Optimal Two and Three Stage Designs for Single-Arm and Two-Arm
Randomized Controlled Trials with a Long-Term Binary Endpoint
Bo Huang <bo.huang@pfizer.com> and Neal Thomas
<neal.thomas@pfizer.com>
Optimal two and three stage designs monitoring
time-to-event endpoints at a specified timepoint
mvtnorm, clinfun, stats, graphics, R (>= 2.14.1)

Estimating the Optimal Number of Migration Edges from 'Treemix'
person("Robert", "Fitak", email = "rfitak9@gmail.com", role = c("aut", "cre"))
The popular population genetic software 'Treemix' by
'Pickrell and Pritchard' (2002) <DOI:10.1371/journal.pgen.1002967>
estimates the number of migration edges on a population tree.
However, it can be difficult to determine the number of migration
edges to include. Previously, it was customary to stop adding migration
edges when 99.8% of variation in the data was explained, but 'OptM'
automates this process using an ad hoc statistic based on the
second-order rate of change in the log likelihood.  'OptM' also
has added functionality for various threshold modeling
to compare with the ad hoc statistic.

The popular population genetic software 'Treemix' by
'Pickrell and Pritchard' (2012) <DOI:10.1371/journal.pgen.1002967>
estimates the number of migration edges on a population tree.
However, it can be difficult to determine the number of migration
edges to include. Previously, it was customary to stop adding migration
edges when 99.8% of variation in the data was explained, but 'OptM'
automates this process using an ad hoc statistic based on the
second-order rate of change in the log likelihood.  'OptM' also
has added functionality for various threshold modeling
to compare with the ad hoc statistic.
SiZer (>= 0.1-4), stats, splines, grDevices, boot (>= 1.3-20)

Optimal Level of Significance for Regression and Other
Statistical Tests
Calculates the optimal level of significance based on a decision-theoretic approach.
The optimal level is chosen so that the expected loss from hypothesis testing is minimized.
A range of statistical tests are covered, including the test for the population mean, population proportion, and a linear restriction in a multiple regression model.
The details are covered in Kim, Jae H. and Choi, In, Choosing the Level of Significance: A Decision-Theoretic Approach (December 18, 2017), available at SSRN: <https://ssrn.com/abstract=2652773> or <doi:10.2139/ssrn.2652773>.
See also Kim and Ji (2015) <doi:10.1016/j.jempfin.2015.08.006>.