Sample records for causal comparative design

  1. Quasi-Experimental Designs for Causal Inference

    ERIC Educational Resources Information Center

    Kim, Yongnam; Steiner, Peter

    2016-01-01

    When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…

  2. Enhancing causal interpretations of quality improvement interventions

    PubMed Central

    Cable, G

    2001-01-01

    In an era of chronic resource scarcity it is critical that quality improvement professionals have confidence that their project activities cause measured change. A commonly used research design, the single group pre-test/post-test design, provides little insight into whether quality improvement interventions cause measured outcomes. A re-evaluation of a quality improvement programme designed to reduce the percentage of bilateral cardiac catheterisations for the period from January 1991 to October 1996 in three catheterisation laboratories in a north eastern state in the USA was performed using an interrupted time series design with switching replications. The accuracy and causal interpretability of the findings were considerably improved compared with the original evaluation design. Moreover, the re-evaluation provided tangible evidence in support of the suggestion that more rigorous designs can and should be more widely employed to improve the causal interpretability of quality improvement efforts. Evaluation designs for quality improvement projects should be constructed to provide a reasonable opportunity, given available time and resources, for causal interpretation of the results. Evaluators of quality improvement initiatives may infrequently have access to randomised designs. Nonetheless, as shown here, other very rigorous research designs are available for improving causal interpretability. Unilateral methodological surrender need not be the only alternative to randomised experiments. Key Words: causal interpretations; quality improvement; interrupted time series design; implementation fidelity PMID:11533426

  3. Educational Outcomes of Synchronous and Asynchronous High School Students: A Quantitative Causal-Comparative Study of Online Algebra 1

    ERIC Educational Resources Information Center

    Berry, Sharon

    2017-01-01

    This study used a quantitative, causal-comparative design. It compared educational outcome data from online Algebra 1 courses to determine if a significant difference existed between synchronous and asynchronous students for end-of-course grades, state assessments scores, and student perceptions of their course. The study found that synchronous…

  4. A Comparative Study of Exact versus Propensity Matching Techniques Using Monte Carlo Simulation

    ERIC Educational Resources Information Center

    Itang'ata, Mukaria J. J.

    2013-01-01

    Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…

  5. Enhancing causal interpretations of quality improvement interventions.

    PubMed

    Cable, G

    2001-09-01

    In an era of chronic resource scarcity it is critical that quality improvement professionals have confidence that their project activities cause measured change. A commonly used research design, the single group pre-test/post-test design, provides little insight into whether quality improvement interventions cause measured outcomes. A re-evaluation of a quality improvement programme designed to reduce the percentage of bilateral cardiac catheterisations for the period from January 1991 to October 1996 in three catheterisation laboratories in a north eastern state in the USA was performed using an interrupted time series design with switching replications. The accuracy and causal interpretability of the findings were considerably improved compared with the original evaluation design. Moreover, the re-evaluation provided tangible evidence in support of the suggestion that more rigorous designs can and should be more widely employed to improve the causal interpretability of quality improvement efforts. Evaluation designs for quality improvement projects should be constructed to provide a reasonable opportunity, given available time and resources, for causal interpretation of the results. Evaluators of quality improvement initiatives may infrequently have access to randomised designs. Nonetheless, as shown here, other very rigorous research designs are available for improving causal interpretability. Unilateral methodological surrender need not be the only alternative to randomised experiments.

  6. Teacher Perception of Principals' Leadership Traits and Middle School Math and Science Teachers' Job Satisfaction: A Causal-Comparative and Correlational Study

    ERIC Educational Resources Information Center

    Cousar, Theresa Ann

    2017-01-01

    The purpose of this quantitative study was to examine middle school teachers' job satisfaction (low vs. high) and how teachers perceive principals' leadership traits. The study used a causal-comparative and correlational design. The teachers were divided into two job satisfaction level groups. Teacher perception of principal leadership traits for…

  7. Causal Inference and the Comparative Interrupted Time Series Design: Findings from Within-Study Comparisons

    ERIC Educational Resources Information Center

    St. Clair, Travis; Hallberg, Kelly; Cook, Thomas D.

    2014-01-01

    Researchers are increasingly using comparative interrupted time series (CITS) designs to estimate the effects of programs and policies when randomized controlled trials are not feasible. In a simple interrupted time series design, researchers compare the pre-treatment values of a treatment group time series to post-treatment values in order to…

  8. Non-manipulation quantitative designs.

    PubMed

    Rumrill, Phillip D

    2004-01-01

    The article describes non-manipulation quantitative designs of two types, correlational and causal comparative studies. Both of these designs are characterized by the absence of random assignment of research participants to conditions or groups and non-manipulation of the independent variable. Without random selection or manipulation of the independent variable, no attempt is made to draw causal inferences regarding relationships between independent and dependent variables. Nonetheless, non-manipulation studies play an important role in rehabilitation research, as described in this article. Examples from the contemporary rehabilitation literature are included. Copyright 2004 IOS Press

  9. The Validity and Precision of the Comparative Interrupted Time-Series Design: Three Within-Study Comparisons

    ERIC Educational Resources Information Center

    St. Clair, Travis; Hallberg, Kelly; Cook, Thomas D.

    2016-01-01

    We explore the conditions under which short, comparative interrupted time-series (CITS) designs represent valid alternatives to randomized experiments in educational evaluations. To do so, we conduct three within-study comparisons, each of which uses a unique data set to test the validity of the CITS design by comparing its causal estimates to…

  10. The role of counterfactual theory in causal reasoning.

    PubMed

    Maldonado, George

    2016-10-01

    In this commentary I review the fundamentals of counterfactual theory and its role in causal reasoning in epidemiology. I consider if counterfactual theory dictates that causal questions must be framed in terms of well-defined interventions. I conclude that it does not. I hypothesize that the interventionist approach to causal inference in epidemiology stems from elevating the randomized trial design to the gold standard for thinking about causal inference. I suggest that instead the gold standard we should use for thinking about causal inference in epidemiology is the thought experiment that, for example, compares an actual disease frequency under one exposure level with a counterfactual disease frequency under a different exposure level (as discussed in Greenland and Robins (1986) and Maldonado and Greenland (2002)). I also remind us that no method should be termed "causal" unless it addresses the effect of other biases in addition to the problem of confounding. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Backward Blocking and Interference between Cues Are Empirically Equivalent in Non-Causally Framed Learning Tasks

    ERIC Educational Resources Information Center

    Luque, David; Moris, Joaquin; Orgaz, Cristina; Cobos, Pedro L.; Matute, Helena

    2011-01-01

    Backward blocking (BB) and interference between cues (IbC) are cue competition effects produced by very similar manipulations. In a standard BB design, both effects might occur simultaneously, which implies a potential problem for studying BB. In the present study with humans, the magnitude of both effects was compared using a non-causal scenario…

  12. Sequential causal inference: Application to randomized trials of adaptive treatment strategies

    PubMed Central

    Dawson, Ree; Lavori, Philip W.

    2009-01-01

    SUMMARY Clinical trials that randomize subjects to decision algorithms, which adapt treatments over time according to individual response, have gained considerable interest as investigators seek designs that directly inform clinical decision making. We consider designs in which subjects are randomized sequentially at decision points, among adaptive treatment options under evaluation. We present a sequential method to estimate the comparative effects of the randomized adaptive treatments, which are formalized as adaptive treatment strategies. Our causal estimators are derived using Bayesian predictive inference. We use analytical and empirical calculations to compare the predictive estimators to (i) the ‘standard’ approach that allocates the sequentially obtained data to separate strategy-specific groups as would arise from randomizing subjects at baseline; (ii) the semi-parametric approach of marginal mean models that, under appropriate experimental conditions, provides the same sequential estimator of causal differences as the proposed approach. Simulation studies demonstrate that sequential causal inference offers substantial efficiency gains over the standard approach to comparing treatments, because the predictive estimators can take advantage of the monotone structure of shared data among adaptive strategies. We further demonstrate that the semi-parametric asymptotic variances, which are marginal ‘one-step’ estimators, may exhibit significant bias, in contrast to the predictive variances. We show that the conditions under which the sequential method is attractive relative to the other two approaches are those most likely to occur in real studies. PMID:17914714

  13. A Complex Systems Approach to Causal Discovery in Psychiatry.

    PubMed

    Saxe, Glenn N; Statnikov, Alexander; Fenyo, David; Ren, Jiwen; Li, Zhiguo; Prasad, Meera; Wall, Dennis; Bergman, Nora; Briggs, Ernestine C; Aliferis, Constantin

    2016-01-01

    Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach--the Complex Systems-Causal Network (CS-CN) method-designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study). Next, it was applied to a much larger dataset of traumatized children (replication study). Finally, the CS-CN method was applied in a controlled experiment using a 'gold standard' dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment). The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro) and high-level (macro) insights and thus represents a promising approach for complex systems-oriented research in psychiatry.

  14. Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality

    ERIC Educational Resources Information Center

    Cattaneo, Matias D.; Titiunik, Rocío; Vazquez-Bare, Gonzalo

    2017-01-01

    The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The most common inference approaches in RD designs employ "flexible" parametric and nonparametric local polynomial methods, which rely on extrapolation and large-sample approximations of conditional expectations…

  15. Instructional Design and Online Learning: A Quality Assurance Study

    ERIC Educational Resources Information Center

    Monroe, Rose M.

    2011-01-01

    The purpose of this study was to investigate the difference in the evaluations of online course quality using the Quality Matters model among four groups of reviewers: instructional designers, faculty with subject-matter expertise, peer faculty with no subject-matter expertise, and administrators. A causal-comparative design was utilized to…

  16. Best Practices for Gauging Evidence of Causality in Air Pollution Epidemiology.

    PubMed

    Dominici, Francesca; Zigler, Corwin

    2017-12-15

    The contentious political climate surrounding air pollution regulations has brought some researchers and policy-makers to argue that evidence of causality is necessary before implementing more stringent regulations. Recently, investigators in an increasing number of air pollution studies have purported to have used "causal analysis," generating the impression that studies not explicitly labeled as such are merely "associational" and therefore less rigorous. Using 3 prominent air pollution studies as examples, we review good practices for how to critically evaluate the extent to which an air pollution study provides evidence of causality. We argue that evidence of causality should be gauged by a critical evaluation of design decisions such as 1) what actions or exposure levels are being compared, 2) whether an adequate comparison group was constructed, and 3) how closely these design decisions approximate an idealized randomized study. We argue that air pollution studies that are more scientifically rigorous in terms of the decisions made to approximate a randomized experiment are more likely to provide evidence of causality and should be prioritized among the body of evidence for regulatory review accordingly. Our considerations, although presented in the context of air pollution epidemiology, can be broadly applied to other fields of epidemiology. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. The Specification of Causal Models with Tetrad IV: A Review

    ERIC Educational Resources Information Center

    Landsheer, J. A.

    2010-01-01

    Tetrad IV is a program designed for the specification of causal models. It is specifically designed to search for causal relations, but also offers the possibility to estimate the parameters of a structural equation model. It offers a remarkable graphical user interface, which facilitates building, evaluating, and searching for causal models. The…

  18. Regression Discontinuity Design: A Guide for Strengthening Causal Inference in HRD

    ERIC Educational Resources Information Center

    Chambers, Silvana

    2016-01-01

    Purpose: Regression discontinuity (RD) design is a sophisticated quasi-experimental approach used for inferring causal relationships and estimating treatment effects. This paper aims to educate human resource development (HRD) researchers and practitioners on the implementation of RD design as an ethical alternative for making causal claims about…

  19. Framework for assessing causality in disease management programs: principles.

    PubMed

    Wilson, Thomas; MacDowell, Martin

    2003-01-01

    To credibly state that a disease management (DM) program "caused" a specific outcome it is required that metrics observed in the DM population be compared with metrics that would have been expected in the absence of a DM intervention. That requirement can be very difficult to achieve, and epidemiologists and others have developed guiding principles of causality by which credible estimates of DM impact can be made. This paper introduces those key principles. First, DM program metrics must be compared with metrics from a "reference population." This population should be "equivalent" to the DM intervention population on all factors that could independently impact the outcome. In addition, the metrics used in both groups should use the same defining criteria (ie, they must be "comparable" to each other). The degree to which these populations fulfill the "equivalent" assumption and metrics fulfill the "comparability" assumption should be stated. Second, when "equivalence" or "comparability" is not achieved, the DM managers should acknowledge this fact and, where possible, "control" for those factors that may impact the outcome(s). Finally, it is highly unlikely that one study will provide definitive proof of any specific DM program value for all time; thus, we strongly recommend that studies be ongoing, at multiple points in time, and at multiple sites, and, when observational study designs are employed, that more than one type of study design be utilized. Methodologically sophisticated studies that follow these "principles of causality" will greatly enhance the reputation of the important and growing efforts in DM.

  20. Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases.

    PubMed

    Wendling, T; Jung, K; Callahan, A; Schuler, A; Shah, N H; Gallego, B

    2018-06-03

    There is growing interest in using routinely collected data from health care databases to study the safety and effectiveness of therapies in "real-world" conditions, as it can provide complementary evidence to that of randomized controlled trials. Causal inference from health care databases is challenging because the data are typically noisy, high dimensional, and most importantly, observational. It requires methods that can estimate heterogeneous treatment effects while controlling for confounding in high dimensions. Bayesian additive regression trees, causal forests, causal boosting, and causal multivariate adaptive regression splines are off-the-shelf methods that have shown good performance for estimation of heterogeneous treatment effects in observational studies of continuous outcomes. However, it is not clear how these methods would perform in health care database studies where outcomes are often binary and rare and data structures are complex. In this study, we evaluate these methods in simulation studies that recapitulate key characteristics of comparative effectiveness studies. We focus on the conditional average effect of a binary treatment on a binary outcome using the conditional risk difference as an estimand. To emulate health care database studies, we propose a simulation design where real covariate and treatment assignment data are used and only outcomes are simulated based on nonparametric models of the real outcomes. We apply this design to 4 published observational studies that used records from 2 major health care databases in the United States. Our results suggest that Bayesian additive regression trees and causal boosting consistently provide low bias in conditional risk difference estimates in the context of health care database studies. Copyright © 2018 John Wiley & Sons, Ltd.

  1. Small Learning Communities Sense of Belonging to Reach At-Risk Students of Promise

    ERIC Educational Resources Information Center

    Hackney, Debbie

    2011-01-01

    The research design is a quantitative causal comparative method. The Florida Comprehensive Assessment Test (FCAT) which measures student scores included assessments in mathematics and reading. The design study called for an examination of how type of small learning community (SLC) or the type non-SLC high school environment affected student…

  2. A Comparative Study of Academic Achievement and Participation in a High School Freshman Academy

    ERIC Educational Resources Information Center

    Seng, Mark Patrick

    2014-01-01

    The transition to high school can be problematic for many ninth graders. Researchers and administrators have sought ways to improve academic performance and promotion rates while reducing dropout rates. A quantitative causal-comparative (ex post facto) and correlation study using a two-group design compared two freshman classes at separate…

  3. Applying causal mediation analysis to personality disorder research.

    PubMed

    Walters, Glenn D

    2018-01-01

    This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  4. Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships.

