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  • 101.
    Eriksson, Kimmo
    et al.
    Stockholms universitet, Humanistiska fakulteten, Institutionen för arkeologi och antikens kultur. Mälardalen University, Sweden.
    Häggström, Olle
    Lord's Paradox in a Continuous Setting and a Regression Artifact in Numerical Cognition Research2014Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, nr 4, s. e95949-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper we review, and elaborate on, the literature on a regression artifact related to Lord's paradox in a continuous setting. Specifically, the question is whether a continuous property of individuals predicts improvement from training between a pretest and a posttest. If the pretest score is included as a covariate, regression to the mean will lead to biased results if two critical conditions are satisfied: (1) the property is correlated with pretest scores and (2) pretest scores include random errors. We discuss how these conditions apply to the analysis in a published experimental study, the authors of which concluded that linearity of children's estimations of numerical magnitudes predicts arithmetic learning from a training program. However, the two critical conditions were clearly met in that study. In a reanalysis we find that the bias in the method can fully account for the effect found in the original study. In other words, data are consistent with the null hypothesis that numerical magnitude estimations are unrelated to arithmetic learning.

  • 102.
    Fackle Fornius, Ellinor
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Optimal Design of Experiments for the Quadratic Logistic Model2008Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Optimal design of experiments for binary data is the topic of this thesis. A particular logistic model including a quadratic term in the linear predictor is considered. Determining an optimal design for this model is complicated by the fact that the optimal design is dependent on the unknown true parameters. Methods to obtain locally c- and D-optimal designs are illustrated. c-optimal designs are derived via the canonical design space. This space offers an useful geometric interpretation of the design problem. Using the canonical design space it is shown how the number of design points in a c-optimal design varies depending on the parameter being estimated. Furthermore, formulae for finding the design points along with the corresponding design weights are derived. The small sample performance of the locally optimal designs is compared to the performances of some non-optimal designs in a simulation study. The evaluations are made in terms of mean squared error of the maximum likelihood estimator. The small sample distribution of the maximum likelihood estimator is demonstrated to be quite different from the asymptotic distribution. It was also concluded that non-existence of the maximum likelihood estimator is a critical problem for the quadratic logistic model. The designs differed considerably in this respect and this problem also turned out to be parameter dependent. As a solution to this problem another type of parameter estimator is suggested, which is also evaluated in the simulation study. It performs better in this respect, but not completely satisfactory because it fails in other respects. Two kinds of sequential design approaches are proposed for the purpose of finding the point of optimum response. One is a parametric optimal design approach where c-optimal designs are updated sequentially. The other one is a nonparametric stochastic approximation approach. The suggested designs are evaluated and compared via simulations. Based on the simulation results the c-optimal design approach was consistently favored. Sequential estimation proved to be an effective way to handle the parameter dependence issue.

  • 103.
    Fackle Fornius, Ellinor
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Sequential Designs for Binary Data with the Purpose to Maximize the Probability of Response2008Inngår i: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 37, nr 6, s. 1219-1238Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Two kinds of sequential designs are proposed for finding the point that maximizes the probability of response assuming a binary response variable and a quadratic logistic regression model. One is a parametric optimal design approach and the other one is a nonparametric stochastic approximation approach. The suggested sequential designs are evaluated and compared in a simulation study. In summary the parametric approach performed very well whereas its competitor failed in some cases.

  • 104.
    Fackle-Fornius, Ellinor
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Festschrift in Honor of Hans Nyquist on the Occasion of his 65th Birthday2015Collection/Antologi (Fagfellevurdert)
  • 105.
    Fackle-Fornius, Ellinor
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Miller, Frank
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Nyquist, Hans
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Implementation of maximin efficient designs in dose-finding studies2015Inngår i: Pharmaceutical statistics, ISSN 1539-1604, E-ISSN 1539-1612, Vol. 14, nr 1, s. 63-73Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper considers the maximin approach for designing clinical studies. A maximin efficient design maximizes the smallest efficiency when compared with a standard design, as the parameters vary in a specified subset of the parameter space. To specify this subset of parameters in a real situation, a four-step procedure using elicitation based on expert opinions is proposed. Further, we describe why and how we extend the initially chosen subset of parameters to a much larger set in our procedure. By this procedure, the maximin approach becomes feasible for dose-finding studies. Maximin efficient designs have shown to be numerically difficult to construct. However, a new algorithm, the H-algorithm, considerably simplifies the construction of these designs.We exemplify the maximin efficient approach by considering a sigmoid Emax model describing a dose–response relationship and compare inferential precision with that obtained when using a uniform design. The design obtained is shown to be at least 15% more efficient than the uniform design.

