An improved portmanteau test for autocorrelated errors in interrupted time-series regression models.
A new portmanteau test for autocorrelation among the errors of interrupted time-series regression models is proposed. Simulation results demonstrate that the inferential properties of the proposed Q(H-M) test statistic are considerably more satisfactory than those of the well known Ljung-Box test and moderately better than those of the Box-Pierce test. These conclusions generally hold for a wide variety of autoregressive (AR), moving averages (MA), and ARMA error processes that are associated with time-series regression models of the form described in Huitema and McKean (2000a, 2000b).
Huitema
Bradley E
BE
Department of Psychology, Western Michigan University, Kalamazoo, Michigan 49008, USA. brad.huitema@wmich.edu
McKean
Joseph W
JW
D036262:Empirical Research; D006801:Humans; D008960:Models, Psychological; D012044:Regression Analysis; D013223:Statistics as Topic