empirical.power.calc | Calculates empirical power |
env.params | Parameters to simulate environmental exposures data |
ESPRESSO | Package for power analysis and sample size calculation |
gen.params | Parameters to simulate genetic data |
general.params | Main parameters of the simulations |
get.critical.results | Summarizes the main results |
get.observed.data | Generates exposure data with with some error |
init.data | Simulated genotypes, phenotypes and enviromental exposure data |
is.posdef | Tells if a matrix is positive definite |
make.cov.mat | Generates the covariance matrix required to achieved the desired LD |
make.obs.env | Adds some error to environmental exposure data |
make.obs.geno | Adds some error to genotype data |
make.posdef | Turns a matrix into a positive definite one |
misclassify | Adds some misclassification error to binary data |
model.power.calc | Calculates theoretical power |
obs.data | Simulated genotypes, phenotypes and enviromental exposure data |
regr.analysis | carries out regression analysis |
samplsize.calc | Calculates the sample size required to achieved the desired power |
sim.CC.data | Simulates cases and controls |
sim.env.data | Simulates data for an environmental exposure |
sim.env.sesp | Simulates sensitivity and specificity for environmental exposure assessment |
sim.geno.data | Simulates genotypes for a genetic variant |
sim.geno.sesp | Simulates sensitivity and specificity for genotype assessment |
sim.interact.data | Generates data for the interaction term |
sim.LDgeno.data | Simulates genotypes for two genetic variants in LD |
sim.LDsnps | Simulates alleles for two biallelic SNPs in Linkage Disequilibrium |
sim.pheno.bin | Simulates binary outcome data |
sim.pheno.qtl | Simulates continuous outcome data |
sim.QTL.data | Simulates subjects for a continuous outcome |
sim.sesp.params | Table of paramaters to simulate sensitivity and specificity values |
sim.subject.data | Simulates the individual effect related to heterogeneity in disease risk |
skew.rnorm | Allows to generate right or left-skewed normal distribution |