The Experts below are selected from a list of 126 Experts worldwide ranked by ideXlab platform
Sanjay Shete - One of the best experts on this subject based on the ideXlab platform.
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Mediation analysis in a case-control study when the mediator is a censored Variable.
Statistics in medicine, 2018Co-Authors: Jian Wang, Jing Ning, Sanjay SheteAbstract:Mediation analysis is an approach for assessing the direct and indirect effects of an Initial Variable on an outcome through a mediator. In practice, mediation models can involve a censored mediator (eg, a woman's age at menopause). The current research for mediation analysis with a censored mediator focuses on scenarios where outcomes are continuous. However, the outcomes can be binary (eg, type 2 diabetes). Another challenge when analyzing such a mediation model is to use data from a case-control study, which results in biased estimations for the Initial Variable-mediator association if a standard approach is directly applied. In this study, we propose an approach (denoted as MAC-CC) to analyze the mediation model with a censored mediator given data from a case-control study, based on the semiparametric accelerated failure time model along with a pseudo-likelihood function. We adapted the measures for assessing the indirect and direct effects using counterfactual definitions. We conducted simulation studies to investigate the performance of MAC-CC and compared it to those of the naive approach and the complete-case approach. MAC-CC accurately estimates the coefficients of different paths, the indirect effects, and the proportions of the total effects mediated. We applied the proposed and existing approaches to the mediation study of genetic variants, a woman's age at menopause, and type 2 diabetes based on a case-control study of type 2 diabetes. Our results indicate that there is no mediating effect from the age at menopause on the association between the genetic variants and type 2 diabetes.
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An approach to estimate bidirectional mediation effects with application to body mass index and fasting glucose
Annals of human genetics, 2018Co-Authors: Rajesh Talluri, Sanjay SheteAbstract:Obesity and type 2 diabetes are major public health issues with known interdependence. Genetic variants have been associated with obesity, type 2 diabetes, or both; thus, we hypothesize that some single nucleotide polymorphisms (SNPs) associated with both conditions may be mediated through obesity to affect type 2 diabetes or vice versa. We propose a framework for bidirectional mediation analyses. Simulations show that this approach accurately estimates the parameters, whether the mediation is unidirectional or bidirectional. In many scenarios, when the mediator is regressed on the Initial Variable and the outcome is regressed on the mediator and the Initial Variable, the resulting residuals are correlated because of other unmeasured covariates not in the model. We show that the proposed model provides accurate estimates in this scenario, too. We applied the proposed approach to investigate the mediating effects of SNPs associated with type 2 diabetes and obesity using genetic data from the Multi-Ethnic Study of Atherosclerosis cohort. Specifically, we used body mass index (BMI) as a measure for obesity and fasting glucose as a measure for type 2 diabetes. We evaluated the top 6 SNPs associated with both BMI and fasting glucose. Two SNPs (rs3752355 and rs6087982) had indirect effects on BMI mediated through fasting glucose [0.2677; 95% confidence interval (CI) (0.0007, 0.6548) and 0.3301; 95% CI (0.0881, 0.8544), respectively]. The remaining four SNPs (rs7969190, rs4869710, rs10201400, and rs12421620) directly affect BMI and fasting glucose without mediating effects.
Rachid Rebiha - One of the best experts on this subject based on the ideXlab platform.
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On the Termination of Linear and Affine Programs over the Integers
arXiv: Discrete Mathematics, 2014Co-Authors: Rachid Rebiha, Arnaldo Vieira Moura, Nadir MatringeAbstract:The termination problem for affine programs over the integers was left open in\cite{Braverman}. For more that a decade, it has been considered and cited as a challenging open problem. To the best of our knowledge, we present here the most complete response to this issue: we show that termination for affine programs over Z is decidable under an assumption holding for almost all affine programs, except for an extremely small class of zero Lesbegue measure. We use the notion of asymptotically non-terminating Initial Variable values} (ANT, for short) for linear loop programs over Z. Those values are directly associated to Initial Variable values for which the corresponding program does not terminate. We reduce the termination problem of linear affine programs over the integers to the emptiness check of a specific ANT set of Initial Variable values. For this class of linear or affine programs, we prove that the corresponding ANT set is a semi-linear space and we provide a powerful computational methods allowing the automatic generation of these $ANT$ sets. Moreover, we are able to address the conditional termination problem too. In other words, by taking ANT set complements, we obtain a precise under-approximation of the set of inputs for which the program does terminate.
