TY - JOUR
T1 - Evaluating causal models
T2 - An application of maximum-likelihood analysis of structural equations
AU - Maruyama, Geoffrey
AU - McGarvey, Bill
PY - 1980/5
Y1 - 1980/5
N2 - Describes how causal modeling techniques can be improved through the use of maximum-likelihood analysis of structural equations. Within the context of scholastic achievement, the logic of applying this approach to causal modeling studies is presented, and the advantages of such an approach are elaborated. As a demonstration, a computer program called Linear Structural Relations, appropriate for causal modeling techniques, is used to analyze data that explore hypothesized causal relations between peer acceptance and classroom achievement. (28 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).
AB - Describes how causal modeling techniques can be improved through the use of maximum-likelihood analysis of structural equations. Within the context of scholastic achievement, the logic of applying this approach to causal modeling studies is presented, and the advantages of such an approach are elaborated. As a demonstration, a computer program called Linear Structural Relations, appropriate for causal modeling techniques, is used to analyze data that explore hypothesized causal relations between peer acceptance and classroom achievement. (28 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).
KW - maximum likelihood analysis of structural equations, evaluation of causal models
UR - http://www.scopus.com/inward/record.url?scp=0012550298&partnerID=8YFLogxK
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U2 - 10.1037/0033-2909.87.3.502
DO - 10.1037/0033-2909.87.3.502
M3 - Article
AN - SCOPUS:0012550298
SN - 0033-2909
VL - 87
SP - 502
EP - 512
JO - Psychological Bulletin
JF - Psychological Bulletin
IS - 3
ER -