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GPL (>= 2)
September 22nd, 2021
Functions in psych (2.1.9)
Decision Theory measures of specificity, sensitivity, and d prime
Data from Gruber et al, 2020, Study 2: Gender Related Attributes Survey
Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss)
Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
Example data set from Gorsuch (1997) for an example factor extension.
Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010)
create control code for ICLUST graphical output
Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.
A package for personality, psychometric, and psychological research
Function to form hierarchical cluster analysis of items
iclust: Item Cluster Analysis -- Hierarchical cluster analysis using psychometric principles
Sort items by absolute size of cluster loadings
Draw an ICLUST graph using the Rgraphviz package
Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy
Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6.
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles.
Compute the Moore-Penrose Pseudo Inverse of a matrix
Model comparison for regression, mediation, and factor analysis
Draw pairs of bargraphs based on two groups
25 Personality items representing 5 factors
A bootstrap aggregation function for choosing most predictive unit weighted items
Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors.
The Bass-Ackward factoring algorithm discussed by Goldberg
Plot VSS fits
9 Cognitive variables discussed by Tucker and Lewis (1973)
12 cognitive variables from Cattell (1963)
Find item by cluster correlations, corrected for overlap and reliability
Create a block randomized structure for n independent variables
Apply four tests of circumplex versus simple structure
Compare real and random VSS solutions
Plot factor/cluster loadings and assign items to clusters by their highest loading.
Seven data sets showing a bifactor solution.
Draw biplots of factor or component scores by factor or component loadings
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics
Bootstrapped and normal confidence intervals for raw and composite correlations
Create an image plot for a correlation or factor matrix
Smooth a non-positive definite correlation matrix to make it positive definite
Convert correlations to distances (necessary to do multidimensional scaling of correlation data)
The sample size weighted correlation may be used in correlating aggregated data
Plot the successive eigen values for a scree test
Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases
Find correlations of composite variables (corrected for overlap) from a larger matrix.
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
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.
Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters.
Find Cohen d and confidence intervals
cluster Fit: fit of the cluster model to a correlation matrix
Bock and Liberman (1970) data set of 1000 observations of the LSAT
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame.
Find a Full Information Maximum Likelihood (FIML) correlation or covariance matrix from a data matrix with missing data
Count number of pairwise cases for a data set with missing (NA) data and impute values.
Simulate the C(ues) T(endency) A(ction) model of motivation
Find dis-attenuated correlations given correlations and reliabilities
Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal.
Functions for analysis of circadian or diurnal data
Basic descriptive statistics useful for psychometrics
Deprecated Exploratory Factor analysis functions. Please use fa
Bartlett's test that a correlation matrix is an identity matrix
Create a 'violin plot' or density plot of the distribution of a set of variables
Plot data and 1 and 2 sigma correlation ellipses
Basic summary statistics by group
Create dummy coded variables
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation
Helper functions for drawing path model diagrams
Plot means and confidence intervals
Two way plots of means, error bars, and sample sizes
Plot means and confidence intervals for multiple groups
Plot x and y error bars
8 cognitive variables used by Dwyer for an example.
A set of functions for factorial and empirical scale construction
Apply Dwyer's factor extension to find factor loadings for extended variables
Sort factor analysis or principal components analysis loadings
Correlations between two factor analysis solutions
``Hand" rotate a factor loading matrix
R* = R- F F'
Show a dot.chart with error bars for different groups or variables
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques
How well does the factor model fit a correlation matrix. Part of the VSS package
Find R = F F' + U2 is the basic factor model
Coefficient of factor congruence
Scree plots of data or correlation matrix compared to random ``parallel" matrices
Multi level (hierarchical) factor analysis
A first approximation to Random Effects Exploratory Factor Analysis
Draw an ICLUST hierarchical cluster structure diagram
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals
Graph factor loading matrices
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood
Extract cluster definitions from factor loadings
Find the greatest lower bound to reliability.
Sort the elements of a correlation matrix to reflect factor loadings
Find various goodness of fit statistics for factor analysis and principal components
Parse and exten formula input from a model and return the DV, IV, and associated terms.
