| bassAckward |
The Bass-Ackward factoring algorithm discussed by Goldberg |
| bassAckward.diagram |
The Bass-Ackward factoring algorithm discussed by Goldberg |
| Bechtoldt |
Seven data sets showing a bifactor solution. |
| Bechtoldt.1 |
Seven data sets showing a bifactor solution. |
| Bechtoldt.2 |
Seven data sets showing a bifactor solution. |
| bestItems |
A bootstrap aggregation function for choosing most predictive unit weighted items |
| bestScales |
A bootstrap aggregation function for choosing most predictive unit weighted items |
| bfi |
25 Personality items representing 5 factors |
| bfi.keys |
25 Personality items representing 5 factors |
| bi.bars |
Draw pairs of bargraphs based on two groups |
| bifactor |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| bigCor |
Find large correlation matrices by stitching together smaller ones found more rapidly |
| biplot.psych |
Draw biplots of factor or component scores by factor or component loadings |
| biquartimin |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| BISCUIT |
A bootstrap aggregation function for choosing most predictive unit weighted items |
| biscuit |
A bootstrap aggregation function for choosing most predictive unit weighted items |
| BISCWIT |
A bootstrap aggregation function for choosing most predictive unit weighted items |
| biscwit |
A bootstrap aggregation function for choosing most predictive unit weighted items |
| biserial |
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input |
| block.random |
Create a block randomized structure for n independent variables |
| bock |
Bock and Liberman (1970) data set of 1000 observations of the LSAT |
| bock.lsat |
Bock and Liberman (1970) data set of 1000 observations of the LSAT |
| bock.table |
Bock and Liberman (1970) data set of 1000 observations of the LSAT |
| cancorDiagram |
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques |
| cattell |
12 cognitive variables from Cattell (1963) |
| cd.validity |
Find Cohen d and confidence intervals |
| char2numeric |
Miscellaneous helper functions for the psych package |
| Chen |
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation |
| chi2r |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| circ.sim |
Generate simulated data structures for circumplex, spherical, or simple structure |
| circ.sim.plot |
Simulations of circumplex and simple structure |
| circ.simulation |
Simulations of circumplex and simple structure |
| circ.tests |
Apply four tests of circumplex versus simple structure |
| circadian.cor |
Functions for analysis of circadian or diurnal data |
| circadian.F |
Functions for analysis of circadian or diurnal data |
| circadian.linear.cor |
Functions for analysis of circadian or diurnal data |
| circadian.mean |
Functions for analysis of circadian or diurnal data |
| circadian.phase |
Functions for analysis of circadian or diurnal data |
| circadian.reliability |
Functions for analysis of circadian or diurnal data |
| circadian.sd |
Functions for analysis of circadian or diurnal data |
| circadian.stats |
Functions for analysis of circadian or diurnal data |
| circular.cor |
Functions for analysis of circadian or diurnal data |
| circular.mean |
Functions for analysis of circadian or diurnal data |
| cluster.cor |
Find correlations of composite variables (corrected for overlap) from a larger matrix. |
| 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. |
| cohen.d |
Find Cohen d and confidence intervals |
| cohen.d.by |
Find Cohen d and confidence intervals |
| cohen.d.ci |
Find Cohen d and confidence intervals |
| cohen.kappa |
Find Cohen's kappa and weighted kappa coefficients for correlation of two raters |
| cohen.profile |
Matrix and profile congruences and distances |
| comorbidity |
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics |
| con2cat |
Generate simulated data structures for circumplex, spherical, or simple structure |
| congeneric.sim |
Simulate a congeneric data set with or without minor factors |
| congruence |
Matrix and profile congruences and distances |
| cor.ci |
Bootstrapped and normal confidence intervals for raw and composite correlations |
| cor.plot |
Create an image plot for a correlation or factor matrix |
| cor.plot.upperLowerCi |
Create an image plot for a correlation or factor matrix |
| cor.smooth |
Smooth a non-positive definite correlation matrix to make it positive definite |
| cor.smoother |
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 |
| cor2 |
Miscellaneous helper functions for the psych package |
| cor2cov |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| cor2dist |
Convert correlations to distances (necessary to do multidimensional scaling of correlation data) |
| corCi |
Bootstrapped and normal confidence intervals for raw and composite correlations |
| corFiml |
Find a Full Information Maximum Likelihood (FIML) correlation or covariance matrix from a data matrix with missing data |
| corPlot |
Create an image plot for a correlation or factor matrix |
| corPlotUpperLowerCi |
Create an image plot for a correlation or factor matrix |
| corr.p |
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame. |
| corr.test |
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame. |
| correct.cor |
Find dis-attenuated correlations given correlations and reliabilities |
| corTest |
Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame. |
| cortest |
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 |
| cortest.jennrich |
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal. |
| cortest.mat |
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal. |
| cortest.normal |
Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal. |
| cosinor |
Functions for analysis of circadian or diurnal data |
| cosinor.period |
Functions for analysis of circadian or diurnal data |
| cosinor.plot |
Functions for analysis of circadian or diurnal data |
| count.pairwise |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| crossValidation |
Multiple Regression, Canonical and Set Correlation from matrix or raw input |
| crossValidationBoot |
Multiple Regression, Canonical and Set Correlation from matrix or raw input |
| cs |
Miscellaneous helper functions for the psych package |
| cta |
Simulate the C(ues) T(endency) A(ction) model of motivation |
| cta.15 |
Simulate the C(ues) T(endency) A(ction) model of motivation |
| d.ci |
Find Cohen d and confidence intervals |
| d.robust |
Find Cohen d and confidence intervals |
| d2CL |
Find Cohen d and confidence intervals |
| d2OVL |
Find Cohen d and confidence intervals |
| d2OVL2 |
Find Cohen d and confidence intervals |
| d2r |
Find Cohen d and confidence intervals |
| d2t |
Find Cohen d and confidence intervals |
| d2U3 |
Find Cohen d and confidence intervals |
| densityBy |
Create a 'violin plot' or density plot of the distribution of a set of variables |
| describe |
Basic descriptive statistics useful for psychometrics |
| describe.by |
Basic summary statistics by group |
| describeBy |
Basic summary statistics by group |
| describeData |
Basic descriptive statistics useful for psychometrics |
| describeFast |
Basic descriptive statistics useful for psychometrics |
| dia.arrow |
Helper functions for drawing path model diagrams |
| dia.cone |
Helper functions for drawing path model diagrams |
| dia.curve |
Helper functions for drawing path model diagrams |
| dia.curved.arrow |
Helper functions for drawing path model diagrams |
| dia.ellipse |
Helper functions for drawing path model diagrams |
| dia.ellipse1 |
Helper functions for drawing path model diagrams |
| dia.rect |
Helper functions for drawing path model diagrams |
| dia.self |
Helper functions for drawing path model diagrams |
| dia.shape |
Helper functions for drawing path model diagrams |
| dia.triangle |
Helper functions for drawing path model diagrams |
| diagram |
Helper functions for drawing path model diagrams |
| directSl |
Calculate McDonald's omega estimates of general and total factor saturation |
| distance |
Matrix and profile congruences and distances |
| draw.cor |
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation |
| draw.tetra |
Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation |
| dummy.code |
Create dummy coded variables |
| Dwyer |
8 cognitive variables used by Dwyer for an example. |
| fa |
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood |
| fa.congruence |
Coefficient of factor congruence |
| fa.diagram |
Graph factor loading matrices |
| fa.extend |
Apply Dwyer's factor extension to find factor loadings for extended variables |
| fa.extension |
Apply Dwyer's factor extension to find factor loadings for extended variables |
| fa.graph |
Graph factor loading matrices |
| fa.lookup |
A set of functions for factorial and empirical scale construction |
| fa.multi |
Multi level (hierarchical) factor analysis |
| fa.multi.diagram |
Multi level (hierarchical) factor analysis |
| fa.organize |
Sort factor analysis or principal components analysis loadings |
| fa.parallel |
Scree plots of data or correlation matrix compared to random "parallel" matrices |
| fa.parallel.poly |
Scree plots of data or correlation matrix compared to random "parallel" matrices |
| fa.plot |
Plot factor/cluster loadings and assign items to clusters by their highest loading. |
| fa.poly |
Deprecated Exploratory Factor analysis functions. Please use fa |
| fa.pooled |
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood |
| fa.random |
A first approximation to Random Effects Exploratory Factor Analysis |
| fa.rgraph |
Graph factor loading matrices |
| fa.sapa |
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.stats |
Find various goodness of fit statistics for factor analysis and principal components |
| fa2irt |
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations |
| faBy |
Find statistics (including correlations) within and between groups for basic multilevel analyses |
| fac |
Exploratory Factor analysis using MinRes (minimum residual) as well as EFA by Principal Axis, Weighted Least Squares or Maximum Likelihood |
| faCor |
Correlations between two factor analysis solutions |
| factor.congruence |
Coefficient of factor congruence |
| factor.fit |
How well does the factor model fit a correlation matrix. Part of the VSS package |
| factor.minres |
Deprecated Exploratory Factor analysis functions. Please use fa |
| factor.model |
Find R = F F' + U2 is the basic factor model |
| factor.pa |
Deprecated Exploratory Factor analysis functions. Please use fa |
| factor.plot |
Plot factor/cluster loadings and assign items to clusters by their highest loading. |
| factor.residuals |
R* = R- F F' |
| factor.rotate |