  • 106.
    Fackle-Fornius, Ellinor
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Nyquist, Hans
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Optimal Allocation for Comparing Treatment Effects2010Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Suppose the mean responses from m-1 treatment groups in an experiment are to be compared to the mean of a control group. A uniform allocation of observations over the treatment groups is then often used. However, other allocation schemes can give a better precision in the inference. This is particularly emphasised when the variances of the responses are different in different treatment groups. Here we consider optimal allocation according to the A- and D_{A}-criteria for the cases of equal as well as different variances of the responses in the treatment groups. We also consider the case when costs for observations are different in different treatment groups. As expected, optimal allocation depends on the variances of the responses in the treatment groups. If the variances are unknown, a minimax strategy can be used. This means that allocation is made subject to the worst case as the variances are varied within specified intervals. In general, minimax designs are difficult to find. However, for the case of treatment groups, as is considered here, we show that the minimax strategy is very simple to apply. The efficiency of allocations according to the minimax strategy is compared to the uniform as well as the locally optimal D_{A}- and A-optimal allocations.

  • 107.
    Fackle-Fornius, Ellinor
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Nyquist, Hans
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Optimal allocation to treatment groups under variance heterogeneity2015Inngår i: Statistica sinica, ISSN 1017-0405, E-ISSN 1996-8507, Vol. 25, nr 2, s. 537-549Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The problem of allocating experimental units to treatment groups when variance heterogeneity over treatment groups is present is considered. A(A)- and D-A-optimal allocations are derived for estimation of linear combinations of treatment means. Explicit expressions for the design weights are provided for the A(A)-optimal design. The minimax strategy is introduced as an approach to handle unknown variances. Efficiencies of minimax allocations are evaluated.

  • 108.
    Fackle-Fornius, Ellinor
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Wänström, Linda
    Construction of Minimax Designs for the Trinomial Spike Model in Contingent Valuation Experiments2013Inngår i: mODa 10 – Advances in Model-Oriented Design and Analysis: Proceedings of the 10th International Workshop in Model-Oriented Design and Analysis Held in Łagów Lubuski, Poland, June 10–14, 2013 / [ed] Dariusz Ucinski, Anthony C. Atkinson, Maciej Patan, Springer, 2013, s. 63-72Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    This paper concerns design of contingent valuation experiments when interest is in knowing whether respondents have positive willingness to pay and if so, if they are willing to pay a certain amount for a specified good. A trinomial spike model is used to model the response. Locally D- and c-optimal designs are derived and it is shown that any locally optimal design can be deduced from the locally optimal design for the case when one of the model parameters is standardized. It is demonstrated how information about the parameters, e.g. from pilot studies, can be used to construct minimax and maximin efficient designs, for which the best guaranteed value of the criterion function or efficiency function is sought under the assumption that the parameter values are within certain regions. The proposed methodology is illustrated in an application where the value of environmentally friendly produced clothes is evaluated.

  • 109.
    Fackle-Fornius, Ellinor
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Wänström, Linda
    Minimax D-optimal designs of contingent valuation experiments: willingness to pay for environmentally friendly clothes2014Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, nr 4, s. 895-908Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper demonstrates how to plan a contingent valuation experiment to assess the value of ecologically produced clothes. First, an appropriate statistical model (the trinomial spike model) that describes the probability that a randomly selected individual will accept any positive bid, and if so, will accept the bid A, is defined. Secondly, an optimization criterion that is a function of the variances of the parameter estimators is chosen. However, the variances of the parameter estimators in this model depend on the true parameter values. Pilot study data are therefore used to obtain estimates of the parameter values and a locally optimal design is found. Because this design is only optimal given that the estimated parameter values are correct, a design that minimizes the maximum of the criterion function over a plausable parameter region (i.e. a minimax design) is then found.

  • 110. Fenske, Nora
    et al.
    Fahrmeir, Ludwig
    Rzehak, Peter
    Hothorn, Torsten
    Höhle, Michael
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Boosting Structured Additive Quantile Regression for Longitudinal Childhood Obesity Data2013Inngår i: The International Journal of Biostatistics, ISSN 1557-4679, E-ISSN 1557-4679, Vol. 9, nr 1, s. 1-18Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

