Package: psych 2.6.5

psych: Procedures for Psychological, Psychometric, and Personality Research

A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r/> web page.

Authors:William Revelle [aut, cre]

psych_2.6.5.tar.gz
psych_2.6.5.zip(r-4.7)psych_2.6.5.zip(r-4.6)psych_2.6.5.zip(r-4.5)
psych_2.6.5.tgz(r-4.6-any)psych_2.6.5.tgz(r-4.5-any)
psych_2.6.5.tar.gz(r-4.7-any)psych_2.6.5.tar.gz(r-4.6-any)
psych_2.6.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
psych/json (API)

# Install 'psych' in R:

install.packages('psych', repos = c('https://revelle.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

Bechtoldt - Seven data sets showing a bifactor solution.
Bechtoldt.1 - Seven data sets showing a bifactor solution.
Bechtoldt.2 - Seven data sets showing a bifactor solution.
bfi - 25 Personality items representing 5 factors
bfi.dictionary - 25 Personality items representing 5 factors
bfi.keys - 25 Personality items representing 5 factors
bock.table - Bock and Liberman (1970) data set of 1000 observations of the LSAT
cattell - 12 cognitive variables from Cattell
Chen - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
Dwyer - 8 cognitive variables used by Dwyer for an example.
Garcia - Data from the sexism
Gleser - Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.
Gorsuch - Example data set from Gorsuch (1997) for an example factor extension.
Harman_5 - Six data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Harman.5 - Six data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Harman.8 - Six data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Harman.Burt - Six data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Harman.Holzinger - Six data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Harman.political - Six data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Holzinger - Seven data sets showing a bifactor solution.
Holzinger.9 - Seven data sets showing a bifactor solution.
lsat6 - Bock and Liberman (1970) data set of 1000 observations of the LSAT
lsat7 - Bock and Liberman (1970) data set of 1000 observations of the LSAT
Reise - Seven data sets showing a bifactor solution.
sat.act - 3 Measures of ability: SATV, SATQ, ACT
Schmid - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
schmid.leiman - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
small.msq - A small example data set taken from a larger data set
Tal_Or - Data set testing causal direction in presumed media influence
Tal.Or - Data set testing causal direction in presumed media influence
Thurstone - Seven data sets showing a bifactor solution.
Thurstone.33 - Seven data sets showing a bifactor solution.
Thurstone.33G - Seven data sets showing a bifactor solution.
Thurstone.9 - Seven data sets showing a bifactor solution.
Tucker - 9 Cognitive variables discussed by Tucker and Lewis
West - 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
withinBetween - An example of the distinction between within group and between group correlations

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

14.30 score 57 stars 346 packages 34k scripts 244k downloads 1.1k mentions 483 exports 4 dependencies

Last updated from:2b17d1e78b. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	240
source / vignettes	OK	270
linux-release-x86_64	OK	214
macos-release-arm64	OK	137
macos-oldrel-arm64	OK	146
windows-devel	OK	227
windows-release	OK	202
windows-oldrel	OK	225
wasm-release	OK	97

