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Hmisc (version 2.2-0)

Harrell Miscellaneous

Description

The Hmisc library contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of S objects to LaTeX code, and recoding variables.

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Version

Install

install.packages('Hmisc')

Monthly Downloads

215,759

Version

2.2-0

License

GPL version 2 or newer

Homepage

http://biostat.mc.vanderbilt.edu/s/Hmisc

Maintainer

Frank E Harrell Jr

Last Published

March 16th, 2025

Functions in Hmisc (2.2-0)

Character strings from unquoted names

Box-percentile plots

Linear Extrapolation

Generic Functions and Methods for Imputation

Enhanced Dot Chart

Convert an S object to HTML

Overview of Hmisc Library

Miscellaneous Functions

Back to Back Histograms

Bootstrap Kaplan-Meier Estimates

First Word in a String or Expression

Indexes of Absolute Prediction Error for Linear Models

Flexible Event Chart for Time-to-Event Data

Confidence Intervals for Binomial Probabilities

Internal Hmisc functions

Gaussian Bayesian Posterior and Predictive Distributions

Power of Cox/log-rank Two-Sample Test

Design Effect and Intra-cluster Correlation

Representativeness of Observations in a Data Set

Matrix of Hoeffding's D Statistics

Statistics by Categories

na.detail.response

Detailed Response Variable Information

Row-wise Deletion na.action

Concise Statistical Description of a Vector, Matrix, Data Frame, or Formula

Harrell-Davis Distribution-Free Quantile Estimator

Power of Interaction Test for Exponential Survival

Special Version of legend for R

Do-nothing na.action

Check if All Elements in Character Vector are Numeric

Pretty-print the Structure of a Data Object

Multiple Imputation using Additive Regression, Bootstrapping, and Predictive Mean Matching

Minor Tick Marks

Restricted Cubic Spline Design Matrix

Date/Time/Directory Stamp the Current Plot

Plot smoothed estimates

Box-Percentile Panel Function for Trellis

Cut a Numeric Variable into Intervals

Format a Data Frame or Matrix for LaTeX or HTML

Power and Sample Size for Ordinal Response

plotCorrPrecision

Plot Precision of Estimate of Pearson Correlation Coefficient

Postscript and Adobe PDF Setup for 35mm Slides and Other Formats

Character String Editing and Miscellaneous Character Handling Functions

Lag a Numeric, Character, or Factor Vector

Store an Object Permanently

Plot Error Bars

Summarize Scalars or Matrices by Cross-Classification

Simulate Power of 2-Sample Test for Survival under Complex Conditions

Label Curves, Make Keys, and Interactively Draw Points and Curves

Display Colors, Plotting Symbols, and Symbol Numeric Equivalents

Rank Correlation for Paired Predictors with a Censored Response

Source a File from the Current Working Directory

solve Function with tol argument

Empirical Cumulative Distribution Plot

Plot Restricted Cubic Spline Function

Run Unix or Dos Depending on System

First Principal Component

Translate Vector or Matrix of Text Strings

Generate Multinomial Random Variables with Varying Probabilities

Sample Size for 2-sample Binomial

Print and Object with its Name

xyplot and dotplot with Matrix Variables to Plot Error Bars and Bands

Produces event.history graph for survival data

Mean x vs. function of y in groups of x

Draw Axes With Side-Specific mgp Parameters

hist.data.frame

Histograms for Variables in a Data Frame

summary.formula

Summarize Data for Making Tables and Plots

Power and Sample Size for Two-Sample Binomial Test

print.char.matrix

Function to print a matrix with stacked cells

Reorder Factor Levels

rcspline.restate

Re-state Restricted Cubic Spline Function

Convert an S object to LaTeX, and Related Utilities

Label Attribute of an Object

Convert a SAS Dataset to an S Data Frame

Score a Series of Binary Variables

Somers' Dxy Rank Correlation

Rank Correlation for Censored Data

Graphic Representation of a Frequency Table

data.frame.create.modify.check

Tips for Creating, Modifying, and Checking Data Frames

Enhanced Importing of SAS Transport Files using read.xport

Reshape Matrices and Serial Data

Enhanced Importing of SPSS Files

t-test for Clustered Data

Units Attribute of a Vector

Weighted Statistical Estimates

Variable Clustering

One-Dimensional Scatter Diagram, Spike Histogram, or Density

Transformations/Imputations using Canonical Variates

Update a Data Frame or Cleanup a Data Frame after Importing

Find Matching (or Non-Matching) Elements

Download and Install Datasets for Hmisc, Design, and Statistical Modeling

Compute the Interaction of Several Factors

Group Sequential Boundaries using the Lan-DeMets Approach

Bootstrap Repeated Measurements Model

Compute Summary Statistics on a Vector

Metadata for a Data Frame

Find Close Matches

Matrix of Correlations and Generalized Spearman Rank Correlation

Additive Regression and Transformations using ace or avas