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  • 51.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Statistics. Umeå University, Faculty of Social Sciences, Statistics.
    Bengtsson, Tommy
    Inheritance, Environment, and Mortality in Older Ages, Southern Sweden, 1813-18942008In: Kinship and Demographic Behavior in the Past, 2008, p. 185-201Chapter in book (Refereed)
    Abstract [en]

    This essay explores the role played by the inheritance on human longevity. We estimate a model of overall mortality among married persons aged 50 years and above taking genetic as well as socioeconomic factors into account. We consider whether these factors have temporal or long-lasting effects on health. The demographic and economic individual level data come from the Scanian Demographic Database. These data cover five rural parishes in the southernmost part of Sweden for the period 1813-1894. To these, local grain prices, as an indicator of food costs, and the local infant mortality rate, as an indicator of the disease load, have been added. We find that age of death of the mother and the father have persistent impacts on their adult children's overall mortality regardless of sex, even after controlling for socioeconomic an environmental factors throughout the life course. In addition, we find strong birth cohort effects and effects of the disease load in the first year of life on male offspring. We are, however, unable to find any effects of socioeconomic status, neither at the time of birth or achieved later in life, a result consistent with earlier findings.

  • 52.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Brändström, Anders
    Umeå University, Faculty of Social Sciences, Centre for Population Studies.
    Persson, Lars-Åke
    Umeå University, Faculty of Medicine, Public Health and Clinical Medicine, Epidemiology and Public Health Sciences.
    The impact of feeding patterns on infant mortality in a nineteenth century Swedish parish1984In: Journal of Tropical Pediatrics, ISSN 0142-6338, E-ISSN 1465-3664, Vol. 30, p. 154-159Article in journal (Refereed)
  • 53.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Lundin, Mathias
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Att läsa i Umeå är ett bra val2005In: Västerbottens-Kuriren, no 9 december, p. 4-Article in journal (Other (popular science, discussion, etc.))
  • 54.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Holmberg, Henrik
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Generalized linear models with clustered data: fixed and random effects models2011In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 55, no 12, p. 3123-3134Article in journal (Refereed)
    Abstract [en]

    The statistical analysis of mixed effects models for binary and count data is investigated. In the statistical computing environment R, there are a few packages that estimate models of this kind. The packagelme4 is a de facto standard for mixed effects models. The packageglmmML allows non-normal distributions in the specification of random intercepts. It also allows for the estimation of a fixed effects model, assuming that all cluster intercepts are distinct fixed parameters; moreover, a bootstrapping technique is implemented to replace asymptotic analysis. The random intercepts model is fitted using a maximum likelihood estimator with adaptive Gauss–Hermite and Laplace quadrature approximations of the likelihood function. The fixed effects model is fitted through a profiling approach, which is necessary when the number of clusters is large. In a simulation study, the two approaches are compared. The fixed effects model has severe bias when the mixed effects variance is positive and the number of clusters is large.

  • 55.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Johansson, Per
    Palme, Mårten
    Economic incentives and gender differences in work absence behavior2004In: Swedish Economic Policy Review, Vol. 11, p. 33-63Article in journal (Refereed)
  • 56.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Lindkvist, Marie
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Partial Partial Likelihood2008In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 37, no 4, p. 679-686Article in journal (Refereed)
    Abstract [en]

    The maximum likelihood and maximum partial likelihood approaches to the proportional hazards model are unified. The purpose is to give a general approach to the analysis of the proportional hazards model, whether the baseline distribution is absolutely continuous, discrete, or a mixture. The advantage is that heavily tied data will be analyzed with a discrete time model, while data with no ties is analyzed with ordinary Cox regression. Data sets in between are treated by a compromise between the discrete time model and Efron's approach to tied data in survival analysis, and the transitions between modes are automatic. A simulation study is conducted comparing the proposed approach to standard methods of handling ties. A recent suggestion, that revives Breslow's approach to tied data, is finally discussed.

