Hierarchical statistical techniques are necessary to draw reliable conclusions from analysis of isolated cardiomyocyte studies
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Aims
It is generally accepted that post-MI heart failure (HF) changes a variety of aspects of sarcoplasmic reticular Ca2+ fluxes but for some aspects there is disagreement over whether there is an increase or decrease. The commonest statistical approach is to treat data collected from each cell as independent, even though they are really clustered with multiple likely similar cells from each heart. In this study, we test whether this statistical assumption of independence can lead the investigator to draw conclusions that would be considered erroneous if the analysis handled clustering with specific statistical techniques (hierarchical tests).
Methods and results
Ca2+ transients were recorded in cells loaded with Fura-2AM and sparks were recorded in cells loaded with Fluo-4AM. Data were analysed twice, once with the common statistical approach (assumption of independence) and once with hierarchical statistical methodologies designed to allow for any clustering. The statistical tests found that there was significant hierarchical clustering. This caused the common statistical approach to underestimate the standard error and report artificially small P values. For example, this would have led to the erroneous conclusion that time to 50% peak transient amplitude was significantly prolonged in HF.
Spark analysis showed clustering, both within each cell and also within each rat, for morphological variables. This means that a three-level hierarchical model is sometimes required for such measures. Standard statistical methodologies, if used instead, erroneously suggest that spark amplitude is significantly greater in HF and spark duration is reduced in HF.
Conclusion
Ca2+ fluxes in isolated cardiomyocytes show so much clustering that the common statistical approach that assumes independence of each data point will frequently give the false appearance of statistically significant changes. Hierarchical statistical methodologies need a little more effort, but are necessary for reliable conclusions. We present cost-free simple tools for performing these analyses.
It is generally accepted that post-MI heart failure (HF) changes a variety of aspects of sarcoplasmic reticular Ca2+ fluxes but for some aspects there is disagreement over whether there is an increase or decrease. The commonest statistical approach is to treat data collected from each cell as independent, even though they are really clustered with multiple likely similar cells from each heart. In this study, we test whether this statistical assumption of independence can lead the investigator to draw conclusions that would be considered erroneous if the analysis handled clustering with specific statistical techniques (hierarchical tests).
Methods and results
Ca2+ transients were recorded in cells loaded with Fura-2AM and sparks were recorded in cells loaded with Fluo-4AM. Data were analysed twice, once with the common statistical approach (assumption of independence) and once with hierarchical statistical methodologies designed to allow for any clustering. The statistical tests found that there was significant hierarchical clustering. This caused the common statistical approach to underestimate the standard error and report artificially small P values. For example, this would have led to the erroneous conclusion that time to 50% peak transient amplitude was significantly prolonged in HF.
Spark analysis showed clustering, both within each cell and also within each rat, for morphological variables. This means that a three-level hierarchical model is sometimes required for such measures. Standard statistical methodologies, if used instead, erroneously suggest that spark amplitude is significantly greater in HF and spark duration is reduced in HF.
Conclusion
Ca2+ fluxes in isolated cardiomyocytes show so much clustering that the common statistical approach that assumes independence of each data point will frequently give the false appearance of statistically significant changes. Hierarchical statistical methodologies need a little more effort, but are necessary for reliable conclusions. We present cost-free simple tools for performing these analyses.
Date Issued
2017-08-30
Date Acceptance
2017-08-29
Citation
Cardiovascular Research, 2017, 113 (14), pp.1743-1752
ISSN
1755-3245
Publisher
Oxford University Press
Start Page
1743
End Page
1752
Journal / Book Title
Cardiovascular Research
Volume
113
Issue
14
Copyright Statement
© The Author 2017. Published on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Sponsor
Wellcome Trust
Grant Number
092852/Z/10/Z
Subjects
Ca2+ spark
Ca2+ transient
Cardiomyocyte
Hierarchical statistics
1102 Cardiovascular Medicine And Haematology
Cardiovascular System & Hematology
Publication Status
Published