Missing data are common with large scale assessments (LSAs). A typical approach to handling missing data with LSAs is the use of listwise deletion, despite decades of research showing that approach can be a suboptimal strategy resulting in biased estimates. In order to help researchers account for missing data, we provide a tutorial using R and…

The paper has three major objectives. The first objective of the paper is to synthesize and define common categories of meta-analysis. The second objective is to propose a way to comprehend these common categories of meta-analysis through learning from their respective generic conceptual frameworks. The third objective is to point out which R…

This paper puts forward a research agenda in the area of explicit and implicit knowledge and learning of second or additional languages. Based on a brief overview of reliable findings as well as open questions in the field, three agenda items are highlighted. First, valid and reliable measures of explicit and, in particular, implicit knowledge and…

This article examines an important and thorny problem in interview research: How to assess whether what people say motivated their actions actually did so? We ask three questions: What specific challenges are at play? How have researchers addressed them? And how should those strategies be evaluated? We argue that such research faces at least five…

What do we actually do when we research education policy and governance? Why do we tame the messy hinterland of research into smooth accounts and what do we lose in the process? In this volume, distinguished scholars in education policy and governance research discuss how the practice of methods is messy, subjective, and provisional. They approach…

Doubly robust (DR) estimators that combine regression adjustments and inverse probability weighting (IPW) are widely used in causal inference with observational data because they are claimed to be consistent when either the outcome or the treatment selection model is correctly specified (Scharfstein et al., 1999). This property of "double…

Large-scale analyses are a powerful and increasingly common tool for investigating a range of public health and social concerns (Pienta, O'Rourke, & Franks, 2011). This series will provide a primer on large-scale secondary analysis in school psychology, with this article focusing on considerations for researchers interested in applying and…

Qualitative research (QR) has gained visibility and acceptance in the field of special education due to early efforts to identify quality indicators focused on technical and methodological aspects of QR. Whereas these indicators focused on credibility and trustworthiness of data, this article articulates additional QR quality indicators to enhance…

This article is developed from the contents from one of the chapters the researcher has written as part of her PhD thesis. It discusses various methodological challenges the researcher had to face during the phase of data collection in the prisons of Kerala, India, and the strategies adopted to overcome these challenges. This article is intended…

This powerful resource is for researchers and educational leaders who are interested in understanding and applying research methods that emphasize youth voice. The authors argue that most educational research either omits critical understandings of youth or, even worse, presents inaccuracies due to faulty techniques. Researching how youth…

In this paper, we explore the methodological implications of conducting qualitative interviews when researchers and participants come from different social classes. Singling out class on its own terms, rather than considering it as an auxiliary structural factor, we examine the unique challenges that arise during cross-class interviews. Such…

This paper presents best practices for conducting survey research using Amazon Mechanical Turk (MTurk). Readers will learn the benefits, limitations, and trade-offs of using MTurk as compared to other recruitment services, including SurveyMonkey and Qualtrics. A synthesis of survey design guidelines along with a sample survey are presented to help…

Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…

The purpose of this article is to clarify the discrepancy in the use of "queer" as a sexual identity classification in education survey research. This study extends the work completed by Dugan and Yurman (2011), who empirically demonstrated problems with treating LGB students as a homogenous population through collapsing all respondents…

We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…