| 1. |
- Andersson, Björn, et al.
(författare)
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Fast estimation of multiple group generalized linear latent variable models for categorical observed variables
- 2023
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Ingår i: Computational Statistics & Data Analysis. - : Elsevier. - 0167-9473 .- 1872-7352. ; 182
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Tidskriftsartikel (refereegranskat)abstract
- A computationally efficient method for marginal maximum likelihood estimation of multiple group generalized linear latent variable models for categorical data is introduced. The approach utilizes second-order Laplace approximations of the integrals in the likelihood function. It is demonstrated how second-order Laplace approximations can be utilized highly efficiently for generalized linear latent variable models by considering symmetries that exist for many types of model structures. In a simulation with binary observed variables and four correlated latent variables in four groups, the method has similar bias and mean squared error compared to adaptive Gauss-Hermite quadrature with five quadrature points while substantially improving computational efficiency. An empirical example from a large-scale educational assessment illustrates the accuracy and computational efficiency of the method when compared against adaptive Gauss-Hermite quadrature with three, five, and 13 quadrature points.
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| 2. |
- Ankargren, Sebastian, et al.
(författare)
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On the least-squares model averaging interval estimator
- 2018
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Ingår i: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 47:1, s. 118-132
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Tidskriftsartikel (refereegranskat)abstract
- In many applications of linear regression models, randomness due to model selection is commonly ignored in post-model selection inference. In order to account for the model selection uncertainty, least-squares frequentist model averaging has been proposed recently. We show that the confidence interval from model averaging is asymptotically equivalent to the confidence interval from the full model. The finite-sample confidence intervals based on approximations to the asymptotic distributions are also equivalent if the parameter of interest is a linear function of the regression coefficients. Furthermore, we demonstrate that this equivalence also holds for prediction intervals constructed in the same fashion.
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| 3. |
- Cao, Chunzheng, et al.
(författare)
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Bayesian inference in a heteroscedastic replicated measurement error model using heavy-tailed distributions
- 2017
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Ingår i: Journal of Statistical Computation and Simulation. - : Informa UK Limited. - 0094-9655 .- 1563-5163. ; 87:15, s. 2915-2928
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Tidskriftsartikel (refereegranskat)abstract
- We introduce a multivariate heteroscedastic measurement error model for replications under scale mixtures of normal distribution. The model can provide a robust analysis and can be viewed as a generalization of multiple linear regression from both model structure and distribution assumption. An efficient method based on Markov Chain Monte Carlo is developed for parameter estimation. The deviance information criterion and the conditional predictive ordinates are used as model selection criteria. Simulation studies show robust inference behaviours of the model against both misspecification of distributions and outliers. We work out an illustrative example with a real data set on measurements of plant root decomposition.
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| 4. |
- Cao, Chunzheng, et al.
(författare)
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Improved likelihood ratio tests in a measurement error model for multivariate replicated data
- 2020
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Ingår i: Communications in Statistics - Theory and Methods. - : TAYLOR & FRANCIS INC. - 0361-0926 .- 1532-415X. ; 49:5, s. 1025-1042
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Tidskriftsartikel (refereegranskat)abstract
- We present a measurement error model for multivariate replicated data and focus on the improved likelihood ratio tests for parameters of interest. By assuming that the random terms follow the scale mixtures of normal distributions, the model can bring robust inference and can target on both error-prone and error-free covariates. We derive modified versions from the original likelihood ratio statistics to achieve better asymptotic properties with high degree of accuracy. Simulation studies are conducted to display finite sample behavior as compared to the unmodified counterpart. The practical utility is illustrated through a root decomposition data.
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| 5. |
- Giordano, Michael L., et al.
