John Ioannidis argues that "claimed research findings may often be simply accurate measures of the prevailing bias." He lists the following factors as those that make a paper with a positive result more likely to enter the literature and suppress negative-result papers: * The studies conducted in a field have small sample sizes. * The effect sizes in a field tend to be smaller. * There is both a greater number and lesser preselection of tested relationships. * There is greater flexibility in designs, definitions, outcomes, and analytical modes. * There are prejudices (financial interest, political, or otherwise). * The scientific field is hot and there are more scientific teams pursuing<unk> . Other factors include experimenter bias and white hat bias.
Publication bias
Information bias 
Funding bias
Recall bias
Length time bias
Ceiling effect 
Lead time bias
Age bias 