Exports:%+%acs alpha alpha.ci alpha2r anova.psych AUC autoR bassAckward bassAckward.diagram bestItems bestScales bi.bars bifactor bigCor biPlot biplot.psych biquartimin biserial block.random cancorDiagram cd.validity CFA CFA.bifactor char2numeric chi2r circ.sim circ.sim.plot circ.simulation circ.tests circadian.cor circadian.F circadian.linear.cor circadian.mean circadian.phase circadian.reliability circadian.sd circadian.stats circular.cor circular.mean cluster.cor cluster.fit cluster.loadings cluster.plot cluster2keys cohen.d cohen.d.by cohen.d.ci cohen.kappa cohen.profile cohenPooled comorbidity con2cat congeneric.sim congruence cor.ci cor.plot cor.plot.upperLowerCi cor.smooth cor.smoother cor.wt cor2 cor2cov cor2dist corCi corFiml corInfo corPlot corPlotUpperLowerCi corr.p corr.test correct.cor cortest corTest cortest.bartlett cortest.jennrich cortest.mat cortest.normal cosinor cosinor.period cosinor.plot count.pairwise crossValidation crossValidationBoot cs cta cta.15 d.ci d.robust d2CL d2OVL d2OVL2 d2r d2t d2U3 densityBy describe describe.by describeBy describeData describeFast dia.arrow dia.cone dia.curve dia.curved.arrow dia.ellipse dia.ellipse1 dia.rect dia.self dia.shape dia.triangle diagram directSl distance draw.cor draw.tetra dummy.code eigen.loadings eigenCi ellipses equamax error.bars error.bars.by error.bars.tab error.crosses error.dots errorCircles esem esem.diagram esemDiagram extension.diagram fa fa.congruence fa.diagram fa.extend fa.extension fa.graph fa.lookup fa.multi fa.multi.diagram fa.organize fa.parallel fa.parallel.poly fa.plot fa.poly fa.pooled fa.random fa.rgraph fa.sapa fa.sort fa.stats fa2irt faBy fac faCor factor.congruence factor.fit factor.minres factor.model factor.pa factor.plot factor.residuals factor.rotate factor.scores factor.stats factor.wls factor2cluster faReg faRegression faRotate faRotations fisherz fisherz2r fparse fromTo fsi g2r geometric.mean glb glb.algebraic glb.fa guttman harmonic.mean headtail headTail het.diagram histBy ICC iclust ICLUST ICLUST.cluster iclust.diagram ICLUST.graph ICLUST.rgraph iclust.sort ICLUST.sort interbattery interp.boxplot interp.median interp.q interp.qplot.by interp.quantiles interp.quart interp.quartiles interp.values irt.0p irt.1p irt.2p irt.CFA irt.discrim irt.fa irt.item.diff.rasch irt.person.rasch irt.responses irt.se irt.select irt.stats.like irt.tau isCorrelation isCovariance item.dichot item.lookup item.sim item.validity itemSort kaiser keys.lookup keys2list keysort KMO kurtosi lavaan.diagram lavParse levels2numeric lmCor lmCor.diagram lmCorLookup lmDiagram logistic logistic.grm logit lookup lookupFromKeys lookupItems lowerCor lowerMat lowerUpper m2d m2t make.congeneric make.hierarchical make.irt.stats make.keys makePositiveKeys manhattan mardia mat.regress mat.sort matMult matPlot matReg matSort mediate mediate.diagram minkowski mixed.cor mixedCor mlArrange mlPlot mlr moderate.diagram mssd multi.arrow multi.curved.arrow multi.hist multi.rect multi.self multilevel.reliability nchar2numeric nfactors omega omega.diagram omega.graph omegaDirect omegaFromSem omegah omegaSem omegaStats outlier p.rep p.rep.f p.rep.r p.rep.t paired.r pairs.panels pairwiseCount pairwiseCountBig pairwiseDescribe pairwiseImpute pairwisePlot pairwiseReport pairwiseSample pairwiseZero parcels partial.r paSelect pca phi phi.demo phi.list phi2poly phi2poly.matrix phi2tetra Pinv plot.irt plot.poly plot.poly.parallel plot.psych plot.reliability plot.residuals polar poly.mat polychoric polydi polyserial predict.psych predicted.validity principal print.psych Procrustes progressBar Promax psych psych.misc quickView r.con r.test r2alpha r2c r2chi r2d r2p r2t radar rangeCorrection reflect reliability removeMissing rescale resid.psych residuals.psych response.frequencies responseFrequency reverse.code RMSEA rmssd RV SAPAfy scaling.fits scatter.hist scatterHist schmid score.alpha score.irt score.irt.2 score.irt.poly score.items score.multiple.choice scoreBy scoreFast scoreIrt scoreIrt.1pl scoreIrt.2pl scoreItems scoreOverlap scoreVeryFast scoreWtd scree scrub SD selectFromKeys sem.diagram sem.graph set.cor setCor shannon sim sim.anova sim.bonds sim.circ sim.congeneric sim.correlation sim.dichot sim.general sim.hierarchical sim.irt sim.item sim.minor sim.multi sim.multilevel sim.npl sim.npn sim.omega sim.parallel sim.poly sim.poly.ideal sim.poly.ideal.npl sim.poly.ideal.npn sim.poly.mat sim.poly.npl sim.poly.npn sim.rasch sim.simplex sim.spherical sim.structural sim.structure sim.VSS simCor simulation.circ skew smc spider splitHalf statsBy statsBy.boot statsBy.boot.summary structure.diagram structure.graph structure.list structure.sem summary.psych super.matrix superCor superMatrix t2d t2r table2df table2matrix tableF target.rot TargetQ TargetT tenberge test.all test.irt test.psych testRetest tetrachoric thurstone topBottom tr unidim validityItem varimin vech vgQ.bimin vgQ.targetQ vgQ.varimin violin violinBy vss VSS VSS.parallel VSS.plot VSS.scree VSS.sim VSS.simulate vssSelect winsor winsor.mean winsor.means winsor.sd winsor.var wkappa Yule Yule.inv Yule2phi Yule2phi.matrix Yule2poly Yule2poly.matrix Yule2tetra YuleBonett YuleCor

