# psych v2.0.12

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## Procedures for Psychological, Psychometric, and Personality Research

A general purpose toolbox 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. Functions for simulating and testing particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, 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.

## Functions in psych

Name | Description | |

Gorsuch | Example data set from Gorsuch (1997) for an example factor extension. | |

Garcia | Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010) | |

Gleser | Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory. | |

AUC | Decision Theory measures of specificity, sensitivity, and d prime | |

ICC | Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss) | |

Harman | Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt | |

ICLUST.graph | create control code for ICLUST graphical output | |

00.psych | A package for personality, psychometric, and psychological research | |

ICLUST.cluster | Function to form hierarchical cluster analysis of items | |

ICLUST.sort | Sort items by absolute size of cluster loadings | |

KMO | Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy | |

iclust | iclust: Item Cluster Analysis -- Hierarchical cluster analysis using psychometric principles | |

ICLUST.rgraph | Draw an ICLUST graph using the Rgraphviz package | |

Schmid | 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation | |

SD | Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases | |

Promax | Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. | |

VSS | Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors. | |

VSS.parallel | Compare real and random VSS solutions | |

Pinv | Compute the Moore-Penrose Pseudo Inverse of a matrix | |

Tucker | 9 Cognitive variables discussed by Tucker and Lewis (1973) | |

Bechtoldt | Seven data sets showing a bifactor solution. | |

bfi | 25 Personality items representing 5 factors | |

bassAckward | The Bass-Ackward factoring algorithm discussed by Goldberg | |

anova.psych | Model comparison for regression, mediation, and factor analysis | |

bi.bars | Draw pairs of bargraphs based on two groups | |

VSS.plot | Plot VSS fits | |

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. | |

bestScales | A bootstrap aggregation function for choosing most predictive unit weighted items | |

bock | Bock and Liberman (1970) data set of 1000 observations of the LSAT | |

cattell | 12 cognitive variables from Cattell (1963) | |

VSS.scree | Plot the successive eigen values for a scree test | |

biplot.psych | Draw biplots of factor or component scores by factor or component loadings | |

alpha | Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6. | |

block.random | Create a block randomized structure for n independent variables | |

circ.tests | Apply four tests of circumplex versus simple structure | |

cluster.plot | Plot factor/cluster loadings and assign items to clusters by their highest loading. | |

scoreOverlap | Find correlations of composite variables (corrected for overlap) from a larger matrix. | |

cluster2keys | Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters. | |

cluster.fit | cluster Fit: fit of the cluster model to a correlation matrix | |

cor.smooth | Smooth a non-positive definite correlation matrix to make it positive definite | |

corr.test | Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame. | |

cluster.loadings | Find item by cluster correlations, corrected for overlap and reliability | |

cor.wt | The sample size weighted correlation may be used in correlating aggregated data | |

corCi | Bootstrapped and normal confidence intervals for raw and composite correlations | |

cor.plot | Create an image plot for a correlation or factor matrix | |

comorbidity | Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics | |

cohen.d | Find Cohen d and confidence intervals | |

correct.cor | Find dis-attenuated correlations given correlations and reliabilities | |

corFiml | Find a Full Information Maximum Likelihood (FIML) correlation or covariance matrix from a data matrix with missing data | |

cor2dist | Convert correlations to distances (necessary to do multidimensional scaling of correlation data) | |

cta | Simulate the C(ues) T(endency) A(ction) model of motivation | |

densityBy | Create a 'violin plot' or density plot of the distribution of a set of variables | |

cortest.mat | 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 | |

diagram | Helper functions for drawing path model diagrams | |

fa.poly | Deprecated Exploratory Factor analysis functions. Please use fa | |

describeBy | Basic summary statistics by group | |

describe | Basic descriptive statistics useful for psychometrics | |

ellipses | Plot data and 1 and 2 sigma correlation ellipses | |

error.dots | Show a dot.chart with error bars for different groups or variables | |

