Research in animal nutrition and physiology, primarily requires processing and modeling of nutritional data. In certain fields of research, the number of publications and results per publications is vast. Results from single classical experiment cannot be the basis for a large inference space because the conditions under which observations are made in a single experiment are generally very narrow. A single experimentation generally measures the effect of one or two variables while maintaining all other factors as constant as possible. Often these experiments are repeated by other workers/labs to verify the generalization and repeatability of the observations and sometime to challenge the range of applicability of observed results and conclusions. This leads to large number of similar studies being carried out and research papers published, even on a relatively narrow research domain. Often researchers are confused with the different results of similar research. In this context, there is a need to summarize the results across all the published studies. In such instances, the statistical methods dealing with the analysis of literature data, known as meta-analysis is used.
Meta-analysis, Animal nutritional data, Results and published article
