An integrated population‐averaged approach to the design, analysis and sample size determination of cluster‐unit trials

Preisser, John S.; Young, Mary Lynn; Zaccaro, Daniel; Wolfson, Mark

doi:10.1002/sim.1379

Cited by 97 publications

(116 citation statements)

References 39 publications

(46 reference statements)

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“…Epidemiology and the social sciences have a long history of using matched cohort designs to study interventions and exposures that are not randomly assigned (14,15). Recent efforts have used the design in prospective group-level intervention studies (16)(17)(18) and in preexisting intervention studies (19)(20)(21). In a typical scenario, investigators define a study population, and a subset of the population is selected to receive the intervention by a known or unknown process that is not random.…”

Section: Methodsmentioning

confidence: 99%

Causal inference methods to study nonrandomized, preexisting development interventions

Arnold

Khush

Padmavathi

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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Empirical measurement of interventions to address significant global health and development problems is necessary to ensure that resources are applied appropriately. Such intervention programs are often deployed at the group or community level. The gold standard design to measure the effectiveness of communitylevel interventions is the community-randomized trial, but the conditions of these trials often make it difficult to assess their external validity and sustainability. The sheer number of community interventions, relative to randomized studies, speaks to a need for rigorous observational methods to measure their impact. In this article, we use the potential outcomes model for causal inference to motivate a matched cohort design to study the impact and sustainability of nonrandomized, preexisting interventions. We illustrate the method using a sanitation mobilization, water supply, and hygiene intervention in rural India. In a matched sample of 25 villages, we enrolled 1,284 children <5 y old and measured outcomes over 12 mo. Although we found a 33 percentage point difference in new toilet construction [95% confidence interval (CI) = 28%, 39%], we found no impacts on height-for-age Z scores (adjusted difference = 0.01, 95% CI = −0.15, 0.19) or diarrhea (adjusted longitudinal prevalence difference = 0.003, 95% CI = −0.001, 0.008) among children <5 y old. This study demonstrates that matched cohort designs can estimate impacts from nonrandomized, preexisting interventions that are used widely in development efforts. Interpreting the impacts as causal, however, requires stronger assumptions than prospective, randomized studies.impact evaluation | study design | propensity score matching | communityled total sanitation | open defecation

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Section: Methodsmentioning

confidence: 99%

Causal inference methods to study nonrandomized, preexisting development interventions

Arnold

Khush

Padmavathi

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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“…The Web-based College Drinking Survey was adapted from items used previously in the Harvard College Alcohol Survey ( Wechsler, Davenport, Dowdall, Moeykens, & Castillo, 1994 ), the Core Institute Drug and Alcohol Survey ( Presley, Meilman, & Lyerla, 1994 ), the Youth Survey used in the National Evaluation of the Enforcing Underage Drinking Laws Program ( Preisser, Young, Zaccaro, & Wolfson, 2003 ;Wolfson et al, 2004 ), and the Centers for Disease Control and Prevention (CDC) Youth Risk Behavior Survey ( Kolbe, 1990 ). The survey focused on alcohol and measured demographic variables, alcohol consumption behaviors, and consequences experienced from alcohol use.…”

Section: Methodsmentioning

confidence: 99%

Are college student smokers really a homogeneous group? A latent class analysis of college student smokers

Sutfin

Reboussin²,

McCoy³

et al. 2009

Nicotine &Amp; Tobacco Research

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Introduction: College smokers are often considered to be one homogenous group, those reporting smoking on at least one of the past 30 days. However, considerable heterogeneity exists among college students who report current smoking. The aim of this paper is to characterize disparate patterns of smoking among college students using latent class analysis (LCA). Methods:The sample consisted of 1,102 past-month smokers from 10 colleges in North Carolina who completed a Web-based survey. LCA was used to create homogeneous groups of smokers with similar patterns defi ned by multiple indicators of smoking behavior, including quantity and frequency of smoking, smoking contexts, and weekly patterns of smoking.Results: Five subclasses of smokers were identifi ed: " heavy smokers " (28%), moderate smokers (22%), social smokers (19%), puffers (26%), and no-context smokers (4%). Demographic characteristics that varied among these subgroups were year in school, Greek membership, and residence location. Puffers were more likely to be younger students than heavy and social smokers, suggesting a transition from experimentation to regular use over time. Social smokers and puffers were more likely to be involved in Greek organizations than were heavy and moderate smokers. Moderate and social smokers were more likely to be current drinkers and to have engaged in binge drinking in the past month than were heavy smokers. This fi nding suggests that, for moderate and social smokers, a strong relationship exists between alcohol and tobacco use. Discussion:The results highlight the heterogeneity of college student smokers and underscore the need for targeted interventions.

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“…The CDS was developed using items from surveys of alcohol use and other health behaviors among college students and high school -aged youth and middle-school -aged youth ( Kolbe, 1990 ;Preisser, Young, Zaccaro, & Wolfson, 2003 ;Presley, Meilman, & Lyerla, 1994 ;Wechsler, Davenport, Dowdall, Moeykens, & Castillo, 1994 ), as well as new items. Items regarding SHS exposure were adapted from a survey of SHS exposure among a cohort of adults with asthma living in northern California ( Eisner, Katz, Yelin, Hammond, & Blanc, 2001 ).…”

Section: Methodsmentioning

confidence: 99%

College students' exposure to secondhand smoke

Wolfson

McCoy

Sutfin

2009

Nicotine &Amp; Tobacco Research

Self Cite

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An integrated population‐averaged approach to the design, analysis and sample size determination of cluster‐unit trials

Cited by 97 publications

References 39 publications

Causal inference methods to study nonrandomized, preexisting development interventions

Causal inference methods to study nonrandomized, preexisting development interventions

Are college student smokers really a homogeneous group? A latent class analysis of college student smokers

College students' exposure to secondhand smoke

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