  • 57.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Nilsson, Lennart
    Umeå University, Faculty of Science and Technology, Mathematical statistics.
    Acceptance-rejection sampling from the conditional distribution of independent discrete random variables, given their sum2000In: Statistics (Berlin), ISSN 0233-1888, E-ISSN 1029-4910, Vol. 34, p. 247-257Article in journal (Refereed)
  • 58.
    Broström, Göran
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Råde, Lennart
    Further study of R-censoring and the exponential distribution1986Report (Other academic)
  • 59.
    Brunström, Henrik
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Eriksson, Kim
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    När gör hjälpinformation mest nytta-vid urval eller estimering?2011Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
  • 60.
    Bränberg, Kenny
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Kernel equating with covariatesManuscript (preprint) (Other academic)
    Abstract [en]

    To equate two forms of a test we need to collect data in such a way that the link between the scales of the two test froms can be esitmated. The traditional approach is to use common examinees and/or common items. In this paper we explore the idea of using variables correlated with the test scores (e.g., school grades, education) as a substitute for common items in a non-equivalent groups design. This is done in the framework of Kernel Equating, and with an extension of the method developed for post-stratification equating  (PSE) in the non-equivalent groups with anchor test (NEAT) design. Data from two administrations of the data sufficiency subtest of the Swedish Scholastic Assessment Test (SweSAT), fall 1996 (96B) and spring 1997 (97A), are used to illustrate the use of the method. 

  • 61.
    Bränberg, Kenny
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Observed score equating with covariates2010Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In test score equating the focus is on the problem of finding the relationship between the scales of different test forms. This can be done only if data are collected in such a way that the effect of differences in ability between groups taking different test forms can be separated from the effect of differences in test form difficulty. In standard equating procedures this problem has been solved by using common examinees or common items. With common examinees, as in the equivalent groups design, the single group design, and the counterbalanced design, the examinees taking the test forms are either exactly the same, i.e., each examinee takes both test forms, or random samples from the same population. Common items (anchor items) are usually used when the samples taking the different test forms are assumed to come from different populations.

    The thesis consists of four papers and the main theme in three of these papers is the use of covariates, i.e., background variables correlated with the test scores, in observed score equating. We show how covariates can be used to adjust for systematic differences between samples in a non-equivalent groups design when there are no anchor items. We also show how covariates can be used to decrease the equating error in an equivalent groups design or in a non-equivalent groups design.

    The first paper, Paper I, is the only paper where the focus is on something else than the incorporation of covariates in equating. The paper is an introduction to test score equating, and the author's thoughts on the foundation of test score equating. There are a number of different definitions of test score equating in the literature. Some of these definitions are presented and the similarities and differences between them are discussed. An attempt is also made to clarify the connection between the definitions and the most commonly used equating functions.

    In Paper II a model is proposed for observed score linear equating with background variables. The idea presented in the paper is to adjust for systematic differences in ability between groups in a non-equivalent groups design by using information from background variables correlated with the observed test scores. It is assumed that conditional on the background variables the two samples can be seen as random samples from the same population. The background variables are used to explain the systematic differences in ability between the populations. The proposed model consists of a linear regression model connecting the observed scores with the background variables and a linear equating function connecting observed scores on one test forms to observed scores on the other test form. Maximum likelihood estimators of the model parameters are derived, using an assumption of normally distributed test scores, and data from two administrations of the Swedish Scholastic Assessment Test are used to illustrate the use of the model.

    In Paper III we use the model presented in Paper II with two different data collection designs: the non-equivalent groups design (with and without anchor items) and the equivalent groups design. Simulated data are used to examine the effect - in terms of bias, variance and mean squared error - on the estimators, of including covariates. With the equivalent groups design the results show that using covariates can increase the accuracy of the equating. With the non-equivalent groups design the results show that using an anchor test together with covariates is the most efficient way of reducing the mean squared error of the estimators. Furthermore, with no anchor test, the background variables can be used to adjust for the systematic differences between the populations and produce unbiased estimators of the equating relationship, provided that the “right” variables are used, i.e., the variables explaining those differences.