    PubMed

    Rassen, Jeremy A; Brookhart, M Alan; Glynn, Robert J; Mittleman, Murray A; Schneeweiss, Sebastian

    2009-12-01

    The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of "exchangeability" between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects.

  5. Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships

    PubMed Central

    Rassen, Jeremy A.; Brookhart, M. Alan; Glynn, Robert J.; Mittleman, Murray A.; Schneeweiss, Sebastian

    2010-01-01

    The gold standard of study design for treatment evaluation is widely acknowledged to be the randomized controlled trial (RCT). Trials allow for the estimation of causal effect by randomly assigning participants either to an intervention or comparison group; through the assumption of “exchangeability” between groups, comparing the outcomes will yield an estimate of causal effect. In the many cases where RCTs are impractical or unethical, instrumental variable (IV) analysis offers a nonexperimental alternative based on many of the same principles. IV analysis relies on finding a naturally varying phenomenon, related to treatment but not to outcome except through the effect of treatment itself, and then using this phenomenon as a proxy for the confounded treatment variable. This article demonstrates how IV analysis arises from an analogous but potentially impossible RCT design, and outlines the assumptions necessary for valid estimation. It gives examples of instruments used in clinical epidemiology and concludes with an outline on estimation of effects. PMID:19356901

  6. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II.

    PubMed

    Cox, Emily; Martin, Bradley C; Van Staa, Tjeerd; Garbe, Edeltraut; Siebert, Uwe; Johnson, Michael L

    2009-01-01

    The goal of comparative effectiveness analysis is to examine the relationship between two variables, treatment, or exposure and effectiveness or outcome. Unlike data obtained through randomized controlled trials, researchers face greater challenges with causal inference with observational studies. Recognizing these challenges, a task force was formed to develop a guidance document on methodological approaches to addresses these biases. The task force was commissioned and a Chair was selected by the International Society for Pharmacoeconomics and Outcomes Research Board of Directors in October 2007. This report, the second of three reported in this issue of the Journal, discusses the inherent biases when using secondary data sources for comparative effectiveness analysis and provides methodological recommendations to help mitigate these biases. The task force report provides recommendations and tools for researchers to mitigate threats to validity from bias and confounding in measurement of exposure and outcome. Recommendations on design of study included: the need for data analysis plan with causal diagrams; detailed attention to classification bias in definition of exposure and clinical outcome; careful and appropriate use of restriction; extreme care to identify and control for confounding factors, including time-dependent confounding. Design of nonrandomized studies of comparative effectiveness face several daunting issues, including measurement of exposure and outcome challenged by misclassification and confounding. Use of causal diagrams and restriction are two techniques that can improve the theoretical basis for analyzing treatment effects in study populations of more homogeneity, with reduced loss of generalizability.

  7. Graphical Models for Quasi-Experimental Designs

    ERIC Educational Resources Information Center

    Steiner, Peter M.; Kim, Yongnam; Hall, Courtney E.; Su, Dan

    2017-01-01

    Randomized controlled trials (RCTs) and quasi-experimental designs like regression discontinuity (RD) designs, instrumental variable (IV) designs, and matching and propensity score (PS) designs are frequently used for inferring causal effects. It is well known that the features of these designs facilitate the identification of a causal estimand…

  8. Comparing Distance vs. Campus-Based Delivery of Research Methods Courses

    ERIC Educational Resources Information Center

    Girod, Mark; Wojcikiewicz, Steve

    2009-01-01

    A causal-comparative pre-test, post-test design was used to investigate differences in learning in a research methods course for face-to-face and web-based delivery models. Analyses of participant achievement (N = 205) revealed almost no differences but post-hoc analyses revealed important differences in pedagogy between delivery models despite…

  9. Factors Influencing Teacher Absenteeism in a Middle Tennessee School System

    ERIC Educational Resources Information Center

    Shockley, Kristy

    2012-01-01

    Using a causal-comparative research design, this study analyzed and compared absence data of teachers in relation to specific teacher demographics to determine if certain teachers were more susceptible to absenteeism than others. Additionally, school level placement and whether or not a teacher was teaching in a Title I school were analyzed to…

  10. The Effects of Differentiated Instruction Support Inclusion Services on Fifth Grade Reading/Language Arts Achievement

    ERIC Educational Resources Information Center

    Wendt, Stephanie L.

    2012-01-01

    Using a causal-comparative research design, this study investigated the effectiveness of Differentiated Instruction Support Inclusion Services on fifth grade regular education and gifted students' Reading/Language Arts achievement. The study analyzed and compared the achievement of the regular education students who received no inclusion support…

  11. Effect of Instructional Design on Academic Success of Adult Basic Education Learners: Individualized versus Group Design

    ERIC Educational Resources Information Center

    Frazier Varner, Debrah

    2010-01-01

    Many adult basic education (ABE) programs do not achieve a high success rate in meeting student academic needs. Rooted in Knowles' theory of andragogy and Bandura's theory of modeling, this quantitative causal comparative study examined the effects of individualized instruction (IGI) and of facilitated, participatory group programs (SPOKES) on the…

  12. Reducing Bias and Increasing Precision by Adding Either a Pretest Measure of the Study Outcome or a Nonequivalent Comparison Group to the Basic Regression Discontinuity Design: An Example from Education

    ERIC Educational Resources Information Center

    Tang, Yang; Cook, Thomas D.; Kisbu-Sakarya, Yasemin

    2015-01-01

    Regression discontinuity design (RD) has been widely used to produce reliable causal estimates. Researchers have validated the accuracy of RD design using within study comparisons (Cook, Shadish & Wong, 2008; Cook & Steiner, 2010; Shadish et al, 2011). Within study comparisons examines the validity of a quasi-experiment by comparing its…

  13. High School Learning Environments: Hybrid versus Traditional Formats

    ERIC Educational Resources Information Center

    Clifton, Mary Beth

    2017-01-01

    This research study examined the effects of hybrid course format as compared to face-to-face instruction format in a high school setting. At this time, there is little research on hybrid courses in the secondary schools. The quantitative portion of this ex post facto study utilized causal comparative design. Student data was collected from teacher…

  14. Comparing Types of Student Placement and the Effect on Achievement for Students with Disabilities

    ERIC Educational Resources Information Center

    Mason, Patricia Lynn

    2013-01-01

    Since implementing No Child Left Behind, schools have improved student achievement while also preparing students for the 21st century. Schools continue to strive for 100% proficiency in all subgroups by 2014, but achievement gap exists for students with disabilities. This study used a causal comparative research design to test the concept of…

  15. The Effects of an Academic Alternative High School on Academically At-Risk Students

    ERIC Educational Resources Information Center

    Winningham, Mark L.

    2012-01-01

    In a causal-comparative research design, this study investigated the effectiveness of an academic alternative school in improving at-risk student outcomes in a selected county school system in the Upper Cumberland region of Tennessee. The academic alternative high school was compared to a traditional high school serving at-risk populations.…

  16. Designing Effective Supports for Causal Reasoning

    ERIC Educational Resources Information Center

    Jonassen, David H.; Ionas, Ioan Gelu

    2008-01-01

    Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…

  17. Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review.

    PubMed

    Haber, Noah; Smith, Emily R; Moscoe, Ellen; Andrews, Kathryn; Audy, Robin; Bell, Winnie; Brennan, Alana T; Breskin, Alexander; Kane, Jeremy C; Karra, Mahesh; McClure, Elizabeth S; Suarez, Elizabeth A

    2018-01-01

    The pathway from evidence generation to consumption contains many steps which can lead to overstatement or misinformation. The proliferation of internet-based health news may encourage selection of media and academic research articles that overstate strength of causal inference. We investigated the state of causal inference in health research as it appears at the end of the pathway, at the point of social media consumption. We screened the NewsWhip Insights database for the most shared media articles on Facebook and Twitter reporting about peer-reviewed academic studies associating an exposure with a health outcome in 2015, extracting the 50 most-shared academic articles and media articles covering them. We designed and utilized a review tool to systematically assess and summarize studies' strength of causal inference, including generalizability, potential confounders, and methods used. These were then compared with the strength of causal language used to describe results in both academic and media articles. Two randomly assigned independent reviewers and one arbitrating reviewer from a pool of 21 reviewers assessed each article. We accepted the most shared 64 media articles pertaining to 50 academic articles for review, representing 68% of Facebook and 45% of Twitter shares in 2015. Thirty-four percent of academic studies and 48% of media articles used language that reviewers considered too strong for their strength of causal inference. Seventy percent of academic studies were considered low or very low strength of inference, with only 6% considered high or very high strength of causal inference. The most severe issues with academic studies' causal inference were reported to be omitted confounding variables and generalizability. Fifty-eight percent of media articles were found to have inaccurately reported the question, results, intervention, or population of the academic study. We find a large disparity between the strength of language as presented to the research consumer and the underlying strength of causal inference among the studies most widely shared on social media. However, because this sample was designed to be representative of the articles selected and shared on social media, it is unlikely to be representative of all academic and media work. More research is needed to determine how academic institutions, media organizations, and social network sharing patterns impact causal inference and language as received by the research consumer.

  18. Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review

    PubMed Central

    Smith, Emily R.; Moscoe, Ellen; Audy, Robin; Bell, Winnie; Brennan, Alana T.; Breskin, Alexander; Kane, Jeremy C.; Suarez, Elizabeth A.

    2018-01-01

    Background The pathway from evidence generation to consumption contains many steps which can lead to overstatement or misinformation. The proliferation of internet-based health news may encourage selection of media and academic research articles that overstate strength of causal inference. We investigated the state of causal inference in health research as it appears at the end of the pathway, at the point of social media consumption. Methods We screened the NewsWhip Insights database for the most shared media articles on Facebook and Twitter reporting about peer-reviewed academic studies associating an exposure with a health outcome in 2015, extracting the 50 most-shared academic articles and media articles covering them. We designed and utilized a review tool to systematically assess and summarize studies’ strength of causal inference, including generalizability, potential confounders, and methods used. These were then compared with the strength of causal language used to describe results in both academic and media articles. Two randomly assigned independent reviewers and one arbitrating reviewer from a pool of 21 reviewers assessed each article. Results We accepted the most shared 64 media articles pertaining to 50 academic articles for review, representing 68% of Facebook and 45% of Twitter shares in 2015. Thirty-four percent of academic studies and 48% of media articles used language that reviewers considered too strong for their strength of causal inference. Seventy percent of academic studies were considered low or very low strength of inference, with only 6% considered high or very high strength of causal inference. The most severe issues with academic studies’ causal inference were reported to be omitted confounding variables and generalizability. Fifty-eight percent of media articles were found to have inaccurately reported the question, results, intervention, or population of the academic study. Conclusions We find a large disparity between the strength of language as presented to the research consumer and the underlying strength of causal inference among the studies most widely shared on social media. However, because this sample was designed to be representative of the articles selected and shared on social media, it is unlikely to be representative of all academic and media work. More research is needed to determine how academic institutions, media organizations, and social network sharing patterns impact causal inference and language as received by the research consumer. PMID:29847549

  19. Preschool Children Learn about Causal Structure from Conditional Interventions

    ERIC Educational Resources Information Center

    Schulz, Laura E.; Gopnik, Alison; Glymour, Clark

    2007-01-01

    The conditional intervention principle is a formal principle that relates patterns of interventions and outcomes to causal structure. It is a central assumption of experimental design and the causal Bayes net formalism. Two studies suggest that preschoolers can use the conditional intervention principle to distinguish causal chains, common cause…

  20. The Impact of Project-Based Learning on Minority Student Achievement: Implications for School Redesign

    ERIC Educational Resources Information Center

    Cervantes, Bernadine; Hemmer, Lynn; Kouzekanani, Kamiar

    2015-01-01

    Project-Based Learning (PBL) serves as an instructional approach to classroom teaching and learning that is designed to engage students in the investigation of real-world problems to create meaningful and relevant educational experiences. The causal-comparative study compared 7th and 8th students who had utilized the PBL with a comparison group in…

  1. A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs

    ERIC Educational Resources Information Center

    Karabatsos, George; Walker, Stephen G.

    2013-01-01

    The regression discontinuity (RD) design (Thistlewaite & Campbell, 1960; Cook, 2008) provides a framework to identify and estimate causal effects from a non-randomized design. Each subject of a RD design is assigned to the treatment (versus assignment to a non-treatment) whenever her/his observed value of the assignment variable equals or…

  2. Afro-Caribbean and African American Students, Family Factors, and the Influence on Science Performance in the United States: The Untold Story

    ERIC Educational Resources Information Center

    Pinder, Patrice Juliet

    2012-01-01

    The primary objectives of this research were to explore achievement pattern differences and the influence of family factors on the achievement patterns of Afro-Caribbean and African American students within the United States (U.S.). The study utilized two research designs; a causal-comparative and a correlational design. A student family…

  3. Empirical Assessment of Effect of Publication Bias on a Meta-Analysis of Validity Studies on University Matriculation Examinations in Nigeria

    ERIC Educational Resources Information Center

    Adeyemo, Emily Oluseyi

    2012-01-01

    This study examined the impact of publication bias on a meta-analysis of empirical studies on validity of University Matriculation Examinations in Nigeria with a view to determine the level of difference between published and unpublished articles. Specifically, the design was an ex-post facto, a causal comparative design. The sample size consisted…

  4. A social impact assessment of the floodwater spreading project on the Gareh-Bygone plain in Iran: A causal comparative approach

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ahmadvand, Mostafa; Karami, Ezatollah

    2009-02-15

    The purpose of this study was to explore the social impacts of the floodwater spreading project (FWSP) on the Gareh-Bygone plain, Iran. The study was in the form of a causal comparative design, and a triangulation technique was used to collect data including the use of survey data, archival data, and a participatory rural appraisal (PRA). The causal comparative method requires a comparison of villages with and without the FWSP. Therefore, a survey was conducted using stratified random sampling to select 202 households in villages with and without FWSP in the plain. Significant differences were found between the respondents inmore » villages with and without FWSP with regard to social impact criteria. In spite of the project had negative impact on perceived wellbeing, social capital, social structure development; it had positive impact on quality of life, rural and agricultural economic conditions, and conservation of community resources. However, no significant difference was found between women and men regarding the SIA of FWSP in Gareh-Bygone plain. Analysis of the archival data and PRA techniques supported the survey results and demonstrated that the project improved environmental criteria and deteriorated social dimensions.« less

  5. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption.

    PubMed

    Hartwig, Fernando Pires; Davey Smith, George; Bowden, Jack

    2017-12-01

    Mendelian randomization (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic associations for a variety of phenotypes from large genome-wide association studies (GWAS) allows straightforward application of MR using summary data methods, typically in a two-sample design. In addition to the conventional inverse variance weighting (IVW) method, recently developed summary data MR methods, such as the MR-Egger and weighted median approaches, allow a relaxation of the instrumental variable assumptions. Here, a new method - the mode-based estimate (MBE) - is proposed to obtain a single causal effect estimate from multiple genetic instruments. The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid. We evaluate the performance of the method in simulations designed to mimic the two-sample summary data setting, and demonstrate its use by investigating the causal effect of plasma lipid fractions and urate levels on coronary heart disease risk. The MBE presented less bias and lower type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared with the IVW and weighted median methods, but was larger than that of MR-Egger regression, with sample size requirements typically smaller than those available from GWAS consortia. The MBE relaxes the instrumental variable assumptions, and should be used in combination with other approaches in sensitivity analyses. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association

  6. Causal inference, probability theory, and graphical insights.

    PubMed

    Baker, Stuart G

    2013-11-10

    Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design. Published 2013. This article is a US Government work and is in the public domain in the USA.

