Package: MOST
Type: Package
Title: Multiphase Optimization Strategy
Version: 0.1.2
Authors@R: c(
person("Linda","Collins", email = "lmc9580@nyu.edu", role = "aut"),
person("Liying","Huang", email = "lxh37@PSU.EDU", role = "aut"),
person("John","Dziak", email = "dziakj1@gmail.com", role = c("aut","cre")))
Depends: R (>= 2.15.0)
Encoding: UTF-8
Copyright: 2022 by The Pennsylvania State University
Description: Provides functions similar to the 'SAS' macros previously provided
to accompany Collins, Dziak, and Li (2009) <DOI:10.1037/a0015826>
and Dziak, Nahum-Shani, and Collins (2012) <DOI:10.1037/a0026972>, papers
which outline practical benefits and challenges of factorial
and fractional factorial experiments for scientists interested
in developing biological and/or behavioral interventions, especially
in the context of the multiphase optimization strategy
(see Collins, Kugler & Gwadz 2016) <DOI:10.1007/s10461-015-1145-4>.  The package
currently contains three functions. First, RelativeCosts1() draws a graph
of the relative cost of complete and reduced factorial designs versus
other alternatives. Second, RandomAssignmentGenerator() returns a dataframe
which contains a list of random numbers that can be used to conveniently
assign participants to conditions in an experiment with
many conditions. Third, FactorialPowerPlan() estimates the power, detectable effect
size, or required sample size of a factorial or fractional factorial
experiment, for main effects or interactions, given several possible choices
of effect size metric, and allowing pretests and clustering.
License: GPL (>= 2)
NeedsCompilation: no
RoxygenNote: 7.2.0
Packaged: 2022-06-22 22:09:39 UTC; John
Author: Linda Collins [aut],
Liying Huang [aut],
John Dziak [aut, cre]
Maintainer: John Dziak <dziakj1@gmail.com>
Repository: CRAN
Date/Publication: 2022-06-23 22:20:08 UTC

Title: Effect Size and Confidence Interval Calculator
Authors@R: c(person("Erin M.", "Buchanan", role = c("aut", "cre"),
person("Amber M", "Gillenwaters", role = "aut",
person("John E.", "Scofield", role = "aut",
person("K. D.", "Valentine", role = "aut",
Description: Measure of the Effect ('MOTE') is an effect size calculator, including a
wide variety of effect sizes in the mean differences family (all versions of d) and
the variance overlap family (eta, omega, epsilon, r). 'MOTE' provides non-central
confidence intervals for each effect size, relevant test statistics, and output
for reporting in APA Style (American Psychological Association, 2010,
<ISBN:1433805618>) with 'LaTeX'. In research, an over-reliance on p-values
may conceal the fact that a study is under-powered (Halsey, Curran-Everett,
Vowler, & Drummond, 2015 <doi:10.1038/nmeth.3288>). A test may be statistically
significant, yet practically inconsequential (Fritz, Scherndl, & Kühberger, 2012
<doi:10.1177/0959354312436870>). Although the American Psychological Association
has long advocated for the inclusion of effect sizes (Wilkinson & American
Psychological Association Task Force on Statistical Inference, 1999
<doi:10.1037/0003-066X.54.8.594>), the vast majority of peer-reviewed,
published academic studies stop short of reporting effect sizes and confidence
the use and interpretation of effect sizes and confidence intervals. For more
Author: Erin M. Buchanan [aut, cre] (<https://orcid.org/0000-0002-9689-4189>),
Amber M Gillenwaters [aut] (<https://orcid.org/0000-0002-7580-3591>),
Maintainer: Erin M. Buchanan <buchananlab@gmail.com>