psych v1.3.10.12
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Procedures for Psychological, Psychometric, and Personality Research
A number of routines for personality, psychometrics and experimental psychology. Functions are primarily for scale construction using factor analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for simulating particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometrics as well as publications in personality research. For more information, see the personality-project.org/r webpage.
Functions in psych
| Name | Description | |
| cor.smooth | Smooth a non-positive definite correlation matrix to make it positive definite | |
| cities | Distances between 11 US cities | |
| bi.bars | Draw pairs of bargraphs based on two groups | |
| epi.bfi | 13 personality scales from the Eysenck Personality Inventory and Big 5 inventory | |
| dummy.code | Create dummy coded variables | |
| Dwyer | 8 cognitive variables used by Dwyer for an example. | |
| Gorsuch | Example data set from Gorsuch (1997) for an example factor extension. | |
| factor.fit | How well does the factor model fit a correlation matrix. Part of the VSS package | |
| ICC | Intraclass Correlations (ICC1, ICC2, ICC3 from Shrout and Fleiss) | |
| kaiser | Apply the Kaiser normalization when rotating factors | |
| factor.stats | Find various goodness of fit statistics for factor analysis and principal components | |
| Harman.5 | 5 socio-economic variables from Harman (1967) | |
| VSS.parallel | Compare real and random VSS solutions | |
| irt.fa | Item Response Analysis by Exploratory Factor Analysis of tetrachoric/polychoric correlations | |
| error.bars | Plot means and confidence intervals | |
| errorCircles | Two way plots of means, error bars, and sample sizes | |
| phi2tetra | Convert a phi coefficient to a tetrachoric correlation | |
| ICLUST.rgraph | Draw an ICLUST graph using the Rgraphviz package | |
| factor.rotate | ``Hand" rotate a factor loading matrix | |
| fisherz | Fisher r to z and z to r and confidence intervals | |
| cortest.mat | Chi square tests of whether a single matrix is an identity matrix, or a pair of matrices are equal. | |
| Promax | Perform bifactor, promax or targeted rotations and return the inter factor angles. | |
| fa.extension | Apply Dwyer's factor extension to find factor loadings for extended variables | |
| cluster.loadings | Find item by cluster correlations, corrected for overlap and reliability | |
| logistic | Logistic transform from x to p and logit transform from p to x | |
| cluster2keys | Convert a cluster vector (from e.g., kmeans) to a keys matrix suitable for scoring item clusters. | |
| alpha | Find two estimates of reliability: Cronbach's alpha and Guttman's Lambda 6. | |
| fa.parallel | Scree plots of data or correlation matrix compared to random ``parallel" matrices | |
| error.crosses | Plot x and y error bars | |
| Bechtoldt | Seven data sets showing a bifactor solution. | |
| parcels | Find miniscales (parcels) of size 2 or 3 from a set of items | |
| galton | Galton's Mid parent child height data | |
| partial.r | Find the partial correlations for a set (x) of variables with set (y) removed. | |
| iclust.diagram | Draw an ICLUST hierarchical cluster structure diagram | |
| VSS.scree | Plot the successive eigen values for a scree test | |
| blot | Bond's Logical Operations Test -- BLOT | |
| cor.ci | Bootstrapped confidence intervals for raw and composite correlations | |
| cor2dist | Convert correlations to distances (necessary to do multidimensional scaling of correlation data) | |
| factor.scores | Various ways to estimate factor scores for the factor analysis model | |
| cortest.bartlett | Bartlett's test that a correlation matrix is an identity matrix | |
| circ.tests | Apply four tests of circumplex versus simple structure | |
| Schmid | 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation | |
| cushny | A data set from Cushny and Peebles (1905) on the effect of three drugs on hours of sleep, used by Student (1908) | |
| fa.sort | Sort factor analysis or principal components analysis loadings | |
| error.bars.by | Plot means and confidence intervals for multiple groups | |
| SD | Find the Standard deviation for a vector, matrix, or data.frame - do not return error if there are no cases | |
| lowerUpper | Combine two square matrices to have a lower off diagonal for one, upper off diagonal for the other | |
| scaling.fits | Test the adequacy of simple choice, logistic, or Thurstonian scaling. | |
| ellipses | Plot data and 1 and 2 sigma correlation ellipses | |
| draw.tetra | Draw a correlation ellipse and two normal curves to demonstrate tetrachoric correlation | |
| bock | Bock and Liberman (1970) data set of 1000 observations of the LSAT | |
