Statistical Framework for in Vivo Drug Combination Studies
A Priori Synergy Power Analysis Based on Variability and Drug Effe...
Cook's distance for individual subjects
Helper function to calculate the relative tumor volume from an imput d...
Get estimates from a linear mixed model of tumor growth data
Linear Mixed Effect Model for Tumor Growth
Synergy calculation using linear-mixed and non-linear mixed-effect mod...
Likelihood displacements for the model
Observed vs predicted values and performance of the model
Pipe operator
Plotting of tumor growth data from a fitted model
Plotting synergy results
Plots of Observed vs Predicted Values
Plots for random effects diagnostics
Plots for residuals diagnostics
Plotting SynergyLMM results
Post hoc power calculation based on simulations of the synergy evaluat...
Performs power calculations
Calculates power based on a model fit
A Priori Synergy Power Analysis Based on Sample Size
A Priori Synergy Power Analysis Based on Time
Diagnostics of random effects of the linear mixed model
Diagnostics of residuals of the linear mixed model
Helper function to simulate tumor growth data for a two-drug combinati...
A framework for evaluating drug combination effects in preclinical in vivo studies. 'SynergyLMM' provides functions to analyze longitudinal tumor growth experiments using mixed-effects models, perform time-resolved analyses of synergy and antagonism, evaluate model diagnostics and performance, and assess both post-hoc and a priori statistical power. The calculation of drug combination synergy follows the statistical framework provided by Demidenko and Miller (2019, <doi:10.1371/journal.pone.0224137>). The implementation and analysis of linear mixed-effect models is based on the methods described by Pinheiro and Bates (2000, <doi:10.1007/b98882>), and Gałecki and Burzykowski (2013, <doi:10.1007/978-1-4614-3900-4>).