Kenward-Roger Method for Small Sample Inference in Mixed Models
View Presentation *Min Zhu, SAS Institute Inc. Keywords: Small Sample Inference, Mixed Model, Kenward-Roger Method, Degrees of Freedom Method Linear mixed models have become a popular framework for analyzing data that have complicated design and structured covariance. It is known that exact test is not available for fixed effects except for balanced data and special covariance structures. Test statistics based on asymptotic distribution of parameter estimates are useful for large samples. However, these tests can be unreliable in applications with small sample sizes. Kenward and Roger (KR) proposed a scaled Wald-Type statistic and a method to approximate its small sample distribution. This presentation discusses the motivation and approach of the Kenward-Roger method. This presentation also describes caveats of the Kenward-Roger method as it applies to a nonlinear covariance structure and how these caveats motivated the latest improvement for the Kenward-Roger approach (Kenward and Roger 2009).
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Key Dates
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April 30 - May 22, 2013
Invited Abstract Submission Open -
June 4, 2013
Online Registration Opens -
August 9 - August 23, 2013
Invited Abstract Editing -
August 23, 2013
Short Course materials due from Instructors -
August 26, 2013
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September 9, 2013
Cancellation Deadline and Registration Closes @ 11:59 pm EDT -
September 16 - September 18, 2013
Marriott Wardman Park, Washington, DC