    In Paper IV we explore the idea of using covariates as a substitute for an anchor test with a non-equivalent groups design in the framework of Kernel Equating. Kernel Equating can be seen as a method including five different steps: presmoothing, estimation of score probabilities, continuization, equating, and calculating the standard error of equating. For each of these steps we give the theoretical results when observations on covariates are used as a substitute for scores on an anchor test. It is shown that we can use the method developed for Post-Stratification Equating in the non-equivalent groups with anchor test design, but with observations on the covariates instead of scores on an anchor test. The method is illustrated using data from the Swedish Scholastic Assessment Test.

  • 62.
    Bränberg, Kenny
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Observed score linear equating using background variablesManuscript (preprint) (Other academic)
    Abstract [en]

    To equate two test forms of a test we need to collect data in such a way that the link between the scales of the two test forms can be estimated. The traditional approach is to use common examinees and/or common items (i.e., an anchor test). In this paper we propose a model for observed score linear equating in a non-equivalent groups design, using background variables as a substitute for common items. Maximum likelihood estimators of the equating parameters are derived, and data from two administrations of the Swedeish Scholastic Assessment Test are used to illustrate the use of the model.

  • 63.
    Bränberg, Kenny
    Umeå University, Faculty of Social Sciences, Statistics.
    On Test Score Equating1997Licentiate thesis, monograph (Other academic)
  • 64.
    Bränberg, Kenny
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Some thoughts on the foundations of test score equatingManuscript (preprint) (Other academic)
    Abstract [en]

    Even if there is a general agreement on the basic idea behind test score equating, and also some consensus behind the requirements of test score equating, a number of different definitions can be found in the literature. One purpose of this paper is to present some of these definitions and discuss the similarities and differences between them. Another purpose is to present two of the most frequently used functions, the equipercentile equating function and the item response theory (IRT) true score equating function, and to discuss the connections between these functions and the different definitions. A conclusion is that it is important to understand the difference between an approach where the starting point is the stochastic individual whose answer on an item is governed by some probability distribution and an approach where the starting point is a distribution of potential scores in a population of individuals. This distinction is behind some of the differences between the definitions of equating, and also of importance for the entire equating process. 

  • 65.
    Bränberg, Kenny
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Wiberg, Marie
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Observed score linear equating with covariates2011In: Journal of educational measurement, ISSN 0022-0655, E-ISSN 1745-3984, Vol. 48, no 4, p. 419-440Article in journal (Refereed)
    Abstract [en]

    This paper examined observed score linear equating in two different data collection designs, the equivalent groups design and the nonequivalent groups design, when information from covariates (i.e. background variables correlated with the test scores) was included. The main purpose of the study was to examine the effect (i.e. bias, variance, and mean square error) on the estimators of including this additional information. A model for observed-score linear equating with covariates first was suggested. As a second step, the model was used in a simulation study to show that the use of covariates such as gender and education can increase the accuracy of an equating by reducing the mean squared error of the estimators. Finally, data from two administrations of the Swedish Scholastic Assessment Test were used to illustrate the use of the model.

  • 66.
    Bränberg, Kenny
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Wiberg, Marie
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    The effect on equating of using background variablesManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper observed score linear equating with two different data collection designs, the equivalent groups design and the non-equivalent groups design, is examined when including information from background variables. The purpose of the study is to examine the effect (i.e., bias, variance and mean squared error) on the estimators of including this additional information. In a simulation study, we show that the use of background variables, such as gender and education, can increase the accuracy of an equating by reducing the mean squared error (MSE) of the estimators. 

  • 67.
    Brändström, Anders
    et al.
    Umeå University, Faculty of Social Sciences, Centre for Population Studies.
    Broström, Göran
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Life-histories for nineteenth-century Swedish hospital patients: Chances of survival1989In: Journal of Family History, ISSN 0363-1990, E-ISSN 1552-5473, Vol. 14, p. 195-209Article in journal (Refereed)
  • 68.
    Brändström, Anders
    et al.
    Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS). Umeå University, Faculty of Arts, Historical Studies.
    Edvinsson, Sören
    Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS). Umeå University, Faculty of Social Sciences, Demographic Data Base.
    Lindkvist, Marie
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Rogers, John
    Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS).
    Clustering across generations: a comparative analysis of infant mortality in 19th century Sweden2007In: ESSHC Conference in Lisbon, 26 February-1 March, 2008, 2007Conference paper (Other academic)
    Abstract [en]

    Many studies in the past have emphasized the positive correlation between infant mortality and fertility, but how this operates remain unclear. In this paper, we investigate these interdependent processes using data from the Demographic Data base at Ume{\aa} University. More specifically, we have data from regions in the northern part of Sweden, starting in the fifteenth century and ending around the year 1900. In an earlier paper, we have studied the intergenerational aspects of infant mortality and in this paper we incorporate fertility. We investigate the interaction between the two processes and how patterns are tranferred from generation to generation.

