Meta-Analysis of Generalized Additive Models
Get maximum of the absolute standard deviations
Prepare heterogeneity data
metagam: Meta-analysis of generalized additive models.
Meta-analysis of generalized additive models
Plot estimated smooth terms
Plot between-study standard deviation
Dominance plot
Heterogeneity Plot
Heterogeneity p-plot
Heterogeneity Q-plot
Print method for metagam objects.
Print method for striprawdata
Print output from summary of metagam fit.
Strip rawdata from a generalized additive model
Summary method for metagam objects
Summary method for GAMs stripped for rawdata
Meta-analysis of generalized additive models and generalized additive mixed models. A typical use case is when data cannot be shared across locations, and an overall meta-analytic fit is sought. 'metagam' provides functionality for removing individual participant data from models computed using the 'mgcv' and 'gamm4' packages such that the model objects can be shared without exposing individual data. Furthermore, methods for meta-analysing these fits are provided. The implemented methods are described in Sorensen et al. (2020), <doi:10.1016/j.neuroimage.2020.117416>, extending previous works by Schwartz and Zanobetti (2000) and Crippa et al. (2018) <doi:10.6000/1929-6029.2018.07.02.1>.
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