MRTAnalysis 0.3.0

• Added new functionality for mediated causal excursion effects in MRTs:
  • Added mcee() function: streamlined workflow for estimating natural direct excursion effect (NDEE) and natural indirect excursion effect (NIEE) in micro-randomized trials (MRTs) with distal outcomes.
  • Added two advanced wrappers:
  • mcee_general(): flexible configuration of nuisance models (p, q, eta, mu, nu) with support for multiple learners (glm, gam, lm, rf, ranger, sl).
  • mcee_userfit_nuisance(): allows users to inject externally fitted nuisance predictions.
  • Included config helper functions (mcee_config_glm(), mcee_config_gam(), mcee_config_ranger(), etc.) and mcee_config_maker() for building nuisance specifications to pass into mcee_general().
  • New dataset data_time_varying_mediator_distal_outcome included to illustrate usage.
  • Added vignette “Time-Varying Causal Excursion Effect Mediation in MRT: Continuous Distal Outcomes” with detailed examples and best practices.

MRTAnalysis 0.2.0

• Added new functionality for distal outcomes in MRTs:
  • Implemented dcee() for estimating distal causal excursion effects.
  • Supports flexible nuisance regression learners (lm, gam, rf, ranger, SuperLearner) with optional cross-fitting.
  • Provides small-sample t inference via summary.dcee_fit(), consistent with wcls() and emee().
  • New synthetic dataset data_distal_continuous for examples and testing.
  • Added vignette: Exploratory Analysis for MRT: Distal Outcomes.
• Minor bug fixes and improvements to wcls() and emee() documentation.

MRTAnalysis 0.1.2

• Fixed a bug in wcls when the randomization probability is time-varying.
• Now all variable inputs need to be in quotation marks; for example, from now on one should specify id = “userid” instead of id = userid. This is to allow dynamically specified column names.

MRTAnalysis 0.1.1

• Updated vignette to improve clarify.

MRTAnalysis 0.1.0

• Initial release.