Emma Somer
Biographic Data
| ID | 6629994 |
|---|---|
| NAME | Emma Somer |
| GIVEN NAMES | Emma |
| FAMILY NAME | Somer |
| SIGNATURE | SOMER E |
| AFFILIATIONS | McGill University |
| ORCID | 0000-0001-9346-3378 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
A Comparison of Regularization, Alignment, and a Traditional Method for Estimating Structural Relationships Across Two Groups
Establishing the correct partial measurement invariance model is crucial for ensuring unbiased comparisons of relationships between latent variables across multiple groups. While traditional approaches rely on detecting noninvariant items followed by estimation of structural relationships, more recently, approaches that estimate latent parameters without prior knowledge of anchor items have been developed. Specifically, regularization and alignme…
Latent Variable Interactions with Categorical Indicators
Social science phenomena are often predicted by interactions between variables. When these variables cannot be directly observed, one option is to model them as latent variables that are measured by multiple indicators. When indicators are continuous, latent interactions can be modeled and estimated using the latent moderated structural equations (LMS) approach. A categorical LMS (LMS-cat) approach with full information estimation was more recent…
Comparing Factor Score Approaches to SEM in Multigroup Models with Small Samples
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon’s correction and the bias avoiding method, for multigroup models with small samples and compare the methods to SEM. W…
Prior Predictive Checks for the Method of Covariances in Bayesian Mediation Analysis
Bayesian mediation analysis using the method of covariances requires specifying a prior for the covariance matrix of the independent variable, mediator, and outcome. Using a conjugate inverse-Wishart prior has been the norm, even though this choice assumes equal levels of informativeness for all elements in the covariance matrix. This paper describes separation strategy priors for the single mediator model, develops a Prior Predictive Check (PrPC…
No prominent works on this page.
Prior Predictive Checks for the Method of Covariances in Bayesian Mediation Analysis
Bayesian mediation analysis using the method of covariances requires specifying a prior for the covariance matrix of the independent variable, mediator, and outcome. Using a conjugate inverse-Wishart prior has been the norm, even though this choice assumes equal levels of informativeness for all elements in the covariance matrix. This paper describes separation strategy priors for the single mediator model, develops a Prior Predictive Check (PrPC…
Comparing Factor Score Approaches to SEM in Multigroup Models with Small Samples
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon’s correction and the bias avoiding method, for multigroup models with small samples and compare the methods to SEM. W…
Latent Variable Interactions with Categorical Indicators
Social science phenomena are often predicted by interactions between variables. When these variables cannot be directly observed, one option is to model them as latent variables that are measured by multiple indicators. When indicators are continuous, latent interactions can be modeled and estimated using the latent moderated structural equations (LMS) approach. A categorical LMS (LMS-cat) approach with full information estimation was more recent…
A Comparison of Regularization, Alignment, and a Traditional Method for Estimating Structural Relationships Across Two Groups
Establishing the correct partial measurement invariance model is crucial for ensuring unbiased comparisons of relationships between latent variables across multiple groups. While traditional approaches rely on detecting noninvariant items followed by estimation of structural relationships, more recently, approaches that estimate latent parameters without prior knowledge of anchor items have been developed. Specifically, regularization and alignme…
Econometrics (3 works) · Mathematics (3 works) · Psychometric Methodologies and Testing (3 works) · Statistics (3 works) · Structural equation modeling (3 works) · Advanced Statistical Modeling Techniques (2 works) · Computer Science (2 works) · Factor analysis (2 works) · Latent variable (2 works) · Mental Health Research Topics (2 works)