defineMONITORvars: Helper routine to define the monitoring indicator and time...

In osofr/stremr: Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data

Description

Helper routine to define the monitoring indicator and time since last visit

Usage

defineMONITORvars(
  data,
  ID,
  t,
  imp.I,
  MONITOR.name = "N",
  tsinceNis1 = "last.Nt"
)

Arguments

data	Input data.table or data.frame
ID	The name of the unique subject identifier (character, numeric or factor).
t	The name of the time/period variable in data.
imp.I	The name of the binary indicator of missingness or imputation for I at time point t. This is used for coding MONITOR(t-1):=1-imp.I(t). When imp.I(t)=1 it means that the patient was not observed (no office visit) at time-point t and hence no biomarker was measured.
MONITOR.name	The name of the new column that represents for each row t the indicator of being MONITORed (having a visit) at time points t+1. This variable is added as a new column to the output dataset. The column MONITOR(t) is set to 1 when the indicator imp.I (imputed biomarker) is 0 at time-point t+1 and vice versa.
tsinceNis1	The name of the future column (created by this routine) that counts number of periods since last monitoring event at t-1. More precisely, it is a function of the past N(t-1), where 0 means that N(t-1)=1; 1 means that N(t-2)=1 and N(t-1)=0; etc.
I	The name of the numeric biomarker value which determines the dynamic treatment rule at each time point t.

Value

A data.table in long format with ordering (I, CENS, TRT, MONITOR)

Details

Convert the input long format data with the time ordering: (I(t), imp.I(t), C(t), A(t)) into the data format required by the stremr input functions: (I(t), C(t), A(t), N(t):=1-imp.I(t+1)). N(t) at time-point t is defined as the indicator of being observed (having an office visit) at time point t+1 (next timepoint after t) The very first value of I(t) (at the first time-cycle) is ALWAYS ASSUMED observed/measured (hence I.imp=0 for each first subject-time observation).

Data Format

The input data.frame data needs to be in long format.

The format of the specified columns needs to be as follows.

The time ordering of the input data at each t is as follows: (I, imp.I, CENS, TRT)

The time ordering of the output data at each t is as follows: (I, CENS, TRT, MONITOR), where MONITOR(t)=1-imp.I(t+1).

In output data.table, MONITOR(t-1)=1 indicates that the biomarker I(t) at t is observed and vice versa.

In addition the output data.table will contain a column 'tsinceNis1', where:

• tsinceNis1(t) = 0 means that the person was monitored at time-point t-1.

• tsinceNis1(t) > 0 is the count of the number of cycles since last monitoring event.

osofr/stremr documentation built on Jan. 25, 2022, 8:07 a.m.