Dependencies:GPArotation lattice mnormt nlme

Scoring scales with psych

Rendered fromscoring.Rnwusingknitr::knitr

Last update: 2026-05-16
Started: 2020-10-05

Help page	Topics
A package for personality, psychometric, and psychological research	psych-package psych
Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6.	alpha alpha.ci alpha.scale alpha2r r2alpha
Model comparison for regression, mediation, cluster and factor analysis	anova.psych
Decision Theory measures of specificity, sensitivity, and d prime	AUC auc Sensitivity Specificity
The Bass-Ackward factoring algorithm discussed by Goldberg	bassAckward bassAckward.diagram
Seven data sets showing a bifactor solution.	Bechtoldt Bechtoldt.1 Bechtoldt.2 Holzinger Holzinger.9 Reise Thurstone Thurstone.33 Thurstone.33G Thurstone.9
A bootstrap aggregation function for choosing most predictive unit weighted items	bestItems bestScales BISCUIT biscuit BISCWIT biscwit
25 Personality items representing 5 factors	bfi bfi.dictionary bfi.keys
Draw pairs of bargraphs based on two groups	bi.bars
Find large correlation matrices by stitching together smaller ones found more rapidly	bigCor
Draw biplots of factor or component scores by factor or component loadings	biPlot biplot.psych
Create a block randomized structure for n independent variables	block.random
Bock and Liberman (1970) data set of 1000 observations of the LSAT	bock bock.lsat bock.table lsat6 lsat7
12 cognitive variables from Cattell (1963)	cattell
Confirmatory Factor Analysis Without Iteration	CFA CFA.bifactor irt.CFA
Apply four tests of circumplex versus simple structure	circ.tests
cluster Fit: fit of the cluster model to a correlation matrix	cluster.fit
Find item by cluster correlations, corrected for overlap and reliability	cluster.loadings
Plot factor/cluster loadings and assign items to clusters by their highest loading.	cluster.plot fa.plot factor.plot
Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters.	cluster2keys
Find Cohen d and confidence intervals	cd.validity cohen.d cohen.d.by cohen.d.ci cohenPooled d.ci d.robust d2CL d2OVL d2OVL2 d2r d2t d2U3 m2d m2t r2d t2d
Find Cohen's kappa and weighted kappa coefficients for correlation of two raters	cohen.kappa wkappa
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics	comorbidity
Matrix and profile congruences and distances	cohen.profile congruence distance
Smooth a non-positive definite correlation matrix to make it positive definite	cor.smooth cor.smoother
The sample size weighted correlation may be used in correlating aggregated data	cor.wt
Convert correlations to distances (necessary to do multidimensional scaling of correlation data)	cor2dist
Bootstrapped and normal confidence intervals for raw and composite correlations	cor.ci corCi
Find a Full Information Maximum Likelihood (FIML) correlation or covariance matrix from a data matrix with missing data	corFiml
Create an image plot for a correlation or factor matrix	cor.plot cor.plot.upperLowerCi corPlot corPlotUpperLowerCi
Find dis-attenuated correlations given correlations and reliabilities	correct.cor
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal.	cortest cortest.jennrich cortest.mat cortest.normal
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame.	corInfo corr.p corr.test corTest
Bartlett's test that a correlation matrix is an identity matrix	cortest.bartlett
Functions for analysis of circadian or diurnal data	circadian.cor circadian.F circadian.linear.cor circadian.mean circadian.phase circadian.reliability circadian.sd circadian.stats circular.cor circular.mean cosinor cosinor.period cosinor.plot
Simulate the C(ues) T(endency) A(ction) model of motivation	cta cta.15
Create a 'violin plot' or density plot of the distribution of a set of variables	densityBy violin violinBy
Basic descriptive statistics useful for psychometrics	describe describeData describeFast
Basic summary statistics by group	describe.by describeBy
Helper functions for drawing path model diagrams	dia.arrow dia.cone dia.curve dia.curved.arrow dia.ellipse dia.ellipse1 dia.rect dia.self dia.shape dia.triangle diagram multi.arrow multi.curved.arrow multi.rect multi.self
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation	draw.cor draw.tetra
Create dummy coded variables	dummy.code
8 cognitive variables used by Dwyer for an example.	Dwyer
Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings	eigen.loadings
