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The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients
BACKGROUND: Various studies have shown that caregiving relatives of schizophrenic patients are at risk of suffering from depression. These studies differ with respect to the applied statistical methods, which could influence the findings. Therefore, the present study analyzes to which extent differe...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4917596/ https://www.ncbi.nlm.nih.gov/pubmed/27294269 http://dx.doi.org/10.1007/s40211-016-0180-3 |
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author | Alexandrowicz, Rainer W. Jahn, Rebecca Friedrich, Fabian Unger, Anne |
author_facet | Alexandrowicz, Rainer W. Jahn, Rebecca Friedrich, Fabian Unger, Anne |
author_sort | Alexandrowicz, Rainer W. |
collection | PubMed |
description | BACKGROUND: Various studies have shown that caregiving relatives of schizophrenic patients are at risk of suffering from depression. These studies differ with respect to the applied statistical methods, which could influence the findings. Therefore, the present study analyzes to which extent different methods may cause differing results. METHODS: The present study contrasts by means of one data set the results of three different modelling approaches, Rasch Modelling (RM), Structural Equation Modelling (SEM), and Linear Regression Modelling (LRM). RESULTS: The results of the three models varied considerably, reflecting the different assumptions of the respective models. CONCLUSIONS: Latent trait models (i. e., RM and SEM) generally provide more convincing results by correcting for measurement error and the RM specifically proves superior for it treats ordered categorical data most adequately. |
format | Online Article Text |
id | pubmed-4917596 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer Vienna |
record_format | MEDLINE/PubMed |
spelling | pubmed-49175962016-07-07 The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients Alexandrowicz, Rainer W. Jahn, Rebecca Friedrich, Fabian Unger, Anne Neuropsychiatr Original Article BACKGROUND: Various studies have shown that caregiving relatives of schizophrenic patients are at risk of suffering from depression. These studies differ with respect to the applied statistical methods, which could influence the findings. Therefore, the present study analyzes to which extent different methods may cause differing results. METHODS: The present study contrasts by means of one data set the results of three different modelling approaches, Rasch Modelling (RM), Structural Equation Modelling (SEM), and Linear Regression Modelling (LRM). RESULTS: The results of the three models varied considerably, reflecting the different assumptions of the respective models. CONCLUSIONS: Latent trait models (i. e., RM and SEM) generally provide more convincing results by correcting for measurement error and the RM specifically proves superior for it treats ordered categorical data most adequately. Springer Vienna 2016-06-13 2016 /pmc/articles/PMC4917596/ /pubmed/27294269 http://dx.doi.org/10.1007/s40211-016-0180-3 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Alexandrowicz, Rainer W. Jahn, Rebecca Friedrich, Fabian Unger, Anne The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients |
title | The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients |
title_full | The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients |
title_fullStr | The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients |
title_full_unstemmed | The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients |
title_short | The importance of statistical modelling in clinical research: Comparing multidimensional Rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients |
title_sort | importance of statistical modelling in clinical research: comparing multidimensional rasch-, structural equation and linear regression models for analyzing the depression of relatives of psychiatric patients |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4917596/ https://www.ncbi.nlm.nih.gov/pubmed/27294269 http://dx.doi.org/10.1007/s40211-016-0180-3 |
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