TY - JOUR
T1 - Advanced statistical modelling ideas, a challenge for research in culture and education
AU - Salas, Naymé Daniela
AU - Hefetz, Amir
AU - Liberman, Gabriel
PY - 2017/1/1
Y1 - 2017/1/1
N2 - © 2017 Fundacion Infancia y Aprendizaje. The availability of computerized statistical packages allows us to plug in our data and to expect a set of estimates, which we can communicate in our final research report. However, statistical software is not an end; it is only the means. Our responsibility as researchers is to develop a set of arguments that explain why our final methodological choice is the better one, which will yield reliable answers for the study questions within the theoretical setting. Journals of all types require authors to deploy innovative statistical models when analysing collected data. Yet, the problem of advanced modelling strategies still remains — authors disregard key assumptions, choose the wrong analytical strategies and are not aware of alternative strategies to support or reject their hypotheses. This special issue provides readers with a reference framework for some of the most common methodological concerns. The articles included in this monographic issue deal with relatable scenarios and offer state-of-the-art statistical approaches to data treatment. We are confident that this special issue will be extremely useful to past and future authors of Cultura y Educación, and we hope it will increase the quality of the papers published by the journal.
AB - © 2017 Fundacion Infancia y Aprendizaje. The availability of computerized statistical packages allows us to plug in our data and to expect a set of estimates, which we can communicate in our final research report. However, statistical software is not an end; it is only the means. Our responsibility as researchers is to develop a set of arguments that explain why our final methodological choice is the better one, which will yield reliable answers for the study questions within the theoretical setting. Journals of all types require authors to deploy innovative statistical models when analysing collected data. Yet, the problem of advanced modelling strategies still remains — authors disregard key assumptions, choose the wrong analytical strategies and are not aware of alternative strategies to support or reject their hypotheses. This special issue provides readers with a reference framework for some of the most common methodological concerns. The articles included in this monographic issue deal with relatable scenarios and offer state-of-the-art statistical approaches to data treatment. We are confident that this special issue will be extremely useful to past and future authors of Cultura y Educación, and we hope it will increase the quality of the papers published by the journal.
KW - Sample size
KW - Bayesian statistics
KW - Mixed methods
KW - Plausible values
KW - Statistical modelling
UR - https://dialnet.unirioja.es/servlet/articulo?codigo=6264037
U2 - 10.1080/11356405.2017.1368163
DO - 10.1080/11356405.2017.1368163
M3 - Article
SN - 1135-6405
VL - 29
SP - 395
EP - 408
JO - Cultura y Educacion
JF - Cultura y Educacion
IS - 3
ER -