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Generating Asymptotically Non-Terminating Initial Values for Linear Programs
arXiv: Discrete Mathematics, 2014Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo Vieira MouraAbstract:We present the notion of asymptotically non-terminating Initial Variable values for linear loop programs. Those values are directly associated to Initial Variable values for which the corresponding program does not terminate. Our theoretical contributions provide us with powerful computational methods for automatically generating sets of asymptotically non-terminating Initial Variable values. Such sets are represented symbolically and exactly by a semi-linear space, e.g., characterized by conjunctions and disjunctions of linear equalities and inequalities. Moreover, by taking their complements, we obtain a precise under-approximation of the set of inputs for which the program does terminate. We can then reduce the termination problem of linear programs to the emptiness check of a specific set of asymptotically non-terminating Initial Variable values. Our static input data analysis is not restricted only to programs where the Variables are interpreted over the reals. We extend our approach and provide new decidability results for the termination problem of affine integer and rational programs.
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SCSS - Generating Asymptotically Non-Terminant Initial Variable Values for Linear Diagonalizable Programs
2013Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo MouraAbstract:We present the key notion of asymptotically non-terminant Initial Variable values for non-terminant loop programs. We show that those specic values are directly associated to inital Variable values for which the corresponding loop program does not terminate. Considering linear diagonalizable programs, we describe powerful computational methods that generate automatically and symbolically a semi-linear space represented by a linear system of equalities and inequalities. Each element of this space provides us with asymptotically non-terminant Initial Variable values. Our approach is based on linear algebraic methods. We obtain specic conditions using certain basis and matrix encodings related to the loop conditions and instructions.
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generating asymptotically non terminant Initial Variable values for linear diagonalizable programs
SCSS, 2013Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo MouraAbstract:We present the key notion of asymptotically non-terminant Initial Variable values for non-terminant loop programs. We show that those specic values are directly associated to inital Variable values for which the corresponding loop program does not terminate. Considering linear diagonalizable programs, we describe powerful computational methods that generate automatically and symbolically a semi-linear space represented by a linear system of equalities and inequalities. Each element of this space provides us with asymptotically non-terminant Initial Variable values. Our approach is based on linear algebraic methods. We obtain specic conditions using certain basis and matrix encodings related to the loop conditions and instructions.
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Generating Asymptotically Non-terminant Initial Variable Values for Linear Diagonalizable Programs.
1Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo Vieira MouraAbstract:We present the key notion of "asymptotically non-terminant Initial Variable values" for non-terminant loop programs. We show that those specific values are directly associated to inital Variable values for which the loop program does not terminate.Considering linear diagonalizable programs, we describe powerful computational methods that generate automatically and symbolically a semi-linear space represented by a linear system of equalities and inequalities. Each element of this space provides us with asymptotically non-terminant Initial Variable values. Our approach is based on linear algebraic methods and results. We obtain conditions using a decomposition on a specific basis, involving the loop condition and the matrix encoding the instructions of the loop.
Nadir Matringe - One of the best experts on this subject based on the ideXlab platform.
