The importance of statistical modelling in clinical research

作     者：Alexandrowicz, Rainer W. Jahn, Rebecca Friedrich, Fabian Unger, Anne 

作者机构：Alps Adria Univ Klagenfurt Dept Appl Psychol & Methods Res Inst Psychol Univ Str 65-67 A-9020 Klagenfurt Austria Med Univ Vienna Dept Psychiat & Psychotherapy Clin Div Social Psychiat Vienna Austria 

出 版 物：《NEUROPSYCHIATRIE》 (Neuropsychiatrie)

年 卷 期：2016年第30卷第2期

页      面：92-102页

学科分类：1002[医学-临床医学] 10[医学] 

基　　金：Jubilaumsfonds der Osterreichischen Nationalbank 

主　　题：Rasch Model Structural Equation Model Linear Regression Model Latent regression Model comparison 

摘      要：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. 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). The results of the three models varied considerably, reflecting the different assumptions of the respective models. 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.