We analyze data from over 20,000 subjects, each of whom participated in an identical ten item free recall experiment. The experiment involved three study-test trials followed by a delayed test trial, where presentation order was identical over study trials. The subjects ranged from healthy elderly to elderly with early stage dementia, and each subject's data included covariates on gender, age, and education. Some subjects had complete neurological classifications. We analyzed the data on each item at four levels: 1. percent correct over the four test trials; 2. a ten by four bit- map of correct and incorrect recalls; 3. four-tupple frequencies of the sixteen possible successful and unsuccessful recalls of each item across the four test trials; and 4. actual item recall orders on test trials. A correspondence analysis of the bitmap data provided accurate classification of those subjects with mild dementia. A Markov model of the four tupple frequencies was analyzed with various Bayesian hierarchical versions that allowed both subject and item inhomogeneity. We provided a model of recall order based on memory strength, and we show using odds ratios that departures from the model suggest that there is a competing tendency to recall non-recency items in the presentation order and recency items in the reverse order. While we are yet to provide a satisfactory model of the recall order data, the huge size of the data based provides a test bed for future free recall models. |