spsurvey.analysis: Create an Object of Class spsurvey.analysis
In mhweber/spsurvey: Spatial Survey Design and Analysis

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

This function creates an object of class spsurvey.analysis that contains all of the information necessary to use the analysis functions in the spsurvey package.

spsurvey.analysis(sites = NULL, subpop = NULL, design = NULL,
  data.cat = NULL, data.cont = NULL, siteID = NULL, wgt = NULL,
  sigma = NULL, var.sigma = NULL, xcoord = NULL, ycoord = NULL,
  stratum = NULL, cluster = NULL, wgt1 = NULL, xcoord1 = NULL,
  ycoord1 = NULL, popsize = NULL, popcorrect = FALSE,
  pcfsize = NULL, N.cluster = NULL, stage1size = NULL,
  support = NULL, sizeweight = FALSE, swgt = NULL, swgt1 = NULL,
  vartype = "Local", conf = 95, pctval = c(5, 10, 25, 50, 75, 90,
  95))

`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 this data frame is not provided, then the data frame will be created, where (1) site IDs are obtained either from the design argument, the siteID argument, or both (when siteID is a formula); and (2) a variable named use.sites that contains the value TRUE for all sites is created. The default is NULL.
`subpop`	Data frame describing sets of populations and subpopulations for which estimates will be calculated. The first variable is siteIDs and 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 this data frame is not provided, then the data frame will be created, where (1) site IDs are obtained either from the design argument, the siteID argument, or both (when siteID is a formula); and (2) a single Type variable named all.sites that contains the value "All Sites" for all sites is created. The default is NULL.
`design`	Data frame consisting of design variables. If variable names are provided as formulas in the corresponding arguments, then the formulas are interpreted using this data frame. If this data frame is not provided, then the data frame will be created from inputs to the design variables in the argument list. The default is NULL. If variable names are not provided as formulas, then 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 psurvey.obj is not provided, then this argument is required. The default is NULL.
`data.cont`	Data frame of continuous response variables. The first variable is site IDs. Subsequent variables are response variables. Missing data (NA) is allowed. The default is NULL.
`siteID`	site IDs. This variable can be input directly or as a formula and must be supplied either as this argument or in the design data frame. The default is NULL.
`wgt`	Vector of final adjusted weights, which are either the weights for a single- stage sample or the stage two weights for a two-stage sample. This variable can be input directly or as a formula and must be supplied either as this argument or in the design data frame. The default is NULL.
`sigma`	Measurement error variance. This variable must be a vector containing a value for each response variable and must have the names attribute set to identify the response variable names. Missing data (NA) is allowed. The default is NULL.
`var.sigma`	Variance of the measurement error variance. This variable must be a vector containing a value for each response variable and must have the names attribute set to identify the response variable names. Missing data (NA) is allowed. The default is NULL.
`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. This variable can be input directly or as a formula and must be supplied either as this argument or in the design data frame when argument vartype is set to "Local". The default is NULL.
`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. This variable can be input directly or as a formula and must be supplied either as this argument or in the design data frame when argument vartype is set to "Local". The default is NULL.
`stratum`	The stratum codes. This variable can be input directly or as a formula. The default is NULL.
`cluster`	Vector of the stage one sampling unit (primary sampling unit or cluster) codes. This variable can be input directly or as a formula. The default is NULL.
`wgt1`	Vector of final adjusted stage one weights. This variable can be input directly or as a formula. The default is NULL.
`xcoord1`	Vector of the stage one x-coordinates for location. This variable can be input directly or as a formula. The default is NULL.
`ycoord1`	Vector of the stage one y-coordinates for location. This variable can be input directly or as a formula. 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. 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`	The 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.
`support`	Vector of the support value for each site - the value one (1) for a site from a finite resource or the measure of the sampling unit associated with a site from an extensive resource, which is required for calculation of finite and continuous population correction factors. This variable can be input directly or as a formula. 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.
`swgt`	Vector of the size-weight for each site, which is the stage two size-weight for a two-stage sample. This variable can be input directly or as a formula. The default is NULL.
`swgt1`	Vector of the stage one size-weight for each site. This variable can be input directly or as a formula. The default is NULL.
`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.
`pctval`	The set of values at which percentiles are estimated. The default set is: 5, 10, 25, 50, 75, 90, 95.

List of class spsurvey.analysis. Only those sites indicated by the logical variable in the sites data frame are retained in the output. The sites, subpop, and design data frames will always exist in the output. At least one of the data.cat and data.cont data frames will exist. Depending upon values of the input variables, other elements in the output may be NULL. The output list is composed of the following elements:

sites: the sites data frame.
subpop: the subpop data frame.
design: the design data frame.
data.cat: the data.cat data frame.
data.cont: the data.cont data frame.
sigma: measurement error variance.
var.sigma: variance of the estimated measurement error variance.
stratum.ind: a logical value that indicates whether the sample is stratified, where TRUE = a stratified sample and FALSE = not a stratified sample.
cluster.ind: a logical value that indicates whether the sample is a two-stage sample, where TRUE = a two-stage sample and FALSE = not a two-stage sample.
popsize: the known size of the resource.
pcfactor.ind: a logical value that indicates whether the population correction factor is used during variance estimation, where TRUE = use the population correction factor and FALSE = do not use the factor.
pcfsize: size of the resource, which is required for calculation of finite and continuous population correction factors for a single-stage sample.
N.cluster: the number of stage one sampling units in the resource stage1size

size of the stage one sampling units of a two-stage sample.

swgt.ind: a logical value that indicates whether the sample is a size-weighted sample, where TRUE = a size-weighted sample and FALSE = not a size-weighted sample.
vartype: the choice of variance estimator, where "Local" = local mean estimator and "SRS" = SRS estimator.
conf: the confidence level.
pctval: the set of values at which percentiles are estimated.

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

Tom Kincaid Kincaid.Tom@epa.gov

#Categorical variable example:
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)))

# Continuous variable example - including deconvolution estimates:
mydesign <- data.frame(
  ID=mysiteID,
  wgt=runif(100, 10, 100),
  xcoord=runif(100),
  ycoord=runif(100),
  stratum=rep(c("Stratum1", "Stratum2"), 50))
ContVar <- rnorm(100, 10, 1)
mydata.cont <- data.frame(
  siteID=mysiteID,
  ContVar=ContVar,
  ContVar.1=ContVar + rnorm(100, 0, sqrt(0.25)),
  ContVar.2=ContVar + rnorm(100, 0, sqrt(0.50)))
mysigma <- c(ContVar=NA, ContVar.1=0.25, ContVar.2=0.50)
spsurvey.analysis(sites=mysites, subpop=mysubpop[,1:2], design=mydesign,
  data.cont=mydata.cont, siteID=~ID, sigma=mysigma, popsize=mypopsize[1])