  • 69.
    Brändström, Anders
    et al.
    Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS).
    Edvinsson, Sören
    Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS). Umeå University, Faculty of Social Sciences, Demographic Data Base.
    Rogers, John
    Broström, Göran
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    High risk families: The unequal distribution of infant mortality in nineteenth century Sweden2005In: Population Studies, ISSN 0032-4728, E-ISSN 1477-4747, Vol. 59, no 3, p. 321-337Article in journal (Refereed)
  • 70.
    Brännäs, Kurt
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    On estimation in econometric systems in the presence of time-varying parameters1980Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Economic systems are often subject to structural variability. For the achievement of correct structural specification in econometric modelling it is then important to allow for parameters that are time-varying, and to apply estimation techniques suitably designed for inference in such models. One realistic model assumption for such parameter variability is the Markovian model, and Kaiman filtering is then assumed to be a convenient estimator. In the thesis several aspects of using Kaiman filtering approaches to estimation in that framework are considered. The application of the Kaiman filter to estimation in econometric models is straightforward if a set of basic assumptions are satisfied, and if necessary initial specifications can be accurately made. Typically, however, these requirements can generally not be perfectly met. It is therefore of great importance to know the consequences of deviations from the basic assumptions and correct initial specifications for inference, in particular for the small sample situations typical in econometrics. If the consequences are severe it is essential to develop techniques to cope with such aspects.For estimation in interdependent systems a two stage Kaiman filter is proposed and evaluated, theoretically, as well as by a small sample Monte Carlo study, and empirically. The estimator is approximative, but with promising small sample properties. Only if the transition matrix of the parameter model and an initial parameter vector are misspecified, the performance deteriorates. Furthermore, the approach provides useful information about structural properties, and forms a basis for good short term forecasting.In a reduced form fraaework most of the basic assumptions of the traditional Kaiman filter are relaxed, and the implications are studied. The case of stochastic regressors is, under reasonable additional assumptions, shown to result in an estimator structurally similar to that due to the basic assumptions. The robustness properties are such that in particular the transition matrix and the initial parameter vector should be carefully estimated. An estimator for the joint estimation of the transition matrix, the parameter vector and the model residual variance is suggested and utilized to study the consequences of a misspecified parameter model. By estimating th transitions the parameter estimates are seen to be robust in this respect.

  • 71. Bygren, Lars-Olov
    et al.
    Edvinsson, Sören
    Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS).
    Broström, Göran
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Change in food availability during pregnancy, Is it related to adult sudden death from cerebro- and cardiovascular disease in offspring?2000In: American Journal of Human Biology, ISSN 1042-0533, E-ISSN 1520-6300, Vol. 12, p. 447-453Article in journal (Refereed)
  • 72. Cantoni, Eva
    et al.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Statistics.
    Non-parametric adjustment for covariates when estimating a treatment effect2004Report (Other academic)
  • 73. Cantoni, Eva
    et al.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Statistics.
    Non-parametric adjustment for covariates when estimating a treatment effect2006In: Journal of Nonparametric Statistics, Vol. 18, p. 227-244Article in journal (Refereed)
  • 74.
    Carelli, Grazia
    et al.
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Wiberg, Britt
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Wiberg, Marie
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Development and Construct Validation of the Swedish Zimbardo Time Perspective Inventory (S-ZTPI).2011In: European Journal of Psychological Assessment, ISSN 1015-5759, E-ISSN 2151-2426, Vol. 27, no 4, p. 220-227Article in journal (Refereed)
    Abstract [en]

