Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 
Home Print this page Email this page
Users Online: 502

 Table of Contents  
Year : 2019  |  Volume : 16  |  Issue : 2  |  Page : 91-92

Variable selection, unnecessary adjustments, and multicollinearity in thyroid eye disease studies

1 Medical Researcher, Ottawa, ON, Canada
2 Department of Health - Eye Center, East Avenue Medical Center, Quezon City, Philippines

Date of Web Publication15-Jul-2019

Correspondence Address:
Dr. Red Thaddeus Dela PeÑa Miguel
Ortigas Center, Pasig City 1605, Philippines
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/trp.trp_18_19

Rights and Permissions

How to cite this article:
Miguel RT, Medalle RS. Variable selection, unnecessary adjustments, and multicollinearity in thyroid eye disease studies. Thyroid Res Pract 2019;16:91-2

How to cite this URL:
Miguel RT, Medalle RS. Variable selection, unnecessary adjustments, and multicollinearity in thyroid eye disease studies. Thyroid Res Pract [serial online] 2019 [cited 2023 Jan 29];16:91-2. Available from: https://www.thetrp.net/text.asp?2019/16/2/91/262728


We read with interest the study by Lavaju et al. regarding patterns of ocular manifestations in patients with thyroid eye disease (TED).[1] The study is similar to a study we completed last year in a tertiary hospital in the Philippines, which is now being prepared for publication. The study conducted in Nepal carried out a multiple logistic regression model to find out the independent association of variables, such as age and sex to TED. The model employed, however, raises few questions.

First, the study failed to discuss the reasons for selecting the variables included in the multiple regression model. The lack of a theoretical or statistical framework for deciding which covariates to control for in the model may lead readers to assume certain relationships exist. For example, in univariate analysis, the study failed to show a significant difference between groups with or without cardiovascular disease (CVD) in having TED (P = 0.164). We, however, note in [Table 5] that CVD is included in the model. This leads us to assume an underlying relationship with CVD and TED that needs to be accounted for, despite the absence of significant difference in earlier analysis conducted. Furthermore, the failure to report the reason for choosing the variables may leave readers to wonder if including all variables could have caused diluted true associations or spurious associations.[2]

Second, the study explains that TED was diagnosed clinically based on the presence of a thyroid disorder associated with one of the thyroid eye signs. However, Mourits clinical activity score (CAS) was also entered into the model as a risk factor for TED. Given that everyone with CAS has a thyroid disorder, and a higher CAS score will indicate a higher probability of having an eye sign (being a component of CAS), is it therefore not possible that the relationship of CAS and the outcome could have affected the precision of the other variables unnecessarily? Adjusting for both CAS and NOSPECS, given that their components define TED, could have increased the likelihood of accuracy gain or loss in the results of the model.[3] Although the effect is evident in the association of mean CAS score and TED as manifested with a high odds ratio (49.17, P < 0.0001), the effect of using CAS and NOSPECS in the model as confounding variables could have had even more detrimental effects on the association of the other variables with TED.

Finally, the model includes variables with multicollinearity and overlapping variables without adequate investigation. For example, components of CAS are already accounted for in NOSPECS and the model could be deemed to be overadjusting.[4] Further, there could be collinearity between age and duration of disease as well as age and the comorbidities included. Without proper consideration for the relationship between variables, the results could be misleading.[5]

In conclusion, we look forward to the reply of our colleagues from Nepal. Further, we feel that future studies on TED could account for the concerns raised herein.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Lavaju P, Badhu BP, Maskey R. Pattern of ocular manifestations in patients with thyroid disease presenting in Eastern Nepal. Thyroid Res Pract 2019;16:20-5.  Back to cited text no. 1
  [Full text]  
Ranganathan P, Pramesh CS, Aggarwal R. Common pitfalls in statistical analysis: Logistic regression. Perspect Clin Res 2017;8:148-51.  Back to cited text no. 2
  [Full text]  
Schisterman EF, Cole SR, Platt RW. Overadjustment bias and unnecessary adjustment in epidemiologic studies. Epidemiology 2009;20:488-95.  Back to cited text no. 3
Leistikow B. Commentary: Questionable premises, overadjustment, and a smoking/suicide association in younger adult men. Int J Epidemiol 2003;32:1005-6.  Back to cited text no. 4
Vatcheva KP, Lee M, McCormick JB, Rahbar MH. Multicollinearity in regression analyses conducted in epidemiologic studies. Epidemiology (Sunnyvale) 2016;6. pii: 227.  Back to cited text no. 5


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article

 Article Access Statistics
    PDF Downloaded144    
    Comments [Add]    

Recommend this journal