| data_binary {MRTAnalysis} | R Documentation |
A synthetic data set of an MRT with binary outcome
Description
A synthetic data set of an MRT with binary outcome
Usage
data_binary
Format
a data frame with 3000 observations and 10 variables
This random sample uses the baseline model: log E(Y_t+1 | A_t = 0, I_t = 1) = alpha_0 + alpha_1 * time / total_T + alpha_2 * 1(time > total_T/2), the treatment effect model: log relative risk = beta_0 + beta_1 * time / total_T, the probability of treatment assignment p_t: 0.3, 0.5, 0.7 with repetition, and exogenous probability of availability: 0.8 at all time points.
- userid
individual id number
- time
decision point index
- time_var1
time-varying covariate 1, the "standardized time in study", defined as the current decision point index divided by the total number of decision points
- time_var2
time-varying covariate 2, indicator of "the second half of the study", defined as whether the current decision point index is greater than the total number of decision points divided by 2.
- Y
binary proximal outcome
- A
treatment assignment, i.e., whether the intervention is randomized to be delivered (=1) or not (=0) at the current decision point
- rand_prob
the randomization probability P(A=1) for the current decision point
- avail
whether the individual is available (=1) or not (=0) at the current decision point