  7. Automated Writing Evaluation Program's Effect on Student Writing Achievement

    ERIC Educational Resources Information Center

    Holman, Lester Donnie

    2011-01-01

    In an ex post facto causal-comparative research design, this study investigated the effectiveness of Automated Writing Evaluation (AWE) programs on raising the student writing achievement. Tennessee Comprehensive Assessment Program (TCAP) writing achievement scores from the 2010 administration were utilized for this study. The independent variable…

  8. Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes.

    PubMed

    Kim, Na Young; Wittenberg, Ellen; Nam, Chang S

    2017-01-01

    This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time) and neurophysiological (P300 amplitude and alpha band power) metrics on the inhibition task (i.e., flanker task) were influenced by the updating load (n-back level) and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT), and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels) and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

  9. The Relationship between Principal Leadership Practices and Teacher Morale

    ERIC Educational Resources Information Center

    Williams, Fabre K.

    2013-01-01

    This research explores the relationship of principal leadership practices and teacher morale. Six schools in a West Tennessee school system participated in the study. The participants in the study were executive principals and classroom teachers. The study was a descriptive, causal-comparative research design chosen to examine the possible…

  10. Student Participation in Dual Enrollment and College Success

    ERIC Educational Resources Information Center

    Jones, Stephanie J.

    2014-01-01

    The study investigated the impact of dual enrollment participation on the academic preparation of first-year full-time college students at a large comprehensive community college and a large research university. The research design was causal-comparative and utilized descriptive and inferential statistics. Multivariate analysis of variances were…

  11. Effects of a Math Intervention Program on Math Academic Performance among African American Students

    ERIC Educational Resources Information Center

    Johnson, Willie F., Jr.

    2013-01-01

    In the United States, an academic achievement gap has prevented many African American students from advancement and educational empowerment. Guided by Bandura's theoretical belief, which posits a relationship between social factors and an individual's perception, this non-experimental, causal comparative, control treatment group design study…

  12. Teaching Perspectives and Usage of Journal Writing by Clinical Faculty

    ERIC Educational Resources Information Center

    Alschuler, Mari L.

    2012-01-01

    The purpose of this study was to investigate the associations between teaching perspectives (TPs), faculty usage and perceptions of reflective journaling (RJ), and demographic characteristics among clinical faculty in nursing, social work, and counseling. A combination of causal-comparative and correlational designs was utilized, with stratified…

  13. The Effects of Write Score Formative Assessment on Student Achievement

    ERIC Educational Resources Information Center

    Fox, Janice M.

    2013-01-01

    In an "ex post facto" causal-comparative research design, this study investigated the effectiveness of a formative writing assessment program, Write Score, on increasing student writing achievement. Tennessee Comprehensive Assessment Program (TCAP) reading language arts and writing scores from 2012 were utilized for this study. The…

  14. The Influence of Mother Tongue and Gender on the Acquisition of English (L2). The Case of Afrikaans in Windhoek Schools, Namibia

    ERIC Educational Resources Information Center

    van Wyk, Jacolynn; Mostert, Maria Louise

    2016-01-01

    This study investigated the effect of mother tongue instruction and gender on second language acquisition using a causal-comparative quantitative research design. The two distinguishing groups compared were (i) learners that were taught in their mother tongue (Afrikaans) and (ii) learners that were not taught in their mother tongue but in English,…

  15. Failures of explaining away and screening off in described versus experienced causal learning scenarios.

    PubMed

    Rehder, Bob; Waldmann, Michael R

    2017-02-01

    Causal Bayes nets capture many aspects of causal thinking that set them apart from purely associative reasoning. However, some central properties of this normative theory routinely violated. In tasks requiring an understanding of explaining away and screening off, subjects often deviate from these principles and manifest the operation of an associative bias that we refer to as the rich-get-richer principle. This research focuses on these two failures comparing tasks in which causal scenarios are merely described (via verbal statements of the causal relations) versus experienced (via samples of data that manifest the intervariable correlations implied by the causal relations). Our key finding is that we obtained stronger deviations from normative predictions in the described conditions that highlight the instructed causal model compared to those that presented data. This counterintuitive finding indicate that a theory of causal reasoning and learning needs to integrate normative principles with biases people hold about causal relations.

  16. Designing effective animations for computer science instruction

    NASA Astrophysics Data System (ADS)

    Grillmeyer, Oliver

    This study investigated the potential for animations of Scheme functions to help novice computer science students understand difficult programming concepts. These animations used an instructional framework inspired by theories of constructivism and knowledge integration. The framework had students make predictions, reflect, and specify examples to animate to promote autonomous learning and result in more integrated knowledge. The framework used animated pivotal cases to help integrate disconnected ideas and restructure students' incomplete ideas by illustrating weaknesses in their existing models. The animations scaffolded learners, making the thought processes of experts more visible by modeling complex and tacit information. The animation design was guided by prior research and a methodology of design and refinement. Analysis of pilot studies led to the development of four design concerns to aid animation designers: clearly illustrate the mapping between objects in animations with the actual objects they represent, show causal connections between elements, draw attention to the salient features of the modeled system, and create animations that reduce complexity. Refined animations based on these design concerns were compared to computer-based tools, text-based instruction, and simpler animations that do not embody the design concerns. Four studies comprised this dissertation work. Two sets of animated presentations of list creation functions were compared to control groups. No significant differences were found in support of animations. Three different animated models of traces of recursive functions ranging from concrete to abstract representations were compared. No differences in learning gains were found between the three models in test performance. Three models of animations of applicative operators were compared with students using the replacement modeler and the Scheme interpreter. Significant differences were found favoring animations that addressed causality and salience in their design. Lastly, two binary tree search algorithm animations designed to reduce complexity were compared with hand-tracing of calls. Students made fewer mistakes in predicting the tree traversal when guided by the animations. However, the posttest findings were inconsistent. In summary, animations designed based on the design concerns did not consistently add value to instruction in the form investigated in this research.

  17. City Connects: Building an Argument for Effects on Student Achievement with a Quasi-Experimental Design

    ERIC Educational Resources Information Center

    Walsh, Mary; Raczek, Anastasia; Sibley, Erin; Lee-St. John, Terrence; An, Chen; Akbayin, Bercem; Dearing, Eric; Foley, Claire

    2015-01-01

    While randomized experimental designs are the gold standard in education research concerned with causal inference, non-experimental designs are ubiquitous. For researchers who work with non-experimental data and are no less concerned for causal inference, the major problem is potential omitted variable bias. In this presentation, the authors…

  18. Experimental Design and Some Threats to Experimental Validity: A Primer

    ERIC Educational Resources Information Center

    Skidmore, Susan

    2008-01-01

    Experimental designs are distinguished as the best method to respond to questions involving causality. The purpose of the present paper is to explicate the logic of experimental design and why it is so vital to questions that demand causal conclusions. In addition, types of internal and external validity threats are discussed. To emphasize the…

  19. [Clinical research. XIII. Research design contribution in the structured revision of an article].

    PubMed

    Talavera, Juan O; Rivas-Ruiz, Rodolfo

    2013-01-01

    The quality of information obtained in accordance to research design is integrated to the revision structured in relation to the causality model, used in the article "Reduction in the Incidence of Nosocomial Pneumonia Poststroke by Using the 'Turn-mob' Program", which corresponds to a clinical trial design. Points to identify and analyze are ethical issues in order to safeguard the security and respect for patients, randomization that seek to create basal homogeneous groups, subjects with the same probability of receiving any of the maneuvers in comparison, with the same pre maneuver probability of adherence, and which facilitate the blinding of outcome measurement and the distribution between groups of subjects with the same probability of leaving the study for reasons beyond the maneuvers. Other aspects are the relativity of comparison, the blinding of the maneuver, the parallel application of comparative maneuver, early stopping, and analysis according to the degree of adherence. The analysis in accordance with the design is complementary, since it is done based on the architectural model of causality, and the statistical and clinical relevance consideration.

  20. Inferential reasoning by exclusion in children (Homo sapiens).

    PubMed

    Hill, Andrew; Collier-Baker, Emma; Suddendorf, Thomas

    2012-08-01

    The cups task is the most widely adopted forced-choice paradigm for comparative studies of inferential reasoning by exclusion. In this task, subjects are presented with two cups, one of which has been surreptitiously baited. When the empty cup is shaken or its interior shown, it is possible to infer by exclusion that the alternative cup contains the reward. The present study extends the existing body of comparative work to include human children (Homo sapiens). Like chimpanzees (Pan troglodytes) that were tested with the same equipment and near-identical procedures, children aged three to five made apparent inferences using both visual and auditory information, although the youngest children showed the least-developed ability in the auditory modality. However, unlike chimpanzees, children of all ages used causally irrelevant information in a control test designed to examine the possibility that their apparent auditory inferences were the product of contingency learning (the duplicate cups test). Nevertheless, the children's ability to reason by exclusion was corroborated by their performance on a novel verbal disjunctive syllogism test, and we found preliminary evidence consistent with the suggestion that children used their causal-logical understanding to reason by exclusion in the cups task, but subsequently treated the duplicate cups information as symbolic or communicative, rather than causal. Implications for future comparative research are discussed. 2012 APA, all rights reserved

  1. The Relationship between Teaching Presence and Student Course Outcomes in an Online International Population

    ERIC Educational Resources Information Center

    Wendt, Jillian; Courduff, Jennifer

    2018-01-01

    A causal comparative research design was utilized in this study to examine the relationship between international students' perceptions of teacher presence in the online learning environment and students' achievement as measured by end of course grades. Spearman's analysis indicated no statistically significant correlation between the composite…

  2. The Effect of Single Gender Instruction on Eighth Grade Students' Mathematics Achievement

    ERIC Educational Resources Information Center

    Hammel, David Michael

    2013-01-01

    In the research study, this investigator utilized a non-experimental, causal-comparative design (ex post facto) with archival data to determine the real impact single gender instruction had on eighth grade students' mathematics achievement. The purpose of this study was to quantitatively analyze the benefits of single gender mathematics…

  3. From "At Risk" to "At Promise": An Evaluation of an Early Reading First Project

    ERIC Educational Resources Information Center

    Zoll, Susan Marie

    2012-01-01

    This study demonstrates the impact of an Early Reading First intervention on preschool children's language and literacy development using an ex post facto, causal-comparative research design. The project's professional development model was evaluated to produce a process and outcome evaluation to answer two overarching research questions: (1) What…

  4. The Effects of Curriculum Integration on the Academic Achievement of Secondary Career and Technical Students

    ERIC Educational Resources Information Center

    Jones, Patricia Anders

    2012-01-01

    Using a causal-comparative design, this quantitative study investigated whether or not the curriculum integration of academic subjects with career and technical education classes affected secondary students' academic performance as assessed by scores on standardized tests. The purposive sample was drawn from students in Trade and Industry classes…

  5. Ethnic Differences in Completion Rates as a Function of School Size in Texas High Schools

    ERIC Educational Resources Information Center

    Fitzgerald, Kim; Gordon, Teandra; Canty, Antoinette; Stitt, Ruth E.; Onwuegbuzie, Anthony J.; Frels, Rebecca K.

    2013-01-01

    The purpose of this study was to investigate differences in high school completion rates among White, African American, and Hispanic students enrolled in different school sizes--small, medium, and large. For this causal-comparative research design, this study utilized archival data from the Texas Education Association's Academic Excellence…

  6. Design approaches to experimental mediation☆

    PubMed Central

    Pirlott, Angela G.; MacKinnon, David P.

    2016-01-01

    Identifying causal mechanisms has become a cornerstone of experimental social psychology, and editors in top social psychology journals champion the use of mediation methods, particularly innovative ones when possible (e.g. Halberstadt, 2010, Smith, 2012). Commonly, studies in experimental social psychology randomly assign participants to levels of the independent variable and measure the mediating and dependent variables, and the mediator is assumed to causally affect the dependent variable. However, participants are not randomly assigned to levels of the mediating variable(s), i.e., the relationship between the mediating and dependent variables is correlational. Although researchers likely know that correlational studies pose a risk of confounding, this problem seems forgotten when thinking about experimental designs randomly assigning participants to levels of the independent variable and measuring the mediator (i.e., “measurement-of-mediation” designs). Experimentally manipulating the mediator provides an approach to solving these problems, yet these methods contain their own set of challenges (e.g., Bullock, Green, & Ha, 2010). We describe types of experimental manipulations targeting the mediator (manipulations demonstrating a causal effect of the mediator on the dependent variable and manipulations targeting the strength of the causal effect of the mediator) and types of experimental designs (double randomization, concurrent double randomization, and parallel), provide published examples of the designs, and discuss the strengths and challenges of each design. Therefore, the goals of this paper include providing a practical guide to manipulation-of-mediator designs in light of their challenges and encouraging researchers to use more rigorous approaches to mediation because manipulation-of-mediator designs strengthen the ability to infer causality of the mediating variable on the dependent variable. PMID:27570259

  7. Design approaches to experimental mediation.

    PubMed

    Pirlott, Angela G; MacKinnon, David P

    2016-09-01

    Identifying causal mechanisms has become a cornerstone of experimental social psychology, and editors in top social psychology journals champion the use of mediation methods, particularly innovative ones when possible (e.g. Halberstadt, 2010, Smith, 2012). Commonly, studies in experimental social psychology randomly assign participants to levels of the independent variable and measure the mediating and dependent variables, and the mediator is assumed to causally affect the dependent variable. However, participants are not randomly assigned to levels of the mediating variable(s), i.e., the relationship between the mediating and dependent variables is correlational. Although researchers likely know that correlational studies pose a risk of confounding, this problem seems forgotten when thinking about experimental designs randomly assigning participants to levels of the independent variable and measuring the mediator (i.e., "measurement-of-mediation" designs). Experimentally manipulating the mediator provides an approach to solving these problems, yet these methods contain their own set of challenges (e.g., Bullock, Green, & Ha, 2010). We describe types of experimental manipulations targeting the mediator (manipulations demonstrating a causal effect of the mediator on the dependent variable and manipulations targeting the strength of the causal effect of the mediator) and types of experimental designs (double randomization, concurrent double randomization, and parallel), provide published examples of the designs, and discuss the strengths and challenges of each design. Therefore, the goals of this paper include providing a practical guide to manipulation-of-mediator designs in light of their challenges and encouraging researchers to use more rigorous approaches to mediation because manipulation-of-mediator designs strengthen the ability to infer causality of the mediating variable on the dependent variable.