error.crosses | Plot x and y error bars | |

error.bars | Plot means and confidence intervals | |

Dwyer | 8 cognitive variables used by Dwyer for an example. | |

error.bars.by | Plot means and confidence intervals for multiple groups | |

eigen.loadings | Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings | |

errorCircles | Two way plots of means, error bars, and sample sizes | |

cosinor | Functions for analysis of circadian or diurnal data | |

pairwiseCount | Count number of pairwise cases for a data set with missing (NA) data and impute values. | |

draw.tetra | Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation | |

dummy.code | Create dummy coded variables | |

fa.multi | Multi level (hierarchical) factor analysis | |

fa.lookup | A set of functions for factorial and empirical scale construction | |

fa.diagram | Graph factor loading matrices | |

fa.parallel | Scree plots of data or correlation matrix compared to random ``parallel" matrices | |

faCor | Correlations between two factor analysis solutions | |

fa.random | A first approximation to Random Effects Exploratory Factor Analysis | |

factor.congruence | Coefficient of factor congruence | |

esem | Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques | |

factor.model | Find R = F F' + U2 is the basic factor model | |

factor.fit | How well does the factor model fit a correlation matrix. Part of the VSS package | |

fa | 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.extension | Apply Dwyer's factor extension to find factor loadings for extended variables | |

factor.stats | Find various goodness of fit statistics for factor analysis and principal components | |

factor.residuals | R* = R- F F' | |

headTail | Combine calls to head and tail | |

irt.item.diff.rasch | Simple function to estimate item difficulties using IRT concepts | |

fparse | Parse and exten formula input from a model and return the DV, IV, and associated terms. | |

glb.algebraic | Find the greatest lower bound to reliability. | |

fisherz | Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals | |

factor2cluster | Extract cluster definitions from factor loadings | |

geometric.mean | Find the geometric mean of a vector or columns of a data.frame. | |

cohen.kappa | Find Cohen's kappa and weighted kappa coefficients for correlation of two raters | |

manhattan | "Manhattan" plots of correlations with a set of criteria. | |

irt.1p | Item Response Theory estimate of theta (ability) using a Rasch (like) model | |

mat.sort | Sort the elements of a correlation matrix to reflect factor loadings | |

lowerUpper | Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the other | |

factor.rotate | ``Hand" rotate a factor loading matrix | |

mediate | Estimate and display direct and indirect effects of mediators and moderator in path models | |

iclust.diagram | Draw an ICLUST hierarchical cluster structure diagram | |

logistic | Logistic transform from x to p and logit transform from p to x | |

make.keys | Create a keys matrix for use by score.items or cluster.cor | |

harmonic.mean | Find the harmonic mean of a vector, matrix, or columns of a data.frame | |

matrix.addition | A function to add two vectors or matrices | |

splitHalf | Alternative estimates of test reliabiity | |

multilevel.reliability | Find and plot various reliability/gneralizability coefficients for multilevel data | |

omega | Calculate McDonald's omega estimates of general and total factor saturation | |

factor.scores | Various ways to estimate factor scores for the factor analysis model | |

omega.graph | Graph hierarchical factor structures | |

outlier | Find and graph Mahalanobis squared distances to detect outliers | |

kaiser | Apply the Kaiser normalization when rotating factors | |

irt.responses | Plot probability of multiple choice responses as a function of a latent trait | |

plot.psych | Plotting functions for the psych package of class ``psych" | |

interp.median | Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame | |

psych.misc | Miscellaneous helper functions for the psych package | |

p.rep | 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 | |

irt.fa | Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations | |

phi.demo | A simple demonstration of the Pearson, phi, and polychoric corelation | |

phi2tetra | Convert a phi coefficient to a tetrachoric correlation | |

mixedCor | Find correlations for mixtures of continuous, polytomous, and dichotomous variables | |

predict.psych | Prediction function for factor analysis, principal components (pca), bestScales | |

polychor.matrix | Phi or Yule coefficient matrix to polychoric coefficient matrix | |