"Hand" rotate a factor loading matrix |
| factor.scores |
Various ways to estimate factor scores for the factor analysis model |
| factor.stats |
Find various goodness of fit statistics for factor analysis and principal components |
| factor.wls |
Deprecated Exploratory Factor analysis functions. Please use fa |
| factor2cluster |
Extract cluster definitions from factor loadings |
| faReg |
Apply Dwyer's factor extension to find factor loadings for extended variables |
| faRegression |
Apply Dwyer's factor extension to find factor loadings for extended variables |
| faRotate |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| faRotations |
Multiple rotations of factor loadings to find local minima |
| fisherz |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| fisherz2r |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| fparse |
Parse and exten formula input from a model and return the DV, IV, and associated terms. |
| fromTo |
Miscellaneous helper functions for the psych package |
| ICC |
Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss) |
| ICLUST |
iclust: Item Cluster Analysis - Hierarchical cluster analysis using psychometric principles |
| iclust |
iclust: Item Cluster Analysis - Hierarchical cluster analysis using psychometric principles |
| ICLUST.cluster |
Function to form hierarchical cluster analysis of items |
| ICLUST.diagram |
Draw an ICLUST hierarchical cluster structure diagram |
| iclust.diagram |
Draw an ICLUST hierarchical cluster structure diagram |
| ICLUST.graph |
create control code for ICLUST graphical output |
| iclust.graph |
create control code for ICLUST graphical output |
| ICLUST.rgraph |
Draw an ICLUST graph using the Rgraphviz package |
| ICLUST.sort |
Sort items by absolute size of cluster loadings |
| iclust.sort |
Sort items by absolute size of cluster loadings |
| interbattery |
Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques |
| interp.boxplot |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| interp.median |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| interp.q |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| interp.qplot.by |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| interp.quantiles |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| interp.quart |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| interp.quartiles |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| interp.values |
Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame |
| irt.0p |
Item Response Theory estimate of theta (ability) using a Rasch (like) model |
| irt.1p |
Item Response Theory estimate of theta (ability) using a Rasch (like) model |
| irt.2p |
Item Response Theory estimate of theta (ability) using a Rasch (like) model |
| irt.discrim |
Simple function to estimate item difficulties using IRT concepts |
| irt.fa |
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations |
| irt.item.diff.rasch |
Simple function to estimate item difficulties using IRT concepts |
| irt.person.rasch |
Item Response Theory estimate of theta (ability) using a Rasch (like) model |
| irt.responses |
Plot probability of multiple choice responses as a function of a latent trait |
| irt.se |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| irt.select |
Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations |
| irt.stats.like |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| irt.tau |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| isCorrelation |
Miscellaneous helper functions for the psych package |
| isCovariance |
Miscellaneous helper functions for the psych package |
| item.dichot |
Generate simulated data structures for circumplex, spherical, or simple structure |
| item.lookup |
A set of functions for factorial and empirical scale construction |
| item.sim |
Generate simulated data structures for circumplex, spherical, or simple structure |
| item.validity |
Find the predicted validities of a set of scales based on item statistics |
| itemSort |
A set of functions for factorial and empirical scale construction |
| m2d |
Find Cohen d and confidence intervals |
| m2t |
Find Cohen d and confidence intervals |
| make.congeneric |
Simulate a congeneric data set with or without minor factors |
| make.hierarchical |
Create a population or sample correlation matrix, perhaps with hierarchical structure. |
| make.irt.stats |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| make.keys |
Create a keys matrix for use by score.items or cluster.cor |
| makePositiveKeys |
Create a keys matrix for use by score.items or cluster.cor |
| manhattan |
"Manhattan" plots of correlations with a set of criteria. |
| MAP |
Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors. |
| mardia |
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame |
| mat.regress |
Multiple Regression, Canonical and Set Correlation from matrix or raw input |
| mat.sort |
Sort the elements of a correlation matrix to reflect factor loadings |
| matMult |
Miscellaneous helper functions for the psych package |
| matPlot |
Multiple Regression, Canonical and Set Correlation from matrix or raw input |
| matReg |
Multiple Regression, Canonical and Set Correlation from matrix or raw input |
| matrix.addition |
A function to add two vectors or matrices |
| matSort |