  8. Experimental verification of an indefinite causal order

    PubMed Central

    Rubino, Giulia; Rozema, Lee A.; Feix, Adrien; Araújo, Mateus; Zeuner, Jonas M.; Procopio, Lorenzo M.; Brukner, Časlav; Walther, Philip

    2017-01-01

    Investigating the role of causal order in quantum mechanics has recently revealed that the causal relations of events may not be a priori well defined in quantum theory. Although this has triggered a growing interest on the theoretical side, creating processes without a causal order is an experimental task. We report the first decisive demonstration of a process with an indefinite causal order. To do this, we quantify how incompatible our setup is with a definite causal order by measuring a “causal witness.” This mathematical object incorporates a series of measurements that are designed to yield a certain outcome only if the process under examination is not consistent with any well-defined causal order. In our experiment, we perform a measurement in a superposition of causal orders—without destroying the coherence—to acquire information both inside and outside of a “causally nonordered process.” Using this information, we experimentally determine a causal witness, demonstrating by almost 7 SDs that the experimentally implemented process does not have a definite causal order. PMID:28378018

  9. Transformational Leadership, Transactional Contingent Reward, and Organizational Identification: The Mediating Effect of Perceived Innovation and Goal Culture Orientations.

    PubMed

    Xenikou, Athena

    2017-01-01

    Purpose: The aim of this research was to investigate the effect of transformational leadership and transactional contingent reward as complementary, but distinct, forms of leadership on facets of organizational identification via the perception of innovation and goal organizational values. Design/Methodology/Approach: Three studies were carried out implementing either a measurement of mediation or experimental-causal-chain design to test for the hypothesized effects. Findings: The measurement of mediation study showed that transformational leadership had a positive direct and indirect effect, via innovation value orientation, on cognitive identification, whereas transactional contingent reward was more strongly related to affective, rather than cognitive, identification, and goal orientation was a mediator of their link. The findings of the two experimental-causal-chain studies further supported the hypothesized effects. Transformational leadership was found to lead subordinates to perceive the culture as more innovative compared to transactional contingent reward, whereas transactional contingent reward led employees to perceive the culture as more goal, than innovation, oriented. Finally, innovation, compared to goal, value orientation increased cognitive identification, while goal orientation facilitated affective, rather than cognitive, identification. Implications: The practical implications involve the development of strategies organizations can apply, such as leadership training programs, to strengthen their ties with their employees, which, in turn, may have a positive impact on in-role, as well as extra-role, behaviors. Originality/Value: The originality of this research concerns the identification of distinct mechanisms explaining the effect of transformational leadership and transactional contingent reward on cognitive and affective identification applying an organizational culture perspective and a combination of measurement and causal mediation designs.

  10. Transformational Leadership, Transactional Contingent Reward, and Organizational Identification: The Mediating Effect of Perceived Innovation and Goal Culture Orientations

    PubMed Central

    Xenikou, Athena

    2017-01-01

    Purpose: The aim of this research was to investigate the effect of transformational leadership and transactional contingent reward as complementary, but distinct, forms of leadership on facets of organizational identification via the perception of innovation and goal organizational values. Design/Methodology/Approach: Three studies were carried out implementing either a measurement of mediation or experimental-causal-chain design to test for the hypothesized effects. Findings: The measurement of mediation study showed that transformational leadership had a positive direct and indirect effect, via innovation value orientation, on cognitive identification, whereas transactional contingent reward was more strongly related to affective, rather than cognitive, identification, and goal orientation was a mediator of their link. The findings of the two experimental-causal-chain studies further supported the hypothesized effects. Transformational leadership was found to lead subordinates to perceive the culture as more innovative compared to transactional contingent reward, whereas transactional contingent reward led employees to perceive the culture as more goal, than innovation, oriented. Finally, innovation, compared to goal, value orientation increased cognitive identification, while goal orientation facilitated affective, rather than cognitive, identification. Implications: The practical implications involve the development of strategies organizations can apply, such as leadership training programs, to strengthen their ties with their employees, which, in turn, may have a positive impact on in-role, as well as extra-role, behaviors. Originality/Value: The originality of this research concerns the identification of distinct mechanisms explaining the effect of transformational leadership and transactional contingent reward on cognitive and affective identification applying an organizational culture perspective and a combination of measurement and causal mediation designs. PMID:29093688

  11. Designs of Empirical Evaluations of Nonexperimental Methods in Field Settings.

    PubMed

    Wong, Vivian C; Steiner, Peter M

    2018-01-01

    Over the last three decades, a research design has emerged to evaluate the performance of nonexperimental (NE) designs and design features in field settings. It is called the within-study comparison (WSC) approach or the design replication study. In the traditional WSC design, treatment effects from a randomized experiment are compared to those produced by an NE approach that shares the same target population. The nonexperiment may be a quasi-experimental design, such as a regression-discontinuity or an interrupted time-series design, or an observational study approach that includes matching methods, standard regression adjustments, and difference-in-differences methods. The goals of the WSC are to determine whether the nonexperiment can replicate results from a randomized experiment (which provides the causal benchmark estimate), and the contexts and conditions under which these methods work in practice. This article presents a coherent theory of the design and implementation of WSCs for evaluating NE methods. It introduces and identifies the multiple purposes of WSCs, required design components, common threats to validity, design variants, and causal estimands of interest in WSCs. It highlights two general approaches for empirical evaluations of methods in field settings, WSC designs with independent and dependent benchmark and NE arms. This article highlights advantages and disadvantages for each approach, and conditions and contexts under which each approach is optimal for addressing methodological questions.

  12. Feature Inference and the Causal Structure of Categories

    ERIC Educational Resources Information Center

    Rehder, B.; Burnett, R.C.

    2005-01-01

    The purpose of this article was to establish how theoretical category knowledge-specifically, knowledge of the causal relations that link the features of categories-supports the ability to infer the presence of unobserved features. Our experiments were designed to test proposals that causal knowledge is represented psychologically as Bayesian…

  13. Learning What Works in Sensory Disabilities: Establishing Causal Inference

    ERIC Educational Resources Information Center

    Cooney, John B.; Young, John, III; Luckner, John L.; Ferrell, Kay Alicyn

    2015-01-01

    This article is intended to assist teachers and researchers in designing studies that examine the efficacy of a particular intervention or strategy with students with sensory disabilities. Ten research designs that can establish causal inference (the ability to attribute any effects to the intervention) with and without randomization are discussed.

  14. Research designs and making causal inferences from health care studies.

    PubMed

    Flannelly, Kevin J; Jankowski, Katherine R B

    2014-01-01

    This article summarizes the major types of research designs used in healthcare research, including experimental, quasi-experimental, and observational studies. Observational studies are divided into survey studies (descriptive and correlational studies), case-studies and analytic studies, the last of which are commonly used in epidemiology: case-control, retrospective cohort, and prospective cohort studies. Similarities and differences among the research designs are described and the relative strength of evidence they provide is discussed. Emphasis is placed on five criteria for drawing causal inferences that are derived from the writings of the philosopher John Stuart Mill, especially his methods or canons. The application of the criteria to experimentation is explained. Particular attention is given to the degree to which different designs meet the five criteria for making causal inferences. Examples of specific studies that have used various designs in chaplaincy research are provided.

  15. Examining How Professional Development Impacted Teachers and Students of U.S. History Courses

    ERIC Educational Resources Information Center

    Duffield, Stacy; Wageman, Justin; Hodge, Angela

    2013-01-01

    A causal-comparative, mixed methods design was used to study a partnership between a university and school district formed with the goal of improving history teachers' United States history content knowledge to raise student engagement and achievement. Data were collected from middle and high school history teachers including teacher interviews,…

  16. Do Leaders' Experience and Concentration Area Influence School Performance?

    ERIC Educational Resources Information Center

    Sturgis, Kimberlin; Shiflett, Brittanee; Tanner, Tyrone

    2017-01-01

    The purpose of this study was to examine the educational background of leaders in small, high poverty, high minority schools in an effort to determine if the leader's concentration area and background were related to the academic success of the students. Through a causal comparative design, a modified version of the Interstate School Leaders…

  17. Investigating the Effects of the Academy of Reading Program on Middle School Reading Achievement

    ERIC Educational Resources Information Center

    Myers, Brenda Gail

    2016-01-01

    Using a quantitative ex post facto causal comparative research design, this study analyzed the effects of the Academy of Reading software program on students' reading achievement. Tennessee Comprehensive Assessment Program (TCAP) reading scale scores of students in the fourth, fifth, and sixth grades from 2013-2014 were utilized in this study. The…

  18. The Impact of Professional Learning Communities on Urban Teachers and Their Students' Reading and Math Achievement

    ERIC Educational Resources Information Center

    Williams, Deborah Johnson

    2011-01-01

    This study followed a causal comparative research design that utilized mixed methods. This non-experimental investigation sought to identify potential cause and effect relationships between variations in achievement data among schools. The purpose of the study was to determine if urban students' reading and math achievement increased as a result…

  19. A Causal-Comparative Analysis of the Effects of a Student Support Team (SST) Intervention Model at a Secondary School

    ERIC Educational Resources Information Center

    Johnson, Mid D.

    2010-01-01

    The purpose of this research was to identify and examine the effectiveness of a "Student Support Team" (SST) intervention model designed to increase the performance of struggling secondary students and to help them achieve prescribed state standards on the mathematics "Texas Assessment of Knowledge and Skills (TAKS)"…

  20. A Comparison of Factors that Influence the Quality of PEPs in Title I Schools

    ERIC Educational Resources Information Center

    Williams, Connie Jean

    2009-01-01

    The purpose of this study was to investigate the relationship between school-based organizational structures that support teachers' development of Personalized Education Plans (PEPs) and their quality as written for third through fifth grade students in each of two Title I schools. A causal comparative design was implemented. Teachers' responses…

  1. An Action Research Study on the Effect of Interactive Technology and Active Learning on Student Performance

    ERIC Educational Resources Information Center

    Bear, Teresa J.

    2013-01-01

    This quantitative action science research study utilized a causal-comparative experimental research design in order to determine if the use of student response systems (clickers), as an active learning strategy in a community college course, improved student performance in the course. Students in the experimental group (n = 26) used clickers to…

  2. Impact of Curriculum Training on State-Funded Prekindergarten Teachers' Knowledge, Beliefs, and Practices

    ERIC Educational Resources Information Center

    Breffni, Lorraine

    2011-01-01

    The number of state-funded prekindergarten programs continues to grow in the United States. The quality of these early childhood programs, however, often depends on the type of professional development provided. In this investigative study, an experimental pre-post causal-comparative research design was employed to evaluate the impact of an 8-week…

  3. Cause and Event: Supporting Causal Claims through Logistic Models

    ERIC Educational Resources Information Center

    O'Connell, Ann A.; Gray, DeLeon L.

    2011-01-01

    Efforts to identify and support credible causal claims have received intense interest in the research community, particularly over the past few decades. In this paper, we focus on the use of statistical procedures designed to support causal claims for a treatment or intervention when the response variable of interest is dichotomous. We identify…

  4. Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference

    ERIC Educational Resources Information Center

    Schochet, Peter Z.

    2013-01-01

    This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for…

  5. Child Care Subsidy Use and Child Development: Potential Causal Mechanisms

    ERIC Educational Resources Information Center

    Hawkinson, Laura E.

    2011-01-01

    Research using an experimental design is needed to provide firm causal evidence on the impacts of child care subsidy use on child development, and on underlying causal mechanisms since subsidies can affect child development only indirectly via changes they cause in children's early experiences. However, before costly experimental research is…

  6. The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis

    PubMed Central

    Ploner, Alexander; Fischer, Krista; Horikoshi, Momoko; Sarin, Antti-Pekka; Thorleifsson, Gudmar; Ladenvall, Claes; Kals, Mart; Kuningas, Maris; Draisma, Harmen H. M.; Ried, Janina S.; van Zuydam, Natalie R.; Huikari, Ville; Mangino, Massimo; Sonestedt, Emily; Benyamin, Beben; Nelson, Christopher P.; Rivera, Natalia V.; Kristiansson, Kati; Shen, Huei-yi; Havulinna, Aki S.; Dehghan, Abbas; Donnelly, Louise A.; Kaakinen, Marika; Nuotio, Marja-Liisa; Robertson, Neil; de Bruijn, Renée F. A. G.; Ikram, M. Arfan; Amin, Najaf; Balmforth, Anthony J.; Braund, Peter S.; Doney, Alexander S. F.; Döring, Angela; Elliott, Paul; Esko, Tõnu; Franco, Oscar H.; Gretarsdottir, Solveig; Hartikainen, Anna-Liisa; Heikkilä, Kauko; Herzig, Karl-Heinz; Holm, Hilma; Hottenga, Jouke Jan; Hyppönen, Elina; Illig, Thomas; Isaacs, Aaron; Isomaa, Bo; Karssen, Lennart C.; Kettunen, Johannes; Koenig, Wolfgang; Kuulasmaa, Kari; Laatikainen, Tiina; Laitinen, Jaana; Lindgren, Cecilia; Lyssenko, Valeriya; Läärä, Esa; Rayner, Nigel W.; Männistö, Satu; Pouta, Anneli; Rathmann, Wolfgang; Rivadeneira, Fernando; Ruokonen, Aimo; Savolainen, Markku J.; Sijbrands, Eric J. G.; Small, Kerrin S.; Smit, Jan H.; Steinthorsdottir, Valgerdur; Syvänen, Ann-Christine; Taanila, Anja; Tobin, Martin D.; Uitterlinden, Andre G.; Willems, Sara M.; Willemsen, Gonneke; Witteman, Jacqueline; Perola, Markus; Evans, Alun; Ferrières, Jean; Virtamo, Jarmo; Kee, Frank; Tregouet, David-Alexandre; Arveiler, Dominique; Amouyel, Philippe; Ferrario, Marco M.; Brambilla, Paolo; Hall, Alistair S.; Heath, Andrew C.; Madden, Pamela A. F.; Martin, Nicholas G.; Montgomery, Grant W.; Whitfield, John B.; Jula, Antti; Knekt, Paul; Oostra, Ben; van Duijn, Cornelia M.; Penninx, Brenda W. J. H.; Davey Smith, George; Kaprio, Jaakko; Samani, Nilesh J.; Gieger, Christian; Peters, Annette; Wichmann, H.-Erich; Boomsma, Dorret I.; de Geus, Eco J. C.; Tuomi, TiinaMaija; Power, Chris; Hammond, Christopher J.; Spector, Tim D.; Lind, Lars; Orho-Melander, Marju; Palmer, Colin Neil Alexander; Morris, Andrew D.; Groop, Leif; Järvelin, Marjo-Riitta; Salomaa, Veikko; Vartiainen, Erkki; Hofman, Albert; Ripatti, Samuli; Metspalu, Andres; Thorsteinsdottir, Unnur; Stefansson, Kari; Pedersen, Nancy L.; McCarthy, Mark I.; Ingelsson, Erik; Prokopenko, Inga

    2013-01-01

    Background The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001). Conclusions We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes. Please see later in the article for the Editors' Summary PMID:23824655

  7. Supporting inquiry learning by promoting normative understanding of multivariable causality

    NASA Astrophysics Data System (ADS)

    Keselman, Alla

    2003-11-01

    Early adolescents may lack the cognitive and metacognitive skills necessary for effective inquiry learning. In particular, they are likely to have a nonnormative mental model of multivariable causality in which effects of individual variables are neither additive nor consistent. Described here is a software-based intervention designed to facilitate students' metalevel and performance-level inquiry skills by enhancing their understanding of multivariable causality. Relative to an exploration-only group, sixth graders who practiced predicting an outcome (earthquake risk) based on multiple factors demonstrated increased attention to evidence, improved metalevel appreciation of effective strategies, and a trend toward consistent use of a controlled comparison strategy. Sixth graders who also received explicit instruction in making predictions based on multiple factors showed additional improvement in their ability to compare multiple instances as a basis for inferences and constructed the most accurate knowledge of the system. Gains were maintained in transfer tasks. The cognitive skills and metalevel understanding examined here are essential to inquiry learning.

