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This function estimates change between two probability surveys. Upper and lower confidence bounds also are estimated.
change.est(resp.ind, z_1, wgt_1, x_1=NULL, y_1=NULL, repeat_1, z_2,
wgt_2, x_2=NULL, y_2=NULL, repeat_2, revisitwgt=FALSE, test="mean",
stratum_1=NULL,stratum_2=NULL, cluster_1=NULL, cluster_2=NULL, wgt1_1=NULL,
x1_1=NULL, y1_1=NULL, wgt1_2=NULL, x1_2=NULL, y1_2=NULL, popsize_1=NULL,
popsize_2=NULL, popcorrect_1=FALSE, pcfsize_1=NULL, N.cluster_1=NULL,
stage1size_1=NULL, support_1=NULL, popcorrect_2=FALSE, pcfsize_2=NULL,
N.cluster_2=NULL, stage1size_2=NULL, support_2=NULL, sizeweight_1=FALSE,
swgt_1=NULL, swgt1_1=NULL, sizeweight_2=FALSE, swgt_2=NULL, swgt1_2=NULL,
vartype_1="Local", vartype_2="Local", conf=95, check.ind=TRUE, warn.ind=NULL,
warn.df=NULL, warn.vec=NULL)a character value that indicates the type of response variable, where "cat" indicates a categorical variable and "cont" indicates a continuous variable.
response value for each survey one site.
the final adjusted weight (inverse of the sample inclusion probability) for each survey one site, which is either the weight for a single-stage sample or the stage two weight for a two-stage sample.
x-coordinate for location for each survey one site, which is either the x-coordinate for a single-stage sample or the stage two x-coordinate for a two-stage sample. The default is NULL.
y-coordinate for location for each survey one site, which is either the y-coordinate for a single-stage sample or the stage two y-coordinate for a two-stage sample. The default is NULL.
a logical variable that identifies repeat visit sites for survey one.
response value for each survey two site.
the final adjusted weight for each survey two site.
x-coordinate for location for each survey two site. The default is NULL.
y-coordinate for location for each survey two site. The default is NULL.
a logical variable that identifies repeat visit sites for survey two.
a logical value that indicates whether each repeat visit site has the same survey design weight in the two surveys, where TRUE = the weight for each repeat visit site is the same and FALSE = the weight for each repeat visit site is not the same. When this argument is FALSE, all of the repeat visit sites are assigned equal weights when calculating the covariance component of the change estimate standard error. The default is FALSE.
a character string or character vector providing the location measure(s) to use for change estimation for continuous variables. The choices are "mean", "median", or c("mean", "median"). The default is "mean".
the stratum for each survey one site. The default is NULL.
the stratum for each survey two site. The default is NULL.
the stage one sampling unit (primary sampling unit or cluster) code for each survey one site. The default is NULL.
the stage one sampling unit (primary sampling unit or cluster) code for each survey two site. The default is NULL.
the final adjusted stage one weight for each survey one site. The default is NULL.
the stage one x-coordinate for location for each survey one site. The default is NULL.
the stage one y-coordinate for location for each survey one site. The default is NULL.
the final adjusted stage one weight for each survey two site. The default is NULL.
the stage one x-coordinate for location for each survey two site. The default is NULL.
the stage one y-coordinate for location for each survey two site. The default is NULL.
known size of the survey one 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. For a stratified sample this variable 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.
known size of the survey two resource. The default is NULL.
a logical value that indicates whether finite or continuous population correction factors should be employed during variance estimation for survey one, 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 arguments pcfsize_1 and support_1. To employ the correction factor for a two-stage sample, values must be supplied for arguments N.cluster_1, stage1size_1, and support_1.
size of the survey one 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 NULLL.
the number of stage one sampling units in the survey one resource, which is required for calculation of finite and continuous population correction factors for a two-stage sample. For a stratified sample this variable 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.
size of the stage one sampling units of a two-stage sample for survey one, 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.
the support value for each survey one 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. The default is NULL.
a logical value that indicates whether finite or continuous population correction factors should be employed during variance estimation for survey two, 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 arguments pcfsize_2 and support_2. To employ the correction factor for a two-stage sample, values must be supplied for arguments N.cluster_2, stage1size_2, and support_2.
size of the survey two resource. The default is NULLL.
the number of stage one sampling units in the survey two resource. The default is NULL.
size of the stage one sampling units of a two-stage sample for survey two. The default is NULL.
the support value for each survey two site. The default is NULL.
a logical value that indicates whether size-weights should be used in the analysis for survey one, where TRUE = use the size-weights and FALSE = do not use the size-weights. The default is FALSE.
