Basic Principles of Structural Equation Modeling

Ziegel, Eric R.; Mueller, Ralph O.

doi:10.1007/978-1-4612-3974-1

Cited by 517 publications

(281 citation statements)

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“…This is a statistical analysis method that has been developed by Sewall Wright, one of the founders of the field of population genetics (DUNCAN 1966;KENNY 1979;MUELLER 1996;WRIGHT 1934WRIGHT , 1960. It relies on the development of path models, which are diagrams that facilitate the visualization of the relationships between variables measuring phenotypic traits, any intermediate variables, and fitness (RICE 2004).…”

Section: The Fundamental Requirement For Evolution Of Traits Through mentioning

confidence: 99%

“…are measured as standardized partial regression coefficients, also referred to as path coefficients. They are of the same type as the coefficients generated in multiple regression analyses (MUELLER 1996;WRIGHT 1960).…”

Section: The Fundamental Requirement For Evolution Of Traits Through mentioning

confidence: 99%

“…A fundamental property of path models is that the covariance between any pair of variables equals the sum of the products of the path coefficients in all possible paths connecting the two variables (DUNCAN 1966;MUELLER 1996;WRIGHT 1934WRIGHT , 1960. Combining this property with Equation (4) for the trait x leads to the requirement for evolution of that trait expressed in Equation (5).…”

Section: The Fundamental Requirement For Evolution Of Traits Through mentioning

confidence: 99%

“…Because of this, mate selection traits take up a proportion of the explained variance of m, which in path models cannot be higher than 1 (MUELLER 1996;WRIGHT 1960), effectively crowding the variance space that can be occupied by other mate choice traits. That is, as more independent mate selection traits are evolved, the probability that new such traits will evolve gradually decreases until it reaches zero.…”

Section: The Limits On the Number Of Independent Traits Used In Mate mentioning

confidence: 99%

“…The curved arrow indicates that a level of covariance exists between the measures of traits x and y, which is equivalent to saying that those measures are correlated. We can use path analysis properties (MUELLER 1996;RICE 2004;WRIGHT 1934WRIGHT , 1960 here in the same way as in the development of the inequalities that described the conditions for evolution of independent traits. Doing so leads to Equations (17) to (20).…”

Section: The Limits On the Number Of Independent Traits Used In Mate mentioning

confidence: 99%

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A mathematical analysis of the evolution of human mate choice traits: Implications for evolutionary psychologists

Kock¹

2011

Journal of Evolutionary Psychology

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Abstract. Sexually reproducing organisms often rely on various traits to judge the attractiveness of potential mates. Many mate choice preferences and traits have evolved through selection by those organisms' ancestors, with traits having been either costly (detrimental to survival) or noncostly in the environment of their evolutionary adaptation. A general mathematical analysis of the evolution of traits used in mate choice is presented. The analysis builds on a combination of Price's covariance equation and Wright's method of path analysis, and includes a set of Monte Carlo simulations. The usefulness of the mathematical analysis is demonstrated through the development of a small but important set of hypotheses and implications for the human species: (1) costly traits used in mate choice by humans should be generally less common and more attractive to the other sex than non-costly traits; (2) costly traits should be disproportionately less common in human females than in males; and (3) some harmful human mental disorders, such as schizophrenia, may have co-evolved as costs of attractive mental traits. It is also shown that similar analyses can be easily employed by evolutionary psychologists to theorize about the evolution of complex mate choice traits, and to test the resulting theories with modern humans through the method of path analysis.

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Section: The Fundamental Requirement For Evolution Of Traits Through mentioning

confidence: 99%

Section: The Fundamental Requirement For Evolution Of Traits Through mentioning

confidence: 99%

Section: The Fundamental Requirement For Evolution Of Traits Through mentioning

confidence: 99%

Section: The Limits On the Number Of Independent Traits Used In Mate mentioning

confidence: 99%

Section: The Limits On the Number Of Independent Traits Used In Mate mentioning

confidence: 99%

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A mathematical analysis of the evolution of human mate choice traits: Implications for evolutionary psychologists

Kock¹

2011

Journal of Evolutionary Psychology

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Structural Equation Models

Bentler¹,

Yuan²

2004

Encyclopedia of Statistical Sciences

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This LISREL study examines the robustness of the maximum likelihood estimates under varying degrees of measurement model misspecification. A true model containing five latent variables (two endogenous and three exogenous) and two indicator variables per latent variable was used. Measurement model misspecification considered included errors of omission, errors of inclusion, and simultaneous errors of omission and inclusion. A sample size of 200 was used for all replications. LISREL programs were written for each of six models to be tested. The PC version of LISREL VII was used to estimate the models. Assessments of results were based on average parameter estimates for each model acres replications, average chi-square value across replications, modification indices for errors of omission, and t-values for errors of inclusion. Results indicate that minor misspecifications in LISREL measurement models in the LY matrix are the most problematic, particularly for compound errors. In general, the ability of the LISREL program to detect measurement, model misspecification is quite good. One figure illustrating the true population model and six data tables are included. (TJH)

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Structural Equation Models

2005

Encyclopedia of Statistical Sciences

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Basic Principles of Structural Equation Modeling

Cited by 517 publications

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A mathematical analysis of the evolution of human mate choice traits: Implications for evolutionary psychologists

A mathematical analysis of the evolution of human mate choice traits: Implications for evolutionary psychologists

Structural Equation Models

Structural Equation Models

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