In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…

This dissertation is aimed at investigating the impact of missing data and evaluating the performance of five selected methods for handling missing responses in the implementation of Cognitive Diagnostic Models (CDMs). The five methods are: a) treating missing data as incorrect (IN), b) person mean imputation (PM), c) two-way imputation (TW), d)…

Apprentice and trainee data are reported by the State and Territory Training Authorities to National Centre for Vocational Education Research (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred…

This methodological brief introduces basic procedures and issues for conducting a high-quality meta-analysis in gifted education. Specifically, we discuss issues such as how to select a topic and formulate research problems, search for and identify qualified studies, code studies and extract data, choose and calculate effect sizes, analyze data,…

It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…

Two-phase designs in epidemiological studies of autism prevalence introduce methodological complications that can severely limit the precision of resulting estimates. If the assumptions used to derive the prevalence estimate are invalid or if the uncertainty surrounding these assumptions is not properly accounted for in the statistical inference…

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

Apprentice and trainee data are reported by the State and Territory Training Authorities to NCVER (National Centre for Vocational Education Research) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred…

Apprentice and trainee data are reported by the state and territory training authorities to the National Centre for Vocational Education and Training (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as collection 1. The sets of data submitted in subsequent quarters are…

Instrumental variable estimators hold the promise of enabling researchers to estimate the effects of educational treatments that are not (or cannot be) randomly assigned but that may be affected by randomly assigned interventions. Examples of the use of instrumental variables in such cases are increasingly common in educational and social science…

This methodological note illustrates how a commonly used calculation of the Delta-p statistic is inappropriate for categorical independent variables, and this note provides users of logistic regression with a revised calculation of the Delta-p statistic that is more meaningful when studying the differences in the predicted probability of an…

Data analysis is critical to educational planning. Determining the number of school leavers is crucial for a school board when planning for interventions and supports. In researching the number of early school leavers in the province of Prince Edward Island, the method in which the data were reported affected the rates. Two critical considerations…

Risks of life on the street caused by inclement weather, harassment, and assault threaten the unsheltered homeless population. We address some challenges of enumerating the street homeless population by testing a novel capture-recapture (CR) estimation approach that models individuals' intermittent daytime visibility. We tested walking and…

This paper details the challenges encountered by authors summarizing evidence from a primary study to describe a treatment's effectiveness using an effect size (ES) estimate. Dilemmas that are encountered, including how to calculate and interpret the pertinent standardized mean difference ES for results from studies of various research designs,…