ObjectiveTo compare estimates of effect and variability resulting from standard linear regression analysis and hierarchical multilevel analysis with cross-classified multilevel analysis under various scenarios.Study design and settingWe performed a simulation study based on a data structure from an observational study in clinical mental health care. We used a Markov chain Monte Carlo approach to simulate 18 scenarios, varying sample sizes, cluster sizes, effect sizes and between group variances. For each scenario, we performed standard linear regression, multilevel regression with random intercept on patient level, multilevel regression with random intercept on nursing team level and cross-classified multilevel analysis.ResultsApplying cross-classified multilevel analyses had negligible influence on the effect estimates. However, ignoring cross-classification led to underestimation of the standard errors of the covariates at the two cross-classified levels and to invalidly narrow confidence intervals. This may lead to incorrect statistical inference. Varying sample size, cluster size, effect size and variance had no meaningful influence on these findings.ConclusionIn case of cross-classified data structures, the use of a cross-classified multilevel model helps estimating valid precision of effects, and thereby, support correct inferences.
MULTIFILE
Today, consumers expect companies to be socially responsible. However, the literature is undecided about the effects of communicating one's corporate social responsibility activities to consumers. This raises the question of how sustainability-driven companies can best advertise their products to stimulate ethical consumption: using self-benefit frames, where the main beneficiary is the consumer, or using other-benefit frames, where the main beneficiary is a third party. Using three experiments, this study examines the effect of other-benefit (vs. self-benefit) advertising frames on consumers' impulse purchases from sustainability-driven companies. Increasing impulse purchases can help such companies to strengthen their competitive positions. Additionally, it is studied to what extent two types of justification (moral versus deservingness) explain the proposed effect of advertising frames. The results show that only other-benefit frames affect impulse buying behavior, both directly, as mediated by moral justification. This study's insights may help sustainability-driven companies to decide on their advertising strategies by providing evidence that other-benefit-framed advertisements are more effective in enhancing impulse purchases than self-benefit-framed advertisements.
