Simulation functions

rnorm_multi()

Multiple correlated normal distributions

rnorm_pre()

Make a normal vector correlated to existing vectors

sim_design()

Simulate data from design

sim_df()

Simulate an existing dataframe

sim_joint_dist()

Simulate category joint distribution

Mixed effects functions

add_random()

Add random factors to a data structure

add_within()

Add within factors

add_between()

Add between factors

add_recode()

Recode a categorical column

add_ranef()

Add random effects to a data frame

sim_mixed_cc()

Generate a cross-classified sample

sim_mixed_df()

Generate a mixed design from existing data

Contrasts

add_contrast()

Add a contrast to a data frame

contr_code_treatment()

Treatment code a factor

contr_code_anova()

Anova code a factor

contr_code_sum()

Sum code a factor

contr_code_difference()

Difference code a factor

contr_code_helmert()

Helmert code a factor

contr_code_poly()

Polynomial code a factor

Other useful functions

codebook()

Create PsychDS Codebook from Data

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

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()

Get design

get_design_long()

Get design from long data

getcols()

Get data columns

interactive_design()

Set design interactively

is_pos_def()

Check a Matrix is Positive Definite

nested_list()

Output a nested list in RMarkdown list format

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

set_design()

Set design

unique_pairs()

Make unique pairs of level names for correlations

Distribution functions

std_alpha2average_r()

Standardized Alpha to Average R

norm2likert()

Convert normal to likert

norm2beta()

Convert normal to beta

norm2binom()

Convert normal to binomial

norm2gamma()

Convert normal to gamma

norm2pois()

Convert normal to poisson

norm2trunc()

Convert normal to truncated normal

trunc2norm()

Convert truncated normal to normal

norm2unif()

Convert normal to uniform

beta2norm()

Convert beta to normal

binom2norm()

Convert binomial to normal

gamma2norm()

Convert gamma to normal

unif2norm()

Convert uniform to normal