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1.
    
Recently, there has been a growing interest in designing cluster trials using stepped wedge design (SWD). An SWD is a type of cluster–crossover design in which clusters of individuals are randomized unidirectional from a control to an intervention at certain time points. The intraclass correlation coefficient (ICC) that measures the dependency of subject within a cluster plays an important role in design and analysis of stepped wedge trials. In this paper, we discuss a Bayesian approach to address the dependency of SWD on the ICC and robust Bayesian SWDs are proposed. Bayesian design is shown to be more robust against the misspecification of the parameter values compared to the locally optimal design. Designs are obtained for the various choices of priors assigned to the ICC. A detailed sensitivity analysis is performed to assess the robustness of proposed optimal designs. The power superiority of Bayesian design against the commonly used balanced design is demonstrated numerically using hypothetical as well as real scenarios.  相似文献   

2.
    
Standard sample size calculation formulas for stepped wedge cluster randomized trials (SW-CRTs) assume that cluster sizes are equal. When cluster sizes vary substantially, ignoring this variation may lead to an under-powered study. We investigate the relative efficiency of a SW-CRT with varying cluster sizes to equal cluster sizes, and derive variance estimators for the intervention effect that account for this variation under a mixed effects model—a commonly used approach for analyzing data from cluster randomized trials. When cluster sizes vary, the power of a SW-CRT depends on the order in which clusters receive the intervention, which is determined through randomization. We first derive a variance formula that corresponds to any particular realization of the randomized sequence and propose efficient algorithms to identify upper and lower bounds of the power. We then obtain an “expected” power based on a first-order approximation to the variance formula, where the expectation is taken with respect to all possible randomization sequences. Finally, we provide a variance formula for more general settings where only the cluster size arithmetic mean and coefficient of variation, instead of exact cluster sizes, are known in the design stage. We evaluate our methods through simulations and illustrate that the average power of a SW-CRT decreases as the variation in cluster sizes increases, and the impact is largest when the number of clusters is small.  相似文献   

3.
    
Stepped wedge cluster randomized trials (SWCRT) are increasingly used for the evaluation of complex interventions in health services research. They randomly allocate treatments to clusters that switch to intervention under investigation at variable time points without returning to control condition. The resulting unbalanced allocation over time periods and the uncertainty about the underlying correlation structures at cluster-level renders designing and analyzing SWCRTs a challenge. Adjusting for time trends is recommended, appropriate parameterizations depend on the particular context. For sample size calculation, the covariance structure and covariance parameters are usually assumed to be known. These assumptions greatly affect the influence single cluster-period cells have on the effect estimate. Thus, it is important to understand how cluster-period cells contribute to the treatment effect estimate. We therefore discuss two measures of cell influence. These are functions of the design characteristics and covariance structure only and can thus be calculated at the planning stage: the coefficient matrix as discussed by Matthews and Forbes and information content (IC) as introduced by Kasza and Forbes. The main result is a new formula for IC that is more general and computationally more efficient. The formula applies to any generalized least squares estimator, especially for any type of time trend adjustment or nonblock diagonal matrices. We further show a functional relationship between IC and the coefficient matrix. We give two examples that tie in with current literature. All discussed tools and methods are implemented in the R package SteppedPower .  相似文献   

4.
    
The ability to accurately estimate the sample size required by a stepped‐wedge (SW) cluster randomized trial (CRT) routinely depends upon the specification of several nuisance parameters. If these parameters are misspecified, the trial could be overpowered, leading to increased cost, or underpowered, enhancing the likelihood of a false negative. We address this issue here for cross‐sectional SW‐CRTs, analyzed with a particular linear‐mixed model, by proposing methods for blinded and unblinded sample size reestimation (SSRE). First, blinded estimators for the variance parameters of a SW‐CRT analyzed using the Hussey and Hughes model are derived. Following this, procedures for blinded and unblinded SSRE after any time period in a SW‐CRT are detailed. The performance of these procedures is then examined and contrasted using two example trial design scenarios. We find that if the two key variance parameters were underspecified by 50%, the SSRE procedures were able to increase power over the conventional SW‐CRT design by up to 41%, resulting in an empirical power above the desired level. Thus, though there are practical issues to consider, the performance of the procedures means researchers should consider incorporating SSRE in to future SW‐CRTs.  相似文献   

5.
    