  • 111.
    Fetisova, Ekaterina
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Evaluation of climate model simulations by means of statistical methods2015Licentiatavhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Evaluation of climate model simulations is a key issue within climate research. The statistical framework proposed by Sundberg et al., 2012, provides a theoretical underpinning of methods for evaluation of climate models by use of climateproxy data from the last millennium. In the present work, the statistical framework above is used to suggest several latent factor models of different complexity that can be used for estimating the amplitude of a forcing effect in aclimate model by comparison with the observed/reconstructed climate. The performance of the models is evaluated and compared in a pseudo-proxy experiment, in which the true unobservable temperature series is replaced by selected realizations of a climate simulation model. For different levels of added noise, different conclusions can be drawn. However, for realistic noise levels, we find that the simplest model, the just-identified two-indicator one-factor model, denoted j.i.FA(2,1), is a competitive alternative to models with more complicated structure. Moreover, we discover that the Fieller method of constructing confidence regions, associated with the j.i.FA(2,1)-model, outperforms the Wald confidence interval, which in most cases fails to provide sensible and interpretable conclusions about the climate model under consideration. Last but not least, the results indicate a good performance of the j.i.FA(2,1)-model even in the presence of heteroscedasticity.

  • 112. Flygare, Ann-Marie
    et al.
    Hedlin, Dan
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Empirical Study on the Size of Nonresponse Bias2018Inngår i: JSM Proceedings, Survey Research Methods Section, Alexandria, VA, 2018Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    There are expressions for nonresponse bias, all of which require population quantities. In one expression for nonresponse bias, due to Bethlehem (1988, 2009), the bias is approximately equal to a function of the population covariance between the study variable and the response propensity (probability) and the population mean of the propensities. The covariance is hard to estimate (due to nonresponse). To empirically examine the covariance and the nonresponse bias, we have done two studies where the sample values of survey variables are known and the response propensities are estimated.The first study is a mail survey of a population of residents in the city of Solna in Sweden,20-74 years of age. The questionnaire consists of items on marital status and income; we have obtained the true values of those from the Swedish Tax Agency. We also know birth country, the type of area of residents, specific age and gender of each sampled individual.The second study is a web survey at Stockholm University, the population is faculty employees at the department of psychology. This survey is a census and the variables that we regard as our study variables are income from university and total income. The true values of income from university are given by the HR-department and total income from the Tax Agency.

  • 113.
    Frank, Ove
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Assessing dependence, independence, and conditional independence2015Inngår i: Festschrift in Honor of Hans Nyquist on the Occation of His 65th Birthday / [ed] Ellinor Fackle-Fornius, Stockholm: Stockholm University, 2015, s. 100-115Kapittel i bok, del av antologi (Fagfellevurdert)
  • 114.
    Frank, Ove
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Network sampling2011Inngår i: International Encyclopedia of Statistical Science / [ed] Miodrag Lovric, Berlin: Springer, 2011, s. 404-Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 115.
    Frank, Ove
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Network surveys2010Inngår i: Official statistics: methodology and applications in honour of Daniel Thorburn / [ed] Michael Carlson, Hans Nyquist, Mattias Villani, Stockholm: Department of Statistics, Stockholm University , 2010, s. 51-60Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 116.
    Frank, Ove
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Probabilistic network models2011Inngår i: International Encyclopedia of Statistical Science / [ed] Miodrag Lovric, Berlin: Springer, 2011, s. 458-Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 117.
    Frank, Ove
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Social Network Analysis, Estimation, and Sampling in2015Inngår i: Encyclopedia of Complexity and Systems Science / [ed] Robert A. Meyers, New York: Springer Berlin/Heidelberg, 2015, s. 1-26Kapittel i bok, del av antologi (Fagfellevurdert)
  • 118.
    Frank, Ove
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Social Network Analysis, Estimation and Sampling in2009Inngår i: Encyclopedia of Complexity and Systems Science / [ed] Robert A. Meyers, New York: Springer , 2009, s. 8213-8231Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 119.
    Frank, Ove
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Tid för nya metoder i tillämpad statistik.2011Inngår i: Qvintensen, ISSN 2000-1819, nr 2, s. 14-16Artikkel i tidsskrift (Annet (populærvitenskap, debatt, mm))
  • 120.
    Frank, Ove
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Carrington, Peter J.
    Estimation of offending and co-offending using available data with model support2007Inngår i: The Journal of mathematical sociology, ISSN 0022-250X, E-ISSN 1545-5874, Vol. 31, nr 1, s. 1-46Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Police data under-report the numbers of crimes and of offenders, the numbers of offenders participating in individual criminal incidents (incident sizes) and the numbers of incidents in which individual offenders participate (offender activity). Criminal participation in incidents is a concept that underlies and unifies all of these phenomena, so that the numbers of incidents and of offenders, and incident size distributions and offender activity distributions, can all be derived from the criminal participation matrix. Two related probability models are presented that permit the estimation of numbers of incidents and offenders, incident size distributions, offender activity distributions, and co-offending distributions, from police-reported crime data, and data on the reporting of crime to police. The models are estimated, using data from the Canadian Uniform Crime Reporting Survey and national victimization surveys for the period 1995 - 2001.

