ebp_reportdescriptives {povmap}

Create Descriptive Statistics for Small Area Estimation Report

Description

This function estimates the coefficient of variation at level specified, basic statistics such number of units, regions and target areas as well as the threshold on which SAE is applied and the outcome indicator of interest (i.e. poverty line and poverty rate). These indicators are all expressed for the census and survey

Usage

ebp_reportdescriptives(
  model,
  direct,
  pop_data,
  pop_domains,
  smp_data,
  threshold = NULL,
  weights = NULL,
  pop_weights = NULL,
  CV_level,
  indicator = "Head_Count"
)

Arguments

model

an object returned by the ebp function of type "emdi ebp", representing point and MSE estimates

direct

an object of type "direct","emdi", representing point and MSE estimates.

pop_data

the population/census/training data

pop_domains

the target area variable within 'pop_data'

smp_data

sample data

threshold

a number defining a threshold. The argument defaults to NULL. In this case, the threshold is set to 60% of the median of the variable that is selected as dependent variable similary to the at-risk-of-poverty rate used in the EU (see also Social Protection Committee 2001). However, any desired threshold can be chosen.

weights

a character string containing the name of a variable that indicates weights in the sample data. If a character string is provided a weighted version of the ebp will be used. The variable has to be numeric. Defaults to NULL.

pop_weights

a character string containing the name of a variable that indicates population weights in the populatation data. If a character string is provided weighted indicators are estimated using population weights. The variable has to be numeric. Defaults to NULL.

CV_level

the variable level at which Coefficient of Variation should be computed

indicator

a character string containing the name of the indicator to compute the Coefficient of Variation for. Defaults to "Head_Count"

Value

an list containing three dataframes (first dataframe with direct an ebp CV values, second dataframe with basic statistics and third dataframe with national poverline and rate for census and survey

Examples

data("eusilcA_pop")
data("eusilcA_smp")

# estimate a unit model
ebp_model <- ebp(fixed = eqIncome ~ gender + eqsize + cash +
                    self_empl + unempl_ben + age_ben + surv_ben + sick_ben +
                    dis_ben + rent + fam_allow + house_allow + cap_inv +
                    tax_adj,
                 pop_data = eusilcA_pop, pop_domains = "district",
                 smp_data = eusilcA_smp, smp_domains = "district",
                 na.rm = TRUE, weights = "weight",
                 pop_weights = "hhsize", MSE = TRUE, weights_type = "nlme",
                 B = 2, L = 2)

# estimate direct
direct_est <- direct(y = "eqIncome", smp_data = eusilcA_smp,
                     smp_domains = "district", weights = "weight",
                     var = TRUE, B = 2)

# descritives
ebp_reportdescriptives(model = ebp_model, direct = direct_est,
                       smp_data = eusilcA_smp, weights = "weight",
                       pop_weights = "hhsize", CV_level = "state",
                       pop_data = eusilcA_pop, pop_domains = "district")