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DClinPsy.Prep

Statistics · Core

Reliability and validity

Reliability is consistency; validity is whether the measure captures what it claims to. A measure can be highly reliable and completely invalid — consistently measuring the wrong thing — but it cannot be valid without being reliable.

Types of reliability

  • Internal consistency — do items measure the same construct? Cronbach’s alpha, where roughly .7 to .9 is acceptable. Above .95 suggests redundant items.
  • Test-retest — stability over time, assuming the construct itself is stable.
  • Inter-rater — agreement between raters. Cohen’s kappa corrects for chance agreement; raw percentage agreement does not.
  • Parallel forms — agreement between equivalent versions.

Types of validity

  • Face — does it look appropriate? The weakest form.
  • Content — does it cover the whole construct?
  • Criterion — does it agree with an external standard? Concurrent (now) or predictive (later).
  • Construct — does it behave as the theory says it should? Convergent validity with related measures, discriminant validity with unrelated ones.
  • Ecological — do findings generalise to real settings?

Threats to internal validity

Internal validity is whether the study supports a causal claim. Common threats are history, maturation, regression to the mean, selection bias, attrition and testing effects.

Regression to the mean is particularly important clinically: people typically present at their worst, so improvement follows even without treatment. This is a large part of why control groups exist.

Where marks get lost

  • Assuming a reliable measure is therefore valid.
  • Reporting percentage agreement rather than kappa for inter-rater reliability.
  • Attributing improvement in an uncontrolled study to the intervention when regression to the mean would predict it anyway.

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