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Review
. 2018 Mar 27;19(1):48.
doi: 10.1186/s12931-018-0745-8.

Prediction equations of forced oscillation technique: the insidious role of collinearity

Hassib Narchi  1 , Afaf AlBlooshi  2
Affiliations
Review

Prediction equations of forced oscillation technique: the insidious role of collinearity

Hassib Narchi et al. Respir Res. .

Abstract

Many studies have reported reference data for forced oscillation technique (FOT) in healthy children. The prediction equation of FOT parameters were derived from a multivariable regression model examining the effect of age, gender, weight and height on each parameter. As many of these variables are likely to be correlated, collinearity might have affected the accuracy of the model, potentially resulting in misleading, erroneous or difficult to interpret conclusions.The aim of this work was: To review all FOT publications in children since 2005 to analyze whether collinearity was considered in the construction of the published prediction equations. Then to compare these prediction equations with our own study. And to analyse, in our study, how collinearity between the explanatory variables might affect the predicted equations if it was not considered in the model. The results showed that none of the ten reviewed studies had stated whether collinearity was checked for. Half of the reports had also included in their equations variables which are physiologically correlated, such as age, weight and height. The predicted resistance varied by up to 28% amongst these studies. And in our study, multicollinearity was identified between the explanatory variables initially considered for the regression model (age, weight and height). Ignoring it would have resulted in inaccuracies in the coefficients of the equation, their signs (positive or negative), their 95% confidence intervals, their significance level and the model goodness of fit. In Conclusion with inaccurately constructed and improperly reported models, understanding the results and reproducing the models for future research might be compromised.

Keywords: Collinearity; Forced oscillation technique; Multicollinearity; Multivariable models.

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Conflict of interest statement

Ethics approval and consent to participate

This study was approved by Al Ain medical district human research ethics committee (Ref. DT/bb/15–32).

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Comparison of the predicted airway resistance (Rrs) by height between our study with an equation based exclusively on height (ABlooshi, unpublished) and reports that included other correlated variables in their respective equations (Dencker [10], Nowowiejska [16], Park [17], Calogero [8])
Fig. 2
Fig. 2
Scatterplot matrix of the explanatory variables initially considered in the multivariable linear regression model of resistance (Rrs5) in 291 healthy children (AlBlooshi, et al. unpublished data). r = Pearson correlation coefficients (r) between the 3 explanatory variables
Fig. 3
Fig. 3
Comparison of the predicted linear equations slopes of resistance (Rrs5) expressed as cm H2O.s.L− 1, with their 95% confidence intervals (shaded zones), amongst three multivariable linear regression models with inclusion of different collinear explanatory variables, in 291 healthy children (AlBlooshi, et al. unpublished data)
See this image and copyright information in PMC

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