Transform a row-dependent variable to a row-independent variable using first occurrence

Creates a row-independent (ri_) variable by finding the first occurrence where a condition is TRUE and extracting the corresponding value. This is a common pattern in longitudinal registry data analysis for creating stable person-level characteristics from time-varying skeleton columns.

Usage

make_rowind_first_occurrence(dt, condition, value_var, new_var)

Arguments

dt

A data.table with longitudinal data

condition

Character string representing the logical condition to evaluate

value_var

Character string naming the column to extract values from

new_var

Character string naming the new ri_* variable to create

Value

The data.table is modified by reference (invisibly returned)

Details

swereg distinguishes two variable shapes in longitudinal skeleton data:

row-dependent (prefix rd_)

Values that can change over time for a person. Examples: rd_age_continuous, rd_education, rd_income_inflation_adjusted.

row-independent (prefix ri_)

Values that are fixed person-level. Examples: ri_birthcountry, ri_age_first_diagnosis, ri_isoyear_first_diagnosis, ri_register_tag.

This function automates the common rd_ -> ri_ transformation of capturing "the value at the first time something became true". The transformation follows these steps:

1. Create a temporary column where condition is TRUE

2. Use first_non_na() to find the first occurrence for each person

3. Clean up the temporary column automatically

Equivalent to the manual pattern: dt[condition, temp := value_var] dt[, new_var := first_non_na(temp), by = .(id)] dt[, temp := NULL]

See also

first_non_na for the aggregation function used internally

Examples

if (FALSE) { # \dontrun{
# Create example skeleton with diagnosis data
skeleton <- create_skeleton(c(1,2,3), 2020, "2020-53")

# Add some example diagnosis data
add_diagnoses(skeleton, diagnosis_data, "lopnr",
              codes = list("example_diag" = "^F64"))

# Transform: age at first example diagnosis
make_rowind_first_occurrence(skeleton,
                             condition = "example_diag == TRUE",
                             value_var = "age",
                             new_var = "ri_age_first_example_diag")
} # }