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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Centro Provincial de Información de Ciencias Médicas. Cienfuegos
2020-04-01
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Online Access: | http://medisur.sld.cu/index.php/medisur/article/view/4415 |
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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 |
work_keys_str_mv |
AT nelsamariasagarodelcampo howtointerpretstatisticalanalysisresultsimplicatedinhealthcausalitystudies AT larisazamoramatamoros howtointerpretstatisticalanalysisresultsimplicatedinhealthcausalitystudies |
_version_ |
1721188405383004160 |