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Latent variables.

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This title shows how uniting ordinary loglinear analysis and latent class analysis into a general loglinear model with latent variables can result in a modified LISREL approach. This modified LISREL model will enable researchers to analyze categorical data in the same way that they have been able to use LISREL to analyze continuous data.

Log-linear models. --- Latent variables.

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Naomi Levy discusses latent variable modeling and how latent growth curve models can be used to understand trajectories of change.

Latent variables. --- Latent structure analysis.

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This paper unites the treatment effect literature and the latent variable literature. The economic questions answered by the commonly used treatment effect parameters are considered. We demonstrate how the marginal treatment effect parameter can be used in a latent variable framework to generate the average treatment effect, the effect of treatment on the treated and the local average treatment effect, thereby establishing a new relationship among these parameters. The method of local instrumental variables directly estimates the marginal treatment effect parameters, and thus can be used to estimate all of the conventional treatment effect parameters when the index condition holds and the parameters are identified. When they are not, the method of local instrumental variables can be used to produce bounds on the parameters with the width of the bounds depending on the width of the support for the index generating the choice of the observed potential outcome.

Instrumental variables (Statistics) --- Latent variables. --- Estimation theory.

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Mathematical statistics --- Latent variables --- Factor analysis --- Path analysis (Statistics) --- Structural equation modeling --- Factor analysis. --- Latent structure analysis. --- Latent variables. --- Structural equation modeling. --- Path analysis (Statistics). --- Wiskundige statistiek