# psych v1.7.8

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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 <http://personality-project.org/r> web page.

## Functions in psych

Name | Description | |

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

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

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

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

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

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

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

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

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

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

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 | |

Schutz | The Schutz correlation matrix example from Shapiro and ten Berge | |

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

bestScales | A set of functions for factorial and empirical scale construction | |

bfi | 25 Personality items representing 5 factors | |

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

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

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

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

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

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

affect | Two data sets of affect and arousal scores as a function of personality and movie conditions | |

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

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. | |

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

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

blant | A 29 x 29 matrix that produces weird factor analytic results | |

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

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

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

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

VSS.plot | Plot VSS fits | |

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

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. | |

burt | 11 emotional variables from Burt (1915) | |

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

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

ability | 16 ability items scored as correct or incorrect. | |

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

blot | Bond's Logical Operations Test -- BLOT | |

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

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

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

cor.smooth | 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 | |

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

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

cushny | A data set from Cushny and Peebles (1905) on the effect of three drugs on hours of sleep, used by Student (1908) | |

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

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

cubits | Galton's example of the relationship between height and 'cubit' or forearm length | |

dfOrder | Sort (order) a dataframe or matrix by multiple columns | |

diagram | Helper functions for drawing path model diagrams | |

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

epi | Eysenck Personality Inventory (EPI) data for 3570 participants | |

cities | Distances between 11 US cities | |

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

cor.ci | Bootstrapped confidence intervals for raw and composite correlations | |

epi.bfi | 13 personality scales from the Eysenck Personality Inventory and Big 5 inventory | |

error.bars | Plot means and confidence intervals | |

fa.sort | Sort factor analysis or principal components analysis loadings | |

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

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

factor2cluster | Extract cluster definitions from factor loadings | |

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

iqitems | 16 multiple choice IQ items | |

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

count.pairwise | Count number of pairwise cases for a data set with missing (NA) data. | |

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

dummy.code | Create dummy coded variables | |

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

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

msq | 75 mood items from the Motivational State Questionnaire for 3896 participants | |

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

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

cortest.bartlett | Bartlett's test that a correlation matrix is an identity matrix | |

cortest.mat | Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal. | |

describeBy | Basic summary statistics by group | |

describe | Basic descriptive statistics useful for psychometrics | |

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

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

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

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

fa | Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood | |

fa.diagram | Graph factor loading matrices | |

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

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

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

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

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

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

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

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

peas | Galton`s Peas | |

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

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

splitHalf | Alternative estimates of test reliabiity | |

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

headTail | Combine calls to head and tail | |

heights | A data.frame of the Galton (1888) height and cubit data set. | |

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

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

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

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

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

omega.graph | Graph hierarchical factor structures | |

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

polar | Convert Cartesian factor loadings into polar coordinates | |

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

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

read.file | Shortcuts for reading from the clipboard or a file | |

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

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

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

df2latex | Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table | |

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

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

factor.congruence | Coefficient of factor congruence | |

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

income | US family income from US census 2008 | |

kaiser | Apply the Kaiser normalization when rotating factors | |

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

neo | NEO correlation matrix from the NEO_PI_R manual | |

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

galton | Galton's Mid parent child height data | |

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

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

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

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

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

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 | |

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

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

pairs.panels | SPLOM, histograms and correlations for a data matrix | |

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

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

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

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

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

r.test | Tests of significance for correlations | |

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

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

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

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

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

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

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

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

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

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

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

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

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

thurstone | Thurstone Case V scaling | |

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

statsBy | 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 | |

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

predict.psych | Prediction function for factor analysis or principal components | |

principal | Principal components analysis (PCA) | |

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. | |

vegetables | Paired comparison of preferences for 9 vegetables | |

sim.congeneric | Simulate a congeneric data set | |

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

spi | A sample from the SAPA Personality Inventory including an item dictionary and scoring keys. | |

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

tr | Find the trace of a square matrix | |

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

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 | |

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

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

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

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

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 | |

sim.VSS | create VSS like data | |

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

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

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

No Results! |

## Vignettes of psych

Name | ||

intro.Rnw | ||

overview.Rnw | ||

psych_for_sem.Rnw | ||

No Results! |

## Last month downloads

## Details

Date | 2017-08-17 |

License | GPL (>= 2) |

LazyData | true |

ByteCompile | TRUE |

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

NeedsCompilation | no |

Packaged | 2017-09-08 23:08:04 UTC; WR |

Repository | CRAN |

Date/Publication | 2017-09-09 14:12:52 UTC |

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