iclust: Item Cluster Analysis -- Hierarchical cluster analysis using psychometric principles
Function to form hierarchical cluster analysis of items
A package for personality, psychometric, and psychological research
Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.
Eight political variables used by Harman (1967) as example 8.17
Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss)
Example data set from Gorsuch (1997) for an example factor extension.
5 socio-economic variables from Harman (1967)
Correlations of eight physical variables (from Harman, 1966)
Two data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
create control code for ICLUST graphical output
Draw an ICLUST graph using the Rgraphviz package
Compare real and random VSS solutions
Plot VSS fits
Perform bifactor, promax or targeted rotations and return the inter factor angles.
Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases
Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6.
9 Cognitive variables discussed by Tucker and Lewis (1973)
Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors.
16 ability items scored as correct or incorrect.
Two data sets of affect and arousal scores as a function of personality and movie conditions
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
The Schutz correlation matrix example from Shapiro and ten Berge
Plot the successive eigen values for a scree test
From a two by two table, find the Yule coefficients of association, convert to phi, or tetrachoric, recreate table the table to create the Yule coefficient.
Sort items by absolute size of cluster loadings
Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy
Create a block randomized structure for n independent variables
Bond's Logical Operations Test -- BLOT
Create an image plot for a correlation or factor matrix
Smooth a non-positive definite correlation matrix to make it positive definite
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal.
Functions for analysis of circadian or diurnal data
25 Personality items representing 5 factors
Draw pairs of bargraphs based on two groups
Seven data sets showing a bifactor solution.
A set of functions for factorial and empirical scale construction
12 cognitive variables from Cattell (1963)
Apply four tests of circumplex versus simple structure
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics
Draw biplots of factor or component scores by factor or component loadings
Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table
Sort (order) a dataframe or matrix by multiple columns
The sample size weighted correlation may be used in correlating aggregated data
Convert correlations to distances (necessary to do multidimensional scaling of correlation data)
Find dis-attenuated correlations given correlations and reliabilities
Bartlett's test that a correlation matrix is an identity matrix
Create dummy coded variables
8 cognitive variables used by Dwyer for an example.
Distances between 11 US cities
Find correlations of composite variables (corrected for overlap) from a larger matrix.
Plot factor/cluster loadings and assign items to clusters by their highest loading.
Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings
Plot data and 1 and 2 sigma correlation ellipses
``Hand" rotate a factor loading matrix
Various ways to estimate factor scores for the factor analysis model
Helper functions for drawing path model diagrams
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation
Find R = F F' + U2 is the basic factor model
R* = R- F F'
Bock and Liberman (1970) data set of 1000 observations of the LSAT
11 emotional variables from Burt (1915)
cluster Fit: fit of the cluster model to a correlation matrix
Find item by cluster correlations, corrected for overlap and reliability
Find a Full Information Maximum Likelihood (FIML) correlation or covariance matrix from a data matrix with missing data
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame.
Deprecated Exploratory Factor analysis functions. Please use fa
Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters.
Galton's example of the relationship between height and 'cubit' or forearm length
A data set from Cushny and Peebles (1905) on the effect of three drugs on hours of sleep, used by Student (1908)
Basic descriptive statistics useful for psychometrics
Basic summary statistics by group
Eysenck Personality Inventory (EPI) data for 3570 participants
13 personality scales from the Eysenck Personality Inventory and Big 5 inventory
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood
Create a 'violin plot' or density plot of the distribution of a set of variables
Two way plots of means, error bars, and sample sizes
Plot x and y error bars
Apply Dwyer's factor extension to find factor loadings for extended variables
Scree plots of data or correlation matrix compared to random ``parallel" matrices
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame
16 multiple choice IQ items
Apply the Kaiser normalization when rotating factors
Find Cohen's kappa and weighted kappa coefficients for correlation of two raters
Plot means and confidence intervals
Plot means and confidence intervals for multiple groups
Sort factor analysis or principal components analysis loadings
Transformations of r including Fisher r to z and z to r and confidence intervals
Galton's Mid parent child height data
Draw an ICLUST hierarchical cluster structure diagram
US family income from US census 2008
Bootstrapped confidence intervals for raw and composite correlations
Count number of pairwise cases for a data set with missing (NA) data.