  • 121.
    Frank, Ove
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Shafie, Termeh
    University of Konstanz, Germany.
    Multigraph Complexity, Data Aggregation, and Statistical Analysis2013Rapport (Annet vitenskapelig)
  • 122.
    Frank, Ove
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Shafie, Termeh
    Multivariate Entropy Analysis of Network Data2016Inngår i: Bulletin of Sociological Methodology, ISSN 0759-1063, E-ISSN 2070-2779, Vol. 129, s. 45-63Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Multigraphs with numerical or qualitative attributes defined on vertices and edges can benefit from systematic methods based on multivariate entropies for describing and analysing the interdependencies that are present between vertex and edge attributes. This is here illustrated by application of these tools to a subset of data on the social relations among Renaissance Florentine families collected by John Padgett. Using multivariate entropies we show how it is possible to systematically check for tendencies in data that can be described as independencies or conditional independencies, or as dependencies allowing certain combinations of variables to predict other variables. We also show how different structural models can be tested by divergence measures obtained from the multivariate entropies.

  • 123.
    Frank, Ove
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Shafie, Termeh
    Random multigraphs and aggregated triads with fixed degrees2018Inngår i: Network Science, ISSN 2050-1242, Vol. 6, nr 2, s. 232-250Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Random multigraphs with fixed degrees are obtained by the configuration model or by so called random stub matching. New combinatorial results are given for the global probability distribution of edge multiplicities and its marginal local distributions of loops and edges. The number of multigraphs on triads is determined for arbitrary degrees, and aggregated triads are shown to be useful for analyzing regular and almost regular multigraphs. Relationships between entropy and complexity are given and numerically illustrated for multigraphs with different number of vertices and specified average and variance for the degrees.

  • 124.
    Franzén, Jessica
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Bayesian Cluster Analysis: Some Extensions to Non-standard Situations2008Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    The Bayesian approach to cluster analysis is presented. We assume that all data stem from a finite mixture model, where each component corresponds to one cluster and is given by a multivariate normal distribution with unknown mean and variance. The method produces posterior distributions of all cluster parameters and proportions as well as associated cluster probabilities for all objects. We extend this method in several directions to some common but non-standard situations. The first extension covers the case with a few deviant observations not belonging to one of the normal clusters. An extra component/cluster is created for them, which has a larger variance or a different distribution, e.g. is uniform over the whole range. The second extension is clustering of longitudinal data. All units are clustered at all time points separately and the movements between time points are modeled by Markov transition matrices. This means that the clustering at one time point will be affected by what happens at the neighbouring time points. The third extension handles datasets with missing data, e.g. item non-response. We impute the missing values iteratively in an extra step of the Gibbs sampler estimation algorithm. The Bayesian inference of mixture models has many advantages over the classical approach. However, it is not without computational difficulties. A software package, written in Matlab for Bayesian inference of mixture models is introduced. The programs of the package handle the basic cases of clustering data that are assumed to arise from mixture models of multivariate normal distributions, as well as the non-standard situations.

