# psych v1.6.12

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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 personality-project.org/r web page.

## Functions in psych

Name | Description | |

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

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

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

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. | |

bfi | 25 Personality items representing 5 factors | |

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

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

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

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

cities | Distances between 11 US cities | |

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 | |

error.bars | Plot means and confidence intervals | |

describeBy | Basic summary statistics by group | |

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

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

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

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

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

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

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

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

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

factor.congruence | Coefficient of factor congruence | |

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

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

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

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

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

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

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

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

diagram | Helper functions for drawing path model diagrams | |

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

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

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

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

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

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

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

headTail | Combine calls to head and tail | |

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

factor2cluster | Extract cluster definitions from factor loadings | |

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

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

kaiser | Apply the Kaiser normalization when rotating factors | |

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

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

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

income | US family income from US census 2008 | |

r.test | Tests of significance for correlations | |

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

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

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

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

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

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

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

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

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

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

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

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

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

polar | Convert Cartesian factor loadings into polar coordinates | |

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

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

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

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

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

sim.congeneric | Simulate a congeneric data set | |

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

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

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

vegetables | Paired comparison of preferences for 9 vegetables | |

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

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

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

p.rep | Find the probability of replication for an F, t, or r and estimate effect size | |

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

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

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

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

scatter.hist | Draw a scatter plot with associated X and Y histograms, densitie and correlation | |

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

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

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 | |

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

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

tr | Find the trace of a square matrix | |

Harman.political | Eight political variables used by Harman (1967) as example 8.17 | |

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

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

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

omega.graph | Graph hierarchical factor structures | |

fa.diagram | Graph factor loading matrices | |

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

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

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

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

iqitems | 16 multiple choice IQ items | |

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

neo | NEO correlation matrix from the NEO_PI_R manual | |

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

peas | Galton`s Peas | |

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

principal | Principal components analysis (PCA) | |

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. | |

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

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

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

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

scoreIrt | Find Item Response Theory (IRT) based scores for dichotomous or polytomous items | |

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

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

VSS.plot | Plot VSS fits | |

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

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

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

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

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

dummy.code | Create dummy coded variables | |

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

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

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

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

Harman.8 | Correlations of eight physical variables (from Harman, 1966) | |

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

Harman.5 | 5 socio-economic variables from Harman (1967) | |

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

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

mixed.cor | Find correlations for mixtures of continuous, polytomous, and dichotomous variables | |

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

paired.r | Test the difference between (un)paired correlations | |

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

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

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

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

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

scoreItems | 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 | |

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

sim.VSS | create VSS like data | |

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

thurstone | Thurstone Case V scaling | |

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

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

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## Last month downloads

## Details

Date | 2016-12-31 |

License | GPL (>= 2) |

LazyData | true |

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

NeedsCompilation | no |

Packaged | 2017-01-07 20:33:14 UTC; WR |

Repository | CRAN |

Date/Publication | 2017-01-08 12:02:16 |

imports | foreign , graphics , grDevices , methods , mnormt , parallel , stats |

suggests | GPArotation , graph , lavaan , Rcsdp , Rgraphviz , sem |

depends | R (>= 2.10) |

Contributors | William Revelle |

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