activity
20242026
most citedBias-Reduced Estimation of Structural Equation Models

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ME2026

Informative Distance-Based Priors for Correlation Matrices Centred on a Target Reference

Anna Freni-Sterrantino, Janet van Niekerk, Elias Teixeira Krainski +3

Specifying a prior over the space of correlation matrices is a persistent challenge in Bayesian analysis. The space is a curved manifold whose dimension grows quadratically with th…

stat.CO2026

Implementation and Workflows for INLA-Based Approximate Bayesian Structural Equation Modelling

Haziq Jamil, HÃ¥vard Rue

Bayesian structural equation modelling (BSEM) offers many advantages such as principled uncertainty quantification, small-sample regularisation, and flexible model specification. H…

stat.ME2026

Approximate Bayesian Inference for Structural Equation Models using Integrated Nested Laplace Approximations

Haziq Jamil, HÃ¥vard Rue

Markov chain Monte Carlo (MCMC) methods remain the mainstay of Bayesian estimation of structural equation models (SEM), though they often incur a high computational cost. We presen…

stat.ME20251 cited

Bias-Reduced Estimation of Structural Equation Models

Haziq Jamil, Yves Rosseel, Oliver Kemp +1

Finite-sample bias is a pervasive challenge in the estimation of structural equation models (SEMs), especially when sample sizes are small or measurement reliability is low. A rang…

stat.ME2024

Pairwise likelihood estimation and limited information goodness-of-fit test statistics for binary factor analysis models under complex survey sampling

Haziq Jamil, Irini Moustaki, Chris Skinner

This paper discusses estimation and limited information goodness-of-fit test statistics in factor models for binary data using pairwise likelihood estimation and sampling weights.…