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Autoren Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H.  
Titel Dealing with item nonresponse in large-scale cognitive assessments. The impact of missing data methods on estimated explanatory relationships.  
URL https://doi.org/10.1111/jedm.12154  
URN, persistent 10.1111/jedm.12154  
Erscheinungsjahr 2017, Jg. 54, H. 4  
Seitenzahl S. 397-419  
Zeitschrift Journal of educational measurement  
ISSN 0022-0655; 1745-3984  
Dokumenttyp Zeitschriftenaufsatz; gedruckt; online  
Beigaben Literaturangaben, Abbildungen, Tabellen  
Sprache englisch  
Forschungsschwerpunkt Bildungspanel (NEPS)  
Schlagwörter Kompetenzmessung; Itemanalyse; Antwortverhalten; Antwortvergleich; Strukturmodell; Regressionsanalyse;  
Abstract Competence data from low‐stakes educational large‐scale assessment studies allow for evaluating relationships between competencies and other variables. The impact of item‐level nonresponse has not been investigated with regard to statistics that determine the size of these relationships (e.g., correlations, regression coefficients). Classical approaches such as ignoring missing values or treating them as incorrect are currently applied in many large‐scale studies, while recent model‐based approaches that can account for nonignorable nonresponse have been developed. Estimates of item and person parameters have been demonstrated to be biased for classical approaches when missing data are missing not at random (MNAR). In our study, we focus on parameter estimates of the structural model (i.e., the true regression coefficient when regressing competence on an explanatory variable), simulating data according to various missing data mechanisms. We found that model‐based approaches and ignoring missing values performed well in retrieving regression coefficients even when we induced missing data that were MNAR. Treating missing values as incorrect responses can lead to substantial bias. We demonstrate the validity of our approach empirically and discuss the relevance of our results (Orig.).  
Förderkennzeichen 01GJ0888