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truncSP: an R package for estimation of semi-parametric truncated linear regression models
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
2014 (English)In: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 57, no 14, 1-19 p.Article in journal (Refereed) Published
Abstract [en]

Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP. The package contains functions for the estimation of semi-parametric truncated linear regression models using three different estimators: the symmetrically trimmed least squares, quadratic mode, and left truncated estimators, all of which have been shown to have good asymptotic and finite sample properties. The package also provides functions for the analysis of the estimated models. Data from the environmental sciences are used to illustrate the functions in the package.

Place, publisher, year, edition, pages
American Statistical Association , 2014. Vol. 57, no 14, 1-19 p.
Keyword [en]
truncation, limited dependent variable, semi-parametric estimators, R
National Category
Probability Theory and Statistics Computer Science Mathematics
Research subject
URN: urn:nbn:se:umu:diva-88483DOI: 10.18637/jss.v057.i14ISI: 000341021200001ScopusID: 2-s2.0-84899828272OAI: diva2:715868
Available from: 2014-05-06 Created: 2014-05-06 Last updated: 2016-09-29Bibliographically approved
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.
Statistical studies, ISSN 1100-8989 ; 49
Registers, quality of care, socioeconomic status, hospital performance, stroke, mediation, sensitivity analysis, truncation, censoring
National Category
Probability Theory and Statistics
Research subject
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)
Available from: 2016-09-30 Created: 2016-09-23 Last updated: 2016-09-29Bibliographically approved

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