(författare)
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Estimating and Testing Random Intercept Multilevel Structural Equation Models with Model Implied Instrumental Variables
- 2022
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Ingår i: Structural Equation Modeling. - : Taylor & Francis Group. - 1070-5511 .- 1532-8007. ; 29:4, s. 584-599
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Tidskriftsartikel (refereegranskat)abstract
- This study develops a new limited information estimator for random intercept Multilevel Structural Equation Models (MSEM). It is based on the Model Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) estimator, which has been shown to be an excellent alternative or supplement to maximum likelihood (ML) in SEMs (Bollen, 1996). We also develop a multilevel overidentification test statistic that applies to equations at the within or between levels. Our Monte Carlo simulation analysis suggests that MIIV-2SLS is more robust than ML to misspecification at within or between levels, performs well given fewer than 100 clusters, and shows that our multilevel overidentification test for equations performs well at both levels of the model.
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| 6. |
- Jin, Shaobo, 1987-, et al.
(författare)
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A note on the accuracy of adaptive Gauss-Hermite quadrature
- 2020
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Ingår i: Biometrika. - : Oxford Academic. - 0006-3444 .- 1464-3510. ; 107:3, s. 737-744
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Tidskriftsartikel (refereegranskat)abstract
- Numerical quadrature methods are needed for many models in order to approximate integrals in the likelihood function. In this note, we correct the error rate given by Liu & Pierce (1994) for integrals approximated with adaptive Gauss–Hermite quadrature and show that the approximation is less accurate than previously thought. We discuss the relationship between the error rates of adaptive Gauss–Hermite quadrature and Laplace approximation, and provide a theoretical explanation of simulation results obtained in previous studies regarding the accuracy of adaptive Gauss–Hermite quadrature.
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| 7. |
- Jin, Shaobo, 1987-, et al.
(författare)
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A review of h-likelihood and hierarchical generalized linear model
- 2021
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Ingår i: Wiley Interdisciplinary Reviews. - : John Wiley & Sons. - 1939-5108 .- 1939-0068. ; 13:5
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Forskningsöversikt (refereegranskat)abstract
- Fisher's classical likelihood has become the standard procedure to make inference for fixed unknown parameters. Recently, inferences of unobservable random variables, such as random effects, factors, missing values, etc., have become important in statistical analysis. Because Fisher's likelihood cannot have such unobservable random variables, the full Bayesian method is only available for inference. An alternative likelihood approach is proposed by Lee and Nelder. In the context of Fisher likelihood, the likelihood principle means that the likelihood function carries all relevant information regarding the fixed unknown parameters. Bjørnstad extended the likelihood principle to extended likelihood principle; all information in the observed data for fixed unknown parameters and unobservables are in the extended likelihood, such as the h-likelihood. However, it turns out that the use of extended likelihood for inferences is not as straightforward as the Fisher likelihood. In this paper, we describe how to extract information of the data from the h-likelihood. This provides a new way of statistical inferences in entire fields of statistical science.
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| 8. |
- Jin, Shaobo, 1987-, et al.
(författare)
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A unified model-implied instrumental variable approach for structural equation modeling with mixed variables
- 2021
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Ingår i: Psychometrika. - : Springer Nature. - 0033-3123 .- 1860-0980. ; 86:2, s. 564-594
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Tidskriftsartikel (refereegranskat)abstract
- The model-implied instrumental variable (MIIV) estimator is an equation-by-equation estimator of structural equation models that is more robust to structural misspecifications than full information estimators. Previous studies have concentrated on endogenous variables that are all continuous (MIIV-2SLS) or all ordinal . We develop a unified MIIV approach that applies to a mixture of binary, ordinal, censored, or continuous endogenous observed variables. We include estimates of factor loadings, regression coefficients, variances, and covariances along with their asymptotic standard errors. In addition, we create new goodness of fit tests of the model and overidentification tests of single equations. Our simulation study shows that the proposed MIIV approach is more robust to structural misspecifications than diagonally weighted least squares (DWLS) and that both the goodness of fit model tests and the overidentification equations tests can detect structural misspecifications. We also find that the bias in asymptotic standard errors for the MIIV estimators of factor loadings and regression coefficients are often lower than the DWLS ones, though the differences are small in large samples. Our analysis shows that scaling indicators with low reliability can adversely affect the MIIV estimators. Also, using a small subset of MIIVs reduces small sample bias of coefficient estimates, but can lower the power of overidentification tests of equations.
