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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
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
Lu, Peiyi; Shelley, Mack – International Journal of Social Research Methodology, 2023
Imputation or likelihood-based approaches to handle missing data assume the data are missing completely at random (MCAR) or missing at random (MAR). However, little research has examined the missingness pattern before using these imputation/likelihood methods. Three missingness mechanisms -- MCAR, MAR, and not missing at random (NMAR) -- can be…
Descriptors: Research Methodology, Longitudinal Studies, Health, Retirement
Bryan J. Duarte – Educational Studies: Journal of the American Educational Studies Association, 2024
Critical quantitative methods provide opportunities for Queer Theory to challenge, re-define, and re-claim the historically privileged research tradition. In this paper, I begin by summarizing the various binaries that oppress research and individuality. I then engage with Queer Theory and my own intersectional positionality to propose a nonbinary…
Descriptors: Statistical Analysis, Research Methodology, Social Justice, Homosexuality
Menglin Xu; Jessica A. R. Logan – Educational and Psychological Measurement, 2024
Research designs that include planned missing data are gaining popularity in applied education research. These methods have traditionally relied on introducing missingness into data collections using the missing completely at random (MCAR) mechanism. This study assesses whether planned missingness can also be implemented when data are instead…
Descriptors: Research Design, Research Methodology, Monte Carlo Methods, Statistical Analysis
Babcock, Ben; Marks, Peter E. L.; van den Berg, Yvonne H. M.; Cillessen, Antonius H. N. – International Journal of Behavioral Development, 2022
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…
Descriptors: Research Methodology, Peer Relationship, Statistical Analysis, Error Patterns
Lund, Thorleif – Scandinavian Journal of Educational Research, 2022
Criteria are briefly proposed for final conclusions, research problems, and research hypotheses in quantitative research. Moreover, based on a proposed definition of applied and basic/general research, it is argued that (1) in applied quantitative research, while research problems are necessary, research hypotheses are unjustified, and that (2) in…
Descriptors: Research Problems, Research Methodology, Hypothesis Testing, Statistical Analysis
Paul J. Dizona – ProQuest LLC, 2022
Missing data is a common challenge to any researcher in almost any field of research. In particular, human participants in research do not always respond or return for assessments leaving the researcher to rely on missing data methods. The most common methods (i.e., Multiple Imputation and Full Information Maximum Likelihood) assume that the…
Descriptors: Pretests Posttests, Research Design, Research Problems, Dropouts
Huang, Francis L. – Gifted Child Quarterly, 2020
Multivariate analysis of variance (MANOVA) is a statistical procedure commonly used in fields such as education and psychology. However, MANOVA's popularity may actually be for the wrong reasons. The large majority of published research using MANOVA focus on univariate research questions rather than on the multivariate questions that MANOVA is…
Descriptors: Multivariate Analysis, Research Methodology, Research Problems, Statistical Analysis
Lorette, Pernelle – Journal of Multilingual and Multicultural Development, 2023
Quantitative social scientists have adopted the positivist epistemology and methodology of natural sciences, seeking objectivity, generalisability, and neutrality. However, in social sciences -- unlike in natural sciences -- humans are both the investigators and the object of investigation, leading to intricate interconnections between researchers…
Descriptors: Social Sciences, Statistical Analysis, Research Problems, Interpersonal Relationship
Ting, Carol; Fitzgerald, Richard – International Journal of Social Research Methodology, 2020
Contrary to its typical presentation in scientific publications as a certain and linear process, in reality, the experimental method, not least the design aspect of it, requires a great deal of trial-and-error and ad hoc decision-making on the part of the researchers. This uncertain and contingent aspect of research, although little known outside…
Descriptors: Research Design, Logical Thinking, Research Methodology, Ethnography
Katz-Buonincontro, Jen; Anderson, Ross C. – Journal of Creative Behavior, 2020
This paper reports on an integrative literature review of published articles that used either quantitative or qualitative observation methods to research creativity in learning contexts. Observation is an empirical research method used in quantitative and qualitative naturalistic studies focused on understanding behavior and interactions as they…
Descriptors: Educational Research, Research Methodology, Qualitative Research, Statistical Analysis
Sim, Julius; Saunders, Benjamin; Waterfield, Jackie; Kingstone, Tom – International Journal of Social Research Methodology, 2018
There has been considerable recent interest in methods of determining sample size for qualitative research a priori, rather than through an adaptive approach such as saturation. Extending previous literature in this area, we identify four distinct approaches to determining sample size in this way: rules of thumb, conceptual models, numerical…
Descriptors: Sample Size, Qualitative Research, Research Methodology, Statistical Analysis
Thompson, W. Burt – Teaching of Psychology, 2019
When a psychologist announces a new research finding, it is often based on a rejected null hypothesis. However, if that hypothesis is true, the claim is a false alarm. Many students mistakenly believe that the probability of committing a false alarm equals alpha, the criterion for statistical significance, which is typically set at 5%. Instructors…
Descriptors: Statistical Analysis, Hypothesis Testing, Misconceptions, Data Interpretation
Chou, Winston; Imai, Kosuke; Rosenfeld, Bryn – Sociological Methods & Research, 2020
Scholars increasingly rely on indirect questioning techniques to reduce social desirability bias and item nonresponse for sensitive survey questions. The major drawback of these approaches, however, is their inefficiency relative to direct questioning. We show how to improve the statistical analysis of the list experiment, randomized response…
Descriptors: Surveys, Test Items, Questioning Techniques, Statistical Analysis