One-Arm Analysis

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 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)


1. DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled Clinical Trials. 1986.

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.