Using the extreme groups strategy when measures are not normally distributed
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Using the extreme groups strategy when measures are not normally distributed
Authors
Published Date
1992
Publisher
Type
Article
Abstract
The extreme groups research strategy is a two-stage
measurement procedure that may be
employed when it is relatively simple and inexpensive
to obtain data on a psychological variable (X)
in the first stage of investigation, but it is quite
complex and expensive to measure subsequently a
second variable (Y). This strategy is related to the
selection of upper and lower groups for item discrimination
analysis (Kelley, 1939) and to the
treatments x blocks design in which participants
are first "blocked" on the X variable and then
only the extreme (highest and lowest means) blocks
are compared on the Y variable, usually by a t test
or an analysis of variance. Feldt (1961) showed
analytically that if the population correlation
coefficient between X and Y is p = .10, the power
of the t test is maximized if each extreme group
consists of 27% of the population tested on the X
variable. However, Feldt’s derivation assumes that
the X and Y variables are normally distributed. The
present study employed a monte carlo simulation
to explore the question of how to optimize power
in the extreme groups strategy when sampling from
non-normal distributions. The results showed that
the optimum percent for the extreme group selection
was approximately the same for all population
shapes except for the extremely platykurtic (uniform)
distribution. The power of the extreme groups
strategy under conditions of normality was compared
to the power of other research strategies,
and an extension of the extreme groups approach
was developed and applied in an example. Index
terms: construct validation; extreme-group design;
monte carlo technique; non-normal distributions;
statistical power; upper-lower index.
Keywords
Description
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Fowler, Robert L. (1992). Using the extreme groups strategy when measures are not normally distributed. Applied Psychological Measurement, 16, 249-259. doi:10.1177/014662169201600305
Other identifiers
doi:10.1177/014662169201600305
Suggested citation
Fowler, Robert L.. (1992). Using the extreme groups strategy when measures are not normally distributed. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/115653.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.