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Tools include within/between-group statistics, machine-learning validation and cross-validation of scales, simulation and testing of item/test structures, and front-end support for structural equation modeling with path diagrams and mediation models.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/technology/","Technology",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/psych-r-package-procedures-for-psychological-psychometric-and-personality-research/296271/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/psych-r-package-procedures-for-psychological-psychometric-and-personality-research/296271.png","ImageObject",300,407,{"name":42,"@type":43},"Ethan Miller","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-20","2026-09-18",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",10,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What main analyses does the psych toolbox provide?","Question",{"text":63,"@type":64},"It provides multivariate analysis and scale construction using methods such as factor analysis, principal component analysis, cluster analysis, and reliability analysis, along with basic descriptive statistics.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How does psych handle Item Response Theory?",{"text":68,"@type":64},"It performs Item Response Theory using factor analysis of tetrachoric and polychoric correlations.",{"name":70,"@type":61,"acceptedAnswer":71},"Does psych support validation and structural equation modeling workflows?",{"text":72,"@type":64},"Yes. It offers scale validation and cross-validation using basic machine learning algorithms and provides functions that serve as a useful front end for structural equation modeling, including graphical path diagrams and mediation models.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},296271,1790461368,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,105,110,115,120,123,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":103,"slug":104},6,50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":112,"show_sort_weight":113,"slug":114},8,"Research & Report",30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":55,"slug":125},"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":102,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145},687207017582,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","Package ‘psych’  \nMay 16, 2026  \nVersion 2.6.5 Date 2026-05-11  \nTitle Procedures for Psychological, Psychometric, and Personality  \nResearch  \nDescription  \nA general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component 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 analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to sup  \nport a book on psychometric theory as well as publications in personality research. For more information, see the \u003C[https://personality-project.org/r/](https://personality-project.org/r/)> web page.  \nLicense GPL (>= 2)  \nImports mnormt,parallel,stats,graphics,grDevices,methods,lattice,nlme,GPArotation Suggests psychTools, lavaan, lme4, Rcsdp, graph, knitr, Rgraphviz  \nLazyData yes ByteCompile true VignetteBuilder knitr  \nURL [https://personality-project.org/r/psych/](https://personality-project.org/r/psych/)[ ](https://personality-project.org/r/psych/)[https://personality-project.org/r/psych-manual.pdf](https://personality-project.org/r/psych-manual.pdf)  \nNeedsCompilation no  \nAuthor William Revelle [aut, cre](ORCID:  \n\u003C[https://orcid.org/0000-0003-4880-9610](https://orcid.org/0000-0003-4880-9610)>) Maintainer William Revelle \u003C[revelle@northwestern.edu](revelle@northwestern.edu)> Repository CRAN  \nDate/Publication 2026-05-16 00:10:02 UTC  \nContents  \n00.psych ........................................... 6  \nalpha ............................................. 16  \nanova.psych ......................................... 21  \nAUC ............................................. 23  \nbassAckward ........................................ 26  \nBechtoldt .......................................... 29  \nbestScales .......................................... 32  \nbfi .............................................. 38  \nbi.bars ............................................ 40  \nbigCor ............................................ 42  \nbiPlot ............................................ 45  \nblock.random ........................................ 47  \nbock ............................................. 48  \ncattell ............................................ 50  \nCFA ............................................. 51  \ncirc.tests ........................................... 56  \n[cluster.fit ...........................................](cluster.fit ........................................... 59)[ 59](cluster.fit ........................................... 59)  \n[cluster.loadings .......................................](cluster.loadings ....................................... 60)[ 60](cluster.loadings ....................................... 60)  \n[cluster.plot ..........................................](cluster.plot .......................................... 62)[ 62](cluster.plot .......................................... 62)  \n[cluster2keys .........................................](cluster2keys ......................................... 63)[ 63](cluster2keys ......................................... 63)  \n[cohen.d ...........................................](cohen.d ........................................... 64)[ 64](cohen.d ........................................... 64)  \n[cohen.kappa ......","cbCaiiaPwvjDSYRM","https://ap.wps.com/l/cbCaiiaPwvjDSYRM","pdf",1501238,497,"English","# Package Overview\n## Core Analytics and Scale Construction\n## Item Response Theory and Multilevel Analysis\n## Validation, Simulation, and Structural Equation Front-End\n## Graphical Outputs\n# Package Contents (Function Index)","[{\"question\":\"What main analyses does the psych toolbox provide?\",\"answer\":\"It provides multivariate analysis and scale construction using methods such as factor analysis, principal component analysis, cluster analysis, and reliability analysis, along with basic descriptive statistics.\"},{\"question\":\"How does psych handle Item Response Theory?\",\"answer\":\"It performs Item Response Theory using factor analysis of tetrachoric and polychoric correlations.\"},{\"question\":\"Does psych support validation and structural equation modeling workflows?\",\"answer\":\"Yes. It offers scale validation and cross-validation using basic machine learning algorithms and provides functions that serve as a useful front end for structural equation modeling, including graphical path diagrams and mediation models.\"}]","psych - R Package Procedures for Psychological, Psychometric, and Personality Research | PDF",1789730255,1252]