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More on time series designs: A reanalysis of mayer and Kozlow's data
Author(s) -
Willson Victor L.
Publication year - 1982
Publication title -
journal of research in science teaching
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.067
H-Index - 131
eISSN - 1098-2736
pISSN - 0022-4308
DOI - 10.1002/tea.3660190706
Subject(s) - series (stratigraphy) , computer science , time series , set (abstract data type) , variance (accounting) , heuristic , mathematics education , mathematics , artificial intelligence , machine learning , programming language , paleontology , accounting , business , biology
Abstract A recent article by Mayer and Kozlow introduces a time series experiment to science education researchers. This article examines in greater detail design considerations and reanalyzes their data using time series analysis. The first applications of time series experimental methodology to science education research were reported by Mayer and Lewis (1979) and by Mayer and Kozlow (1980). This article discusses Mayer and Kozlow's work and presents a reanalysis of their data which is intended to be heuristic, not critical. (All data were supplied by Dr. Mayer and permission was granted to use the data.) Both design and analysis will be examined. It is important to distinguish time series experimental design from time series analysis. The former, as presented by Campbell and Stanley (1966) and detailed by Glass, Willson, and Gottman (1975), is concerned with structuring treatment conditions and observations over time to make causal inferences. Time series analysis is a set of statistical techniques from which an appropriate technique can be selected to analyze collected data in the framework of a time series design. Just as data from in a randomized experiment might be analyzed using a one‐way analysis of variance or a Kruskal‐ Wallis H ‐test, data from a time series design may be subjected to several alternative analysis techniques.