Sort the elements of a correlation matrix to reflect factor loadings |
| mediate |
Estimate and display direct and indirect effects of mediators and moderator in path models |
| mediate.diagram |
Estimate and display direct and indirect effects of mediators and moderator in path models |
| minkowski |
Plot data and 1 and 2 sigma correlation ellipses |
| misc |
Miscellaneous helper functions for the psych package |
| mixed.cor |
Find correlations for mixtures of continuous, polytomous, and dichotomous variables |
| mixedCor |
Find correlations for mixtures of continuous, polytomous, and dichotomous variables |
| mlArrange |
Find and plot various reliability/gneralizability coefficients for multilevel data |
| mlPlot |
Find and plot various reliability/gneralizability coefficients for multilevel data |
| mlr |
Find and plot various reliability/gneralizability coefficients for multilevel data |
| moderate.diagram |
Estimate and display direct and indirect effects of mediators and moderator in path models |
| mssd |
Find von Neuman's Mean Square of Successive Differences |
| multi.arrow |
Helper functions for drawing path model diagrams |
| multi.curved.arrow |
Helper functions for drawing path model diagrams |
| multi.hist |
Multiple histograms with density and normal fits on one page |
| multi.rect |
Helper functions for drawing path model diagrams |
| multi.self |
Helper functions for drawing path model diagrams |
| multilevel.reliability |
Find and plot various reliability/gneralizability coefficients for multilevel data |
| p.rep |
Find the probability of replication for an F, t, or r and estimate effect size |
| p.rep.f |
Find the probability of replication for an F, t, or r and estimate effect size |
| p.rep.r |
Find the probability of replication for an F, t, or r and estimate effect size |
| p.rep.t |
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 |
| pairwiseCount |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| pairwiseCountBig |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| pairwiseDescribe |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| pairwiseImpute |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| pairwisePlot |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| pairwiseReport |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| pairwiseSample |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| pairwiseZero |
Count number of pairwise cases for a data set with missing (NA) data and impute values. |
| panel.cor |
SPLOM, histograms and correlations for a data matrix |
| panel.cor.scale |
SPLOM, histograms and correlations for a data matrix |
| panel.ellipse |
SPLOM, histograms and correlations for a data matrix |
| panel.hist |
SPLOM, histograms and correlations for a data matrix |
| panel.hist.density |
SPLOM, histograms and correlations for a data matrix |
| panel.lm |
SPLOM, histograms and correlations for a data matrix |
| panel.lm.ellipse |
SPLOM, histograms and correlations for a data matrix |
| panel.smoother |
SPLOM, histograms and correlations for a data matrix |
| parcels |
Find miniscales (parcels) of size 2 or 3 from a set of items |
| partial.r |
Find the partial correlations for a set (x) of variables with set (y) removed. |
| paSelect |
Scree plots of data or correlation matrix compared to random "parallel" matrices |
| pca |
Principal components analysis (PCA) |
| phi |
Find the phi coefficient of correlation between two dichotomous variables |
| phi.demo |
A simple demonstration of the Pearson, phi, and polychoric corelation |
| phi.list |
Create factor model matrices from an input list |
| phi2poly |
Convert a phi coefficient to a tetrachoric correlation |
| phi2poly.matrix |
Phi or Yule coefficient matrix to polychoric coefficient matrix |
| phi2tetra |
Convert a phi coefficient to a tetrachoric correlation |
| Pinv |
Compute the Moore-Penrose Pseudo Inverse of a matrix |
| plot.irt |
Plotting functions for the psych package of class "psych" |
| plot.poly |
Plotting functions for the psych package of class "psych" |
| plot.poly.parallel |
Scree plots of data or correlation matrix compared to random "parallel" matrices |
| plot.psych |
Plotting functions for the psych package of class "psych" |
| plot.reliability |
Reports 7 different estimates of scale reliabity including alpha, omega, split half |
| plot.residuals |
Plotting functions for the psych package of class "psych" |
| pmi |
Data set testing causal direction in presumed media influence |
| polar |
Convert Cartesian factor loadings into polar coordinates |
| poly.mat |
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input |
| polychor.matrix |
Phi or Yule coefficient matrix to polychoric coefficient matrix |
| polychoric |
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input |
| polydi |
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input |
| polyserial |
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input |
| predict.psych |
Prediction function for factor analysis, principal components (pca), bestScales |
| predicted.validity |
Find the predicted validities of a set of scales based on item statistics |
| principal |
Principal components analysis (PCA) |
| print.psych |
Print and summary functions for the psych class |
| Procrustes |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| progressBar |
Miscellaneous helper functions for the psych package |
