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Klaus-Peter L?hr 《Informatik - Forschung und Entwicklung》1999,14(2):61
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The principle of aggregation states that the sum of a set of multiple measurements is a more stable and representative estimator than any single measurement. This greater representation occurs because there is inevitably some error associated with measurement. By combining numerous exemplars, such errors of measurement are averaged out, leaving a clearer view of underlying relationships. The present study explored the effect of score aggregation over various time periods on correlations among a number of reliable measures frequently used in open-field testing. Twenty-six male rats were given four open-field tests (4 min in duration) at 48-h intervals. Ambulation, rearing, and defecation responses were measured on a minute-by-minute basis in the open-field tests. Correlation matrices were calculated among the three measures for unaggregated scores (1-min totals) and for scores aggregated over daily tests, and mean correlation coefficients were computed for all three pairwise comparisons of the three response variables. These mean correlations were then compared to those obtained when the open-field measures were aggregated over all 4 test days. The results showed that aggregation produced substantial increases in correlation-coefficient magnitude. The correlation between ambulation and rearing increased from a mean of .39 to a value of .81. Similar increases were observed when defecation scores were correlated with ambulation (?.17 to ?.59) and rearing (?.16 to ?.49). Thus aggregation is an important factor to be considered in the design of psychobiological correlational studies. 相似文献
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