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