پکیج های مربوط به تحلیل ساختار دانش و دیگر نرم افزارهای مربوط به روانسنجی در نرم افزار R

پکیج های مربوط به تحلیل ساختار دانش  در نرم افزار R

در لینک زیر می توانید پکیج های مربوط به تحلیل ساختار دانش در نرم افزار R را مشاهده کنید:

http://cran.r-project.org/web/views/Psychometrics.html

Functions and example datasets for the psychometric theory of knowledge spaces. Data analysis methods and procedures for simulating data and transforming different formulations in knowledge space theory.	DAKS	1
Basic functionality to generate, handle, and manipulate deterministic knowledge structures based on sets and relations Functions for fitting probabilistic knowledge structures	kst pks	2
پکیج های مربوط به دیگر نرم افزارهای مربوط به روانسنجی در نرم افزار R در لینک زیر می توانید پکیج های مربوط به دیگر نرم افزارهای مربوط به روانسنجی در نرم افزار R را مشاهده کنید: http://cran.r-project.org/web/views/Psychometrics.html
Infrastructure for psychometric modeling such as data classes (e.g., for paired comparisons) and basic model fitting functions (e.g., for Rasch and Bradley-Terry models).	psychotools	1
Recursive partitioning based on psychometric models, employing the general MOB algorithm (from package party)  Currently, only Bradley-Terry trees are provided.	psychotree	2
Psychometric mixture models based on flexmix infrastructure (at the moment Rasch mixture models and Bradley-Terry mixture models).	psychomix	3
Functions for non-IRT equating under both random groups and nonequivalent groups with anchor test designs Mean, linear, equipercentile and circle-arc equating  as are methods for univariate and bivariate presmoothing of score distributions Specific equating methods currently supported include Tucker, Levine observed score, Levine true score, Braun/Holland, frequency estimation, and chained equating.	equate	4
IRT and non-IRT based statistical indices proposed in the literature for detecting answer copying on multiple-choice examinations	CopyDetect	5
Latent class analysis with random effects  Function lca()  Polytomous variable latent class analysis	randomLCA e1071 poLCA	6
computation of simple, more-sample, and stepwise configural frequency analysis (CFA).	cfa	7
Coefficents for interrater reliability and agreements	irr	8
Generates design matrices for analysing real paired comparisons and derived paired comparison data (Likert type items / ratings or rankings) using a loglinear approach  Fits loglinear Bradley-Terry model (LLBT) exploting an eliminate feature  Computes pattern models for paired comparisons, rankings, and ratings. Some treatment of missing values (MCAR and MNAR).	prefmod	9
Bradley-Terry models for paired comparisons Elimination-by-aspects models	BradleyTerry2 eba
Psychophysical data Functions to estimate the contribution of the n scales to the judgment by a maximum likelihood method under several hypotheses of how the perceptual dimensions interact.	psyphy MLCM
Functions and example datasets for Fechnerian scaling of discrete object sets Computes Fechnerian distances among objects representing subjective dissimilarities, and other related information	fechner
Functions for nonparametric estimation of a psychometric function and for estimation of a derived threshold and slope, and their standard deviations and confidence intervals	modelfree
Confidence intervals for standardized effect sizes	MBESS	10
parametric and nonparametric causal mediation analysis  conduct sensitivity analysis for certain parametric models	mediation	12
Functions for data screening, testing moderation, mediation, and estimating power	QuantPsyc	13
Social networks with relations at different levels. Multiple networks data sets with routines that combine algebraic structures like the partially ordered semigroup with the existing relational bundles found in multiple networks.	multiplex	14
Visualizing data as networks	qgraph	15
Social Relations Analyses for round robin designs  Functionality of the SOREMO software  New functions like the handling of missing values, significance tests for single groups, or the calculation of the self enhancement index.	TripleR	16
Fitting and testing multinomial processing tree models, a class of statistical models for categorical data with latent parameters package. The link probabilities of a tree-like graph and represent the cognitive processing steps executed to arrive at observable response categories Analysis of multinomial processing tree (MPT) models.	mpt MPTinR	17
Beta regression for modeling beta-distributed dependent variables, e.g., rates and proportions	betareg	18
functions to compare two correlations based on either dependent or independent groups	cocor	19
A set of tools that implement profile analysis and cross-validation techniques	profileR	20
A GUI for entering test items and obtaining raw and transformed scores.	TestScorer	21

