Packaged: 2020-10-13 13:29:52 UTC; federico.giorgi4

Packaged: 2020-10-23 11:37:38 UTC; federico.giorgi4

Packaged: 2021-03-05 16:26:34 UTC; federico.giorgi4

Packaged: 2021-05-24 16:01:42 UTC; federico.giorgi4

Packaged: 2021-09-29 15:16:13 UTC; federico.giorgi4

Title: Create and Format Correlation Matrices
Description: Create correlation (or partial correlation) matrices. Correlation matrices are formatted with significance stars based on user preferences. Matrices of coefficients, p-values, and number of pairwise observations are returned. Send resultant formatted matrices to the clipboard to be pasted into excel and other programs. A plot method allows users to visualize correlation matrices created with 'corx'.
Imports: ppcor, crayon, ggcorrplot, glue, psych, clipr, tidyselect,
Author: James Conigrave [aut, cre] (<https://orcid.org/0000-0002-8816-6229>)

moments, ggpubr, ggplot2, magrittr, stats

Imports: crayon, ggcorrplot, glue, clipr, tidyselect, moments, ggpubr,

Title: Constrained Optimal Sample Allocation
Authors@R: person("Metin", family = "Bulus", role = c("aut", "cre", "cph"), email = "bulusmetin@gmail.com")
Implements generalized constrained optimal sample allocation framework for multilevel regression discontinuity studies and multilevel randomized trials with continuous outcomes. Bulus, M. (2017). Design Considerations in Three-level Regression Discontinuity Studies (Doctoral dissertation). University of Missouri, Columbia, MO.

Implements generalized constrained optimal sample allocation framework for two-group multilevel regression discontinuity studies and multilevel randomized trials with continuous outcomes. Bulus, M. (2017). Design Considerations in Three-level Regression Discontinuity Studies (Doctoral dissertation). University of Missouri, Columbia, MO.

Authors@R: c(person("Metin", family = "Bulus", role = c("aut", "cre", "cph"), email = "bulusmetin@gmail.com"))

Title: Bound Constrained Optimal Sample Allocation
Authors@R: c(person("Metin", family = "Bulus", role = c("aut", "cre", "cph"), email = "bulusmetin@gmail.com"), person("Nianbo", family = "Dong", role = c("aut", "cph")))
Implements bound constrained optimization of sample sizes in power analysis of multilevel regression discontinuity studies (RDDs) and multilevel randomized controlled trials (RCTs) with continuous outcomes. Functions for statistical power and minimum detectable effect size calculations are also provided. Bulus, M. (2017). Design Considerations in Three-level Regression Discontinuity Studies (Doctoral dissertation). University of Missouri, Columbia, MO.