Auto Correlation Effects on Least - Squares Intervention Analysis of Short Time Series  

Oleh:

Huitema, Bradley E. ; McKnight, Scott ; McKean, Joseph W.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 59 no. 5 (1999), page 767-786.
Topik: ANALYSIS OF VARIANCE; mathematical analysis; time series; mathematical models
Fulltext: 767.pdf (160.71KB)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: EE30.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Several issues regarding the effects of autocorrelated errors on type I error in ordinary least - squares models are clarified. Although auto correlated errors have a large effect on both omnibus F tests and tests on individual intervention effect coefficients in many applications, there are exceptions that have not been pointed out previously. It is demonstrated that under certain conditions, distortion in type I error is far less than is predicted by asymptotic theory. It is shown that these exceptions occur because the effect of auto correlated errors is dependent on : a. the type of parameters (e. g. level change and / or slope change) required in the model b. the number of variables in th edesign matrix, and c. the sample size. Because existing time - series methods perform poorly with small samples, this may be a useful finding in some situations, however a better general solution is to use a recently developed small - sample method.

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