which is the stage two size-weight for a two-stage design. swgt1 Vector of stage one size-weights for a two-stage design.
`data.cat`	Data frame of categorical response variables. The first variable is site IDs. Subsequent variables are response variables. Missing data (NA) is allowed. If spsurvey.obj is not provided, then this argument is required. The default is NULL.
`popsize`	Known size of the resource, which is used to perform ratio adjustment to estimators expressed using measurement units for the resource and to calculate strata proportions for calculating estimates for a stratified sample. For a finite resource, this argument is either the total number of sampling units or the known sum of size-weights. For an extensive resource, this argument is the measure of the resource, i.e., either known total length for a linear resource or known total area for an areal resource. The argument must be in the form of a list containing an element for each population Type in the subpop data frame, where NULL is a valid choice for a population Type. The list must be named using the column names for the population Types in subpop. If a population Type doesn't contain subpopulations, then each element of the list is either a single value for an unstratified sample or a vector containing a value for each stratum for a stratified sample, where elements of the vector are named using the stratum codes. If a population Type contains subpopulations, then each element of the list is a list containing an element for each subpopulation, where the list is named using the subpopulation names. The element for each subpopulation will be either a single value for an unstratified sample or a named vector of values for a stratified sample. The default is NULL. Example popsize for a stratified sample: popsize = list("Pop 1"=c("Stratum 1"=750, "Stratum 2"=500, "Stratum 3"=250), "Pop 2"=list("SubPop 1"=c("Stratum 1"=350, "Stratum 2"=250, "Stratum 3"=150), "SubPop 2"=c("Stratum 1"=250, "Stratum 2"=150, "Stratum 3"=100), "SubPop 3"=c("Stratum 1"=150, "Stratum 2"=150, "Stratum 3"=75)), "Pop 3"=NULL) Example popsize for an unstratified sample: popsize = list("Pop 1"=1500, "Pop 2"=list("SubPop 1"=750, "SubPop 2"=500, "SubPop 3"=375), "Pop 3"=NULL)
`popcorrect`	Logical value that indicates whether finite or continuous population correction factors should be employed during variance estimation, where TRUE = use the correction factor and FALSE = do not use the correction factor. The default is FALSE. To employ the correction factor for a single-stage sample, values must be supplied for argument pcfsize and for the support variable of the design argument. To employ the correction factor for a two-stage sample, values must be supplied for arguments N.cluster and stage1size, and for the support variable of the design argument.
`pcfsize`	Size of the resource, which is required for calculation of finite and continuous population correction factors for a single-stage sample. For a stratified sample this argument must be a vector containing a value for each stratum and must have the names attribute set to identify the stratum codes. The default is NULL.
`N.cluster`	Number of stage one sampling units in the resource, which is required for calculation of finite and continuous population correction factors for a two-stage sample. For a stratified sample this argument must be a vector containing a value for each stratum and must have the names attribute set to identify the stratum codes. The default is NULL.
`stage1size`	Size of the stage one sampling units of a two-stage sample, which is required for calculation of finite and continuous population correction factors for a two-stage sample and must have the names attribute set to identify the stage one sampling unit codes. For a stratified sample, the names attribute must be set to identify both stratum codes and stage one sampling unit codes using a convention where the two codes are separated by the & symbol, e.g., "Stratum 1&Cluster 1". The default is NULL.
`sizeweight`	Logical value that indicates whether size-weights should be used in the analysis, where TRUE = use the size-weights and FALSE = do not use the size-weights. The default is FALSE.
`vartype`	The choice of variance estimator, where "Local" = local mean estimator and "SRS" = SRS estimator. The default is "Local".
`conf`	Numeric value for the confidence level. The default is 95.
`spsurvey.obj`	List of class spsurvey.analysis that was produced by the function spsurvey.analysis. Depending on input to that function, some elements of the list may be NULL. The default is NULL.

A data frame of population estimates for all combinations of population Types, subpopulations within Types, response variables, and categories within each response variable. Estimates are provided for proportion and size of the population plus standard error and confidence interval estimates.

dframe.check: check site IDs, the sites data frame, the subpop data frame, and the data.cat data frame to assure valid contents and, as necessary, create the sites data frame and the subpop data frame
vecprint: takes an input vector and outputs a character string with line breaks inserted
uniqueID: creates unique site IDs by appending a unique number to each occurrence of a site ID
input.check: check input values for errors, consistency, and compatibility with analytical functions
category.est: estimate proportion (expressed as percent) and size of a resource in each of a set of categories

Tony Olsen Olsen.Tony@epa.gov
Tom Kincaid Kincaid.Tom@epa.gov

Diaz-Ramos, S., D.L. Stevens, Jr., and A.R. Olsen. (1996). EMAP Statistical Methods Manual. EPA/620/R-96/XXX. Corvallis, OR: U.S. Environmental Protection Agency, Office of Research and Development, National Health Effects and Environmental Research Laboratory, Western Ecology Division.

category.est

# Categorical variable example for two resource classes:
mysiteID <- paste("Site", 1:100, sep="")
mysites <- data.frame(
  siteID=mysiteID,
  Active=rep(TRUE, 100))
mysubpop <- data.frame(
  siteID=mysiteID,
  All.Sites=rep("All Sites", 100),
  Resource.Class=rep(c("Good","Poor"), c(55,45)))
mydesign <- data.frame(
  siteID=mysiteID,
  wgt=runif(100, 10, 100),
  xcoord=runif(100),
  ycoord=runif(100),
  stratum=rep(c("Stratum1", "Stratum2"), 50))
mydata.cat <- data.frame(
  siteID=mysiteID,
  CatVar=rep(c("north", "south", "east", "west"), 25))
mypopsize <- list(
  All.Sites=c(Stratum1=3500, Stratum2=2000),
  Resource.Class=list(Good=c(Stratum1=2500, Stratum2=1500),
                      Poor=c(Stratum1=1000, Stratum2=500)))
cat.analysis(sites=mysites, subpop=mysubpop, design=mydesign,
  data.cat=mydata.cat, popsize=mypopsize)

# Exclude category "south" from the analysis:
mysites <- data.frame(
  siteID=mysiteID,
  Active=rep(c(TRUE, FALSE, TRUE, TRUE), 25))
cat.analysis(sites=mysites, subpop=mysubpop, design=mydesign,
  data.cat=mydata.cat, popsize=mypopsize)