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6.
    
Stepped wedge designed trials are a type of cluster-randomized study in which the intervention is introduced to each cluster in a random order over time. This design is often used to assess the effect of a new intervention as it is rolled out across a series of clinics or communities. Based on a permutation argument, we derive a closed-form expression for an estimate of the intervention effect, along with its standard error, for a stepped wedge design trial. We show that these estimates are robust to misspecification of both the mean and covariance structure of the underlying data-generating mechanism, thereby providing a robust approach to inference for the intervention effect in stepped wedge designs. We use simulations to evaluate the type 1 error and power of the proposed estimate and to compare the performance of the proposed estimate to the optimal estimate when the correct model specification is known. The limitations, possible extensions, and open problems regarding the method are discussed.  相似文献   

7.
    
In the management of most chronic conditions characterized by the lack of universally effective treatments, adaptive treatment strategies (ATSs) have grown in popularity as they offer a more individualized approach. As a result, sequential multiple assignment randomized trials (SMARTs) have gained attention as the most suitable clinical trial design to formalize the study of these strategies. While the number of SMARTs has increased in recent years, sample size and design considerations have generally been carried out in frequentist settings. However, standard frequentist formulae require assumptions on interim response rates and variance components. Misspecifying these can lead to incorrect sample size calculations and correspondingly inadequate levels of power. The Bayesian framework offers a straightforward path to alleviate some of these concerns. In this paper, we provide calculations in a Bayesian setting to allow more realistic and robust estimates that account for uncertainty in inputs through the ‘two priors’ approach. Additionally, compared to the standard frequentist formulae, this methodology allows us to rely on fewer assumptions, integrate pre-trial knowledge, and switch the focus from the standardized effect size to the MDD. The proposed methodology is evaluated in a thorough simulation study and is implemented to estimate the sample size for a full-scale SMART of an internet-based adaptive stress management intervention on cardiovascular disease patients using data from its pilot study conducted in two Canadian provinces.  相似文献   

8.
    
In an individually randomized group treatment (IRGT) trial, participant outcomes can be positively correlated due to, for example, shared therapists in treatment delivery. Oftentimes, because of limited treatment resources or participants at one location, an IRGT trial can be carried out across multiple centers. This design can be subject to potential correlations in the participant outcomes between arms within the same center. While the design of a single-center IRGT trial has been studied, little is known about the planning of a multicenter IRGT trial. To address this gap, this paper provides analytical sample size formulas for designing multicenter IRGT trials with a continuous endpoint under the linear mixed model framework. We found that accounting for the additional center-level correlation at the design stage can lead to sample size reduction, and the magnitude of reduction depends on the amount of between-therapist correlation. However, if the variance components of therapist-level random effects are considered as input parameters in the design stage, accounting for the additional center-level variance component has no impact on the sample size estimation. We presented our findings through numeric illustrations and performed simulation studies to validate our sample size procedures under different scenarios. Optimal design configurations under the multicenter IRGT trials have also been discussed, and two real-world trial examples are drawn to illustrate the use of our method.  相似文献   

9.
    
There is growing interest in conducting cluster randomized trials (CRTs). For simplicity in sample size calculation, the cluster sizes are assumed to be identical across all clusters. However, equal cluster sizes are not guaranteed in practice. Therefore, the relative efficiency (RE) of unequal versus equal cluster sizes has been investigated when testing the treatment effect. One of the most important approaches to analyze a set of correlated data is the generalized estimating equation (GEE) proposed by Liang and Zeger, in which the “working correlation structure” is introduced and the association pattern depends on a vector of association parameters denoted by ρ. In this paper, we utilize GEE models to test the treatment effect in a two‐group comparison for continuous, binary, or count data in CRTs. The variances of the estimator of the treatment effect are derived for the different types of outcome. RE is defined as the ratio of variance of the estimator of the treatment effect for equal to unequal cluster sizes. We discuss a commonly used structure in CRTs—exchangeable, and derive the simpler formula of RE with continuous, binary, and count outcomes. Finally, REs are investigated for several scenarios of cluster size distributions through simulation studies. We propose an adjusted sample size due to efficiency loss. Additionally, we also propose an optimal sample size estimation based on the GEE models under a fixed budget for known and unknown association parameter (ρ) in the working correlation structure within the cluster.  相似文献   

