While conflict event data sets are increasingly used in contemporary conflict research, important concerns persist regarding the quality of the collected data. Such concerns are not necessarily new. Yet, because the methodological debate and evidence on potential errors remains scattered across different subdisciplines of social sciences, there is…

Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data--in particular, polygenic scores--in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened…

All students, from college freshmen to advanced graduate students, have asked themselves, "Will this decision make me happy?" The vast majority of them have been wrong. Affective forecasting, the process of predicting future feelings, is a topic of great interest to students due to its applicable and highly relatable nature. This article…

The aim of this paper is to provide an introduction of new imputation algorithms for estimating missing values from official statistics in larger data sets of data pre-processing, or outliers. The goal is to propose a new algorithm called IRMI (iterative robust model-based imputation). This algorithm is able to deal with all challenges like…

This discussion constructs a survey data quality strategy for institutional researchers in higher education in light of total survey error theory. It starts with describing the characteristics of institutional research and identifying the gaps in literature regarding survey data quality issues in institutional research and then introduces the…

Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…

This manual has been produced to familiarize data users with the design, and the procedures followed for data collection and processing, in the base year and first follow-up of the High School Longitudinal Study of 2009 (HSLS:09), with emphasis on the first follow-up. It also provides the necessary documentation for use of the public-use data…

The manual that accompanies these appendices was produced to familiarize data users with the design, and the procedures followed for data collection and processing, in the base year and first follow-up of the High School Longitudinal Study of 2009 (HSLS:09), with emphasis on the first follow-up. It also provides the necessary documentation for use…

Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and…

This chapter summarizes ten selected issues and common problems that arise in most assessment research projects. These include: (1) the uses of grades in assessment; (2) institutional review boards; (3) research design as a compromise; (4) standardized testing; (5) self-reported measures; (6) missing data; (7) weighting data; (8) conditional…

This paper presents an argument against the wider adoption of complex forms of data analysis, using multi-level modeling (MLM) as an extended case study. MLM was devised to overcome some deficiencies in existing datasets, such as the bias caused by clustering. The paper suggests that MLM has an unclear theoretical and empirical basis, has not led…

Taxometric procedures provide an empirical means of determining which psychiatric disorders are typologically distinct from normal behavioral functioning. Although most disorders reflect extremes along continuously distributed behavioral traits, identifying those that are discrete has important implications for accurate diagnosis, effective…

Suggests that there is a tendency in social science and program evaluation to adhere to some methodological practices by force of custom rather than because of their reasoned applicability. These ideas include regression artifacts, random measurement error, and change or gain scores. (Author/SLD)

Agrees with L. Mohr that researchers are too quick to assume that measurement error is random, but disagrees that the idea of regression toward the mean has been a distraction and the notion that change scores analysis should be avoided in favor of regression analysis. (SLD)

Responds to C. S. Reichardt's discussion of regression artifacts, random measurement error, and change scores. Emphasizes that attention to regression artifacts in program evaluation is almost bound to be problematic and proposes some arguments in support of this position. (SLD)