Table and Figure

⚠️ This Post is Under Construction ⚠️ ⚠️ Make Sure You Understand the Code Before Using It ⚠️ Draft Function # my.data <- power.data.Pcytokine.p1 # group.factor <- "TYPE" # facet.factor <- "TYPE" # time.

Table of Contents Load Package and Data Table 1 with Added P-Value Columns (Parametric, Non-Parametric, and GLM) Basic table Extract Non-parametric p-value Extract regression model p-value Merge basic table and additional columns Including Columns for All Post-Hoc Pairwise Comparisons Univariable Regression Multivariable Regression Merge and group column by each table Merge and group title by header names Convert gtsummary Object to Other Objects Code for Testing Session Info ⚠️ Make Sure You Understand the Code Before Using It ⚠️

Table of Contents Introduction Input Output Example Data Example Data Wrangling Function Plot Without jitter Plot With jitter ⚠️ Make Sure You Understand the Code Before Using It ⚠️

Table of Contents Introduction Input Output Example Data Function Plot WITH single arm Plot WITH response category ⚠️ Make Sure You Understand the Code Before Using It ⚠️ Introduction A function to generate a waterfall plot showing the best percentage change from baseline for each patient, commonly used to visualize tumor response in oncology trials.

Table of Contents Introduction Reference and Resources Library and Data List of Events Code Preparing the dataset Using swimplot package Part I: Timeline Part II: Duration of Response/Events Part III: Event Time Point Part IV: Arrows Session Info Introduction A swimmer plot is a type of data visualization used in clinical trials/studies to represent the duration of treatment and the time to key events for individual patients.

Table of Contents Introduction Code Session Info Introduction This notebook covers extracting plots in different formats. Code library(officer) library(rvg) .esp, .pdf, .png, .tiff formats. postscript("Figure1-RHPD-ForestPlot-v20210729.eps", width=13, height=14, pointsize=12) pdf("ForestPlot.pdf", width=11, height=8, pointsize=16) png("ForestPlot.

Table of Contents Introduction Loading Library Snapshot of the Data Extracting Results from Univariate Models LM GLM of Binary Outcome Cox Model forestplot Package forestploter Package Basic R Extracting Results from Subset Analysis Extracting Results from Multivariate Models Session Info Introduction Forest plots are a key tool for visualizing the results of analyses.

Table of Contents Introduction Package and Data Code and Example Univariate Models Multivariate Models Session Info Introduction This is the code to generate summary table of uni-/multi-variate Cox PH models results.

Table of Contents Introduction Before we start Sample Datasets Render for Descriptive Statistics Render of Continuous Variables Render of Categorical Variables Render for Statistical Tests Two-Sample Parametric Tests Two-Sample Non-Parametric Tests Multi-Sample Parametric Tests Multi-Sample Non-Parametric Tests Sample table1 Code with Overall Sample table1 Code with Customized render and p-value Calcualtion Knit to PDF or HTML Table1 to Kable Table1 to FlexTable Introduction In this post, I will introduce how I utilize the table1 R package, which is designed to create publication-ready tables summarizing descriptive statistics and baseline characteristics of a study population.

Table of Contents Introduction Library, ggplot Theme, and Data Prep One Group Plot Sample KM Plot of Treatment Group Two Groups Plot Sample KM Plot of Two Groups Basic R Method The First Function to Generate Survival Objects The Second Function to Generate the Plot Sample Basic R Single Arm KM Plot Sample Basic R Two Arms KM Plot Session Info ⚠️ Make Sure You Understand the Code Before Using It ⚠️