LC References and Software Downloads
LC Strategy provides an objective way to "design" a statistical analysis. After all, when one's data are observational, it's frequently already too late to design their collection!
Traditional Covariate Adjustment methods use Multivariable MODELS that make quite STRONG assumptions in order to simultaneously Estimate effects "parametrically" as well as Predict patient Y-outcomes.
In stark contrast, LC methods deliberately separate Estimation from Prediction. This allows LC treatment effect estimation to not only be non-parametric (distribution-free) and highly visual (graphical) but also to deliberately stress "fair" comparisons between relatively well-matched patients who made different treatment choices.
LC methods [a] estimate Local Treatment Differences (LTDs) only within X-space CLUSTERS of similar patients and [b] examine the joint DISTRIBUTION of these LTDs, thereby characterizing the full spectrum of patient differential response to treatment. Although somewhat computationally intensive, the LC approach is nevertheless ideal when databases are very large and encompass patients from numerous, diverse sub-populations. LC methods are based upon the Propensity Scoring theory of Rosenbaum and Rubin, Biometrika (1983). Specifically, cluster membership becomes a guaranteed BALANCING Score, "finer" than the unknown true propensity score, in the limit as clusters become small, compact and numerous!
The LC approach consists of FOUR PHASES of activities which (when repeatedly applied, checked and redone) ultimately assure that robust and objective (statistically valid) results are being generated. The four links below display pages that introduce and illustrate the specific sorts of statistical methods and graphical displays typically examined in each of the four phases of a LC Analysis...
Phase One: Aggregate
Phase Two: Confirm
Phase Three: Explore
Phase Four: Reveal
Want to learn more about methods for Observational Data Analysis?
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KISS: Keep It Sophisticatedly Simple
Arnold Zellner, ASA Presidential Address, 1991