  8. Undertaking Experiments in Social Sciences: Sequential, Multiple Time Series Designs for Consideration

    ERIC Educational Resources Information Center

    Phan, Huy P.; Ngu, Bing H.

    2017-01-01

    In social sciences, the use of stringent methodological approaches is gaining increasing emphasis. Researchers have recognized the limitations of cross-sectional, non-manipulative data in the study of causality. True experimental designs, in contrast, are preferred as they represent rigorous standards for achieving causal flows between variables.…

  9. Statistical Power for Causally Defined Indirect Effects in Group-Randomized Trials with Individual-Level Mediators

    ERIC Educational Resources Information Center

    Kelcey, Benjamin; Dong, Nianbo; Spybrook, Jessaca; Cox, Kyle

    2017-01-01

    Designs that facilitate inferences concerning both the total and indirect effects of a treatment potentially offer a more holistic description of interventions because they can complement "what works" questions with the comprehensive study of the causal connections implied by substantive theories. Mapping the sensitivity of designs to…

  10. The Pervasive Problem With Placebos in Psychology: Why Active Control Groups Are Not Sufficient to Rule Out Placebo Effects.

    PubMed

    Boot, Walter R; Simons, Daniel J; Stothart, Cary; Stutts, Cassie

    2013-07-01

    To draw causal conclusions about the efficacy of a psychological intervention, researchers must compare the treatment condition with a control group that accounts for improvements caused by factors other than the treatment. Using an active control helps to control for the possibility that improvement by the experimental group resulted from a placebo effect. Although active control groups are superior to "no-contact" controls, only when the active control group has the same expectation of improvement as the experimental group can we attribute differential improvements to the potency of the treatment. Despite the need to match expectations between treatment and control groups, almost no psychological interventions do so. This failure to control for expectations is not a minor omission-it is a fundamental design flaw that potentially undermines any causal inference. We illustrate these principles with a detailed example from the video-game-training literature showing how the use of an active control group does not eliminate expectation differences. The problem permeates other interventions as well, including those targeting mental health, cognition, and educational achievement. Fortunately, measuring expectations and adopting alternative experimental designs makes it possible to control for placebo effects, thereby increasing confidence in the causal efficacy of psychological interventions. © The Author(s) 2013.

  11. Teaching Statistical Inference for Causal Effects in Experiments and Observational Studies

    ERIC Educational Resources Information Center

    Rubin, Donald B.

    2004-01-01

    Inference for causal effects is a critical activity in many branches of science and public policy. The field of statistics is the one field most suited to address such problems, whether from designed experiments or observational studies. Consequently, it is arguably essential that departments of statistics teach courses in causal inference to both…

  12. Correlation of causal factors that influence construction safety performance: A model.

    PubMed

    Rodrigues, F; Coutinho, A; Cardoso, C

    2015-01-01

    The construction sector has presented positive development regarding the decrease in occupational accident rates in recent years. Regardless, the construction sector stands out systematically from other industries due to its high number of fatalities. The aim of this paper is to deeply understand the causality of construction accidents from the early design phase through a model. This study reviewed several research papers presenting various analytical models that correlate the contributing factors to occupational accidents in this sector. This study also analysed different construction projects and conducted a survey of design and site supervision teams. This paper proposes a model developed from the analysis of existing ones, which correlates the causal factors through all the construction phases. It was concluded that effective risk prevention can only be achieved by a global correlation of causal factors including not only production ones but also client requirements, financial climate, design team competence, project and risk management, financial capacity, health and safety policy and early planning. Accordingly, a model is proposed.

  13. Assessing the Generalizability of Estimates of Causal Effects from Regression Discontinuity Designs

    ERIC Educational Resources Information Center

    Bloom, Howard S.; Porter, Kristin E.

    2012-01-01

    In recent years, the regression discontinuity design (RDD) has gained widespread recognition as a quasi-experimental method that when used correctly, can produce internally valid estimates of causal effects of a treatment, a program or an intervention (hereafter referred to as treatment effects). In an RDD study, subjects or groups of subjects…

  14. Causal reasoning with forces

    PubMed Central

    Wolff, Phillip; Barbey, Aron K.

    2015-01-01

    Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed. PMID:25653611

  15. The Impact of Teacher Furloughs on Academic Achievement in Hawaii Public Schools

    ERIC Educational Resources Information Center

    Soares, Katina M.

    2013-01-01

    Due to budget shortfalls, teacher furloughs were imposed in 2009 in Hawaii Public Schools. The furloughs resulted in a 2009-2010 school year of 167 days as opposed to the regular school year of 180 days. The purpose of this causal-comparative study with a pretest-posttest design was to examine the found effects of those furloughs on academic…

  16. The Value of School Facilities: Evidence from a Dynamic Regression Discontinuity Design. NBER Working Paper No. 14516

    ERIC Educational Resources Information Center

    Cellini, Stephanie Riegg; Ferreira, Fernando; Rothstein, Jesse

    2008-01-01

    This paper analyzes the impact of voter-approved school bond issues on school district balance sheets, local housing prices, and student achievement. We draw on the unique characteristics of California's system of school finance to obtain clean identification of bonds' causal effects, comparing districts in which school bond referenda passed or…

  17. Mathematics Achievement with Digital Game-Based Learning in High School Algebra 1 Classes

    ERIC Educational Resources Information Center

    Ferguson, Terri Lynn Kurley

    2014-01-01

    This study examined the impact of digital game-based learning (DGBL) on mathematics achievement in a rural high school setting in North Carolina. A causal comparative research design was used in this study to collect data to determine the effectiveness of DGBL in high school Algebra 1 classes. Data were collected from the North Carolina…

  18. Design and analysis of post-marketing research.

    PubMed

    Zhou, Xiao-Hua Andrew; Yang, Wei

    2013-07-01

    A post-marketing study is an integral part of research that helps to ensure a favorable risk-benefit profile for approved drugs used in the market. Because most of post-marketing studies use observational designs, which are liable to confounding, estimation of the causal effect of a drug versus a comparative one is very challenging. This article focuses on methodological issues of importance in designing and analyzing studies to evaluate the safety of marketed drugs, especially marketed traditional Chinese medicine (TCM) products. Advantages and limitations of the current designs and analytic methods for postmarketing studies are discussed, and recommendations are given for improving the validity of postmarketing studies in TCM products.

  19. CauseMap: fast inference of causality from complex time series.

    PubMed

    Maher, M Cyrus; Hernandez, Ryan D

    2015-01-01

    Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data. Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM), a method for establishing causality from long time series data (≳25 observations). Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens' Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement CCM in Julia, a high-performance programming language designed for facile technical computing. Our software package, CauseMap, is platform-independent and freely available as an official Julia package. Conclusions. CauseMap is an efficient implementation of a state-of-the-art algorithm for detecting causality from time series data. We believe this tool will be a valuable resource for biomedical research and personalized medicine.

  20. Causal learning and inference as a rational process: the new synthesis.

    PubMed

    Holyoak, Keith J; Cheng, Patricia W

    2011-01-01

    Over the past decade, an active line of research within the field of human causal learning and inference has converged on a general representational framework: causal models integrated with bayesian probabilistic inference. We describe this new synthesis, which views causal learning and inference as a fundamentally rational process, and review a sample of the empirical findings that support the causal framework over associative alternatives. Causal events, like all events in the distal world as opposed to our proximal perceptual input, are inherently unobservable. A central assumption of the causal approach is that humans (and potentially nonhuman animals) have been designed in such a way as to infer the most invariant causal relations for achieving their goals based on observed events. In contrast, the associative approach assumes that learners only acquire associations among important observed events, omitting the representation of the distal relations. By incorporating bayesian inference over distributions of causal strength and causal structures, along with noisy-logical (i.e., causal) functions for integrating the influences of multiple causes on a single effect, human judgments about causal strength and structure can be predicted accurately for relatively simple causal structures. Dynamic models of learning based on the causal framework can explain patterns of acquisition observed with serial presentation of contingency data and are consistent with available neuroimaging data. The approach has been extended to a diverse range of inductive tasks, including category-based and analogical inferences.

  1. Treating the Cause of Illness Rather than the Symptoms: Parental Causal Beliefs and Treatment Choices in Autism Spectrum Disorder

    ERIC Educational Resources Information Center

    Dardennes, Roland M.; Al Anbar, Nebal N.; Prado-Netto, Arthur; Kaye, Kelley; Contejean, Yves; Al Anbar, Nesreen N.

    2011-01-01

    Objectives: To explore the relationship between causal beliefs on autism (CBA) and treatment choices. Design and methods: A cross-sectional design was employed. Parents of a child with autism spectrum disorder (ASD) were asked to complete the Lay-Beliefs about Autism Questionnaire (LBA-Q) and answer questions about treatments used. Only items…

  2. Contending Claims to Causality: A Critical Review of Mediation Research in HRD

    ERIC Educational Resources Information Center

    Ghosh, Rajashi; Jacobson, Seth

    2016-01-01

    Purpose: The purpose of this paper is to conduct a critical review of the mediation studies published in the field of Human Resource Development (HRD) to discern if the study designs, the nature of data collection and the choice of statistical methods justify the causal claims made in those studies. Design/methodology/approach: This paper conducts…

  3. Attention Deficit Hyperactivity Disorder Symptoms and Low Educational Achievement: Evidence Supporting A Causal Hypothesis.

    PubMed

    de Zeeuw, Eveline L; van Beijsterveldt, Catharina E M; Ehli, Erik A; de Geus, Eco J C; Boomsma, Dorret I

    2017-05-01

    Attention Deficit Hyperactivity Disorder (ADHD) and educational achievement are negatively associated in children. Here we test the hypothesis that there is a direct causal effect of ADHD on educational achievement. The causal effect is tested in a genetically sensitive design to exclude the possibility of confounding by a third factor (e.g. genetic pleiotropy) and by comparing educational achievement and secondary school career in children with ADHD who take or do not take methylphenidate. Data on ADHD symptoms, educational achievement and methylphenidate usage were available in a primary school sample of ~10,000 12-year-old twins from the Netherlands Twin Register. A substantial group also had longitudinal data at ages 7-12 years. ADHD symptoms were cross-sectionally and longitudinally, associated with lower educational achievement at age 12. More ADHD symptoms predicted a lower-level future secondary school career at age 14-16. In both the cross-sectional and longitudinal analyses, testing the direct causal effect of ADHD on educational achievement, while controlling for genetic and environmental factors, revealed an association between ADHD symptoms and educational achievement independent of genetic and environmental pleiotropy. These findings were confirmed in MZ twin intra-pair differences models, twins with more ADHD symptoms scored lower on educational achievement than their co-twins. Furthermore, children with ADHD medication, scored significantly higher on the educational achievement test than children with ADHD who did not use medication. Taken together, the results are consistent with a direct causal effect of ADHD on educational achievement.

  4. Darwin revisited: The vagus nerve is a causal element in controlling recognition of other's emotions.

    PubMed

    Colzato, Lorenza S; Sellaro, Roberta; Beste, Christian

    2017-07-01

    Charles Darwin proposed that via the vagus nerve, the tenth cranial nerve, emotional facial expressions are evolved, adaptive and serve a crucial communicative function. In line with this idea, the later-developed polyvagal theory assumes that the vagus nerve is the key phylogenetic substrate that regulates emotional and social behavior. The polyvagal theory assumes that optimal social interaction, which includes the recognition of emotion in faces, is modulated by the vagus nerve. So far, in humans, it has not yet been demonstrated that the vagus plays a causal role in emotion recognition. To investigate this we employed transcutaneous vagus nerve stimulation (tVNS), a novel non-invasive brain stimulation technique that modulates brain activity via bottom-up mechanisms. A sham/placebo-controlled, randomized cross-over within-subjects design was used to infer a causal relation between the stimulated vagus nerve and the related ability to recognize emotions as indexed by the Reading the Mind in the Eyes Test in 38 healthy young volunteers. Active tVNS, compared to sham stimulation, enhanced emotion recognition for easy items, suggesting that it promoted the ability to decode salient social cues. Our results confirm that the vagus nerve is causally involved in emotion recognition, supporting Darwin's argumentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Squeezing observational data for better causal inference: Methods and examples for prevention research.

    PubMed

    Garcia-Huidobro, Diego; Michael Oakes, J

    2017-04-01

    Randomised controlled trials (RCTs) are typically viewed as the gold standard for causal inference. This is because effects of interest can be identified with the fewest assumptions, especially imbalance in background characteristics. Yet because conducting RCTs are expensive, time consuming and sometimes unethical, observational studies are frequently used to study causal associations. In these studies, imbalance, or confounding, is usually controlled with multiple regression, which entails strong assumptions. The purpose of this manuscript is to describe strengths and weaknesses of several methods to control for confounding in observational studies, and to demonstrate their use in cross-sectional dataset that use patient registration data from the Juan Pablo II Primary Care Clinic in La Pintana-Chile. The dataset contains responses from 5855 families who provided complete information on family socio-demographics, family functioning and health problems among their family members. We employ regression adjustment, stratification, restriction, matching, propensity score matching, standardisation and inverse probability weighting to illustrate the approaches to better causal inference in non-experimental data and compare results. By applying study design and data analysis techniques that control for confounding in different ways than regression adjustment, researchers may strengthen the scientific relevance of observational studies. © 2016 International Union of Psychological Science.

