Optimal Data Collection for Randomized Control Trials

In a randomized control trial, the precision of an average treatment effect estimator can be improved either by collecting data on additional individuals, or by collecting additional covariates that predict the outcome variable. We propose the use of pre-experimental data such as a census, or a household survey, to inform the choice of both the sample size and the covariates to be collected. Our procedure seeks to minimize the resulting average treatment effect estimator's mean squared error, subject to the researcher's budget constraint. We rely on a modification of an orthogonal greedy algorithm that is conceptually simple and easy to implement in the presence of a large number of potential covariates, and does not require any tuning parameters. In two empirical applications, we show that our procedure can lead to substantial gains of up to 58%, measured either in terms of reductions in data collection costs or in terms of improvements in the precision of the treatment effect estimator.Comment: 54 pages, 1 figur

A simulation program for the timing of fungicides to control Sooty Blotch in organic apple growing. First results in 2003

A simulation program for infections by Sooty Blotch was developed based on literature data and expert judgements. The value of the model as tool for timing fungicide sprays to control Sooty Blotch was tested in 2003 in two randomized plot trials, and four “on farm” trials where the treatments where made by the growers. Disease pressure was relative low due to the warm and dry summer of 2003. Two to five post infection treatments with lime sulfur or coconut soap aimed at severe infection periods as indicated by the model provides 72 to 100 % control

Standard operating procedures (SOP) in experimental stroke research: SOP for middle cerebral artery occlusion in the mouse

Recently, systematic reviews have found quantitative evidence that low study quality may have introduced a bias into preclinical stroke research. Monitoring, auditing, and standard operating procedures (SOPs) are already key elements of quality control in randomized clinical trials and will hopefully be widely adopted by preclinical stroke research in the near future. Increasingly, funding bodies and review boards overseeing animal experiments are taking a proactive stance, and demand auditable quality control measures in preclinical research. Every good quality control system is based on its SOPs. This article introduces the concept of quality control and presents for the first time an SOP in experimental stroke research

Cairo Evaluation Clinic: Thoughts on Randomized Trials for Evaluation of Development

We were asked to discuss specific methodological approaches to evaluating three hypothetical interventions. This article uses this forum to discuss three misperceptions about randomized trials. First, nobody argues that randomized trials are appropriate in all settings, and for all questions. Everyone agrees that asking the right question is the highest priority. Second, the decision about what to measure and how to measure it, i.e., through qualitative or participatory methods versus quantitative survey or administrative data methods, is independent of the decision about whether to conduct a randomized trial. Third, randomized trials can be used to evaluate complex and dynamic processes, not just simple and static interventions. Evaluators should aim to answer the most important questions for future decisions, and to do so as reliably as possible. Reliability is improved with randomized trials, when feasible, and with attention to underlying theory and tests of why interventions work or fail so that lessons can be transferred as best as possible to other settings.program evaluation, randomized control trial

Is it all about Money? A Randomized Evaluations of the Impact of Insurance Literacy and Marketing Treatments on the Demand for Health Microinsurance in Senegal

In Senegal mutual health organizations (MHOs) have been present in the greater region of Thiès for years. Despite their benefits, in some areas there remain low take-up rates. We offer an insurance literacy module, communicating the benefits from health microinsurance and the functioning of MHOs, to a randomly selected sample of households in the city of Thiès. The effects of this training, and three cross-cutting marketing treatments, are evaluated using a randomized control trial. We find that the insurance literacy module has no impact, but that our marketing treatment has a significant effect on the take up decisions of households.community based health insurance scheme; Randomized control trials; Africa; Senegal

Is it all about Money? A Randomized Evaluation of the Impact of Insurance Literacy and Marketing Treatments on the Demand for Health Microinsurance in Senegal

In Senegal mutual health organizations (MHOs) have been present in the greater region of Thiès for years. Despite their benefits, in some areas there remain low take-up rates. We offer an insurance literacy module, communicating the benefits from health microinsurance and the functioning of MHOs, to a randomly selected sample of households in the city of Thiès. The effects of this training, and three cross-cutting marketing treatments, are evaluated using a randomized control trial. We find that the insurance literacy module has no impact, but that our marketing treatment has a significant effect on the take up decisions of households.Community based health insurance scheme, Randomized control trials, Africa, Senegal

The role of adjuvant chemotherapy for patients with resected pancreatic cancer: Systematic review of randomized controlled trials and meta-analysis

Background: In patients undergoing surgery for resectable pancreatic cancer prognosis still remains poor. The role of adjuvant treatment strategies (including chemotherapy and chemoradiotherapy) following resection of pancreatic cancer remains controversial. Methods: A Medline-based literature search was undertaken to identify randomized controlled trials that evaluated adjuvant chemotherapy after complete macroscopic resection for cancer of the exocrine pancreas. Five trials of adjuvant chemotherapy were eligible and critically reviewed for this article. A meta-analysis (based on published data) was performed with survival (median survival time and 5-year survival rate) being the primary endpoint. Results: For the meta-analysis, 482 patients were allocated to the chemotherapy group and 469 patients to the control group. The meta-analysis estimate for prolongation of median survival time for patients in the chemotherapy group was 3 months (95% CI 0.3-5.7 months, p = 0.03). The difference in 5-year survival rate was estimated with 3.1% between the chemotherapy and the control group (95% CI -4.6 to 10.8%, p > 10.05). Conclusion: Currently available data from randomized trials indicate that adjuvant chemotherapy after resection of pancreatic cancer may substantially prolong disease-free survival and cause a moderate increase in overall survival. In the current meta-analysis, a significant survival benefit was only seen with regard to median survival, but not for the 5-year survival rate. The optimal chemotherapy regimen in the adjuvant setting as well as individualized treatment strategies (also including modern chemoradiotherapy regimens) still remain to be defined. Copyright (C) 2008 S. Karger AG, Basel

Optimal Tests of Treatment Effects for the Overall Population and Two Subpopulations in Randomized Trials, using Sparse Linear Programming

We propose new, optimal methods for analyzing randomized trials, when it is suspected that treatment effects may differ in two predefined subpopulations. Such sub-populations could be defined by a biomarker or risk factor measured at baseline. The goal is to simultaneously learn which subpopulations benefit from an experimental treatment, while providing strong control of the familywise Type I error rate. We formalize this as a multiple testing problem and show it is computationally infeasible to solve using existing techniques. Our solution involves a novel approach, in which we first transform the original multiple testing problem into a large, sparse linear program. We then solve this problem using advanced optimization techniques. This general method can solve a variety of multiple testing problems and decision theory problems related to optimal trial design, for which no solution was previously available. In particular, we construct new multiple testing procedures that satisfy minimax and Bayes optimality criteria. For a given optimality criterion, our new approach yields the optimal tradeoff? between power to detect an effect in the overall population versus power to detect effects in subpopulations. We demonstrate our approach in examples motivated by two randomized trials of new treatments for HIV