Poster #36 - Using Time Series Analysis to Estimate Complex Regular Cycles in Daily High School Attendance

• In Event: 77.059 - MTCC Tuesday Poster Session 18
  In Poster Session: 77.059-4 - Educational Statisticians SIG Poster Session: Statistical Issues and Investigations

Abstract

This presentation seeks to introduce educational researchers to the Trigonometric Box-Cox ARMA Trend Seasonal (TBATS) model, which is designed to estimate complex cyclical patterns (e.g., weeks within years) in time series data. Attendance rates in four high schools are analyzed over a ten year period using TBATS to illustrate the presence both weekly and annual patterns in three of the schools and only weekly patterns in the fourth. The model features are explicated and it is shown how the estimation of weekly and annual cycles enhances the description of the data and improves our understanding of how the assessment of endogenous variability contributes to our understanding of daily high school attendance behavior. R script is provided in an appendix.

Author

• Matthijs Koopmans, Mercy College