پکیج های مربوط به نظریه کلاسیک آزمون در نرم افزار R

در لینک زیر می توانید پکیج های مربوط به نظریه کلاسیک آزمون در نرم افزار R را مشاهده کنید:

http://cran.r-project.org/web/views/Psychometrics.html

score multiple-choice responses reliability analyses item analyses transform scores onto different scales	CTT	1
Functions for correlation theory, meta-analysis (validity generalization), reliability, item analysis, inter-rater reliability, and classical utility are contained	psychometric	2
Functions to statistically compare two or more alpha coefficients based on either dependent or independent groups of individuals	cocron	3
Calculates and plots the step-by-step Cronbach-Mesbach curve.	CMC	4
Cronbach alpha, kappa coefficients  intra-class correlation coefficients (ICC) Functions for ICC computation	psy  psych psychometric  ICC	5
A number of routines for scale construction and reliability analysis useful for personality and experimental psychology	psych MiscPsycho	6
Computes measures from generalizability theory	QME (not on CRAN)	7

پکیج های مربوط به مقیاس پردازی چندبعدی در نرم افزار R

در لینک زیر می توانید پکیج های مربوط به مقیاس پردازی چندبعدی را در نرم افزار R را مشاهده کنید:

http://cran.r-project.org/web/views/Psychometrics.html

multidimensional scaling (MDS) based on stress minimization by means of majorization: Simple smacof on symmetric dissimilarity matrices, smacof for rectangular matrices (unfolding models), smacof with constraints on the configuration, three-way smacof for individual differences (including constraints for idioscal, indscal, and identity), and spherical smacof (primal and dual algorithm).	smacof	1
multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions Some other multiway methods: PCAn (Tucker-n) and PARAFAC/CANDECOMP with extensions.	PTAk	2
functionalities for computing classical MDS using the cmdscale() function. Sammon mapping sammon()  non-metric MDS isoMDS()	MASS	3
Non-metric MDS  with metaMDS()  Function nmds() Some routines Function for metric MDS	vegan labdsv  ecodist xgobi ExPosition	4
Principal coordinate analysis with capscale()pco() and with dudi.pco()	vegan labdsv ecodist ade4	5
maximum likelihood difference scaling (MLDS).	MLDS	6

پکیج های مربوط به معادلات ساختاری و تحلیل عاملی را در نرم افزار R

در لینک زیر می توانید پکیج های مربوط به معادلات ساختاری و تحلیل عاملی را در نرم افزار R را مشاهده کنید:

