English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Mobile health is a rapidly developing field in which behavioral treatmentsare delivered to individuals via wearables or smartphones to facilitatehealth-related behavior change. Micro-randomized trials (MRT) are anexperimental design for developing mobile health interventions. In an MRT thetreatments are randomized numerous times for each individual over course of thetrial. Along with assessing treatment effects, behavioral scientists aim tounderstand between-person heterogeneity in the treatment effect. A naturalapproach is the familiar linear mixed model. However, directly applying linearmixed models is problematic because potential moderators of the treatmenteffect are frequently endogenous---that is, may depend on prior treatment. Wediscuss model interpretation and biases that arise in the absence of additionalassumptions when endogenous covariates are included in a linear mixed model. Inparticular, when there are endogenous covariates, the coefficients no longerhave the customary marginal interpretation. However, these coefficients stillhave a conditional-on-the-random-effect interpretation. We provide anadditional assumption that, if true, allows scientists to use standard softwareto fit linear mixed model with endogenous covariates, and person-specificpredictions of effects can be provided. As an illustration, we assess theeffect of activity suggestion in the HeartSteps MRT and analyze thebetween-person treatment effect heterogeneity.

Linear mixed models with endogenous covariates: modeling sequential treatment effects with application to a mobile health study