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