blog – Examined Algorithms

Measurement, Latent Factors and the Garden of Forking Paths

Confirmatory Factor Analysis and Structural Equations in PyMC

cfa

sem

measurment

Choices are made as we step down the garden of forking paths in the course of any analysis. Often, in the process of frantic search we cling too strongly to the first…

Heuristics in Latent Space: VAEs and Bayesian Inference

pytorch

variational auto-encoders

amortized bayesian inference

Missing data imposes two costs: the expense of collecting new observations and the risk of distorting the underlying structure when we construct plausible replacements. In job satisfaction surveys, non-response patterns can conceal meaningful latent relationships. This study compares statistical and machine learning approaches for imputation, focusing on their ability to preserve these latent structures while producing realistic reconstructions.

Freedom, Hierarchies and Confounded Estimates

TWFE

mundlak

hierarchical models

DiD

Two Way Fixed Effects (TWFE) regression models are often used in Differences-in-Differences designs to estimate treatment effects while accounting for variation due to group…

GAMs and GPs: Flexibility and Calibration

probability

generalised additive models

gaussian processes

Flexible Spline models risk overfit and need to be carefully calibrated against real data. Hierarchical models impose structure and aid calibration. We combine them.