Models for Quantal Response Experiments Over Time

Petkau, A. John; Sitter, R. R.; Carter, E. M.; Hubert, J. J.

doi:10.2307/2531782

Cited by 19 publications

(8 citation statements)

References 18 publications

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“…I also excluded studies in which time series for a response variable (biological or chemical) were measured over a range of doses, usually to examine concentration-time relationships (e.g., changes in LC50 over time, or differences in uptake or elimination curves among doses). These studies can and often should be analyzed using repeated measures and related approaches, but those approaches may be more complex than the simple design in Table 1 [5][6][7]. Sixteen studies used or could have applied RM designs.…”

Section: Repeated Measures Designsmentioning

confidence: 99%

Repeated measures designs

Paine

1996

Enviro Toxic and Chemistry

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Section: Repeated Measures Designsmentioning

confidence: 99%

Repeated measures designs

Paine

1996

Enviro Toxic and Chemistry

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“…Petkau and Sitter (1989), subsequently denoted PS, suggested a Dirichlet-multinomial model to incorporate extra-multinomial variation, and reanalyzed the fish mortality data in Carter and Hubert (1984). Petkau and Sitter (1989), subsequently denoted PS, suggested a Dirichlet-multinomial model to incorporate extra-multinomial variation, and reanalyzed the fish mortality data in Carter and Hubert (1984).…”

Section: A Simulation Studymentioning

confidence: 99%

A Quasi-Likelihood Approach for Ordered Categorical Data with Overdispersion

Wang¹

1996

Biometrics

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JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. This content downloaded from 128.235.251.160 on Mon, SUMMARY Quasi-likelihood (QL) methods are often used to account for overdispersion in categorical data. This paper proposes a new way of constructing a QL function that stems from the conditional meanvariance relationship. Unlike traditional QL approaches to categorical data, this QL function is, in general, not a scaled version of the ordinary log-likelihood function. A simulation study is carried out to examine the performance of the proposed QL method. Fish mortality data from quantal response experiments are used for illustration.

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“…O'Hara Hines (1989) and O'Hara Hines and Lawless (1993) gave a good description of the related work on such problems. This problem is related to the grouped survival data problem (Prentice and Gloeckler, 1978;Lawless, 1982;Petkau and Sitter, 1989;Sinha et al, 1993;Sinha, 1993). The dependence of ®shes within a tank makes this problem dierent from ordinary grouped survival data with independent subjects.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Analysis of Multivariate Mortality Data with Large Families

Chen

Dey

Sinha

2000

Journal of the Royal Statistical Society Series C: Applied Statistics

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This paper presents a Bayesian method for the analysis of toxicological multivariate mortality data when the discrete mortality rate for each family of subjects at a given time depends on familial random effects and the toxicity level experienced by the family. Our aim is to model and analyse one set of such multivariate mortality data with large family sizes: the potassium thiocyanate (KSCN) tainted ®sh tank data of O'Hara Hines. The model used is based on a discretized hazard with additional time-varying familial random effects. A similar previous study (using sodium thiocyanate (NaSCN)) is used to construct a prior for the parameters in the current study. A simulationbased approach is used to compute posterior estimates of the model parameters and mortality rates and several other quantities of interest. Recent tools in Bayesian model diagnostics and variable subset selection have been incorporated to verify important modelling assumptions regarding the effects of time and heterogeneity among the families on the mortality rate. Further, Bayesian methods using predictive distributions are used for comparing several plausible models.

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Models for Quantal Response Experiments Over Time

Cited by 19 publications

References 18 publications

Repeated measures designs

Repeated measures designs

A Quasi-Likelihood Approach for Ordered Categorical Data with Overdispersion

Bayesian Analysis of Multivariate Mortality Data with Large Families

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