Using secondary data has many advantages, but there are also many limitations, including the lack of relevant information. This article draws on a previous study that used secondary data to investigate substance use in young, elite athletes. Three types of missing data appeared: missing data, lack of information about the data collection process,…

Preventing panel members from attriting is a fundamental challenge for panel surveys. Research has shown that response behavior in earlier waves (response or nonresponse) is a good predictor of panelists' response behavior in upcoming waves. However, response behavior can be described in greater detail by considering the time until the response is…

Small sample sizes contribute to several problems in research and knowledge advancement. This conceptual replication study confirmed and extended the inflation of type II errors and confidence intervals in correlation analyses of small sample sizes common in kinesiology/exercise science. Current population data (N = 18, 230, & 464) on four…

The educational technology field is at a critical juncture, facing the dual pressures of rapid technological advancement and a pressing need for research that genuinely addresses educational challenges. Despite increasing awareness of these issues, a significant amount of educational technology research remains entrenched in superficial or…

This article critically assesses the impact of neoliberal imperatives on academic research, questioning the emphasis on economic benefits over intellectual richness and the ethical implications of such a skewed focus. Drawing on Sara Delamont's metaphor of "the great gates," which conceptualizes distinct research trajectories, a…

Missing covariates is a common issue when fitting meta-regression models. Standard practice for handling missing covariates tends to involve one of two approaches. In a complete-case analysis, effect sizes for which relevant covariates are missing are omitted from model estimation. Alternatively, researchers have employed the so-called…

Shaping public research to enhance its societal contribution has become a key policy concern. Against this background, how research funding may stimulate the societal orientation of scientific research--or how funding is societally targeted--has been underexplored. This article proposes an exploratory approach to characterize societal targeting in…

A wide variety of methodological choices and situations can affect the quality of peer nomination measurements but have not received adequate study. This article begins by focusing on systematic nominator missingness as an example of one such situation. We reanalyzed findings from a recent study by Bukowski, Dirks, Commisso, Velàsquez, and Lopez…

Measuring the existence and patterning of white flight (WF) using aggregate data has a long history in the social sciences. In this article, we assess past measurement approaches and identify several technical and conceptual limitations. To address these shortcomings, we propose a new multicomponent approach to detecting WF that requires tracts to…

Single-case experimental designs (SCEDs) are frequently used to evaluate whether a functional relation exists between interventions and student outcomes. A critical factor in decision making is the evaluation of graphical data, typically displayed in time-series graphs. Distortion in the graphical display of data can lead to invalid decisions on…

Qualitative research sample size determination has always been a contentious and confusing issue. Studies are often vague when explaining the processes and justifications that have been used to determine sample size and strategy. Some provide no mention of sampling at all, whilst others rely too heavily on the concept of saturation for determining…

With the prevalence of missing data in social science research, it is necessary to use methods for handling missing data. One framework in which data with missing values can still be used for parameter estimation is the Bayesian framework. In this tutorial, different missing data mechanisms including Missing Completely at Random, Missing at…

This article analyses and discusses dilemmas, ambivalences and problematic issues related to research ethics. This is done firstly by making a distinction between procedural research ethics and particularistic research ethics. Such a distinction reflects a theoretical construction and generalization. In practice, there can be a very close…

Thematic analysis is a methodology with wide use in content analysis and field work through interviews, observations, and focus groups. Despite popularity with researchers, there are several questions and problems with the methodology. There was an absence in exploration and explanation of the methods and hidden steps in thematic analysis. Using a…

Purpose: Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation…