# Structure for Organizing Monte Carlo Simulation Designs

## Documentation for package ‘SimDesign’ version 2.8

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

add_missing | Add missing values to a vector given a MCAR, MAR, or MNAR scheme
aggregate_simulations | Collapse separate simulation files into a single result
Analyse | Compute estimates and statistics
AnalyseIf | Perform a test that indicates whether a given 'Analyse()' function should be executed
Attach | Attach objects for easier reference
BF_sim | Example simulation from Brown and Forsythe (1974)
BF_sim_alternative | (Alternative) Example simulation from Brown and Forsythe (1974)
bias | Compute (relative/standardized) bias summary statistic
boot_predict | Compute prediction estimates for the replication size using bootstrap MSE estimates
CC | Compute congruence coefficient
createDesign | Create the simulation Design object
ECR | Compute empirical coverage rates
EDR | Compute the empirical detection rate for Type I errors and Power
Generate | Generate data
IRMSE | Compute the integrated root mean-square error
MAE | Compute the mean absolute error
MSRSE | Compute the relative performance behavior of collections of standard errors
print.Design | Create the simulation Design object
print.SimDesign | Run a Monte Carlo simulation given a data.frame of conditions and simulation functions
quiet | Suppress function messages and Concatenate and Print (cat)
RAB | Compute the relative absolute bias of multiple estimators
rbind.SimDesign | Combine two separate SimDesign objects by row
RD | Compute the relative difference
RE | Compute the relative efficiency of multiple estimators
rejectionSampling | Rejection sampling (i.e., accept-reject method)
reSummarise | Run a summarise step for results that have been saved to the hard drive
rHeadrick | Generate non-normal data with Headrick's (2002) method
rint | Generate integer values within specified range
rinvWishart | Generate data with the inverse Wishart distribution
rmgh | Generate data with the multivariate g-and-h distribution
RMSD | Compute the (normalized) root mean square error
RMSE | Compute the (normalized) root mean square error
rmvnorm | Generate data with the multivariate normal (i.e., Gaussian) distribution
rmvt | Generate data with the multivariate t distribution
RSE | Compute the relative standard error ratio
rtruncate | Generate a random set of values within a truncated range
runSimulation | Run a Monte Carlo simulation given a data.frame of conditions and simulation functions
rValeMaurelli | Generate non-normal data with Vale & Maurelli's (1983) method
Serlin2000 | Empirical detection robustness method suggested by Serlin (2000)
SimAnova | Function for decomposing the simulation into ANOVA-based effect sizes
SimCheck | Check the status of the simulation's temporary results
SimClean | Removes/cleans files and folders that have been saved
SimDesign | Structure for Organizing Monte Carlo Simulation Designs
SimExtract | Function to extract extra information from SimDesign objects
SimFunctions | Template-based generation of the Generate-Analyse-Summarise functions
SimResults | Function to read in saved simulation results
SimShiny | Generate a basic Monte Carlo simulation GUI template
Summarise | Summarise simulated data using various population comparison statistics
summary.SimDesign | Run a Monte Carlo simulation given a data.frame of conditions and simulation functions