ci_score(): Returns confidence intervals for test scores.critical_difference(): Returns critical difference for test scores.nice_contingency_table(): Creates a nicely formatted contingency table with one or more summary functions.create_data_description(): Creates a README.md file with a data description.nice_frequencies(): Now has a grouping argument. This allows creating contingency tables (e.g. nice_frequencies(mtcars$cyl, mtcars$am)).nice_table():
markdown. If TRUE, interprets cell content as markdown.nice_regression_table(), nice_efa(), and a default method for data.frame objects.rownames = NULL now automatically shows row names unless they are as.character(1:nrow(x)).sort allows sorting by a character vector.nice_regression_table(): Now supports gls models.nice_efa(): now works for one factor solutions.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 lm, lme, lmerTest, or glmer models.round_numeric(): Rounds numeric columns in a data frame to a specified number of digits.logit2prob() / prob2logit(): Convert between logit and probability.add_label(): Adds haven labels. Accepts a list input, e.g., mtcars <- add_label(mtcars, list(cyl = "cylind", mpg = "Miles")).get_labels(): Retrieves haven labels.nice_loadings(): Extracts loadings from a psych::fa object.nice_efa(): Returns a formatted table from a psych::fa object.nice_agreement_table(): Returns a formatted table for agreement analyses.flip(): Flips a data frame or matrix, e.g., flip(mtcars, rownames = TRUE).change_values(): Recodes values using formula syntax, e.g., change_values(c(1, 2, 3), 2 ~ "two", 3 ~ "three").percentage_bar(): Creates a ggplot percentage bar, e.g., percentage_bar(20, "test").nice_table(): Now defaults to gt tables; the older kable output is being retired.fill_missing_l2(): Fills in missing values in multilevel/repeated measurement long format data. Useful for level-2 variables like gender that may only appear in one measurement occasion.chi_test_table(): Compares the proportions of a dichotomous variable across two groups for multiple variables. Similar to t_test_table() but for categorical variables.t_test_table(): Added arguments caption, bootstrap_options, and full_width.alpha_table():
VAR renamed to scales.difficulty: If TRUE, reports item difficulties.values: Required for calculating item difficulty; specify min and max values for each scale.