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| 9. |
- Jin, Shaobo, 1987-, et al.
(författare)
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Approximate Bayesianity of frequentist confidence intervals for a binomial proportion
- 2017
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Ingår i: American Statistician. - : Informa UK Limited. - 0003-1305 .- 1537-2731. ; 71, s. 106-111
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Tidskriftsartikel (refereegranskat)abstract
- The well-known Wilson and Agresti–Coull confidence intervals for a binomial proportion p are centered around a Bayesian estimator. Using this as a starting point, similarities between frequentist confidence intervals for proportions and Bayesian credible intervals based on low-informative priors are studied using asymptotic expansions. A Bayesian motivation for a large class of frequentist confidence intervals is provided. It is shown that the likelihood ratio interval for p approximates a Bayesian credible interval based on Kerman’s neutral noninformative conjugate prior up to O(n− 1) in the confidence bounds. For the significance level α ≲ 0.317, the Bayesian interval based on the Jeffreys’ prior is then shown to be a compromise between the likelihood ratio and Wilson intervals. Supplementary materials for this article are available online.
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| 10. |
- Jin, Shaobo, 1987-, et al.
(författare)
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Approximated penalized maximum likelihood for exploratory factor analysis : An orthogonal case
- 2018
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Ingår i: Psychometrika. - : Springer Science and Business Media LLC. - 0033-3123 .- 1860-0980. ; 83:3, s. 628-649
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Tidskriftsartikel (refereegranskat)abstract
- The problem of penalized maximum likelihood (PML) for an exploratory factor analysis (EFA) model is studied in this paper. An EFA model is typically estimated using maximum likelihood and then the estimated loading matrix is rotated to obtain a sparse representation. Penalized maximum likelihood simultaneously fits the EFA model and produces a sparse loading matrix. To overcome some of the computational drawbacks of PML, an approximation to PML is proposed in this paper. It is further applied to an empirical dataset for illustration. A simulation study shows that the approximation naturally produces a sparse loading matrix and more accurately estimates the factor loadings and the covariance matrix, in the sense of having a lower mean squared error than factor rotations, under various conditions.
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| 11. |
- Jin, Shaobo, 1987-, et al.
(författare)
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Asymptotic Robustness Study Of The Polychoric Correlation Estimation
- 2017
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Ingår i: Psychometrika. - : Springer Science and Business Media LLC. - 0033-3123 .- 1860-0980. ; 82:1, s. 67-85
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Tidskriftsartikel (refereegranskat)abstract
- Asymptotic robustness against misspecification of the underlying distribution for the polychoric correlation estimation is studied. The asymptotic normality of the pseudo-maximum likelihood estimator is derived using the two-step estimation procedure. The t distribution assumption and the skew-normal distribution assumption are used as alternatives to the normal distribution assumption in a numerical study. The numerical results show that the underlying normal distribution can be substantially biased, even though skewness and kurtosis are not large. The skew-normal assumption generally produces a lower bias than the normal assumption. Thus, it is worth using a non-normal distributional assumption if the normal assumption is dubious.
