Summary of problems, in roughly temporal order as they afflicted the study in question:
1. priors for the phenomenon imply many small correlates, and past results have failed to replicate
2. low statistical power for claimed results, from both planned & post hoc perspective
3. small sample biases: can't estimate accurately (without relatively exotic techniques) when p>n
4. measurement error in diagnosing depression: investigators chose a self-report of lower reliability compared to the available alternative data from a more reliable interview that they had,
5. substantial & likely biased attrition of subjects
6. correlational result is confounded by antidepressant usage, smoking, etc (many things correlate with being depressed, so any blood test may be picking out those instead) and by the small sample size, results may not generalize
7. failing multiple-comparison correction of final results
#statistics #psychology #depression
1. priors for the phenomenon imply many small correlates, and past results have failed to replicate
2. low statistical power for claimed results, from both planned & post hoc perspective
3. small sample biases: can't estimate accurately (without relatively exotic techniques) when p>n
4. measurement error in diagnosing depression: investigators chose a self-report of lower reliability compared to the available alternative data from a more reliable interview that they had,
5. substantial & likely biased attrition of subjects
6. correlational result is confounded by antidepressant usage, smoking, etc (many things correlate with being depressed, so any blood test may be picking out those instead) and by the small sample size, results may not generalize
7. failing multiple-comparison correction of final results
#statistics #psychology #depression
