Age differences in storage and retrieval: A multinomial modeling analysis

Abstract

An experiment is reported that examined the memory differences between 23 college students (21-41 years old) and 23 elderly adults (64-92 years old). Both groups memorized lists ofcategorically related words over a series of three study-test trials in a free-recall design. Consistent with prior research on aging effects, the elderly subjects performed more poorly on the number of words recalled, the number of categories recalled, the number of items recalled per category, and the amount of category clustering. To help determine if these differences were due to storage or retrieval processes, Batchelder and Riefer's multinomial model for measuring storage and retrieval was used to analyze the data. The model suggested that age differences were primarily due to retrieval factors and not to storage factors . These results are consistent with a number of retrievalbased theories of aging effects .

The Item-Specific Deficit Approach to evaluating verbal memory dysfunction: Rationale, psychometrics, and application

“…This research met with some criticism due to the choice of retrieval indices used and the fact that an external verbal memory criterion was not utilized to validate the retrieval indices in the study (Delis et al, 2000). Nevertheless, the use of recognition–free-recall discrepancies has resulted in mixed findings in other studies as well (see Riefer & Batchelder, 1991). It has been suggested that results based on such discrepancies can be misleading, as they reflect multiple processes.…”

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

“…The pair-clustering model is one of the best analyzed members of the family of multinomial models (e.g., Batchelder & Riefer, 1986Riefer & Batchelder, 1991). It is based on a free-recall task in which participants are presented with a list of words that are related by categories.…”

Extending General Processing Tree Models to Analyze Reaction Time Experiments

“…(2) in the form of % 1 , % 2 or (1&% 1 ), (1&% 2 ). Models with the above characteristics have been used in cognitive psychology research, especially in human memory studies (Riefer 6 Rouder, 1992;Riefer 6 Batchelder, 1991;Batchelder 6 Riefer, 1980;Batchelder, Hu, 6 Riefer, 1994;Batchelder 6 Riefer, 1986;Riefer, Hu, 6 Batchelder, 1994;Batchelder, Riefer, 6 Hu, 1994). studied the entire family of such models and named the family general processing tree (GPT) models (see Hu, 1998b, for other resources about GPT models).…”