Literature DB >> 29542004

Inverse Propensity Score Weighting with a Latent Class Exposure: Estimating the Causal Effect of Reported Reasons for Alcohol Use on Problem Alcohol Use 16 Years Later.

Bethany C Bray1,2, John J Dziak3, Megan E Patrick4, Stephanie T Lanza3,5,6.   

Abstract

Latent class analysis (LCA) has proven to be a useful tool for identifying qualitatively different population subgroups who may be at varying levels of risk for negative outcomes. Recent methodological work has improved techniques for linking latent class membership to distal outcomes; however, these techniques do not adjust for potential confounding variables that may provide alternative explanations for observed relations. Inverse propensity score weighting provides a way to account for many confounders simultaneously, thereby strengthening causal inference of the effects of predictors on outcomes. Although propensity score weighting has been adapted to LCA with covariates, there has been limited work adapting it to LCA with distal outcomes. The current study proposes a step-by-step approach for using inverse propensity score weighting together with the "Bolck, Croon, and Hagenaars" approach to LCA with distal outcomes (i.e., the BCH approach), in order to estimate the causal effects of reasons for alcohol use latent class membership during the year after high school (at age 19) on later problem alcohol use (at age 35) with data from the longitudinal sample in the Monitoring the Future study. A supplementary appendix provides evidence for the accuracy of the proposed approach via a small-scale simulation study, as well as sample programming code to conduct the step-by-step approach.

Entities:  

Keywords:  Alcohol use; Causal inference; Latent class analysis; Motives; Propensity scores; Reasons for drinking

Year:  2019        PMID: 29542004      PMCID: PMC6139077          DOI: 10.1007/s11121-018-0883-8

Source DB:  PubMed          Journal:  Prev Sci        ISSN: 1389-4986


  40 in total

1.  Doubly robust estimation in missing data and causal inference models.

Authors:  Heejung Bang; James M Robins
Journal:  Biometrics       Date:  2005-12       Impact factor: 2.571

2.  Comment: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data.

Authors:  Anastasios A Tsiatis; Marie Davidian
Journal:  Stat Sci       Date:  2007       Impact factor: 2.901

3.  For whom does it work? Subgroup differences in the effects of a school-based universal prevention program.

Authors:  Jantine L Spilt; Johannes M Koot; Pol A C van Lier
Journal:  Prev Sci       Date:  2013-10

4.  Latent class analysis: an alternative perspective on subgroup analysis in prevention and treatment.

Authors:  Stephanie T Lanza; Brittany L Rhoades
Journal:  Prev Sci       Date:  2013-04

5.  Causal Inference in Latent Class Analysis.

Authors:  Stephanie T Lanza; Donna L Coffman; Shu Xu
Journal:  Struct Equ Modeling       Date:  2013-07       Impact factor: 6.125

6.  ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME.

Authors:  Megan S Schuler; Jeannie-Marie S Leoutsakos; Elizabeth A Stuart
Journal:  Health Serv Outcomes Res Methodol       Date:  2014-12

7.  Pre-college matriculation risk profiles and alcohol consumption patterns during the first semesters of college.

Authors:  Jerod L Stapleton; Rob Turrisi; Michael J Cleveland; Anne E Ray; Shou-En Lu
Journal:  Prev Sci       Date:  2014-10

8.  Hurting, helping, or neutral? The effects of parental permissiveness toward adolescent drinking on college student alcohol use and problems.

Authors:  Lindsey Varvil-Weld; D Max Crowley; Rob Turrisi; Mark T Greenberg; Kimberly A Mallett
Journal:  Prev Sci       Date:  2014-10

9.  An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.

Authors:  Peter C Austin
Journal:  Multivariate Behav Res       Date:  2011-06-08       Impact factor: 5.923

10.  Drinking to Cope: a Latent Class Analysis of Coping Motives for Alcohol Use in a Large Cohort of Adolescents.

Authors:  Lexine A Stapinski; Alexis C Edwards; Matthew Hickman; Ricardo Araya; Maree Teesson; Nicola C Newton; Kenneth S Kendler; Jon Heron
Journal:  Prev Sci       Date:  2016-07
View more
  11 in total

1.  Advances in Statistical Methods for Causal Inference in Prevention Science: Introduction to the Special Section.

Authors:  Wolfgang Wiedermann; Nianbo Dong; Alexander von Eye
Journal:  Prev Sci       Date:  2019-04

2.  Alcohol motivations and behaviors during months young adults experience social role transitions: Microtransitions in early adulthood.

Authors:  Megan E Patrick; Isaac C Rhew; Melissa A Lewis; Devon A Abdallah; Mary E Larimer; John E Schulenberg; Christine M Lee
Journal:  Psychol Addict Behav       Date:  2018-12

3.  Ensuring Causal, Not Casual, Inference.

Authors:  Rashelle J Musci; Elizabeth Stuart
Journal:  Prev Sci       Date:  2019-04

4.  Estimating the Effects of a Complex, Multidimensional Moderator: An Example of Latent Class Moderation to Examine Differential Intervention Effects of Substance Use Services.

Authors:  Bethany C Bray; Eric K Layland; Samuel W Stull; Sara A Vasilenko; Stephanie T Lanza
Journal:  Prev Sci       Date:  2022-10-12

5.  Motives for Alcohol and Marijuana Use as Predictors of Use and Problem Use Among Young Adult College Students.

Authors:  Akilah Patterson; Milkie Vu; Regine Haardörfer; Michael Windle; Carla J Berg
Journal:  J Drug Issues       Date:  2020-05-14

Review 6.  Sensitivity and specificity of information criteria.

Authors:  John J Dziak; Donna L Coffman; Stephanie T Lanza; Runze Li; Lars S Jermiin
Journal:  Brief Bioinform       Date:  2020-03-23       Impact factor: 11.622

7.  Drinking Intensity at Age 29/30 as a Predictor of Alcohol Use Disorder Symptoms at Age 35 in a National Sample.

Authors:  Megan E Patrick; Rebecca J Evans-Polce; Michael J Parks; Yvonne M Terry-McElrath
Journal:  J Stud Alcohol Drugs       Date:  2021-05       Impact factor: 2.582

8.  A Latent Transition Analysis of Self-Reported Reasons for Marijuana Use During Young Adulthood.

Authors:  Bethany C Bray; Patricia A Berglund; Rebecca J Evans-Polce; Megan E Patrick
Journal:  Eval Health Prof       Date:  2020-12-30       Impact factor: 2.651

9.  Causal inference with observational data: the need for triangulation of evidence.

Authors:  Gemma Hammerton; Marcus R Munafò
Journal:  Psychol Med       Date:  2021-03-08       Impact factor: 7.723

10.  Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound.

Authors:  Izzuddin M Aris; Aaron L Sarvet; Mats J Stensrud; Romain Neugebauer; Ling-Jun Li; Marie-France Hivert; Emily Oken; Jessica G Young
Journal:  Am J Epidemiol       Date:  2021-07-01       Impact factor: 4.897

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.