  6. Causality and causal inference in epidemiology: the need for a pluralistic approach

    PubMed Central

    Vandenbroucke, Jan P; Broadbent, Alex; Pearce, Neil

    2016-01-01

    Abstract Causal inference based on a restricted version of the potential outcomes approach reasoning is assuming an increasingly prominent place in the teaching and practice of epidemiology. The proposed concepts and methods are useful for particular problems, but it would be of concern if the theory and practice of the complete field of epidemiology were to become restricted to this single approach to causal inference. Our concerns are that this theory restricts the questions that epidemiologists may ask and the study designs that they may consider. It also restricts the evidence that may be considered acceptable to assess causality, and thereby the evidence that may be considered acceptable for scientific and public health decision making. These restrictions are based on a particular conceptual framework for thinking about causality. In Section 1, we describe the characteristics of the restricted potential outcomes approach (RPOA) and show that there is a methodological movement which advocates these principles, not just for solving particular problems, but as ideals for which epidemiology as a whole should strive. In Section 2, we seek to show that the limitation of epidemiology to one particular view of the nature of causality is problematic. In Section 3, we argue that the RPOA is also problematic with regard to the assessment of causality. We argue that it threatens to restrict study design choice, to wrongly discredit the results of types of observational studies that have been very useful in the past and to damage the teaching of epidemiological reasoning. Finally, in Section 4 we set out what we regard as a more reasonable ‘working hypothesis’ as to the nature of causality and its assessment: pragmatic pluralism. PMID:26800751

  7. Causality and causal inference in epidemiology: the need for a pluralistic approach.

    PubMed

    Vandenbroucke, Jan P; Broadbent, Alex; Pearce, Neil

    2016-12-01

    Causal inference based on a restricted version of the potential outcomes approach reasoning is assuming an increasingly prominent place in the teaching and practice of epidemiology. The proposed concepts and methods are useful for particular problems, but it would be of concern if the theory and practice of the complete field of epidemiology were to become restricted to this single approach to causal inference. Our concerns are that this theory restricts the questions that epidemiologists may ask and the study designs that they may consider. It also restricts the evidence that may be considered acceptable to assess causality, and thereby the evidence that may be considered acceptable for scientific and public health decision making. These restrictions are based on a particular conceptual framework for thinking about causality. In Section 1, we describe the characteristics of the restricted potential outcomes approach (RPOA) and show that there is a methodological movement which advocates these principles, not just for solving particular problems, but as ideals for which epidemiology as a whole should strive. In Section 2, we seek to show that the limitation of epidemiology to one particular view of the nature of causality is problematic. In Section 3, we argue that the RPOA is also problematic with regard to the assessment of causality. We argue that it threatens to restrict study design choice, to wrongly discredit the results of types of observational studies that have been very useful in the past and to damage the teaching of epidemiological reasoning. Finally, in Section 4 we set out what we regard as a more reasonable 'working hypothesis' as to the nature of causality and its assessment: pragmatic pluralism. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

  8. Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

    PubMed

    Meng, Xiang-He; Shen, Hui; Chen, Xiang-Ding; Xiao, Hong-Mei; Deng, Hong-Wen

    2018-03-01

    Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.

  9. The Relationship between Grade Configuration and Standardized Science Test Scores of Fifth-Grade Students: What School Administrators Should Know

    ERIC Educational Resources Information Center

    Johnson, Delonda; Jones, Lisa; Simieou, Felix; Matthew, Kathryn; Morgan, Bryan

    2013-01-01

    This study utilized a causal comparative (ex post facto) design to determine if a consistent relationship existed between fifth-grade students' success on the Science Texas Assessment of Knowledge and Skills (TAKS) at the elementary (K-5) level in comparison to fifth-grade students' success on the science TAKS at the intermediate (5-6) level. The…

  10. A Multidimensional View of Resistance to Organizational Change: Exploring Cognitive, Emotional, and Intentional Responses to Planned Change across Perceived Change Leadership Strategies

    ERIC Educational Resources Information Center

    Szabla, David B.

    2007-01-01

    In this survey research study, the researcher employed a causal-comparative, or ex post facto, design to explore the relationship between how union employees of a U.S. county government perceived implementation of a new electronic performance appraisal process and how they responded to the planned organizational change along cognitive, emotional,…

  11. Quasi-experimental study designs series-paper 7: assessing the assumptions.

    PubMed

    Bärnighausen, Till; Oldenburg, Catherine; Tugwell, Peter; Bommer, Christian; Ebert, Cara; Barreto, Mauricio; Djimeu, Eric; Haber, Noah; Waddington, Hugh; Rockers, Peter; Sianesi, Barbara; Bor, Jacob; Fink, Günther; Valentine, Jeffrey; Tanner, Jeffrey; Stanley, Tom; Sierra, Eduardo; Tchetgen, Eric Tchetgen; Atun, Rifat; Vollmer, Sebastian

    2017-09-01

    Quasi-experimental designs are gaining popularity in epidemiology and health systems research-in particular for the evaluation of health care practice, programs, and policy-because they allow strong causal inferences without randomized controlled experiments. We describe the concepts underlying five important quasi-experimental designs: Instrumental Variables, Regression Discontinuity, Interrupted Time Series, Fixed Effects, and Difference-in-Differences designs. We illustrate each of the designs with an example from health research. We then describe the assumptions required for each of the designs to ensure valid causal inference and discuss the tests available to examine the assumptions. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available.

    PubMed

    Hernán, Miguel A; Robins, James M

    2016-04-15

    Ideally, questions about comparative effectiveness or safety would be answered using an appropriately designed and conducted randomized experiment. When we cannot conduct a randomized experiment, we analyze observational data. Causal inference from large observational databases (big data) can be viewed as an attempt to emulate a randomized experiment-the target experiment or target trial-that would answer the question of interest. When the goal is to guide decisions among several strategies, causal analyses of observational data need to be evaluated with respect to how well they emulate a particular target trial. We outline a framework for comparative effectiveness research using big data that makes the target trial explicit. This framework channels counterfactual theory for comparing the effects of sustained treatment strategies, organizes analytic approaches, provides a structured process for the criticism of observational studies, and helps avoid common methodologic pitfalls. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  13. Causal interpretation of correlational studies - Analysis of medical news on the website of the official journal for German physicians.

    PubMed

    Buhse, Susanne; Rahn, Anne Christin; Bock, Merle; Mühlhauser, Ingrid

    2018-01-01

    Media frequently draws inappropriate causal statements from observational studies. We analyzed the reporting of study results in the Medical News section of the German medical journal Deutsches Ärzteblatt (DÄ). Study design: Retrospective quantitative content analysis of randomly selected news reports and related original journal articles and press releases. A medical news report was selected if headlines comprised at least two linked variables. Two raters independently categorized the headline and text of each news report, conclusions of the abstract and full text of the related journal article, and the press release. The assessment instrument comprised five categories from 'neutral' to 'unconditionally causal'. Outcome measures: degree of matching between 1) news headlines and conclusions of the journal article, 2) headlines and text of news reports, 3) text and conclusions, and 4) headlines and press releases. We analyzed whether news headlines rated as unconditionally causal based on randomized controlled trials (RCTs). One-thousand eighty-seven medical news reports were published between April 2015 and May 2016. The final random sample comprised 176 news reports and 100 related press releases. Degree of matching: 1) 45% (79/176) for news headlines and journal article conclusions, 2) 55% (97/176) for headlines and text, 3) 53% (93/176) for text and conclusions, and 4) 41% (41/100) for headlines and press releases. Exaggerations were found in 45% (80/176) of the headlines compared to the conclusions of the related journal article. Sixty-five of 137 unconditionally causal statements of the news headlines were phrased more weakly in the subsequent news text body. Only 52 of 137 headlines (38%) categorized as unconditionally causal reported RCTs. Reporting of medical news in the DÄ medical journal is misleading. Most headlines that imply causal associations were not based on RCTs. Medical journalists should follow standards of reporting scientific study results.

  14. Causality networks from multivariate time series and application to epilepsy.

    PubMed

    Siggiridou, Elsa; Koutlis, Christos; Tsimpiris, Alkiviadis; Kimiskidis, Vasilios K; Kugiumtzis, Dimitris

    2015-08-01

    Granger causality and variants of this concept allow the study of complex dynamical systems as networks constructed from multivariate time series. In this work, a large number of Granger causality measures used to form causality networks from multivariate time series are assessed. For this, realizations on high dimensional coupled dynamical systems are considered and the performance of the Granger causality measures is evaluated, seeking for the measures that form networks closest to the true network of the dynamical system. In particular, the comparison focuses on Granger causality measures that reduce the state space dimension when many variables are observed. Further, the linear and nonlinear Granger causality measures of dimension reduction are compared to a standard Granger causality measure on electroencephalographic (EEG) recordings containing episodes of epileptiform discharges.

  15. The Causal Effects of Father Absence

    PubMed Central

    McLanahan, Sara; Tach, Laura; Schneider, Daniel

    2014-01-01

    The literature on father absence is frequently criticized for its use of cross-sectional data and methods that fail to take account of possible omitted variable bias and reverse causality. We review studies that have responded to this critique by employing a variety of innovative research designs to identify the causal effect of father absence, including studies using lagged dependent variable models, growth curve models, individual fixed effects models, sibling fixed effects models, natural experiments, and propensity score matching models. Our assessment is that studies using more rigorous designs continue to find negative effects of father absence on offspring well-being, although the magnitude of these effects is smaller than what is found using traditional cross-sectional designs. The evidence is strongest and most consistent for outcomes such as high school graduation, children’s social-emotional adjustment, and adult mental health. PMID:24489431

  16. Causal cognition in human and nonhuman animals: a comparative, critical review.

    PubMed

    Penn, Derek C; Povinelli, Daniel J

    2007-01-01

    In this article, we review some of the most provocative experimental results to have emerged from comparative labs in the past few years, starting with research focusing on contingency learning and finishing with experiments exploring nonhuman animals' understanding of causal-logical relations. Although the theoretical explanation for these results is often inchoate, a clear pattern nevertheless emerges. The comparative evidence does not fit comfortably into either the traditional associationist or inferential alternatives that have dominated comparative debate for many decades now. Indeed, the similarities and differences between human and nonhuman causal cognition seem to be much more multifarious than these dichotomous alternatives allow.

  17. Education and coronary heart disease: mendelian randomisation study.

    PubMed

    Tillmann, Taavi; Vaucher, Julien; Okbay, Aysu; Pikhart, Hynek; Peasey, Anne; Kubinova, Ruzena; Pajak, Andrzej; Tamosiunas, Abdonas; Malyutina, Sofia; Hartwig, Fernando Pires; Fischer, Krista; Veronesi, Giovanni; Palmer, Tom; Bowden, Jack; Davey Smith, George; Bobak, Martin; Holmes, Michael V

    2017-08-30

    Objective  To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. Design  Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. Setting  The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors. Participants  The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin. Exposure  A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education. Main outcome measure  Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D). Results  Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10 -8 ). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile. Conclusions  This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits.

  18. Education and coronary heart disease: mendelian randomisation study

    PubMed Central

    Vaucher, Julien; Okbay, Aysu; Pikhart, Hynek; Peasey, Anne; Kubinova, Ruzena; Pajak, Andrzej; Tamosiunas, Abdonas; Malyutina, Sofia; Hartwig, Fernando Pires; Fischer, Krista; Veronesi, Giovanni; Palmer, Tom; Bowden, Jack; Davey Smith, George; Bobak, Martin; Holmes, Michael V

    2017-01-01

    Objective To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. Design Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. Setting The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors. Participants The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin. Exposure A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education. Main outcome measure Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D). Results Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10−8). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile. Conclusions This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits. PMID:28855160

  19. Formulating and Answering High-Impact Causal Questions in Physiologic Childbirth Science: Concepts and Assumptions.

    PubMed

    Snowden, Jonathan M; Tilden, Ellen L; Odden, Michelle C

    2018-06-08

    In this article, we conclude our 3-part series by focusing on several concepts that have proven useful for formulating causal questions and inferring causal effects. The process of causal inference is of key importance for physiologic childbirth science, so each concept is grounded in content related to women at low risk for perinatal complications. A prerequisite to causal inference is determining that the question of interest is causal rather than descriptive or predictive. Another critical step in defining a high-impact causal question is assessing the state of existing research for evidence of causality. We introduce 2 causal frameworks that are useful for this undertaking, Hill's causal considerations and the sufficient-component cause model. We then provide 3 steps to aid perinatal researchers in inferring causal effects in a given study. First, the researcher should formulate a rigorous and clear causal question. We introduce an example of epidural analgesia and labor progression to demonstrate this process, including the central role of temporality. Next, the researcher should assess the suitability of the given data set to answer this causal question. In randomized controlled trials, data are collected with the express purpose of answering the causal question. Investigators using observational data should also ensure that their chosen causal question is answerable with the available data. Finally, investigators should design an analysis plan that targets the causal question of interest. Some data structures (eg, time-dependent confounding by labor progress when estimating the effect of epidural analgesia on postpartum hemorrhage) require specific analytical tools to control for bias and estimate causal effects. The assumptions of consistency, exchangeability, and positivity may be especially useful in carrying out these steps. Drawing on appropriate causal concepts and considering relevant assumptions strengthens our confidence that research has reduced the likelihood of alternative explanations (eg bias, chance) and estimated a causal effect. © 2018 by the American College of Nurse-Midwives.

  20. Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies1

    PubMed Central

    Bowden, Jack; Relton, Caroline; Davey Smith, George

    2016-01-01

    Mendelian randomization (MR) is an increasingly important tool for appraising causality in observational epidemiology. The technique exploits the principle that genotypes are not generally susceptible to reverse causation bias and confounding, reflecting their fixed nature and Mendel’s first and second laws of inheritance. The approach is, however, subject to important limitations and assumptions that, if unaddressed or compounded by poor study design, can lead to erroneous conclusions. Nevertheless, the advent of 2-sample approaches (in which exposure and outcome are measured in separate samples) and the increasing availability of open-access data from large consortia of genome-wide association studies and population biobanks mean that the approach is likely to become routine practice in evidence synthesis and causal inference research. In this article we provide an overview of the design, analysis, and interpretation of MR studies, with a special emphasis on assumptions and limitations. We also consider different analytic strategies for strengthening causal inference. Although impossible to prove causality with any single approach, MR is a highly cost-effective strategy for prioritizing intervention targets for disease prevention and for strengthening the evidence base for public health policy. PMID:26961927

  1. Causal inference from observational data.

    PubMed

    Listl, Stefan; Jürges, Hendrik; Watt, Richard G

    2016-10-01

    Randomized controlled trials have long been considered the 'gold standard' for causal inference in clinical research. In the absence of randomized experiments, identification of reliable intervention points to improve oral health is often perceived as a challenge. But other fields of science, such as social science, have always been challenged by ethical constraints to conducting randomized controlled trials. Methods have been established to make causal inference using observational data, and these methods are becoming increasingly relevant in clinical medicine, health policy and public health research. This study provides an overview of state-of-the-art methods specifically designed for causal inference in observational data, including difference-in-differences (DiD) analyses, instrumental variables (IV), regression discontinuity designs (RDD) and fixed-effects panel data analysis. The described methods may be particularly useful in dental research, not least because of the increasing availability of routinely collected administrative data and electronic health records ('big data'). © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Development and Inter-Rater Reliability of the Liverpool Adverse Drug Reaction Causality Assessment Tool

    PubMed Central

    Gallagher, Ruairi M.; Kirkham, Jamie J.; Mason, Jennifer R.; Bird, Kim A.; Williamson, Paula R.; Nunn, Anthony J.; Turner, Mark A.; Smyth, Rosalind L.; Pirmohamed, Munir

    2011-01-01

    Aim To develop and test a new adverse drug reaction (ADR) causality assessment tool (CAT). Methods A comparison between seven assessors of a new CAT, formulated by an expert focus group, compared with the Naranjo CAT in 80 cases from a prospective observational study and 37 published ADR case reports (819 causality assessments in total). Main Outcome Measures Utilisation of causality categories, measure of disagreements, inter-rater reliability (IRR). Results The Liverpool ADR CAT, using 40 cases from an observational study, showed causality categories of 1 unlikely, 62 possible, 92 probable and 125 definite (1, 62, 92, 125) and ‘moderate’ IRR (kappa 0.48), compared to Naranjo (0, 100, 172, 8) with ‘moderate’ IRR (kappa 0.45). In a further 40 cases, the Liverpool tool (0, 66, 81, 133) showed ‘good’ IRR (kappa 0.6) while Naranjo (1, 90, 185, 4) remained ‘moderate’. Conclusion The Liverpool tool assigns the full range of causality categories and shows good IRR. Further assessment by different investigators in different settings is needed to fully assess the utility of this tool. PMID:22194808

  3. Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

    PubMed

    Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

    2013-01-01

    Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

  4. Principal stratification in causal inference.

    PubMed

    Frangakis, Constantine E; Rubin, Donald B

    2002-03-01

    Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.

