smoothArea {SUMMER} | R Documentation |
Small area estimation via basic area level model
Description
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 |
Value
A svysae object
Examples
## Not run:
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)
## End(Not run)