| iclust | iclust: Item Cluster Analysis -- Hierarchical cluster analysis using psychometric principles | |
| Tucker | 9 Cognitive variables discussed by Tucker and Lewis (1973) | |
| spider | Make "radar" or "spider" plots. | |
| cor.wt | The sample size weighted correlation may be used in correlating aggregated data | |
| comorbidity | Convert base rates of two diagnoses and their comorbidity into phi, Yule, and tetrachorics | |
| cubits | Galton's example of the relationship between height and 'cubit' or forearm length | |
| set.cor | Set Correlation and Multiple Regression from matrix or raw input | |
| score.alpha | Score scales and find Cronbach's alpha as well as associated statistics | |
| VSS | Apply the Very Simple Structure and MAP criteria to determine the appropriate number of factors. | |
| sim.structure | Create correlation matrices or data matrices with a particular measurement and structural model | |
| factor.model | Find R = F F' + U2 is the basic factor model | |
| predict.psych | Prediction function for factor analysis or principal components | |
| Harman.political | Eight political variables used by Harman (1967) as example 8.17 | |
| sim.congeneric | Simulate a congeneric data set | |
| phi.demo | A simple demonstration of the Pearson, phi, and polychoric corelation | |
| factor.residuals | R* = R- F F' | |
| biplot.psych | Draw biplots of factor or component scores by factor or component loadings | |
| tetrachoric | Tetrachoric, polychoric, biserial and polyserial correlations from various types of input | |
| headTail | Combine calls to head and tail | |
| block.random | Create a block randomized structure for n independent variables | |
| Harman | Two data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt | |
| describeBy | Basic summary statistics by group | |
| VSS.plot | Plot VSS fits | |
| cohen.kappa | Find Cohen's kappa and weighted kappa coefficients for correlation of two raters | |
| eigen.loadings | Convert eigen vectors and eigen values to the more normal (for psychologists) component loadings | |
| sat.act | 3 Measures of ability: SATV, SATQ, ACT | |
| matrix.addition | A function to add two vectors or matrices | |
| mixed.cor | Find correlations for mixtures of continuous, polytomous, and dichotomous variables | |
| fa.diagram | Graph factor loading matrices | |
| mardia | Calculate univariate or multivariate (Mardia's test) skew and kurtosis for a vector, matrix, or data.frame | |
| diagram | Helper functions for drawing path model diagrams | |
| msq | 75 mood items from the Motivational State Questionnaire for 3896 participants | |
| polychor.matrix | Phi or Yule coefficient matrix to polychoric coefficient matrix | |
| glb.algebraic | Find the greatest lower bound to reliability. | |
| scrub | A utility for basic data cleaning and recoding. Changes values outside of minimum and maximum limits to NA. | |
| 00.psych | A package for personality, psychometric, and psychological research | |
| omega.graph | Graph hierarchical factor structures | |
| mat.sort | Sort the elements of a correlation matrix to reflect factor loadings | |
| iqitems | 16 multiple choice IQ items | |
| affect | Two data sets of affect and arousal scores as a function of personality and movie conditions | |
| statsBy | Find statistics (including correlations) within and between groups for basic multilevel analyses | |
| heights | A data.frame of the Galton (1888) height and cubit data set. | |
| thurstone | Thurstone Case V scaling | |
| count.pairwise | Count number of pairwise cases for a data set with missing (NA) data. | |
| p.rep | Find the probability of replication for an F, t, or r and estimate effect size | |
| interp.median | Find the interpolated sample median, quartiles, or specific quantiles for a vector, matrix, or data frame | |
| neo | NEO correlation matrix from the NEO_PI_R manual | |
| harmonic.mean | Find the harmonic mean of a vector, matrix, or columns of a data.frame | |
| tr | Find the trace of a square matrix | |
| irt.item.diff.rasch | Simple function to estimate item difficulties using IRT concepts | |
| test.psych | Testing of functions in the psych package | |
| phi | Find the phi coefficient of correlation between two dichotomous variables | |
| polar | Convert Cartesian factor loadings into polar coordinates | |
| peas | Galton`s Peas | |
| winsor | Find the Winsorized scores, means, sds or variances for a vector, matrix, or data.frame | |
| print.psych | Print and summary functions for the psych class | |
| score.multiple.choice | Score multiple choice items and provide basic test statistics | |
| rangeCorrection | Correct correlations for restriction of range. (Thorndike Case 2) | |
| bfi | 25 Personality items representing 5 factors | |
| sim.anova | Simulate a 3 way balanced ANOVA or linear model, with or without repeated measures. | |
