Power Analysis via Monte Carlo Simulation for Correlated Data

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Documentation for package ‘mpower’ version 0.1.0

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bkmr_wrapper Fits a BKMR model with significance criteria: PIP and group-wise PIP
bma_wrapper Fits a linear model with Bayesian model selection with significance criteria: PIP and posterior probability of nonzero coefficients being on one side of zero.
bws_wrapper Fits a Bayesian weighted sums
cor2partial Convert a correlation matrix into a partial correlation matrix
cvine Citation: Daniel Lewandowski, Dorota Kurowicka, Harry Joe, Generating random correlation matrices based on vines and extended onion method, Journal of Multivariate Analysis, Volume 100, Issue 9, 2009, Pages 1989-2001, ISSN 0047-259X, https://doi.org/10.1016/j.jmva.2009.04.008.
estimate_snr Monte Carlo approximation of the SNR
fin_wrapper Fits a Bayesian factor model with interactions
fit Fits the model to given data and gets a list of significance criteria
genx Generates a matrix of n observations of p predictors
geny Generates a vector of outcomes
glm_wrapper Fits a generalized linear model
InferenceModel Statistical model that returns significance criterion
MixtureModel Correlated predictors generator
mplot Visualize marginals and Gaussian copula correlations of simulated data
mpower mpower: Power analysis using Monte Carlo for correlated predictors.
nhanes1518 NHANES data from 2015-2016 and 2017-2018 cycles
OutcomeModel Outcome generator
partial Partial correlations between elements in x and elements in y
plot_summary Plot summaries of power simulation
qgcomp_lin_wrapper Fits a linear Quantile G-Computation model with no interactions
qmultinom Quantile function for the multinomial distribution, size = 1
rsq2snr Convert R-squared value to the SNR
scale_f Rescale the mean function of an OutcomeModel to meet a given SNR
scale_sigma Rescale the noise variance of a Gaussian OutcomeModel to meet a given SNR
set_value This function updates values in an OutcomeModel object
sim_curve Power curve using Monte Carlo simulation
sim_power Power analysis using Monte Carlo simulation
summary Tabular summaries of power simulation