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Unformatted text preview: Journal of Data Science 5(2007), 23-40 Assessing the E ec f tiveness of Anti-smoking Media Campaigns by R ecall and Rating Scores — A Pattern-Mixture GEE Model Approach Ming J i 1 , Chengjie Xiong 2 , Elizabeth A. Gilpin 3 and Lois Biener 4 1 San Diego State University, 2 Washington University in St. Louis, 3 University of California, San Diego, and 4 University of Massachusetts Abstract : Anti-smoking media campaign is an e f ective tobacco control strategy. How to identify what types of advertising messages are e f ective is important for maximizing the use of limited funding sources for such campaigns. In this paper, we propose a statistical modeling approach for systematically assessing the e f ectiveness of anti-smoking media campaigns based on ad recall rates and rating scores. This research is motivated by the need for evaluating youth responses to the Massachusetts Tobacco Control Program (MTCP) media campaign. Pattern-mixture GEE models are pro- posed to evaluate the impact of viewer and ads characteristics on ad recall rates and rating scores controlling for missing values, confounding and cor- relations in the data. A key di cul ﬃ ty for pattern-mixture modeling is that there were too many distinct missing data patterns which cause convergence problem for modeling fitting based on limited data. A heuristic argument based on collapsing missing data patterns is used to test the missing com- pletely at random (MCAR) assumption in pattern-mixture GEE models. The proposed modeling approach and the recall-rating study design pro- vide a complete system for identifying the most e f ective type of advertising messages. Key words: Anti-smoking advertising, generalized estimating equations, missing completely at random, missing data, pattern-mixture models, rating score, recall rate, tobacco control. 1. Intro duction 1.1 Ant i-smoking media cam paigns Anti-smoking mass media campaign has been shown to significantly reduce the progression to regular smoking among both adults and adolescents, Flynn et. al (1992, 1994, 1995), Hu et. al (1995), Popham et. al (1995), Siegel et. al (1998, 2000) and Worden et. al (1996). However, development and evaluation of anti- smoking media campaign are di ﬃ cult due to multiple reasons, such as insu ﬃ cient 24 Ming Ji et al....
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- Spring '10
- Accounting, Rating Scores, Dr. Ming Ji, data patterns, Media Campaigns