Quantitative Literature Review

According to Guzzo, et.al. (1987), meta-analysis is a quantitative form of literature review. Literature reviews are acknowledged as valuable contributions to the advancement of science. If done well, it helps researchers sum up where researches have been and where they need to go next. It identifies gaps in new knowledge and suggests new directions for future research. Reviews of research literature are carried out for several reasons: (1) to assess the state of current knowledge; (2) to assess what is not known - the gaps of knowledge; (3) to advance theory; and (4) to provide statements about the policy implications of research findings. Also, good literature reviews can make strong statements about the validity of theories and can stimulate

It investigates not only the reported results of the studies but all aspects of research designs that produced them, including theoretical constructs, operational definitions of the independent or manipulated variable, moderating and mediating variables, and dependent variables, population samples, data collection procedures, statistical analysis, and especially the handling of possible confounding variables that would provide an alternative explanation for the reported results. Like primary research, meta-analysis proceeds by framing a research question to be addressed by sampling a defined population of completed primary hypotheses derived from the research question. In the context of research about the outcomes of interventions to preserve or enhance physical psychological, or social functioning, meta-analysis addresses two principal questions: (1) is there support in the sampled population for studies for the causal inference that the intervention made a statistically significant difference in the outcome(s)? And if so (2) how large an effect on differences did the intervention make? The substantive importance or significance of the size of the intervention effect is a separate matter that invokes value judgments based on criteria that are outside the scope of

At the problem formulation stage of meta- analysis involving specification of causally related variables, abstracting the content of primary studies that provide too little detail about how latent constructs are operationalized can mask the influence of interacting moderating and/or mediating variables that serve to explain cause – effect relationships. At the data collection stage, accessing primary studies that contain population samples that are so different because of exclusions from the intended target population that generalized application of the results to the target population is invalid. The definition of the target population can be so vague that it makes sample selection arbitrary, or the sample selected even with a clear definition does not represent the defined