Plot data and 1 and 2 sigma correlation ellipses	ellipses minkowski
Plot means and confidence intervals	error.bars error.bars.tab
Plot means and confidence intervals for multiple groups	error.bars.by
Plot x and y error bars	error.crosses
Show a dot.chart with error bars for different groups or variables	error.dots
Two way plots of means, error bars, and sample sizes	errorCircles
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques	cancorDiagram esem esem.diagram esemDiagram interbattery
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood	fa fa.pooled fa.sapa fac
Graph factor loading matrices	extension.diagram fa.diagram fa.graph fa.rgraph het.diagram
Apply Dwyer's factor extension to find factor loadings for extended variables	fa.extend fa.extension faReg faRegression
A set of functions for factorial and empirical scale construction	fa.lookup item.lookup itemSort keys.lookup lmCorLookup lookup lookupFromKeys lookupItems
Multi level (hierarchical) factor analysis	fa.multi fa.multi.diagram
Scree plots of data or correlation matrix compared to random ``parallel" matrices	fa.parallel fa.parallel.poly paSelect plot.poly.parallel
Deprecated Exploratory Factor analysis functions. Please use fa	fa.poly factor.minres factor.pa factor.wls
A first approximation to Random Effects Exploratory Factor Analysis	fa.random
Sort factor analysis or principal components analysis loadings	fa.organize fa.sort
Correlations between two factor analysis solutions	faCor
Coefficient of factor congruence	fa.congruence factor.congruence
How well does the factor model fit a correlation matrix. Part of the VSS package	factor.fit
Find R = F F' + U2 is the basic factor model	factor.model
R* = R- F F'	factor.residuals
``Hand" rotate a factor loading matrix	factor.rotate
Various ways to estimate factor scores for the factor analysis model	factor.scores
Find various goodness of fit statistics for factor analysis and principal components	fa.stats factor.stats
Extract cluster definitions from factor loadings	factor2cluster
Multiple rotations of factor loadings to find local minima	faRotations
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals	chi2r cor2cov fisherz fisherz2r g2r r.con r2c r2chi r2p r2t t2r
Parse and extend formula input from a model and return the DV(s), IV(s), and associated terms.	fparse lavParse
Factor Score Indeterminacy estimates )	fsi
Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010)	Garcia GSBE protest
Find the geometric mean of a vector or columns of a data.frame.	geometric.mean
Find the greatest lower bound to reliability.	glb.algebraic
Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.	Gleser
Example data set from Gorsuch (1997) for an example factor extension.	Gorsuch
Six data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt	Harman Harman.5 Harman.8 Harman.Burt Harman.Holzinger Harman.political Harman_5
Find the harmonic mean of a vector, matrix, or columns of a data.frame	harmonic.mean
Combine calls to head and tail	headTail headtail quickView topBottom
Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss)	ICC
iclust: Item Cluster Analysis - Hierarchical cluster analysis using psychometric principles	ICLUST iclust
Function to form hierarchical cluster analysis of items	ICLUST.cluster
Draw an ICLUST hierarchical cluster structure diagram	ICLUST.diagram iclust.diagram
create control code for ICLUST graphical output	ICLUST.graph iclust.graph
Draw an ICLUST graph using the Rgraphviz package	ICLUST.rgraph
Sort items by absolute size of cluster loadings	ICLUST.sort iclust.sort
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame	interp.boxplot interp.median interp.q interp.qplot.by interp.quantiles interp.quart interp.quartiles interp.values
Item Response Theory estimate of theta (ability) using a Rasch (like) model	irt.0p irt.1p irt.2p irt.person.rasch
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations	fa2irt irt.fa irt.select
Simple function to estimate item difficulties using IRT concepts	irt.discrim irt.item.diff.rasch
Plot probability of multiple choice responses as a function of a latent trait	irt.responses
Apply the Kaiser normalization when rotating factors	kaiser
Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy	KMO
Multiple Regression, Canonical and Set Correlation from matrix or raw input	crossValidation crossValidationBoot lmCor lmCor.diagram lmDiagram mat.regress matPlot matReg set.cor setCor