| Promax |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| protest |
Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010) |
| psych |
A package for personality, psychometric, and psychological research |
| psych.misc |
Miscellaneous helper functions for the psych package |
| r.con |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| r.test |
Tests of significance for correlations |
| r2c |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| r2chi |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| r2d |
Find Cohen d and confidence intervals |
| r2t |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| radar |
Make "radar" or "spider" plots. |
| rangeCorrection |
Correct correlations for restriction of range. (Thorndike Case 2) |
| reflect |
Miscellaneous helper functions for the psych package |
| Reise |
Seven data sets showing a bifactor solution. |
| reliability |
Reports 7 different estimates of scale reliabity including alpha, omega, split half |
| rescale |
Function to convert scores to "conventional " metrics |
| resid.psych |
Extract residuals from various psych objects |
| residuals.psych |
Extract residuals from various psych objects |
| response.frequencies |
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations |
| responseFrequency |
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations |
| reverse.code |
Reverse the coding of selected items prior to scale analysis |
| RMSEA |
Root Mean Squared Error of Approximation from chisq, df, and n |
| rmssd |
Find von Neuman's Mean Square of Successive Differences |
| SAPAfy |
Miscellaneous helper functions for the psych package |
| sat.act |
3 Measures of ability: SATV, SATQ, ACT |
| scaling.fits |
Test the adequacy of simple choice, logistic, or Thurstonian scaling. |
| scatter.hist |
Draw a scatter plot with associated X and Y histograms, densities and correlation |
| scatterHist |
Draw a scatter plot with associated X and Y histograms, densities and correlation |
| Schmid |
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation |
| schmid |
Apply the Schmid Leiman transformation to a correlation matrix |
| schmid.leiman |
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation |
| score.alpha |
Score scales and find Cronbach's alpha as well as associated statistics |
| score.irt |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| score.irt.2 |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| score.irt.poly |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| score.items |
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 |
| scoreBy |
Find correlations of composite variables (corrected for overlap) from a larger matrix. |
| scoreFast |
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations |
| scoreIrt |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| scoreIrt.1pl |
Find Item Response Theory (IRT) based scores for dichotomous or polytomous items |
| scoreIrt.2pl |
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 |
| scoreOverlap |
Find correlations of composite variables (corrected for overlap) from a larger matrix. |
| scoreVeryFast |
Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations |
| scoreWtd |
Score items using regression or correlation based weights |
| scree |
Plot the successive eigen values for a scree test |
| scrub |
A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA. |
| SD |
Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases |
| selectFromKeys |
Create a keys matrix for use by score.items or cluster.cor |
| sem.diagram |
Draw a structural equation model specified by two measurement models and a structural model |
| sem.graph |
Draw a structural equation model specified by two measurement models and a structural model |
| Sensitivity |
Decision Theory measures of specificity, sensitivity, and d prime |
| set.cor |
Multiple Regression, Canonical and Set Correlation from matrix or raw input |
| setCor |
Multiple Regression, Canonical and Set Correlation from matrix or raw input |
| shannon |
Miscellaneous helper functions for the psych package |
| sim |
Functions to simulate psychological/psychometric data. |
| sim.anova |
Simulate a 3 way balanced ANOVA or linear model, with or without repeated measures. |
| sim.bonds |
Create a population or sample correlation matrix, perhaps with hierarchical structure. |
| sim.circ |
Generate simulated data structures for circumplex, spherical, or simple structure |
| sim.congeneric |
Simulate a congeneric data set with or without minor factors |
| sim.correlation |
Create correlation matrices or data matrices with a particular measurement and structural model |
| sim.dichot |
Generate simulated data structures for circumplex, spherical, or simple structure |
| sim.general |
Further functions to simulate psychological/psychometric data. |
| sim.hierarchical |
Create a population or sample correlation matrix, perhaps with hierarchical structure. |
| sim.irt |
Functions to simulate psychological/psychometric data. |
| sim.item |
Generate simulated data structures for circumplex, spherical, or simple structure |
| sim.minor |
Functions to simulate psychological/psychometric data. |
| sim.multi |
Simulate multilevel data with specified within group and between group correlations |
| sim.multilevel |
