Statistics in respiratory research: from data to application

A. Bignamini (Milan, Italy)

Source: ERS Course 2015
Number: 5

Slide presentationWebcastMultimedia files

Rating: 0
You must login to grade this presentation.

Share or cite this content

Citations should be made in the following way:
A. Bignamini (Milan, Italy). Statistics in respiratory research: from data to application. ERS Course 2015

You must login to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.

Member's Comments

No comment yet.
You must Login to comment this presentation.


Related content which might interest you:
Reporting data analysis methods in high impact respiratory journals
Source: International Congress 2016 – Abstracts in medical education, the web and the internet
Year: 2016


Research emphysis in China: big data network for respiratory health
Source: International Congress 2019 – Chinese programme 2019: Part I
Year: 2019


Reporting data analysis methods in high-impact respiratory journals
Source: ERJ Open Res, 4 (2) 00140-2017; 10.1183/23120541.00140-2017
Year: 2018



Statistics for the European Respiratory Journal
Source: Eur Respir J 2001; 18: 393-401
Year: 2001



A bibliometric evaluation of European Union research of the respiratory system from 1987-1998
Source: Eur Respir J 2001; 17: 1175-1180
Year: 2001



Classification of clinical spirometry data using global lung initiative (GLI) and national health and nutrition examination survey (NHANES-III) models
Source: Annual Congress 2013 –Expiration, exhalation and exhaustion: measures of dynamic volumes, breath analysis and respiratory muscles
Year: 2013


New uses of data: from big data to artificial intelligence and clinical decision tools  in children with respiratory diseases
Source: Virtual Congress 2021 – New technologies for the management of children with respiratory diseases
Year: 2021


Spirometry longitudinal data analysis software (SPIROLA) in a routine clinical laboratory
Source: International Congress 2014 – Respiratory function: quality and new technologies
Year: 2014

International research outputs and funding in respiratory medicine
Source: Eur Respir J 2003; 22: Suppl. 45, 484s
Year: 2003

The primary care routine data registry BeoNet: First pilot phase results for COPD research
Source: International Congress 2015 – Patient health gains related to the economic effectiveness of disease management programmes
Year: 2015

Some principles and practices of genetic biobanking studies
Source: Eur Respir J 2009; 33: 419-425
Year: 2009



Research methodology and data analysis
Source: International Congress 2015 – ME11 Research methodology and data analysis
Year: 2015

Electronic data collection as an aid to quantification of the burden of COPD in general practice
Source: Eur Respir J 2004; 24: Suppl. 48, 87s
Year: 2004

Application of big data technology for COVID-19: Health economics of COVID
Source: ERS Course 2021 - COVID-19: State of the art
Year: 2021

Bibliometric analysis of respiratory research within biomedical research
Source: ERS Summit on priorities in respiratory medicine 2011
Year: 2011

Tools for research on respiratory health
Source: Annual Congress 2004 - PG17 - How to conduct a scientific survey on respiratory health
Year: 2004

Late Breaking Abstract - COVID-19 epidemic in Respiratory Diseases Unit: partioning analysis and data mining. Results from a single Institution experience.
Source: Virtual Congress 2020 – Air pollution and comorbidities
Year: 2020


Development and validation of respiratory nurse´s opinion about nursing standardized language, care plans and conceptual models: MOCMEL Survey
Source: International Congress 2017 – Patient experience of smoking cessation: new approaches
Year: 2017