date: 2021-01-22T11:05:32Z pdf:PDFVersion: 1.5 pdf:docinfo:title: Score-Guided Structural Equation Model Trees xmp:CreatorTool: LaTeX with hyperref package access_permission:can_print_degraded: true subject: Structural equation model (SEM) trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. dc:format: application/pdf; version=1.5 pdf:docinfo:creator_tool: LaTeX with hyperref package access_permission:fill_in_form: true pdf:encrypted: false dc:title: Score-Guided Structural Equation Model Trees modified: 2021-01-22T11:05:32Z cp:subject: Structural equation model (SEM) trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. pdf:docinfo:subject: Structural equation model (SEM) trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. pdf:docinfo:creator: Manuel Arnold meta:author: Manuel Arnold meta:creation-date: 2021-01-22T10:32:51Z created: 2021-01-22T10:32:51Z access_permission:extract_for_accessibility: true Creation-Date: 2021-01-22T10:32:51Z Author: Manuel Arnold producer: pdfTeX-1.40.15 pdf:docinfo:producer: pdfTeX-1.40.15 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: Structural equation model (SEM) trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. Keywords: exploratory data analysis, heterogeneity, model-based recursive partitioning, parameter stability, structural change tests, structural equation modeling access_permission:modify_annotations: true PDFVersion: 1.5 dc:creator: Manuel Arnold description: Structural equation model (SEM) trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. dcterms:created: 2021-01-22T10:32:51Z Last-Modified: 2021-01-22T11:05:32Z dcterms:modified: 2021-01-22T11:05:32Z title: Score-Guided Structural Equation Model Trees xmpMM:DocumentID: uuid:959590ae-418d-4c90-8a3e-a82b6c462059 Last-Save-Date: 2021-01-22T11:05:32Z pdf:docinfo:keywords: exploratory data analysis, heterogeneity, model-based recursive partitioning, parameter stability, structural change tests, structural equation modeling pdf:docinfo:modified: 2021-01-22T11:05:32Z meta:save-date: 2021-01-22T11:05:32Z pdf:docinfo:custom:PDFVersion: 1.5 Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Manuel Arnold dc:subject: exploratory data analysis, heterogeneity, model-based recursive partitioning, parameter stability, structural change tests, structural equation modeling access_permission:assemble_document: true xmpTPg:NPages: 18 pdf:charsPerPage: 3535 access_permission:extract_content: true access_permission:can_print: true meta:keyword: exploratory data analysis, heterogeneity, model-based recursive partitioning, parameter stability, structural change tests, structural equation modeling access_permission:can_modify: true pdf:docinfo:created: 2021-01-22T10:32:51Z