  5. Using Qualitative Comparative Analysis (QCA) of Key Informant Interviews in Health Services Research: Enhancing a Study of Adjuvant Therapy Use in Breast Cancer Care

    PubMed Central

    McAlearney, Ann Scheck; Walker, Daniel; Moss, Alexandra DeNardis; Bickell, Nina A.

    2015-01-01

    Background Qualitative Comparative Analysis (QCA) is a methodology created to address causal complexity in social sciences research by preserving the objectivity of quantitative data analysis without losing detail inherent in qualitative research. However, its use in health services research (HSR) is limited, and questions remain about its application in this context. Objective To explore the strengths and weaknesses of using QCA for HSR. Research Design Using data from semi-structured interviews conducted as part of a multiple case study about adjuvant treatment underuse among underserved breast cancer patients, findings were compared using qualitative approaches with and without QCA to identify strengths, challenges, and opportunities presented by QCA. Subjects Ninety administrative and clinical key informants interviewed across ten NYC area safety net hospitals. Measures Transcribed interviews were coded by three investigators using an iterative and interactive approach. Codes were calibrated for QCA, as well as examined using qualitative analysis without QCA. Results Relative to traditional qualitative analysis, QCA strengths include: (1) addressing causal complexity, (2) results presentation as pathways as opposed to a list, (3) identification of necessary conditions, (4) the option of fuzzy-set calibrations, and (5) QCA-specific parameters of fit that allow researchers to compare outcome pathways. Weaknesses include: (1) few guidelines and examples exist for calibrating interview data, (2) not designed to create predictive models, and (3) unidirectionality. Conclusions Through its presentation of results as pathways, QCA can highlight factors most important for production of an outcome. This strength can yield unique benefits for HSR not available through other methods. PMID:26908085

  6. New Evidence on Causal Relationship between Approximate Number System (ANS) Acuity and Arithmetic Ability in Elementary-School Students: A Longitudinal Cross-Lagged Analysis.

    PubMed

    He, Yunfeng; Zhou, Xinlin; Shi, Dexin; Song, Hairong; Zhang, Hui; Shi, Jiannong

    2016-01-01

    Approximate number system (ANS) acuity and mathematical ability have been found to be closely associated in recent studies. However, whether and how these two measures are causally related still remain less addressed. There are two hypotheses about the possible causal relationship: ANS acuity influences mathematical performances, or access to math education sharpens ANS acuity. Evidences in support of both hypotheses have been reported, but these two hypotheses have never been tested simultaneously. Therefore, questions still remain whether only one-direction or reciprocal causal relationships existed in the association. In this work, we provided a new evidence on the causal relationship between ANS acuity and arithmetic ability. ANS acuity and mathematical ability of elementary-school students were measured sequentially at three time points within one year, and all possible causal directions were evaluated simultaneously using cross-lagged regression analysis. The results show that ANS acuity influences later arithmetic ability while the reverse causal direction was not supported. Our finding adds a strong evidence to the causal association between ANS acuity and mathematical ability, and also has important implications for educational intervention designed to train ANS acuity and thereby promote mathematical ability.

  7. New Evidence on Causal Relationship between Approximate Number System (ANS) Acuity and Arithmetic Ability in Elementary-School Students: A Longitudinal Cross-Lagged Analysis

    PubMed Central

    He, Yunfeng; Zhou, Xinlin; Shi, Dexin; Song, Hairong; Zhang, Hui; Shi, Jiannong

    2016-01-01

    Approximate number system (ANS) acuity and mathematical ability have been found to be closely associated in recent studies. However, whether and how these two measures are causally related still remain less addressed. There are two hypotheses about the possible causal relationship: ANS acuity influences mathematical performances, or access to math education sharpens ANS acuity. Evidences in support of both hypotheses have been reported, but these two hypotheses have never been tested simultaneously. Therefore, questions still remain whether only one-direction or reciprocal causal relationships existed in the association. In this work, we provided a new evidence on the causal relationship between ANS acuity and arithmetic ability. ANS acuity and mathematical ability of elementary-school students were measured sequentially at three time points within one year, and all possible causal directions were evaluated simultaneously using cross-lagged regression analysis. The results show that ANS acuity influences later arithmetic ability while the reverse causal direction was not supported. Our finding adds a strong evidence to the causal association between ANS acuity and mathematical ability, and also has important implications for educational intervention designed to train ANS acuity and thereby promote mathematical ability. PMID:27462291

  8. Accounting for respiration is necessary to reliably infer Granger causality from cardiovascular variability series.

    PubMed

    Porta, Alberto; Bassani, Tito; Bari, Vlasta; Pinna, Gian D; Maestri, Roberto; Guzzetti, Stefano

    2012-03-01

    This study was designed to demonstrate the need of accounting for respiration (R) when causality between heart period (HP) and systolic arterial pressure (SAP) is under scrutiny. Simulations generated according to a bivariate autoregressive closed-loop model were utilized to assess how causality changes as a function of the model parameters. An exogenous (X) signal was added to the bivariate autoregressive closed-loop model to evaluate the bias on causality induced when the X source was disregarded. Causality was assessed in the time domain according to a predictability improvement approach (i.e., Granger causality). HP and SAP variability series were recorded with R in 19 healthy subjects during spontaneous and controlled breathing at 10, 15, and 20 breaths/min. Simulations proved the importance of accounting for X signals. During spontaneous breathing, assessing causality without taking into consideration R leads to a significantly larger percentage of closed-loop interactions and a smaller fraction of unidirectional causality from HP to SAP. This finding was confirmed during paced breathing and it was independent of the breathing rate. These results suggest that the role of baroreflex cannot be correctly assessed without accounting for R.

  9. On the road toward formal reasoning: reasoning with factual causal and contrary-to-fact causal premises during early adolescence.

    PubMed

    Markovits, Henry

    2014-12-01

    Understanding the development of conditional (if-then) reasoning is critical for theoretical and educational reasons. Here we examined the hypothesis that there is a developmental transition between reasoning with true and contrary-to-fact (CF) causal conditionals. A total of 535 students between 11 and 14 years of age received priming conditions designed to encourage use of either a true or CF alternatives generation strategy and reasoning problems with true causal and CF causal premises (with counterbalanced order). Results show that priming had no effect on reasoning with true causal premises. By contrast, priming with CF alternatives significantly improved logical reasoning with CF premises. Analysis of the effect of order showed that reasoning with CF premises reduced logical responding among younger students but had no effect among older students. Results support the idea that there is a transition in the reasoning processes in this age range associated with the nature of the alternatives generation process required for logical reasoning with true and CF causal conditionals. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. On the origin of Hill's causal criteria.

    PubMed

    Morabia, A

    1991-09-01

    The rules to assess causation formulated by the eighteenth century Scottish philosopher David Hume are compared to Sir Austin Bradford Hill's causal criteria. The strength of the analogy between Hume's rules and Hill's causal criteria suggests that, irrespective of whether Hume's work was known to Hill or Hill's predecessors, Hume's thinking expresses a point of view still widely shared by contemporary epidemiologists. The lack of systematic experimental proof to causal inferences in epidemiology may explain the analogy of Hume's and Hill's, as opposed to Popper's, logic.

  11. Can chance cause cancer? A causal consideration.

    PubMed

    Stensrud, Mats Julius; Strohmaier, Susanne; Valberg, Morten; Aalen, Odd Olai

    2017-04-01

    The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonising views arise due to estimation of substantially different causal effects. These effects may be hard to interpret, and the results cannot be immediately compared. Indeed, it is not clear whether it is possible to define a causal effect of chance at all. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Causal interpretation of correlational studies – Analysis of medical news on the website of the official journal for German physicians

    PubMed Central

    Rahn, Anne Christin; Bock, Merle; Mühlhauser, Ingrid

    2018-01-01

    Background Media frequently draws inappropriate causal statements from observational studies. We analyzed the reporting of study results in the Medical News section of the German medical journal Deutsches Ärzteblatt (DÄ). Methods Study design: Retrospective quantitative content analysis of randomly selected news reports and related original journal articles and press releases. A medical news report was selected if headlines comprised at least two linked variables. Two raters independently categorized the headline and text of each news report, conclusions of the abstract and full text of the related journal article, and the press release. The assessment instrument comprised five categories from ‘neutral’ to ‘unconditionally causal’. Outcome measures: degree of matching between 1) news headlines and conclusions of the journal article, 2) headlines and text of news reports, 3) text and conclusions, and 4) headlines and press releases. We analyzed whether news headlines rated as unconditionally causal based on randomized controlled trials (RCTs). Results One-thousand eighty-seven medical news reports were published between April 2015 and May 2016. The final random sample comprised 176 news reports and 100 related press releases. Degree of matching: 1) 45% (79/176) for news headlines and journal article conclusions, 2) 55% (97/176) for headlines and text, 3) 53% (93/176) for text and conclusions, and 4) 41% (41/100) for headlines and press releases. Exaggerations were found in 45% (80/176) of the headlines compared to the conclusions of the related journal article. Sixty-five of 137 unconditionally causal statements of the news headlines were phrased more weakly in the subsequent news text body. Only 52 of 137 headlines (38%) categorized as unconditionally causal reported RCTs. Conclusion Reporting of medical news in the DÄ medical journal is misleading. Most headlines that imply causal associations were not based on RCTs. Medical journalists should follow standards of reporting scientific study results. PMID:29723258

  13. Siblings within Families: Levels of Analysis and Patterns of Influence

    ERIC Educational Resources Information Center

    Jenkins, Jennifer; Dunn, Judy

    2009-01-01

    The study of siblings has become increasingly central to developmental science. Sibling relationships have unique effects on development, and sibling designs allow researchers to isolate causal mechanisms in development. This volume emphasizes causal mechanisms in the social domain. We review the preceding chapters in relation to six topics: a…

  14. Effects of Attributional Retraining on Strategy-Based Reading Comprehension in Learning-Disabled Students.

    ERIC Educational Resources Information Center

    Borkowski, John G.; And Others

    1988-01-01

    Seventy-five learning-disabled students (10 to 14 years old) received instructions about summarization strategies and about personal causality that were designed to improve reading comprehension. Changes in antecedent attributions about personal causality were not usually altered by this program-specific attributional training, although…

  15. Commentary: Using Potential Outcomes to Understand Causal Mediation Analysis

    ERIC Educational Resources Information Center

    Imai, Kosuke; Jo, Booil; Stuart, Elizabeth A.

    2011-01-01

    In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by…

  16. The Effect of Causal Chain Length on Counterfactual Conditional Reasoning

    ERIC Educational Resources Information Center

    Beck, Sarah R.; Riggs, Kevin J.; Gorniak, Sarah L.

    2010-01-01

    We investigated German and Nichols' finding that 3-year-olds could answer counterfactual conditional questions about short causal chains of events, but not long. In four experiments (N = 192), we compared 3- and 4-year-olds' performance on short and long causal chain questions, manipulating whether the child could draw on general knowledge to…

  17. Articles Published in Four School Psychology Journals from 2000 to 2005: An Analysis of Experimental/Intervention Research

    ERIC Educational Resources Information Center

    Bliss, Stacy L.; Skinner, Christopher H.; Hautau, Briana; Carroll, Erin E.

    2008-01-01

    Using an experimenter-developed system, articles from four school psychology journals for the years 2000-2005 (n = 929) were classified. Results showed that 40% of the articles were narrative, 29% correlational, 16% descriptive, 8% causal-experimental, 4% causal-comparative, and 2% were meta-analytic. Further analysis of the causal-experimental…

  18. Deconstructing events: The neural bases for space, time, and causality

    PubMed Central

    Kranjec, Alexander; Cardillo, Eileen R.; Lehet, Matthew; Chatterjee, Anjan

    2013-01-01

    Space, time, and causality provide a natural structure for organizing our experience. These abstract categories allow us to think relationally in the most basic sense; understanding simple events require one to represent the spatial relations among objects, the relative durations of actions or movements, and links between causes and effects. The present fMRI study investigates the extent to which the brain distinguishes between these fundamental conceptual domains. Participants performed a one-back task with three conditions of interest (SPACE, TIME and CAUSALITY). Each condition required comparing relations between events in a simple verbal narrative. Depending on the condition, participants were instructed to either attend to the spatial, temporal, or causal characteristics of events, but between participants, each particular event relation appeared in all three conditions. Contrasts compared neural activity during each condition against the remaining two and revealed how thinking about events is deconstructed neurally. Space trials recruited neural areas traditionally associated with visuospatial processing, primarily bilateral frontal and occipitoparietal networks. Causality trials activated areas previously found to underlie causal thinking and thematic role assignment, such as left medial frontal, and left middle temporal gyri, respectively. Causality trials also produced activations in SMA, caudate, and cerebellum; cortical and subcortical regions associated with the perception of time at different timescales. The TIME contrast however, produced no significant effects. This pattern, indicating negative results for TIME trials, but positive effects for CAUSALITY trials in areas important for time perception, motivated additional overlap analyses to further probe relations between domains. The results of these analyses suggest a closer correspondence between time and causality than between time and space. PMID:21861674

  19. Designing Studies to Test Causal Questions About Early Math: The Development of Making Pre-K Count.

    PubMed

    Mattera, Shira K; Morris, Pamela A; Jacob, Robin; Maier, Michelle; Rojas, Natalia

    2017-01-01

    A growing literature has demonstrated that early math skills are associated with later outcomes for children. This research has generated interest in improving children's early math competencies as a pathway to improved outcomes for children in elementary school. The Making Pre-K Count study was designed to test the effects of an early math intervention for preschoolers. Its design was unique in that, in addition to causally testing the effects of early math skills, it also allowed for the examination of a number of additional questions about scale-up, the influence of contextual factors and the counterfactual environment, the mechanism of long-term fade-out, and the role of measurement in early childhood intervention findings. This chapter outlines some of the design considerations and decisions put in place to create a rigorous test of the causal effects of early math skills that is also able to answer these questions in early childhood mathematics and intervention. The study serves as a potential model for how to advance science in the fields of preschool intervention and early mathematics. © 2017 Elsevier Inc. All rights reserved.

