{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T16:10:45Z","timestamp":1772122245802,"version":"3.50.1"},"reference-count":62,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T00:00:00Z","timestamp":1544140800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Int Neuropsychol Soc"],"published-print":{"date-parts":[[2019,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:bold>Objectives:<\/jats:bold>\n                    Prior research has identified numerous genetic (including sex), education, health, and lifestyle factors that predict cognitive decline. Traditional model selection approaches (e.g., backward or stepwise selection) attempt to find one model that best fits the observed data, risking interpretations that only the selected predictors are important. In reality, several predictor combinations may fit similarly well but result in different conclusions (e.g., about size and significance of parameter estimates). In this study, we describe an alternative method, Information-Theoretic (IT) model averaging, and apply it to characterize a set of complex interactions in a longitudinal study on cognitive decline.\n                    <jats:bold>Methods:<\/jats:bold>\n                    Here, we used longitudinal cognitive data from 1256 late\u2013middle aged adults from the Wisconsin Registry for Alzheimer\u2019s Prevention study to examine the effects of sex, apolipoprotein E (\n                    <jats:italic>APOE<\/jats:italic>\n                    ) \u025b4 allele (non-modifiable factors), and literacy achievement (modifiable) on cognitive decline. For each outcome, we applied IT model averaging to a set of models with different combinations of interactions among sex,\n                    <jats:italic>APOE,<\/jats:italic>\n                    literacy, and age.\n                    <jats:bold>Results:<\/jats:bold>\n                    For a list-learning test, model-averaged results showed better performance for women\n                    <jats:italic>versus<\/jats:italic>\n                    men, with faster decline among men; increased literacy was associated with better performance, particularly among men.\n                    <jats:italic>APOE<\/jats:italic>\n                    had less of an association with cognitive performance in this age range (\u223c40\u201370 years).\n                    <jats:bold>Conclusions:<\/jats:bold>\n                    These results illustrate the utility of the IT approach and point to literacy as a potential modifier of cognitive decline. Whether the protective effect of literacy is due to educational attainment or intrinsic verbal intellectual ability is the topic of ongoing work. (\n                    <jats:italic>JINS<\/jats:italic>\n                    , 2019,\n                    <jats:italic>25<\/jats:italic>\n                    , 119\u2013133)\n                  <\/jats:p>","DOI":"10.1017\/s1355617718000954","type":"journal-article","created":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T04:50:06Z","timestamp":1544158206000},"page":"119-133","source":"Crossref","is-referenced-by-count":6,"title":["Characterizing the Effects of Sex,\n                    <i>APOE<\/i>\n                    \u025b4, and Literacy on Mid-life Cognitive Trajectories: Application of Information-Theoretic Model Averaging and Multi-model Inference Techniques to the Wisconsin Registry for Alzheimer\u2019s Prevention Study"],"prefix":"10.1017","volume":"25","author":[{"given":"Rebecca L.","family":"Koscik","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Derek 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