    In this study, we developed and evaluated a Swedish version of the Zimbardo Time Perspective Inventory (ZTPI;Zimbardo & Boyd, 1999). The original version of the ZTPI was extended by including a Future Negative scale, and the psychometric properties of both versions were examined in a sample of 419 adults aged between 18 and 80 years. Confirmatory factor analysis (CFA) provided support both for the original five-factor solution proposed byZimbardo and Boyd (1999) in a Swedish sample and for a six-factor solution with the Future Negative scale as an independent factor. These findings extend the original ZTPI and suggest that negative feelings about the future constitute a central dimension of the temporal perspective. The Swedish Zimbardo Time Perspective Inventory (S-ZTPI) provides a reliable and valid instrument for measuring time perspective in the context of Swedish research and to be beneficial in its application in multiple areas of psychology and related disciplines.

  • 75.
    Carlsson, Olle
    Umeå University, Faculty of Social Sciences, Statistics.
    Om fördelningen av en summa av vägda oberoende Poissonvariabler med tillämpningar inom statistisk inferensteori och stokastiska processer1970Licentiate thesis, monograph (Other academic)
  • 76.
    Carlsson, Olle
    Umeå University, Faculty of Social Sciences, Statistics.
    On Quality Selection1990Doctoral thesis, monograph (Other academic)
  • 77.
    Cassel, Claes-Magnus
    Umeå University, Faculty of Social Sciences, Statistics.
    Inferensproblemet vid ändliga populationer: några synpunkter1970Licentiate thesis, monograph (Other academic)
  • 78.
    Danardono,
    Umeå University, Faculty of Social Sciences, Statistics.
    Event History Analysis of Childhood Mortality and Morbidity in Purworejo, Indonesia2003Licentiate thesis, monograph (Other academic)
  • 79.
    Danardono,
    Umeå University, Faculty of Social Sciences, Statistics.
    Multiple Time Scales and Longitudinal Measurements in Event History Analysis2005Doctoral thesis, monograph (Other academic)
    Abstract [en]

    A general time-to-event data analysis known as event history analysis is considered. The focus is on the analysis of time-to-event data using Cox's regression model when the time to the event may be measured from different origins giving several observable time scales and when longitudinal measurements are involved. For the multiple time scales problem, procedures to choose a basic time scale in Cox's regression model are proposed. The connections between piecewise constant hazards, time-dependent covariates and time-dependent strata in the dual time scales are discussed. For the longitudinal measurements problem, four methods known in the literature together with two proposed methods are compared. All quantitative comparisons are performed by means of simulations. Applications to the analysis of infant mortality, morbidity, and growth are provided.

  • 80.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Statistics.
    Guaranteed-content prediction intervals for non-linear autoregressions2001In: Journal of Forecasting, Vol. 20, no 4, p. 265-272Article in journal (Refereed)
  • 81.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Daunfeldt, Sven-Olov
    Central bank independence and price stability: evidence from OECD-countries2008In: Oxford Economic Papers, ISSN 0030-7653, E-ISSN 1464-3812, Vol. 60, no 3, p. 410-422Article in journal (Refereed)
  • 82.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Daunfeldt, Sven-Olov
    The Efficacy and Cost of Regime Shifts in Inflation Policies: Evidence from New Zealand and Sweden2001In: Applied Economics, Vol. 33, p. 217-224Article in journal (Refereed)
  • 83.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Forslund, Anders
    Liljeberg, Linus
    Effekter av yrkesinriktad arbetsmarknadsutbildning för deltagare under perioden 2002-042008Report (Other academic)
  • 84.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Genton, Marc G
    Predictive spatio-temporal models for spatially sparse environmental data2005In: Statistica Sinica, Vol. 15, p. 547-568Article in journal (Refereed)
  • 85.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Genton, Marc G.
    Robust Simulation-Based Estimation of ARMA Models2001In: Journal of Computational and Graphical Statistics, Vol. 10, p. 370-387Article in journal (Refereed)
    Abstract [en]