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| 12. |
- Jin, Shaobo, 1987-
(författare)
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Essays on Estimation Methods for Factor Models and Structural Equation Models
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis which consists of four papers is concerned with estimation methods in factor analysis and structural equation models. New estimation methods are proposed and investigated.In paper I an approximation of the penalized maximum likelihood (ML) is introduced to fit an exploratory factor analysis model. Approximated penalized ML continuously and efficiently shrinks the factor loadings towards zero. It naturally factorizes a covariance matrix or a correlation matrix. It is also applicable to an orthogonal or an oblique structure.Paper II, a simulation study, investigates the properties of approximated penalized ML with an orthogonal factor model. Different combinations of penalty terms and tuning parameter selection methods are examined. Differences in factorizing a covariance matrix and factorizing a correlation matrix are also explored. It is shown that the approximated penalized ML frequently improves the traditional estimation-rotation procedure.In Paper III we focus on pseudo ML for multi-group data. Data from different groups are pooled and normal theory is used to fit the model. It is shown that pseudo ML produces consistent estimators of factor loadings and that it is numerically easier than multi-group ML. In addition, normal theory is not applicable to estimate standard errors. A sandwich-type estimator of standard errors is derived.Paper IV examines properties of the recently proposed polychoric instrumental variable (PIV) estimators for ordinal data through a simulation study. PIV is compared with conventional estimation methods (unweighted least squares and diagonally weighted least squares). PIV produces accurate estimates of factor loadings and factor covariances in the correctly specified confirmatory factor analysis model and accurate estimates of loadings and coefficient matrices in the correctly specified structure equation model. If the model is misspecified, robustness of PIV depends on model complexity, underlying distribution, and instrumental variables.
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| 13. |
- Jin, Shaobo, 1987-, et al.
(författare)
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Frequentist Model Averaging in Structural Equation Modelling
- 2019
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Ingår i: Psychometrika. - : SPRINGER. - 0033-3123 .- 1860-0980. ; 84:1, s. 84-104
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Tidskriftsartikel (refereegranskat)abstract
- Model selection from a set of candidate models plays an important role in many structural equation modelling applications. However, traditional model selection methods introduce extra randomness that is not accounted for by post-model selection inference. In the current study, we propose a model averaging technique within the frequentist statistical framework. Instead of selecting an optimal model, the contributions of all candidate models are acknowledged. Valid confidence intervals and a 2 test statistic are proposed. A simulation study shows that the proposed method is able to produce a robust mean-squared error, a better coverage probability, and a better goodness-of-fit test compared to model selection. It is an interesting compromise between model selection and the full model.
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| 14. |
- Jin, Shaobo, 1987-
(författare)
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Frequentist Model Averaging in Structure Equation Model With Ordinal Data
- 2022
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Ingår i: Psychometrika. - : Springer Nature. - 0033-3123 .- 1860-0980. ; 87:3, s. 1130-1145
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Tidskriftsartikel (refereegranskat)abstract
- In practice, it is common that a best fitting structural equation model (SEM) is selected from a set of candidate SEMs and inference is conducted conditional on the selected model. Such post-selection inference ignores the model selection uncertainty and yields too optimistic inference. Using the largest candidate model avoids model selection uncertainty but introduces a large variation. Jin and Ankargren (Psychometrika 84:84-104, 2019) proposed to use frequentist model averaging in SEM with continuous data as a compromise between model selection and the full model. They assumed that the true values of the parameters depend on n(-1/2) with n being the sample size, which is known as a local asymptotic framework. This paper shows that their results are not directly applicable to SEM with ordinal data. To address this issue, we prove consistency and asymptotic normality of the polychoric correlation estimators under the local asymptotic framework. Then, we propose a new frequentist model averaging estimator and a valid confidence interval that are suitable for ordinal data. Goodness-of-fit test statistics for the model averaging estimator are also derived.
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| 15. |
- Jin, Shaobo, 1987-, et al.
(författare)
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H-Likelihood Approach to Factor Analysis for Ordinal Data
- 2018
-
Ingår i: Structural Equation Modeling. - : Informa UK Limited. - 1070-5511 .- 1532-8007. ; 25:4, s. 530-540
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Tidskriftsartikel (refereegranskat)abstract
- Marginal likelihood-based methods are commonly used in factor analysis for ordinal data. To obtain the maximum marginal likelihood estimator, the full information maximum likelihood (FIML) estimator uses the (adaptive) Gauss-Hermite quadrature or stochastic approximation. However, the computational burden increases rapidly as the number of factors increases, which renders FIML impractical for large factor models. Another limitation of the marginal likelihood-based approach is that it does not allow inference on the factors. In this study, we propose a hierarchical likelihood approach using the Laplace approximation that remains computationally efficient in large models. We also proposed confidence intervals for factors, which maintains the level of confidence as the sample size increases. The simulation study shows that the proposed approach generally works well.
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| 16. |
- Jin, Shaobo, 1987-
(författare)
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On Inconsistency of the Overidentification Test for the Model-implied Instrumental Variable Approach
- 2023
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Ingår i: Structural Equation Modeling. - : Routledge. - 1070-5511 .- 1532-8007. ; 30:2, s. 245-257
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Tidskriftsartikel (refereegranskat)abstract
- In the context of structural equation modeling, the model-implied instrumental variable (MIIV) approach has been shown to be more robust against model misspecification than the systemwide approaches (e.g., maximum likelihood and least squares). Besides the goodness-of-fit tests that test the fit of the entire hypothesized covariance structure, the overidentification tests for MIIV can be used to test model specification on an equation-by-equation basis. However, it is known in the econometrics literature that the overidentification tests are inconsistent against general misspecification, if it is used to test a zero correlation between the instrumental variables and the error terms. In this paper, we show that such inconsistency can also occur for the MIIV approach. Numerical examples where the powers of the tests converge to the size are presented. Theoretical results are proved to support the numerical findings. Implications on when the overidentification tests are consistent are also presented.
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| 17. |
- Jin, Shaobo, 1987-, et al.
(författare)
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Robust nonlinear structural equation modeling with interaction between exogenous and endogenous latent variables
- 2021
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Ingår i: Structural Equation Modeling. - : Taylor & Francis Group. - 1070-5511 .- 1532-8007. ; 28:4, s. 547-556
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Tidskriftsartikel (refereegranskat)abstract
- A handful of studies have been devoted to nonlinear structural equation modeling (SEM) in the literature. However, they generally overlooked the interactions among exogenous and endogenous latent variables and the interactions among endogenous latent variables. In this study, we propose a maximum likelihood approach for a nonlinear SEM model that incorporates such overlooked interactions. We also propose a two-stage pseudo maximum likelihood approach under the assumption of a normal mixture, being computationally efficient and robust against distributional misspecification. The simulation study shows that both approaches accurately estimate the unknown parameters if the distribution is correctly specified. However, only the pseudo maximum likelihood approach is robust against distributional misspecification.
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| 18. |
- Jin, Shaobo, 1987-, et al.
(författare)
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Selecting polychoric instrumental variables in confirmatory factor analysis : An alternative specification test and effects of instrumental variables
- 2018
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Ingår i: British Journal of Mathematical & Statistical Psychology. - : John Wiley & Sons. - 0007-1102 .- 2044-8317. ; 71:2, s. 387-413
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Tidskriftsartikel (refereegranskat)abstract
- The polychoric instrumental variable (PIV) approach is a recently proposed method to fit a confirmatory factor analysis model with ordinal data. In this paper, we first examine the small‐sample properties of the specification tests for testing the validity of instrumental variables (IVs). Second, we investigate the effects of using different numbers of IVs. Our results show that specification tests derived for continuous data are extremely oversized at all sample sizes when applied to ordinal variables. Possible modifications for ordinal data are proposed in the present study. Simulation results show that the modified specification tests with all available IVs are able to detect model misspecification. In terms of estimation accuracy, the PIV approach where the IVs outnumber the endogenous variables by one produces a lower bias but a higher variation than the PIV approach with more IVs for correctly specified factor loadings at small samples.
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| 19. |
- Jin, Shaobo, 1987-, et al.
(författare)
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Standard error estimates in hierarchical generalized linear models
- 2024
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Ingår i: Computational Statistics & Data Analysis. - : Elsevier. - 0167-9473 .- 1872-7352. ; 189
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Tidskriftsartikel (refereegranskat)abstract
- Hierarchical generalized linear models are often used to fit random effects models. However, attention is mostly paid to the estimation of fixed unknown parameters and inference for latent random effects. In contrast, standard error estimators receive less attention than they should be. Currently, the standard error estimators are based on various approximations, even when the mean parameters may be estimated from a higher-order approximation of the likelihood and the dispersion parameters are estimated by restricted maximum likelihood. Existing standard error estimation procedures are reviewed. A numerical illustration shows that the current standard errors are not necessarily accurate. Alternative standard errors are also proposed. In particular, a sandwich estimator that accounts for the dependence between the mean parameters and the dispersion parameters greatly improve the current standard errors.
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| 20. |
- Nyström, Bo, et al.
(författare)
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Are degenerative spondylolisthesis and further slippage postoperatively really issues in spinal stenosis surgery?
- 2020
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Ingår i: Scandinavian Journal of Pain. - : WALTER DE GRUYTER GMBH. - 1877-8860 .- 1877-8879. ; 20:2, s. 307-317
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Tidskriftsartikel (refereegranskat)abstract
- Background and aims: Opinions diverge concerning the prognostic importance of preoperative degenerative spondylolisthesis in patients with lumbar spinal stenosis, as well as the significance of further slippage post-operatively following decompression alone. However, a slip is only one among several factors related to the topic, e.g. duration and intensity of back and leg pain, pre-operative walking ability, number of levels operated and not least the experience of the surgeon. Our aim was to take all of the above-mentioned factors into consideration when analysing the patients' clinical outcome, reported as Change in back pain, Change in leg pain, Overall satisfaction and Change in walking ability, with special emphasis on the possible importance of pre- and/or post-operative degenerative spondylolisthesis. Methods: We studied 200 consecutive patients, mean follow-up time 81 months (range 62-108). Before treatment and on the follow-up occasion all patients answered the SF-36 questionnaire and assessed their back and leg pain on a visual analogue scale (VAS). At follow-up the patients were asked about possible changes in back and leg pain (completely free, much better, somewhat better, unchanged, somewhat worse, much worse) and whether they were; satisfied with the outcome, in doubt or not satisfied. Before treatment and at follow-up the presence or not of degenerative spondylolisthesis was determined in the lateral view on a plain X-ray or MRI. By use of a microsurgical technique decompression was achieved in all patients by bilateral laminotomy not sparing the midline ligaments, irrespective of a degenerative spondylolisthesis or not. Eight surgeons with different surgical experience performed the operations. Four separate multivariate analyses were conducted, one for each clinical outcome. The Lasso method was used for variable selection and multiple imputation was applied to handle missing values. Results: At follow-up 78.5% of the patients were completely satisfied with the outcome. Minimal clinical important difference (MCID) was achieved for 69% of the patients. Before surgery 28 patients were able to walk more than 1 km compared to 111 at follow-up. The reoperation rate at 6.8 years was 12% further decompressions and 2.5% fusions at the index level. Post-operative slippage was equally common in patients with and without a preoperative slip (around 30%). There were no notable differences in outcome in patients with and without a preoperative slip and no effect of further slippage at the index or another level post-operatively. Nor could the statistical analysis show any of the other covariates (age, gender, duration and intensity of back and leg pain, pre-operative walking ability or number of levels operated) to be of statistically significant importance for predicting the outcome. In the univariate statistical analysis differences were found between the patients of individual surgeons regarding satisfaction, pain improvement, and reoperation rates in favour of surgical experience, which were, however, not statistically significant in the multivariate analysis. Conclusions: None of the covariates, including pre-operative spondylolisthesis and further slippage post-operatively, were statistically significant for predicting the clinical outcome. Implication: Our results provide no evidence for adding fusion to the decompression.