10.
We propose drug screening designs based on a Bayesian decision-theoretic approach. The discussion is motivated by screening designs for phase II studies. The proposed screening designs allow consideration of multiple treatments simultaneously. In each period, new treatments can arise and currently considered treatments can be dropped. Once a treatment is removed from the phase II screening trial, a terminal decision is made about abandoning the treatment or recommending it for a future confirmatory phase III study. The decision about dropping treatments from the active set is a sequential stopping decision. We propose a solution based on decision boundaries in the space of marginal posterior moments for the unknown parameter of interest that relates to each treatment. We present a Monte Carlo simulation algorithm to implement the proposed approach. We provide an implementation of the proposed method as an easy to use R library available for public domain download (http://www.stat.rice.edu/~rusi/ or http://odin.mdacc.tmc.edu/~pm/).  相似文献   

11.
    
The stepped wedge cluster randomized trial (SW-CRT) is an increasingly popular design for evaluating health service delivery or policy interventions. An essential consideration of this design is the need to account for both within-period and between-period correlations in sample size calculations. Especially when embedded in health care delivery systems, many SW-CRTs may have subclusters nested in clusters, within which outcomes are collected longitudinally. However, existing sample size methods that account for between-period correlations have not allowed for multiple levels of clustering. We present computationally efficient sample size procedures that properly differentiate within-period and between-period intracluster correlation coefficients in SW-CRTs in the presence of subclusters. We introduce an extended block exchangeable correlation matrix to characterize the complex dependencies of outcomes within clusters. For Gaussian outcomes, we derive a closed-form sample size expression that depends on the correlation structure only through two eigenvalues of the extended block exchangeable correlation structure. For non-Gaussian outcomes, we present a generic sample size algorithm based on linearization and elucidate simplifications under canonical link functions. For example, we show that the approximate sample size formula under a logistic linear mixed model depends on three eigenvalues of the extended block exchangeable correlation matrix. We provide an extension to accommodate unequal cluster sizes and validate the proposed methods via simulations. Finally, we illustrate our methods in two real SW-CRTs with subclusters.  相似文献   

12.
《Anthrozo?s》2013,26(4):379-385
Abstract

This study was designed to assess the impact of an ongoing pet visitation program on the behavior and emotional state of adjudicated female adolescents at a medium secure residential facility over an eight-week period. To our knowledge, this study is the first randomized trial with a pretest-posttest design aimed at determining whether unstructured animal-assisted activities (AAA) have a positive impact on this unique population of adolescents. Using a random number table, 23 residents were randomly assigned to participate either in the pet visitation program (n = 13) or the facility's usual activities (n = 10). The program entailed weekly one-hour sessions during which participants were involved in activities such as grooming the animals, giving commands, playing fetch, and talking to the animals' handlers. To assess the program's effects on participants' behavior and emotional state, two quantitative instruments, the Youth Self-Report for Ages 11–18 (YSR) and the Resident Behavior Assessment (RBA), and a qualitative survey (designed by the researchers) were administered to the participants both prior to the pet visitation program and following its completion.

Results from the two quantitative measures suggested that the pet visitation program did not have a significant effect on the behavior or emotional state of the pet visitation participants. Qualitative results indicated that most of the participants enjoyed some aspect of the pet visitation program. In light of the small sample size and the unanticipated difficulties encountered in the conduct of the study, this research should be considered a pilot study. The limitations inherent to studying the effects of AAA programs in adjudicated adolescents are discussed.  相似文献   

13.
    
