I think I will leave this to others to try to tackle
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Reference: Goldsmith, KA, Chalder, TC, White, PD et al., (2016). Measurement error, time lag, unmeasured confounding: considerations for longitudinal estimation of the effect of a mediator in randomised clinical trials. Statistical Methods in Medical Research.
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Title: Measurement error, time lag, unmeasured confounding: considerations for longitudinal estimation of the effect of a mediator in randomised clinical trials
Abstract:
Clinical trials are expensive and time-consuming and so should also be used to study how treatments work.
This would allow evaluation of theoretical treatment models and refinement and improvement of treatments.
Treatment processes can be studied using mediation analysis.
Randomised treatment makes some of the assumptions of mediation models plausible, but the mediator – outcome relationship remains one that can be subject to bias.
In addition, mediation is assumed to be a temporally ordered longitudinal process, but most mediation studies to date have been cross-sectional and unable to explore this assumption.
This study used longitudinal structural equation modelling of mediator and outcome measurements from the PACE trial of rehabilitative treatments for chronic fatigue syndrome (ISRCTN 54285094) to address these issues.
In particular, autoregressive and simplex models were used to study measurement error in the mediator, different time lags in the mediator – outcome relationship, unmeasured confounding of the mediator and outcome, and the assumption of a constant mediator – outcome relationship over time.
Results showed that allowing for measurement error and unmeasured confounding were important.
Concurrent rather than lagged mediator – outcome effects were more consistent with the data, possibly due to the wide spacing of measurements.
Assuming a constant mediator-outcome relationship over time increased precision.
Publication status: In press
Peer Review status: Peer reviewed
Version: Accepted manuscript
Funder: Medical Research Council
Funder: Department for Health for England
Funder: The Scottish Chief Scientist Office
Funder: Department for Work and Pensions
Notes: © The Author(s) 2016. This article has been accepted for Statistical Methods in Medical Research.
About The Authors
Goldsmith, KA More by this author
Chalder, TC More by this author
White, PD More by this author
Sharpe, Michael More by this author
Oxford, MSD, Psychiatry
St Cross College