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On the Termination of Linear and Affine Programs over the Integers
arXiv: Discrete Mathematics, 2014Co-Authors: Rachid Rebiha, Arnaldo Vieira Moura, Nadir MatringeAbstract:The termination problem for affine programs over the integers was left open in\cite{Braverman}. For more that a decade, it has been considered and cited as a challenging open problem. To the best of our knowledge, we present here the most complete response to this issue: we show that termination for affine programs over Z is decidable under an assumption holding for almost all affine programs, except for an extremely small class of zero Lesbegue measure. We use the notion of asymptotically non-terminating Initial Variable values} (ANT, for short) for linear loop programs over Z. Those values are directly associated to Initial Variable values for which the corresponding program does not terminate. We reduce the termination problem of linear affine programs over the integers to the emptiness check of a specific ANT set of Initial Variable values. For this class of linear or affine programs, we prove that the corresponding ANT set is a semi-linear space and we provide a powerful computational methods allowing the automatic generation of these $ANT$ sets. Moreover, we are able to address the conditional termination problem too. In other words, by taking ANT set complements, we obtain a precise under-approximation of the set of inputs for which the program does terminate.
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Generating Asymptotically Non-Terminating Initial Values for Linear Programs
arXiv: Discrete Mathematics, 2014Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo Vieira MouraAbstract:We present the notion of asymptotically non-terminating Initial Variable values for linear loop programs. Those values are directly associated to Initial Variable values for which the corresponding program does not terminate. Our theoretical contributions provide us with powerful computational methods for automatically generating sets of asymptotically non-terminating Initial Variable values. Such sets are represented symbolically and exactly by a semi-linear space, e.g., characterized by conjunctions and disjunctions of linear equalities and inequalities. Moreover, by taking their complements, we obtain a precise under-approximation of the set of inputs for which the program does terminate. We can then reduce the termination problem of linear programs to the emptiness check of a specific set of asymptotically non-terminating Initial Variable values. Our static input data analysis is not restricted only to programs where the Variables are interpreted over the reals. We extend our approach and provide new decidability results for the termination problem of affine integer and rational programs.
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SCSS - Generating Asymptotically Non-Terminant Initial Variable Values for Linear Diagonalizable Programs
2013Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo MouraAbstract:We present the key notion of asymptotically non-terminant Initial Variable values for non-terminant loop programs. We show that those specic values are directly associated to inital Variable values for which the corresponding loop program does not terminate. Considering linear diagonalizable programs, we describe powerful computational methods that generate automatically and symbolically a semi-linear space represented by a linear system of equalities and inequalities. Each element of this space provides us with asymptotically non-terminant Initial Variable values. Our approach is based on linear algebraic methods. We obtain specic conditions using certain basis and matrix encodings related to the loop conditions and instructions.
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generating asymptotically non terminant Initial Variable values for linear diagonalizable programs
SCSS, 2013Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo MouraAbstract:We present the key notion of asymptotically non-terminant Initial Variable values for non-terminant loop programs. We show that those specic values are directly associated to inital Variable values for which the corresponding loop program does not terminate. Considering linear diagonalizable programs, we describe powerful computational methods that generate automatically and symbolically a semi-linear space represented by a linear system of equalities and inequalities. Each element of this space provides us with asymptotically non-terminant Initial Variable values. Our approach is based on linear algebraic methods. We obtain specic conditions using certain basis and matrix encodings related to the loop conditions and instructions.
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Generating Asymptotically Non-terminant Initial Variable Values for Linear Diagonalizable Programs.
1Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo Vieira MouraAbstract:We present the key notion of "asymptotically non-terminant Initial Variable values" for non-terminant loop programs. We show that those specific values are directly associated to inital Variable values for which the loop program does not terminate.Considering linear diagonalizable programs, we describe powerful computational methods that generate automatically and symbolically a semi-linear space represented by a linear system of equalities and inequalities. Each element of this space provides us with asymptotically non-terminant Initial Variable values. Our approach is based on linear algebraic methods and results. We obtain conditions using a decomposition on a specific basis, involving the loop condition and the matrix encoding the instructions of the loop.
Arnaldo Vieira Moura - One of the best experts on this subject based on the ideXlab platform.
