Bound Constrained Optimal Sample Size Allocation
Bound Constrained Optimal Design of MRDDs and MRTs
Cluster-level Regression Discontinuity (Two-level Design, Discontinuit...
Cluster-level Regression Discontinuity (Three-level Design, Discontinu...
Cluster-level Regression Discontinuity (Four-level Design, Discontinui...
Computes Regression Discontinuity Design Effects
Simple Individual-level Regression Discontinuity (w/ or w/o Strata or ...
Moments
Blocked (Random) Cluster-level Regression Discontinuity (Three-level D...
Blocked (Random) Cluster-level Regression Discontinuity (Four-level De...
Blocked (Random) Cluster-level Regression Discontinuity (Four-level De...
Blocked (Random) Individual-level Regression Discontinuity (Two-level ...
Blocked (Random) Individual-level Regression Discontinuity (Three-leve...
Blocked (Random) Individual-level Regression Discontinuity (Four-level...
Deprecated and Defunct functions in cosa
Power and MDES Curves
Vectorizes BCOSSA Solutions
Implements bound constrained optimal sample size allocation (BCOSSA) framework described in Bulus & Dong (2021) <doi:10.1080/00220973.2019.1636197> for power analysis of multilevel regression discontinuity designs (MRDDs) and multilevel randomized trials (MRTs) with continuous outcomes. Minimum detectable effect size (MDES) and power computations for MRDDs allow polynomial functional form specification for the score variable (with or without interaction with the treatment indicator). See Bulus (2021) <doi:10.1080/19345747.2021.1947425>.