Statistical conclusion validity refers to the appropriate use of statistics to infer whether the presumed independent and dependent variables covary (Cook & Campbell, 1979). It concerns two related statistical inferences: (1) whether the presumed cause and effect covary and (2) how strongly they covary.
The most common threats to statistical conclusion validity are:
- Low statistical power
- Violated assumptions of the test statistics
- Fishing and the error rate problem
- Unreliability of measures
- Restriction of range
- Unreliability of treatment implementation
- Extraneous variance in the experimental setting
- Heterogeneity of the units under study
- Inaccurate effect size estimation
Read more about Statistical Conclusion Validity: See Also
Famous quotes containing the words conclusion and/or validity:
“The conclusion suggested by these arguments might be called the paradox of theorizing. It asserts that if the terms and the general principles of a scientific theory serve their purpose, i. e., if they establish the definite connections among observable phenomena, then they can be dispensed with since any chain of laws and interpretive statements establishing such a connection should then be replaceable by a law which directly links observational antecedents to observational consequents.”
—C.G. (Carl Gustav)
“It does not follow, because our difficulties are stupendous, because there are some souls timorous enough to doubt the validity and effectiveness of our ideals and our system, that we must turn to a state controlled or state directed social or economic system in order to cure our troubles.”
—Herbert Hoover (1874–1964)