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psych (version 1.6.6)

Procedures for Psychological, Psychometric, and Personality Research

Description

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 multi-levels include within and between group statistics, including correlations and factor analysis. Functions for simulating 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 psychometrics as well as publications in personality research. For more information, see the personality-project.org/r webpage.

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Install

install.packages('psych')

Monthly Downloads

193,272

Version

1.6.6

License

GPL (>= 2)

Maintainer

William Revelle

Last Published

June 28th, 2016

Functions in psych (1.6.6)

Draw pairs of bargraphs based on two groups

Seven data sets showing a bifactor solution.

Distances between 11 US cities

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

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

Create dummy coded variables

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

8 cognitive variables used by Dwyer for an example.

Plot means and confidence intervals for multiple groups

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

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

factor.residuals

create control code for ICLUST graphical output

Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations

16 multiple choice IQ items

75 mood items from the Motivational State Questionnaire for 3896 participants

Find von Neuman's Mean Square of Successive Differences

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

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

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

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

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

Simulate a congeneric data set

sim.hierarchical

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

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

Thurstone Case V scaling

Plot the successive eigen values for a scree test

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

Draw biplots of factor or component scores by factor or component loadings

11 emotional variables from Burt (1915)

Apply four tests of circumplex versus simple structure

Create a block randomized structure for n independent variables

The sample size weighted correlation may be used in correlating aggregated data

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

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

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

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

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

Extract cluster definitions from factor loadings

Alternative estimates of test reliabiity

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

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

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

Sort items by absolute size of cluster loadings

Draw an ICLUST graph using the Rgraphviz package

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

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

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

Find the phi coefficient of correlation between two dichotomous variables

Convert a phi coefficient to a tetrachoric correlation

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

Tests of significance for correlations

Simulate multilevel data with specified within group and between group correlations

Generate simulated data structures for circumplex, spherical, or simple structure

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

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

25 Personality items representing 5 factors

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

Sort factor analysis or principal components analysis loadings

Galton's Mid parent child height data

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

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

US family income from US census 2008

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

Bond's Logical Operations Test -- BLOT

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

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

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

Functions for analysis of circadian or diurnal data

Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation

Helper functions for drawing path model diagrams

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

Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy

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

Multiple histograms with density and normal fits on one page

NEO correlation matrix from the NEO_PI_R manual

Principal components analysis (PCA)

Print and summary functions for the psych class

Function to convert scores to ``conventional " metrics

residuals.psych

Extract residuals from various psych objects

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

Set Correlation and Multiple Regression from matrix or raw input

Plot data and 1 and 2 sigma correlation ellipses

5 socio-economic variables from Harman (1967)

Correlations of eight physical variables (from Harman, 1966)

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

Harman.political

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

Apply the Kaiser normalization when rotating factors

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

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

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

Find and graph Mahalanobis squared distances to detect outliers

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

polychor.matrix

Phi or Yule coefficient matrix to polychoric coefficient matrix

Prediction function for factor analysis or principal components

Reverse the coding of selected items prior to scale analysis

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

3 Measures of ability: SATV, SATQ, ACT

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

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

Create correlation matrices or data matrices with a particular measurement and structural model

create VSS like data

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

Testing of functions in the psych package

Make "radar" or "spider" plots.

9 Cognitive variables discussed by Tucker and Lewis (1973)

Paired comparison of preferences for 9 vegetables

Compare real and random VSS solutions

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

Bootstrapped confidence intervals for raw and composite correlations

Create an image plot for a correlation or factor matrix

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

Smooth a non-positive definite correlation matrix to make it positive definite

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

Eysenck Personality Inventory (EPI) data for 3570 participants

13 personality scales from the Eysenck Personality Inventory and Big 5 inventory

``Hand" rotate a factor loading matrix

Various ways to estimate factor scores for the factor analysis model

Multi level (hierarchical) factor analysis

Fisher r to z and z to r and confidence intervals

Function to form hierarchical cluster analysis of items

irt.item.diff.rasch

Simple function to estimate item difficulties using IRT concepts

Draw an ICLUST hierarchical cluster structure diagram

Plot probability of multiple choice responses as a function of a latent trait

Sort the elements of a correlation matrix to reflect factor loadings

matrix.addition

A function to add two vectors or matrices

Graph hierarchical factor structures

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

A simple demonstration of the Pearson, phi, and polychoric corelation

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

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

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

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

structure.diagram

Draw a structural equation model specified by two measurement models and a structural model

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.

16 ability items scored as correct or incorrect.

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

cluster.loadings

Find item by cluster correlations, corrected for overlap and reliability

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

Find dis-attenuated correlations given correlations and reliabilities

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

cortest.bartlett

Bartlett's test that a correlation matrix is an identity matrix

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

Plot x and y error bars

factor.congruence

Coefficient of factor congruence

Graph factor loading matrices

Find the greatest lower bound to reliability.

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

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

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

Combine calls to head and tail

Test the difference between (un)paired correlations

SPLOM, histograms and correlations for a data matrix

rangeCorrection

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

Convert Cartesian factor loadings into polar coordinates

Plotting functions for the psych package of class ``psych"

shortcut for reading from the clipboard

Create factor model matrices from an input list

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

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

Form a super matrix from two sub matrices.