How to interpret statistical analysis results implicated in health causality studies?

The improvement of statistical techniques is a research problem which does not lose its validity. Once it was identified and founded the use of the statistical analysis involved in the search for possible causal factors in health, it was necessary to design a methodology for its optimal application,...

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Main Authors: Nelsa María Sagaró del Campo, Larisa Zamora Matamoros
Format: Article
Language:Spanish
Published: Centro Provincial de Información de Ciencias Médicas. Cienfuegos 2020-04-01
Series:Medisur
Subjects:
Online Access:http://medisur.sld.cu/index.php/medisur/article/view/4415
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spelling doaj-087173eab2ba445e8c8b18b51a23ac2f2021-08-27T02:17:02ZspaCentro Provincial de Información de Ciencias Médicas. CienfuegosMedisur1727-897X2020-04-011822923061803How to interpret statistical analysis results implicated in health causality studies?Nelsa María Sagaró del Campo0Larisa Zamora Matamoros1Universidad de Ciencias Médicas de Santiago de Cuba. Santiago de CubaUniversidad de Ciencias Médicas de Santiago de Cuba. Santiago de CubaThe improvement of statistical techniques is a research problem which does not lose its validity. Once it was identified and founded the use of the statistical analysis involved in the search for possible causal factors in health, it was necessary to design a methodology for its optimal application, in which the most complex stage turned was result interpretation. Therefore, this work aims at describing how to perform this interpretation, whose base is founded on literature theoretical references, and the practical ones, based on the experiences acquired from the various case studies and controls with the application of the technique. Indices, tables and graphs of the type are presented in the interpretation, similarity and cohesive trees, and implicative graph, from which the possible causal factors, confusing variables, effect modifiers and others that are identified and others which could be involved.http://medisur.sld.cu/index.php/medisur/article/view/4415análisis estadísticointerpretación estadística de datoscausalidad
collection DOAJ
language Spanish
format Article
sources DOAJ
author Nelsa María Sagaró del Campo
Larisa Zamora Matamoros
spellingShingle Nelsa María Sagaró del Campo
Larisa Zamora Matamoros
How to interpret statistical analysis results implicated in health causality studies?
Medisur
análisis estadístico
interpretación estadística de datos
causalidad
author_facet Nelsa María Sagaró del Campo
Larisa Zamora Matamoros
author_sort Nelsa María Sagaró del Campo
title How to interpret statistical analysis results implicated in health causality studies?
title_short How to interpret statistical analysis results implicated in health causality studies?
title_full How to interpret statistical analysis results implicated in health causality studies?
title_fullStr How to interpret statistical analysis results implicated in health causality studies?
title_full_unstemmed How to interpret statistical analysis results implicated in health causality studies?
title_sort how to interpret statistical analysis results implicated in health causality studies?
publisher Centro Provincial de Información de Ciencias Médicas. Cienfuegos
series Medisur
issn 1727-897X
publishDate 2020-04-01
description The improvement of statistical techniques is a research problem which does not lose its validity. Once it was identified and founded the use of the statistical analysis involved in the search for possible causal factors in health, it was necessary to design a methodology for its optimal application, in which the most complex stage turned was result interpretation. Therefore, this work aims at describing how to perform this interpretation, whose base is founded on literature theoretical references, and the practical ones, based on the experiences acquired from the various case studies and controls with the application of the technique. Indices, tables and graphs of the type are presented in the interpretation, similarity and cohesive trees, and implicative graph, from which the possible causal factors, confusing variables, effect modifiers and others that are identified and others which could be involved.
topic análisis estadístico
interpretación estadística de datos
causalidad
url http://medisur.sld.cu/index.php/medisur/article/view/4415
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