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Ioana-Elena Oana; Carsten Q. Schneider – Sociological Methods & Research, 2024
The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…
Descriptors: Robustness (Statistics), Qualitative Research, Comparative Analysis, Decision Making
Casement, Christopher J. – International Journal of Mathematical Education in Science and Technology, 2023
Statistical tables associated with named probability distributions and their families, such as the standard normal, Student's t, and chi-square tables, among others, have been utilized for years and are still widely used today, especially for mathematics and statistics education. While such tables can be found in many statistics textbooks and even…
Descriptors: Tables (Data), Statistics Education, Computer Software, Mathematics Education
Parkkinen, Veli-Pekka; Baumgartner, Michael – Sociological Methods & Research, 2023
In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal…
Descriptors: Robustness (Statistics), Comparative Analysis, Causal Models, Models
Lübke, Karsten; Gehrke, Matthias; Horst, Jörg; Szepannek, Gero – Journal of Statistics Education, 2020
Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…
Descriptors: Inferences, Simulation, Attribution Theory, Teaching Methods
Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
Gorard, Stephen – International Journal of Social Research Methodology, 2019
This paper compares the use of confidence intervals (CIs) and a sensitivity analysis called the number needed to disturb (NNTD), in the analysis of research findings expressed as 'effect' sizes. Using 1,000 simulations of randomised trials with up to 1,000 cases in each, the paper shows that both approaches are very similar in outcomes, and each…
Descriptors: Intervals, Statistics, Social Sciences, Foreign Countries
Siegel, Lianne; Chu, Haitao – Research Synthesis Methods, 2023
Reference intervals, or reference ranges, aid medical decision-making by containing a pre-specified proportion (e.g., 95%) of the measurements in a representative healthy population. We recently proposed three approaches for estimating a reference interval from a meta-analysis based on a random effects model: a frequentist approach, a Bayesian…
Descriptors: Bayesian Statistics, Meta Analysis, Intervals, Decision Making
Kuha, Jouni; Mills, Colin – Sociological Methods & Research, 2020
It is widely believed that regression models for binary responses are problematic if we want to compare estimated coefficients from models for different groups or with different explanatory variables. This concern has two forms. The first arises if the binary model is treated as an estimate of a model for an unobserved continuous response and the…
Descriptors: Comparative Analysis, Regression (Statistics), Research Problems, Computation
Merkle, Edgar C.; Fitzsimmons, Ellen; Uanhoro, James; Goodrich, Ben – Grantee Submission, 2021
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…
Descriptors: Bayesian Statistics, Structural Equation Models, Psychometrics, Factor Analysis
Efthimiou, Orestis; White, Ian R. – Research Synthesis Methods, 2020
Standard models for network meta-analysis simultaneously estimate multiple relative treatment effects. In practice, after estimation, these multiple estimates usually pass through a formal or informal selection procedure, eg, when researchers draw conclusions about the effects of the best performing treatment in the network. In this paper, we…
Descriptors: Models, Meta Analysis, Network Analysis, Simulation
Sebastian, TaliaMarie; Qu, Ke; Zeng, Xiangqun – Journal of Chemical Education, 2021
We have revamped a classic analytical chemistry laboratory experiment, "Determination of an Unknown Acid", to provide students an opportunity to learn about new advances in the material sciences and their applications in analytical chemistry in an effort to reinforce the key concepts of chemical analysis. Specifically, students were…
Descriptors: Chemistry, Science Instruction, Teaching Methods, Laboratory Experiments
Chalikias, Miltiadis; Kossieri, Evangelia; Lalou, Panagiota – Teaching Statistics: An International Journal for Teachers, 2020
The aim of this paper is to approach the teaching of the Poisson distribution in a friendly and amusing way. It constitutes a common practice to adopt the main probability distributions in order to predict results of sport events and to estimate the win return of betting activities (Chalikias 2009). In particular, by using the Poisson…
Descriptors: Decision Making, Team Sports, Probability, Statistics
Reiser, Elana – Mathematics Teacher: Learning and Teaching PK-12, 2021
The two most popular decision-making processes are tossing a coin and playing rock, paper, scissors. In the activity described in this article, students find the theoretical probabilities of winning a coin toss and a round of the rock, paper, scissors game. They next devise strategies to win and test them out. Students then compare the theoretical…
Descriptors: Probability, Mathematics Instruction, Decision Making, Learning Activities
Frischemeier, Daniel; Leavy, Aisling – Teaching Statistics: An International Journal for Teachers, 2020
Posing statistical questions is a fundamental and often overlooked component of statistical inquiry. In this paper, we provide an overview of shared understandings regarding what constitutes a good statistical question. We then describe three approaches--a checklist for improving statistical questions, a three-phase feedback activity, and a…
Descriptors: Statistics, Teaching Methods, Questioning Techniques, Check Lists
Rutten, Roel – Sociological Methods & Research, 2022
Applying qualitative comparative analysis (QCA) to large Ns relaxes researchers' case-based knowledge. This is problematic because causality in QCA is inferred from a dialogue between empirical, theoretical, and case-based knowledge. The lack of case-based knowledge may be remedied by various robustness tests. However, being a case-based method,…
Descriptors: Comparative Analysis, Correlation, Case Studies, Attribution Theory

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