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A transition model for ordinal response data with random drop-out: An application to fluvoxamine data

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A transition model for ordinal response data with random drop-out: An application to fluvoxamine data. / Rezaei, Z; Ganjali, M; Berridge, Damon.
In: Journal of Biopharmaceutical Statistics, Vol. 19, No. 4, 08.2009, p. 658-671.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Rezaei, Z, Ganjali, M & Berridge, D 2009, 'A transition model for ordinal response data with random drop-out: An application to fluvoxamine data', Journal of Biopharmaceutical Statistics, vol. 19, no. 4, pp. 658-671. https://doi.org/10.1080/10543400902964100

APA

Rezaei, Z., Ganjali, M., & Berridge, D. (2009). A transition model for ordinal response data with random drop-out: An application to fluvoxamine data. Journal of Biopharmaceutical Statistics, 19(4), 658-671. https://doi.org/10.1080/10543400902964100

Vancouver

Rezaei Z, Ganjali M, Berridge D. A transition model for ordinal response data with random drop-out: An application to fluvoxamine data. Journal of Biopharmaceutical Statistics. 2009 Aug;19(4):658-671. doi: 10.1080/10543400902964100

Author

Rezaei, Z ; Ganjali, M ; Berridge, Damon. / A transition model for ordinal response data with random drop-out : An application to fluvoxamine data. In: Journal of Biopharmaceutical Statistics. 2009 ; Vol. 19, No. 4. pp. 658-671.

Bibtex

@article{3250348fd6f3452f84aa8e3d80109f3e,
title = "A transition model for ordinal response data with random drop-out: An application to fluvoxamine data",
abstract = "Many methods are available to analyze incomplete longitudinal ordinal responses. In this paper a general transition model is proposed for longitudinal ordinal responses with random dropout. Maximum likelihood estimates are obtained for the transition probabilities when there are repeated observations. The likelihood function of the general model is partitioned to make possible the use of existing software to estimate model parameters. Some reduced forms of the model are also considered where for estimation of parameters in these models one has to use numerical optimization methods. The approach is applied to the well-known Fluvoxamine data. For these data, two important results, which have not been previously reported, are obtained: (1) some transition probabilities are estimated to be zero and (2) the model for current response, which conditions on previous response, removes the effects of some covariates that had previously been significant.",
keywords = "Backward approach, Cumulative logit model, Gamma, Longitudinal ordinal response data, Partial Correlation , Random dropout",
author = "Z Rezaei and M Ganjali and Damon Berridge",
year = "2009",
month = aug,
doi = "10.1080/10543400902964100",
language = "English",
volume = "19",
pages = "658--671",
journal = "Journal of Biopharmaceutical Statistics",
issn = "1054-3406",
publisher = "Taylor and Francis Ltd.",
number = "4",

}

RIS

TY - JOUR

T1 - A transition model for ordinal response data with random drop-out

T2 - An application to fluvoxamine data

AU - Rezaei, Z

AU - Ganjali, M

AU - Berridge, Damon

PY - 2009/8

Y1 - 2009/8

N2 - Many methods are available to analyze incomplete longitudinal ordinal responses. In this paper a general transition model is proposed for longitudinal ordinal responses with random dropout. Maximum likelihood estimates are obtained for the transition probabilities when there are repeated observations. The likelihood function of the general model is partitioned to make possible the use of existing software to estimate model parameters. Some reduced forms of the model are also considered where for estimation of parameters in these models one has to use numerical optimization methods. The approach is applied to the well-known Fluvoxamine data. For these data, two important results, which have not been previously reported, are obtained: (1) some transition probabilities are estimated to be zero and (2) the model for current response, which conditions on previous response, removes the effects of some covariates that had previously been significant.

AB - Many methods are available to analyze incomplete longitudinal ordinal responses. In this paper a general transition model is proposed for longitudinal ordinal responses with random dropout. Maximum likelihood estimates are obtained for the transition probabilities when there are repeated observations. The likelihood function of the general model is partitioned to make possible the use of existing software to estimate model parameters. Some reduced forms of the model are also considered where for estimation of parameters in these models one has to use numerical optimization methods. The approach is applied to the well-known Fluvoxamine data. For these data, two important results, which have not been previously reported, are obtained: (1) some transition probabilities are estimated to be zero and (2) the model for current response, which conditions on previous response, removes the effects of some covariates that had previously been significant.

KW - Backward approach

KW - Cumulative logit model

KW - Gamma

KW - Longitudinal ordinal response data

KW - Partial Correlation

KW - Random dropout

UR - http://www.scopus.com/inward/record.url?scp=70449688339&partnerID=8YFLogxK

U2 - 10.1080/10543400902964100

DO - 10.1080/10543400902964100

M3 - Journal article

AN - SCOPUS:70449688339

VL - 19

SP - 658

EP - 671

JO - Journal of Biopharmaceutical Statistics

JF - Journal of Biopharmaceutical Statistics

SN - 1054-3406

IS - 4

ER -