    This article proposes a new approach to the robust estimation of a mixed autoregressive and moving average (ARMA) model. It is based on the indirect inference method that originally was proposed for models with an intractable likelihood function. The estimation algorithm proposed is based on an auxiliary autoregressive representation whose parameters are first estimated on the observed time series and then on data simulated from the ARMA model. To simulate data the parameters of the ARMA model have to be set. By varying these we can minimize a distance between the simulation-based and the observation-based auxiliary estimate. The argument of the minimum yields then an estimator for the parameterization of the ARMA model. This simulation-based estimation procedure inherits the properties of the auxiliary model estimator. For instance, robustness is achieved with GM estimators. An essential feature of the introduced estimator, compared to existing robust estimators for ARMA models, is its theoretical tractability that allows us to show consistency and asymptotic normality. Moreover, it is possible to characterize the influence function and the breakdown point of the estimator. In a small sample Monte Carlo study it is found that the new estimator performs fairly well when compared with existing procedures. Furthermore, with two real examples, we also compare the proposed inferential method with two different approaches based on outliers detection.

  • 86.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Genton, Marc G.
    Simulation-based Inference for Simultaneous Processes on Regular Lattices2002In: Statistics and Computing, Vol. 12, p. 125-134Article in journal (Refereed)
  • 87.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Genton, Marc G
    Spatio-temporal autoregressive models for US unemployment rate2004In: Spatial and Spatiotemporal Econometrics, Elsevier, Amsterdam , 2004, p. 279-294Chapter in book (Refereed)
  • 88.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Johansson, Per
    Comment on "Maximum likelihood estimation in semiparametric regression models with censored data" by D. Zeng and D.Y. Lin2007In: Journal of the Royal Statistical Society, Series B, Vol. 69, no 4, p. 554-555Article in journal (Other academic)
  • 89.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Johansson, Per
    Exogeneity in structural equation models2006In: Journal of Econometrics, Vol. 132, p. 527-543Article in journal (Refereed)
    Abstract [en]

    The practical relevance of several concepts of exogeneity of treatments

    for the estimation of causal parameters based on observational data are

    discussed. We show that the traditional concepts, such as strong ignorability

    and weak and super-exogeneity, are too restrictive if interest lies

    in average effects (i.e. not on distributional effects of the treatment). We

    suggest a new definition of exogeneity, KL−exogeneity. It does not rely

    on distributional assumptions and is not based on counterfactual random

    variables. As a consequence it can be empirically tested using a proposed

    test that is simple to implement and is distribution-free.

  • 90.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Johansson, Per
    Uppsala University.
    Graphical diagnostics of endogeneity2008In: Modelling and Evaluating Treatment Effects in Econometrics / [ed] Tom Fomby, R. Carter Hill, Daniel L. Millimet, Jeffrey A. Smith, Edward J. Vytlacil, Emerald Group Publishing Limited, 2008, p. 147-166Chapter in book (Other academic)
    Abstract [en]

    We show that in sorting cross-sectional data, the endogeneity of a variable may be successfully detected by graphically examining the cumulative sum of the recursive residuals. Moreover, the sign of the bias implied by the endogeneity may be deducible through such graphs. In general, instrumental variables are needed to implement the graphical test. However, when a continuous or ordered (e.g. years of schooling) variable is suspected to be endogenous, a graphical test for misspecification due to endogeneity (e.g. self-selection) can be obtained without instrumental variables.

  • 91.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Johansson, Per
    Matching estimators for the effect of a treatment on survival times2007Report (Other academic)
  • 92.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Johansson, Per
    Uppsala University and IFAU, Uppsala.
    Non-parametric inference for the effect of a treatment on survival times with application in the health and social sciences2010In: Journal of Statistical Planning and Inference, ISSN 0378-3758, E-ISSN 1873-1171, Vol. 140, no 7, p. 2122-2137Article in journal (Refereed)
    Abstract [en]

    In this paper we perform inference on the effect of a treatment on survival times in studies where the treatment assignment is not randomized and the assignment time is not known in advance. Two such studies are discussed: a heart transplant program and a study of Swedish unemployed eligible for employment subsidy. We estimate survival functions on a treated and a control group which are made comparable through matching on observed covariates. The inference is performed by conditioning on waiting time to treatment, that is, time between the entrance in the study and treatment. This can be done only when sufficient data are available. In other cases, averaging over waiting times is a possibility, although the classical interpretation of the estimated survival functions is lost unless hazards are not functions of waiting time. To show unbiasedness and to obtain an estimator of the variance, we build on the potential outcome framework, which was introduced by J. Neyman in the context of randomized experiments, and adapted to observational studies by D.B. Rubin. Our approach does not make parametric or distributional assumptions. In particular, we do not assume proportionality of the hazards compared. Small sample performance of the estimator and a derived test of no treatment effect are studied in a Monte Carlo study.

