Conditions for Confirmatory Analysis and Causal Inference.

Abstract

Confirmatory analysis refers to a family of analytic procedures designed to evaluate the utility of causal hypotheses and to support inferences regarding causality among naturally occurring events derived from field studies. These analytic procedures are gaining rapid exposure in psychology, and include techniques such as confirmatory factor analysis, linear structural relations, path analysis, structural equations, and time series. This report specifies and discusses the conditions that justify the use of confirmatory analysis to evaluate causal hypotheses and to support causal inferences. The conditions include the need for strong theory, specification of causal order and direction, meaningful operationalization of variables, and statistical demonstration of goodness of fit between theoretical models and empirical data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 03, 1982
Accession Number
ADA114373

Entities

People

  • Jeanne M. Brett
  • Lawrence R. James
  • Stanley A. Mulaik

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Applied Psychology
  • Cognition
  • Data Mining
  • Data Science
  • Factor Analysis
  • Human Behavior
  • Information Processing
  • Information Science
  • Knowledge Management
  • Psychology
  • Reasoning
  • Reliability
  • Social Sciences
  • Statistical Algorithms
  • Statistical Tests
  • Statistics
  • Surveys

Readers

  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference