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  "Description": "Provides functions similar to the 'SAS' macros previously\nprovided to accompany Collins, Dziak, and Li (2009)\n<DOI:10.1037/a0015826> and Dziak, Nahum-Shani, and Collins\n(2012) <DOI:10.1037/a0026972>, papers which outline practical\nbenefits and challenges of factorial and fractional factorial\nexperiments for scientists interested in developing biological\nand/or behavioral interventions, especially in the context of\nthe multiphase optimization strategy (see Collins, Kugler &\nGwadz 2016) <DOI:10.1007/s10461-015-1145-4>.  The package\ncurrently contains three functions. First, RelativeCosts1()\ndraws a graph of the relative cost of complete and reduced\nfactorial designs versus other alternatives. Second,\nRandomAssignmentGenerator() returns a dataframe which contains\na list of random numbers that can be used to conveniently\nassign participants to conditions in an experiment with many\nconditions. Third, FactorialPowerPlan() estimates the power,\ndetectable effect size, or required sample size of a factorial\nor fractional factorial experiment, for main effects or\ninteractions, given several possible choices of effect size\nmetric, and allowing pretests and clustering.",
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