  • 125.
    Franzén, Jessica
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Bayesian Inference for a Mixture Moddel using the Gibbs SamplerManuskript (Annet vitenskapelig)
  • 126.
    Franzén, Jessica
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Classification with the Possibility of a Deviant Group: An Approach to Twelve-Year-Old StudentsInngår i: Multivariate Behavioral ResearchArtikkel i tidsskrift (Fagfellevurdert)
  • 127.
    Franzén, Jessica
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Implementation of the MBCA Matlab Program for Model-Based Cluster AnalysisManuskript (Annet vitenskapelig)
  • 128.
    Franzén, Jessica
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Longitudinal, Model-Based Clustering with Missing DataManuskript (Annet vitenskapelig)
  • 129.
    Franzén, Jessica
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Successive Clustering of Longitudinal Data: A Bayesian ApproachManuskript (Annet vitenskapelig)
  • 130.
    Franzén, Jessica
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen. Swedish University of Agricultural Sciences, Sweden.
    Thorburn, Daniel
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Urioste, Jorge I.
    Strandberg, Erling
    Genetic evaluation of mastitis liability and recovery through longitudinal analysis of transition probabilities2012Inngår i: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 44, artikkel-id 10Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Many methods for the genetic analysis of mastitis use a cross-sectional approach, which omits information on, e.g., repeated mastitis cases during lactation, somatic cell count fluctuations, and recovery process. Acknowledging the dynamic behavior of mastitis during lactation and taking into account that there is more than one binary response variable to consider, can enhance the genetic evaluation of mastitis. Methods: Genetic evaluation of mastitis was carried out by modeling the dynamic nature of somatic cell count (SCC) within the lactation. The SCC patterns were captured by modeling transition probabilities between assumed states of mastitis and non-mastitis. A widely dispersed SCC pattern generates high transition probabilities between states and vice versa. This method can model transitions to and from states of infection simultaneously, i.e. both the mastitis liability and the recovery process are considered. A multilevel discrete time survival model was applied to estimate breeding values on simulated data with different dataset sizes, mastitis frequencies, and genetic correlations. Results: Correlations between estimated and simulated breeding values showed that the estimated accuracies for mastitis liability were similar to those from previously tested methods that used data of confirmed mastitis cases, while our results were based on SCC as an indicator of mastitis. In addition, unlike the other methods, our method also generates breeding values for the recovery process. Conclusions: The developed method provides an effective tool for the genetic evaluation of mastitis when considering the whole disease course and will contribute to improving the genetic evaluation of udder health.

  • 131. Friede, Tim
    et al.
    Posch, Martin
    Zohar, Sarah
    Alberti, Corinne
    Benda, Norbert
    Comets, Emmanuelle
    Day, Simon
    Dmitrienko, Alex
    Graf, Alexandra
    Guenhan, Burak Kuersad
    Hee, Siew Wan
    Lentz, Frederike
    Madan, Jason
    Miller, Frank
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Ondra, Thomas
    Pearce, Michael
    Roever, Christian
    Toumazi, Artemis
    Unkel, Steffen
    Ursino, Moreno
    Wassmer, Gernot
    Stallard, Nigel
    Recent advances in methodology for clinical trials in small populations: the InSPiRe project2018Inngår i: Orphanet Journal of Rare Diseases, ISSN 1750-1172, E-ISSN 1750-1172, Vol. 13, artikkel-id 186Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017. The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods.

  • 132. Gasbarra, Dario
    et al.
    Morlanes, José Igor
    Aalto University, Finland.
    Valkeila, Esko
    Initial Enlargement in a Markov Chain Market Model2011Inngår i: Stochastics and Dynamics, ISSN 0219-4937, Vol. 11, nr 2-3, s. 389-413Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Enlargement of filtrations is a classical topic in the general theory of stochastic processes. This theory has been applied to stochastic finance in order to analyze models with insider information. In this paper we study initial enlargement in a Markov chain market model, introduced by Norberg. In the enlarged filtration, several things can happen: some of the jumps times can be accessible or predictable, but in the original filtration all the jumps times are totally inaccessible. But even if the jumps times change to accessible or predictable, the insider does not necessarily have arbitrage possibilities. Read More: http://www.worldscientific.com/doi/abs/10.1142/S021949371100336X

  • 133.
    Geli, Patricia
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Models Related to Growth and Selection of Antibiotic Resistant Bacteria under Drug Exposure2007Licentiatavhandling, monografi (Annet vitenskapelig)
  • 134.
    Geli Rolfhamre, Patricia
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    From Penicillin Binding Proteins to Community Interventions: Mathematical and Statistical Models Related to Antibiotic Resistance2009Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Antibiotic resistance has become a major public health concern and mathematical models are important analytical tools for the understanding, evaluation and prediction of the resistance problem and related control strategies.

    The risk of emerging antibiotic resistance and selection has rarely been a concern in the design of antibiotic drug dosing regimens. In the first paper, a selection of antibiotic resistant subpopulations for different antibiotic dosing regimens was studied in vitro. The demonstrated complex relationship was influenced by both the rise of new mutants and a postantibiotic effect (PAE) (continued inhibition of bacterial growth after removal of the antibiotic drug). By constructing a mathematical model that incorporated biologically relevant parameters, we were able to assess the risks of resistance development under different dosing strategies.

    In the second paper, the model for PAEs is further developed to determine the implications for different dosing regimens. The result challenges the conventional notion that long PAEs promote extended drug dosing intervals and it allows new hypotheses to be tested experimentally based on the findings from the theoretical framework.

    Since PAE experiments often are time-consuming and laborious, very few studies have been reporting variation for this phenomenon. In the third paper, an extension to capture the stochastic behavior of bacterial population growth under drug exposure is made. The stochastic nature of the model is also an important complement to the existing deterministic models on drug dose drug effect relationships.

