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  • 151.
    Jansson, Ingegerd
    et al.
    Statistiska centralbyrån, Statistics Sweden.
    Bernström, Fredrik
    Statistiska centralbyrån, Statistics Sweden.
    Carlson, Michael
    Stockholm University, Faculty of Social Sciences, Department of Statistics. Statistiska centralbyrån, Statistics Sweden.
    The Process of Practicing Statistical Disclosure Control in Tabular Data at Statistics Sweden2010In: Q2010 European Conference on Quality in Official Statistics, Helsinki, Finland, 3-6 May 2010, 2010Conference paper (Other academic)
    Abstract [en]

    It follows from Swedish legislation that Statistics Sweden, when publishing statistical data, must first assess the risk of disclosing confidential information, and then assess the risk that disclosure will result in any harm or damage. In case of considerable risk of the latter, data should be properly protected. We are attempting to handle this by a simple process describing how disclosure control should be applied within Statistics Sweden. Following the general process orientation of statistics production within Statistics Sweden, the process of statistical disclosure control (SDC) in tables must fit within the general production process, and the recommended methods and tools used should as much as possible be shared by all statistical products. We will describe the process for SDC in tables, the contents of a handbook where the process and appropriate methods are described, and the ongoing work with IT-solutions. Presently, work is concentrated on making it possible to run τ-Argus from SAS. Plans for implementation and training will also be briefly described.

  • 152.
    Japec, Lilli
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Interviewer Burden and Its Effects on Data Quality in the Swedish Part of the European Social SurveyManuscript (Other academic)
  • 153.
    Japec, Lilli
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Methodological Research in Interview Surveys: Some Implications and Research NeedsManuscript (Other academic)
  • 154.
    Japec, Lilli
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Quality Issues in Interview Surveys: Some Contributions2005Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In Paper I, I give a brief overview of the “state of the art” in methodological research related to interview surveys and I discuss some implications for survey practices. I study the literature on participation strategies, interviewer effects that can occur during the interview, methods for quality assurance and interviewer training. Methods that are used to study quality aspects of interview surveys are also described. The discussion highlights areas where more research is needed.

    Paper II deals with the interview process and the concept of interviewer burden. Interviewer errors have been described in the survey methodology literature. This literature, however, has not to a great extent addressed the question of why interviewer errors occur or why interviewers behave the way they do. In this paper these issues are addressed. I model the interview process, address interviewers’ cognitive processes, define the concept of interviewer burden and discuss its effects. Data from two interviewer surveys are used to illustrate aspects of interviewer burden.

    In Paper III I explore some components of interviewer burden further. I use data from the Swedish part of the European Social Survey (ESS) to study the effects of interviewer burden and strategies on data quality. Multilevel regression analysis is used to model effects due to respondents and to interviewers. From the data analysis I found that interviewer burden, as I define it, affects data quality. For example, interviewers with a heavy burden tend to have lower response rates, higher refusal and noncontact rates, and shorter interview time.

    In Paper IV we study the effects of the fieldwork on nonresponse bias in the Swedish Labour Force Survey. In the evaluation study we use external data that is available for both respondents and nonrespondents to estimate the nonresponse bias. We apply the generalised regression estimator (GREG) using strong auxiliary information in the estimation procedure. We also carry out the same analysis assuming a simple random sample was drawn and that no auxiliary information is available. Furthermore we study noncontacts and refusals to address the question whether there is a bias caused by either group of nonrespondents. Finally we estimate the cost for the current fieldwork strategy compared with less elaborate strategies.

  • 155.
    Japec, Lilli
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    The Interview Process and the Concept of Interviewer BurdenManuscript (Other academic)
  • 156.
    Japec, Lilli
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Hörngren, Jan
    Effects of Field Efforts on Nonresponse Bias and Costs in the Swedish Labour Force SurveyManuscript (Other academic)
  • 157. Japec, Lilli
    et al.
    Kreuter, Frauke
    Berg, Marcus
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Biemer, Paul
    Decker, Paul
    Lampe, Cliff
    Lane, Julia
    O'Neil, Cathy
    Usher, Abe
    BIG DATA IN SURVEY RESEARCH2015In: Public Opinion Quarterly, ISSN 0033-362X, E-ISSN 1537-5331, Vol. 79, no 4, p. 839-880Article in journal (Refereed)
    Abstract [en]

    Recent years have seen an increase in the amount of statistics describing different phenomena based on Big Data. This term includes data characterized not only by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, and the way in which they are collected and disseminated is fundamental. This change constitutes a paradigm shift for survey research. There is great potential in Big Data, but there are some fundamental challenges that have to be resolved before its full potential can be realized. This report provides examples of different types of Big Data and their potential for survey research; it also describes the Big Data process, discusses its main challenges, and considers solutions and research needs.

