Generalized Latent Variable Modeling: Multilevel,Longitudinal, and Structural Equation Models

By Stan Lipovetsky. Technometrics, 2005

1,236 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f1e25c99aed657f86005d76c4709d31c216e6ec1

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In Computer Networks and Communications

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Intelligence and Creativity Are Pretty Similar After All (2015, background): “Latent variable models allow researchers to model a construct’s true score and error separately (Skrondal and Rabe-Hesketh 2004).”
Assumptions of cross-level measurement and structural invariance in the analysis of multilevel data: Problems and solutions (2008, background): “…independent structures may be posited as influencing these two sources of variation, meaning that we may separately model relationships at the between- and within-groups level of analysis (Muthén, 1989, 1991, 1994, 1997; Rabe-Hesketh, Skrondal, & Pickles, 2004; Skrondal & Rabe-Hesketh, 2004).”
Distance‐based multivariate analyses confound location and dispersion effects (2012, background): “4a also exist – in particular, generalised latent variable models have potential (Skrondal & Rabe-Hesketh 2004) – however, we are yet to find freely available software, and its application in ecology is yet to be evaluated.”
The multilevel latent covariate model: a new, more reliable approach to group-level effects in contextual studies. (2008, background): “Recently, several methodologists have proposed that the conceptualization of latent variables be broadened to include other circumstances in which unobserved individual values might profitably be included in the model (B. O. Muthén, 2002; Raykov, 2007; Skrondal & Rabe-Hesketh, 2004).”
Applied Longitudinal Analysis (2005, neutral): “Hoboken, NJ: Wiley, 2004.”
Serum Vaccine Antibody Concentrations in Children Exposed to Perfluorinated Compounds (2012, background): “17 Structural equation models 18,19 were generated to determine the joint associations of PFCs with the overall antibody concentrations.”
Structural Equation Modeling: Categorical Variables (2005, background): “Skrondal and Rabe-Hesketh [13] provide an extensive overview of estimation methods for SEMs with noncontinuous responses and related models.”
Principal causal effect identification and surrogate end point evaluation by multiple trials (2015, background): “In practice, the full rank condition of ∇f |ξ0 can be tested empirically by the rank of ∇f |ξ̂, where ξ̂ is the MLE of ξ0 (Goodman, 1974; Skrondal and Rabe-Hesketh, 2004).”
Comparison of Methods of Handling Missing Time-Invariant Covariates in Latent Growth Models Under the Assumption of Missing Completely at Random (2007, background): “Recently, LGMs across both SEM and MLM have been fully integrated into a general framework (e.g., Bauer, 2003; Curran, 2003; Mehta & Neale, 2005; B. Muthén, 2002; L. Muthén & Muthén, 2006; Skrondal & Rabe-Hesketh, 2004; but see Hox [2002, chap.”
A cognitive latent variable model for the simultaneous analysis of behavioral and personality data. (2014, methodology): “This type of data analysis is widely known as latent variable modeling (Bartholomew, Knott, & Moustaki, 2011; Skrondal & Rabe-Hesketh, 2004).”
New Evidence on Cross-Country Differences in Job Satisfaction Using Anchoring Vignettes (2008, neutral): “Also see Skrondal and Rabe-Hesketh (2004).”
Multilevel modelling of complex survey data (2006, methodology): “For these models we view the variables, indicators or items measuring the latent variables as level 1 units and the subjects as level 2 units, since the latent variables vary at the subject level (e.g. Skrondal and Rabe-Hesketh (2004)).”
Assessing creativity with self-report scales: A review and empirical evaluation. (2012, methodology): “Latent variable models for diverse kinds of outcomes are well-developed in the statistics literature (Skrondal & Rabe-Hesketh, 2004), but they have been slow to catch on in the world of applied research.”
Bayesian Workflow (2020, background): “, 1972, Gelman and Hill, 2007, Finkel and Manning, 2009, Daumé, 2009), regularization to facilitate the use of large nonparametric models (Hill, 2011), and multilevel modeling for latent variables (Skrondal and Rabe-Hesketh, 2004), and there are connections between transportability and Bayesian grap”
Correcting for covariate measurement error in logistic regression using nonparametric maximum likelihood estimation (2003, methodology): “Currently, gllamm allows continuous, dichotomous, ordered and unordered categorical responses to be modelled, as well as rankings (Skrondal and Rabe-Hesketh, 2003), counts and continuous or discrete durations (Rabe-Hesketh et al., 2001c), see also Skrondal and Rabe-Hesketh (2004) for application.”
EIGHT MYTHS ABOUT CAUSALITY AND STRUCTURAL EQUATION MODELS (2013, neutral): “…model that links the noncontinuous observed variables to an underlying continuous variable via a series of thresholds or through formulations that deal directly with the assumed probability distribution functions without threshold models (e.g., Muthén 1984; Skrondal and Rabe-Hesketh 2005).”
Correcting for Test Score Measurement Error in ANCOVA Models for Estimating Treatment Effects (2014, background): “Latent Variable Regression (LVR)/Likelihood Methods A traditional approach to estimating coefficients on unobserved variables is latent regression modeling (Bollen, 1989; Skrondal & Rabe-Hesketh, 2004; Wansbeek & Meijer, 2000).”