This article argues that, across different psychological contexts, the methods of data collection, treatment, and analysis in word association tests have hitherto been inconsistent. We demonstrate that this inconsistency has resulted from inadequate control, in previous studies, of certain important variables including the basis of norm comparisons, and we present a principled method for collecting, scoring, and analysing association responses, to address these issues. The method is evaluated using test and retest data sets from 16-year-old and over-65-year-old twins (n = 636), which enable us to (a) compare samples matched for key environmental variables, (b) assess the transferability of norming information between age cohorts, and (c) evaluate the reliability of the scoring protocols. We find systematic differences in the association behaviour of the two age cohorts, indicating the importance of evaluating data only against norms lists that are matched to the target population. Individual association behaviour is found to be consistent across test times, both in terms of response stereotypy and response type.

Acronyms are an idiosyncratic part of our everyday vocabulary. Research in word processing has used acronyms as a tool to answer fundamental questions such as the nature of the word superiority effect (WSE) or which is the best way to account for word-reading processes. In this study, acronym naming was assessed by looking at the influence that a number of variables known to affect mainstream word processing has had in acronym naming. The nature of the effect of these factors on acronym naming was examined using a multilevel regression analysis. First, 146 acronyms were described in terms of their age of acquisition, bigram and trigram frequencies, imageability, number of orthographic neighbors, frequency, orthographic and phonological length, print-to-pronunciation patterns, and voicing characteristics. Naming times were influenced by lexical and sublexical factors, indicating that acronym naming is a complex process affected by more variables than those previously considered.

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