  • 158.
    Jutterström, Mats
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Centre for Organizational Research (SCORE). Handelshögskolan i Stockholm, Sverige.
    Segnestam Larsson, Ola
    Stockholm University, Faculty of Social Sciences, Stockholm Centre for Organizational Research (SCORE). Ersta Sköndal Bräcke högskola, Sverige.
    Zetterström, Stina
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Hedlin, Dan
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Anställd i det svenska civilsamhället - engagemang, ansvar och delaktighet2018Report (Other academic)
    Abstract [sv]

    Tack vare tidigare forskning vet vi förhållandevis mycket om hur det är att vara medlem eller frivillig i ideella organisationer i Sverige. Men hur är det att vara anställd i det svenska civilsamhället? Med denna studie vill vi bidra till kunskapen om anställdas arbetsvillkor och drivkrafter i ideella organisationer i Sverige. Områden av intresse inkluderar till exempel vad som kännetecknar organisationer med anställda i det svenska civilsamhället, vilka de anställda är och vad de har för befattningar och villkor samt hur de anställda ser på för- och nackdelar med att arbeta i ideell sektor i jämförelse med privat och offentlig sektor.

  • 159. Kandala, Ngianga-Bakwin
    et al.
    Ghilagaber, Gebrenegus
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    A Geo-additive Bayesian Discrete-time Survival Model: and its Application to Spatial Analysis of Childhood Mortality in Malawi2006In: Quality & Quantity: International Journal of Methodology, Vol. 40, no 6, p. 935-957Article in journal (Refereed)
  • 160. Kandala, Ngianga-Bakwin
    et al.
    Ghilagaber, GebrenegusStockholm University, Faculty of Social Sciences, Department of Statistics.
    Advanced techniques for modelling maternal and child health in Africa2014Collection (editor) (Refereed)
  • 161. Karin, Alexandra
    et al.
    Hannesdottir, Kristin
    Jaeger, Judith
    Annas, Peter
    Segerdahl, Märta
    Karlsson, Pär
    Sjögren, Niclas
    von Rosen, Tatjana
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Miller, Frank
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Psychometric evaluation of ADAS-Cog and NTB for measuring drug response:  2013In: Acta Neurologica Scandinavica, ISSN 0001-6314, E-ISSN 1600-0404, Vol. 129, no 2, p. 113-122Article in journal (Refereed)
    Abstract [en]

    AIMS: To conduct a psychometric analysis to determine the adequacy of instruments that measure cognition in Alzheimer's disease trials.

    BACKGROUND: Both the Alzheimer's Disease Assessment Scale - Cognition (ADAS-Cog) and the Neuropsychological Test Battery (NTB) are validated outcome measures for clinical trials in Alzheimer's disease and are approved also for regulatory purposes. However, it is not clear how comparable they are in measuring cognitive function. In fact, many recent trials in Alzheimer's disease patients have failed and it has been questioned if ADAS-Cog still is a sensitive measure.

    MATERIALS AND METHODS: The present paper examines the psychometric properties of ADAS-Cog and NTB, based on a post hoc analysis of data from a clinical trial (NCT01024660), which was conducted by AstraZeneca, in mild-to-moderate Alzheimer's disease (AD) patients, with a Mini Mental State Examination (MMSE) Total score 16-24. Acceptability, reliability, different types of validity and ability to detect change were assessed using relevant statistical methods. Total scores of both tests, as well as separate domains of both tests, including the Wechsler Memory Scale (WMS), Rey Auditory Verbal Learning Test (RAVLT) and Delis-Kaplan Executive Function System (D-KEFS) Verbal Fluency Condition, were analyzed.

    RESULTS: Overall, NTB performed well, with acceptable reliability and ability to detect change, while ADAS-Cog had insufficient psychometric properties, including ceiling effects in 8 out of a total of 11 ADAS-Cog items in mild AD patients, as well as low test-retest reliability in some of the items.

    DISCUSSION: Based on a direct comparison on the same patient sample, we see advantages of the NTB compared with the ADAS-Cog for the evaluation of cognitive function in the population of mild-to-moderate AD patients. The results suggest that not all of ADAS-Cog items are relevant for both mild and moderate AD population.

    CONCLUSIONS: This validation study demonstrates satisfactory psychometric properties of the NTB, while ADAS-Cog was found to be psychometrically inadequate.

  • 162.
    Karlberg, Martin
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Triad count estimation and transitivity testing in graphs and digraphs1997Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Triads and transitivity are two concepts within the field of social network analysis that are closely related to each other. We study some estimation and testing problems related to those concepts, using the tools of graph theory; the results obtained could be applied to graphs representing other kinds of data than social relations. Throughout this thesis, we focus on the role of local networks. A local network for an individual in a friendship network may be regarded as the network between the friends of this person. Two local network attributes that we pay special attention to are the size and the density. The local size of a vertex is defined so that it counts the number of transitive relationships in which that vertex is involved; this definition is not undisputable in the digraph situation, since not all edges in the local network are counted using that definition. We define the local density of a vertex in such a way, that its expected value is equal to the expected overall density of the network under some commonly used simple random graph and random digraph models. When dealing with triad count estimation, we consider the situation when we have observed information about a probability sample of vertices in a graph or digraph; we let the amount of information observed for each vertex range from the vertex degree to the entire local network of that vertex. Horvitz-Thompson estimators (and variance estimators for those estimators) for the triad counts are given. A main result is that when local networks without information on the identities of the vertices in that network are observed, the triad counts may be expressed as sums of vertex attributes; this greatly facilitates the estimation based on vertex sampling designs more complex than simple random sampling. Transitivity testing is considered for graphs and digraphs that are observed in their entirety. We study two different kinds of transitivity tests; tests based on the counts of transitive and intransitive triads and triples, and tests based on the mean local density over all vertices. The null hypothesis used is that the graphs and digraphs observed have been generated according to some conditional uniform random graph model that does not imply a high degree of transitivity. The powers of the tests against random graph distributions that generate highly transitive graphs are examined in simulation studies. In other simulation studies, the tests are applied to a large set of school class sociograms. When (undirected) graphs are considered, the test based on the proportion of transitive triads out of the non-vacuously transitive ones is found to be best at detecting transitivity; for digraphs, the test based on the difference between the mean local density and the overall network density is the best transitivity detector.

  • 163. Khatab, Khaled
    et al.
    Felten, Michael K.
    Kandala, Nagianga B.
    Ghilagaber, Gebrenegus
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Gumber, Anil
    Kraus, Thomas
    Risk Factors Associated with Asbestos-related Diseases: Results of the Asbestos Surveillance Programme Aachen2014In: European medical journal. Respiratory, ISSN 2054-3166, p. 1-9Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to examine the association between workplace exposure to asbestos and risk factors for developing related chronic respiratory diseases, using the analysis of a cohort of 8,582 formerly asbestos-exposed workers, as well as to assess the grade value of three risk categories used for a focused surveillance procedure. The results showed that the participants who were aged over 65 (OR and 95% CI: 11.47 [5.48-23.99]) and active smokers (OR and 95% CI: 9.48 [4.07-22.09]), were at a significantly high risk for developing lung cancer. The risk of developing benign lesions of the lung or pleura (BLLP) was almost 6-times higher (OR and 95% CI: 5.76 [4.7-7]) for the age group over 65. The risk of developing mesothelioma was influenced by exposure duration (OR and 95% CI: 4.36 [1-19.01]); and for the age group over 65 (OR and 95% CI: 4.58 [1.86-11.27]). The study has demonstrated that the use of risk categories based on a combination of risk factors (age, smoking status, and duration of exposure) could be advantageous for planning the target health surveillance programmes.

  • 164.
    Kollo, Tõnu
    et al.
    University of Tartu, Institute of mathematical statistics.
    von Rosen, Tatjana
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Dietrich
    The Department of Energy and Technology, SLU, Sweden.
    Estimation in high-dimensional analysis and multivariate linear models2008Report (Other academic)
    Abstract [en]

    When the number of variables compared with the number of observationsis large this paper presents a new approach of estimating the parametersdescribing the mean structure in the Growth Curve model. An explicitestimator is obtained which is unbiased, consistent and asymptoticallynormally distributed. Its variance is also derived.

  • 165. Kollo, Tõnu
    et al.
    von Rosen, Tatjana
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Dietrich
    Estimation in high-dimensional analysis and multivariate linear models2011In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 40, no 7, p. 1241-1253Article in journal (Refereed)
    Abstract [en]

    This article presents a new approach of estimating the parameters describing the mean structure in the Growth Curve model when the number of variables compared with the number of observations is large.

  • 166.
    Koskinen, Johan
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Bayesian Analysis of Exponential Random Graphs: Estimation of Parameters and Model SelectionManuscript (Other academic)
  • 167.
    Koskinen, Johan
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Bayesian Inference for Longitudinal Social NetworksManuscript (Other academic)
  • 168.
    Koskinen, Johan
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Essays on Bayesian Inference for Social Networks2004Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time.

    A social network is conceived as being a structure consisting of actors and their social interaction with each other. A common conceptualisation of social networks is to let the actors be represented by nodes in a graph with edges between pairs of nodes that are relationally tied to each other according to some definition. Statistical analysis of social networks is to a large extent concerned with modelling of these relational ties, which lends itself to empirical evaluation.