Logistic transform from x to p and logit transform from p to x	logistic logistic.grm logit
Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the other	lowerUpper
Create a keys matrix for use by score.items or cluster.cor	keys2list make.keys makePositiveKeys selectFromKeys
"Manhattan" plots of correlations with a set of criteria.	manhattan
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame	kurtosi mardia skew
Sort the elements of a correlation matrix to reflect factor loadings	mat.sort matSort
A function to add two vectors or matrices	%+% matrix.addition
Estimate and display direct and indirect effects of mediators and moderator in path models	mediate mediate.diagram moderate.diagram
Find correlations for mixtures of continuous, polytomous, and dichotomous variables	mixed.cor mixedCor
Find von Neuman's Mean Square of Successive Differences	autoR mssd rmssd
Multiple histograms with density and normal fits on one page	histBy histo.density multi.hist
Find and plot various reliability/gneralizability coefficients for multilevel data	mlArrange mlPlot mlr multilevel.reliability
Calculate McDonald's omega estimates of general and total factor saturation	directSl omega omegaDirect omegaFromSem omegah omegaSem
Graph hierarchical factor structures	omega.diagram omega.graph
Omega Statistics from a Factor Loading Matrix	omegaStats
Find and graph Mahalanobis squared distances to detect outliers	outlier
Find the probability of replication for an F, t, or r and estimate effect size	p.rep p.rep.f p.rep.r p.rep.t
Test the difference between (un)paired correlations	paired.r
SPLOM, histograms and correlations for a data matrix	pairs.panels panel.cor panel.cor.scale panel.ellipse panel.hist panel.hist.density panel.lm panel.lm.ellipse panel.smoother
Count number of pairwise cases for a data set with missing (NA) data and impute values.	count.pairwise pairwiseCount pairwiseCountBig pairwiseDescribe pairwiseImpute pairwisePlot pairwiseReport pairwiseSample pairwiseZero
Find miniscales (parcels) of size 2 or 3 from a set of items	keysort parcels
Find the partial correlations for a set (x) of variables with set (y) removed.	partial.r
Find the phi coefficient of correlation between two dichotomous variables	phi
A simple demonstration of the Pearson, phi, and polychoric corelation	phi.demo
Convert a phi coefficient to a tetrachoric correlation	phi2poly phi2tetra
Compute the Moore-Penrose Pseudo Inverse of a matrix	Pinv
Plotting functions for the psych package of class ``psych"	plot.irt plot.poly plot.psych plot.residuals
Convert Cartesian factor loadings into polar coordinates	polar
Phi or Yule coefficient matrix to polychoric coefficient matrix	phi2poly.matrix polychor.matrix Yule2phi.matrix Yule2poly.matrix
Prediction function for factor analysis, principal components (pca), bestScales	predict.psych
Find the predicted validities of a set of scales based on item statistics	item.validity predicted.validity validityItem
Principal components analysis (PCA)	pca principal
Print and summary functions for the psych class	print.psych summary.psych
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles.	bifactor biquartimin equamax faRotate Procrustes Promax target.rot TargetQ TargetT varimin vgQ.bimin vgQ.targetQ vgQ.varimin
Miscellaneous helper functions for the psych package	acs char2numeric cor2 cs fromTo isCorrelation isCovariance levels2numeric lowerCor lowerMat matMult misc nchar2numeric progressBar psych.misc reflect SAPAfy shannon tableF test.all vech
Tests of significance for correlations	r.test
Correct correlations for restriction of range. (Thorndike Case 2)	rangeCorrection
Reports 7 different estimates of scale reliabity including alpha, omega, split half	plot.reliability reliability
Function to convert scores to ``conventional " metrics	rescale
Extract residuals from various psych objects	resid.psych residuals.psych
Reverse the coding of selected items prior to scale analysis	reverse.code
Root Mean Squared Error of Approximation from chisq, df, and n	RMSEA
Three measures of the correlations between sets of variables	RV
3 Measures of ability: SATV, SATQ, ACT	sat.act
Test the adequacy of simple choice, logistic, or Thurstonian scaling.	scaling.fits
Draw a scatter plot with associated X and Y histograms, densities and correlation	scatter.hist scatterHist
Apply the Schmid Leiman transformation to a correlation matrix	schmid
