create_lagged_cov: Create lagged choice covariates

In RprobitB: Bayesian Probit Choice Modeling

Create lagged choice covariates

Description

This function creates lagged choice covariates from the data.frame choice_data, which is assumed to be sorted by the choice occasions.

Usage

create_lagged_cov(choice_data, column = character(), k = 1, id = "id")

Arguments

choice_data	[data.frame] Choice data in wide format, where each row represents one choice occasion.
column	[character()] Covariate names in choice_data.
k	[integer()] The number of lags (in units of observations), see the details.
id	[character(1)] The name of the column in choice_data that contains unique identifier for each decision maker.

Details

Say that choice_data contains the column column. Then, the function call

create_lagged_cov(choice_data, column, k, id)

returns the input choice_data which includes a new column named column.k. This column contains for each decider (based on id) and each choice occasion the covariate faced before k choice occasions. If this data point is not available, it is set to NA. In particular, the first k values of column.k will be NA (initial condition problem).

Value

The input choice_data with the additional columns named column.k for each element column and each number k containing the lagged covariates.

Examples

choice_data <- data.frame(id = rep(1:2, each = 3), cov = LETTERS[1:6])
create_lagged_cov(choice_data, column = "cov", k = 1:2)

RprobitB documentation built on Aug. 26, 2025, 1:08 a.m.