Statistical Learning methodology for analysis of large collections of cross-sectional
observational data can be most effective when the approach used is both Nonparametric …

Claims from observational studies that use traditional model specification searches often fail
to replicate, partially because the available data tend to be biased. There is an urgent need …

The NU. Learning-package provides R functions that implement newer methods for analysis
of observational data that are" Nonparametric" and use" Unsupervised learning." In other …

It is well-known that claims coming from observational studies often fail to replicate when
rigorously re-tested. The technical problems include multiple testing, multiple modeling and …

The LocalControl R package implements novel approaches to address biases and
confounding when comparing treatments or exposures in observational studies of outcomes …

The LocalControlStrategy-package provides R functions that implement rather new methods
for analysis of observational data that are" nonparametric" and mostly use" unsupervised …

The possible association between Particulate Matter 2.5 (PM2. 5) and lung cancer mortality
can be partitioned into components, within similar observational units, and across different …

Large (observational) data sets typically present research opportunities, but also problems
that can lead to false claims. In Big Data, the standard error of an average effect estimate …