Statistical Conclusion Validity

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

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