tidycomm 0.4.1
tidycomm 0.3.0
New features
- Converted
tibble returns into tdcmm/tibble return objects (they behave just like tibbles but are in essence our own objects now)
- Added partial correlation in
correlate(..., partial = z_var)
- Added correlation with a focus variable
correlate(..., with = focus_var)
- Added linear regression
regress()
- Added one-sample t-test
t_test(..., mu = ...)
- Added
reverse_scale(), minmax_scale(), z_scale(), center_scale(), setna_scale(), recode_cat_scale(), recode_scale(), and dummify_cale() to shift and modify continuous and categorical scales
- Added
tab_percentiles()
- Added
visualize() to visualize almost everything
- Added
snscomments and incvlcomments as additional data sets
Minor changes
- Changed
unianova() and t_test() to build on leveneTest()
- Allowed
test_icr() to work with grouped data
- Converted all code examples in documentation to be built on
tidycomm-provided data sets
- Added
omega_squared, Levene_p, and var_equal columns to default return from unianova()
- Added
d, se, t, and df
- Removed
null.value from list of return values in unianova() post-hoc test
- Renamed
unianova() return column names to Variable (previously: Var), Group_Var (prev. term), Delta_M (prev. estimate), p (prev. adj.p.value), conf.lower and conf.upper (prev. conf.low and conf.high)
Bugfixes
- Unified output to coherent number of after-comma digits
tidycomm 0.2.0
New features
- Added Fretwurst’s Lotus and S-Lotus intercoder reliability coeffecients to
test_icr() function
describe_cat() function added to describe categorical variables
Minor changes
- More descriptive error messages for common errors
describe() now also reports 95% confidence intervals
describe() now reports valid N instead of full N
test_icr() now works with tidyselect selection
Bugfixes
- Empty groups are dropped if describing with more than one grouping variable
- Krippendorff’s Alpha returns 1 if variable has only one category
unianova() now works with variable names containing whitespace
- Groups are dropped for
test_icr() to avoid computational issues