Summary Cluster randomization trials with relatively few clusters have been widely used in recent years for evaluation of health‐care strategies. On average, randomized treatment assignment achieves balance in both known and unknown confounding factors between treatment groups, however, in practice investigators can only introduce a small amount of stratification and cannot balance on all the important variables simultaneously. The limitation arises especially when there are many confounding variables in small studies. Such is the case in the INSTINCT trial designed to investigate the effectiveness of an education program in enhancing the tPA use in stroke patients. In this article, we introduce a new randomization design, the balance match weighted (BMW) design, which applies the optimal matching with constraints technique to a prospective randomized design and aims to minimize the mean squared error (MSE) of the treatment effect estimator. A simulation study shows that, under various confounding scenarios, the BMW design can yield substantial reductions in the MSE for the treatment effect estimator compared to a completely randomized or matched‐pair design. The BMW design is also compared with a model‐based approach adjusting for the estimated propensity score and Robins‐Mark‐Newey E‐estimation procedure in terms of efficiency and robustness of the treatment effect estimator. These investigations suggest that the BMW design is more robust and usually, although not always, more efficient than either of the approaches. The design is also seen to be robust against heterogeneous error. We illustrate these methods in proposing a design for the INSTINCT trial.  相似文献   

14.
    
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15.
    
Calorie restriction (CR) without malnutrition slows aging in animal models. Oxidative stress reduction was proposed to mediate CR effects. CR effect on urinary F2‐isoprostanes, validated oxidative stress markers, was assessed in CALERIE, a two‐year randomized controlled trial. Healthy volunteers (n = 218) were randomized to prescribed 25% CR (n = 143) or ad libitum control (AL, n = 75) stratifying the randomization schedule by site, sex, and BMI. F2‐isoprostanes were quantified using LC‐MS/MS in morning, fasted urine specimens at baseline, at 12 and 24 months. The primary measure of oxidative status was creatinine‐adjusted 2,3‐dinor‐iPF(2α)‐III concentration, additional measured included iPF(2α)‐III, iPF2a‐VI, and 8,12‐iso‐iPF2a‐VI. Intention‐to‐treat analyses assessed change in 2,3‐dinor‐iPF(2α)‐III using mixed models assessing treatment, time, and treatment‐by‐time interaction effects, adjusted for blocking variables and baseline F2‐isoprostane value. Exploratory analyses examined changes in iPF(2α)‐III, iPF(2α)‐VI, and 8,12‐iso‐iPF(2α)‐VI. A factor analysis used aggregate information on F2‐isoprostane values. In CR group, 2,3‐dinor‐iPF(2α)‐III concentrations were reduced from baseline by 17% and 13% at 12 and 24 months, respectively; these changes were significantly different from AL group (p < .01). CR reduced iPF(2α)‐III concentrations by 20% and 27% at 12 and 24 months, respectively (p < .05). The effects were weaker on the VI‐species. CR caused statistically significant reduction in isoprostane factor at both time points, and mean (se) changes were ?0.36 (0.06) and ?0.31 (0.06). No significant changes in isoprostane factor were at either time point in AL group (p < .01 between‐group difference). We conclude that two‐year CR intervention in healthy, nonobese men and women reduced whole body oxidative stress as assessed by urinary concentrations of F2‐isoprostanes.  相似文献   

16.
    
The current understanding of the placebo response in vitiligo is limited. Nonetheless, it is difficult to compare the outcomes of vitiligo trials if the repigmentation rates in placebo patients vary significantly. We conducted a meta-analysis of the placebo response in vitiligo trials. Overall, repigmentation rates in patients receiving placebo were 22%, ranging substantially from 0 to 60%. Repigmentation (>25%) was still relatively common for placebo (9.35%), but fell to 5% when >50% improvement was analyzed. Higher frequencies of placebo responses correlated with more repigmentation in the intervention groups. Facial vitiligo and sunlight exposure was linked to higher placebo responses. Roughly estimating the amount of improvement using quartiles (0–25, 25%–50%, 50%–75%, 75%–100% repigmentation) resulted in higher placebo rates compared to other assessment methods. In clinical studies with older patients, the ratio of placebo reactions to treatment responses was higher. This is likely because clinical trials with older patients reported less repigmentation after treatment than studies with younger patients. The percentual difference in affected body surface area during the study period ranged from 6.2% worsening to 17.6% improvement in the placebo groups. This high variability in placebo responses illustrates the need for standardized outcome measures and more head-to-head trials in vitiligo.  相似文献   

17.
    
