{"title":"Exploratory Factor Analysis","authors":"D. Gunzler, A. Perzynski, A. Carle","doi":"10.1201/9780203701133-11","DOIUrl":null,"url":null,"abstract":"It is important to distinguish between exploratory and confirmatory analysis. In an exploratory analysis, one wants to explore the empirical data to discover and detect characteristic features and interesting relationships without imposing any definite model on the data. An exploratory analysis may be structure generating, model generating, or hypothesis generating. In confirmatory analysis, on the other hand, one builds a model assumed to describe, explain, or account for the empirical data in terms of relatively few parameters. The model is based on a priori information about the data structure in the form of a specified theory or hypothesis, a given classificatory design for items or subtests according to objective features of content and format, known experimental conditions, or knowledge from previous studies based on extensive data.","PeriodicalId":314183,"journal":{"name":"Structural Equation Modeling for Health and Medicine","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Equation Modeling for Health and Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1201/9780203701133-11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
It is important to distinguish between exploratory and confirmatory analysis. In an exploratory analysis, one wants to explore the empirical data to discover and detect characteristic features and interesting relationships without imposing any definite model on the data. An exploratory analysis may be structure generating, model generating, or hypothesis generating. In confirmatory analysis, on the other hand, one builds a model assumed to describe, explain, or account for the empirical data in terms of relatively few parameters. The model is based on a priori information about the data structure in the form of a specified theory or hypothesis, a given classificatory design for items or subtests according to objective features of content and format, known experimental conditions, or knowledge from previous studies based on extensive data.