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On the Termination of Linear and Affine Programs over the Integers
arXiv: Discrete Mathematics, 2014Co-Authors: Rachid Rebiha, Arnaldo Vieira Moura, Nadir MatringeAbstract:The termination problem for affine programs over the integers was left open in\cite{Braverman}. For more that a decade, it has been considered and cited as a challenging open problem. To the best of our knowledge, we present here the most complete response to this issue: we show that termination for affine programs over Z is decidable under an assumption holding for almost all affine programs, except for an extremely small class of zero Lesbegue measure. We use the notion of asymptotically non-terminating Initial Variable values} (ANT, for short) for linear loop programs over Z. Those values are directly associated to Initial Variable values for which the corresponding program does not terminate. We reduce the termination problem of linear affine programs over the integers to the emptiness check of a specific ANT set of Initial Variable values. For this class of linear or affine programs, we prove that the corresponding ANT set is a semi-linear space and we provide a powerful computational methods allowing the automatic generation of these $ANT$ sets. Moreover, we are able to address the conditional termination problem too. In other words, by taking ANT set complements, we obtain a precise under-approximation of the set of inputs for which the program does terminate.
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Generating Asymptotically Non-Terminating Initial Values for Linear Programs
arXiv: Discrete Mathematics, 2014Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo Vieira MouraAbstract:We present the notion of asymptotically non-terminating Initial Variable values for linear loop programs. Those values are directly associated to Initial Variable values for which the corresponding program does not terminate. Our theoretical contributions provide us with powerful computational methods for automatically generating sets of asymptotically non-terminating Initial Variable values. Such sets are represented symbolically and exactly by a semi-linear space, e.g., characterized by conjunctions and disjunctions of linear equalities and inequalities. Moreover, by taking their complements, we obtain a precise under-approximation of the set of inputs for which the program does terminate. We can then reduce the termination problem of linear programs to the emptiness check of a specific set of asymptotically non-terminating Initial Variable values. Our static input data analysis is not restricted only to programs where the Variables are interpreted over the reals. We extend our approach and provide new decidability results for the termination problem of affine integer and rational programs.
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Generating Asymptotically Non-terminant Initial Variable Values for Linear Diagonalizable Programs.
1Co-Authors: Rachid Rebiha, Nadir Matringe, Arnaldo Vieira MouraAbstract:We present the key notion of "asymptotically non-terminant Initial Variable values" for non-terminant loop programs. We show that those specific values are directly associated to inital Variable values for which the loop program does not terminate.Considering linear diagonalizable programs, we describe powerful computational methods that generate automatically and symbolically a semi-linear space represented by a linear system of equalities and inequalities. Each element of this space provides us with asymptotically non-terminant Initial Variable values. Our approach is based on linear algebraic methods and results. We obtain conditions using a decomposition on a specific basis, involving the loop condition and the matrix encoding the instructions of the loop.
Jian Wang - One of the best experts on this subject based on the ideXlab platform.
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Mediation analysis in a case-control study when the mediator is a censored Variable.
Statistics in medicine, 2018Co-Authors: Jian Wang, Jing Ning, Sanjay SheteAbstract:Mediation analysis is an approach for assessing the direct and indirect effects of an Initial Variable on an outcome through a mediator. In practice, mediation models can involve a censored mediator (eg, a woman's age at menopause). The current research for mediation analysis with a censored mediator focuses on scenarios where outcomes are continuous. However, the outcomes can be binary (eg, type 2 diabetes). Another challenge when analyzing such a mediation model is to use data from a case-control study, which results in biased estimations for the Initial Variable-mediator association if a standard approach is directly applied. In this study, we propose an approach (denoted as MAC-CC) to analyze the mediation model with a censored mediator given data from a case-control study, based on the semiparametric accelerated failure time model along with a pseudo-likelihood function. We adapted the measures for assessing the indirect and direct effects using counterfactual definitions. We conducted simulation studies to investigate the performance of MAC-CC and compared it to those of the naive approach and the complete-case approach. MAC-CC accurately estimates the coefficients of different paths, the indirect effects, and the proportions of the total effects mediated. We applied the proposed and existing approaches to the mediation study of genetic variants, a woman's age at menopause, and type 2 diabetes based on a case-control study of type 2 diabetes. Our results indicate that there is no mediating effect from the age at menopause on the association between the genetic variants and type 2 diabetes.