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
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