smoothing function

Variance Smoothing and Effective Sample Sizes Estimation

The smoothing() function implements three methods, all yielding refined estimates of either variance or effective sample size, to account for indicators with different variance functions. The output estimates are ready to be used as known parameters in an area-level model, and they need to be added to the analysed data.frame object. All the implemented methods enable the estimation of the effective sample sizes, whereas "ols" and "gls" also perform a variance smoothing procedure.

smoothing(
  data,
  direct_estimates,
  area_id = NULL,
  raw_variance = NULL,
  areas_sample_sizes = NULL,
  additional_covariates = NULL,
  method = c("ols", "gls", "kish"),
  var_function = NULL,
  survey_data = NULL,
  survey_area_id = NULL,
  weights = NULL,
  sizes = NULL
)

Arguments

• data: A data.frame object including the direct estimates.
• direct_estimates: Character string specifying the variable in data denoting the direct estimates.
• area_id: Character string indicating the variable with domain names included in data, to be specified if method "kish" is selected.
• raw_variance: Character string indicating the variable name for raw variance estimates included in data object, to be specified if methods "ols" or "gls" are selected.
• areas_sample_sizes: Character string indicating the variable name for domain sample sizes included in data object, to be specified if methods "ols" or "gls" are selected.
• additional_covariates: A vector of character strings indicating the variable names of possible additional covariates, included in data, to be added to the smoothing procedure if methods "ols" or "gls" are selected.
• method: The method to be used. The choices are "kish","ols" and "gls".
• var_function: An object of class function denoting the variance function of the response variable. The default option (NULL) matches the proportion case being equal to function(x) x * (1 - x). If an alternative function is specified, only variance estimates are provided.
• survey_data: An additional dataset to be specified when method "kish" is selected, defined at sampling unit level (e.g., households) and comprising sampling weights, unit sizes and domain names.
• survey_area_id: Character string indicating the variable denoting the domain names included in the survey_data object.
• weights: Character string indicating the variable including sampling weights in survey_data object.
• sizes: Character string indicating the variable including unit sizes in survey_data object.

Returns

An object of class smoothing_fitsae, being a list of vectors including dispersion estimates: the variances and, when no alternative variance functions are specified, the effective sample sizes. When "ols" or "gls" method has been selected, the list incorporates also an object of class gls from nlme package.

Examples

library(tipsae)

# loading toy dataset
data("emilia_cs")

# perform smoothing procedure
smoo <- smoothing(emilia_cs, direct_estimates = "hcr", area_id = "id",
                  raw_variance = "vars", areas_sample_sizes = "n",
                  var_function = NULL, method = "ols")

References

\insertRef kish1992weightingtipsae

\insertRef fabrizi2011hierarchicaltipsae

\insertRef JSStipsae

See Also

gls for details on estimation procedure for "ols" and "gls" methods.