Abstract
"Variance accounted for" - calculated by squaring one of the various measures of association - is the most common estimate of experimental effect or strength of association reported in communication studies. However, methodologists in other social science disciplines have made compelling cases that the statistic itself, not its square, is the appropriate index of shared variation. The basic principles and arguments for interpreting unsquared measures of effect are presented and the implications for the practice of communication theory and research are discussed.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 605-611 |
| Number of pages | 7 |
| Journal | Human Communication Research |
| Volume | 28 |
| Issue number | 4 |
| DOIs | |
| State | Published - Oct 2002 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Communication
Cite this
Do We Know a Vector from a Scalar? Why Measures of Association (not Their Squares) Are Appropriate Indices of Effect. / Beatty, Michael.
In: Human Communication Research, Vol. 28, No. 4, 10.2002, p. 605-611.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Do We Know a Vector from a Scalar?
T2 - Why Measures of Association (not Their Squares) Are Appropriate Indices of Effect
AU - Beatty, Michael
PY - 2002/10
Y1 - 2002/10
N2 - "Variance accounted for" - calculated by squaring one of the various measures of association - is the most common estimate of experimental effect or strength of association reported in communication studies. However, methodologists in other social science disciplines have made compelling cases that the statistic itself, not its square, is the appropriate index of shared variation. The basic principles and arguments for interpreting unsquared measures of effect are presented and the implications for the practice of communication theory and research are discussed.
AB - "Variance accounted for" - calculated by squaring one of the various measures of association - is the most common estimate of experimental effect or strength of association reported in communication studies. However, methodologists in other social science disciplines have made compelling cases that the statistic itself, not its square, is the appropriate index of shared variation. The basic principles and arguments for interpreting unsquared measures of effect are presented and the implications for the practice of communication theory and research are discussed.
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UR - http://www.scopus.com/inward/citedby.url?scp=0036412412&partnerID=8YFLogxK
U2 - 10.1093/hcr/28.4.605
DO - 10.1093/hcr/28.4.605
M3 - Article
AN - SCOPUS:0036412412
VL - 28
SP - 605
EP - 611
JO - Human Communication Research
JF - Human Communication Research
SN - 0360-3989
IS - 4
ER -