    The first paper deals with a family of statistical models for social networks called exponential random graphs that takes various structural features of the network into account. In general, the likelihood functions of exponential random graphs are only known up to a constant of proportionality. A procedure for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods is presented. The algorithm consists of two basic steps, one in which an ordinary Metropolis-Hastings up-dating step is used, and another in which an importance sampling scheme is used to calculate the acceptance probability of the Metropolis-Hastings step.

    In paper number two a method for modelling reports given by actors (or other informants) on their social interaction with others is investigated in a Bayesian framework. The model contains two basic ingredients: the unknown network structure and functions that link this unknown network structure to the reports given by the actors. These functions take the form of probit link functions. An intrinsic problem is that the model is not identified, meaning that there are combinations of values on the unknown structure and the parameters in the probit link functions that are observationally equivalent. Instead of using restrictions for achieving identification, it is proposed that the different observationally equivalent combinations of parameters and unknown structure be investigated a posteriori. Estimation of parameters is carried out using Gibbs sampling with a switching devise that enables transitions between posterior modal regions. The main goal of the procedures is to provide tools for comparisons of different model specifications.

    Papers 3 and 4, propose Bayesian methods for longitudinal social networks. The premise of the models investigated is that overall change in social networks occurs as a consequence of sequences of incremental changes. Models for the evolution of social networks using continuos-time Markov chains are meant to capture these dynamics. Paper 3 presents an MCMC algorithm for exploring the posteriors of parameters for such Markov chains. More specifically, the unobserved evolution of the network in-between observations is explicitly modelled thereby avoiding the need to deal with explicit formulas for the transition probabilities. This enables likelihood based parameter inference in a wider class of network evolution models than has been available before. Paper 4 builds on the proposed inference procedure of Paper 3 and demonstrates how to perform model selection for a class of network evolution models.

  • 169.
    Koskinen, Johan
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Model selection for Cognitive Social StructuresManuscript (Other academic)
  • 170.
    Koskinen, Johan
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Model Selection for Longitudinal Social NetworksManuscript (Other academic)
  • 171.
    Kum, Cletus Kwa
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Bayesian Analysis of Two Malaria Treatments and Probability Modelling of Malaria Parasite Genotypes2009Licentiate thesis, monograph (Other academic)
  • 172.
    Kum, Cletus Kwa
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Bayesian Analysis of Two Malaria Treatments and Probability Modelling of Malaria Parasite Gentypes2009Licentiate thesis, comprehensive summary (Other academic)
  • 173. Kum, Cletus Kwa
    et al.
    Thorburn, Daniel
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Ghilagaber, Gebrenegus
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Björkman, Anders
    Gil, José Pedro
    Effects of Some Biological Covariates on the Probability of First Recurrence of Malaria following Treatment with Artemisinin Combination Therapy2018In: International Journal of Statistics in Medical Research, ISSN 1929-6029, Vol. 7, no 1, p. 1-9Article in journal (Refereed)
    Abstract [en]

    Many investigations have shown that artemisinin-based combination therapies are effective in the treatment of uncomplicated malaria and that they do not increase parasite resistance to treatment as much as treatment with single substance. We study the relation between some biological covariates and the time to first recurrence of malaria for children treated for malaria in a clinical trial. One group received artesunate plus sulfadoxine-pyrimethamine and the other only sulfadoxine-pyrimethamine. We consider the event malaria-free for the first 42 (and 84) days. We use logistic regression models for the analyses. The main results show that the probability of no recurrence is higher if the parasite density in the blood is high. The results are inconclusive for other explanatory biological variables. The infecting parasites having genes that indicate resistance, gave different results at the two different treatment centres. There was no appreciable difference in the effects of treatment over the two follow-up periods and these treatments do not have any effect on the probability of a recurrence.

  • 174.
    Kum, Cletus Kwa
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Thorburn, Daniel
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Ghilagaber, Gebrenegus
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Gil, Perdo
    Björkman, Anders
    On the Effects of Malaria Treatment on Parasite Drug Resistance: Probability Modelling of Genotyped Malaria Infections2013In: The International Journal of Biostatistics, ISSN 1557-4679, E-ISSN 1557-4679, Vol. 9, no 1, p. 135-148Article in journal (Refereed)
    Abstract [en]

    We compare the frequency of resistant genes of malaria parasites before treatment and at first malaria incidence after treatment. The data come from a clinical trial at two health facilities in Tanzania and concerns single nucleotide polymorphisms (SNPs) at three positions believed to be related to resistance to malaria treatment. A problem is that mixed infections are common, which both obscures the underlying frequency of alleles at each locus as well as the associations between loci in samples where alleles are mixed. We use combinatorics and quite involved probability methods to handle multiple infections and multiple haplotypes. The infection with the different haplotypes seemed to be independent of each other. We showed that at two of the three studied SNPs, the proportion of resistant genes had increased after treatment with sulfadoxine-pyrimethamine alone but when treated in combination with artesunate, no effect was noticed. First recurrences of malaria associated more with sulfadoxine-pyrimethamine alone as treatment than when in combination with artesunate. We also found that the recruited children had two different ongoing malaria infections where the parasites had different gene types.