Simulate multilevel data with specified within group and between group correlations |
| sim.npl |
Functions to simulate psychological/psychometric data. |
| sim.npn |
Functions to simulate psychological/psychometric data. |
| sim.omega |
Further functions to simulate psychological/psychometric data. |
| sim.parallel |
Further functions to simulate psychological/psychometric data. |
| sim.poly |
Functions to simulate psychological/psychometric data. |
| sim.poly.ideal |
Functions to simulate psychological/psychometric data. |
| sim.poly.ideal.npl |
Functions to simulate psychological/psychometric data. |
| sim.poly.ideal.npn |
Functions to simulate psychological/psychometric data. |
| sim.poly.mat |
Functions to simulate psychological/psychometric data. |
| sim.poly.npl |
Functions to simulate psychological/psychometric data. |
| sim.poly.npn |
Functions to simulate psychological/psychometric data. |
| sim.rasch |
Functions to simulate psychological/psychometric data. |
| sim.simplex |
Functions to simulate psychological/psychometric data. |
| sim.spherical |
Generate simulated data structures for circumplex, spherical, or simple structure |
| sim.structural |
Create correlation matrices or data matrices with a particular measurement and structural model |
| sim.structure |
Create correlation matrices or data matrices with a particular measurement and structural model |
| sim.VSS |
create VSS like data |
| simCor |
Create correlation matrices or data matrices with a particular measurement and structural model |
| simulation.circ |
Simulations of circumplex and simple structure |
| skew |
Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame |
| smc |
Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrix |
| Specificity |
Decision Theory measures of specificity, sensitivity, and d prime |
| spider |
Make "radar" or "spider" plots. |
| splitHalf |
Alternative estimates of test reliabiity |
| statsBy |
Find statistics (including correlations) within and between groups for basic multilevel analyses |
| statsBy.boot |
Find statistics (including correlations) within and between groups for basic multilevel analyses |
| statsBy.boot.summary |
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 |
| structure.graph |
Draw a structural equation model specified by two measurement models and a structural model |
| structure.list |
Create factor model matrices from an input list |
| structure.sem |
Draw a structural equation model specified by two measurement models and a structural model |
| summary.psych |
Print and summary functions for the psych class |
| super.matrix |
Form a super matrix from two sub matrices. |
| superCor |
Form a super matrix from two sub matrices. |
| superMatrix |
Form a super matrix from two sub matrices. |
| t2d |
Find Cohen d and confidence intervals |
| t2r |
Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
| table2df |
Convert a table with counts to a matrix or data.frame representing those counts. |
| table2matrix |
Convert a table with counts to a matrix or data.frame representing those counts. |
| tableF |
Miscellaneous helper functions for the psych package |
| Tal.Or |
Data set testing causal direction in presumed media influence |
| Tal_Or |
Data set testing causal direction in presumed media influence |
| target.rot |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| TargetQ |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| TargetT |
Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
| tctg |
Data set testing causal direction in presumed media influence |
| tenberge |
Alternative estimates of test reliabiity |
| test.all |
Miscellaneous helper functions for the psych package |
| test.irt |
A simple demonstration (and test) of various IRT scoring algorthims. |
| test.psych |
Testing of functions in the psych package |
| testReliability |
Find various test-retest statistics, including test, person and item reliability |
| testRetest |
Find various test-retest statistics, including test, person and item reliability |
| tetrachor |
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input |
| tetrachoric |
Tetrachoric, polychoric, biserial and polyserial correlations from various types of input |
| Thurstone |
Seven data sets showing a bifactor solution. |
| thurstone |
Thurstone Case V scaling |
| Thurstone.33 |
Seven data sets showing a bifactor solution. |
| Thurstone.33G |
Seven data sets showing a bifactor solution. |
| Thurstone.9 |
Seven data sets showing a bifactor solution. |
| topBottom |
Combine calls to head and tail |
| tr |
Find the trace of a square matrix |
| Tucker |
9 Cognitive variables discussed by Tucker and Lewis (1973) |
| 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. |
| Yule.inv |
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. |
| Yule2phi |
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. |
| Yule2phi.matrix |
Phi or Yule coefficient matrix to polychoric coefficient matrix |
| Yule2poly |
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. |
| Yule2poly.matrix |
Phi or Yule coefficient matrix to polychoric coefficient matrix |
| Yule2tetra |
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. |
| YuleBonett |
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. |
| YuleCor |
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. |
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