    The last paper describes a controlled clinical intervention study aiming at determining whether the frequency of trimethoprim resistance in E. coli can be decreased by a sudden and drastic reduction in trimethoprim use. In addition to evaluating the intervention effect, the model, given estimated parameters, is also used for predicting other interesting outcomes.

  • 135.
    Ghachem, Montasser
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Nationalekonomiska institutionen. Harvard University, United States.
    Distribution of matchings in Myerson’s network formation modelManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Consider a population of n players playing a variant of Myerson's network formation model. Each player simultaneously chooses k other players he would want to be connected to. If two players are in each other choice set, a matching occurs. We call the outcome of the network formation model a k-uniform Myerson graph and study the distribution of matchings on such graphs with homogeneous and heterogeneous populations.

  • 136.
    Ghafouri, Soheila
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för matematikämnets och naturvetenskapsämnenas didaktik.
    Två synsätt på elevers lärande av ämnet statistik: En studie av elever i årskurs 72014Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    The purpose of this paper is to create increased understanding of how pupils learn statistics. This includes gaining insight into pupils' use of their own experience and group experience to help to get a better understanding of statistical problem solving. The study's research questions are about how pupils learn to work with data in tables and diagram and how pupils learn to work with measures.

    The theoretical framework consists of two approaches to studying learning. One approach is based on pupils’ cognitive conditions, called set-befores, and the pupils' previous experiences, called met-befores. The second starting point is the pragmatic mindset that focuses on the language game – how pupils learn during meetings between pupils and between pupils and teachers. The survey was conducted by using structured observations of pupils' statistical problem solving and the discourse that went on in the classroom. The one teacher and the teacher's pupils were observed during six sessions with small groups of Year 7 pupils, who in turn were part of two larger groups.

    The result showed that pupils were able to identify, understand and interpret statistical data by seeing patterns, similarities and differences. The participants' learning was affected by the language they used. Pupils were able to recreate images using reflective thought experiments during the meetings. The discussions helped the participants to get started with their thoughts and to give those thoughts some structure in developing and understanding the relationships between different diagrams. The teacher and the group helped the pupils to learn to interpret data while working. It made it easier if pupils to used the correct words when pupils had to argue. Proper use of words from the statistical register, when pupils worked with measures of center, also helped the pupils to develop cognitively. The pupils who could use the statistical register also became easier understood and respected by the group.

  • 137.
    Ghilagaber, Gebrenegus
    Uppsala University, Sweden.
    A competing-risks analysis of the choice between marriage and cohabitation: experience of Swedish men born in 1936-19641995Inngår i: Demography, Economy and Welfare / [ed] Christer Lundh, Lund: Lund University Press , 1995, s. 64-76Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 138.
    Ghilagaber, Gebrenegus
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Environmental recidivism in Sweden: distributional shape and effects of sanctions on duration of compliance2018Inngår i: Quality and quantity, ISSN 0033-5177, E-ISSN 1573-7845, Vol. 52, nr 2, s. 21s. 869-882Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The study examines the association between the size of previous environmental sanction charges and subsequent compliance towards environmental regulations. Data used for the study come from about 9000 Swedish firms fined sometime between January 2002 and December 2012. Probabilities of compliance across various levels of sanctions are estimated using life-table methods and tested for equality using standard nonparametric methods. Association between size of sanction charges and subsequent behaviour is modelled by proportional hazard model for the rate of recidivism as well as by a family of flexible parametric accelerated failure-time models for the duration of compliance. The results show that duration of compliance may be described by a log-normal distribution. Further, it is demonstrated that sanctions charges do have significant detering effects on the risk of recidivism though the strength of the detering effect depends on whether or not we account for other possible correlates of recidivism. Possible explanations of the results and their policy implications are discussed; limitations of the current study highlighted; and potential extensions for future studies outlined. 

