비판적 논문 검토
대부분의 논문은 보여준 것보다 조금 더 주장합니다. 이 논문이 어디서 그러는지 보세요.
Reading a paper critically means holding two questions apart: is this study sound, and does its conclusion follow from what it found. The second is where most published papers slip, usually mildly — a correlational design described in causal language, a subgroup result reported as though it were the primary outcome, a conclusion stated for a population broader than the sample. None of that requires a statistics background to notice once you know the shapes. Checklists such as CASP and Newcastle-Ottawa formalise the first question; the second is judgement, and it is the one that decides whether you can cite the paper for the claim you wanted.
What is the most common overreach in published papers?
Causal language for a correlational design, and conclusions stated for a population wider than the sample supports.
Do I need statistics to appraise a study?
Less than people assume. Most overreach is visible in the mismatch between design and conclusion, which is a logical rather than statistical problem.
Which checklist should I use?
One matched to the design: CASP for many types, Newcastle-Ottawa for observational studies, Cochrane RoB for trials. The design decides the tool.