Graphics and statistics for cardiology: clinical prediction rules

Mark Woodward (Lead / Corresponding author), Hugh Tunstall-Pedoe, Sanne A. E. Peters

Research output: Contribution to journalReview article

4 Citations (Scopus)
153 Downloads (Pure)

Abstract

Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland.

Original languageEnglish
Pages (from-to)538-545
Number of pages8
JournalHeart
Volume103
Issue number7
Early online date8 Feb 2017
DOIs
Publication statusPublished - Apr 2017

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Decision Support Techniques
Cardiology
Scotland
Statistical Models
Research Personnel
Research

Cite this

Woodward, Mark ; Tunstall-Pedoe, Hugh ; Peters, Sanne A. E. / Graphics and statistics for cardiology : clinical prediction rules. In: Heart. 2017 ; Vol. 103, No. 7. pp. 538-545.
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Graphics and statistics for cardiology : clinical prediction rules. / Woodward, Mark (Lead / Corresponding author); Tunstall-Pedoe, Hugh; Peters, Sanne A. E.

In: Heart, Vol. 103, No. 7, 04.2017, p. 538-545.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Graphics and statistics for cardiology

T2 - clinical prediction rules

AU - Woodward, Mark

AU - Tunstall-Pedoe, Hugh

AU - Peters, Sanne A. E.

N1 - No funding info.

PY - 2017/4

Y1 - 2017/4

N2 - Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland.

AB - Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland.

U2 - 10.1136/heartjnl-2016-310210

DO - 10.1136/heartjnl-2016-310210

M3 - Review article

C2 - 28179372

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SP - 538

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JO - Heart

JF - Heart

SN - 1355-6037

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