clusterModel_u5mr: Calculate cluster model estimates using beta binomial model...

In surveyPrev: Mapping the Prevalence of Binary Indicators using Survey Data in Small Areas

Calculate cluster model estimates using beta binomial model for U5MR

Description

This function calculate smoothed direct estimates at given admin level.

Usage

clusterModel_u5mr(
  data,
  cluster.info,
  admin.info,
  X = NULL,
  X.unit = NULL,
  X.pixel = NULL,
  admin,
  CI = 0.95,
  model = c("bym2", "iid"),
  stratification = FALSE,
  aggregation = FALSE,
  nested = FALSE,
  interact = FALSE,
  overdisp.mean = 0,
  overdisp.prec = 0.4,
  pc.u = 1,
  pc.alpha = 0.01,
  pc.u.phi = 0.5,
  pc.alpha.phi = 2/3,
  age.space.group = c(1, 2, 2, 2, 3, 3, 3, 3)
)

Arguments

data	dataframe that contains the indicator of interests(column name is value), output of getDHSindicator function
cluster.info	dataframe that contains admin 1 and admin 2 information and coordinates for each cluster.
admin.info	dataframe that contains population and urban/rural proportion at specific admin level
X	dataframe that contains areal covariates, the first column should be the same admin name as in admin.info$data.
X.unit	dataframe that contains unit covariates, must contain cluster
X.pixel	dataframe that contains pixel covariates, must contain 1. admin1.name or admin2.name.full, 2. Population, 3. strata if stratification==T
admin	admin level for the model
CI	Credible interval to be used. Default to 0.95.
model	smoothing model used in the random effect. Options are independent ("iid") or spatial ("bym2").
stratification	whether or not to include urban/rural stratum.
aggregation	whether or not report aggregation results.
nested	whether or not to fit a nested model.
interact	whether or not to fit a admin1 x urban/rural model.
overdisp.mean	prior mean for logit(d), where d is the intracluster correlation.
overdisp.prec	prior precision for logit(d), where d is the intracluster correlation.
pc.u	pc prior u for iid or bym2 precision.
pc.alpha	pc prior alpha for iid or bym2 precision.
pc.u.phi	pc prior u for bym2 mixing paramete.
pc.alpha.phi	pc prior u for bym2 mixing paramete.
age.space.group	vector indicating grouping of the ages groups in the spatial model. For example, if each age group is assigned a different spatial component, then set age.group.group to c(1:length(age.group)); if all age groups share the same spatial component, then set age.group.group to a rep(1, length(age.group)). The default for 8 age groups is c(1,2,2,2,3,3,3,3), which assigns a separate hazards to the first two groups and a common hazard for the rest of the age groups. The vector should contain values starting from 1.

Value

This function returns the dataset that contain district name and population for given tiff files and polygons of admin level,

surveyPrev documentation built on June 19, 2026, 5:06 p.m.