Two-Method Planned Missing Designs for Longitudinal Research

We examine longitudinal extensions of the two-method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-measure constructs. These designs use a combination of two measures: a “gold standard” that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based) measure that contains systematic measurement bias (e.g., response bias). Using simulated data on four measurement occasions, we compared the cost-efficiency and validity of longitudinal designs where the gold standard is measured at one or more measurement occasions. We manipulated the nature of the response bias over time (constant, increasing, fluctuating), the factorial structure of the response bias over time, and the constraints placed on the latent variable model. Our results showed that parameter bias is lowest when the gold standard is measured on at least two occasions. When a multifactorial structure was used to model response bias over time, it is necessary to have the “gold standard” measures included at every time point, in which case most of the parameters showed low bias. Almost all parameters in all conditions displayed high relative efficiency, suggesting that the 2-method design is an effective way to reduce costs and improve both power and accuracy in longitudinal research

Crossing MGLS with the Middle Grades Research Agenda: A Guide for Researchers

For the past several years, leaders in middle grades education research have strengthened their call for more methodologically robust quantitative research to address important questions in the field. Recently, two important routes towards addressing this call have emerged: the Middle Grades Longitudinal Study from the National Center for Education Statistics, and a new research agenda from the Middle Level Education Research Special Interest Group of the American Educational Research Association. In this paper, we conduct a content analysis of the items in the forthcoming longitudinal study in light of the extant research agenda. Results indicate that research questions in eight sections of the agenda are moderately to well-addressed by the data, and that the longitudinal study will provide rich contextual data related to many others. The concurrent emergence of the research agenda and this data offers an opportunity for the research community to engage in high-level quantitative research with a middle grades lens to inform future policy. The item-by-item crosswalk available for download (scroll down for link below) provides guidance for researchers using the Middle Grades Longitudinal Study data to address questions from the research agenda

Workforce participation: developing a theoretical framework for longitudinal research

This paper describes and evaluates an action research project on workforce participation at Viewpoint Research Community Interest Company (CIC). By setting out the research protocols devised by Viewpoint to stimulate and study co-operative management, it is possible to abstract a theoretical framework that emerged from a pilot case study. The paper contributes to theory by highlighting not only the potential of action research to catalyse interest in co operative management but also how to engage theoretically with the paradox of a workforce voting to limit its own participation in ownership, governance and management. In this study, the authors interpreted that participants did not automatically equate participatory management with workplace democracy leading to a theoretical perspective that “democratic management is the propensity and capacity of management systems to respond to members’ desires regarding the scope, depth, level and quality of participation in management”. The paper concludes by evaluating the efficacy of Viewpoint’s action research methodology as a strategy for deepening knowledge on workforce participation in co-operatives and employee-owned businesses

A Review on Joint Models in Biometrical Research

In some fields of biometrical research joint modelling of longitudinal measures and event time data has become very popular. This article reviews the work in that area of recent fruitful research by classifying approaches on joint models in three categories: approaches with focus on serial trends, approaches with focus on event time data and approaches with equal focus on both outcomes. Typically longitudinal measures and event time data are modelled jointly by introducing shared random effects or by considering conditional distributions together with marginal distributions. We present the approaches in an uniform nomenclature, comment on sub-models applied to longitudinal measures and event time data outcomes individually and exemplify applications in biometrical research