NONSTATIONARY DATA SHOULD NOT BE “CORRECTED”
作者:
SALLY A. JACKSON,
BARBARA J. O'KEEFE,
期刊:
Human Communication Research
(WILEY Available online 1982)
卷期:
Volume 8,
issue 2
页码: 146-153
ISSN:0360-3989
年代: 1982
DOI:10.1111/j.1468-2958.1982.tb00661.x
出版商: Blackwell Publishing Ltd
数据来源: WILEY
摘要:
Ellis (1979), in his study of interaction patterns in groups, discovered that his data did not satisfy the assumptions of a simple Markov model. In particular, he found that his data failed to satisfy the assumption of stationarity. In response to this, Ellis employed a new composite matrix procedure to generate a single set of predicted one‐step transition probabilities. This essay argues that this procedure (1) does not generate one‐step probabilities, (2) does not produce legitimately interpretable results, and (3) is a fundamentally inappropriate response to the discovery of nonstationary data. The composite matrix procedure used by Ellis is discussed and appropriate responses to the discovery of nonstationary interaction data are propo
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