(2) Secondary outcome and sensitivity analyses
REGRESSION, SECONDARY
We will use GLMRM with logit or log links for binary or count outcomes, respectively, to evaluate group differences in the outcome changes from baseline to 3- and 12-month follow-up. The models will include predictors of dummy variables for time and group assignment as well as for group by time interaction as described above. Aim 1 (smoking behavior) secondary outcomes are whether smokers have successfully quit (binary), the mean number of quitting attempts (continuous). Aim 2 (exposure to secondhand smoke) secondary outcomes include ever observing someone smoking indoors within the building in the past 7 days (both smoker and non-smoker participants) (binary), hours of secondhand smoke exposure in the building in the past 7 days (count), number of people smoking, and number of cigarette butts in common areas of the building (count).With regard to differential effect of the tobacco retail environment, the impact of differential tobacco retail environments (e.g., retailer density) around each building will be systematically evaluated for the primary outcomes and for quantitative secondary outcomes listed in Aims 1 and 2. The tobacco retail environment will be measured at the longitude-latitude point coordinate of each building using a geographic kernel density estimate with standard bandwidth to estimate the square mileage density of tobacco sellers in the surrounding area for each specific building point coordinate. This information is publicly available from the City of New York. As continuous metrics, these kernel density estimates will be separated in tertiles and at median breaks and the relationships tested in Aims 1 and 2 will then be tested within separate levels of tobacco retail density. We will also extend the GLMRM with identity or log link for each outcome variable in Aims 1 and 2 by adding the factor for retail environment, its interaction with group, time, and group by time interaction. In addition to the analysis for effect of a pre-specified modifier (the retail environment), we will conduct several a priori subgroup analyses to explore potential differential effect of the interventions in the continuous outcomes by age, sex, knowledge, and attitude towards the policy.We will evaluate reliability of self-reported measures of active and passive smoking and revisit the primary analyses adjusting for potential imperfect reliability using regression calibration approaches.