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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
Jill Fenton Taylor; Ivana Crestani – Qualitative Research Journal, 2024
Purpose: This paper aims to explore how an academic researcher and a practitioner experience scepticism for their qualitative research. Design/methodology/approach: The study applies Olt and Teman's new conceptual phenomenological polyethnography (2019) methodology, a hybrid of phenomenology and duoethnography. Findings: For the…
Descriptors: Qualitative Research, Phenomenology, Ethnography, Bias
Kacey Beddoes – International Journal of Social Research Methodology, 2024
Despite their many benefits, longitudinal studies are much less common than one-time data collection or pre-post intervention designs. One reason for their scarcity is that longitudinal studies introduce requirements and challenges that non-longitudinal studies do not. One of the biggest challenges is participant attrition. In order to help…
Descriptors: Longitudinal Studies, Attrition (Research Studies), Research Problems, Research Methodology
Aasli Abdi Nur; Christine Leibbrand; Sara R. Curran; Elizabeth Votruba-Drzal; Christina Gibson-Davis – International Journal of Social Research Methodology, 2024
With the increasing sophistication of online survey tools and the necessity of distanced research during the COVID-19 pandemic, the use of online questionnaires for research purposes has proliferated. Still, many researchers undertake online survey research without knowledge of the prevalence and likelihood of experiencing survey questionnaire…
Descriptors: Parents, Child Caregivers, Online Surveys, Deception
Bing Lu; Emily F. Henderson – Studies in Graduate and Postdoctoral Education, 2025
Purpose: This paper contends that data generated by research on supervision are often taken as authentic data. Through an examination of studies that use audio/visual recordings to investigate supervision, the paper both promotes and problematises the recording of supervision meetings as a useful technique for doctoral supervision research. This…
Descriptors: Foreign Countries, Doctoral Students, Supervision, Research Methodology
Yinying Wang; Joonkil Ahn – Educational Management Administration & Leadership, 2025
School leadership research literature has a large number of widely used constructs. Could fewer constructs bring more clarity? This study evaluates construct content validity, defined as the extent to which a measure's items reflect a theoretical content domain, in school leadership literature. To do so, we reviewed 29 articles that used Teaching…
Descriptors: Network Analysis, Construct Validity, Content Validity, Instructional Leadership
Terry A. Beehr; Minseo Kim; Ian W. Armstrong – International Journal of Social Research Methodology, 2024
Previous research extensively studied reasons for and ways to avoid low response rates, but it largely ignored the primary research issue of the degree to which response rates matter, which we address. Methodological survey research on response rates has been concerned with how to increase responsiveness and with the effects of response rates on…
Descriptors: Surveys, Response Rates (Questionnaires), Effect Size, Research Methodology
David Bruns-Smith; Oliver Dukes; Avi Feller; Elizabeth L. Ogburn – Grantee Submission, 2024
We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning (AutoDML). These popular "doubly robust" or "de-biased machine learning estimators" combine outcome modeling with balancing weights -- weights that achieve covariate balance directly in lieu of estimating and…
Descriptors: Regression (Statistics), Weighted Scores, Data Analysis, Robustness (Statistics)
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
Micaela Sánchez-Martín; Marta Gutiérrez-Sánchez; Eva María Olmedo-Moreno; Fernando Navarro-Mateu – Cogent Education, 2024
Introduction: Concerns about the risk of bias (RoB) of Meta-analysis (MAs) have grown in parallel with the exponential increase in the number of publications in science. However, this has not been properly assessed in Education. The aims were to evaluate the RoB of MAs in Education and to identify potential predictors of a lower RoB. Methods:…
Descriptors: Literature Reviews, Meta Analysis, Bias, Research Problems
Maya B. Mathur – Research Synthesis Methods, 2024
As traditionally conceived, publication bias arises from selection operating on a collection of individually unbiased estimates. A canonical form of such selection across studies (SAS) is the preferential publication of affirmative studies (i.e., those with significant, positive estimates) versus nonaffirmative studies (i.e., those with…
Descriptors: Meta Analysis, Research Reports, Research Methodology, Research Problems
Micheal Sandbank; Kristen Bottema-Beutel; Ya-Cing Syu; Nicolette Caldwell; Jacob I. Feldman; Tiffany Woynaroski – Autism: The International Journal of Research and Practice, 2024
We conducted a multi-pronged investigation of different types of reporting bias in autism early childhood intervention research. First, we investigated the prevalence of reporting failures of completed trials registered on clinicaltrials.gov, and found that only 7% of registered trials were updated with results on the registration platform and…
Descriptors: Literature Reviews, Meta Analysis, Autism Spectrum Disorders, Children
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