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The effectLiteR approach for analyzing average and conditional effects

(2016) MULTIVARIATE BEHAVIORAL RESEARCH. 51(2-3). p.374-391
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Abstract
We present a framework for estimating average and conditional effects of a discrete treatment variable on a continuous outcome variable, conditioning on categorical and continuous covariates. Using the new approach, termed the EffectLiteR approach, researchers can consider conditional treatment effects given values of all covariates in the analysis and various aggregates of these conditional treatment effects such as average effects, effects on the treated, or aggregated conditional effects given values of a subset of covariates. Building on structural equation modeling, key advantages of the new approach are (1) It allows for latent covariates and outcome variables; (2) it permits (higher order) interactions between the treatment variable and categorical and (latent) continuous covariates; and (3) covariates can be treated as stochastic or fixed. The approach is illustrated by an example, and open source software EffectLiteR is provided, which makes a detailed analysis of effects conveniently accessible for applied researchers.
Keywords
LATENT CURVE ANALYSIS, PROPENSITY SCORE, PROBING INTERACTIONS, TEST, STATISTICS, INCOMPLETE DATA, REGRESSION, MODEL, VARIABLES, COVARIANCE, MEDIATION, Average and conditional effects, multigroup structural equation, modeling, moderation, stochastic regressors, interactions

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Citation

Please use this url to cite or link to this publication:

Chicago
Mayer, Axel, Lisa Dietzfelbinger, Yves Rosseel, and Rolf Steyer. 2016. “The effectLiteR Approach for Analyzing Average and Conditional Effects.” Multivariate Behavioral Research 51 (2-3): 374–391.
APA
Mayer, A., Dietzfelbinger, L., Rosseel, Y., & Steyer, R. (2016). The effectLiteR approach for analyzing average and conditional effects. MULTIVARIATE BEHAVIORAL RESEARCH, 51(2-3), 374–391.
Vancouver
1.
Mayer A, Dietzfelbinger L, Rosseel Y, Steyer R. The effectLiteR approach for analyzing average and conditional effects. MULTIVARIATE BEHAVIORAL RESEARCH. Abingdon: Routledge Journals, Taylor & Francis Ltd; 2016;51(2-3):374–91.
MLA
Mayer, Axel, Lisa Dietzfelbinger, Yves Rosseel, et al. “The effectLiteR Approach for Analyzing Average and Conditional Effects.” MULTIVARIATE BEHAVIORAL RESEARCH 51.2-3 (2016): 374–391. Print.
@article{8507852,
  abstract     = {We present a framework for estimating average and conditional effects of a discrete treatment variable on a continuous outcome variable, conditioning on categorical and continuous covariates. Using the new approach, termed the EffectLiteR approach, researchers can consider conditional treatment effects given values of all covariates in the analysis and various aggregates of these conditional treatment effects such as average effects, effects on the treated, or aggregated conditional effects given values of a subset of covariates. Building on structural equation modeling, key advantages of the new approach are (1) It allows for latent covariates and outcome variables; (2) it permits (higher order) interactions between the treatment variable and categorical and (latent) continuous covariates; and (3) covariates can be treated as stochastic or fixed. The approach is illustrated by an example, and open source software EffectLiteR is provided, which makes a detailed analysis of effects conveniently accessible for applied researchers.},
  author       = {Mayer, Axel and Dietzfelbinger, Lisa and Rosseel, Yves and Steyer, Rolf},
  issn         = {0027-3171},
  journal      = {MULTIVARIATE BEHAVIORAL RESEARCH},
  keyword      = {LATENT CURVE ANALYSIS,PROPENSITY SCORE,PROBING INTERACTIONS,TEST,STATISTICS,INCOMPLETE DATA,REGRESSION,MODEL,VARIABLES,COVARIANCE,MEDIATION,Average and conditional effects,multigroup structural equation,modeling,moderation,stochastic regressors,interactions},
  language     = {eng},
  number       = {2-3},
  pages        = {374--391},
  publisher    = {Routledge Journals, Taylor \& Francis Ltd},
  title        = {The effectLiteR approach for analyzing average and conditional effects},
  url          = {http://dx.doi.org/10.1080/00273171.2016.1151334},
  volume       = {51},
  year         = {2016},
}

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