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It explains the software’s purpose for researchers to analyze both cross-sectional and longitudinal data, single-level and multilevel data, and data with missing values. The guide highlights model flexibility across variable types, including continuous, censored, binary, ordinal, nominal, and count outcomes, and supports Monte Carlo simulation studies for generating and analyzing data under included models.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":30,"@type":76,"position":81},"https://docshare.wps.com/document/technology/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/statistical-analysis-with-latent-variables-users-guide-sixth-edition/292196/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/statistical-analysis-with-latent-variables-users-guide-sixth-edition/292196.png","ImageObject",300,407,{"name":92,"@type":93},"Skyler","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-21","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is Mplus designed to do for researchers?","Question",{"text":113,"@type":114},"Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze data using a wide choice of models, estimators, and algorithms with an easy-to-use interface and graphical displays.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What kinds of data and modeling situations does Mplus support?",{"text":118,"@type":114},"Mplus supports cross-sectional and longitudinal data, single-level and multilevel data, observed and unobserved heterogeneity across populations, and data containing missing values.",{"name":120,"@type":111,"acceptedAnswer":121},"Which variable types can Mplus analyze?",{"text":122,"@type":114},"Mplus can analyze continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, and combinations of these variable types.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},292196,1789648912,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":29,"category_name":30,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":130,"read_time":145},2336464648746,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Statistical Analysis With Latent Variables  \nUser’s Guide  \nLinda K. Muthén Bengt O. Muthén  \nFollowing is the correct citation for this document:  \nMuthén, L.K. and Muthén, B.O. (1998-2010) . Mplus User’s Guide. Sixth Edition.  \nLos Angeles, CA: Muthén & Muthén  \nCopyright © 1998-2010 Muthén & Muthén Program Copyright © 1998-2010 Muthén & Muthén Version 6  \nApril 2010  \nThe development of this software has been funded in whole or in part with Federal funds from the National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, under Contract No . N44AA52008 and Contract No. N44AA92009 .  \nMuthén & Muthén  \n3463 Stoner Avenue  \nLos Angeles, CA 90066  \nTel: (310) 391-9971  \nFax: (310) 391-8971  \n[Web: www.StatModel.com](Web: www.StatModel.com)  \n[Support@StatModel.com](Support@StatModel.com)  \nTABLE OF CONTENTS  \nChapter 1: Introduction 1  \nChapter 2: Getting started with Mplus 13  \nChapter 3: Regression and path analysis 19  \nChapter 4: Exploratory factor analysis 41  \nChapter 5: Confirmatory factor analysis and structural equation modeling 51  \nChapter 6: Growth modeling and survival analysis 97  \nChapter 7: Mixture modeling with cross-sectional data 141  \nChapter 8: Mixture modeling with longitudinal data 197  \nChapter 9: Multilevel modeling with complex survey data 233  \nChapter 10: Multilevel mixture modeling 289  \nChapter 11: Missing data modeling and Bayesian analysis 337  \nChapter 12: Monte Carlo simulation studies 357  \nChapter 13: Special features 391  \nChapter 14: Special modeling issues 407  \nChapter 15: TITLE, DATA, VARIABLE, and DEFINE commands 449  \nChapter 16: ANALYSIS command 519  \nChapter 17: MODEL command 567  \nChapter 18: OUTPUT, SAVEDATA, and PLOT commands 633  \nChapter 19: MONTECARLO command 689  \nChapter 20: A summary of the Mplus language 711  \nPREFACE  \nWe started to develop Mplus fifteen years ago with the goal of providing researchers with powerful new statistical modeling techniques . We saw a wide gap between new statistical methods presented in the statistical literature and the statistical methods used by researchers in substantively-oriented papers . Our goal was to help bridge this gap with easy-to-use but powerful software . Version 1 of Mplus was released in November 1998; Version 2 was released in February 2001; Version 3 was released in March 2004; Version 4 was released in February 2006; and Version 5 was released in November 2007. We are now proud to present the new and unique features of Version 6. With Version 6, we have gone a considerable way toward accomplishing our goal, and we plan to continue to pursue it in the future .  \nThe new features that have been added between Version 5 and Version 6 would never have been accomplished without two very important team members, Tihomir Asparouhov and Thuy Nguyen . It may be hard to believe that the Mplus team has only two programmers, but these two programmers are extraordinary. Tihomir has developed and programmed sophisticated statistical algorithms to make the new modeling possible. Without his ingenuity, they would not exist. His deep insights into complex modeling issues and statistical theory are invaluable. Thuy has developed the post-processing graphics module and the Mplus editor and language generator. In addition, Thuy has programmed the Mplus language and is responsible for keeping control of the entire code which has grown enormously. Her unwavering consistency, logic, and steady and calm approach to problems keep everyone on target. We feel fortunate to work with such a talented team . Not only are they extremely bright, but they are also hard-working, loyal, and always striving for excellence. Mplus Version 6 would not have been possible without them.  \nAnother important team member is Michelle Conn. Michelle was with us at the beginning when she was instrumental in setting up the Mplus office and has been managing the office for the past six years . In addition, Michelle is responsible for creating the pictu","cbCaitREBDrG6v5j","https://ap.wps.com/l/cbCaitREBDrG6v5j","pdf",2334328,758,"English","# Chapter 1: Introduction\n# Chapter 2: Getting started with Mplus\n# Chapter 3: Regression and path analysis\n# Chapter 4: Exploratory factor analysis\n# Chapter 5: Confirmatory factor analysis and structural equation modeling\n# Chapter 6: Growth modeling and survival analysis\n# Chapter 7: Mixture modeling with cross-sectional data\n# Chapter 8: Mixture modeling with longitudinal data\n# Chapter 9: Multilevel modeling with complex survey data\n# Chapter 10: Multilevel mixture modeling\n# Chapter 11: Missing data modeling and Bayesian analysis\n# Chapter 12: Monte Carlo simulation studies\n# Chapter 13: Special features\n# Chapter 14: Special modeling issues\n# Chapter 15: TITLE, DATA, VARIABLE, and DEFINE commands\n# Chapter 16: ANALYSIS command\n# Chapter 17: MODEL command\n# Chapter 18: OUTPUT, SAVEDATA, and PLOT commands\n# Chapter 19: MONTECARLO command\n# Chapter 20: A summary of the Mplus language","[{\"question\":\"What is Mplus designed to do for researchers?\",\"answer\":\"Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze data using a wide choice of models, estimators, and algorithms with an easy-to-use interface and graphical displays.\"},{\"question\":\"What kinds of data and modeling situations does Mplus support?\",\"answer\":\"Mplus supports cross-sectional and longitudinal data, single-level and multilevel data, observed and unobserved heterogeneity across populations, and data containing missing values.\"},{\"question\":\"Which variable types can Mplus analyze?\",\"answer\":\"Mplus can analyze continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, and combinations of these variable types.\"}]","Statistical Analysis With Latent Variables - User’s Guide - Sixth Edition | PDF",1910]