Flexibility of Single-Subject Experimental Designs. Part II

1986 ◽  
Vol 51 (3) ◽  
pp. 204-214 ◽  
Author(s):  
Kevin P. Kearns
Keyword(s):  
Clinical Research ◽  
Experimental Designs ◽  
Single Subject ◽  
Treatment Comparison ◽  
General Evaluation ◽  
Evaluation Strategies ◽  
Successive Level ◽  
Research Questions ◽  
Design Selection ◽  
Design Options

The purpose of this paper is to present a taxonomy of single-subject experimental designs and discuss relevant examples that underscore the versatility and flexibility of this approach to clinical research. The proposed taxonomy serves as a heuristic model that may facilitate an understanding of single-subject experimental designs. Four general evaluation strategies employed in applied research—treatment-no treatment comparison, component assessment, treatment-treatment comparison, and successive level analysis—are discussed within this schema. Each of these evaluation strategies is related to commonly posed clinical research questions, and published examples of design options that address these questions are presented. Throughout the discussion basic considerations relating to appropriate design selection are reviewed.

Bias Corrections for Standardized Effect Size Estimates Used With Single-Subject Experimental Designs

2013 ◽  
Vol 82 (3) ◽  
pp. 358-374 ◽  
Author(s):  
Maaike Ugille ◽  
Mariola Moeyaert ◽  
S. Natasha Beretvas ◽  
John M. Ferron ◽  
Wim Van den Noortgate
Keyword(s):  
Effect Size ◽  
Experimental Designs ◽  
Single Subject ◽  
Size Estimates ◽  
Bias Corrections

The Social Value of Research and Health Research Priority-Setting

2021 ◽  
Author(s):  
D.M. Wenner
Keyword(s):  
Clinical Research ◽  
Priority Setting ◽  
Health Research ◽  
Human Subjects ◽  
Social Value ◽  
Research Priority ◽  
The Social ◽  
Research Questions ◽  
Social Scientific ◽  
Health Research Priority Setting

This chapter discusses the social value requirement in clinical research and its intersection with health research priority-setting. The social value requirement states that clinical research involving human subjects is only ethical if it has the potential to produce socially valuable knowledge. The chapter discusses various ways to specify both the justification for and the content of the social value requirement. It goes on to consider the implications of various accounts of the content and justification for the requirement for the ethics of health research priority-setting, showing that while some accounts of the requirement are largely silent with respect to how research questions should be prioritized, others entail robust obligations to prioritize research that might benefit particular groups. The chapter also briefly examines potential arguments for something like a social value requirement in other kinds of research, specifically social scientific research.

scholarly journals Matching research design to clinical research questions

2012 ◽  
Vol 33 (1) ◽  
pp. 49 ◽  
Author(s):  
Sadaf Aslam ◽  
Kedar Mehta ◽  
Helen Georgiev ◽  
Ambuj Kumar
Keyword(s):  
Clinical Research ◽  
Research Design ◽  
Research Questions

scholarly journals Estimands: bringing clarity and focus to research questions in clinical trials

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e052953
Author(s):  
Timothy Peter Clark ◽  
Brennan C Kahan ◽  
Alan Phillips ◽  
Ian White ◽  
James R Carpenter
Keyword(s):  
Clinical Trial ◽  
Sensitivity Analysis ◽  
Clinical Trials ◽  
Clinical Research ◽  
Recent Work ◽  
Treatment Effect ◽  
Research Question ◽  
Probability Of Success ◽  
Research Questions

Precise specification of the research question and associated treatment effect of interest is essential in clinical research, yet recent work shows that they are often incompletely specified. The ICH E9 (R1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials introduces a framework that supports researchers in precisely and transparently specifying the treatment effect they aim to estimate in their clinical trial. In this paper, we present practical examples to demonstrate to all researchers involved in clinical trials how estimands can help them to specify the research question, lead to a better understanding of the treatment effect to be estimated and hence increase the probability of success of the trial.

Comments on Bulterman-Bos: Education Research as a Distributed Activity Across Universities

2008 ◽  
Vol 37 (7) ◽  
pp. 424-428 ◽  
Author(s):  
Ellen Condliffe Lagemann
Keyword(s):  
Education Research ◽  
Problem Solving ◽  
Clinical Research ◽  
Research Universities ◽  
Policy Makers ◽  
Problem Finding ◽  
Finding Study ◽  
Research Questions ◽  
Good Research

In response to Bulterman-Bos (2008) , this article discusses three kinds of research needed in education: problem-finding research, which helps frame good research questions; problem-solving research, which helps illuminate educational problems; and translational work, which transforms the findings of research into tools that practitioners and policy makers need. Clinical research is most important as a form of problem-finding study. Although it is best carried on in “ed schools,” other kinds of education research are best done in other faculties. For this reason, education research should be a distributed activity, encouraged across all the faculties of research universities.

scholarly journals TREC-COVID: rationale and structure of an information retrieval shared task for COVID-19

2020 ◽  
Vol 27 (9) ◽  
pp. 1431-1436 ◽  
Author(s):  
Kirk Roberts ◽  
Tasmeer Alam ◽  
Steven Bedrick ◽  
Dina Demner-Fushman ◽  
Kyle Lo ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Clinical Research ◽  
Data Use ◽  
Iteration Process ◽  
Assessment Process ◽  
Evaluation Metrics ◽  
Test Collection ◽  
Shared Task ◽  
Relevance Criteria ◽  
Research Questions

Abstract TREC-COVID is an information retrieval (IR) shared task initiated to support clinicians and clinical research during the COVID-19 pandemic. IR for pandemics breaks many normal assumptions, which can be seen by examining 9 important basic IR research questions related to pandemic situations. TREC-COVID differs from traditional IR shared task evaluations with special considerations for the expected users, IR modality considerations, topic development, participant requirements, assessment process, relevance criteria, evaluation metrics, iteration process, projected timeline, and the implications of data use as a post-task test collection. This article describes how all these were addressed for the particular requirements of developing IR systems under a pandemic situation. Finally, initial participation numbers are also provided, which demonstrate the tremendous interest the IR community has in this effort.

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