alexa

GET THE APP

The Effect of Ignoring Statistical Interactions in Regression Analyses Conducted in Epidemiologic Studies: An Example with Survival Analysis Using Cox Proportional Hazards Regression Model| Abstract
ISSN: 2161-1165

Epidemiology: Open Access
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
  • Research Article   
  • Epidemiology (Sunnyvale) 2016, Vol 6(1): 216
  • DOI: 10.4172/2161-1165.1000216

The Effect of Ignoring Statistical Interactions in Regression Analyses Conducted in Epidemiologic Studies: An Example with Survival Analysis Using Cox Proportional Hazards Regression Model

Vatcheva KP1, Lee M3,4, McCormick JB1 and Rahbar MH2,3,4*
1Division of Epidemiology, University of Texas Health Science Center-Houston, School of Public Health, Brownsville Campus, , Brownsville, TX, USA
2Department of Epidemiology, Human Genetics, and Environmental Sciences (EHGES), University of Texas School of Public Health at Houston, , Houston, TX, USA
3Division of Clinical and Translational Sciences, Department of Internal Medicine, Medical School, The University of Texas Health Science Center at Houston, , Houston, TX, USA
4Biostatistics/Epidemiology/Research Design (BERD) Core, Center for Clinical and Translational Sciences (CCTS), The University of Texas Health Science Center at Houston, , Houston, TX, USA
*Corresponding Author : Rahbar MH PhD, Biostatistics/Epidemiology/Research Design Component of Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, 6410 Fannin Street, UT Professional Building Suite 1100.05, Houston, TX 77030, USA, Tel: (713)500-7901, Fax: (713)500-0766, Email: [email protected]

Received Date: Dec 07, 2015 / Accepted Date: Dec 31, 2015 / Published Date: Jan 15, 2015

Abstract

Objective: To demonstrate the adverse impact of ignoring statistical interactions in regression models used in epidemiologic studies.

Study design and setting: Based on different scenarios that involved known values for coefficient of the interaction term in Cox regression models we generated 1000 samples of size 600 each. The simulated samples and a real life data set from the Cameron County Hispanic Cohort were used to evaluate the effect of ignoring statistical interactions in these models.

Results: Compared to correctly specified Cox regression models with interaction terms, misspecified models without interaction terms resulted in up to 8.95 fold bias in estimated regression coefficients. Whereas when data were generated from a perfect additive Cox proportional hazards regression model the inclusion of the interaction between the two covariates resulted in only 2% estimated bias in main effect regression coefficients estimates, but did not alter the main findings of no significant interactions.

Conclusions: When the effects are synergic, the failure to account for an interaction effect could lead to bias and misinterpretation of the results, and in some instances to incorrect policy decisions. Best practices in regression analysis must include identification of interactions, including for analysis of data from epidemiologic studies.

Keywords: Effect modification; Cox proportional hazards model; Regression analysis; Simulation; Statistical interaction; Type 2 diabetes

Citation: Vatcheva KP, Lee M, McCormick JB, Rahbar MH (2016) The Effect of Ignoring Statistical Interactions in Regression Analyses Conducted in Epidemiologic Studies: An Example with Survival Analysis Using Cox Proportional Hazards Regression Model. Epidemiol 6: 216. Doi: 10.4172/2161-1165.1000216

Copyright: © 2016 Vatcheva KP, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Review summary

  1. Marelyn Hadaway
    Posted on Oct 03 2016 at 5:30 pm
    The work was methodologically very correct and also referred to as new important scientific findings could be useful for methodological discussions.
Top