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Showing all 11 results Save | Export
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Konstantina Chalkou; Tasnim Hamza; Pascal Benkert; Jens Kuhle; Chiara Zecca; Gabrielle Simoneau; Fabio Pellegrini; Andrea Manca; Matthias Egger; Georgia Salanti – Research Synthesis Methods, 2024
Some patients benefit from a treatment while others may do so less or do not benefit at all. We have previously developed a two-stage network meta-regression prediction model that synthesized randomized trials and evaluates how treatment effects vary across patient characteristics. In this article, we extended this model to combine different…
Descriptors: Medical Research, Outcomes of Treatment, Risk, Randomized Controlled Trials
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Pedder, Hugo; Boucher, Martin; Dias, Sofia; Bennetts, Margherita; Welton, Nicky J. – Research Synthesis Methods, 2020
Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies…
Descriptors: Simulation, Randomized Controlled Trials, Meta Analysis, Comparative Analysis
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Pearl, Judea – Sociological Methods & Research, 2017
We address the task of determining, from statistical averages alone, whether a population under study consists of several subpopulations, unknown to the investigator, each responding to a given treatment markedly differently. We show that such determination is feasible in three cases: (1) randomized trials with binary treatments, (2) models where…
Descriptors: Statistical Analysis, Models, Social Science Research, Randomized Controlled Trials
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Zhao, Siyuan; Heffernan, Neil – International Educational Data Mining Society, 2017
Personalized learning considers that the causal effects of a studied learning intervention may differ for the individual student. Making the inference about causal effects of studies interventions is a central problem. In this paper we propose the Residual Counterfactual Networks (RCN) for answering counterfactual inference questions, such as…
Descriptors: Computation, Outcomes of Treatment, Networks, Randomized Controlled Trials
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Chaney, Bradford – American Journal of Evaluation, 2016
The primary technique that many researchers use to analyze data from randomized control trials (RCTs)--detecting the average treatment effect (ATE)--imposes assumptions upon the data that often are not correct. Both theory and past research suggest that treatments may have significant impacts on subgroups even when showing no overall effect.…
Descriptors: Randomized Controlled Trials, Data Analysis, Outcomes of Treatment, Simulation
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Shire, Stephanie Y.; Chang, Ya-Chih; Shih, Wendy; Bracaglia, Suzanne; Kodjoe, Maria; Kasari, Connie – Journal of Child Psychology and Psychiatry, 2017
Background: Interventions found to be effective in research settings are often not as effective when implemented in community settings. Considering children with autism, studies have rarely examined the efficacy of laboratory-tested interventions on child outcomes in community settings using randomized controlled designs. Methods: One hundred and…
Descriptors: Early Intervention, Toddlers, Autism, Attention
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Olivera, Carolina M. X.; Vianna, Elcio Oliveira; Bonizio, Roni C.; de Menezes, Marcelo B.; Ferraz, Erica; Cetlin, Andrea A.; Valdevite, Laura M.; Almeida, Gustavo A.; Araujo, Ana S.; Simoneti, Christian S.; de Freitas, Amanda; Lizzi, Elisangela A.; Borges, Marcos C.; de Freitas, Osvaldo – Health Education Research, 2016
Information for patients provided by the pharmacist is reflected in adhesion to treatment, clinical results and patient quality of life. The objective of this study was to assess an asthma self-management model for rational medicine use. This was a randomized controlled trial with 60 asthmatic patients assigned to attend five modules presented by…
Descriptors: Diseases, Self Management, Randomized Controlled Trials, Models
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Trudeau, Kimberlee J.; Black, Ryan A.; Kamon, Jody L.; Sussman, Steve – Child & Youth Care Forum, 2017
Background: An Internet-based relapse prevention supplement to adolescent substance abuse treatment programming is a promising modality to reinforce treatment gains and enhance recovery; however, an evidence base is lacking. Objective: To assess the efficacy of the online Navigating my Journey (NmJ) program. Methods: 129 adolescent-aged…
Descriptors: Randomized Controlled Trials, Recidivism, Prevention, Internet
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Ingersoll, Brooke; Wainer, Allison L.; Berger, Natalie I.; Pickard, Katherine E.; Bonter, Nicole – Journal of Autism and Developmental Disorders, 2016
This pilot RCT compared the effect of a self-directed and therapist-assisted telehealth-based parent-mediated intervention for young children with ASD. Families were randomly assigned to a self-directed or therapist-assisted program. Parents in both groups improved their intervention fidelity, self-efficacy, stress, and positive perceptions of…
Descriptors: Comparative Analysis, Autism, Pervasive Developmental Disorders, Parent Child Relationship
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Pfiffner, L. J.; Rooney, M.; Haack, L.; Villodas, M.; Delucchi, K.; McBurnett, K. – Grantee Submission, 2016
Objectives: This study evaluated the efficacy of a novel psychosocial intervention (Collaborative Life Skills, CLS) for primary-school students with ADHD symptoms. CLS is a 12-week program consisting of integrated school, parent, and student treatments delivered by school-based mental health providers. Using a cluster randomized design, CLS was…
Descriptors: Randomized Controlled Trials, Intervention, Attention Deficit Hyperactivity Disorder, Symptoms (Individual Disorders)
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Schochet, Peter Z. – Society for Research on Educational Effectiveness, 2013
In randomized control trials (RCTs) of educational interventions, there is a growing literature on impact estimation methods to adjust for missing student outcome data using such methods as multiple imputation, the construction of nonresponse weights, casewise deletion, and maximum likelihood methods (see, for example, Allison, 2002; Graham, 2009;…
Descriptors: Control Groups, Experimental Groups, Educational Research, Data Analysis