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Using Testlet Response Theory to analyze data from a survey of attitude change among breast cancer survivors.

Publication ,  Journal Article
Wang, X; Baldwin, S; Wainer, H; Bradlow, ET; Reeve, BB; Smith, AW; Bellizzi, KM; Baumgartner, KB
Published in: Stat Med
August 30, 2010

In this paper we examine alternative measurement models for fitting data from health surveys. We show why a testlet-based latent trait model that includes covariate information, embedded within a fully Bayesian framework, can allow multiple simultaneous inferences and aid interpretation. We illustrate our approach with a survey of breast cancer survivors that reveals how the attitudes of those patients change after diagnosis toward a focus on appreciating the here-and-now, and away from consideration of longer-term goals. Using the covariate information, we also show the extent to which individual-level variables such as race, age and Tamoxifen treatment are related to a patient's change in attitude.The major contribution of this research is to demonstrate the use of a hierarchical Bayesian IRT model with covariates in this application area; hence a novel case study, and one that is certainly closely aligned with but distinct from the educational testing applications that have made IRT the dominant test scoring model.

Duke Scholars

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

August 30, 2010

Volume

29

Issue

19

Start / End Page

2028 / 2044

Location

England

Related Subject Headings

  • Tamoxifen
  • Survivors
  • Statistics & Probability
  • Psychometrics
  • Neoplasm Recurrence, Local
  • Humans
  • Health Surveys
  • Female
  • Data Interpretation, Statistical
  • Breast Neoplasms
 

Citation

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Wang, X., Baldwin, S., Wainer, H., Bradlow, E. T., Reeve, B. B., Smith, A. W., … Baumgartner, K. B. (2010). Using Testlet Response Theory to analyze data from a survey of attitude change among breast cancer survivors. Stat Med, 29(19), 2028–2044. https://doi.org/10.1002/sim.3945
Wang, Xiaohui, Su Baldwin, Howard Wainer, Eric T. Bradlow, Bryce B. Reeve, Ashley W. Smith, Keith M. Bellizzi, and Kathy B. Baumgartner. “Using Testlet Response Theory to analyze data from a survey of attitude change among breast cancer survivors.Stat Med 29, no. 19 (August 30, 2010): 2028–44. https://doi.org/10.1002/sim.3945.
Wang X, Baldwin S, Wainer H, Bradlow ET, Reeve BB, Smith AW, et al. Using Testlet Response Theory to analyze data from a survey of attitude change among breast cancer survivors. Stat Med. 2010 Aug 30;29(19):2028–44.
Wang, Xiaohui, et al. “Using Testlet Response Theory to analyze data from a survey of attitude change among breast cancer survivors.Stat Med, vol. 29, no. 19, Aug. 2010, pp. 2028–44. Pubmed, doi:10.1002/sim.3945.
Wang X, Baldwin S, Wainer H, Bradlow ET, Reeve BB, Smith AW, Bellizzi KM, Baumgartner KB. Using Testlet Response Theory to analyze data from a survey of attitude change among breast cancer survivors. Stat Med. 2010 Aug 30;29(19):2028–2044.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

August 30, 2010

Volume

29

Issue

19

Start / End Page

2028 / 2044

Location

England

Related Subject Headings

  • Tamoxifen
  • Survivors
  • Statistics & Probability
  • Psychometrics
  • Neoplasm Recurrence, Local
  • Humans
  • Health Surveys
  • Female
  • Data Interpretation, Statistical
  • Breast Neoplasms