  • 175.
    Kum, Cletus Kwa
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Thorburn, Daniel
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Ghilagaber, Gebrenegus
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Pedro, Gil
    Björkman, Anders
    A Nonparametric Bayesian Approach to Estimating Malaria Prophylactic Effect After Two Treatments2013In: International Journal of Statistics in Medical Research, ISSN 1929-6029, Vol. 2, no 2, p. 76-87Article in journal (Refereed)
    Abstract [en]

    Two treatment regimens for malaria are compared in their abilities to cure and combat reinfection. Bayesian analysis techniques are used to compare two typical treatment therapies for uncomplicated malaria in children under five years, not only in their power to resist recrudescence, but also how long they can postpone recrudescence or reinfection in case of failure. We present a new way of analysing this type of data using Markov Chain Monte Carlo techniques. This is done using data from clinical trials at two different centres. The results which give the full posterior distributions show that artemisinin-based combination therapy is more efficacious than sulfadoxine-pyrimethamine. It both reduced the risk of recrudescence and delayed the time until recrudescence.

  • 176. Labruto, F.
    et al.
    Westerberg, M.
    Magnusson, M.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Deep Venous Thrombosis of the Lower Limb: No Difference in Duration of Symptoms Between Proximal and Distal Disease2011In: Clinical and applied thrombosis/hemostasis, ISSN 1076-0296, E-ISSN 1938-2723, Vol. 17, no 4, p. 393-395Article in journal (Refereed)
    Abstract [en]

    In deep vein thrombosis (DVT) of the lower limb, the location of the thrombosis determines how great the risk of pulmonary embolism is. We set out to determine whether the duration of lower limb DVT symptoms could be a predictive factor for the location of the thrombosis. We retrospectively collected a series of 100 lower limb phlebography examinations that were positive for DVT and divided the group into 2 subgroups proximal disease (ie, above the knee) or distal disease (ie, below the knee). The subgroups were then plotted against the individual duration of the symptoms. Of the 100 DVTs, 58% were proximal, while 42% were distal. The average duration of the symptoms was 6.3 days for patients with proximal disease and 6.2 days for patients with distal disease. We, therefore, found no difference in symptom duration between patients with proximal and distal lower limb DVT. This may imply that the duration of the DVT symptoms does not represent a predictive factor for DVT-caused pulmonary embolism.

  • 177.
    Li, Feng
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Bayesian Modeling of Conditional Densities2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis develops models and associated Bayesian inference methods for flexible univariate and multivariate conditional density estimation. The models are flexible in the sense that they can capture widely differing shapes of the data. The estimation methods are specifically designed to achieve flexibility while still avoiding overfitting. The models are flexible both for a given covariate value, but also across covariate space. A key contribution of this thesis is that it provides general approaches of density estimation with highly efficient Markov chain Monte Carlo methods. The methods are illustrated on several challenging non-linear and non-normal datasets.

    In the first paper, a general model is proposed for flexibly estimating the density of a continuous response variable conditional on a possibly high-dimensional set of covariates. The model is a finite mixture of asymmetric student-t densities with covariate-dependent mixture weights. The four parameters of the components, the mean, degrees of freedom, scale and skewness, are all modeled as functions of the covariates. The second paper explores how well a smooth mixture of symmetric components can capture skewed data. Simulations and applications on real data show that including covariate-dependent skewness in the components can lead to substantially improved performance on skewed data, often using a much smaller number of components. We also introduce smooth mixtures of gamma and log-normal components to model positively-valued response variables. In the third paper we propose a multivariate Gaussian surface regression model that combines both additive splines and interactive splines, and a highly efficient MCMC algorithm that updates all the multi-dimensional knot locations jointly. We use shrinkage priors to avoid overfitting with different estimated shrinkage factors for the additive and surface part of the model, and also different shrinkage parameters for the different response variables. In the last paper we present a general Bayesian approach for directly modeling dependencies between variables as function of explanatory variables in a flexible copula context. In particular, the Joe-Clayton copula is extended to have covariate-dependent tail dependence and correlations. Posterior inference is carried out using a novel and efficient simulation method. The appendix of the thesis documents the computational implementation details.