  • 139.
    Ghilagaber, Gebrenegus
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Statistical Analysis of Educational and Urban-Rural Differences in Marriage-timing: Evidence from the 2010 Eritrean Population and Health Survey for Women and Men2018Inngår i: Proceedings of the International Conference on Eritrean Studies, 20-22 July 2016 / [ed] Zemenfes Tsighe, Saleh Mahmud Idris, Yonas Mesfun Asfaha, Senai Woldeab Andemariam, Rediet Kifle Taddese, Ghebrebrhan Ogubazghi, Asmara: National Higher Education and Research Institute , 2018, 2, s. 1097-1124Kapittel i bok, del av antologi (Fagfellevurdert)
  • 140.
    Ghilagaber, Gebrenegus
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Hedlin, Dan
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Model-based indirect standardization with in-built standard population: illustration with demographic and health survey data2010Inngår i: Official statistics : methodology and applications in honour of Daniel Thorburn / [ed] Michael Carlson, Hans Nyquist, Mattias Villani, Stockholm: Department of Statistics, Stockholm University , 2010, s. 179-191Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 141.
    Ghilagaber, Gebrenegus
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Larsson, Rolf
    Maximum Likelihood Adjustment of Anticipatory Covariates in the Analysis of Retrospective Data2019Rapport (Annet vitenskapelig)
    Abstract [en]

    A multiplicative hazard model in the presence of anticipatory covariates is estimated by maximum likelihood. The case study concerns the e§ects of educational level on risks of divorce. For individuals with anticipatory educational levels, conditional probabilities of having attained the reported level before marriage are used as weights in the likelihood. The adjusted estimates of relative risks do not di§er signiÖcantly from those from anticipatory analysis.

  • 142.
    Ghilagaber, Gebrenegus
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Munezero, Parfait
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Bayesian Change-point Modelling of the Effects of 3-points-for-a-win Rule in Football2018Rapport (Annet vitenskapelig)
    Abstract [en]

    We examine the e⁄ects of the 3-point-for-a-win (3pfaw) rule in the football (soccer) world. Data on mean goals and proportions of decided matches from seven leagues around the world form the basis of our analyses. Bayesian change-point analysis shows that the rule had no e⁄ects on the mean goals in any of the leagues but, indeed, had increasing e⁄ects on the proportions of decided matches in most of the leagues studied. This, in turn, implies that while the rule has given teams the incentive to aim at winning matches, such aim was achieved not by scoring excess goals. Instead, it was achieved by scoring enough goals in order to win and, at the same, defending enough in order not to lose.

  • 143.
    Ghilagaber, Gebrenegus
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Munezero, Parfait
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Bayesian Change-point Modelling of the Effects of 3-points-for-a-win Rule in Football2020Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 47, nr 2, s. 248-264, artikkel-id 10.1080/02664763.2019.1635572Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We examine the effects of the 3-points-for-a-win (3pfaw) rule in the football world. Data that form the basis of our analyses come from seven leagues around the world (Albania, Brazil, England, Germany, Poland, Romania, and Scotland) and consist of mean goals and proportions of decided matches over a period of about six years before- and about seven years after the introduction of the rule in the respective leagues. Bayesian change-point analyses and Shiryaev-Roberts tests show that the rule had no effects on the mean goals but, indeed, had increasing effects on the proportions of decided matches in most of the leagues studied. This, in turn, implies that while the rule has given teams the incentive to aim at winning matches, such aim was not achieved by scoring excess goals. Instead, it was achieved by scoring enough goals in order to win and, at the same time, defending enough in order not to lose. Our results are in accordance with recent findings on comparing the values of attack and defense - that, in top-level football, not conceding a goal is more valuable than scoring a single goal.

  • 144.
    Ghilagaber, Gebrenegus
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Peristera, Paraskevi
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Sequential probit modelling of family and community effects on educational progress among children to Polish and Turkish immigrants in Sweden2014Inngår i: Quality and quantity, ISSN 0033-5177, E-ISSN 1573-7845, Vol. 48, nr 6, s. 3243-3253Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We explore effects of individual, family, and neighborhood effects on educational progress. The statistical model used is a multilevel sequential probit model. Such formulation allows the covariate-effects to vary across different educational levels. Results based on about 2,100 children whose parents are either native Swedes or migrants from Poland or Turkey provide new insights with regard to differentials in educational progress across background varaiables. Among others, we find that parental education is a strong predictor of educational progress at all levels. On the other hand, while family structure, family economy, and ethinic background are strongly correlated to educational progress at lower levels, their effect diminishes at higher levels of education. Possible exaplanations and implications of the results are presented.

