attrition_experiment: Simulated experiment encountering attrition

In vayr: Extensions for 'ggplot2' to Visualize as You Randomize

Simulated experiment encountering attrition

Description

Nineteen of the 200 subjects have a missing outcome, and missingness is related to the potential outcomes, so dropping those subjects conditions the analysis on a post-treatment variable. Use with impute_extreme_values(), which imputes the best and worst cases the observed data admit. The outcome is a seven-point Likert item, so its logical range is 1 to 7 even though no subject in this sample answered 1.

Usage

attrition_experiment

Format

attrition_experiment

A tibble with 200 rows and 10 columns:

ID

Subject identifier

U

Unobserved subject-level shock

Y_Z_0, Y_Z_1

Likert potential outcomes under control and treatment

R_Z_0, R_Z_1

Potential response indicators, 1 if the subject would report an outcome

Z

Random assignment, 1 for treatment and 0 for control

Z_cond_prob

Probability of the assigned condition, 0.5 throughout

R

Revealed response indicator, 1 when Y is observed

Y

Revealed outcome, NA for the 19 subjects who did not report

Source

\Sexpr[results=rd]{tools:::Rd_expr_doi("10.7910/DVN/VE6VSR")}

See Also

Other Data: blocked_experiment, clustered_experiment, continuous_interaction, covariate_adjustment, noncompliance_experiment, patriot_act, two_arm_trial

vayr documentation built on Aug. 22, 2026, 1:08 a.m.