She Asked for It: Hardcore Porn, Sexism, and Rape Myth Acceptance

The present study examined pornography viewing, rape myth acceptance, and sexist attitudes. Data came from 392 male and 903 female participants. Multigroup SEM indicated neither pornography viewing, nor hardcore pornography viewing, were related to rape myth acceptance when controlling for sexist attitudes among men. Wald tests indicated hostile sexism to be a significantly stronger predictor of all rape myths examined compared to pornography viewing or hardcore pornography viewing in men and women. Latent variable interaction analyses suggested hardcore pornography viewing as a significant exacerbating factor for the relationship between hostile sexism and “she asked for it” rape myths across genders.

CB-SEM latent interaction: Unconstrained and orthogonalized approaches

© 2020 Australian and New Zealand Marketing Academy Covariance Based – Structural Equation Modelling (CB-SEM) is often used to investigate moderation and latent interaction effects. This study illustrates and compares the application of constrained, unconstrained and orthogonalized CB-SEM approaches to latent variable interaction analysis using AMOS. Although all three techniques provided similar parameter estimates, the orthogonalized approach provided reduced standard errors resulting in identifying a significant latent interaction, suggesting the orthogonalized approach may be better suited for exploratory research. The illustrated example demonstrates three CB-SEM techniques, and the simplicity of the three approaches to test for interaction effects. The three approaches can be comfortably implemented in available software programs. Guidelines and recommendations for the use of the three approaches are identified with a step-wise process of assessing the latent interaction effect in CB-SEM. As far as we are aware this is the first investigation comparing and recommending specific CB-SEM latent variable moderation analysis techniques in marketing research.

CB-SEM latent interaction: Unconstrained and orthogonalized approaches

© 2020 Australian and New Zealand Marketing Academy Covariance Based – Structural Equation Modelling (CB-SEM) is often used to investigate moderation and latent interaction effects. This study illustrates and compares the application of constrained, unconstrained and orthogonalized CB-SEM approaches to latent variable interaction analysis using AMOS. Although all three techniques provided similar parameter estimates, the orthogonalized approach provided reduced standard errors resulting in identifying a significant latent interaction, suggesting the orthogonalized approach may be better suited for exploratory research. The illustrated example demonstrates three CB-SEM techniques, and the simplicity of the three approaches to test for interaction effects. The three approaches can be comfortably implemented in available software programs. Guidelines and recommendations for the use of the three approaches are identified with a step-wise process of assessing the latent interaction effect in CB-SEM. As far as we are aware this is the first investigation comparing and recommending specific CB-SEM latent variable moderation analysis techniques in marketing research.