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Bootstrapping latent variable models for binary response
Author(s) -
Albanese M. T.,
Knott M.
Publication year - 1994
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1994.tb01036.x
Subject(s) - bootstrapping (finance) , statistics , estimator , logit , econometrics , probit , latent variable , probit model , mathematics , binary number , ordered probit , item response theory , binary data , reliability (semiconductor) , latent variable model , psychometrics , power (physics) , physics , arithmetic , quantum mechanics
Estimated asymptotic variances for the estimates of the parameters in a logit‐probit model for binary response data are unreliable for moderate sized samples. We show how bootstrapping gives a better idea of the sampling distribution of the estimators, and can also allow an assessment of the reliability of the scoring of individuals on the latent scale.