Non‐parametric Tests for Censored Data

Bagdonavičius, Vilijandas; Kruopis, Julius; Nikulin, Mikhaïl

doi:10.1002/9781118558072

Cited by 48 publications

(36 citation statements)

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“…(Kennedy, 1951;Munro, 1974;Olin et al, 2004). If traps become saturated at a level of catch unrelated to actual abundance, then statistical models for censored data may be useful (Bagdonavicus et al, 2011). Another factor that may affect trap saturation is changes in feeding motivation of fi shes with time of day or light levels.…”

Section: Figurementioning

confidence: 99%

Influence of soak time and fish accumulation on catches of reef fishes in a multispecies trap survey

Bacheler¹,

Bartolino²,

Reichert³

2013

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Abstract-Catch rates from fisheryindependent surveys often are assumed to vary in proportion to the actual abundance of a population, but this approach assumes that the catchability coefficient (q) is constant. When fish accumulate in a gear, the rate at which the gear catches fish can decline, and, as a result, catch asymptotes and q declines with longer fishing times. We used data from long-term trap surveys in the southeastern U.S. Atlantic to determine whether traps saturated for 8 reef fish species because of the amount of time traps soaked or the level of fish accumulation (the total number of individuals of all fish species caught in a trap). We used a deltageneralized-additive model to relate the catch of each species to a variety of predictor variables to determine how catch was influenced by soak time and fish accumulation after accounting for variability in catch due to the other predictor variables in the model. We found evidence of trap saturation for all 8 reef fish species examined. Traps became saturated for most species across the range of soak times examined, but trap saturation occurred for 3 fish species because of fish accumulation levels in the trap. Our results indicate that, to infer relative abundance levels from catch data, future studies should standardize catch or catch rates with nonlinear regression models that incorporate soak time, fish accumulation, and any other predictor variable that may ultimately influence catch. Determination of the exact mechanisms that cause trap saturation is a critical need for accurate stock assessment, and our results indicate that these mechanisms may vary considerably among species.

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Section: Figurementioning

confidence: 99%

Influence of soak time and fish accumulation on catches of reef fishes in a multispecies trap survey

Bacheler¹,

Bartolino²,

Reichert³

2013

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“…A Chi square like test has been designed for ver ification of this model on the base of data from mortal ity tables used in demography [28]. The case of cen sored data used in longevity analysis is considered in [8,9,21,38].…”

Section: Gompertz and Makeham Distributionsmentioning

confidence: 99%

“…Various statistical methods and their efficiency in anal ysis of biomedical data are described in [21,43,47].…”

Section: Kaplan-meier's Estimator For the Survival Functionmentioning

confidence: 99%

“…In the most recent 30 years, starting from the famous Cox publication [25], great progress has been made in the construction of parametric, nonparamet ric, and semiparametric models for analysis of data on survival, aging, longevity, fatigue, and degradation with regard to the patients' records expressed in terms of explanatory time variables. In addition, statistical analysis methods have been developed to apply these models to censored data [8,21,36,38,41]. As we can not encompass all these results here, we dwell on recent achievements and those that have been poorly elucidated in the Russian literature on longevity, aging, and survival.…”

Section: Introduction To Regression Models Of Accelerated Agingmentioning

confidence: 99%

“…Modern dynamic regression models are suitable for investigation of biologic systems changing with time. We outline some models and methods most commonly used in survival analysis nowadays [7,21,32,34,36,38].…”

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Statistical models of longevity, aging, and degradation in demography, gerontology, and oncology

2012

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Several interesting reports concerning problems of mathematical modeling in connection with studies of aging and longevity have recently been published [1, 2,4,7,10]. Following the main idea of these and some other papers dedicated to this topic, we consider some approaches to construction of statistical models for demography, gerontology, oncology, etc. Modern dynamic regression models are suitable for investigation of biologic systems changing with time. We outline some models and methods most commonly used in survival analysis nowadays [7,21,32,34,36,38].

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2011

Non‐parametric Tests for Complete Data

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Non‐parametric Tests for Censored Data

Cited by 48 publications

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Influence of soak time and fish accumulation on catches of reef fishes in a multispecies trap survey

Influence of soak time and fish accumulation on catches of reef fishes in a multispecies trap survey

Statistical models of longevity, aging, and degradation in demography, gerontology, and oncology

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