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fifer (version 1.1)

A Biostatisticians Toolbox for Various Activities, Including Plotting, Data Cleanup, and Data Analysis

Description

Functions and datasets that can be used for data cleanup (e.g., functions for eliminating all but a few columns from a dataset, selecting a range of columns, quickly editing column names), plotting/presenting data (prism-like reproductions, spearman plots for ordinal data, making colored tables, plotting interactions with quantitative variables), and analyses common to biostatistics (e.g., random forest, multiple comparisons with chi square tests). See the package vignette for a brief introduction to many of the main functions.

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Version

Install

install.packages('fifer')

Monthly Downloads

32

Version

1.1

License

GPL-2

Maintainer

Dustin Fife

Last Published

February 21st, 2017

Functions in fifer (1.1)

contents

View the contents (functions) of a package
auto.layout

Automatically select the layout.
cor2cov

Correlation Matrix to Covariance Matrix Conversion
boxcoxR

Transform data using a boxcox transformation
compute.theta

Calculate inverse tangent.
anchored.gradient

Create a color gradient with a color for zero
chisq.post.hoc

Tests for significant differences among all pairs of populations in a
demographics

Summarize a Data Set (Demographics)
colored.table

Create a color-coded table in latex
clear

Clear memory of all objects
imageInteraction

Plot an two-way quantitative interaction in an image plot
densityPlotR

Generate a density plot using a formula
excelMatch

Obtain column number or variable name from Excel named Columns
gradient.legend

Create a gradiented legend
excelCols

Generate Excel column labels
hash

Create useless hashes
ellipse

Plots an Ellipse
drop.columns

Drop (or keep) all columns containing a vector of strings
get.cols

Extract column index
fakeMedicalData

Fictitious Medical Dataset
make.formula

Convert strings to a formula
intersperse

Intersperse elements of Two+ Vectors
mv.rnorm

Randomly Generate Multivariate Normal Data
par2

Change default par parameters
make.null

Drop or keep variables in a dataset
make.symmetric

Force a matrix to be symmetric
last.sample

Return only one row per ID
par1

Change default par parameters
missing.vals

Summary of Missing Data
number.to.colors

Convert from numbers to colors
plot.rfInterp

Plot rfInterp Summary
plot.rfPred

Plot rfPred Summary
pval.xtable

Convert p-values into strings with inequalities.
prism.plots

Plot prism-like Plots
print.rfThresh

Print rfThesh Summary
print.rfInterp

Print rfInterp Summary
print.rfPred

Print rfPred Summary
printx

Change Defaults of print.xtable
plotSigBars

Add significance bars to a prism plot
plot.rfThresh

rfThesh Summary
random.correlation

Generate a random correlation matrix
rfSensitivity

Output accuracy, sensitivity, specificity, NPV, and PPV.
r.crit

Compute critical r or p.
rfPred

Variable selection in Random Forest
read.fife

Read in a dataset and load the meta-data for a file
r

Extract variable column indices
rfThresh

Variable Selection Using Random Forests
rotateGraph

Rotate a graph using polar coordinates
rfInterp

Variable Selection with Random Forest
roxtemp

Generate a Roxygen Template
spearman.plot

Spearman plot
scaleBreak

Scatterplot with a Scale Break
scaleIt

Scale a variable
stratified

Sample from a
scaleB

Standardize coefficients
SummarizeFactorDefault

Summarize a factor vector with count and percentages
subsetString

Extract only part of a string
SummarizeContinuousDefault

Summarize a continuous vector with mean plus/minus standard deviation
SummarizeVar

Summarize a vector (continuous or factor)
string.to.colors

Convert between strings to colors
univariate.tests

Extract p values for a data frame
z.test

Perform a z test
xtable.rfInterp

Prepare xtable Summary
unfactor

Convert a factor to a character (or number)
write.fife

Write a dataset and load the meta-data
summary.rfPred

Print a Summary Table of rfPred
xtable.rfPred

Prepare xtable Summary