BACKGROUND:Meta-analysis is an approach that combines findings from similar studies. The aggregation of study-level data can provide precise estimates for outcomes of interest, allow for unique treatment comparisons, and explain differences arising from conflicting study results. Proper meta-analysis includes five basic steps: identify relevant studies; extract summary data; compute study effect sizes, perform statistical analysis; and interpret and report the results. OBJECTIVES: This study aims to review meta-analysis methods and their assumptions, apply various meta-techniques to empirical data, and compare the results from each method. METHODS: Three different meta-analysis techniques were applied to a dataset examining the effects of the bacille Calmette-Guerin (BCG) vaccine on tuberculosis (TB). Fixed-effect, random-effect modeling and meta-regression were applied for analysis, with added study-level covariates. Overall and stratified results, by geographic latitude were reported. RESULTS: Estimates of treatment effect differed depending on the technique applied. When a fixed effect model was applied to estimate the effect of a vaccination against tuberculosis, the log odds ratio was -0.436 (confidence interval [CI: -0.528, -0.344]).  After testing for heterogeneity and fitting a random effects model, the estimate was reduced to -0.741 (CI [-1.12, -0.352]), and the CI became wider.  When covariates were added to the model to explain the heterogeneity, the treatment effect was reduced even further. All three techniques showed statistically significant effects from the vaccination.  However, once covariates were added, efficacy diminished.  Independent variables, such as the latitude of the location in which the study was performed, appeared to be partially driving the results. CONCLUSIONS: Meta-analysis is useful to draw general conclusions from a variety of studies. However, proper study and model selection are important to ensure the correct interpretation of results. Basic meta-analysis models are fixed-effects, random-effects, and meta-regression.