DataParty uses Python 3.8.10 for data analysis with the following packages: Matplotlib (3.4.1), NumPy (1.20.2), Pandas (1.2.3), and SciPy (1.5.2).

Forest Plots

For one-arm analysis of data, DataParty supports (but advises against) the meta-analysis of original proportions. For dichotomous data, DataParty includes 2 transformation functions: (1) logit and (2) arcsine square root. For data with original proportions, the logit transformation function is available. The inverse variance method is used for meta-analysis. The DerSimonian-Laird method is implemented for the random effects model.(1)

Meta-Regression

Meta-regression is performed with the logit function. Coefficients express the impact of the independent variable(s) on the logit of proportions. DataParty back-transforms the logit of proportions exclusively for visualization. For fixed effects, the inverse variance method is used. For the random effects model, DataParty implements a DerSimonian-Laird method of moments estimator.(2)

References

1. DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled Clinical Trials. 1986. https://doi.org/10.1016/0197-2456(86)90046-2

2. Veronicki AA, Jackson D, Viechtbauer W, Bender R, Bowden J, Knapp G, Kuss O, Higgins JPT, Langan D, Salanti G. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Research Synthesis Methods. 2014. https://doi.org/10.1002/jrsm.1164