umu.sePublications
Change search
Link to record
Permanent link

Direct link
BETA
Karlsson, Maria
Publications (10 of 18) Show all publications
Karlsson, M. (2018). Omvänt klassrum i en statistikkurs. In: Stefan Hrastinski (Ed.), Digitalisering av högre utbildning: (pp. 153-156). Lund: Studentlitteratur AB
Open this publication in new window or tab >>Omvänt klassrum i en statistikkurs
2018 (Swedish)In: Digitalisering av högre utbildning / [ed] Stefan Hrastinski, Lund: Studentlitteratur AB, 2018, p. 153-156Chapter in book (Other academic)
Place, publisher, year, edition, pages
Lund: Studentlitteratur AB, 2018
Keywords
flipped classroom, Scalable Learning, statistics, teaching statistics, omvänt klassrum, digitalt undervisningsverktyg, statistik, statistikdidaktik
National Category
Didactics Learning Probability Theory and Statistics
Identifiers
urn:nbn:se:umu:diva-151461 (URN)978-91-44-11972-4 (ISBN)
Available from: 2018-09-04 Created: 2018-09-04 Last updated: 2018-10-25Bibliographically approved
Karlsson, M., Lundquist, A. & Lundin, M. (2017). Student active learning online and in the classroom by combining the best of Flipped Classroom and MOOCs when teaching statistics. In: Royal Statistical Society 2017 International Conference, Glasgow, 4-7 september 2017: . Paper presented at Royal Statistical Society 2017 International Conference.
Open this publication in new window or tab >>Student active learning online and in the classroom by combining the best of Flipped Classroom and MOOCs when teaching statistics
2017 (English)In: Royal Statistical Society 2017 International Conference, Glasgow, 4-7 september 2017, 2017Conference paper, Oral presentation with published abstract (Other academic)
National Category
Probability Theory and Statistics Didactics
Identifiers
urn:nbn:se:umu:diva-140579 (URN)
Conference
Royal Statistical Society 2017 International Conference
Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2018-06-09
Karlsson, M., Lundquist, A. & Lundin, M. (2017). Student active learning online and in the classroom by combining the best ofFlipped Classroom and MOOCs. In: Universitetspedagogiska konferensen 2017.: Undervisning i praktiken – föreläsning, flexibelt eller mitt emellan?. Paper presented at Universitetspedagogiska konferensen 2017, Umeå, 24-25 oktober, 2017. (pp. 37-37).
Open this publication in new window or tab >>Student active learning online and in the classroom by combining the best ofFlipped Classroom and MOOCs
2017 (English)In: Universitetspedagogiska konferensen 2017.: Undervisning i praktiken – föreläsning, flexibelt eller mitt emellan?, 2017, p. 37-37Conference paper, Oral presentation with published abstract (Other academic)
National Category
Probability Theory and Statistics Didactics
Identifiers
urn:nbn:se:umu:diva-141381 (URN)
Conference
Universitetspedagogiska konferensen 2017, Umeå, 24-25 oktober, 2017.
Available from: 2017-10-31 Created: 2017-10-31 Last updated: 2018-06-09
diva2:1149056
Open this publication in new window or tab >>Using the FMT estimator for analysis of censored household demand data
2017 (English)In: Royal Statistical Society 2017 International Conference, Glasgow, 4 – 7 september 2017, 2017Conference paper, Poster (with or without abstract) (Other academic)
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-140581 (URN)
Conference
Royal Statistical Society 2017 International Conference
Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2018-06-09
Karlsson, M. & Lundin, M. (2016). On statistical methods for labor market evaluation under interference between units. Uppsala: Institutet för arbetsmarknads- och utbildningspolitisk utvärdering, IFAU
Open this publication in new window or tab >>On statistical methods for labor market evaluation under interference between units
2016 (English)Report (Refereed)
Abstract [en]

Evaluation studies aim to provide answers to important questions like: How does this program or policy intervention affect the outcome variables of interest? In order to answer such questions, using the traditional statistical evaluation (or causal inference) methods, some conditions must be satised. One requirement is that the outcomes of individuals are not affected by the treatment given to other individuals, i.e., that the no-interference assumption is satisfied. This assumption might, in many situations, not be plausible. However, recent progress in the research field has provided us with statistical methods for causal inference even under interference. In this paper, we review some of themost important contributions made. We also discuss how we think these methods can or cannot be used within the field of policy evaluation and if there are some measures to be taken when planning an evaluation study in order to be able to use a particular method. In addition, we give examples on how interference has been dealt within some evaluation applications including, but not limited to, labor market evaluations, in the recent past.

