A package for personality, psychometric, and psychological research
Decision Theory measures of specificity, sensitivity, and d prime
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.
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
Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss)
iclust: Item Cluster Analysis - Hierarchical cluster analysis using psychometric principles
Function to form hierarchical cluster analysis of items
create control code for ICLUST graphical output
Draw an ICLUST graph using the Rgraphviz package
Sort items by absolute size of cluster loadings
Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy
Compute the Moore-Penrose Pseudo Inverse of a matrix
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles.
Root Mean Squared Error of Approximation from chisq, df, and n
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
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
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.
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.
Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6.
Model comparison for regression, mediation, cluster and factor analysis
The Bass-Ackward factoring algorithm discussed by Goldberg
A bootstrap aggregation function for choosing most predictive unit weighted items
25 Personality items representing 5 factors
Draw pairs of bargraphs based on two groups
Seven data sets showing a bifactor solution.
Find large correlation matrices by stitching together smaller ones found more rapidly
Draw biplots of factor or component scores by factor or component loadings
Create a block randomized structure for n independent variables
Bock and Liberman (1970) data set of 1000 observations of the LSAT
12 cognitive variables from Cattell (1963)
Apply four tests of circumplex versus simple structure
Find correlations of composite variables (corrected for overlap) from a larger matrix.
cluster Fit: fit of the cluster model to a correlation matrix
Find item by cluster correlations, corrected for overlap and reliability
Plot factor/cluster loadings and assign items to clusters by their highest loading.
Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters.
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics
Matrix and profile congruences and distances
Bootstrapped and normal confidence intervals for raw and composite correlations
Create an image plot for a correlation or factor matrix
Smooth a non-positive definite correlation matrix to make it positive definite
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 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.
Find dis-attenuated correlations given correlations and reliabilities
Bartlett's test that a correlation matrix is an identity matrix
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
Count number of pairwise cases for a data set with missing (NA) data and impute values.
Simulate the C(ues) T(endency) A(ction) model of motivation
Create a 'violin plot' or density plot of the distribution of a set of variables
Deprecated Exploratory Factor analysis functions.  Please use fa
Basic descriptive statistics useful for psychometrics
Helper functions for drawing path model diagrams
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation
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 for multiple groups
Two way plots of means, error bars, and sample sizes
Show a dot.chart with error bars for different groups or variables
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques
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
A set of functions for factorial and empirical scale construction
Scree plots of data or correlation matrix compared to random "parallel" matrices
A first approximation to Random Effects Exploratory Factor Analysis
Sort factor analysis or principal components analysis loadings
Correlations between two factor analysis solutions
Multi level (hierarchical) factor analysis
Multiple rotations of factor loadings to find local minima
How well does the factor model fit a correlation matrix. Part of the VSS package
Find R = F F' + U2 is the basic factor model
Various ways to estimate factor scores for the factor analysis model
Find various goodness of fit statistics for factor analysis and principal components
Extract cluster definitions from factor loadings
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals
Parse and exten formula input from a model and return the DV, IV, and associated terms.
Find the geometric mean of a vector or columns of a data.frame.
Find the greatest lower bound to reliability.
Alternative estimates of test reliabiity
Find the harmonic mean of a vector, matrix, or columns of a data.frame
Draw an ICLUST hierarchical cluster structure diagram
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations
Simple function to estimate item difficulties using IRT concepts
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
Apply the Kaiser normalization when rotating factors
Find Cohen's kappa and weighted kappa coefficients for correlation of two raters
Multiple Regression, Canonical and Set Correlation from matrix or raw input
Logistic transform from x to p and logit transform from p to x
Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the other
Create a keys matrix for use by score.items or cluster.cor
"Manhattan" plots of correlations with a set of criteria.
Sort the elements of a correlation matrix to reflect factor loadings
A function to add two vectors or matrices
Estimate and display direct and indirect effects of mediators and moderator in path models
Miscellaneous helper functions for the psych package
Find correlations for mixtures of continuous, polytomous, and dichotomous variables
Find von Neuman's Mean Square of Successive Differences
Multiple histograms with density and normal fits on one page
Find and plot various reliability/gneralizability coefficients for multilevel data
Calculate McDonald's omega estimates of general and total factor saturation
Find and graph Mahalanobis squared distances to detect outliers
Find the probability of replication for an F, t, or r and estimate effect size
Test the difference between (un)paired correlations
SPLOM, histograms and correlations for a data matrix
Find miniscales (parcels) of size 2 or 3 from a set of items
Find the partial correlations for a set (x) of variables with set (y) removed.
Find the phi coefficient of correlation between two dichotomous variables
A simple demonstration of the Pearson, phi, and polychoric corelation
Convert a phi coefficient to a tetrachoric correlation
Plotting functions for the psych package of class "psych"
Convert Cartesian factor loadings into polar coordinates
Phi or Yule coefficient matrix to polychoric coefficient matrix
Prediction function for factor analysis, principal components (pca), bestScales
Find the predicted validities of a set of scales based on item statistics
Print and summary functions for the psych class
Correct correlations for restriction of range. (Thorndike Case 2)
Reports 7 different estimates of scale reliabity including alpha, omega, split half
Function to convert scores to "conventional " metrics
Extract residuals from various psych objects
Reverse the coding of selected items prior to scale analysis
Test the adequacy of simple choice, logistic, or Thurstonian scaling.
Draw a scatter plot with associated X and Y histograms, densities and correlation
Apply the Schmid Leiman transformation to a correlation matrix
Score scales and find Cronbach's alpha as well as associated statistics
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
Score multiple choice items and provide basic test statistics
Score items using regression or correlation based weights
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.
Simulate a congeneric data set with or without minor factors
Create a population or sample correlation matrix, perhaps with hierarchical structure.
Generate simulated data structures for circumplex, spherical, or simple structure
Simulate multilevel data with specified within group and between group correlations
Further functions to simulate psychological/psychometric data.
Create correlation matrices or data matrices with a particular measurement and structural model
Simulations of circumplex and simple structure
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame
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
Find statistics (including correlations) within and between groups for basic multilevel analyses
Draw a structural equation model specified by two measurement models and a structural model
Create factor model matrices from an input list
Form a super matrix from two sub matrices.
Convert a table with counts to a matrix or data.frame representing those counts.
Data set testing causal direction in presumed media influence
A simple demonstration (and test) of various IRT scoring algorthims.
Testing of functions in the psych package
Find various test-retest statistics, including test, person and item reliability
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input
Several indices of the unidimensionality of a set of variables.
Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.frame
An example of the distinction between within group and between group correlations