.mcee_resolve_rand_prob

Resolve randomization probability from column name or scalar

Provides methods to analyze micro-randomized trials (MRTs) with binary treatment options. Supports four types of analyses: (1) proximal causal excursion effects, including weighted and centered least squares (WCLS) for continuous proximal outcomes by Boruvka et al. (2018) <doi:10.1080/01621459.2017.1305274> and the estimator for marginal excursion effect (EMEE) for binary proximal outcomes by Qian et al. (2021) <doi:10.1093/biomet/asaa070>; (2) distal causal excursion effects (DCEE) for continuous distal outcomes using a two-stage estimator by Qian (2025) <doi:10.1093/biomtc/ujaf134>; (3) mediated causal excursion effects (MCEE) for continuous distal outcomes, estimating natural direct and indirect excursion effects in the presence of time-varying mediators by Qian (2025) <doi:10.48550/arXiv.2506.20027>; and (4) standardized proximal effect size estimation for continuous proximal outcomes, generalizing the approach in Luers et al. (2019) <doi:10.1007/s11121-017-0862-5> to allow adjustment for baseline and time-varying covariates for improved efficiency.

Tianchen Qian

MRTAnalysis

Assessing Proximal, Distal, and Mediated Causal Excursion
Effects for Micro-Randomized Trials

Shaolin Xiang

Zhaoxi Cheng

Xinyi Song

John Dziak

Audrey Boruvka

.mcee_resolve_rand_prob function

<dl><dt>data</dt>
<dd>Data frame</dd>
<dt>rand_prob</dt>
<dd>Either column name or numeric scalar</dd>
<dt>availability</dt>
<dd>Optional availability column name for validation</dd></dl>

Arguments

Resolve randomization probability from column name or scalar — .mcee_resolve_rand_prob

<dl>

<dt>data</dt>
<dd>Data frame</dd>


<dt>rand_prob</dt>
<dd>Either column name or numeric scalar</dd>


<dt>availability</dt>
<dd>Optional availability column name for validation</dd>

</dl>

.mcee_resolve_rand_prob: Resolve randomization probability from column name or scalar

Description

Usage

Value

Arguments