http://cran.r-project.org/web/views/Psychometrics.html

Ordinary factor analysis (FA) Principal component analysis (PCA) can be fitted with prcomp() (based on svd(), preferred) as well as princomp() (based on eigen() for compatibility with S-PLUS). Additional rotation methods for FA based on gradient projection algorithms Non-graphical solution to the Cattell scree test. Some graphical PCA representations	GPArotation nFactors psy GPArotation nFactors	1
general (i.e., latent-variable) SEMs by FIML, and structural equations in observed-variable models by 2SLS Categorical variables in SEMs Observed-variables models, including nonlinear simultaneous-equations models Partial least-squares estimation Graphical models	sem polycor systemfit pls gR SocialSciences	2
path analysis confirmatory factor analysis structural equation modeling growth curve models lavaan model syntax which allows users to express their models in a compact way and allows for ML, GLS, WLS, robust ML using Satorra-Bentler corrections, and FIML for data with missing values. meanstructures and multiple groups standardized solutions, fit measures, modification indices	lavaan	3
complex survey structural equation modeling (SEM) structural equation models (SEM) factor analysis Multivariate regression models with latent variables and many other latent variable models while correcting estimates, standard errors, and chi-square-derived fit measures for a complex sampling design.  clustering, stratification sampling weights, and finite population corrections	lavaan.survey	4
structural equation models censored and dichotomous variables via a probit link formulation	lava lava.tobit	5
structural equation models using partial least squares (PLS) Segmentation trees in PLS path modeling.	semPLS plspm pathmox	6
Monte Carlo simulations	simsem	7
a package of add on functions that can aid in fitting SEMs in R	semTools	8
path diagrams and visual analysis for outputs of various SEM packages	semPlot	9
tests of difference in fit for mean and covariance structure models	SEMModComp	10
factor analysis based on a genetic algorithm for optimization This makes it possible to impose a wide range of restrictions on the factor analysis model, whether using exploratory factor analysis, confirmatory factor analysis, or a new estimator called semi-exploratory factor analysis (SEFA).	FAiR	11
FA and PCA with supplementary individuals and supplementary quantitative/qualitative variables Sampling from the posterior for ordinal and mixed factor models	FactoMineR MCMCpack	12
nonlinear PCA (aka categorical PCA) nonlinear canonical correlation analysis (models of the Gifi-family).	homals	13
Independent component analysis (ICA)	fastICA	14
robust principal components	pcaPP	15
parallel analysis of continuous, ordered (including dichotomous/binary as a special case) or mixed type of data associated with a principal components analysis	pcaPA	16
functions such as fa.parallel() and VSS() for estimating the appropriate number of factors/components as well as ICLUST() for item clustering	psych	17
An interface between the EQS software for SEM and R	REQS	18
estimation of a wide variety of advanced multivariate statistical models  a library of functions and optimizers that allow you to quickly and flexibly define an SEM model and estimate parameters given observed data.	OpenMX ( link )	19
to automate latent variable model estimation and interpretation using Mplus.	MplusAutomation	20

پکیج های مربوط به Correspondence Analysis در نرم افزار R

در لینک زیر می توانید پکیج های مربوط به Correspondence Analysis را در نرم افزار را مشاهده کنید:

http://cran.r-project.org/web/views/Psychometrics.html

comprises two parts, one for simple correspondence analysis and one for multiple and joint correspondence analysis. Within each part, functions for computation, summaries and visualization in two and three dimensions are provided, including options to display supplementary points and perform subset analyses	ca	1	Correspondence Analysis (CA)
Simple and canonical CA  different scaling methods such as standard scaling, Benzecri scaling, centroid scaling, and Goodman scaling two- and three-dimensional joint plots including confidence ellipsoids  alternative plotting possibilities in terms of transformation plots, Benzecri plots, and regression plots	anacor	2
interactive Biplots	BiplotGUI	3
Homogeneity analysis aka multiple CA and various Gifi extensions Hull plots, span plots, Voronoi plots, star plots, projection plots	homals	4
Simple and multiple correspondence analysis	MASS	5
functions covering, e.g., principal components, simple and multiple, fuzzy, non-symmetric, and decentered correspondence analysis	ade4	6
predictive and symmetric co-correspondence analysis (CoCA) models	cocorresp	7
several factor analytic methods CA including supplementary row and/or column points and multiple correspondence analysis (MCA) with supplementary individuals, supplementary quantitative variables and supplementary qualitative variables	FactoMineR	8
basic ordination methods, including non-metric multidimensional scaling The constrained ordination methods include constrained analysis of proximities, redundancy analysis, and constrained (canonical) and partially constrained correspondence analysis	vegan	9
SVD based multivariate exploratory methods such as PCA, CA, MCA (as well as a Hellinger form of CA)	ExPosition	10