  • 145.
    Ghilagaber, Gebrenegus
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Wänström, Linda
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen. Linköping University, Sweden.
    Adjusting for selection bias in assessing the relationship between sibship size and cognitive performance2015Inngår i: Journal of the Royal Statistical Society: Series A (Statistics in Society), ISSN 0964-1998, E-ISSN 1467-985X, Vol. 178, nr 4, s. 22s. 925-944Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Consistent negative correlations between sibship size and cognitive performance (as measured by IQ and other mental aptitude tests) have been observed in past empirical studies. However, the issue of potential selection process in the decision to have larger families (largersibship size) has been partly neglected in past single- and multilevel investigations. The present work extends existing knowledge in three aspects: (1) as factors affecting decision to increase family size may vary across the number and composition of current family size, we propose a sequential probit model (as opposed to binary or ordered models) for the propensity to increase sibship size; (2) we investigate if families who choose to increase family size are a representative random sample of the population of families or there exists selection; (3) in order to disentangle selection and causality we propose a multilevel multiprocess modelling where a continuous model for performance is estimated jointly with a sequential probit model for family-size decisions. The issues are illustrated through analyses of scores on PIAT tests among children of the NLSY79. We found substiantial between-family heterogeneity in the propensity to increase family size - thereby providing empirical evidence in support of the admixture hypothesis. Ignoring such adverse selection led to overestimation of the negative effects of sibship size on cognitive performance but our multiprocess modelling could mitigate the biasing effects of selection.

  • 146. Ghosh, Subir
    et al.
    Nyquist, Hans
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Model fitting and optimal design for a class of binary response models2016Inngår i: Journal of Statistical Planning and Inference, ISSN 0378-3758, E-ISSN 1873-1171, Vol. 179, s. 22-35Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A class of binary response models is considered for describing the data on a response variable having two possible outcomes and q explanatory variables when the odds ratios on the response are a linear function of the explanatory variables. The models provide the closed form solutions of the maximum likelihood estimating equations for the parameter estimation under a Bernoulli setup. A data example is presented to demonstrate the better goodness of fit of a model within this class in comparison with the logit, probit, and complimentary log log models. The design conditions are given and locally optimal designs are presented for some special cases under the D-, A-, and E-, optimality criterion functions. Two designs, one efficient for identifying one model and other efficient for identifying another model, are then compared for their discrimination abilities between two models even before the data collection.

  • 147. Giordani, Paolo
    et al.
    Villani, Mattias
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Statistiska institutionen.
    Forecasting macroeconomic time series with locally adaptive signal extraction2010Inngår i: International Journal of Forecasting, ISSN 0169-2070, E-ISSN 1872-8200, Vol. 26, nr 2, s. 312-325Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We introduce a non-Gaussian dynamic mixture model for macroeconomic forecasting. The locally adaptive signal extraction and regression (LASER) model is designed to capture relatively persistent AR processes (signal) which are contaminated by high frequency noise. The distributions of the innovations in both noise and signal are modeled robustly using mixtures of normals. The mean of the process and the variances of the signal and noise are allowed to shift either suddenly or gradually at unknown locations and unknown numbers of times. The model is then capable of capturing movements in the mean and conditional variance of a series, as well as in the signal-to-noise ratio. Four versions of the model are estimated by Bayesian methods and used to forecast a total of nine quarterly macroeconomic series from the US, Sweden and Australia. We observe that allowing for infrequent and large parameter shifts while imposing normal and homoskedastic errors often leads to erratic forecasts, but that the model typically forecasts well if it is made more robust by allowing for non-normal errors and time varying variances. Our main finding is that, for the nine series we analyze, specifications with infrequent and large shifts in error variances outperform both fixed parameter specifications and smooth, continuous shifts when it comes to interval coverage.

  • 148.
    Granath, Fredrik
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    In vivo dose, dose-response and cancer risk assessment1998Doktoravhandling, med artikler (Annet vitenskapelig)
  • 149.
    Grünewald, Maria
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Design and analysis of response selective samples in observational studies2011Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Outcome dependent sampling may increase efficiency in observational studies. It is however not always obvious how to sample efficiently, and how to analyze the resulting data without introducing bias. This thesis describes a general framework for efficiency calculations in multistage sampling, with focus on what is sometimes referred to as ascertainment sampling. A method for correcting for the sampling scheme in analysis of ascertainment samples is also presented. Simulation based methods are used to overcome computational issues in both efficiency calculations and analysis of data.

  • 150.
    Grünewald, Maria
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Humphreys, Keith
    A Stochastic EM type algorithm for estimation in data with ascertainment on continuous outcomes2008Rapport (Annet vitenskapelig)
    Abstract [en]

    Outcome dependent sampling probabilities can be used to increase efficiency in observational studies. For continuous outcomes appropriate consideration of sampling design in estimating parameters of interest is often computationally cumbersome. In this article we suggest a Stochastic EM type algorithm for estimation. The computational complexity of the likelihood is avoided by filling in missing data so that the full data likelihood can be used. The method is not restricted to any specific distribution of the data and can be used for a broad range of statistical models.

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