Selective description of specific studies: Good literature reviews provide a concise overview of the research on a topic.They balance the need to be concise with the desire to provide deeper analysis. The choice of which articles are based on specific reasons.
When describing research good literature reviews provide a quick snapshot of the important elements of the research and the important findings, while at the same time not wasting precious words that could be spent on other issues.
Good literature review's “don’t lose the forest for the trees”.
Effect Size: The research literature is filled with findings of the form, there is a relationship between x and y or there is a difference between group A and group B on some variable.
Good literature reviews communicate information about effect sizes (e.g., correlations, Cohen’s d, odds ratio).
This is particularly important in literature reviews concerned with the practical importance of findings.
For example, in research looking at faking personality tests in selection and recruitment, reporting that (a) "student samples were able to increase their conscientiousness score on average by one standard deviation" (e.g., Cohen’s d = 1) when asked to fake is a lot clearer than reporting that "students were able to increase their conscientious score".
For example: It does not matter how many cross-sectional observational studies are conducted looking at the correlation between self-efficacy and performance, this does not prove that one variable causes the other.
Before writing about causality consider whether X could cause Y, Y could cause X, or whether a third variables could cause both X and Y to covary.
This examination of the theoretical literature is then integrated into the conclusions reached.
Causation: Good literature reviews demonstrate an understanding of proper causal inferences.