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| 21. |
- Nyström, Bo, et al.
(författare)
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Usefulness of discography, discoblock and a new mechanical method for identifying a painful segment/disc
- 2023
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Ingår i: Neuro-chirurgie. - : Elsevier. - 0028-3770 .- 1773-0619. ; 69:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundWe previously described a procedure for eliciting deep spatial discrimination of individual segments in the healthy lumbar spine of normal subjects: the percutaneous mechanical provocation (PMP) test. Our goal was to devise a method for accurate identification of the spinal level of pathology in chronic low back pain (CLBP). In the present study, we validated the PMP test, using a subgroup of CLBP patients with isthmic spondylolisthesis (IS). Because there is clinical consensus that IS back pain originates in the slipped segment/disc, the level of pathology can be directly compared to the result of the PMP test. The test is agnostic with respect to the underlying pathological mechanism, and therefore might be useful in identifying the involved segment(s) irrespective of the painful structure.MethodsIn 37 patients with confirmed IS (slippage 3–15 mm), we compared sensitivity between the PMP test, the widely used provocative discography test and the discoblock test.ResultsThe PMP test reliably identified the slip level in patients with IS, with sensitivity of 92%. Accepting the slipped disc as the origin of pain in IS, the sensitivity of the provocative discography and discoblock tests were 49% and 35%, respectively: i.e., too low to be contributive in clinical practice.ConclusionsThe PMP test reliably identified the origin of localized pain in IS as the slip level, but should be used with care in CLBP patients in selecting discogenic pain patients for fusion surgery, since the specificity of the test is not known and it may be positive for any origin of localized pain.
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| 22. |
- Olivetti, Leonardo, et al.
(författare)
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A Quantile Generalized Additive Approach for Compound Climate Extremes : Pan-Atlantic Extremes as a Case Study
- 2024
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Ingår i: Journal of Advances in Modeling Earth Systems. - : American Geophysical Union (AGU). - 1942-2466. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- We present an application of quantile generalized additive models (QGAMs) to study spatially compounding climate extremes, namely extremes that occur (near-) simultaneously in geographically remote regions. We take as an example wintertime cold spells in North America and co-occurring wet or windy extremes in Western Europe, which we collectively term Pan-Atlantic compound extremes. QGAMS are largely novel in climate science applications and present a number of key advantages over conventional statistical models of weather extremes. Specifically, they remove the need for a direct identification and parametrization of the extremes themselves, since they model all quantiles of the distributions of interest. They thus make use of all information available, and not only of a small number of extreme values. Moreover, they do not require any a priori knowledge of the functional relationship between the predictors and the dependent variable. Here, we use QGAMs to both characterize the co-occurrence statistics and investigate the role of possible dynamical drivers of the Pan-Atlantic compound extremes. We find that cold spells in North America are a useful predictor of subsequent wet or windy extremes in Western Europe, and that QGAMs can predict those extremes more accurately than conventional peak-over-threshold models. In this paper we propose a new data-driven method to study climate extremes occurring simultaneously in multiple, possibly remote, locations. Such extremes can pose a greater threat to human societies than single, isolated extremes, as their effects may exacerbate each other and lead to correlated losses. The method we suggest requires fewer assumptions than conventional extreme value statistical techniques, and can help us to identify previously unknown relationships between the extremes themselves and their possible drivers. We exemplify its use by studying the co-occurrence of periods of unusually cold weather in North America and subsequent uncommonly strong wind and abundant precipitation in Western Europe. We find that the new method has better predictive power for the European extremes than conventional statistical approaches. Furthermore, we confirm the results of previous studies suggesting an association between the wintertime extremes in North America and Western Europe. Quantile general additive models (QGAMs) can model the relationship between compound climate extremes flexibly and robustlyNorth American cold spells show some predictive skill for wet or windy extremes in Western Europe, even when accounting for confoundersGiven relevant atmospheric predictors, QGAMs can predict these extremes more accurately than peak-over-threshold models in most regions
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| 23. |
- Vegelius, Johan, 1981-, et al.
