Approximate sampling variances of maximum-likelihood probability estimates in a logit response function

The maximum likelihood parameters estimated in logistic analysis are in terms of a transformation of the original response variable and, although inferences are easily made about the sources of variation in the linearized model using standard procedures applied in regression analysis, the variance-c...

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Main Author: Rege, J.E.O.
Format: Conference Paper
Language:Inglés
Published: International Biometric Society 1997
Subjects:
Online Access:https://hdl.handle.net/10568/50190
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author Rege, J.E.O.
author_browse Rege, J.E.O.
author_facet Rege, J.E.O.
author_sort Rege, J.E.O.
collection Repository of Agricultural Research Outputs (CGSpace)
description The maximum likelihood parameters estimated in logistic analysis are in terms of a transformation of the original response variable and, although inferences are easily made about the sources of variation in the linearized model using standard procedures applied in regression analysis, the variance-covariance structure of the predicted probabilities obtained following back-transformation of logits is complex and estimation of sampling variances normally require inversion of matrices and taking derivatives of the inverse of the link function evaluated at each prediction point. This paper presents a method for estimating sampling variances of such predicted probabilities without the need to invert any matrix or take derivatives of the link function. The method is based on the assumption that the exponent of a linear function of the logits is lognormal. It is demonstrated by way of a numerical example that this approximation is not different from the more complex methods applied by software such as SAS and GENSTAT.
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spelling CGSpace501902025-11-04T14:09:43Z Approximate sampling variances of maximum-likelihood probability estimates in a logit response function Rege, J.E.O. sampling statistical methods The maximum likelihood parameters estimated in logistic analysis are in terms of a transformation of the original response variable and, although inferences are easily made about the sources of variation in the linearized model using standard procedures applied in regression analysis, the variance-covariance structure of the predicted probabilities obtained following back-transformation of logits is complex and estimation of sampling variances normally require inversion of matrices and taking derivatives of the inverse of the link function evaluated at each prediction point. This paper presents a method for estimating sampling variances of such predicted probabilities without the need to invert any matrix or take derivatives of the link function. The method is based on the assumption that the exponent of a linear function of the logits is lognormal. It is demonstrated by way of a numerical example that this approximation is not different from the more complex methods applied by software such as SAS and GENSTAT. 1997 2014-10-31T06:08:54Z 2014-10-31T06:08:54Z Conference Paper https://hdl.handle.net/10568/50190 en Open Access application/pdf International Biometric Society Rege, J.E.O. 1997. Approximate sampling variances of maximum-likelihood probability estimates in a logit response function. IN: Duchateau, L. and Mwambi, H.G. (eds.), Proceedings of the fifth scientific conference of the East, Central and Southern Africa Network of the International Biometric Society, Mombasa, Kenya, 1997: 108-115.
spellingShingle sampling
statistical methods
Rege, J.E.O.
Approximate sampling variances of maximum-likelihood probability estimates in a logit response function
title Approximate sampling variances of maximum-likelihood probability estimates in a logit response function
title_full Approximate sampling variances of maximum-likelihood probability estimates in a logit response function
title_fullStr Approximate sampling variances of maximum-likelihood probability estimates in a logit response function
title_full_unstemmed Approximate sampling variances of maximum-likelihood probability estimates in a logit response function
title_short Approximate sampling variances of maximum-likelihood probability estimates in a logit response function
title_sort approximate sampling variances of maximum likelihood probability estimates in a logit response function
topic sampling
statistical methods
url https://hdl.handle.net/10568/50190
work_keys_str_mv AT regejeo approximatesamplingvariancesofmaximumlikelihoodprobabilityestimatesinalogitresponsefunction