fit_LOCF_longitudinal: Find the last observation carried forward (LOCF) values for...

In isobelbarrott/Landmarking: Analysis using Landmark Models

Find the last observation carried forward (LOCF) values for covariates in a dataset

Description

This function is a helper function for fit_LOCF_landmark.

Usage

fit_LOCF_longitudinal(
  data_long,
  x_L,
  covariates,
  covariates_time,
  cv_name = NA,
  individual_id
)

Arguments

data_long	Data frame in long format i.e. there may be more than one row per individual
x_L	Numeric specifying the landmark time(s)
covariates	Vector of character strings specifying the column names in data_long which correspond to the covariates
covariates_time	Vector of character strings specifying the column names in data_long which contain the times at which covariates were recorded. This should either be length 1 or the same length as covariates. In the latter case the order of elements must correspond to the order of elements in covariates.
cv_name	Character string specifying the column name in data_long that indicates cross-validation fold
individual_id	Character string specifying the column name in data_long which contains the individual identifiers

Details

This function extracts the LOCF value for each of the covariates in data_long up to (and including) time x_L.

Value

List containing data_longitudinal, model_longitudinal, and call.

data_longitudinal has one row for each individual in data_long and contains the LOCF value of covariates at the landmark time x_L.

model_longitudinal indicates that the LOCF approach is used.

call contains the call of the function.

Author(s)

Isobel Barrott [e-mail]

isobelbarrott/Landmarking documentation built on Nov. 22, 2022, 4:50 a.m.