A B C D E F G H I K L M N O P Q R S T U V W Y misc
psych-package | A package for personality, psychometric, and psychological research |
acs | Miscellaneous helper functions for the psych package |
alpha | Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6. |
alpha.ci | 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. |
alpha2r | Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6. |
anova.psych | Model comparison for regression, mediation, cluster and factor analysis |
AUC | Decision Theory measures of specificity, sensitivity, and d prime |
auc | Decision Theory measures of specificity, sensitivity, and d prime |
autoR | Find von Neuman's Mean Square of Successive Differences |
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.dictionary | 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. |
eigen.loadings | Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings |
eigenCi | Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors. |
ellipses | Plot data and 1 and 2 sigma correlation ellipses |
equamax | Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
error.bars | Plot means and confidence intervals |
error.bars.by | Plot means and confidence intervals for multiple groups |
error.bars.tab | Plot means and confidence intervals |
error.crosses | Plot x and y error bars |
error.dots | Show a dot.chart with error bars for different groups or variables |
errorCircles | Two way plots of means, error bars, and sample sizes |
esem | Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques |
esem.diagram | Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques |
esemDiagram | Perform and Exploratory Structural Equation Model (ESEM) by using factor extension techniques |
extension.diagram | Graph factor loading matrices |
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 |
g2r | Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals |
Garcia | Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010) |
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. |
GSBE | Data from the sexism (protest) study of Garcia, Schmitt, Branscome, and Ellemers (2010) |
guttman | Alternative estimates of test reliabiity |
Harman | Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt |
Harman.5 | Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt |
Harman.8 | Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt |
Harman.Burt | Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt |
Harman.Holzinger | Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt |
Harman.political | Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt |
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 |
het.diagram | Graph factor loading matrices |
histBy | Multiple histograms with density and normal fits on one page |
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) |
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 |
kaiser | Apply the Kaiser normalization when rotating factors |
keys.lookup | A set of functions for factorial and empirical scale construction |
keys2list | Create a keys matrix for use by score.items or cluster.cor |
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 |
levels2numeric | Miscellaneous helper functions for the psych package |
lmCor | Multiple Regression, Canonical and Set Correlation from matrix or raw input |
lmCor.diagram | Multiple Regression, Canonical and Set Correlation from matrix or raw input |
lmCorLookup | A set of functions for factorial and empirical scale construction |
lmDiagram | Multiple Regression, Canonical and Set Correlation from matrix or raw input |
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 |
lookupFromKeys | A set of functions for factorial and empirical scale construction |
lookupItems | 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 |
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 |
nchar2numeric | Miscellaneous helper functions for the psych package |
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 |
omegaDirect | Calculate McDonald's omega estimates of general and total factor saturation |
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 |
outlier | Find and graph Mahalanobis squared distances to detect outliers |
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 |
quickView | Combine calls to head and tail |
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 |
r2p | Transformations of r, d, and t including Fisher r to z and z to r 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 |
removeMissing | Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations |
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 |
RV | Three measures of the correlations between sets of variables |
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 |
small.msq | A small example data set taken from a larger data set |
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) |
unidim | Several indices of the unidimensionality of a set of variables. |
validityItem | Find the predicted validities of a set of scales based on item statistics |
varimin | Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
vgQ.bimin | Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
vgQ.targetQ | Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
vgQ.varimin | Perform Procustes,bifactor, promax or targeted rotations and return the inter factor angles. |
violin | Create a 'violin plot' or density plot of the distribution of a set of variables |
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 | Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors. |
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 |
vssSelect | Apply the Very Simple Structure, MAP, and other criteria to determine the appropriate number of factors. |
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 | 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. |
%+% | A function to add two vectors or matrices |