Graham Kalton

Effects of the National Youth Anti-Drug Media Campaign on youths.

OBJECTIVES We examined the cognitive and behavioral effects of the National Youth Anti-Drug Media Campaign on youths aged 12.5 to 18 years and report core evaluation results. METHODS From September 1999 to June 2004, 3 nationally representative cohorts of US youths aged 9 to 18 years were surveyed at home 4 times. Sample size ranged from 8117 in the first to 5126 in the fourth round (65% first-round response rate, with 86%-93% of still eligible youths interviewed subsequently). Main outcomes were self-reported lifetime, past-year, and past-30-day marijuana use and related cognitions. RESULTS Most analyses showed no effects from the campaign. At one round, however, more ad exposure predicted less intention to avoid marijuana use (gamma = -0.07; 95% confidence interval [CI] = -0.13, -0.01) and weaker antidrug social norms (gamma = -0.05; 95% CI = -0.08, -0.02) at the subsequent round. Exposure at round 3 predicted marijuana initiation at round 4 (gamma = 0.11; 95% CI = 0.00, 0.22). CONCLUSIONS Through June 2004, the campaign is unlikely to have had favorable effects on youths and may have had delayed unfavorable effects. The evaluation challenges the usefulness of the campaign.

Design and methods of the Population Assessment of Tobacco and Health (PATH) Study

Background This paper describes the methods and conceptual framework for Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study data collection. The National Institutes of Health, through the National Institute on Drug Abuse, is partnering with the Food and Drug Administrations (FDA) Center for Tobacco Products to conduct the PATH Study under a contract with Westat. Methods The PATH Study is a nationally representative, longitudinal cohort study of 45 971 adults and youth in the USA, aged 12 years and older. Wave 1 was conducted from 12 September 2013 to 15 December 2014 using Audio Computer-Assisted Self-Interviewing to collect information on tobacco-use patterns, risk perceptions and attitudes towards current and newly emerging tobacco products, tobacco initiation, cessation, relapse behaviours and health outcomes. The PATH Studys design allows for the longitudinal assessment of patterns of use of a spectrum of tobacco products, including initiation, cessation, relapse and transitions between products, as well as factors associated with use patterns. Additionally, the PATH Study collects biospecimens from consenting adults aged 18 years and older and measures biomarkers of exposure and potential harm related to tobacco use. Conclusions The cumulative, population-based data generated over time by the PATH Study will contribute to the evidence base to inform FDAs regulatory mission under the Family Smoking Prevention and Tobacco Control Act and efforts to reduce the Nations burden of tobacco-related death and disease.

Experiments in Wording Opinion Questions

It is well known that responses to an opinion question can be influenced by the precise format and wording of the question. This paper reviews published research in two broad areas of question design: the effects of offering different response options, and the effects of response order and the context of the question. Results from a recent experiment provide further examples of question wording effects on both the marginal distributions of responses and the pattern of associations between questionnaire items.

Panel surveys: Adding the fourth dimension

Abstract Surveys across time can serve many objectives. The first half of the paper reviews the abilities of alternative survey designs across time—repeated surveys, panel surveys, rotating panel surveys and split panel surveys—to meet these objectives. The second half concentrates on panel surveys. It discusses the decisions that need to be made in designing a panel survey, the problems of wave non‐response, time‐in‐sample bias and the seam effect and some methods for the longitudinal analysis of panel survey data.

Models in the Practice of Survey Sampling

Summary A distinction is made between the uses of models in sample design and in survey analysis. Sampling practitioners regularly employ models to guide their choice of sample design, but seldom place complete reliance in a model (which would eliminate the need for probability sampling). With the large samples typical of most surveys, they are reluctant to use model-based estimators of descriptive parameters because of the bias resulting from any misspecifications of the model. With small samples, however, they may prefer a model-based estimator, accepting its unknown bias where its variance is much smaller than the design-based estimator; synthetic estimation for small areas illustrates this point. Models are essential for handling nonresponse and with the technique of statistical matching. The use of models for predicting sampling errors is noted. Causal analysis of survey data necessarily involves models; even so, in some circumstances design-based analysis may provide greater protection against model misspecifications than model-based analysis.

Handling Item Nonresponse in the U.S. Component of the IEA Reading Literacy Study

The U.S. component of the International Reading Literacy Study provides a data set where nonresponses to the background questionnaire items were filled in using imputation methods (mainly hot-deck). This study uses the completed data set for analyses and compares the results with those from other methods of handling missing data. Analyses conducted include regression and hierarchical linear models. The imputed data set yields results similar to those produced by available case analyses (pairwise deletion) and by the estimation and maximization algorithm analyses. The results, however, are different from those produced by complete case analyses (casewise deletion). For most analyses of the Reading Literacy Study, the data set completed by imputation is a convenient option.

Basic Ideas of Scientific Sampling (2nd Edition)

Basic Ideas of Scientific Sampling (2nd edition). By Alan Stuart. London, Griffin, 1976. 106 p. 21·5 cm. £2·20. (Griffins Statistical Monographs and Courses No. 4.)

The Development of an Algorithm to Identify Potential Social Security Disability Beneficiaries

The Social Security Administration funded the development of a screener that could accurately classify household members into one of four disability groups (likely disabled, possibly disabled, not disabled, or current social security disability beneficiaries) for purposes of a larger national study. The authors developed a questionnaire, tested five screener algorithms on data from a pilot study, and assessed the performance of each screener in identifying individuals who are likely disabled, possibly disabled, and not disabled. An algorithm using the item response theory methodology of Rasch modeling offered the greatest improvement over the original screener algorithm and appeared to be quite superior to the other alternatives.