Generates small area estimates by smoothing direct estimates using an area level model
Usage
smoothArea(
formula,
domain,
design = NULL,
adj.mat = NULL,
X.domain = NULL,
direct.est = NULL,
domain.size = NULL,
transform = c("identity", "logit", "log"),
pc.u = 1,
pc.alpha = 0.01,
pc.u.phi = 0.5,
pc.alpha.phi = 2/3,
level = 0.95,
n.sample = 250,
var.tol = 1e-10,
return.samples = F
)Arguments
- formula
An object of class 'formula' describing the model to be fitted. If direct.est is specified, the right hand side of the formula is not necessary.
- domain
One-sided formula specifying factors containing domain labels
- design
An object of class "svydesign" containing the data for the model
- adj.mat
Adjacency matrix with rownames matching the domain labels. If set to NULL, the IID spatial effect will be used.
- X.domain
Data frame of areal covariates. One of the column names needs to match the name of the domain variable, in order to be linked to the data input. Currently only supporting time-invariant covariates.
- direct.est
Data frame of direct estimates, with first column containing the domain variable, second column containing direct estimate, and third column containing the variance of direct estimate.
- domain.size
Data frame of domain sizes. One of the column names needs to match the name of the domain variable, in order to be linked to the data input and there must be a column names 'size' containing domain sizes.
- transform
Optional transformation applied to the direct estimates before fitting area level model. The default option is no transformation, but logit and log are implemented.
- pc.u
Hyperparameter U for the PC prior on precisions. See the INLA documentation for more details on the parameterization.
- pc.alpha
Hyperparameter alpha for the PC prior on precisions.
- pc.u.phi
Hyperparameter U for the PC prior on the mixture probability phi in BYM2 model.
- pc.alpha.phi
Hyperparameter alpha for the PC prior on the mixture probability phi in BYM2 model.
- level
The specified level for the posterior credible intervals
- n.sample
Number of draws from posterior used to compute summaries
- var.tol
Tolerance parameter; if variance of an area's direct estimator is below this value, that direct estimator is dropped from model
- return.samples
If TRUE, return matrix of posterior samples of area level quantities
Examples
if (FALSE) { # \dontrun{
data(DemoData2)
data(DemoMap2)
library(survey)
des0 <- svydesign(ids = ~clustid+id, strata = ~strata,
weights = ~weights, data = DemoData2, nest = TRUE)
Xmat <- aggregate(age~region, data = DemoData2, FUN = mean)
# EXAMPLE 1: Continuous response model
cts.res <- smoothArea(tobacco.use ~ 1,
domain = ~region,
design = des0,
adj.mat = DemoMap2$Amat,
pc.u = 1,
pc.alpha = 0.01,
pc.u.phi = 0.5,
pc.alpha.phi = 2/3)
# EXAMPLE 2: Including area level covariates
cts.cov.res <- smoothArea(tobacco.use ~ age,
domain = ~region,
design = des0,
adj.mat = DemoMap2$Amat,
X.domain = Xmat,
pc.u = 1,
pc.alpha = 0.01,
pc.u.phi = 0.5,
pc.alpha.phi = 2/3)
# EXAMPLE 3: Binary response model
bin.res <- smoothArea(tobacco.use ~ 1,
domain = ~region,
design = des0,
adj.mat = DemoMap2$Amat,
transform = "logit",
pc.u = 1,
pc.alpha = 0.01,
pc.u.phi = 0.5,
pc.alpha.phi = 2/3)
# EXAMPLE 4: Including area level covariates in binary response model
bin.cov.res <- smoothArea(tobacco.use ~ age,
domain = ~region,
design = des0,
adj.mat = DemoMap2$Amat,
transform = "logit",
X.domain = Xmat,
pc.u = 1,
pc.alpha = 0.01,
pc.u.phi = 0.5,
pc.alpha.phi = 2/3)
} # }