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…

Critical quantitative methods provide opportunities for Queer Theory to challenge, re-define, and re-claim the historically privileged research tradition. In this paper, I begin by summarizing the various binaries that oppress research and individuality. I then engage with Queer Theory and my own intersectional positionality to propose a nonbinary…

Missing data result in less precise and possibly biased effect estimates in single studies. Bias arising from studies with incomplete outcome data is naturally propagated in a meta-analysis. Conventional analysis using only individuals with available data is adequate when the meta-analyst can be confident that the data are missing at random (MAR)…

In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of…

This article addresses the problem of estimating the proportion Pi[subscript S] of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is…

Treatment effect estimates from a "regression discontinuity design" (RDD) have high internal validity. However, the arguments that support the design apply to a subpopulation that is narrower and usually different from the population of substantive interest in evaluation research. The disconnect between RDD population and the…

Multiple imputation (MI), a two-stage process whereby missing data are imputed multiple times and the resulting estimates of the parameter(s) of interest are combined across the completed datasets, is becoming increasingly popular for handling missing data. However, MI can result in biased inference if not carried out appropriately or if the…

Unlike in elementary schools, high school teacher effects may be confounded with unobserved track-level treatments (such as the AVID program) that are correlated with individual teachers. I present a strategy that exploits detailed course-taking information to credibly estimate the effects of 9th grade Algebra and English teachers on test scores.…

Many states, and the United States as a whole, are doing a better job than they were two years ago of preparing students for college and expanding access to higher education, according to a national report card on higher education released last week. But the country continues to slip behind other nations on measures of enrollment and degree…

Education research rarely lends itself to large scale experimental research and true randomization, leaving the researcher to quasi-experimental designs. The problem with quasi-experimental research is that underlying factors may impact group selection and lead to potentially biased results. One way to minimize the impact of non-randomization is…

The latest national report card on higher education, as in the past, handed out a lot of "incompletes." Like the student who keeps forgetting to turn in that lab report, the grades can't be computed without all the data. There's a lot policy makers don't know about their states' higher-education performance, and the gaps in information limit the…

Describes a sampling strategy which involves linked pairs of persons used to obtain bereaved respondents for a study examining loss and coping responses following a recent natural disaster. The sampling procedure appeared not to produce an obvious bias and was very beneficial in meeting the research objectives. (Author/NRB)

This chapter provides an overview of sampling methods that are appropriate for conducting online surveys. The authors review some of the basic concepts relevant to online survey sampling, present some probability and nonprobability techniques for selecting a sample, and briefly discuss sample size determination and nonresponse bias. Although some…

Presents procedures for reducing attrition in clinical research and provides a case study for examination by researchers. Includes lists of preventative strategies and statistical methodologies to reduce attrition and bias. Argues that early planning for attrition by adjusting sample sizes is a scientifically sound approach to clinical research…

Among the varied analytical challenges institutional researchers face, examining faculty pay may be one of the most vexing. Although the literature on faculty compensation analysis dates back to the 1970s (Loeb and Ferber, 1971; Gordon, Morton, and Braden, 1974; Scott, 1977; Braskamp and Johnson, 1978; McLaughlin, Smart, and Montgomery, 1978),…