(författare)
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A semiparametric approach for structural equation modeling with ordinal data
- 2021
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Ingår i: Structural Equation Modeling. - : Taylor & Francis Group. - 1070-5511 .- 1532-8007. ; 28:4, s. 497-505
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Tidskriftsartikel (refereegranskat)abstract
- There is currently a lack of methods for non-linear structural equation modeling (NSEM) for non-parametric relationships between latent variables when data are ordinal. To this end, a semiparametric approach for flexible NSEMs without parametric forms is developed for ordinal data. An indirect application of a finite mixture of structural equation models (SEMM) is employed for modeling the conditional expected mean of endogenous latent variables. In this context, the latent classes are not to be interpreted as groups of observations belonging to those classes, rather they serve as means to model flexible non-linear functions as locally linear functions which together approximate a globally non-linear function. The proposed method is based on a hybrid of direct maximization and expectation-maximization algorithms. Two simulation studies are performed which show that parameter estimates are associated with low bias and a non-linear functional form is satisfactorily estimated using the proposed approach.
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| 24. |
- Vegelius, Johan, 1981-
(författare)
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Estimation of Nonlinear Latent Variable and Mixture Models
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this thesis methods are developed for estimation of latent variable models. In particular nonlinear structural equation models are estimated in the presence of ordinal data and mixture models for count data. Paper I introduces an extended nonlinear structural model which allows for interactions between exogenous and endogenous latent variables in the presence of ordinal data. The adaptive Gauss-Hermite quadrature (AGHQ) and Laplace approximations are used to approximate intractable integrals.Paper II introduces a semiparametric approach for modeling a flexible nonlinear structural model in the presence of ordinal data. Intractable integrals are approximated by the AGHQ approximation.Paper III investigates and compares the error rates of three versions of the AGHQ approximation.Paper IV develops an extreme value and zero inflated regression model for modeling of count data which includes a proportion of excess zeroes and extreme values. This is a typical situation when modeling the number of fatalities in armed conflicts.
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| 25. |
- Weber, Tobias A, et al.
(författare)
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γ-Secretase modulators show selectivity for γ-secretase-mediated amyloid precursor protein intramembrane processing.
- 2022
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Ingår i: Journal of cellular and molecular medicine. - : Wiley. - 1582-4934 .- 1582-1838. ; 26:3, s. 880-892
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Tidskriftsartikel (refereegranskat)abstract
- The aggregation of β-amyloid peptide 42 results in the formation of toxic oligomers and plaques, which plays a pivotal role in Alzheimer's disease pathogenesis. Aβ42 is one of several Aβ peptides, all of Aβ30 to Aβ43 that are produced as a result of γ-secretase-mediated regulated intramembrane proteolysis of the amyloid precursor protein. γ-Secretase modulators (GSMs) represent a promising class of Aβ42-lowering anti-amyloidogenic compounds for the treatment of AD. Gamma-secretase modulators change the relative proportion of secreted Aβ peptides, while sparing the γ-secretase-mediated processing event resulting in the release of the cytoplasmic APP intracellular domain. In this study, we have characterized how GSMs affect the γ-secretase cleavage of three γ-secretase substrates, E-cadherin, ephrin type A receptor 4 (EphA4) and ephrin type B receptor 2 (EphB2), which all are implicated in important contexts of cell signalling. By using a reporter gene assay, we demonstrate that the γ-secretase-dependent generation of EphA4 and EphB2 intracellular domains is unaffected by GSMs. We also show that γ-secretase processing of EphA4 and EphB2 results in the release of several Aβ-like peptides, but that only the production of Aβ-like proteins from EphA4 is modulated by GSMs, but with an order of magnitude lower potency as compared to Aβ modulation. Collectively, these results suggest that GSMs are selective for γ-secretase-mediated Aβ production.
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