Find the geometric mean of a vector or columns of a data.frame.
Alternative estimates of test reliabiity
Various ways to estimate factor scores for the factor analysis model
Logistic transform from x to p and logit transform from p to x
Combine calls to head and tail
Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the other
Find the harmonic mean of a vector, matrix, or columns of a data.frame
Find Cohen's kappa and weighted kappa coefficients for correlation of two raters
Apply the Kaiser normalization when rotating factors
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations
Calculate McDonald's omega estimates of general and total factor saturation
Graph hierarchical factor structures
Find miniscales (parcels) of size 2 or 3 from a set of items
Convert a phi coefficient to a tetrachoric correlation
A function to add two vectors or matrices
Estimate and display direct and indirect effects of mediators and moderator in path models
Plotting functions for the psych package of class ``psych"
Miscellaneous helper functions for the psych package
Find the partial correlations for a set (x) of variables with set (y) removed.
Item Response Theory estimate of theta (ability) using a Rasch (like) model
Plot probability of multiple choice responses as a function of a latent trait
Simple function to estimate item difficulties using IRT concepts
Find and graph Mahalanobis squared distances to detect outliers
Find correlations for mixtures of continuous, polytomous, and dichotomous variables
SPLOM, histograms and correlations for a data matrix
Create a keys matrix for use by score.items or cluster.cor
Test the difference between (un)paired correlations
Find the phi coefficient of correlation between two dichotomous variables
"Manhattan" plots of correlations with a set of criteria.
Find von Neuman's Mean Square of Successive Differences
Multiple histograms with density and normal fits on one page
Find the predicted validities of a set of scales based on item statistics
A simple demonstration of the Pearson, phi, and polychoric corelation
Prediction function for factor analysis, principal components (pca), bestScales
Find the probability of replication for an F, t, or r and estimate effect size
Convert Cartesian factor loadings into polar coordinates
Extract residuals from various psych objects
Tests of significance for correlations
Phi or Yule coefficient matrix to polychoric coefficient matrix
Correct correlations for restriction of range. (Thorndike Case 2)
Reverse the coding of selected items prior to scale analysis
Score multiple choice items and provide basic test statistics
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations
Score scales and find Cronbach's alpha as well as associated statistics
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items
Apply the Schmid Leiman transformation to a correlation matrix
Draw a scatter plot with associated X and Y histograms, densities and correlation
Score items using regression or correlation based weights
Print and summary functions for the psych class
A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA.
Principal components analysis (PCA)
Reports 7 different estimates of scale reliabity including alpha, omega, split half
Function to convert scores to ``conventional " metrics
Test the adequacy of simple choice, logistic, or Thurstonian scaling.
3 Measures of ability: SATV, SATQ, ACT
Find and plot various reliability/gneralizability coefficients for multilevel data
Multiple Regression and Set Correlation from matrix or raw input
Functions to simulate psychological/psychometric data.
Simulate a congeneric data set
Create a population or sample correlation matrix, perhaps with hierarchical structure.
Generate simulated data structures for circumplex, spherical, or simple structure
Functions to simulate psychological/psychometric data.
Further functions to simulate psychological/psychometric data.
Make "radar" or "spider" plots.
Simulate multilevel data with specified within group and between group correlations
Simulations of circumplex and simple structure
Project Talent data set from Marion Spengler and Rodica Damian
Create correlation matrices or data matrices with a particular measurement and structural model
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.
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame
Create factor model matrices from an input list
Form a super matrix from two sub matrices.
Find the trace of a square matrix
Find statistics (including correlations) within and between groups for basic multilevel analyses
Several indices of the unidimensionality of a set of variables.
create VSS like data
Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.frame
Thurstone Case V scaling
A simple demonstration (and test) of various IRT scoring algorthims.
Find various test-retest statistics, including test, person and item reliability
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input
Draw a structural equation model specified by two measurement models and a structural model
Testing of functions in the psych package
Data set testing causal direction in presumed media influence
Convert a table with counts to a matrix or data.frame representing those counts.
An example of the distinction between within group and between group correlations