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation	Chen Schmid schmid.leiman West
Score scales and find Cronbach's alpha as well as associated statistics	score.alpha
Score multiple choice items and provide basic test statistics	score.multiple.choice
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items	irt.se irt.stats.like irt.tau make.irt.stats score.irt score.irt.2 score.irt.poly scoreIrt scoreIrt.1pl scoreIrt.2pl
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations	removeMissing response.frequencies responseFrequency score.items scoreFast scoreItems scoreVeryFast
Find correlations of composite variables (corrected for overlap) from a larger matrix.	cluster.cor scoreBy scoreOverlap
Score items using regression or correlation based weights	scoreWtd
A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA.	scrub
Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases	SD
Functions to simulate psychological/psychometric data.	sim sim.minor sim.simplex
Simulate a 3 way balanced ANOVA or linear model, with or without repeated measures.	sim.anova
Simulate a congeneric data set with or without minor factors	congeneric.sim make.congeneric sim.congeneric
Create a population or sample correlation matrix, perhaps with hierarchical structure.	make.hierarchical sim.bonds sim.hierarchical
Functions to simulate psychological/psychometric data.	sim.irt sim.npl sim.npn sim.poly sim.poly.ideal sim.poly.ideal.npl sim.poly.ideal.npn sim.poly.mat sim.poly.npl sim.poly.npn sim.rasch
Generate simulated data structures for circumplex, spherical, or simple structure	circ.sim con2cat item.dichot item.sim sim.circ sim.dichot sim.item sim.spherical
Simulate multilevel data with specified within group and between group correlations	sim.multi sim.multilevel
Further functions to simulate psychological/psychometric data.	sim.general sim.omega sim.parallel
Create correlation matrices or data matrices with a particular measurement and structural model	sim.correlation sim.structural sim.structure simCor
create VSS like data	sim.VSS VSS.sim VSS.simulate
Simulations of circumplex and simple structure	circ.sim.plot circ.simulation simulation.circ
A small example data set taken from a larger data set	small.msq
Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrix	smc
Make "radar" or "spider" plots.	radar spider
Alternative estimates of test reliabiity	glb glb.fa guttman splitHalf tenberge
Find statistics (including correlations) within and between groups for basic multilevel analyses	faBy statsBy statsBy.boot statsBy.boot.summary
Draw a structural equation model specified by two measurement models and a structural model	lavaan.diagram sem.diagram sem.graph structure.diagram structure.graph structure.sem
Create factor model matrices from an input list	phi.list structure.list
Form a super matrix from two sub matrices.	super.matrix superCor superMatrix
Convert a table with counts to a matrix or data.frame representing those counts.	table2df table2matrix
Data set testing causal direction in presumed media influence	pmi Tal.Or Tal_Or tctg
A simple demonstration (and test) of various IRT scoring algorthims.	test.irt
Testing of functions in the psych package	test.psych
Find various test-retest statistics, including test, person and item reliability	testReliability testRetest
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input	biserial poly.mat polychoric polydi polyserial tetrachor tetrachoric
Thurstone Case V scaling	thurstone
Find the trace of a square matrix	tr
9 Cognitive variables discussed by Tucker and Lewis (1973)	Tucker
Several indices of the unidimensionality of a set of variables.	unidim
Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors.	eigenCi MAP nfactors VSS vss vssSelect
Compare real and random VSS solutions	VSS.parallel
Plot VSS fits	VSS.plot
Plot the successive eigen values for a scree test	scree VSS.scree
Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.frame	winsor winsor.mean winsor.means winsor.sd winsor.var
An example of the distinction between within group and between group correlations	withinBetween
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.	Yule Yule.inv Yule2phi Yule2poly Yule2tetra YuleBonett YuleCor

Package: psych 2.6.5

psych: Procedures for Psychological, Psychometric, and Personality Research

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