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首页> 外文期刊>Journal of statistical computation and simulation >Gompertz model with time-dependent covariate in the presence of interval-, right- and left-censored data
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Gompertz model with time-dependent covariate in the presence of interval-, right- and left-censored data

机译:在存在区间删减,右删减和数据删减的情况下具有时间相关协变量的Gompertz模型

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摘要

In this paper, the Gompertz model is extended to incorporate time-dependent covariates in the presence of interval-, right-, left-censored and uncensored data. Then, its performance at different sample sizes, study periods and attendance probabilities are studied. Following that, the model is compared to a fixed covariate model. Finally, two confidence interval estimation methods, Wald and likelihood ratio (LR), are explored and conclusions are drawn based on the results of the coverage probability study. The results indicate that bias, standard error and root mean square error values of the parameter estimates decrease with the increase in study period, attendance probability and sample size. Also, LR was found to work slightly better than the Wald for parameters of the model.
机译:在本文中,对Gompertz模型进行了扩展,以在存在区间,右,左删减和未经删减的数据的情况下合并时间相关的协变量。然后,研究了它在不同样本量,研究时间和出勤率下的表现。之后,将模型与固定协变量模型进行比较。最后,探讨了两种置信区间估计方法,即Wald和似然比(LR),并根据覆盖概率研究的结果得出了结论。结果表明,参数估计值的偏差,标准误差和均方根误差值随研究时间,出勤率和样本量的增加而降低。此外,发现LR在模型参数方面比Wald稍好。

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