Restriction of range corrections when both distribution and selection assumptions are violated
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Restriction of range corrections when both distribution and selection assumptions are violated
Authors
Published Date
1983
Publisher
Type
Article
Abstract
In validating a selection test (x) as a predictor of y,
an incomplete xy data set must often be dealt with. A
well-known correction formula is available for estimating
the xy correlation in some total group using the
xy data of the selected cases and x data of the unselected
cases. The formula yields the r[subscript yх] correlation (1)
when the regression of y on x is linear and homoscedastic
and (2) when selection can be assumed to be
based on x alone. Although previous research has considered
the accuracy of the correction formula when
either Condition 1 or 2 is violated, no studies have
considered the most realistic case where both Conditions
1 and 2 are simultaneously violated. In the present
study six real data sets and five simulated selection
models were used to investigate the accuracy of the
correction formula when neither assumption is satisfied.
Each of the data sets violated the linearity and/or
homogeneity assumptions. Further, the selection
models represent cases where selection is not a function
of x alone. The results support two basic conclusions.
First, the correction formula is not robust to violations
in Conditions 1 and 2. Reasonably small
errors occur only for very modest degrees of selection.
Secondly, although biased, the correction formula can
be less biased than the uncorrected correlation for certain
distribution forms. However, for other distribution
forms, the corrected correlation can be less accurate
than the uncorrected correlation. A description of this
latter type of distribution form is given.
Keywords
Description
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Gross, Alan L & Fleischman, Lynn. (1983). Restriction of range corrections when both distribution and selection assumptions are violated. Applied Psychological Measurement, 7, 227-237. doi:10.1177/014662168300700210
Suggested citation
Gross, Alan L.; Fleischman, Lynn E.. (1983). Restriction of range corrections when both distribution and selection assumptions are violated. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/114842.
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.