5 papers
On Associative Confounder Bias
Priyantha Wijayatunga
Conditioning on some set of confounders that causally affect both treatment and outcome variables can be sufficient for eliminating bias introduced by all such confounders when est…
Viewing Simpson's Paradox
Priyantha Wijayatunga
Well known Simpson's paradox is puzzling and surprising for many, especially for the empirical researchers and users of statistics. However there is no surprise as far as mathemati…
A geometric view on Pearson's correlation coefficient and a generalization of it to non-linear dependencies
Priyantha Wijayatunga
Measuring strength or degree of statistical dependence between two random variables is a common problem in many domains. Pearson's correlation coefficient is an accurate measur…
Resolving the Lord's Paradox
Priyantha Wijayatunga
An explanation to Lord's paradox using ordinary least square regression models is given. It is not a paradox at all, if the regression parameters are interpreted as predictive or a…
Probabilistic Analysis of Balancing Scores for Causal Inference
Priyantha Wijayatunga
Propensity scores are often used for stratification of treatment and control groups of subjects in observational data to remove confounding bias when estimating of causal effect of…