  • 178.
    Li, Feng
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Modeling Covariate-Contingent Correlation  and Tail-Dependence with CopulasManuscript (preprint) (Other academic)
    Abstract [en]

    Copula functions give an approach of constructing multivariate densities with  flexible combinations of distinct marginal distributions and also measures  degrees of dependence in the tail and correlations of the marginal  distributions via a novel strategy. Nevertheless common approaches of  estimating tail dependence and correlations are through nuisance parameters  which yields the final results neither tractable nor interpretable for  practitioners. In this paper we address the problem by presenting a general  Bayesian approach for directly modeling covariate-linked tail dependence and  correlations. Posterior inference is carried out using a novel and efficient  simulation method.

  • 179.
    Li, Feng
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Villani, Mattias
    Efficient Bayesian Multivariate Surface Regression2013In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 40, no 4, p. 706-723Article in journal (Refereed)
    Abstract [en]

    Methods for choosing a fixed set of knot locations in additive spline models are fairly well established in the statistical literature. While most of these methods are in principle directly extendable to non-additive surface models, they are likely to be less successful in that setting because of the curse of dimensionality, especially when there are more than a couple of covariates. We propose a regression model for a multivariate Gaussian response that combines both additive splines and interactive splines, and a highly efficient MCMC algorithm that updates all the multivariate knot locations jointly. We use shrinkage priors to avoid overfitting with different estimated shrinkage factors for the additive and surface part of the model, and also different shrinkage parameters for the different response variables. This makes it possible for the model to adapt to varying degrees of nonlinearity in different parts of the data in a parsimonious way. Simulated data and an application to firm leverage data show that the approach is computationally efficient, and that allowing for freely estimated knot locations can offer a substantial improvement in out-of-sample predictive performance.

  • 180.
    Li, Feng
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Villani, Mattias
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Kohn, Robert
    Flexible Modeling of Conditional Distributions using Smooth Mixtures of Asymmetric Student T Densities2010In: Journal of Statistical Planning and Inference, ISSN 0378-3758, E-ISSN 1873-1171, Vol. 140, no 12, p. 3638-3654Article in journal (Refereed)
    Abstract [en]

    A general model is proposed for flexibly estimating the density of a continuous response variableconditional on a possibly high-dimensional set of covariates. The model is a finite mixture ofasymmetric student-t densities with covariate-dependent mixture weights. The four parameters ofthe components, the mean, degrees of freedom, scale and skewness, are all modeled as functionsof the covariates. Inference is Bayesian and the computation is carried out using Markov chainMonte Carlo simulation. To enable model parsimony, a variable selection prior is used in each setof covariates and among the covariates in the mixing weights. The model is used to analyze thedistribution of daily stock market returns, and shown to more accurately forecast the distributionof returns than other widely used models for financial data.

  • 181.
    Li, Feng
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Villani, Mattias
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Kohn, Robert
    Modeling Conditional Densities using Finite Smooth Mixtures2011In: Mixtures: Estimation and Applications / [ed] Kerrie L. Mengersen, Christian P. Robert, D. Michael Titterington, Chichester: John Wiley & Sons, 2011, , p. 20p. 123-144Chapter in book (Refereed)
    Abstract [en]

    Smooth mixtures, i.e. mixture models with covariate-dependent mixing weights,are very useful flexible models for conditional densities. Previous work shows that using toosimple mixture components for modeling heteroscedastic and/or heavy tailed data can givea poor fit, even with a large number of components. This paper explores how well a smoothmixture of symmetric components can capture skewed data. Simulations and applications onreal data show that including covariate-dependent skewness in the components can lead tosubstantially improved performance on skewed data, often using a much smaller number ofcomponents. Furthermore, variable selection is effective in removing unnecessary covariates inthe skewness, which means that there is little loss in allowing for skewness in the componentswhen the data are actually symmetric. We also introduce smooth mixtures of gamma andlog-normal components to model positively-valued response variables.

  • 182.
    Liang, Yuli
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    A study of multilevel models with block circular  symmetric covariance structures2011Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis concerns the study of multilevel models with specific patterned covariance structures and addresses the issues of maximum likelihoodestimation. In particular, circular symmetric hierarchical datastructures are considered.

    In the first paper (Paper I), we consider so-called dihedral block symmetrymodels and extend them to models which covariance structures reflects both circularity and exchangeability present in the data. The main contribution of Paper I are two derived patterns of the covariancematrices which characterizes models under consideration. The relationship between these two patterned covariance matrices was investigatedand it has been verified they are similar matrices. New expressions for the eigenvalues of block circular symmetric matrices are obtained which take into account the block structure. Paper II deals with estimation ofbalanced multilevel models with block circular symmetric covariance matrices. The spectral properties of such patterned covariance matrices are established. Maximum likelihood estimation is considered through the spectral decomposition of the patterned covariance matrix. The main results of Paper II concern the spectrum of the covariance matrix inthe model of interest and the existence of explicit maximum likelihood estimators for the covariance parameters.

  • 183.
    Liang, Yuli
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously.

