Statistical analysis
anxiety
SECONDARY, RECRUITMENT
We calculated the sample size using a separate power analysis for each of the three primary outcome categories: diet, physical activity, and anthropometry. The final sample size was chosen as the maximum of the three sample sizes found to provide power of at least 80% for each outcome category. We did not do a formal power analysis for perceived stress and anxiety because they were secondary outcomes.We did all analyses under the intention-to-treat principle (ie, included all participants randomly assigned to groups), and analysed them as randomised. Because the COVID-19 pandemic affected data collection and might have had an effect on health behaviours, the study team agreed to exclude wave 3, T3 data from the analysis—ie, data collected after Feb 1, 2020. The decision was made a priori, while assessors and investigators were still masked to group assignments. We tested time-by-intervention hypotheses at an α level of 0·04 and intervention effects at T2 and T3 at an α level of 0·005 (99·5% CI), for a total type 1 error rate of (0·04 + 0·005 + 0·005 =) 0·05 per primary outcome. A significant time-by-intervention interaction indicated that the pattern of means over time for the intervention group differed from that of the control group.Participants with and without missing data were compared overall and stratified by intervention assignment using Rao-Scott χFor dietary outcomes, we used general linear mixed models to assess time-by-intervention interaction. The outcome at each timepoint (T1, T2, and T3) was the mean of the response for the 24-h recalls. We modelled correlations using the Kronecker-product covariance matrix, with an unstructured model for the longitudinal repeated measures, and the best-fitting choice of one of two parameterisations to account for clustering: (1) a model with a waiting list random effect only, and (2) a model with a random term for assignment to gardening, nested within the waiting list. For all mixed models, we used jackknife studentised residuals to test modelling assumptions. We assessed significance using the Wald test and Kenward-Roger degrees of freedom. In preliminary modelling, we assessed wave effects and found no difference in outcome by wave. This indicated that data could be combined across the 3 years of recruitment, as we present in the Results. We did a sensitivity analysis to assess whether there was an interaction between social desirability and randomisation assignment, and then, if there were no interactions, whether the social desirability score was associated with dietary outcomes.For physical activity outcomes, we used a similar approach as for the dietary outcomes, with the exception that the initial set of predictors also included an indicator variable for day type (ie, weekend We did modelling and hypothesis testing similarly for BMI and waist circumference as for the dietary and physical activity outcomes, and additionally adjusted for age and sex.We had several preplanned secondary outcome analyses. We assessed secondary outcomes at an α level of 0·05. We calculated difference scores, T2 minus T1 and T3 minus T1, for the secondary outcomes of perceived stress and anxiety. We fit separate general linear mixed models for the T2 minus T1 and T3 minus T1 difference scores to test if the difference score differed by group assignment. Our models controlled for the baseline value and the interaction between baseline value and randomisation assignment. Under the assumption that participants were exchangeable within waiting lists, a random intercept for each garden waiting list produced a compound symmetric variance structure. We used a two degrees-of-freedom test of equality of both intercepts and slopes to test if there was a difference between intervention and control at the α level of 0·05.We did not have an a priori hypothesis about differences at T3, but we present results for T3 for completeness.We did all calculations using General Linear Mixed Model Power and Sample Size (known as GLIMMPSE) software (version 3.0).