getPredictors: Populate predictors based on data mapping

In saharaja/imputeORS: Impute Missing Values in the BLS Occupational Requirements Survey

Description

This function assigns values to each observation for each of the predictors that will be used in the downstream analysis phase. This value assignment relies on an internal mapping, and results in the addition of a handful of columns to the data.

Usage

getPredictors(orsMnGCe)

Arguments

orsMnGCe

Data with errors and bounds (output of errorsAndBounding())

Details

The additions to the data are described below:

(1) The data_element_text field is restructured into a new field, Requirement, and added to the data.

(2) The data_element_text and data_type_text fields have somewhat overlapping roles in the original data. Moreover their structure makes for a large increase in the dimensions of the data. We devised a way to map these two fields to numeric fields (Frequency and Intensity), leading to a significant reduction in dimension. This mapping is applied here, and the new fields are added to the data.

(3) Also added to the data are fields for SOC2, SOC3, and SOC4 codes, as well as a field for the relevant Requirement Category.

(4) An indicator column that differentiates between known estimates missing estimates is added.

Value

Data augmented with relevant predictors

See Also

errorsAndBounding()

predictors.data for data mapping

saharaja/imputeORS documentation built on Feb. 4, 2022, 12:27 a.m.