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Benjamin Rohr; John Levi Martin – Sociological Methods & Research, 2024
It is common for social scientists to use formal quantitative methods to compare ecological units such as towns, schools, or nations. In many cases, the size of these units in terms of the number of individuals subsumed in each differs substantially. When the variables in question are counts, there is generally some attempt to neutralize…
Descriptors: Social Science Research, Population Distribution, Ecology, Demography
Anna-Carolina Haensch; Jonathan Bartlett; Bernd Weiß – Sociological Methods & Research, 2024
Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one or more covariates. Negative consequences of missing covariate data include efficiency losses and possible bias. A popular approach to circumventing…
Descriptors: Research Methodology, Research Problems, Social Science Research, Statistical Analysis
Maxi Schulz; Malte Kramer; Oliver Kuss; Tim Mathes – Research Synthesis Methods, 2024
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…
Descriptors: Meta Analysis, Data Analysis, Research Methodology, Research Problems
Hasan Tutar; Mehmet Sahin; Teymur Sarkhanov – Qualitative Research Journal, 2024
Purpose: The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size,…
Descriptors: Research Problems, Sample Size, Qualitative Research, Models
Hampson, Timothy; McKinley, Jim – Research in Education, 2023
Mixed research is a methodology of growing importance both within and without education. This type of research forces researchers to reconcile conflicting ways of justifying and understanding research with results that have the potential to be forward pointing for all researchers. As mixed research has grown, mixed research has gained an…
Descriptors: Mixed Methods Research, Constructivism (Learning), Epistemology, Pragmatics
Julia Meisters; Adrian Hoffmann; Jochen Musch – Sociological Methods & Research, 2024
Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting…
Descriptors: Foreign Countries, Native Speakers, Adults, Cheating
Olivier Fuchs; Craig Robinson – Qualitative Research Journal, 2024
Purpose: Critical realism is an increasingly popular "lens" through which complex events, entities and phenomena can be studied. Yet detailed operationalisations of critical realism are at present relatively scarce. This study's objective here is built on existing debates by developing an open systems model of reality, a basis for…
Descriptors: Realism, Qualitative Research, Research Methodology, Research Problems
Carpentras, Dino; Quayle, Michael – International Journal of Social Research Methodology, 2023
Agent-based models (ABMs) often rely on psychometric constructs such as 'opinions', 'stubbornness', 'happiness', etc. The measurement process for these constructs is quite different from the one used in physics as there is no standardized unit of measurement for opinion or happiness. Consequently, measurements are usually affected by 'psychometric…
Descriptors: Psychometrics, Error of Measurement, Models, Prediction
Seo, Michael; Furukawa, Toshi A.; Karyotaki, Eirini; Efthimiou, Orestis – Research Synthesis Methods, 2023
Clinical prediction models are widely used in modern clinical practice. Such models are often developed using individual patient data (IPD) from a single study, but often there are IPD available from multiple studies. This allows using meta-analytical methods for developing prediction models, increasing power and precision. Different studies,…
Descriptors: Prediction, Models, Patients, Data Analysis
Reiber, Fabiola; Pope, Harrison; Ulrich, Rolf – Sociological Methods & Research, 2023
Randomized response techniques (RRTs) are useful survey tools for estimating the prevalence of sensitive issues, such as the prevalence of doping in elite sports. One type of RRT, the unrelated question model (UQM), has become widely used because of its psychological acceptability for study participants and its favorable statistical properties.…
Descriptors: Surveys, Responses, Cheating, Deception
Isabella Minderop; Bernd Weiß – International Journal of Social Research Methodology, 2023
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…
Descriptors: Prediction, Models, Behavior Patterns, Attrition (Research Studies)
Rodriguez, AE; Rosen, John – Research in Higher Education Journal, 2023
The various empirical models built for enrollment management, operations, and program evaluation purposes may have lost their predictive power as a result of the recent collective impact of COVID restrictions, widespread social upheaval, and the shift in educational preferences. This statistical artifact is known as model drifting, data-shift,…
Descriptors: Models, Enrollment Management, School Holding Power, Data
Tong, Guangyu; Guo, Guang – Sociological Methods & Research, 2022
Meta-analysis is a statistical method that combines quantitative findings from previous studies. It has been increasingly used to obtain more credible results in a wide range of scientific fields. Combining the results of relevant studies allows researchers to leverage study similarities while modeling potential sources of between-study…
Descriptors: Meta Analysis, Social Science Research, Regression (Statistics), Statistical Bias
Nicholas, Graeme; Foote, Jeff – International Journal of Social Research Methodology, 2021
This paper discusses methodological challenges in researching practice. The primary challenge discussed arises from the view that practice is inextricable from its performance, and that performance is embedded in social relations, material infrastructures and historical context. The paper argues for a philosophical hermeneutics approach that works…
Descriptors: Research Problems, Research Methodology, Qualitative Research, Hermeneutics
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation