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| psych-package | A package for personality, psychometric, and psychological research |
| %+% | A function to add two vectors or matrices |
| alpha.scale | Cronbach alpha for a scale |
| circ.sim | Generate simulated data structures for circumplex or simple structure |
| circ.simulation | Simulations of circumplex and simple structure |
| circ.tests | Apply four tests of circumplex versus simple structure |
| 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 |
| correct.cor | Find dis-attenuated correlations and give alpha reliabilities |
| count.pairwise | Count number of pairwise cases for a data set with missing (NA) data. |
| describe | Basic descriptive statistics useful for psychometrics |
| describe.by | Basic summary statistics by group |
| eigen.loadings | Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings |
| error.crosses | Plot x and y error bars |
| factor.congruence | Coefficient of factor congruence |
| factor.fit | How well does the factor model fit a correlation matrix. Part of the VSS package |
| factor.model | Find R = F F' + U2 is the basic factor model |
| factor.pa | Principal Axis Factor Analysis |
| factor.residuals | R* = R- F F' |
| factor.rotate | "Hand" rotate a factor loading matrix |
| factor2cluster | Extract cluster definitions from factor loadings |
| fisherz | Fisher z transform of r |
| geometric.mean | Find the geometric mean of a vector or columns of a data.frame. |
| harmonic.mean | Find the harmonic mean of a vector, matrix, or columns of a data.frame |
| ICLUST | ICLUST: Item Cluster Analysis - Hierarchical cluster analysis using psychometric principles |
| ICLUST.cluster | Function to form hierarchical cluster analysis of items |
| ICLUST.graph | create control code for ICLUST graphical output |
| ICLUST.sort | sort items by absolute size of cluster loadins |
| 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 |
| kurtosi | Kurtosis of a vector, matrix, or data frame |
| make.hierarchical | Create a population or sample correlation matrix with hierachical structure. |
| mat.regress | Multiple Regression from matrix input |
| multi.hist | Multiple histograms on one screen |
| omega | Calculate the omega estimate of factor saturation |
| paired.r | Test the difference between paired correlations |
| pairs.panels | SPLOM, histograms and correlations for a data matrix |
| panel.cor | SPLOM, histograms and correlations for a data matrix |
| panel.hist | SPLOM, histograms and correlations for a data matrix |
| phi | Find the phi coefficient of correlation between two dichotomous variables |
| phi2poly | Convert a phi coefficient to a polychoric correlation |
| polychor.matrix | Actually, what does this do? Convert a matrix of phi coefficients to a matrix of polycoric correlations |
| principal | Principal components analysis |
| psych | A package for personality, psychometric, and psychological research |
| psycho.demo | Create demo data for psychometrics |
| read.clipboard | shortcut for reading from the clipboard |
| schmid | Apply the Schmid Leiman transformation to a correlation matrix |
| 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 as well as associated statistics |
| skew | Calculate skew for a vector, matrix, or data.frame |
| VSS | Apply the Very Simple Structure criterion to determine the appropriate number of factors. |
| VSS.parallel | Compare real and random VSS solutions |
| VSS.plot | Plot VSS fits |
| VSS.scree | Plot a scree test |
| VSS.simulate | create VSS like data |