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lessR (version 3.2)

Less Code, More Results

Description

Each function accomplishes the work of several or more standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate descriptive statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for descriptive statistics, a comprehensive regression analysis, analysis of variance and t-test, plotting, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function and color themes. The function Help provides a help system that suggests specific analyses and functions. Variable labels are available. A confirmatory factor analysis of multiple indicator measurement models is also available as is a pedagogical routines for data simulation such as for the Central Limit Theorem.

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Version

Install

install.packages('lessR')

Monthly Downloads

2,931

Version

3.2

License

GPL (>= 2)

Maintainer

David W Gerbing

Last Published

February 25th, 2015

Functions in lessR (3.2)

Histogram

Histogram with Color
corScree

Eigenvalue Plot of a Correlation Matrix
dataJackets

Data: Motorcycle Type and Thickness of Jacket
showColors

Display All Named R Colors and Corresponding rgb Values
BarChart

Bar Chart of One or Two Variables
Help

Help System for Statistics by Topic that Suggests Related Functions
LineChart

Line Chart such as a Run Chart or Time-Series Chart
simMeans

Pedagogical Simulation of Sample Means over Repeated Samples
corCFA

Confirmatory Factor Analysis of a Multiple Indicator Measurement Model
corReorder

Reorder Variables in a Correlation Matrix
ScatterPlot

Scatterplot for One (Dot Plot) or Two Variables
CountAll

CountAll Descriptive Analysis of all Variables in the Data Frame
corEFA

Exploratory Factor Analysis and Multiple Indicator Measurement Model
Transform

Transform the Values of an Integer or Factor Variable
dataEmployee

Data: Employees
Nest

Nest the Values of an Integer or Factor Variable
Density

Density Curves from Data plus Histogram
dataMach4

Data: Machiavellianism
prob.tcut

Plot t-distribution Curve and Specified Cutoffs with Normal Curve
ttest

Generic Method for t-test and Standardized Mean Difference with Enhanced Graphics
Sort

Sort the Rows of a Data Frame
Subset

Subset the Values of an Integer or Factor Variable
corReflect

Reflect Specified Variables in a Correlation Matrix
BoxPlot

Boxplot
details

Display Contents of a Data File and Optional Variable Labels
Model

Regression Analysis, ANOVA or t-test
dataBodyMeas

Data: Body Measurements
simCLT

Pedagogical Simulation for the Central Limit Theorem
corProp

Proportionality Coefficients from Correlations
to

Create a Sequence of Numbered Variable Names with a Common Prefix
prob.norm

Compute and Plot Normal Curve Probabilities over an Interval
label

Return or Assign a Variable Label
Correlation

Correlation Analysis
ttestPower

Compute a Power Curve for a One or Two Group t-test
Regression

Regression Analysis
values

List the Values of a Variable
dataLearn

Data: Distributed vs Massed Practice
ANOVA

Analysis of Variance
Write

Write the Contents of a Data Frame to an External File
corRead

Read Specified Correlation Matrix
simFlips

Pedagogical Binomial Simulation, Coin flips
prob.znorm

Plot a Normal Curve with Shaded Intervals by Standard Deviation
PieChart

Pie Chart
Read

Read Contents of a Data File with Optional Variable Labels and Feedback
SummaryStats

Summary Statistics for One or Two Variables
Logit

Logit Regression Analysis
Recode

Recode the Values of an Integer or Factor Variable
dataCars93

Data: Cars93
dataReading

Data: Reading Ability
set

Set the Default Color Theme and Other System Settings
Merge

Merge Two Data Frames Horizontally or Vertically
simCImean

Pedagogical Simulation for the Confidence Interval of the Mean