    We derive two covariance structures under two different invariance restrictions. The obtained covariance structures reflect both circularity and exchangeability present in the data. In particular, estimation in the balanced random effects with block circular covariance matrices is considered. The spectral properties of such patterned covariance matrices are provided. Maximum likelihood estimation is performed through the spectral decomposition of the patterned covariance matrices. Existence of the explicit maximum likelihood estimators is discussed and sufficient conditions for obtaining explicit and unique estimators for the variance-covariance components are derived. Different restricted models are discussed and the corresponding maximum likelihood estimators are presented.

    This thesis also deals with hypothesis testing of block covariance structures, especially block circular Toeplitz covariance matrices. We consider both so-called external tests and internal tests. In the external tests, various hypotheses about testing block covariance structures, as well as mean structures, are considered, and the internal tests are concerned with testing specific covariance parameters given the block circular Toeplitz structure. Likelihood ratio tests are constructed, and the null distributions of the corresponding test statistics are derived.

  • 184.
    Liang, Yuli
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    På väg att lära sig statistik2014In: Qvintense, ISSN 2000-1819, Vol. 3, p. 6-7Article in journal (Other (popular science, discussion, etc.))
  • 185.
    Liang, Yuli
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Dietrich
    Tatjana, von Rosen
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    On estimation in multilevel models with block circular symmetric covariance structure2012In: Acta et Commentationes Universitatis Tartuensis de Mathematica, ISSN 1406-2283, E-ISSN 2228-4699, Vol. 16, no 1, p. 83-96Article in journal (Refereed)
    Abstract [en]

    In this article we consider a multilevel model with block circular symmetric covariance structure. Maximum likelihood estimation of the parameters of this model is discussed. We show that explicit maximum likelihood estimators of variance components exist under certain restrictions on the parameter space.

  • 186.
    Liang, Yuli
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Dietrich
    von Rosen, Tatjana
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    On estimation in hierarchical models with block circular covariance structures2015In: Annals of the Institute of Statistical Mathematics, ISSN 0020-3157, E-ISSN 1572-9052, Vol. 67, no 4, p. 773-791Article in journal (Refereed)
    Abstract [en]

    Hierarchical linear models with a block circular covariance structure are considered. Sufficient conditions for obtaining explicit and unique estimators for the variance–covariance components are derived. Different restricted models are discussed and maximum likelihood estimators are presented. The theory is illustrated through covariance matrices of small sizes and a real-life example.

  • 187.
    Liang, Yuli
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Dietrich
    von Rosen, Tatjana
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Testing in multivariate normal models with block circular covariance structures2015Report (Other academic)
    Abstract [en]

    In this article, the results concerning hypothesis testing in multivariate normal models with block circular covariance structures are obtained. Hypotheses about a general block structure of the covariance matrix and specific covariance parameters have been of main interest. In addition, the tests about patterned mean vectors have been considered.The corresponding likelihood ratio statistics are derived and their null distributions are studied.

  • 188.
    Liang, Yuli
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Tatjana
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Dietrich
    Block Circular Symmetry in Multilevel Models2011Report (Other academic)
    Abstract [en]

    Models that describe symmetries present in the error structure of observations have been widely used in dierent applications, with early examples from psychometric and medical research. The aim of this article is to study a multilevel model with a covariance structure that is block circular symmetric. Useful results are obtained for the spectra of these structured matrices.

  • 189.
    Liang, Yuli
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Tatjana
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    von Rosen, Dietrich
    The Department of Energy and Technology, SLU.
    Estimation in multilevel models with block circular symmetric covariance structure2011Report (Other academic)
    Abstract [en]

    In this article we consider a multilevel model with block circular symmetric covariance structure. Maximum likelihood estimation of the parameters of this model is discussed. We show that explicit maximum likelihood estimators of variance components exist under certain restrictions on the parameter space.

  • 190.
    Lindberg, Mattias
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Guban, Peter
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Auxiliary variables a weight against nonresponse bias: A simulation study2014Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Today’s surveys face a growing problem with increasing nonresponse.  The increase in nonresponse rate causes a need for better and more effective ways to reduce the nonresponse bias.  There are three major scientific orientation of today’s research dealing with nonresponse. One is examining the social factors, the second one studies different data collection methods and the third investigating the use of weights to adjust estimators for nonresponse.  We would like to contribute to the third orientation by evaluating estimators which use and adjust weights based on auxiliary variables to balance the survey nonresponse through simulations. For the simulation we use an artificial population consisting of 35455 participants from the Representativity Indicators for Survey Quality project. We model three nonresponse mechanisms (MCAR, MAR and MNAR) with three different coefficient of determination s between our study variable and the auxiliary variables and under three response rates resulting in 63 simulation scenarios. The scenarios are replicated 1000 times to acquire the results. We outline our findings and results for each estimator in all scenarios with the help of bias measures.

