| Chen |
12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation |
| circ.sim |
Generate simulated data structures for circumplex 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 |
| 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. |
| comorbidity |
Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics |
| congeneric.sim |
Simulate a congeneric data set |
| cor.plot |
Create an image plot for a correlation or factor matrix |
| 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 |
| describe |
Basic descriptive statistics useful for psychometrics |
| describe.by |
Basic summary statistics by group |
| dia.arrow |
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 |
| fa |
Factor analysis by Principal Axis, MinRes (minimum residual), Weighted Least Squares or Maximum Likelihood |
| fa.diagram |
Graph factor loading matrices |
| fa.graph |
Graph factor loading matrices |
| fa.parallel |
Scree plots of data or correlation matrix compared to random "parallel" matrices |
| fa.sort |
Sort factor analysis or principal components analysis loadings |
| 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 analysis by Principal Axis, MinRes (minimum residual), Weighted Least Squares or Maximum Likelihood |
| factor.model |
Find R = F F' + U2 is the basic factor model |
| factor.pa |
Factor analysis by Principal Axis, MinRes (minimum residual), Weighted Least Squares or Maximum Likelihood |
| 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 |
Find various goodness of fit statistics for factor analysis and principal components |
| factor.stats |
Find various goodness of fit statistics for factor analysis and principal components |
| factor.wls |
Factor analysis by Principal Axis, MinRes (minimum residual), Weighted Least Squares or Maximum Likelihood |
| 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 |
| Harman |
Two data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt |
| 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 |
| harmonic.mean |
Find the harmonic mean of a vector, matrix, or columns of a data.frame |
| 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) |
| 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.rgraph |
Draw an ICLUST graph using the Rgraphviz package |
| ICLUST.sort |
Sort items by absolute size of cluster loadings |
| 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 |
| iqitems |
14 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.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 |
| item.dichot |
Generate simulated data structures for circumplex or simple structure |
| item.sim |
Generate simulated data structures for circumplex or simple structure |
| 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 |
| make.structural |
Create correlation matrices or data matrices with a particular measurement and structural model |
| MAP |
Apply the Very Simple Structure and MAP 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 |
| mat.regress |
Multiple Regression from matrix input |
| mat.sort |
Sort the elements of a correlation matrix to reflect factor loadings |
| matrix.addition |
A function to add two vectors or matrices |
| msq |
75 mood items from the Motivational State Questionnaire for 3896 participants |
| multi.hist |
Multiple histograms with density and normal fits on one page |
| 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 |
| 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 |
| 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 polychoric correlation |
| phi2poly.matrix |
Phi or Yule coefficient matrix to polychoric coefficient matrix |
| plot.psych |
Plotting functions for the psych package of class "psych" |
| polar |
Convert Cartesian factor loadings into polar coordinates |
| poly.mat |
Find polychoric correlations of item data |
| polychor.matrix |
Phi or Yule coefficient matrix to polychoric coefficient matrix |
| principal |
Principal components analysis |
| print.psych |
Print and summary functions for the psych class |
| Promax |
Perform promax or targeted rotations and return the inter factor angles |
| psych |
A package for personality, psychometric, and psychological research |
| sat.act |
3 Measures of ability: SATV, SATQ, ACT |
| scaling.fits |
Test the adequacy of simple choice, logistic, or Thurstonian scaling. |
| 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.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 |
| scree |
Plot the successive eigen values for a scree test |
| SD |
Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases |
| 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 or simple structure |
| sim.congeneric |
Simulate a congeneric data set |
| sim.dichot |
Generate simulated data structures for circumplex or simple structure |
| sim.hierarchical |
Create a population or sample correlation matrix, perhaps with hierarchical structure. |
| sim.item |
Generate simulated data structures for circumplex or simple structure |
| sim.minor |
Functions to simulate psychological/psychometric data. |
| sim.simplex |
Functions to simulate psychological/psychometric data. |
| 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 skew or 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 |
| 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. |
| 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 |
| 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 polychoric, 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 polychoric, 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 polychoric, 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 polychoric, recreate table the table to create the Yule coefficient. |
| Yule2poly.matrix |
Phi or Yule coefficient matrix to polychoric coefficient matrix |