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add_between() and add_within() don’t
convert non-character levels to factors any more * submitting to CRAN
(sorry for letting it get archived!)rmulti() function for multivariate distributions that
aren’t all normal (experimental)add_random()long argument for sim_df()rmulti() and associated helper
functions convert_r() and fh_bounds().rmulti() function for multivariate distributions that
aren’t all normal (experimental)rlikert(),
dlikert(), plikert() and
qlikert()add_random() now names random factor items with the
full random factor name (e.g., “class1”, not “c1”)add_random() allows you to set specific factor item
names (see vignette)sim_design() now names anonymous within and between
factors like W and B or W1, W2, W3, …, and B1, B2, … instead of A, B, C,
…add_contrast() and associated contr_code_***
functionsadd_random() and associated mixed design building
functionsget_params() doesn’t need between, within, id, and dv
set for date created by sim_design()plot_design() can display a subset of factorssim_design() fixed a bug in when setting n with an
unnamed vector and within-subjects factorssim_design() when setting n with an
unnamed vector and within-subjects factors (wouldn’t run before).add_between() and add_within() to
make new columns factors with the same ordering as the
specificationadd_between() .prob argument works as expected now (and
has tests)contr_code_deviation() to
contr_code_anova()add_contrast() functioncontr_code_plot_design() can display a subset of factorssim_design()
are now named W and B or W1, W2, W3, …, B1, B2, … instead of A, B, C, …
(and fixed relevant tests and vignette code)get_params() so it doesn’t need between, within,
id, and dv set for date created by sim_design()rnorm_pre() when simulating a vector
with correlations to more than 2 pre-existing vectors.sim_design() should no longer mangle level values in
long format if they have underscoressim_design() should play better with different
separator. FOr example, if you set faux_options(sep = ".")
and have within-subject factors A and B with levels A_1/A_2 and B_1/B_2,
your wide data will have columns A_1.B_1, A_1.B_2, A_2.B_1, A_2.B_2sim_design() where parameters specified as
a named vector couldn’t be in a different order unless both between and
within factors were specified (e.g., mu = c(A2 = 2, A1 = 1)
resulted in a mu of 2 for A1 and 1 for A2).sim_joint_dist() function to simulate the joint
distribution of categoriessim_df() no longer breaks if there are NAs in the DV
columnssim_df() now has an option to include missing data, it
simulates the joint distribution of missingness for each between-subject
cellsim_df() and messy()) can
choose columns with unquoted names now (e.g.,
messy(mtcars, .5, mpg))messy() now takes a vector of proportions so you can
simulate different amounts of missing data per selected columnsample_from_pop() is now vectorisedget_params() doesn’t require within and between set for
data made with faux (that has a “design” attribute)get_params() where the var column was
alphabetised, but the corresponding columns for the correlation table
were in factor ordernested_list() updated to match scienceverse version and
handle edge cases betterrnorm_multi() can get column names from mu, sd, or r
namesseed arguments reinstated as deprecated and produce a
warningseed arguments (at the request of
CRAN)seed argument to
rnorm_multi()nested_list function for printing nested lists in
Rmdcodebook function and vignettenorm2beta functiontrunc2norm now works if min or
max are omitted.rep argument to sim_design() and
sim_data(). If rep > 1, returns a nested data frame with
rep simulated datasets.get_params()make_id() functionfaux_options(plot = TRUE)dv = list(colname = "Name for Plots"))sim_design() can take intercept-only designsrnorm_multi() can take vars = 1 for intercept-only
designsjson_design() to output or save design specs in JSON
formatmessy() (thanks Emily)long2wide() (handle designs with no between
or no within factors)sim_df() returns subject IDs and takes data in long
formatcheck_sim_stats() to get_params(),
which now returns the designsim_design()sim_mixed_cc() to simulate null cross-classified
mixed effect designs by subject, item and error SDssim_design(), sim_df(),
sim_mixed_cc() and sim_mixed_df() take a
seed argument now for reproducible datasetscheck_design() and
sim_design()check_design() have a more
consistent format
within and between are named lists;
factors and labels are no longer separately namedsim_design() (failed when within or
between factor number was 0)NEWS.md file to track changes to the
package.sim_design() to simulate data for mixed ANOVA
designs.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.