Example data set from Gorsuch (1997) for an example factor extension.
Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Three measures of the correlations between sets of variables
Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases
Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010)
Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.
A package for personality, psychometric, and psychological research
Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss)
iclust: Item Cluster Analysis -- Hierarchical cluster analysis using psychometric principles
Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy
Draw an ICLUST graph using the Rgraphviz package
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.
The Bass-Ackward factoring algorithm discussed by Goldberg
Model comparison for regression, mediation, cluster and factor analysis
25 Personality items representing 5 factors
Decision Theory measures of specificity, sensitivity, and d prime
Sort items by absolute size of cluster loadings
Function to form hierarchical cluster analysis of items
create control code for ICLUST graphical output
Compute the Moore-Penrose Pseudo Inverse of a matrix
Draw pairs of bargraphs based on two groups
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
Find correlations of composite variables (corrected for overlap) from a larger matrix.
Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6.
A bootstrap aggregation function for choosing most predictive unit weighted items
Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters.
Seven data sets showing a bifactor solution.
cluster Fit: fit of the cluster model to a correlation matrix
Plot VSS fits
Find item by cluster correlations, corrected for overlap and reliability
9 Cognitive variables discussed by Tucker and Lewis (1973)
Find Cohen d and confidence intervals
Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors.
12 cognitive variables from Cattell (1963)
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles.
Plot factor/cluster loadings and assign items to clusters by their highest loading.
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame.
Create a 'violin plot' or density plot of the distribution of a set of variables
Plot the successive eigen values for a scree test
Compare real and random VSS solutions
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics
Simulate the C(ues) T(endency) A(ction) model of motivation
Find dis-attenuated correlations given correlations and reliabilities
Matrix and profile congruences and distances
Apply four tests of circumplex versus simple structure
8 cognitive variables used by Dwyer for an example.
Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings
Plot data and 1 and 2 sigma correlation ellipses
Plot means and confidence intervals
Convert correlations to distances (necessary to do multidimensional scaling of correlation data)
Create a block randomized structure for n independent variables
Root Mean Squared Error of Approximation from chisq, df, and n
Find a Full Information Maximum Likelihood (FIML) correlation or covariance matrix from a data matrix with missing data
Find large correlation matrices by stitching together smaller ones found more rapidly
Draw biplots of factor or component scores by factor or component loadings
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation
Create dummy coded variables
Create an image plot for a correlation or factor matrix
Bootstrapped and normal confidence intervals for raw and composite correlations
Functions for analysis of circadian or diurnal data
Graph factor loading matrices
Bock and Liberman (1970) data set of 1000 observations of the LSAT
Count number of pairwise cases for a data set with missing (NA) data and impute values.
Plot x and y error bars
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques
Smooth a non-positive definite correlation matrix to make it positive definite
Deprecated Exploratory Factor analysis functions. Please use fa
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood
Apply Dwyer's factor extension to find factor loadings for extended variables
Correlations between two factor analysis solutions
Multi level (hierarchical) factor analysis
The sample size weighted correlation may be used in correlating aggregated data
Show a dot.chart with error bars for different groups or variables
Bartlett's test that a correlation matrix is an identity matrix
How well does the factor model fit a correlation matrix. Part of the VSS package
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal.
Parse and exten formula input from a model and return the DV, IV, and associated terms.
A first approximation to Random Effects Exploratory Factor Analysis
Basic descriptive statistics useful for psychometrics
Basic summary statistics by group
Sort factor analysis or principal components analysis loadings
Helper functions for drawing path model diagrams
Find the geometric mean of a vector or columns of a data.frame.
Find R = F F' + U2 is the basic factor model
Apply the Kaiser normalization when rotating factors
Multiple Regression, Canonical and Set Correlation from matrix or raw input
A set of functions for factorial and empirical scale construction
Scree plots of data or correlation matrix compared to random ``parallel" matrices
Plot means and confidence intervals for multiple groups
Find Cohen's kappa and weighted kappa coefficients for correlation of two raters
Various ways to estimate factor scores for the factor analysis model
R* = R- F F'
Two way plots of means, error bars, and sample sizes
Find various goodness of fit statistics for factor analysis and principal components
Multiple rotations of factor loadings to find local minima
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations
``Hand" rotate a factor loading matrix
Find the greatest lower bound to reliability.
Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the other
Logistic transform from x to p and logit transform from p to x
Find von Neuman's Mean Square of Successive Differences
Coefficient of factor congruence
Multiple histograms with density and normal fits on one page
Simple function to estimate item difficulties using IRT concepts
Extract cluster definitions from factor loadings
Graph hierarchical factor structures
Find the harmonic mean of a vector, matrix, or columns of a data.frame
Combine calls to head and tail
Alternative estimates of test reliabiity
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals
Draw an ICLUST hierarchical cluster structure diagram
Find and plot various reliability/gneralizability coefficients for multilevel data
Item Response Theory estimate of theta (ability) using a Rasch (like) model
"Manhattan" plots of correlations with a set of criteria.
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame
Calculate McDonald's omega estimates of general and total factor saturation
A function to add two vectors or matrices
Plot probability of multiple choice responses as a function of a latent trait
Miscellaneous helper functions for the psych package
Estimate and display direct and indirect effects of mediators and moderator in path models
Create a keys matrix for use by score.items or cluster.cor
Find the partial correlations for a set (x) of variables with set (y) removed.
Find correlations for mixtures of continuous, polytomous, and dichotomous variables
SPLOM, histograms and correlations for a data matrix
Find miniscales (parcels) of size 2 or 3 from a set of items
Print and summary functions for the psych class
A simple demonstration of the Pearson, phi, and polychoric corelation
Find and graph Mahalanobis squared distances to detect outliers
Find the phi coefficient of correlation between two dichotomous variables
Convert a phi coefficient to a tetrachoric correlation
Sort the elements of a correlation matrix to reflect factor loadings
Test the adequacy of simple choice, logistic, or Thurstonian scaling.
Tests of significance for correlations
Find the probability of replication for an F, t, or r and estimate effect size
Correct correlations for restriction of range. (Thorndike Case 2)
Plotting functions for the psych package of class ``psych"
Reports 7 different estimates of scale reliabity including alpha, omega, split half
Phi or Yule coefficient matrix to polychoric coefficient matrix
Convert Cartesian factor loadings into polar coordinates
Function to convert scores to ``conventional
" metrics
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame
Prediction function for factor analysis, principal components (pca), bestScales
Reverse the coding of selected items prior to scale analysis
Draw a scatter plot with associated X and Y histograms, densities and correlation
Test the difference between (un)paired correlations
3 Measures of ability: SATV, SATQ, ACT
Find the predicted validities of a set of scales based on item statistics
create VSS like data
A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA.
Functions to simulate psychological/psychometric data.
Simulate a 3 way balanced ANOVA or linear model, with or without repeated measures.
Extract residuals from various psych objects
Principal components analysis (PCA)
A small example data set taken from a larger data set
Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrix
Simulate a congeneric data set with or without minor factors
Make "radar" or "spider" plots.
Create factor model matrices from an input list
Form a super matrix from two sub matrices.
Create correlation matrices or data matrices with a particular measurement and structural model
An example of the distinction between within group and between group correlations
Simulations of circumplex and simple structure
Create a population or sample correlation matrix, perhaps with hierarchical structure.
Functions to simulate psychological/psychometric data.
Apply the Schmid Leiman transformation to a correlation matrix
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items
Score scales and find Cronbach's alpha as well as associated statistics
Generate simulated data structures for circumplex, spherical, or simple structure
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations
Simulate multilevel data with specified within group and between group correlations
Further functions to simulate psychological/psychometric data.
A simple demonstration (and test) of various IRT scoring algorthims.
Find various test-retest statistics, including test, person and item reliability
Testing of functions in the psych package
Score multiple choice items and provide basic test statistics
Convert a table with counts to a matrix or data.frame representing those counts.
Score items using regression or correlation based weights
Find statistics (including correlations) within and between groups for basic multilevel analyses
Data set testing causal direction in presumed media influence
Draw a structural equation model specified by two measurement models and a structural model
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input
Several indices of the unidimensionality of a set of variables.
Thurstone Case V scaling
Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.frame
Find the trace of a square matrix