  • 93.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Lundin, Mathias
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Sensitivity analysis of the unconfoundedess assumption in observational studies2009Report (Other academic)
  • 94. de Luna, Xavier
    et al.
    Richardson, Thomas S.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Statistics.
    Identification of minimal sets of covariates for the non-parametric estimation of an average treatment effectArticle in journal (Refereed)
  • 95.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Skouras, Kostas
    Choosing a Model Selection Strategy2003In: Scandinavian Journal of Statistics, Vol. 30, p. 113-128Article in journal (Refereed)
  • 96.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Stenberg, Anders
    Institutet för Social forskning, Stockholms universitet.
    Westerlund, Olle
    Umeå University, Faculty of Social Sciences, Department of Economics.
    Can adult education delay retirement from the labour market?2010Report (Other academic)
  • 97.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Stenberg, Anders
    SOFI, Stockholm University.
    Westerlund, Olle
    Umeå University, Faculty of Social Sciences, Department of Economics.
    Can adult education delay retirement from the Labour Market?2008Report (Other academic)
    Abstract [en]

    Several studies have suggested that education is associated with later retirement from the labour market. In this paper, we examine whether adult education, involving enrolees aged 42 or above, delays retirement to potentially increase labour force participation among the elderly. With Swedish register data of transcripts from adult education and an-nual earnings, which encompasses 1979-2004 and 1982-2004 respectively, we exploit the fact that adult education is a large-scale phenomenon in Sweden and construct a measure of the timing of the transition from being self-supported by productive work to being supported by pension transfers. We match samples of treated and controls on the propen-sity score and use non-parametric estimation of survival rates. The results indicate that adult education has no effect on the timing of the retirement from the labour force. This can be contrasted with the fact that adult education is one of the cornerstones of the OECD strategy for “active ageing” and the European Union’s “Lisbon strategy” for growth and jobs.

  • 98. de Luna, Xavier
    et al.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Statistics.
    Covariate selection for non-parametric estimation of treatment effectsManuscript (Other academic)
  • 99.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Statistics.
    Covariate selection for non-parametric estimation of treatment effects2005Report (Other academic)
  • 100.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Richardson, Thomas
    Department of Statistics, University of Washington, Box 354322, Washington 98195-4322 Seattle, U.S.A..
    Covariate selection for the non-parametric estimation of an average treatment effect2011In: Biometrika, ISSN 0006-3444, E-ISSN 1464-3510, Vol. 98, no 4, p. 861-875Article in journal (Refereed)
    Abstract [en]

    Observational studies in which the effect of a nonrandomized treatment on an outcome of interest is estimated are common in domains such as labour economics and epidemiology. Such studies often rely on an assumption of unconfounded treatment when controlling for a given set of observed pre-treatment covariates. The choice of covariates to control in order to guarantee unconfoundedness should primarily be based on subject matter theories, although the latter typically give only partial guidance. It is tempting to include many covariates in the controlling set to try to make the assumption of an unconfounded treatment realistic. Including unnecessary covariates is suboptimal when the effect of a binary treatment is estimated nonparametrically. For instance, when using a n1/2-consistent estimator, a loss of efficiency may result from using covariates that are irrelevant for the unconfoundedness assumption. Moreover, bias may dominate the variance when many covariates are used. Embracing the Neyman–Rubin model typically used in conjunction with nonparametric estimators of treatment effects, we characterize subsets from the original reservoir of covariates that are minimal in the sense that the treatment ceases to be unconfounded given any proper subset of these minimal sets. These subsets of covariates are shown to be identified under mild assumptions. These results lead us to propose data-driven algorithms for the selection of minimal sets of covariates.

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