Not knowing the population size is a common problem in data-limited contexts. Drawing on work in Sierra Leone, this short take outlines a four-step solution to this problem: (1) estimate the population size using expert interviews; (2) verify estimates using interviews with participants sampled; (3) triangulate using secondary data; and (4)…

Physical activity (PA) promotion is an ideal intervention target for public health because it has the potential to help individuals feel better, sleep better, and perform daily tasks more easily, in addition to providing disease prevention benefits. There is strong evidence that individual-level theory-based behavioral interventions are effective…

Mass adoption of advanced information technologies is fueling a need for public servants with the skills to manage data-driven public agencies. Public employees typically acquire data skills through graduate research methods courses, which focus primarily on research design and statistical analysis. What data skills are currently taught, and what…

Public administration is struggling to contend with a substantial shift in practice fueled by the accelerating adoption of information technology. New skills, competencies and pedagogies are required by the field to help overcome the data-skills gap. As a means to address these deficiencies, we introduce the Data Science Literacy Framework, a…

The growing number of interpretive lenses used in mathematics education research are often seen in terms of either/or, such as the individual or the social, the discursive or the bodily, the classroom interactive or the neurological events, the humanist or the post-humanist. We propose stratigraphy as a research (meta-)method that is conjunctive…

This article synthesizes ideas that emerged over the course of a 10-week symposium titled "Teaching Reproducible Research: Educational Outcomes" https://www.projecttier.org/fellowships-and-workshops/2021-spring-symposium that took place in the spring of 2021. The speakers included one linguist, three political scientists, seven…

The What Works Clearinghouse (WWC) uses the term "baseline equivalence" when determining if the intervention group (those that received the intervention of interest) and the comparison group (those that did not receive the intervention) had characteristics that were similar enough ("equivalent") at the start of the study (at…

Thematic analysis is frequently used to analyse qualitative data in psychology, healthcare, social research and beyond. An important stage in planning a study is determining how large a sample size may be required, however current guidelines for thematic analysis are varied, ranging from around 2 to over 400 and it is unclear how to choose a value…

The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the "Journal of Problem Solving." The Bayes factor provides information with a similar purpose to the "p"-value--to allow the researcher to make…

Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and…

A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…

The aim of this paper is to provide an introduction of new imputation algorithms for estimating missing values from official statistics in larger data sets of data pre-processing, or outliers. The goal is to propose a new algorithm called IRMI (iterative robust model-based imputation). This algorithm is able to deal with all challenges like…

Researchers must make numerous choices when conducting factor analyses, each of which can have significant ramifications on the model results. They must decide on an appropriate sample size to achieve accurate parameter estimates and adequate power, a factor model and estimation method, a method for determining the number of factors and evaluating…

Racial/ethnic diversity has become an increasingly important variable in the social sciences. Research from multiple disciplines consistently demonstrates the tremendous impact of ethnic diversity on individuals and organizations. Investigators use a variety of measures, and their choices can affect the conclusions that can be drawn and limit the…

This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…