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Uncertainty intervals for unobserved confounding of direct and indirect effects with extensions to censoring and truncation
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

When performing a mediation analysis, i.e. estimating direct and indirect effects of a given exposure on an outcome, strong assumptions are made about unconfoundedness. These assumptions are difficult to verify in a given situation and therefore a mediation analysis should be complemented with a sensitivity analysis to assess the impact of violations. Lindmark et al. (2016) proposed a sensitivity analysis method for parametric estimation of conditional and marginal direct and indirect effects when the mediator and outcome are binary and modeled using probit models. In this paper we extend this to include cases with continuous mediators and outcomes and suggest extensions to the cases when the continuous outcome variable is censored or truncated. Three sensitivity parameters are used, consisting of the correlations between the error terms of the mediator, outcome and exposure assignment mechanism models. These correlations are incorporated into the estimation of the model parameters and sampling variability is taken into account through the construction of uncertainty intervals.

Keyword [en]
mediation, sensitivity analysis, unmeasured confounding, sequential ignorability, uncertainty intervals, censoring, truncation
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:umu:diva-125930OAI: oai:DiVA.org:umu-125930DiVA: diva2:973916
Available from: 2016-09-23 Created: 2016-09-22 Last updated: 2016-09-28
In thesis
1. Statistical methods for register based studies with applications to stroke
Open this publication in new window or tab >>Statistical methods for register based studies with applications to stroke
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Statistiska metoder för registerbaserade studier med tillämpningar på stroke
Abstract [en]

This thesis adds to the area of register based research, with a particular focus on health care quality and (in)equality. Contributions are made to the areas of hospital performance benchmarking, mediation analysis, and regression when the outcome variable is limited, with applications related to Riksstroke (the Swedish stroke register).

An important part of quality assurance is to identify, follow up, and understand the mechanisms of inequalities in outcome and/or care between different population groups. The first paper of the thesis uses Riksstroke data to investigate socioeconomic differences in survival during different time periods after stroke. The second paper focuses on differences in performance between hospitals, illustrating the diagnostic properties of a method for benchmarking hospital performance and highlighting the importance of balancing clinical relevance and the statistical evidence level used.

Understanding the mechanisms behind observed differences is a complicated but important issue. In mediation analysis the goal is to investigate the causal mechanisms behind an effect by decomposing it into direct and indirect components. Estimation of direct and indirect effects relies on untestable assumptions and a mediation analysis should be accompanied by an analysis of how sensitive the results are to violations of these assumptions. The third paper proposes a sensitivity analysis method for mediation analysis based on binary probit regression. This is then applied to a mediation study based on Riksstroke data.

Data registration is not always complete and sometimes data on a variable are unavailable above or below some value. This is referred to as censoring or truncation, depending on the extent to which data are missing. The final two papers of the thesis are concerned with the estimation of linear regression models for limited outcome variables. The fourth paper presents a software implementation of three semi-parametric estimators of truncated linear regression models. The fifth paper extends the sensitivity analysis method proposed in the third paper to continuous outcomes and mediators, and situations where the outcome is truncated or censored.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2016. 30 p.
Series
Statistical studies, ISSN 1100-8989 ; 49
Keyword
Registers, quality of care, socioeconomic status, hospital performance, stroke, mediation, sensitivity analysis, truncation, censoring
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-125953 (URN)978-91-7601-553-7 (ISBN)
Public defence
2016-10-21, Hörsal E, Humanisthuset, Umeå, 09:30 (English)
Opponent
Supervisors
Available from: 2016-09-30 Created: 2016-09-23 Last updated: 2016-09-29Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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  • asciidoc
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