Background and Context: In 2016, our team designed and implemented a cluster-randomized trial of a school-based empowerment training program, targeting adolescent girls in Nairobi, Kenya (Baiocchi et al., 2019; Rosenman et al., 2020). In that study, the primary outcome was the experience of sexual violence in the prior year. Participants disclosed…

To plan cluster-randomized trials with sufficient statistical power to detect intervention effects on student achievement, researchers need multilevel design parameters, including measures of between-classroom and between-school differences and the amounts of variance explained by covariates at the student, classroom, and school level. Previous…

This rejoinder keeps the original focus on statistical computing pertaining to the correlation of student achievement between mathematics and science from the Trend in Mathematics and Science Study (TIMSS). Albeit the availability of student performance data in TIMSS and the emphasis of the inter-subject connection in the Next Generation Science…

Electronically assisted survey techniques offer several advantages over traditional survey techniques. However, they can also potentially introduce biases, such as coverage biases and measurement error. The current study compares the relative merits of two survey distribution and completion modes: email recruitment with internet completion; and…

Mixed Group Validation (MGV) is an approach for estimating the diagnostic accuracy of tests. MGV is a promising alternative to the more commonly used Known Groups Validation (KGV) approach for estimating diagnostic accuracy. The advantage of MGV lies in the fact that the approach does not require a perfect external validity criterion or gold…

The Total Survey Error (TSE) paradigm provides a framework that supports the effective planning of research, guides decision making about data collection and contextualises the interpretation and dissemination of findings. TSE also allows researchers to systematically evaluate and improve the design and execution of ongoing survey programs and…

Classroom context and climate are inherently classroom-level (L2) constructs, but applied researchers sometimes--inappropriately--represent them by student-level (L1) responses in single-level models rather than more appropriate multilevel models. Here we focus on important conceptual issues (distinctions between climate and contextual variables;…

Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal…

Student's empirical sampling approach is used to assess the magnitude of the sampling errors of statistics describing a recursive causal model. The data were gathered with four complex sample designs commonly used in educational surveys. Jackknife and half-sample error estimates are applied to the data. (Author/CTM)

The presence of artifactual bias in analysis of covariance (ANCOVA) and in matching nonequivalent control group (NECG) designs was empirically investigated. The data set was obtained from a study of the effects of a television program on children from three day care centers in Mexico in which the subjects had been randomly selected within centers.…