the size-weight for each survey one site, which is the stage two size-weight for a two-stage sample. The default is NULL.
the stage one size-weight for each survey one site. The default is NULL.
a logical value that indicates whether size-weights should be used in the analysis for survey two. The default is FALSE.
the size-weight for each survey two site. The default is NULL.
the stage one size-weight for each survey two site. The default is NULL.
the choice of variance estimator for survey one, where "Local" = local mean estimator and "SRS" = SRS estimator. The default is "Local".
the choice of variance estimator for survey two. The default is "Local".
the confidence level. The default is 95%.
a logical value that indicates whether compatability checking of the input values is conducted, where TRUE = conduct compatibility checking and FALSE = do not conduct compatibility checking. The default is TRUE.
a logical value that indicates whether warning messages were generated, where TRUE = warning messages were generated and FALSE = warning messages were not generated. The default is NULL.
a data frame for storing warning messages. The default is NULL.
a vector that contains names of the population type, the subpopulation, and an indicator. The default is NULL.
If the function was called by the change.analysis function, then value is a list containing the following components:
Results - a data frame containing estimates and confidence
bounds
warn.ind - a logical value indicating whether warning messages
were generated
warn.df - a data frame containing warning messages
If the function was called directly, then value is a data frame containing estimates and confidence bounds.
Change estimates are calculated using the Horvitz-Thompson ratio estimator, i.e., the ratio of two Horvitz-Thompson estimators. The numerator of the ratio estimates the size of the category (for categorical variables) or the variable total (for a continuous variable). The denominator of the ratio estimates the size of the resource. Variance estimates for the proportion estimates are calculated using either the local mean variance estimator or the simple random sampling (SRS) variance estimator. The choice of variance estimator is subject to user control. The local mean variance estimator requires the x-coordinate and the y-coordinate of each site. The SRS variance estimator uses the independent random sample approximation to calculate joint inclusion probabilities. Confidence bounds are calculated using a Normal distribution multiplier. For a finite resource size is the number of units in the resource. For an extensive resource size is the measure (extent) of the resource, i.e., length, area, or volume. Size estimates are calculated using the Horvitz- Thompson estimator. Variance estimates for the size estimates are calculated using either the local mean variance estimator or the SRS variance estimator. The function can accommodate a stratified sample. For a stratified sample, separate estimates and standard errors are calculated for each stratum, which are used to produce estimates and standard errors for all strata combined. Strata that contain a single value are removed. For a stratified sample, when either the size of the resource or the sum of the size-weights for the resource is provided for each stratum, those values are used as stratum weights for calculating the estimates and standard errors for all strata combined. In addition, when either of those known values is provided for each stratum, size estimates are obtained by multiplying the proportion estimate, i.e., the Horvitz-Thompson ratio estimator, by the known value for the stratum. For a stratified sample when neither the size of the resource nor the sum of the size-weights of the resource is provided for each stratum, estimated values are used as stratum weights for calculating the estimates and standard errors for all strata combined. The function can accommodate single-stage and two-stage samples for both stratified and unstratified sampling designs. Finite population and continuous population correction factors can be utilized in variance estimation. The function checks for compatibility of input values and removes missing values.
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.
# NOT RUN {
# Categorical variable example:
z_1 <- sample(c("Good","Fair","Poor"), 100, replace=TRUE)
z_2 <- sample(c("Good","Fair","Poor"), 100, replace=TRUE)
wgt_1 <- runif(100, 10, 100)
wgt_2 <- runif(100, 10, 100)
repeat_1 <- rep(c(TRUE,FALSE), c(20,80))
repeat_2 <- rep(c(TRUE,FALSE), c(20,80))
stratum_1 <- rep(c("Stratum1", "Stratum2"), 50)
stratum_2 <- rep(c("Stratum1", "Stratum2"), 50)
change.est(resp.ind="cat", z_1=z_1, wgt_1=wgt_1, repeat_1=repeat_1,
z_2=z_2, wgt_2=wgt_2, repeat_2=repeat_2, stratum_1=stratum_1,
stratum_2=stratum_2, vartype_1="SRS", vartype_2="SRS")
# Continuous variable example:
z_1 <- rnorm(100, 10,10)
z_2 <- rnorm(100, 12, 10)
stratum_1 <- rep(c("Stratum1", "Stratum2"), 50)
stratum_2 <- rep(c("Stratum1", "Stratum2"), 50)
change.est(resp.ind="cont", z_1=z_1, wgt_1=wgt_1, repeat_1=repeat_1,
z_2=z_2, wgt_2=wgt_2, repeat_2=repeat_2, stratum_1=stratum_1,
stratum_2=stratum_2, vartype_1="SRS", vartype_2="SRS")
# }
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