A B C D E F G H I K L M N O P R S T V W Y misc

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

psych-package | A package for personality, psychometric, and psychological research |

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

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

all.income | US family income from US census 2008 |

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

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

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. |

best.items | A set of functions for factorial and empirical scale construction |

best.scales | A set of functions for factorial and empirical scale construction |

bfi | 25 Personality items representing 5 factors |

bfi.dictionary | 25 Personality items representing 5 factors |

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

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

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

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

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

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

blot | Bond's Logical Operations Test - BLOT |

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 |

burt | 11 emotional variables from Burt (1915) |

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

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.linear.cor | Functions for analysis of circadian or diurnal data |

circadian.mean | 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 |

cities | Distances between 11 US cities |

city.location | Distances between 11 US cities |

cluster.cor | Find correlations of composite variables 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.kappa | Find Cohen's kappa and weighted kappa coefficients for correlation of two raters |

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 |

cor.ci | Bootstrapped 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 |

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

cor2latex | Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table |

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

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 | 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 |

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

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

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

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

d2r | Fisher r to z and z to r 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 |

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

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 |

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. |

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 |

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

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

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

error.bars | Plot means and confidence intervals |

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

error.crosses | Plot x and y error bars |

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

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

fa.rgraph | Graph factor loading matrices |

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 |

fa2latex | Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table |

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

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 | |

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

factor.pa | |

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 | |

factor2cluster | Extract cluster definitions from factor loadings |

fisherz | Fisher r to z and z to r and confidence intervals |

fisherz2r | Fisher r to z and z to r and confidence intervals |

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

galton | Galton's Mid parent child height data |

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

glb | Alternative estimates of test reliabiity |

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

glb.fa | Alternative estimates of test reliabiity |

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

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

guttman | Alternative estimates of test reliabiity |

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

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

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

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

Harman.Holzinger | 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 |

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

headTail | Combine calls to head and tail |

headtail | Combine calls to head and tail |

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

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

Holzinger | Seven data sets showing a bifactor solution. |

Holzinger.9 | Seven data sets showing a bifactor solution. |

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

ICC2latex | Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table |

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 |

income | US family income from US census 2008 |

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 | |

interp.quantiles | |

interp.quart | |

interp.quartiles | |

interp.values | |

iqitems | 16 multiple choice IQ items |

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.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 |

irt2latex | Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table |

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 |

kaiser | Apply the Kaiser normalization when rotating factors |

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

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

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

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

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

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

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

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

lowerCor | Miscellaneous helper functions for the psych package |

lowerMat | Miscellaneous helper functions for the psych package |

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

lsat6 | Bock and Liberman (1970) data set of 1000 observations of the LSAT |

lsat7 | Bock and Liberman (1970) data set of 1000 observations of the LSAT |

make.congeneric | Simulate a congeneric data set |

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

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

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

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

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

mat.regress | Set Correlation and Multiple Regression from matrix or raw input |

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

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

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 |

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

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

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

neo | NEO correlation matrix from the NEO_PI_R manual |

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

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

omega.diagram | Graph hierarchical factor structures |

omega.graph | Graph hierarchical factor structures |

omega2latex | Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table |

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

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

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

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 |

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

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. |

peas | Galton's Peas |

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 |

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.residuals | Plotting functions for the psych package of class "psych" |

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 |

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

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

principal | Principal components analysis (PCA) |

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

progressBar | Miscellaneous helper functions for the psych package |

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

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

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

r.con | Fisher r to z and z to r and confidence intervals |

r.test | Tests of significance for correlations |

r2d | Fisher r to z and z to r and confidence intervals |

r2t | 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) |

read.clipboard | shortcut for reading from the clipboard |

read.clipboard.csv | shortcut for reading from the clipboard |

read.clipboard.fwf | shortcut for reading from the clipboard |

read.clipboard.lower | shortcut for reading from the clipboard |

read.clipboard.tab | shortcut for reading from the clipboard |

read.clipboard.upper | shortcut for reading from the clipboard |

reflect | Miscellaneous helper functions for the psych package |

Reise | Seven data sets showing a bifactor solution. |

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 |

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

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

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, densitie 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 |

scoreItems | Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations |

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 |

set.cor | Set Correlation and Multiple Regression 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.circ | Generate simulated data structures for circumplex, spherical, or simple structure |

sim.congeneric | Simulate a congeneric data set |

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

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

sim.parallel | 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 |

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 |

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. |

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

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 |

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

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

tenberge | Alternative estimates of test reliabiity |

test.all | Miscellaneous helper functions for the psych package |

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

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. |

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) |

veg | Paired comparison of preferences for 9 vegetables |

vegetables | Paired comparison of preferences for 9 vegetables |

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

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

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

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

vss | |

VSS.parallel | Compare real and random VSS solutions |

VSS.plot | Plot VSS fits |

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

VSS.sim | create VSS like data |

VSS.simulate | create VSS like data |

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

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

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

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

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

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

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

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

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 | |

Yule2poly.matrix | Phi or Yule coefficient matrix to polychoric coefficient matrix |

Yule2tetra |

%+% | A function to add two vectors or matrices |