rmulti() that assigned correlations to the wrong pairs with
more than 3 variables (thanks @yann1cks!)rmulti() more efficient by skipping adjusted r
simulation for normal-normal pairsnbinom2norm() conversion function, but not sure
it works right unless you set size and prob
manually (produces a warning if you don’t)interactive_design() that didn’t allow
mu, sd or r with more than 0.1 accuracy, and gave incorrect error
messages for r specifications with more than 1 value.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.
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.