risks - Estimate Risk Ratios and Risk Differences using Regression
Risk ratios and risk differences are estimated using regression models that allow for binary, categorical, and continuous exposures and confounders. Implemented are marginal standardization after fitting logistic models (g-computation) with delta-method and bootstrap standard errors, Miettinen's case-duplication approach (Schouten et al. 1993, <doi:10.1002/sim.4780121808>), log-binomial (Poisson) models with empirical variance (Zou 2004, <doi:10.1093/aje/kwh090>), binomial models with starting values from Poisson models (Spiegelman and Hertzmark 2005, <doi:10.1093/aje/kwi188>), and others.
Last updated 14 days ago
binomialbiostatisticsepidemiologyregression-models
5.26 score 5 stars 12 scripts 247 downloadsbatchtma - Batch Effect Adjustments
Different adjustment methods for batch effects in biomarker data, such as from tissue microarrays. Some methods attempt to retain differences between batches that may be due to between-batch differences in "biological" factors that influence biomarker values.
Last updated 10 months ago
batch-effectsmeasurement-errortissue-microarray-analysis
3.70 score 1 stars 3 scripts 275 downloads