Efficient Simulation of HDX-MS Data and Tools for the
Statistical Analysis
c(person(given = "Krystyna",
family = "Grzesiak",
email = "krygrz11@gmail.com",
role = c("cre", "aut")),
person(given = "Mateusz",
family = "Staniak",
email = "mtst@mstaniak.pl",
role = c("aut")),
person(given = "Michal",
family = "Burdukiewicz",
email = "michalburdukiewicz@gmail.com",
comment = c(ORCID = "0000-0001-8926-582X"),
role = c("ctb")))
Facilitates simulating and analyzing data coming from HDX-MS
experiments along with the possibility of comparing the power of
the tests verifying differences in the levels of deuterium uptake.
The simulation of mass spectra is a fast version of
<https://github.com/kanzy/HX-MS-Simulations>.
checkmate, data.table, expm, ggplot2, glmnet, lme4, lmerTest,
methods, nlme, plyr, Rcpp (>= 1.0.3), signal,
testthat, spelling, knitr, rmarkdown, covr
Krystyna Grzesiak [cre, aut],
Mateusz Staniak [aut],
Michal Burdukiewicz [ctb] (<https://orcid.org/0000-0001-8926-582X>)

c(
person("Kirk", "Bansak", , "kbansak@ucsd.edu", c("aut")),
person("Eddie", "Yang", , "z5yang@ucsd.edu", c("aut", "cre"))
)
An implementation of the generalized power analysis for the local average treatment effect (LATE), proposed by Bansak (2020) <doi:10.1214/19-STS732>. Power analysis is in the context of estimating the LATE (also known as the complier average causal effect, or CACE), with calculations based on a test of the null hypothesis that the LATE equals 0 with a two-sided alternative. The method uses standardized effect sizes to place a conservative bound on the power under minimal assumptions. Package allows users to recover power, sample size requirements, or minimum detectable effect sizes. Package also allows users to work with absolute effects rather than effect sizes, to specify an additional assumption to narrow the bounds, and to incorporate covariate adjustment.
Kirk Bansak [aut],
Eddie Yang [aut, cre]

Power/Sample size calculation for mediation analysis
The package contains functions for calculating power,
sample size, and minimal detectable mediation effect for
testing mediation effect (Sobel's test) of a simple mediation
model with continuous response, and only one predictor and only
one mediator. The package also contains functions for
calculating power, sample size, and minimal detectable slope
for testing the slope in a simple linear regression (only one
predictor).