Repeated Measures Model

Helge Toutenburg
Additional contact information
Helge Toutenburg: University of Munich, Institute of Statistics

Chapter 7 in Experimental Design and Model Choice, 1995, pp 217-262 from Springer

Abstract: Abstract In contrast to the previous chapters, we now assume that instead of having only one observation per object/subject (e.g., patient) we now have repeated observations. These repeated measurements are collected at previously exactly defined times. The principle idea is that these observations give information about the development of a response Y. This response might for instance be the blood pressure (measured every hour) for a fixed therapy (medicament A), the blood sugar level (measured every day of the week) or the monthly training performance of sprinters for training method A etc., that is variables which change with time (or a different scale of measurement). The aim of a design like this is not so much the description of the average behaviour of a group (with a fixed treatment), rather than the comparison of two or more treatments in their effect across the scale of measurement (e.g., time), that is the treatment or therapy comparison..

Keywords: Saturated Model; Loglinear Model; Independence Model; Blood Pressure Lowering Effect; Compound Symmetry (search for similar items in EconPapers)
Date: 1995
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-52498-1_7

Ordering information: This item can be ordered from
http://www.springer.com/9783642524981

DOI: 10.1007/978-3-642-52498-1_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().