Assessing Type I error and power of multistate Markov models for panel data—A simulation study. Issue 9 (21st October 2017)

• Record Type: Journal Article
• Authors: Cassarly, Christy; Martin, Renee' H.; Chimowitz, Marc; Peña, Edsel A.; Ramakrishnan, Viswanathan; Palesch, Yuko Y.
• Is Part Of: Communications in statistics. Volume 46:Issue 9(2017)
• Page Start: 7040
• Page End: 7061
• Publication Date: 2017-10-21
• Subjects: Multistate models -- Panel data -- Power -- Stroke -- Type I error; Primary 60J27 -- Secondary 65C60; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2016.1222425
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: 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.