  • 191.
    Lorenc, Boris
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Model-Based Estimation with Double SamplesManuscript (Other academic)
  • 192.
    Lorenc, Boris
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Propensity Score Weighting Using Double SamplesManuscript (Other academic)
  • 193.
    Lorenc, Boris
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Social Distribution of the Response Process in a Survey of SchoolsManuscript (Other academic)
  • 194.
    Lorenc, Boris
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Survey Response Process in Establishments: The Socially Distributed Cognition PerspectiveManuscript (Other academic)
  • 195.
    Lorenc, Boris
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Two Topics in Survey Methodology: Inference from Nonprobability Samples Using the Double Samples Setup2006Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Modelling the response process in establishment surveys proceeded thus far by adding steps of operational character to the core cognitive steps of the individual cognitive model. Here (Paper 1) a larger unit of the cognitive analysis is posited: that part of the enterprise that is engaged in responding to a survey, consisting of one or more employees, the tools they use and the established practices of record keeping and survey responding. Propagation of representational states is the key concept used for analysing the response process. A pilot study conducted on a survey of schools (Paper 2) illustrates the ability of the approach to identify and suggest adjustment of items of questionable accuracy and addresses the possibility of quantifying accuracy of collected data.

    In order to assess the skewness of a nonprobability web sample in relation to the targeted population, George Terhanian proposed a parallel availability of a probability sample from the population and the use of the assessment to reweight data in the nonprobability sample. The parallel availability of the two samples constitutes the double samples setup.

    Propensity scores have been suggested as a way of adjusting web samples. Here (Paper 3) the propensity score approach is broadened by (i) putting it in a wider context of the double samples setup applicable in other fields as well, (ii) showing the theoretical unbiasedness of the estimator and (iii) specifying the assumptions that need to hold. In a simulation, the effects of the factors where an analytic approach was difficult or impossible to apply were investigated. The paper also contains a simple example of applying the technique, with a step-by-step "how to".

    Inference in the double samples setup proceeded thus far by modelling either the probabilities of inclusion in the nonprobability sample or the study variable. A more general framework is presented (Paper 4) that models both components at the same time. From the model an estimator is derived. In a simulation, it is compared with three estimators that model just one of the two components.

    Finally, a nonparametric estimator for the situation of double samples is presented (Paper 5). Here, the values of the study variable---missing by design in the probability sample---are imputed according to a distance measure on auxiliary information. The mean of a number of closest units is imputed with the aim of reducing the variance of the estimator. For the case of univariate auxiliary information treated in the study, an expression for the variance and a variance estimator for this estimator is also presented and verified in a simulation.

  • 196.
    Lundquist, Peter
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Estimating Interviewer Effects in Sample Surveys: Some Contributions2006Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis focuses on measurement errors that could be ascribed to the interviewers. To study interviewer variability a measurement error model is formulated which makes a clear distinction between three sources of randomness: the sample selection, interviewer assignment, and interviewing.

    In the first paper the variance of the observed sample mean is derived, and it is seen how this variance depends on parameters of the measurement error model and on the number of interviewers. An estimator of the interviewer variance, which is seen to be unbiased, and a biased intra-interviewer correlation estimator are suggested. In a simulation study it is seen that the simulation variance of the interviewer variance estimator increases for both high and low interviewer assignments and seems to have a minimum somewhere in between.

    The second paper presents an expression of the variance of the observed sample mean under stratified random sampling. Two possible estimators of the variance of the mean are considered, one of which has a slight positive bias, the other a negative bias, which can be large. Two different estimators of the interviewer variance are studied. Only one of them makes it possible to find a reasonable estimate of the intra-interviewer correlation.

    In the third paper an expression for the variance of the interviewer variance estimator is derived. This result may prove useful in designing future studies of interviewer variance. For a large population it will be possible to use an approximate variance, irrespective of the underlying distribution of the unknown true values.

    The fourth paper deals with some issues in planning and analyzing an interviewer variance study. Three problems are considered: (i) Determining the number of interviewers and the appropriate size of the interviewer assignments; (ii) Finding the probability of negative estimates of the interviewer variance; (iii) Testing for interviewer variance.

  • 197.
    Lundquist, Peter
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Estimating interviewer variance under a measurement error model for continuous survey data: Stratified samplingManuscript (Other academic)
  • 198.
    Lundquist, Peter
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Issues in designing an interviewer variance study under an error model for continuous dataManuscript (Other academic)
  • 199.
    Lundquist, Peter
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    The variance of the interviewer variance estimator under an error model for continuous dataManuscript (Other academic)
  • 200.
    Lundquist, Peter
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Wretman, Jan
    Estimating interviewer variance under a measurement error model for continuous survey dataManuscript (Other academic)
1234567 151 - 200 of 403
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