I n this study we examine a moderated model of group faultlines, team identification, and group performance outcomes. We extend research on faultlines by showing how different faultline bases (social category and information-based faultlines) may have differential effects on the performance of groups. In addition to faultline strength (the extent of demographic alignment across members within a group), we examine the distance between faultline-based subgroups (e.g., two members of age 20 are closer in age to two members of an opposing subgroup of age 25 than of two members of age 50). We test our model using an archival field methodology and multiple-source data (qualitative and quantitative) from 76 workgroups in a Fortune 500 information-processing company. Our results revealed that groups with social category faultlines had low team discretionary awards. Faultline distance further exacerbated the negative effects of strength in groups with social category faultlines and produced similarly negative effects in groups with information-based faultlines. Team identification served as a moderator enhancing performance of groups with information-based faultlines.

Multivariate matching with doses of treatment differs from the treatment-control matching in three ways. First, pairs must not only balance covariates, but also must differ markedly in dose. Second, any two subjects may be paired, so that the matching is nonbipartite, and different algorithms are required. Finally, a propensity score with doses must be used in place of the conventional propensity score. We illustrate multivariate matching with doses using pilot data from a media campaign against drug abuse. The media campaign is intended to change attitudes and intentions related to illegal drugs, and the evaluation compares stated intentions among ostensibly comparable teens who reported markedly different exposures to the media campaign. KeywordsCoherent signed rank test, Equal percent bias reducing, Matching with doses, Nonbipartite matching, Observational studies, Ordinal logit model, Optimal matching, Propensity score Disciplines Communication | Statistics and ProbabilityThis journal article is available at ScholarlyCommons: http://repository.upenn.edu/asc_papers/177 Matching With Doses in an Observational Study of a Media Campaign Against Drug AbuseBo Lu, Elaine Zanutto, Robert Hornik, Paul R. RosenbaumMultivariate matching with doses of treatment differs from the treatment-control matching in three ways. First, pairs must not only balance covariates, but also must differ markedly in dose. Second, any two subjects may be paired, so that the matching is nonbipartite, and different algorithms are required. Finally, a propensity score with doses must be used in place of the conventional propensity score. We illustrate multivariate matching with doses using pilot data from a media campaign against drug abuse. The media campaign is intended to change attitudes and intentions related to illegal drugs, and the evaluation compares stated intentions among ostensibly comparable teens who reported markedly different exposures to the media campaign.

In 1998, the U.S. Office of National Drug Control Policy launched a national media campaign in an effort to reduce and prevent drug use among young Americans. Because the campaign was implemented nationwide, there is no control group available for use in evaluating the effects of the campaign. Nevertheless, it is possible to use propensity score methods to evaluate the effects of the campaign. However, because teens receive varying degrees of exposure to the media campaign, it is necessary to apply propensity score methods that accommodate multiple treatment doses. This work extends that of previous authors to subclassification on the propensity score for observational studies with multiple treatment doses, rather than matching on the propensity score, and proposes modifications to accommodate complex survey data. This methodology is illustrated using data from a pilot study for the media campaign evaluation.

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