Estimation for the multiple factor model when data are missing
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Publication:1136445
DOI10.1007/BF02296204zbMath0427.62036MaRDI QIDQ1136445
Publication date: 1979
Published in: Psychometrika (Search for Journal in Brave)
Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to psychology (62P15)
Related Items (14)
On structural equation modeling with data that are not missing completely at random ⋮ Normal distribution based pseudo ML for missing data: with applications to mean and covariance structure analysis ⋮ Analysis of structural equation models with censored or truncated data via EM algorithm. ⋮ Theory and method for constrained estimation in structural equation models with incomplete data. ⋮ Estimation for the multiple factor model when data are missing ⋮ Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts ⋮ Fully conditional specification in multivariate imputation ⋮ Skew-normal factor analysis models with incomplete data ⋮ A unified approach to exploratory factor analysis with missing data, nonnormal data, and in the presence of outliers ⋮ An estimate of the covariance between variables which are not jointly observed ⋮ Full information maximum likelihood estimation in factor analysis with a large number of missing values ⋮ A distribution-free method for structural equation models with incomplete data ⋮ An evaluation of methods to handle missing data in the context of latent variable interaction analysis: multiple imputation, maximum likelihood, and random forest algorithm ⋮ Estimation for structural equation models with missing data
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