Confusing developmental and individual differences |
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| Affiliation: | 1. Postgraduate student, Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, PR China;2. Postgraduate student, Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, PR China;3. Professor, Division for Globalization Initiative, Liaison Center for Innovative Dentistry, Tohoku University Graduate School of Dentistry, Sendai, Japan;4. Associate Professor, Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Lab of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, PR China;1. Adjunct Associate Professor, Department of Applied Prosthodontics, Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan |
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| Abstract: | T. Globerson (1985, Developmental Review, 5, 261–273) compared the relative effects of an individual difference variable field dependency (FD/I) with a developmental variable (age) on a measure of M-capacity, in an analysis of variance (ANOVA) design. Age is a highly significant effect and the sum of squares associated with this factor accounts for 66% of the variance in M-capacity. FD/I is not significant and accounts for less than 1% of the variance in M-capacity. This is interpreted as indicating that M-capacity is a purely developmental phenomenon showing negligible individual differences. This paper argues that this result is an inevitable artifact of the experimental design. Further, the design is a common one in developmental psychology, and its dangers are largely unrecognized. The main problems concern (1) dichotomizing a continuous variable and treating the dichotomy as two levels of a factorial variable, (2) drawing inferences about the size of relationship between the continuous variable and the dependent variable on the basis of the variance accounted for by the factorial variable in the ANOVA, (3) differential reliability of measures of the independent variables, and (4) selective control of the sampling of the independent variables. These issues are explored in a simulation of Globerson's data and in an analogous analysis of data relating age and height, as independent variables, with weight as a dependent variable. |
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