You want to run an experiment where you anticipate finding a treatment effect. How large should your sample size be to have a reasonable chance of detecting significant results? In this manuscript, I present and explain the Stata code I use to address this question. The code uses simulations to...

Bayes' theorem incorporates distinct types of information through the likelihood and prior. Direct observations of state variables enter the likelihood and modify posterior probabilities through consistent updating. Information in terms of expected values of state variables modify posterior...

We study the falsifiability and identification of Quantal Response Equilibrium (QRE) when each player's utility and error distribution are relaxed to be unknown non-parametric functions. Using variations of players' choices across a series of games, we first show that both the utility function...

This paper is inspired by medical studies in which the same patients with multiple sclerosis are examined at several successive visits (doctor's appointments) and described by fractional anisotropy tract profiles, which can be represented as f unctions. Since the observations for each patient...

This paper summarizes and assesses several of the most popular methods to seasonally adjust weekly data. The industry standard approach, known as X-13ARIMA-SEATS, is suitable only for monthly or quarterly data. Given the increased availability and promise of non-traditional data at higher...

This paper investigates the feasibility of using earlier provisional data to improve the now- and forecasting accuracy of final and official statistics. We propose the use of a multivariate structural time series model which includes common trends and seasonal components to combine official...