Nothing
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.Any scripts or data that you put into this service are public.
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