This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering…

Qualitative comparative analysis (QCA) is an empirical research method that has gained some popularity in the social sciences. At the same time, the literature has long been convinced that QCA is prone to committing causal fallacies when confronted with non-causal data. More specifically, beyond a certain case-to-factor ratio, the method is…

Social scientists seeking to inform policy or public action must carefully consider how to identify effects and express inferences because actions based on invalid inferences will not yield the intended results. Recognizing the complexities and uncertainties of social science, we seek to inform inevitable debates about causal inferences by…

Researchers often seek to synthesize results of multiple studies on the same topic to draw statistical or substantive conclusions and to estimate effect sizes that will inform power analyses for future research. The most popular synthesis approach is meta-analysis. There have been few discussions and applications of other synthesis approaches.…

This article demonstrates how a technique called Agent-Based Modelling can address a significant challenge for effective interdisciplinarity. Different disciplines and research methods make divergent assertions about what a satisfactory explanation requires. However, without a unified framework analysing the implications of these differences…

Obtaining relevant data and conveying limitations of the results are two integral components to a successful statistical analysis. It is difficult for students to internalize a deep understanding of these components using only curated, textbook-style examples. Through hands-on data collection, this activity provides a channel for students to…

Courses: Research methods for undergraduates or graduates. Objectives: The aims of this activity are: (1) to clarify the basics of experimental design; (2) to illustrate the concept of levels of measurement; (3) to demonstrate in-person/hands-on data collection procedures; (4) to understand and practice the steps in null hypothesis testing; and…

Library and information science (LIS) research is becoming more quantitative. However, statistics is not extensively taught within LIS research methods courses, and statistics courses are uncommon within LIS programs. Previous research on statistics in LIS revealed that researchers have mainly relied on descriptive statistics in publications. This…

Purpose: This article presents a basic exploration of Bayesian inference to inform researchers unfamiliar to this type of analysis of the many advantages this readily available approach provides. Method: First, we demonstrate the development of Bayes' theorem, the cornerstone of Bayesian statistics, into an iterative process of updating priors.…

Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…

Evaluating blocked randomized experiments from a potential outcomes perspective has two primary branches of work. The first focuses on larger blocks, with multiple treatment and control units in each block. The second focuses on matched pairs, with a single treatment and control unit in each block. These literatures not only provide different…

Multilevel modeling (MLM) is a statistical technique for analyzing clustered data. Despite its long history, the technique and accompanying computer programs are rapidly evolving. Given the complexity of multilevel models, it is crucial for researchers to provide complete and transparent descriptions of the data, statistical analyses, and results.…

This comment discusses some issues about the use and reporting of experimental studies in education, illustrated by a recently published study that claimed (i) that an educational innovation was effective despite outcomes not reaching statistical significance, and (ii) that this refuted the findings of an earlier study. The two key issues raised…

Psychology teachers have likely heard about the "replication crisis" and the "open science movement" in psychology, and they are probably aware that psychologists have proposed new standards for research practice. How should our psychology courses reflect these new standards? We describe several modern practices that have…