Place, publisher, year, edition, pages
Uppsala: Institutet för arbetsmarknads- och utbildningspolitisk utvärdering, IFAU, 2016. p. 35
Series
IFAU Working Paper, ISSN 1651-1166 ; 2016:24
Keywords
causal effect, causal inference, contagion effect, direct and indirect effects, evaluation studies, neighborhood effect, peer effect, peer influence effect, policy intervention, spillover effect, SUTVA, treatment effect
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-128893 (URN)
Funder
Institute for Evaluation of Labour Market and Education Policy (IFAU), 152/2012
Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2018-06-09
Karlsson, M. (2015). Populärvetenskaplig sammanfattning i studentuppsatser: ett sätt att (del-)examineranationellt examensmål nr 4.. In: Universitetspedagogiska konferensen 2015, Umeå, Umeå universitet, 8-9 okt 2015: Gränslös kunskap. Paper presented at Universitetspedagogiska konferensen 2015: gränslös kunskap (pp. 80-80).
Open this publication in new window or tab >>Populärvetenskaplig sammanfattning i studentuppsatser: ett sätt att (del-)examineranationellt examensmål nr 4.
2015 (Swedish)In: Universitetspedagogiska konferensen 2015, Umeå, Umeå universitet, 8-9 okt 2015: Gränslös kunskap, 2015, p. 80-80Conference paper, Oral presentation with published abstract (Other academic)
National Category
Probability Theory and Statistics Didactics
Identifiers
urn:nbn:se:umu:diva-140540 (URN)
Conference
Universitetspedagogiska konferensen 2015: gränslös kunskap
Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2018-06-09
Lee, M.-j. & Karlsson, M. (2015). Trimmed and winsorized semiparametric estimator for left-truncated and right-censored regression models. Metrika (Heidelberg), 78(4), 485-495
Open this publication in new window or tab >>Trimmed and winsorized semiparametric estimator for left-truncated and right-censored regression models
2015 (English)In: Metrika (Heidelberg), ISSN 0026-1335, E-ISSN 1435-926X, Vol. 78, no 4, p. 485-495Article in journal (Refereed) Published
Abstract [en]

For a linear regression model subject to left-truncation and right-censoring where the truncation and censoring points are known constants (or always observed if random), Karlsson and Laitila (Stat Probab Lett 78:2567–2571,2008) proposed a semiparametric estimator which deals with left-truncation by trimming and right-censoring by ‘winsorizing’. The estimator was motivated by a zero moment condition where a transformed error term appears with trimmed and winsorized tails. This paper takes the semiparametric estimator further by deriving the asymptotic distribution that was not shown in Karlsson and Laitila (Stat Probab Lett 78:2567–2571,2008) and discusses its implementation aspects in practice, albeit brief.

Place, publisher, year, edition, pages
Springer, 2015
Keywords
Left truncation, Right censoring, LTRC, Semiparametrics, Trimmed mean, Winsorized mean
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-95573 (URN)10.1007/s00184-014-0513-9 (DOI)000351703800007 ()
Available from: 2014-11-06 Created: 2014-11-03 Last updated: 2018-06-07Bibliographically approved
Lundin, M. & Karlsson, M. (2014). Estimation of causal effects in observational studies with interference between units. Statistical Methods & Applications, 23(3), 417-433
Open this publication in new window or tab >>Estimation of causal effects in observational studies with interference between units
2014 (English)In: Statistical Methods & Applications, ISSN 1618-2510, E-ISSN 1613-981X, Vol. 23, no 3, p. 417-433Article in journal (Refereed) Published
Abstract [en]

Causal effects are usually estimated under the assumption of no interference between individuals. This assumption means that the potential outcomes for one individual are unaffected by the treatments received by other individuals. In many situations, this is not reasonable to assume. Moreover, not taking interference into account could result in misleading conclusions about the effect of a treatment. For two-stage observational studies, where treatment assigment is randomized in the first stage but not in the second stage, we propose IPW estimators of direct and indirect causal effects as defined by Hudgens and Halloran (J Am Stat Assoc 103(482):832-842, 2008) for two-stage randomized studies. We illustrate the use of these estimators in an evaluation study of an implementation of Triple P (a parenting support program) within preschools in Uppsala, Sweden.

Keywords
Causal inference, direct effect, indirect effect
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-43238 (URN)10.1007/s10260-014-0257-8 (DOI)000339895900010 ()
Note

Originally included in thesis in manuscript form.

Available from: 2011-04-25 Created: 2011-04-25 Last updated: 2018-06-08Bibliographically approved
Karlsson, M. & Laitila, T. (2014). Finite mixture modeling of censored regression models. Statistical papers, 55(3), 627-642
Open this publication in new window or tab >>Finite mixture modeling of censored regression models
2014 (English)In: Statistical papers, ISSN 0932-5026, E-ISSN 1613-9798, Vol. 55, no 3, p. 627-642Article in journal (Refereed) Published
Abstract [en]

A finite mixture of Tobit models is suggested for estimation of regression models with a censored response variable. A mixture of models is not primarily adapted due to a true component structure in the population; the flexibility of the mixture is suggested as a way of avoiding non-robust parametrically specified models. The new estimator has several interesting features. One is its potential to yield valid estimates in cases with a high degree of censoring. The estimator is in a Monte Carlo simulation compared with earlier suggestions of estimators based on semi-parametric censored regression models. Simulation results are partly in favor of the proposed estimator and indicate potentials for further improvements.

Keywords
finite mixture models, censoring, Tobit, EM-algorithm
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-67461 (URN)10.1007/s00362-013-0509-y (DOI)000339339100004 ()
Available from: 2013-03-19 Created: 2013-03-19 Last updated: 2018-06-08Bibliographically approved
Karlsson, M. & Lindmark, A. (2014). truncSP: an R package for estimation of semi-parametric truncated linear regression models. Journal of Statistical Software, 57(14), 1-19
Open this publication in new window or tab >>truncSP: an R package for estimation of semi-parametric truncated linear regression models
2014 (English)In: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 57, no 14, p. 1-19Article 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
Keywords
truncation, limited dependent variable, semi-parametric estimators, R
National Category
Probability Theory and Statistics Computer Sciences Mathematics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-88483 (URN)10.18637/jss.v057.i14 (DOI)000341021200001 ()2-s2.0-84899828272 (Scopus ID)
Available from: 2014-05-06 Created: 2014-05-06 Last updated: 2018-06-07Bibliographically approved
Organisations

Search in DiVA

Show all publications