Simulations

Orthogonal Predictors Influence on Statistical Power

I recently came across a Twitter poll that piqued my interest. The specific poll asked: Including non confounding covariates (Z) in the regression y~ X + Z increases power to detect association of X with y. (assuming association of Z with y is non-zero). My immediate response was “No” because the variance predicted by the covariate will not influence the variance explained by the original predictor and, thus, not influence the standard error.

Visualizing Power

Primer on Statistical Significance Null-hypothesis significant testing (NHST) is a controversial approach to social science research. Although I will not visit the concerns in full, it’s important to have an understanding of concepts related to NHST so you can fully understand why this approach is criticized and its flaws are..well… flaws. One ubiquitous, yet, misunderstood concept is p-values. For you own knowledge: …beginning with the assumption that the true effect is zero (i.