NDLI: Approximate Simultaneous Nonparametric Confidence Intervals for All Pair-Wise Comparisons and Comparisons with a Designated (Control) Group in a One-Way Layout Using the SAS ® System

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Approximate Simultaneous Nonparametric Confidence Intervals for All Pair-Wise Comparisons and Comparisons with a Designated (Control) Group in a One-Way Layout Using the SAS ® System

Content Provider	Semantic Scholar
Author	Juneau, Paul L. Sikka, Aditya Qiao, Jiawei Gayari, Michelle
Copyright Year	2007
Abstract	The SAS ® System (Version 9) presents users with the ability to perform standard parametric multiple comparisons for a one-way layout with PROC GLM and PROC MIXED using the means and lsmeans statements, respectively. Options in these statements exist to construct simultaneous confidence intervals for all pair-wise comparisons or all pair-wise comparisons with a designated (control) group and may be used under circumstances where the measurement error is approximately Gaussian (normal). It is quite common in the early phases of medical research for investigators to have limited knowledge regarding the distributional properties of their measurements (Juneau, 2007). Moreover, in later phases of clinical research, previous experience with important efficacy measurements suggests that the distributional nature of the errors associated with some of them is non-Gaussian. To date, SAS ® code exists to perform simultaneous nonparametric inference for all pair-wise comparisons and all pair-wise comparisons with a control group (Juneau, 2007), but not to construct the corresponding interval estimates. In this presentation, the speaker will introduce some original SAS ® code to construct approximate simultaneous confidence intervals for all pair-wise comparisons and all pair-wise treatment comparisons with a designated control group from measurements occurring in a one-way layout with errors that are non-Gaussian. After illustrating a statistical solution for this setting, the speaker will discuss the flow of this macro code, illustrate its usage and output and demonstrate the application of the program to the analysis of a real data set from a medical investigation in cancer research.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.pharmasug.org/download/bestpapers2008/sp/SP05.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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