Assessing type I error and power of multistate Markov models for panel data-A simulation study.

Assessing type I error and power of multistate Markov models for panel data-A simulation study.
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DOI:
10.1080/03610918.2016.1222425
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发表时间:
2017
期刊:
Communications in statistics: Simulation and computation
影响因子:
--
通讯作者:
Palesch YY
Palesch YY
中科院分区:
其他
文献类型:
--
作者:
Cassarly C;Martin RH;Chimowitz M;Peña EA;Ramakrishnan V;Palesch YY

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在多次随访访视时收集的有序结局在临床试验中很常见。有时,选择一次访问进行初步分析,规模被一分为二,相当于信息丢失。多状态马尔可夫模型描述了一个过程如何随着时间的推移在状态之间移动。在这里,模拟研究进行调查的I型错误和功率特性的多状态马尔可夫模型的面板数据与有限的非相邻状态转移。结果表明,多状态马尔可夫模型保持I型错误和足够的权力是实现与有限的非相邻状态转移的面板数据与适度的样本量。
Ordinal outcomes collected at multiple follow-up visits are common in clinical trials. Sometimes, one visit is chosen for the primary analysis and the scale is dichotomized amounting to loss of information. Multistate Markov models describe how a process moves between states over time. Here, simulation studies are performed to investigate the type I error and power characteristics of multistate Markov models for panel data with limited non-adjacent state transitions. The results suggest that the multistate Markov models preserve the type I error and adequate power is achieved with modest sample sizes for panel data with limited non-adjacent state transitions.
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