Simulate the C(ues) T(endency) A(ction) model of motivation
Show a dot.chart with error bars for different groups or variables
Multi level (hierarchical) factor analysis
Find the geometric mean of a vector or columns of a data.frame.
Find the greatest lower bound to reliability.
Miscellaneous helper functions for the psych package
Create a keys matrix for use by score.items or cluster.cor
Sort the elements of a correlation matrix to reflect factor loadings
Multiple histograms with density and normal fits on one page
Find and plot various reliability/gneralizability coefficients for multilevel data
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations
Generate simulated data structures for circumplex, spherical, or simple structure
Find correlations for mixtures of continuous, polytomous, and dichotomous variables
Convert a phi coefficient to a tetrachoric correlation
Plotting functions for the psych package of class ``psych"
75 mood items from the Motivational State Questionnaire for 3896 participants
Find von Neuman's Mean Square of Successive Differences
SPLOM, histograms and correlations for a data matrix
Alternative estimates of test reliabiity
Find the harmonic mean of a vector, matrix, or columns of a data.frame
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations
Simple function to estimate item difficulties using IRT concepts
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques
Coefficient of factor congruence
How well does the factor model fit a correlation matrix. Part of the VSS package
Find various goodness of fit statistics for factor analysis and principal components
Print and summary functions for the psych class
Tests of significance for correlations
create VSS like data
Simulate a 3 way balanced ANOVA or linear model, with or without repeated measures.
Draw a structural equation model specified by two measurement models and a structural model
Create factor model matrices from an input list
A function to add two vectors or matrices
Estimate and display direct and indirect effects of mediators and moderator in path models
Find the probability of replication for an F, t, or r and estimate effect size
Test the difference between (un)paired correlations
Simulate multilevel data with specified within group and between group correlations
An example of the distinction between within group and between group correlations
Extract cluster definitions from factor loadings
Combine calls to head and tail
A data.frame of the Galton (1888) height and cubit data set.
Graph hierarchical factor structures
Find miniscales (parcels) of size 2 or 3 from a set of items
Correct correlations for restriction of range. (Thorndike Case 2)
Shortcuts for reading from the clipboard or a file
Convert Cartesian factor loadings into polar coordinates
Phi or Yule coefficient matrix to polychoric coefficient matrix
Prediction function for factor analysis or principal components
Principal components analysis (PCA)
Score multiple choice items and provide basic test statistics
A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA.
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame
Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrix
A simple demonstration (and test) of various IRT scoring algorthims.
Testing of functions in the psych package
Find and graph Mahalanobis squared distances to detect outliers
Find the phi coefficient of correlation between two dichotomous variables
A simple demonstration of the Pearson, phi, and polychoric corelation
Reverse the coding of selected items prior to scale analysis
Set Correlation and Multiple Regression from matrix or raw input
Functions to simulate psychological/psychometric data.
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input
Thurstone Case V scaling
Graph factor loading matrices
Item Response Theory estimate of theta (ability) using a Rasch (like) model
Plot probability of multiple choice responses as a function of a latent trait
Logistic transform from x to p and logit transform from p to x
Paired comparison of preferences for 9 vegetables
Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.frame
3 Measures of ability: SATV, SATQ, ACT
Test the adequacy of simple choice, logistic, or Thurstonian scaling.
Draw a scatter plot with associated X and Y histograms, densities and correlation
Simulations of circumplex and simple structure
Form a super matrix from two sub matrices.
Convert a table with counts to a matrix or data.frame representing those counts.
Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the other
NEO correlation matrix from the NEO_PI_R manual
Calculate McDonald's omega estimates of general and total factor saturation
Find the partial correlations for a set (x) of variables with set (y) removed.
Create correlation matrices or data matrices with a particular measurement and structural model
Galton`s Peas
Function to convert scores to ``conventional
" metrics
Extract residuals from various psych objects
Apply the Schmid Leiman transformation to a correlation matrix
Score scales and find Cronbach's alpha as well as associated statistics
Simulate a congeneric data set
Create a population or sample correlation matrix, perhaps with hierarchical structure.
Make "radar" or "spider" plots.
Find statistics (including correlations) within and between groups for basic multilevel analyses
Find the trace of a square matrix
Several indices of the unidimensionality of a set of variables.