NONSTATIONARY DATA SHOULD NOT BE “CORRECTED”

SALLY A. JACKSON*, BARBARA J. O'KEEFE

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

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 proposed.

Original languageEnglish (US)
Pages (from-to)146-153
Number of pages8
JournalHuman Communication Research
Volume8
Issue number2
DOIs
StatePublished - Jan 1 1982

ASJC Scopus subject areas

  • Communication
  • Developmental and Educational Psychology
  • Anthropology
  • Linguistics and Language

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