polar | Convert Cartesian factor loadings into polar coordinates | |

sat.act | 3 Measures of ability: SATV, SATQ, ACT | |

reverse.code | Reverse the coding of selected items prior to scale analysis | |

scaling.fits | Test the adequacy of simple choice, logistic, or Thurstonian scaling. | |

scatterHist | Draw a scatter plot with associated X and Y histograms, densities and correlation | |

print.psych | Print and summary functions for the psych class | |

partial.r | Find the partial correlations for a set (x) of variables with set (y) removed. | |

principal | Principal components analysis (PCA) | |

parcels | Find miniscales (parcels) of size 2 or 3 from a set of items | |

rangeCorrection | Correct correlations for restriction of range. (Thorndike Case 2) | |

r.test | Tests of significance for correlations | |

phi | Find the phi coefficient of correlation between two dichotomous variables | |

residuals.psych | Extract residuals from various psych objects | |

multi.hist | Multiple histograms with density and normal fits on one page | |

mssd | Find von Neuman's Mean Square of Successive Differences | |

rescale | Function to convert scores to ``conventional " metrics | |

score.multiple.choice | Score multiple choice items and provide basic test statistics | |

scrub | A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA. | |

setCor | Multiple Regression and Set Correlation from matrix or raw input | |

schmid | Apply the Schmid Leiman transformation to a correlation matrix | |

score.alpha | Score scales and find Cronbach's alpha as well as associated statistics | |

scoreWtd | Score items using regression or correlation based weights | |

sim | Functions to simulate psychological/psychometric data. | |

scoreIrt | 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 | |

sim.VSS | create VSS like data | |

simulation.circ | Simulations of circumplex and simple structure | |

sim.structure | Create correlation matrices or data matrices with a particular measurement and structural model | |

sim.multilevel | Simulate multilevel data with specified within group and between group correlations | |

sim.anova | Simulate a 3 way balanced ANOVA or linear model, with or without repeated measures. | |

smc | Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrix | |

Spengler | Project Talent data set from Marion Spengler and Rodica Damian | |

mardia | Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame | |

sim.congeneric | Simulate a congeneric data set | |

sim.hierarchical | Create a population or sample correlation matrix, perhaps with hierarchical structure. | |

sim.item | Generate simulated data structures for circumplex, spherical, or simple structure | |

test.psych | Testing of functions in the psych package | |

Tal_Or | Data set testing causal direction in presumed media influence | |

test.irt | A simple demonstration (and test) of various IRT scoring algorthims. | |

testRetest | Find various test-retest statistics, including test, person and item reliability | |

statsBy | Find statistics (including correlations) within and between groups for basic multilevel analyses | |

structure.list | Create factor model matrices from an input list | |

structure.diagram | Draw a structural equation model specified by two measurement models and a structural model | |

spider | Make "radar" or "spider" plots. | |

superMatrix | Form a super matrix from two sub matrices. | |

table2matrix | Convert a table with counts to a matrix or data.frame representing those counts. | |

unidim | Several indices of the unidimensionality of a set of variables. | |

withinBetween | An example of the distinction between within group and between group correlations | |

tr | Find the trace of a square matrix | |

winsor | Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.frame | |

tetrachoric | Tetrachoric, polychoric, biserial and polyserial correlations from various types of input | |

thurstone | Thurstone Case V scaling | |

No Results! |

## Vignettes of psych

Name | ||

intro.Rnw | ||

overview.Rnw | ||

No Results! |

## Last month downloads

## Details

Date | 2020-12-14 |

License | GPL (>= 2) |

LazyData | yes |

ByteCompile | TRUE |

URL | https://personality-project.org/r/psych/ https://personality-project.org/r/psych-manual.pdf |

NeedsCompilation | no |

Packaged | 2020-12-16 00:46:41 UTC; WR |

Repository | CRAN |

Date/Publication | 2020-12-16 16:10:03 UTC |

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