Normative comparison standards for measures of cognition in the canadian longitudinal study on aging (CLSA): Does applying sample weights make a difference?

Megan E. O'Connell, Holly Tuokko, Helena Kadlec, Lauren E. Griffith, Martine Simard, Vanessa Taler, Stacey Voll, Mary E. Thompson, Ivan Panyavin, Christina Wolfson, Susan Kirkland, Parminder Raina

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Large-scale studies present the opportunity to create normative comparison standards relevant to populations. Sampling weights applied to the sample data facilitate extrapolation to the population of origin, but normative scores are often developed without the use of these sampling weights because the values derived from large samples are presumed to be precise estimates of the population parameter. The present article examines whether applying sample weights in the context of deriving normative comparison standards for measures of cognition would affect the distributions of regression-based normative data when using data from a large population-based study. To address these questions, we examined 3 cognitive measures from the Canadian Longitudinal Study on Aging tracking cohort (N = 14,110, Age 45-84 years at recruitment): Rey Auditory Verbal Learning Test - Immediate Recall, Animal Fluency, and the Mental Alternation Test. The use of sampling weights resulted in similar model parameter estimates to unweighted regression analyses and similar cumulative frequency distributions to the unweighted analyses. We randomly sampled progressively smaller subsets from the full database to test the hypothesis that sampling weights would help maintain the estimates from the full sample, but discovered that the weighted and unweighted estimates were similar and were less precise with smaller samples. These findings suggest that although use of sampling weights can help mitigate biases in data from sampling procedures, the application of weights to adjust for sampling biases do not appreciably impact the normative data, which lends support to the current practice in creation of normative data.

Original languageEnglish
Pages (from-to)1081-1091
Number of pages11
JournalPsychological Assessment
Volume31
Issue number9
DOIs
Publication statusPublished - Sept 2019

Bibliographical note

Funding Information:
This research was made possible using the data collected by the Canadian Longitudinal Study on Aging (CLSA). Funding for the CLSA is provided by the Government of Canada through the Canadian Institutes of Health Research (CIHR) under grant reference: LSA 9447 and the Canada Foundation for Innovation. This research has been conducted using the CLSA data set (Baseline Tracking Data set version 3.0), under Application Number 150101. The opinions expressed in this article are the authors’ own and do not reflect the views of the Canadian Longitudinal Study on Aging. The preparation of this article was partially supported by funding provided by Alzheimer Society of Canada/Alzheimer Société de Canada and the Pacific Alzheimer Research Foundation. Support was provided to Lauren E. Griffith by a Canadian Institutes of Health Research New Investigator Award and the McLaughlin Foundation Professorship in Population and Public Health. Parminder Raina holds Tier 1 Canada Research Chair in Geroscience and Labarge Chair in Optimal Aging.

Publisher Copyright:
© 2019 American Psychological Association.

ASJC Scopus Subject Areas

  • Clinical Psychology
  • Psychiatry and Mental health

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