Nonlinear mixed‐effects (NLME) models are commonly used in longitudinal studies such as pharmacokinetics and HIV viral dynamics studies. NLME models are often derived based on underlying data‐generating mechanisms, therefore the parameters in these models often have natural physical interpretations that may suggest reasonable constraints on certain parameters. For example, the HIV viral decay rates for populations receiving anti‐HIV treatments may be reasonably expected to be nonnegative. Hypothesis testing for these parameters should incorporate practically reasonable constraints to increase statistical power. Motivated from HIV viral dynamic models, in this article we propose multiparameter one‐sided or constrained tests for NLME models with censored responses, for example, viral dynamic models with viral loads subject to lower detection limits. We propose approximate likelihood‐based tests that are computationally efficient. We evaluate the tests via simulations and show that the proposed tests are more powerful than the corresponding two‐sided or unrestricted tests. We apply the proposed tests to two AIDS datasets with new findings.

中文翻译：

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具有审查响应的非线性混合效应模型的多参数单边测试

非线性混合效应（NLME）模型通常用于纵向研究中，例如药代动力学和HIV病毒动力学研究。NLME模型通常是基于基础数据生成机制派生的，因此，这些模型中的参数通常具有自然的物理解释，可能暗示对某些参数的合理约束。例如，可以合理地预期接受抗HIV治疗的人群的HIV病毒衰减率是非阴性的。对这些参数的假设检验应结合实际合理的约束条件，以提高统计功效。根据HIV病毒动力学模型，在本文中，我们提出了针对带有审查响应的NLME模型的多参数单边或约束测试，例如，病毒载量受较低检测限限制的病毒动力学模型。我们提出了基于近似似然的测试，该测试在计算上是有效的。我们通过仿真对测试进行评估，结果表明，所提出的测试比相应的双向或无限制测试更强大。我们将建议的测试应用于具有新发现的两个艾滋病数据集。