clinpubr1.1.0 package

Clinical Publication

add_lists

Adding lists element-wise

answer_check

Check answers of multiple choice questions

baseline_table

Create a baseline table for a dataset.

break_at

Generate breaks for histogram

calculate_index

Calculate index based on conditions

check_nonnum

Check elements that are not numeric

check_package

Check if a package is available and provide helpful error message

classif_model_compare

Performance comparison of classification models

combine_files

combine multiple data files into a single data frame

combine_multichoice

Combine multi-choice columns into one

common_prefix

Get common prefix of a string vector

cut_by

Convert Numeric to Factor

df_view_nonnum

Show non-numeric elements in a data frame

emp_colors

default color palette for clinpubr plots

exclusion_count

Count the number of excluded samples at each step

extract_num

Extract numbers from string.

fill_with_last

Fill NA values with the last valid value

filter_rcs_predictors

Filter predictors for RCS

first_mode

Calculate the first mode

format_pval

Format p-value for publication

formula_add_covs

Add covariates to a formula

get_samples

Generate a sample of values from a vector and collapse them.

get_valid_subset

Get the subset that satisfies the missing rate condition.

get_valid

Get one valid value from vector.

get_var_types

Get variable types for baseline table

importance_plot

Importance plot

indicate_duplicates

Determine duplicate elements including their first occurrence.

interaction_p_value

Calculate interaction p-value

interaction_plot

Plot interactions

interaction_scan

Scan for interactions between variables

mad_outlier

Mark possible outliers with MAD.

max_missing_rates

Get the maximum missing rate of rows and columns.

merge_ordered_vectors

Merging vectors while maintaining order

na_max

Safe min and max functions that return NA if all values are NA

na2false

Replace NA values with FALSE

predictor_effect_plot

Plot the effect of a predictor variable

qq_show

QQ plot

rcs_plot

Plot restricted cubic spline

regression_basic_results

Basic results of logistic or Cox regression.

regression_fit

Obtain regression results

regression_forest

Forest plot of regression results

regression_scan

Scan for significant regression predictors

replace_elements

Replacing elements in a vector

split_multichoice

Split multi-choice data into columns

str_match_replace

Match string and replace with corresponding value

subgroup_forest

Create subgroup forest plot.

subject_view

Get an overview of different subjects in data.

test_normality

Test normality of a numeric variable

to_date

Convert numerical or character date to date.

unit_standardize

Standardize units of numeric data.

unit_view

Generate a table of conflicting units.

unmake_names

Unmake names

value_initial_cleaning

Preliminarily cleaning string vectors

vec2code

Generate code from string vector Generate the code that can be used to...

Accelerate the process from clinical data to medical publication, including clinical data cleaning, significant result screening, and the generation of publish-ready tables and figures.

  • Maintainer: Yue Niu
  • License: MIT + file LICENSE
  • Last published: 2025-10-30