Hierarchical cluster analysis in clinical research with heterogeneous study population: Highlighting its visualization with R

Annals of Translational Medicine

Volumn 5, Issue 4, 2017, Pages

  Zhang, Zhongheng ^a   Murtagh, Fionn ^b,c   Poucke, Sven Van ^d   Lin, Su ^e   Lan, Peng ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b UNIVERSITY OF DERBY   (United Kingdom)

^c UNIVERSITY OF LONDON   (United Kingdom)

^d DEPARTMENT OF CARDIOLOGY   (Belgium)

^e FUJIAN MEDICAL UNIVERSITY   (China)

Author keywords

Clinical research; Dendrogram; Heat map; Hierarchical cluster analysis (HCA)

Indexed keywords

CLINICAL RESEARCH; CLINICAL TRIAL; CLUSTER ANALYSIS; HEAT; HUMAN; PHYLOGENETIC TREE;

EID: 85014389283     PISSN: 23055839     EISSN: 23055847     Source Type: Journal    
DOI: 10.21037/atm.2017.02.05     Document Type: Article

References (19)

1. Muntaner C, Chung H, Benach J, et al. Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low-and middle-income countries. BMC Public Health 2012;12:286.
2. Petushkova NA, Pyatnitskiy MA, Rudenko VA, et al. Applying of hierarchical clustering to analysis of protein patterns in the human cancer-associated liver. PLoS One 2014;9:e103950.
3. Murtagh F. Hierarchical Clustering. In: Lovric M. editor. International Encyclopedia of Statistical Science. Berlin, Heidelberg: Springer; 2014:633-5.
4. Gil-Garcia RJ, Badia-Contelles JM, Pons-Porrata A. A General Framework for Agglomerative Hierarchical Clustering Algorithms. IEEE 2006:569-72.
5. Iwashyna TJ, Burke JF, Sussman JB, et al. Implications of Heterogeneity of Treatment Effect for Reporting and Analysis of Randomized Trials in Critical Care. Am J Respir Crit Care Med 2015;192:1045-51.
6. Ruan SY, Lin HH, Huang CT, et al. Exploring the heterogeneity of effects of corticosteroids on acute respiratory distress syndrome: a systematic review and meta-analysis. Crit Care 2014;18:R63.
7. Kalil AC, Florescu DF. Severe sepsis: are PROWESS and PROWESS-SHOCK trials comparable? A clinical and statistical heterogeneity analysis. Crit Care 2013;17:167.
8. Ma PL, Peng XX, Du B, et al. Sources of Heterogeneity in Trials Reporting Hydroxyethyl Starch 130/0.4 or 0.42 Associated Excess Mortality in Septic Patients: A Systematic Review and Meta-regression. Chin Med J (Engl) 2015;128:2374-82.
9. Zhang Z. Model building strategy for logistic regression: purposeful selection. Ann Transl Med 2016;4:111.
10. Murtagh F, Contreras P. Algorithms for hierarchical clustering: an overview. WIREs Data Mining Knowl Discov 2012;2:86-97.
11. Blasius J. Greenacre M. editors. Visualization and Verbalization of Data. Boca Raton: Chapman and Hall/ CRC, 2014:xlii+350.
12. Moss TJ, Lake DE, Calland JF, et al. Signatures of Subacute Potentially Catastrophic Illness in the ICU: Model Development and Validation. Crit Care Med 2016;44:1639-48.
13. Shahid R, Bertazzon S, Knudtson ML, et al. Comparison of distance measures in spatial analytical modeling for health service planning. BMC Health Serv Res 2009;9:200.
14. Murtagh F. A Survey of Recent Advances in Hierarchical Clustering Algorithms. Comput J 1983;26:354-9.
15. Defays D. An efficient algorithm for a complete link method. Comput J 1977;20:364-6.
16. Bates D, Mächler M, Bolker B, et al. Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software 2015;67:1-48.
17. Toddenroth D, Ganslandt T, Castellanos I, et al. Employing heat maps to mine associations in structured routine care data. Artif Intell Med 2014;60:79-88.
18. Sarkar D. Lattice: Multivariate Data Visualization with R. New York: Springer; 2008:1.
19. Maindonald J, Braun WJ. editors. Data Analysis and Graphics Using R -an Example-Based Approach (Cambridge Series in Statistical and Probabilistic Mathematics). 3rd ed. Cambridge: Cambridge University Press; 2009:538.