Pairwise maximum likelihood (PML) estimation method is developed for factor analysis models with ordinal data and fitted both in an exploratory and confirmatory set-up. The performance of the method is studied via simulations and comparisons with full information maximum likelihood (FIML) and...

type="main" xml:id="rssc12032-abs-0001" <title type="main">Summary</title> <p>Responses to a set of indicators, or items, or variables are often used in social sciences for measuring unobserved constructs as attitudes. Latent variable models, which are also known as factor analysis models, are used for linking the observed...</p>

This paper proposes a robust estimator for a general class of linear latent variable models (GLLVM) (Moustaki and Knott 2000, Bartholomew and Knott 1999). It is based on a weighted score function that is simple to implement numerically and is made consistent using the basic idea of indirect...

Until recently, latent variable models such as the factor analysis model for metric responses, the two-parameter logistic model for binary responses, the multinomial model for nominal responses considered only main effects of latent variables without allowing for interaction or polynomial latent...