Reader Comments
Post a new comment on this article
Post Your Discussion Comment
Please follow our guidelines for comments and review our competing interests policy. Comments that do not conform to our guidelines will be promptly removed and the user account disabled. The following must be avoided:
- Remarks that could be interpreted as allegations of misconduct
- Unsupported assertions or statements
- Inflammatory or insulting language
Thank You!
Thank you for taking the time to flag this posting; we review flagged postings on a regular basis.
closeIndependent Teams
Posted by plosmedicine on 31 Mar 2009 at 00:14 GMT
Author: Grayson Palmer
Position: Student
Institution: UCSF
E-mail: GraysonPalmer@gmail.com
Submitted Date: October 03, 2007
Published Date: October 4, 2007
This comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.
Dr. Ioannidis is correct in saying that as more researchers look into the same question that, by chance, researchers will obtain incorrect results. However this does not mean that most research findings are false. The chance of obtaining erroneous results is based on the P-value. The strength of research comes by meta-analysis of the "whole" of the research. Those who perform meta analysis’s realize there is erroneous research and place strict criteria to eliminate bias in all forms.
Also large randomized control studies are the best research possible because researchers are able to control variables and create double and even triple blind experiments to greatly reduce bias and even reveal actual cause and effect of variables not just correlation.