| paired.r | Test the difference between (un)paired correlations | |
| residuals.psych | Extract residuals from various psych objects | |
| plot.psych | Plotting functions for the psych package of class ``psych" | |
| structure.list | Create factor model matrices from an input list | |
| 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. | |
| simulation.circ | Simulations of circumplex and simple structure | |
| mssd | Find von Neuman's Mean Square of Successive Differences | |
| score.items | Score item composite scales and find Cronbach's alpha, Guttman lambda 6 and item whole correlations | |
| factor2cluster | Extract cluster definitions from factor loadings | |
| irt.1p | Item Response Theory estimate of theta (ability) using a Rasch (like) model | |
| table2matrix | Convert a table with counts to a matrix or data.frame representing those counts. | |
| score.irt | Find Item Response Theory (IRT) based scores for dichotomous or polytomous items | |
| Harman.8 | Correlations of eight physical variables (from Harman, 1966) | |
| read.clipboard | shortcut for reading from the clipboard | |
| sim.multilevel | Simulate multilevel data with specified within group and between group correlations | |
| withinBetween | An example of the distinction between within group and between group correlations | |
| ICLUST.graph | create control code for ICLUST graphical output | |
| cor.plot | Create an image plot for a correlation or factor matrix | |
| reverse.code | Reverse the coding of selected items prior to scale analysis | |
| KMO | Find the Kaiser, Meyer, Olkin Measure of Sampling Adequacy | |
| ICLUST.sort | Sort items by absolute size of cluster loadings | |
| ICLUST.cluster | Function to form hierarchical cluster analysis of items | |
| cluster.plot | Plot factor/cluster loadings and assign items to clusters by their highest loading. | |
| describe | Basic descriptive statistics useful for psychometrics | |
| sim | Functions to simulate psychological/psychometric data. | |
| vegetables | Paired comparison of preferences for 9 vegetables | |
| income | US family income from US census 2008 | |
| make.keys | Create a keys matrix for use by score.items or cluster.cor | |
| df2latex | Convert a data frame, correlation matrix, or factor analysis output to a LaTeX table | |
| psych.misc | Miscellaneous helper functions for the psych package | |
| rescale | Function to convert scores to ``conventional " metrics | |
| burt | 11 emotional variables from Burt (1915) | |
| cta | Simulate the C(ues) T(endency) A(ction) model of motivation | |
| geometric.mean | Find the geometric mean of a vector or columns of a data.frame. | |
| scatter.hist | Draw a scatter plot with associated X and Y histograms, densitie and correlation | |
| sim.item | Generate simulated data structures for circumplex, spherical, or simple structure | |
| guttman | Alternative estimates of test reliabiity | |
| structure.diagram | Draw a structural equation model specified by two measurement models and a structural model | |
| multi.hist | Multiple histograms with density and normal fits on one page | |
| r.test | Tests of significance for correlations | |
| cluster.cor | Find correlations of composite variables from a larger matrix | |
| sim.hierarchical | Create a population or sample correlation matrix, perhaps with hierarchical structure. | |
| cluster.fit | cluster Fit: fit of the cluster model to a correlation matrix | |
| correct.cor | Find dis-attenuated correlations given correlations and reliabilities | |
| fa | 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 | |
| smc | Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrix | |
| superMatrix | Form a super matrix from two sub matrices. | |
| corr.test | Find the correlations, sample sizes, and probability values between elements of a matrix or data.frame. | |
| cosinor | Functions for analysis of circadian or diurnal data | |
| irt.responses | Plot probability of multiple choice responses as a function of a latent trait | |
| omega | Calculate McDonald's omega estimates of general and total factor saturation | |
| pairs.panels | SPLOM, histograms and correlations for a data matrix | |
| principal | Principal components analysis (PCA) | |
| sim.VSS | create VSS like data | |
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Details
| Date | 2013-10-12 |
| License | GPL (>= 2) |
| LazyData | true |
| URL | http://personality-project.org/r http://personality-project.org/r/psych.manual.pdf |
| Packaged | 2013-10-13 23:28:48 UTC; revelle |
| NeedsCompilation | no |
| Repository | CRAN |
| Date/Publication | 2013-10-14 07:24:46 |
| suggests | GPArotation , graph , lavaan , MASS , mvtnorm , polycor , Rcsdp , Rgraphviz , sem |
| Contributors | William Revelle |
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