- #1
phoenix95
Gold Member
- 81
- 22
I have been reading statistics for a while (I am a physics major but also a stat-enthusiast), and one of the topics that drew my attention was the misrepresentation, or to be precise, misinterpretation of the data. This came up while reading about Simpson's paradox and the likes. When I see journals that analyze data using statistical tools, I never actually see the data most of the time but I know that the reviewers have access to it. I wonder what the screening/peer-review process for the said studies might be? In other words, how do the reviewers know that the study is misleading?
For instance, take the UK cigarette study example given in this video (time-stamp: 2:21) And the researcher came to you to submit the paper. For a moment assume that he was a rookie grad-student who didn't bother noting the age of the participants. Now the data seems to conclude that smokers have a higher survival rate. But you, the reviewer don't know about the hidden variable that is the age group. So how do you pass the study as publish worthy? Or for the same matter, how do you know that any study is not misleading?
For instance, take the UK cigarette study example given in this video (time-stamp: 2:21) And the researcher came to you to submit the paper. For a moment assume that he was a rookie grad-student who didn't bother noting the age of the participants. Now the data seems to conclude that smokers have a higher survival rate. But you, the reviewer don't know about the hidden variable that is the age group. So how do you pass the study as publish worthy? Or for the same matter, how do you know that any study is not misleading?