nice_frequencies()
: Now has a grouping argument. This allows to create contingency tables (e.g. nice_frequencies(mtcars$cyl, mtcars$am)
).nice_table()
: New argument markdown
. If TRUE, interprets cell content as markdown.nice_frequencies()
: Provides html and word tables for the frequency distribution of a variable.nice_sem()
: Provides html and word tables for lavaan sem objects.nice_regression_table()
: Provides html and word tables for one or multiple lm
, lme
, lmerTest
, or glmer
objects.round_numeric()
: This function rounds numeric columns in a data frame to a specified number of digits.logit2prob()
/ prob2logit()
: Convert Logit to probability and vice versaadd_label()
: Adds haven labels. With a list option: mtcars <- add_label(mtcars, list(cyl = "cylind", mpg = "Miles"))
get_labels()
: Adds haven labels. With a list option: mtcars <- add_label(mtcars, list(cyl = "cylind", mpg = "Miles"))
nice_loadings()
extract loadings from psych::fa objectnice_efa()
Returns a nice table from an psych::fa object.nice_agreement_table()
Returns a nice table for agreement_analyses.flip()
: flip a data.frame or matrix: flip(mtcars, rownames = TRUE)
change_values()
recode values: change_values(c(1, 2, 3), 2 ~ "two", 3 ~ "three")
percentage_bar()
creates ggplot percentage bar: percentage_bar(20, "test")
auto_corr()
nice_statnum()
nice_descriptives()
agreement_analysis()
check(), start_check(). end_check(), check_within(), check_in(), check_not()
progress_feedback.R()
fill_missing_l2()
: Fills in missing data for cases in a multilevel/
repeated measurement long format data frame. This is useful when you have a variable
on level 2 (e.g., gender) but this variable only has a valid value for one measurement time (the others are na). This function will fill in the nas with this one valid value.New function to extend Rmarkdown pages:
create_blogsite()
: Helps to create a blog-like site for Rmarkdown webpages
new_blog_entry()
: Sets up a new blog entry markdown page
chi_test_table()
: Compares the proportions of a dichotomos variable in two groups for multiple variables and puts the results into a table. Like t_test_table() put für dichtomous variables.t_test_table()
: new arguments: caption, bootstrap_options, and full_widthreference_package_version()
alpha_table()
: argument VAR
changed to scales
. New arguements difficulty
: if TRUE reports item difficulties. values
min and max value for each scale as a vector needed for calculating item difficulty.Add the following code to your website.
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