Reference

Simulation functions
sim_design()	Simulate data from design
sim_df()	Simulate an existing dataframe
sim_mixed_cc()	Generate a cross-classified sample
sim_mixed_df()	Generate a mixed design from existing data
Other useful functions
faux2ANOVA_design()	Convert faux design to ANOVApower design
get_params() check_sim_stats()	Get parameters from a data table
json_design()	Convert design to JSON
make_id()	Make ID
messy()	Simulate missing data
rnorm_multi()	Make normally distributed vectors with specified relationships
rnorm_pre()	Make a normal vector correlated to an existing vector
long2wide()	Convert data from long to wide format
wide2long()	Convert data from wide to long format
faux_options()	Set/get global faux options
Datasets
faceratings	Attractiveness ratings of faces
fr4	Attractiveness rating subset
Helper functions
check_design()	Validates the specified design
check_mixed_design()	Get random intercepts for subjects and items
cormat()	Make a correlation matrix
cormat_from_triangle()	Make Correlation Matrix from Triangle
fix_name_labels()	Fix name labels
get_design_long()	Get design from long data
interactive_design()	Set design interactively
is_pos_def()	Check a Matrix is Positive Definite
plot_design() plot(<design>) plot(<faux>)	Plot design
pos_def_limits()	Limits on Missing Value for Positive Definite Matrix
readline_check()	Check readline input
sample_from_pop()	Sample Parameters from Population Parameters
select_num_grp()	Select grouping and numeric columns and group
sim_data()	Simulate data from design (internal)
unique_pairs()	Make unique pairs of level names for correlations
Distribution functions
norm2likert()	Convert normal to likert
norm2binom()	Convert normal to binomial
norm2pois()	Convert normal to poisson
norm2unif()	Convert normal to uniform
unif2norm()	Convert normal to uniform
norm2trunc()	Convert normal to truncated normal
trunc2norm()	Convert truncated normal to normal