Meta-analytic reliability generalizations (RGs) are limited by the scarcity of reliability reporting in primary articles, and currently, RG investigators lack a method to quantify the impact of such nonreporting. This article introduces a stepwise procedure to address this challenge. First, the authors introduce a formula that allows researchers to estimate the lower bound population average reliability for a desired instrument. Second, they present an equation to determine the Fail-Safe N for RG. This equation estimates the number of ''file drawer'' studies required to drop the aggregate score reliability of an instrument below a specified criterion value. Finally, the authors demonstrate the utility of these equations using published RG studies. Comments on the conclusions drawn from each RG application are provided.
Identifer | oai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etsu-works-18690 |
Date | 01 January 2008 |
Creators | Howell, Ryan, Shields, Alan L. |
Publisher | Digital Commons @ East Tennessee State University |
Source Sets | East Tennessee State University |
Detected Language | English |
Type | text |
Source | ETSU Faculty Works |
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