Caloric restriction (CR) modifies lifespan and aging biology in animal models. The Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy (CALERIE™) 2 trial tested translation of these findings to humans. CALERIE™ randomized healthy, nonobese men and premenopausal women (age 21–50y; BMI 22.0–27.9 kg/m2), to 25% CR or ad-libitum (AL) control (2:1) for 2 years. Prior analyses of CALERIE™ participants' blood chemistries, immunology, and epigenetic data suggest the 2-year CR intervention slowed biological aging. Here, we extend these analyses to test effects of CR on telomere length (TL) attrition. TL was quantified in blood samples collected at baseline, 12-, and 24-months by quantitative PCR (absolute TL; aTL) and a published DNA-methylation algorithm (DNAmTL). Intent-to-treat analysis found no significant differences in TL attrition across the first year, although there were trends toward increased attrition in the CR group for both aTL and DNAmTL measurements. When accounting for adherence heterogeneity with an Effect-of-Treatment-on-the-Treated analysis, greater CR dose was associated with increased DNAmTL attrition during the baseline to 12-month weight-loss period. By contrast, both CR group status and increased CR were associated with reduced aTL attrition over the month 12 to month 24 weight maintenance period. No differences were observed when considering TL change across the study duration from baseline to 24-months, leaving it unclear whether CR-related effects reflect long-term detriments to telomere fidelity, a hormesis-like adaptation to decreased energy availability, or measurement error and insufficient statistical power. Unraveling these trends will be a focus of future CALERIE™ analyses and trials.  相似文献   

18.
目的 通过Meta分析探讨静脉注射伏立康唑和静脉注射氟康唑预防真菌感染的临床疗效和安全性。方法 以伏立康唑为实验组,氟康唑为对照组。通过计算机检索中国期刊全文数据库(CNKI)、万方数据库、维普数据库,并进一步对纳入文献的参考文献进行扩大检索。对符合纳入标准的随机对照研究(RCT)按Cochrane系统评价的方法,独立进行资料提取、质量评价并交叉核对后,采用Stata14.0软件进行Meta分析。结果 共纳入19篇研究,共计1492例患者。伏立康唑有着更高的有效率和有更低的不良反应,两者差异有统计学意义(RR=1.20,95%CI=1.14~1.26,P<0.001)和RR=0.76,95%CI=0.65~0.90,P=0.001)。同时在控制感染发热和真菌清除方面,伏立康唑有着更好的效果,两者差异有统计学意义,分别为(RR=1.63,95%CI=1.40~1.90,P<0.001和RR=1.27,95%CI=1.13~1.44,P<0.001)。结论 Meta分析结果表明伏立康唑比氟康唑预防真菌感染有更好的疗效和预后及更低的不良反应。  相似文献   

19.
Community genetics hypothesizes that within a foundation species, the genotype of an individual significantly influences the assemblage of dependent organisms. To assess whether these intra-specific genetic effects are ecologically important, it is required to compare their impact on dependent organisms with that attributable to environmental variation experienced over relevant spatial scales. We assessed bark epiphytes on 27 aspen (Populus tremula L.) genotypes grown in a randomized experimental array at two contrasting sites spanning the environmental conditions from which the aspen genotypes were collected. We found that variation in aspen genotype significantly influenced bark epiphyte community composition, and to the same degree as environmental variation between the test sites. We conclude that maintaining genotypic diversity of foundation species may be crucial for conservation of associated biodiversity.  相似文献   

20.
    
Cluster randomized studies are common in community trials. The standard method for estimating sample size for cluster randomized studies assumes a common cluster size. However often in cluster randomized studies, size of the clusters vary. In this paper, we derive sample size estimation for continuous outcomes for cluster randomized studies while accounting for the variability due to cluster size. It is shown that the proposed formula for estimating total cluster size can be obtained by adding a correction term to the traditional formula which uses the average cluster size. Application of these results to the design of a health promotion educational intervention study is discussed.  相似文献   

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