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Change point testing in logistic regression models with interaction term.

Publication ,  Journal Article
Fong, Y; Di, C; Permar, S
Published in: Stat Med
April 30, 2015

A threshold effect takes place in situations where the relationship between an outcome variable and a predictor variable changes as the predictor value crosses a certain threshold/change point. Threshold effects are often plausible in a complex biological system, especially in defining immune responses that are protective against infections such as HIV-1, which motivates the current work. We study two hypothesis testing problems in change point models. We first compare three different approaches to obtaining a p-value for the maximum of scores test in a logistic regression model with change point variable as a main effect. Next, we study the testing problem in a logistic regression model with the change point variable both as a main effect and as part of an interaction term. We propose a test based on the maximum of likelihood ratios test statistic and obtain its reference distribution through a Monte Carlo method. We also propose a maximum of weighted scores test that can be more powerful than the maximum of likelihood ratios test when we know the direction of the interaction effect. In simulation studies, we show that the proposed tests have a correct type I error and higher power than several existing methods. We illustrate the application of change point model-based testing methods in a recent study of immune responses that are associated with the risk of mother to child transmission of HIV-1.

Duke Scholars

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

April 30, 2015

Volume

34

Issue

9

Start / End Page

1483 / 1494

Location

England

Related Subject Headings

  • Statistics & Probability
  • Monte Carlo Method
  • Logistic Models
  • Likelihood Functions
  • Infectious Disease Transmission, Vertical
  • Humans
  • HIV-1
  • HIV Infections
  • Effect Modifier, Epidemiologic
  • Data Interpretation, Statistical
 

Citation

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Fong, Y., Di, C., & Permar, S. (2015). Change point testing in logistic regression models with interaction term. Stat Med, 34(9), 1483–1494. https://doi.org/10.1002/sim.6419
Fong, Youyi, Chongzhi Di, and Sallie Permar. “Change point testing in logistic regression models with interaction term.Stat Med 34, no. 9 (April 30, 2015): 1483–94. https://doi.org/10.1002/sim.6419.
Fong Y, Di C, Permar S. Change point testing in logistic regression models with interaction term. Stat Med. 2015 Apr 30;34(9):1483–94.
Fong, Youyi, et al. “Change point testing in logistic regression models with interaction term.Stat Med, vol. 34, no. 9, Apr. 2015, pp. 1483–94. Pubmed, doi:10.1002/sim.6419.
Fong Y, Di C, Permar S. Change point testing in logistic regression models with interaction term. Stat Med. 2015 Apr 30;34(9):1483–1494.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

April 30, 2015

Volume

34

Issue

9

Start / End Page

1483 / 1494

Location

England

Related Subject Headings

  • Statistics & Probability
  • Monte Carlo Method
  • Logistic Models
  • Likelihood Functions
  • Infectious Disease Transmission, Vertical
  • Humans
  • HIV-1
  • HIV Infections
  • Effect Modifier, Epidemiologic
  • Data Interpretation, Statistical