{"title":"传播学术中潜在变量混合模型的系统文献综述","authors":"Colton E. Krawietz, Rudy C. Pett","doi":"10.1080/19312458.2023.2179612","DOIUrl":null,"url":null,"abstract":"ABSTRACT Recently, latent variable mixture modeling has gained traction in many disciplines, given its unique ability to discover unknown groups within a broader population. Indeed, this method assumes that a finite number of mixtures (i.e. unknown groups) exist within the population and can be discovered by evaluating participants’ response patterns to a set of manifest indicators. Despite the intuitive approach, recommendations have been proposed to overcome some methodological concerns associated with latent variable mixture modeling. The primary purpose of this study was to understand the characteristics of latent variable mixture modeling in communication research and to evaluate the extent to which the existing research meets these recommendations. Ninety-five manuscripts published between 2010 and 2022 in 18 communication journals were identified and systematically analyzed. The review found that (1) the use of latent variable mixture modeling has increased; (2) latent class analysis and latent profile analysis are the most common models; and (3) most manuscripts did not meet the proscribed standards for random start values, auxiliary variable procedures, indicator requirements, and missing data procedures. These findings are discussed more in comparison with the proscribed standards. In addition, conceptual and applicable recommendations are provided to improve communication scholarship.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":6.3000,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Systematic Literature Review of Latent Variable Mixture Modeling in Communication Scholarship\",\"authors\":\"Colton E. Krawietz, Rudy C. Pett\",\"doi\":\"10.1080/19312458.2023.2179612\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Recently, latent variable mixture modeling has gained traction in many disciplines, given its unique ability to discover unknown groups within a broader population. Indeed, this method assumes that a finite number of mixtures (i.e. unknown groups) exist within the population and can be discovered by evaluating participants’ response patterns to a set of manifest indicators. Despite the intuitive approach, recommendations have been proposed to overcome some methodological concerns associated with latent variable mixture modeling. The primary purpose of this study was to understand the characteristics of latent variable mixture modeling in communication research and to evaluate the extent to which the existing research meets these recommendations. Ninety-five manuscripts published between 2010 and 2022 in 18 communication journals were identified and systematically analyzed. The review found that (1) the use of latent variable mixture modeling has increased; (2) latent class analysis and latent profile analysis are the most common models; and (3) most manuscripts did not meet the proscribed standards for random start values, auxiliary variable procedures, indicator requirements, and missing data procedures. These findings are discussed more in comparison with the proscribed standards. In addition, conceptual and applicable recommendations are provided to improve communication scholarship.\",\"PeriodicalId\":47552,\"journal\":{\"name\":\"Communication Methods and Measures\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2023-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communication Methods and Measures\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1080/19312458.2023.2179612\",\"RegionNum\":1,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communication Methods and Measures","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/19312458.2023.2179612","RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
A Systematic Literature Review of Latent Variable Mixture Modeling in Communication Scholarship
ABSTRACT Recently, latent variable mixture modeling has gained traction in many disciplines, given its unique ability to discover unknown groups within a broader population. Indeed, this method assumes that a finite number of mixtures (i.e. unknown groups) exist within the population and can be discovered by evaluating participants’ response patterns to a set of manifest indicators. Despite the intuitive approach, recommendations have been proposed to overcome some methodological concerns associated with latent variable mixture modeling. The primary purpose of this study was to understand the characteristics of latent variable mixture modeling in communication research and to evaluate the extent to which the existing research meets these recommendations. Ninety-five manuscripts published between 2010 and 2022 in 18 communication journals were identified and systematically analyzed. The review found that (1) the use of latent variable mixture modeling has increased; (2) latent class analysis and latent profile analysis are the most common models; and (3) most manuscripts did not meet the proscribed standards for random start values, auxiliary variable procedures, indicator requirements, and missing data procedures. These findings are discussed more in comparison with the proscribed standards. In addition, conceptual and applicable recommendations are provided to improve communication scholarship.
期刊介绍:
Communication Methods and Measures aims to achieve several goals in the field of communication research. Firstly, it aims to bring attention to and showcase developments in both qualitative and quantitative research methodologies to communication scholars. This journal serves as a platform for researchers across the field to discuss and disseminate methodological tools and approaches.
Additionally, Communication Methods and Measures seeks to improve research design and analysis practices by offering suggestions for improvement. It aims to introduce new methods of measurement that are valuable to communication scientists or enhance existing methods. The journal encourages submissions that focus on methods for enhancing research design and theory testing, employing both quantitative and qualitative approaches.
Furthermore, the journal is open to articles devoted to exploring the epistemological aspects relevant to communication research methodologies. It welcomes well-written manuscripts that demonstrate the use of methods and articles that highlight the advantages of lesser-known or newer methods over those traditionally used in communication.
In summary, Communication Methods and Measures strives to advance the field of communication research by showcasing and discussing innovative methodologies, improving research practices, and introducing new measurement methods.