Advancing statistical analysis of ambulatory assessment data in the study of addictive behavior: A primer on three person-oriented techniques.

Abstract:

:Ambulatory assessment (AA) methodologies have the potential to increase understanding and treatment of addictive behavior in seemingly unprecedented ways, due in part, to their emphasis on intensive repeated assessments of an individual's addictive behavior in context. But, many analytic techniques traditionally applied to AA data - techniques that average across people and time - do not fully leverage this potential. In an effort to take advantage of the individualized, temporal nature of AA data on addictive behavior, the current paper considers three underutilized person-oriented analytic techniques: multilevel modeling, p-technique, and group iterative multiple model estimation. After reviewing prevailing analytic techniques, each person-oriented technique is presented, AA data specifications are mentioned, an example analysis using generated data is provided, and advantages and limitations are discussed; the paper closes with a brief comparison across techniques. Increasing use of person-oriented techniques will substantially enhance inferences that can be drawn from AA data on addictive behavior and has implications for the development of individualized interventions.

journal_name

Addict Behav

journal_title

Addictive behaviors

authors

Foster KT,Beltz AM

doi

10.1016/j.addbeh.2017.12.018

subject

Has Abstract

pub_date

2018-08-01 00:00:00

pages

25-34

eissn

0306-4603

issn

1873-6327

pii

S0306-4603(17)30473-2

journal_volume

83

pub_type

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