1 citations · 1 across the 6 of their papers we have counts for
6 papers
Bayesian Inference Procedures for A/B Testing: An Overview
Mårten Schultzberg, Mattias Frånberg
Bayesian inference for A/B testing is a family of prior and stopping-rule configurations with fundamentally different statistical properties, but it is often discussed as a single…
Statistical Foundations of LLM-based A/B Testing: A Surrogacy Framework for Human Causal Inference
Joel Persson, Mårten Schultzberg, Sebastian Ankargren
Organizations and researchers show increasing interest in using large language models (LLMs) in place of human participants in A/B tests, in the hope of experimenting faster and at…
Risk-aware product decisions in A/B tests with multiple metrics
Mårten Schultzberg, Sebastian Ankargren, Mattias Frånberg
In the past decade, AB tests have become the standard method for making product decisions in tech companies. They offer a scientific approach to product development, using statisti…
Resampling-free bootstrap inference for quantiles
Mårten Schultzberg, Sebastian Ankargren
Bootstrap inference is a powerful tool for obtaining robust inference for quantiles and difference-in-quantiles estimators. The computationally intensive nature of bootstrap infere…
Statistical Properties of Exclusive and Non-exclusive Online Randomized Experiments using Bucket Reuse
Mårten Schultzberg, Oskar Kjellin, Johan Rydberg
Randomized experiments is a key part of product development in the tech industry. It is often necessary to run programs of exclusive experiments, i.e., experiments that cannot be r…
Properties of restricted randomization with implications for experimental design
Mattias Nordin, Mårten Schultzberg
Recently, there as been an increasing interest in the use of heavily restricted randomization designs which enforces balance on observed covariates in randomized controlled trials.…