  20. Microrandomized trials: An experimental design for developing just-in-time adaptive interventions.

    PubMed

    Klasnja, Predrag; Hekler, Eric B; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A

    2015-12-01

    This article presents an experimental design, the microrandomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals' health behaviors. Microrandomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. The article describes the microrandomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Microrandomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Microrandomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions' effects, enabling creation of more effective JITAIs. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  1. Micro-Randomized Trials: An Experimental Design for Developing Just-in-Time Adaptive Interventions

    PubMed Central

    Klasnja, Predrag; Hekler, Eric B.; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A.

    2015-01-01

    Objective This paper presents an experimental design, the micro-randomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals’ health behaviors. Micro-randomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. Methods The paper describes the micro-randomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Results Micro-randomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Conclusions Micro-randomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions’ effects, enabling creation of more effective JITAIs. PMID:26651463

  2. Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care

    PubMed Central

    Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

    2015-01-01

    Purpose of review Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Recent findings Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Summary Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings. PMID:26371463

  3. Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care.

    PubMed

    Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

    2015-11-01

    Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings.

  4. FPGA design for constrained energy minimization

    NASA Astrophysics Data System (ADS)

    Wang, Jianwei; Chang, Chein-I.; Cao, Mang

    2004-02-01

    The Constrained Energy Minimization (CEM) has been widely used for hyperspectral detection and classification. The feasibility of implementing the CEM as a real-time processing algorithm in systolic arrays has been also demonstrated. The main challenge of realizing the CEM in hardware architecture in the computation of the inverse of the data correlation matrix performed in the CEM, which requires a complete set of data samples. In order to cope with this problem, the data correlation matrix must be calculated in a causal manner which only needs data samples up to the sample at the time it is processed. This paper presents a Field Programmable Gate Arrays (FPGA) design of such a causal CEM. The main feature of the proposed FPGA design is to use the Coordinate Rotation DIgital Computer (CORDIC) algorithm that can convert a Givens rotation of a vector to a set of shift-add operations. As a result, the CORDIC algorithm can be easily implemented in hardware architecture, therefore in FPGA. Since the computation of the inverse of the data correlction involves a series of Givens rotations, the utility of the CORDIC algorithm allows the causal CEM to perform real-time processing in FPGA. In this paper, an FPGA implementation of the causal CEM will be studied and its detailed architecture will be also described.

  5. Causal Analysis After Haavelmo

    PubMed Central

    Heckman, James; Pinto, Rodrigo

    2014-01-01

    Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123

  6. Evaluation of occupational health interventions using a randomized controlled trial: challenges and alternative research designs.

    PubMed

    Schelvis, Roosmarijn M C; Oude Hengel, Karen M; Burdorf, Alex; Blatter, Birgitte M; Strijk, Jorien E; van der Beek, Allard J

    2015-09-01

    Occupational health researchers regularly conduct evaluative intervention research for which a randomized controlled trial (RCT) may not be the most appropriate design (eg, effects of policy measures, organizational interventions on work schedules). This article demonstrates the appropriateness of alternative designs for the evaluation of occupational health interventions, which permit causal inferences, formulated along two study design approaches: experimental (stepped-wedge) and observational (propensity scores, instrumental variables, multiple baseline design, interrupted time series, difference-in-difference, and regression discontinuity). For each design, the unique characteristics are presented including the advantages and disadvantages compared to the RCT, illustrated by empirical examples in occupational health. This overview shows that several appropriate alternatives for the RCT design are feasible and available, which may provide sufficiently strong evidence to guide decisions on implementation of interventions in workplaces. Researchers are encouraged to continue exploring these designs and thus contribute to evidence-based occupational health.

  7. The Validity of the Comparative Interrupted Time Series Design for Evaluating the Effect of School-Level Interventions.

    PubMed

    Jacob, Robin; Somers, Marie-Andree; Zhu, Pei; Bloom, Howard

    2016-06-01

    In this article, we examine whether a well-executed comparative interrupted time series (CITS) design can produce valid inferences about the effectiveness of a school-level intervention. This article also explores the trade-off between bias reduction and precision loss across different methods of selecting comparison groups for the CITS design and assesses whether choosing matched comparison schools based only on preintervention test scores is sufficient to produce internally valid impact estimates. We conduct a validation study of the CITS design based on the federal Reading First program as implemented in one state using results from a regression discontinuity design as a causal benchmark. Our results contribute to the growing base of evidence regarding the validity of nonexperimental designs. We demonstrate that the CITS design can, in our example, produce internally valid estimates of program impacts when multiple years of preintervention outcome data (test scores in the present case) are available and when a set of reasonable criteria are used to select comparison organizations (schools in the present case). © The Author(s) 2016.

  8. The Impact of Troops to Teachers Participants on Student Achievement: A Causal-Comparative Study

    ERIC Educational Resources Information Center

    Osuch, Kurt Stanley

    2014-01-01

    The purpose of this causal-comparative study is to examine the impact of Troops to Teachers (TTT) participants on student achievement by comparing the mean scores of Texas students in the eighth grade during the 2011-2012 academic year taught by TTT participants with the mean scores of all other Texas eighth grade students on each of four…

  9. Causal uncertainty, claimed and behavioural self-handicapping.

    PubMed

    Thompson, Ted; Hepburn, Jonathan

    2003-06-01

    Causal uncertainty beliefs involve doubts about the causes of events, and arise as a consequence of non-contingent evaluative feedback: feedback that leaves the individual uncertain about the causes of his or her achievement outcomes. Individuals high in causal uncertainty are frequently unable to confidently attribute their achievement outcomes, experience anxiety in achievement situations and as a consequence are likely to engage in self-handicapping behaviour. Accordingly, we sought to establish links between trait causal uncertainty, claimed and behavioural self-handicapping. Participants were N=72 undergraduate students divided equally between high and low causally uncertain groups. We used a 2 (causal uncertainty status: high, low) x 3 (performance feedback condition: success, non-contingent success, non-contingent failure) between-subjects factorial design to examine the effects of causal uncertainty on achievement behaviour. Following performance feedback, participants completed 20 single-solution anagrams and 12 remote associate tasks serving as performance measures, and 16 unicursal tasks to assess practice effort. Participants also completed measures of claimed handicaps, state anxiety and attributions. Relative to low causally uncertain participants, high causally uncertain participants claimed more handicaps prior to performance on the anagrams and remote associates, reported higher anxiety, attributed their failure to internal, stable factors, and reduced practice effort on the unicursal tasks, evident in fewer unicursal tasks solved. These findings confirm links between trait causal uncertainty and claimed and behavioural self-handicapping, highlighting the need for educators to facilitate means by which students can achieve surety in the manner in which they attribute the causes of their achievement outcomes.

  10. Case Studies Nested in Fuzzy-Set QCA on Sufficiency: Formalizing Case Selection and Causal Inference

    ERIC Educational Resources Information Center

    Schneider, Carsten Q.; Rohlfing, Ingo

    2016-01-01

    Qualitative Comparative Analysis (QCA) is a method for cross-case analyses that works best when complemented with follow-up case studies focusing on the causal quality of the solution and its constitutive terms, the underlying causal mechanisms, and potentially omitted conditions. The anchorage of QCA in set theory demands criteria for follow-up…

  11. A Study of Students' Reasoning about Probabilistic Causality: Implications for Understanding Complex Systems and for Instructional Design

    ERIC Educational Resources Information Center

    Grotzer, Tina A.; Solis, S. Lynneth; Tutwiler, M. Shane; Cuzzolino, Megan Powell

    2017-01-01

    Understanding complex systems requires reasoning about causal relationships that behave or appear to behave probabilistically. Features such as distributed agency, large spatial scales, and time delays obscure co-variation relationships and complex interactions can result in non-deterministic relationships between causes and effects that are best…

  12. Productivity in Academia: An Assessment of Causal Linkages between Output and Outcome Indicators

    ERIC Educational Resources Information Center

    Wamala, Robert; Ssembatya, Vincent A.

    2015-01-01

    Purpose: The purpose of this paper is to investigate causal linkages between output and outcome indicators of productivity in academia. Design/methodology/approach: The duration of teaching service and the number of graduate students supervised to completion were adopted as output indicators of productivity. Equivalent outcome indicators were the…

  13. Predicting Teacher Value-Added Results in Non-Tested Subjects Based on Confounding Variables: A Multinomial Logistic Regression

    ERIC Educational Resources Information Center

    Street, Nathan Lee

    2017-01-01

    Teacher value-added measures (VAM) are designed to provide information regarding teachers' causal impact on the academic growth of students while controlling for exogenous variables. While some researchers contend VAMs successfully and authentically measure teacher causality on learning, others suggest VAMs cannot adequately control for exogenous…

  14. The Causal Effects of Grade Retention on Behavioral Outcomes

    ERIC Educational Resources Information Center

    Martorell, Paco; Mariano, Louis T.

    2018-01-01

    This study examines the impact of grade retention on behavioral outcomes under a comprehensive assessment-based student promotion policy in New York City. To isolate the causal effect of grade retention, we implement a fuzzy regression discontinuity (RD) design that exploits the fact that grade retention is largely determined by whether a student…

  15. The Children's Perceived Locus of Causality Scale for Physical Education

    ERIC Educational Resources Information Center

    Pannekoek, Linda; Piek, Jan P.; Hagger, Martin S.

    2014-01-01

    A mixed methods design was applied to evaluate the application of the Perceived Locus of Causality scale (PLOC) to preadolescent samples in physical education settings. Subsequent to minor item adaptations to accommodate the assessment of younger samples, qualitative pilot tests were performed (N = 15). Children's reports indicated the need…

  16. Design of an impact evaluation using a mixed methods model--an explanatory assessment of the effects of results-based financing mechanisms on maternal healthcare services in Malawi.

    PubMed

    Brenner, Stephan; Muula, Adamson S; Robyn, Paul Jacob; Bärnighausen, Till; Sarker, Malabika; Mathanga, Don P; Bossert, Thomas; De Allegri, Manuela

    2014-04-22

    In this article we present a study design to evaluate the causal impact of providing supply-side performance-based financing incentives in combination with a demand-side cash transfer component on equitable access to and quality of maternal and neonatal healthcare services. This intervention is introduced to selected emergency obstetric care facilities and catchment area populations in four districts in Malawi. We here describe and discuss our study protocol with regard to the research aims, the local implementation context, and our rationale for selecting a mixed methods explanatory design with a quasi-experimental quantitative component. The quantitative research component consists of a controlled pre- and post-test design with multiple post-test measurements. This allows us to quantitatively measure 'equitable access to healthcare services' at the community level and 'healthcare quality' at the health facility level. Guided by a theoretical framework of causal relationships, we determined a number of input, process, and output indicators to evaluate both intended and unintended effects of the intervention. Overall causal impact estimates will result from a difference-in-difference analysis comparing selected indicators across intervention and control facilities/catchment populations over time.To further explain heterogeneity of quantitatively observed effects and to understand the experiential dimensions of financial incentives on clients and providers, we designed a qualitative component in line with the overall explanatory mixed methods approach. This component consists of in-depth interviews and focus group discussions with providers, service user, non-users, and policy stakeholders. In this explanatory design comprehensive understanding of expected and unexpected effects of the intervention on both access and quality will emerge through careful triangulation at two levels: across multiple quantitative elements and across quantitative and qualitative elements. Combining a traditional quasi-experimental controlled pre- and post-test design with an explanatory mixed methods model permits an additional assessment of organizational and behavioral changes affecting complex processes. Through this impact evaluation approach, our design will not only create robust evidence measures for the outcome of interest, but also generate insights on how and why the investigated interventions produce certain intended and unintended effects and allows for a more in-depth evaluation approach.

  17. Functional brain networks and white matter underlying theory-of-mind in autism.

    PubMed

    Kana, Rajesh K; Libero, Lauren E; Hu, Christi P; Deshpande, Hrishikesh D; Colburn, Jeffrey S

    2014-01-01

    Human beings constantly engage in attributing causal explanations to one's own and to others' actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism.

  18. Quasi-experimental study designs series-paper 4: uses and value.

    PubMed

    Bärnighausen, Till; Tugwell, Peter; Røttingen, John-Arne; Shemilt, Ian; Rockers, Peter; Geldsetzer, Pascal; Lavis, John; Grimshaw, Jeremy; Daniels, Karen; Brown, Annette; Bor, Jacob; Tanner, Jeffery; Rashidian, Arash; Barreto, Mauricio; Vollmer, Sebastian; Atun, Rifat

    2017-09-01

    Quasi-experimental studies are increasingly used to establish causal relationships in epidemiology and health systems research. Quasi-experimental studies offer important opportunities to increase and improve evidence on causal effects: (1) they can generate causal evidence when randomized controlled trials are impossible; (2) they typically generate causal evidence with a high degree of external validity; (3) they avoid the threats to internal validity that arise when participants in nonblinded experiments change their behavior in response to the experimental assignment to either intervention or control arm (such as compensatory rivalry or resentful demoralization); (4) they are often well suited to generate causal evidence on long-term health outcomes of an intervention, as well as nonhealth outcomes such as economic and social consequences; and (5) they can often generate evidence faster and at lower cost than experiments and other intervention studies. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts.

    PubMed

    Brion, Marie-Jo A; Lawlor, Debbie A; Matijasevich, Alicia; Horta, Bernardo; Anselmi, Luciana; Araújo, Cora L; Menezes, Ana Maria B; Victora, Cesar G; Smith, George Davey

    2011-06-01

    A novel approach is explored for improving causal inference in observational studies by comparing cohorts from high-income with low- or middle-income countries (LMIC), where confounding structures differ. This is applied to assessing causal effects of breastfeeding on child blood pressure (BP), body mass index (BMI) and intelligence quotient (IQ). Standardized approaches for assessing the confounding structure of breastfeeding by socio-economic position were applied to the British Avon Longitudinal Study of Parents and Children (ALSPAC) (N ≃ 5000) and Brazilian Pelotas 1993 cohorts (N ≃ 1000). This was used to improve causal inference regarding associations of breastfeeding with child BP, BMI and IQ. Analyses were extended to include results from a meta-analysis of five LMICs (N ≃ 10 000) and compared with a randomized trial of breastfeeding promotion. Findings Although higher socio-economic position was strongly associated with breastfeeding in ALSPAC, there was little such patterning in Pelotas. In ALSPAC, breastfeeding was associated with lower BP, lower BMI and higher IQ, adjusted for confounders, but in the directions expected if due to socioeconomic patterning. In contrast, in Pelotas, breastfeeding was not strongly associated with BP or BMI but was associated with higher IQ. Differences in associations observed between ALSPAC and the LMIC meta-analysis were in line with those observed between ALSPAC and Pelotas, but with robust evidence of heterogeneity detected between ALSPAC and the LMIC meta-analysis associations. Trial data supported the conclusions inferred by the cross-cohort comparisons, which provided evidence for causal effects on IQ but not for BP or BMI. While reported associations of breastfeeding with child BP and BMI are likely to reflect residual confounding, breastfeeding may have causal effects on IQ. Comparing associations between populations with differing confounding structures can be used to improve causal inference in observational studies.

  20. Disease causality extraction based on lexical semantics and document-clause frequency from biomedical literature.

    PubMed

    Lee, Dong-Gi; Shin, Hyunjung

    2017-05-18

    Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this paper, we propose a causal disease network that implements disease causality through text mining on biomedical literature. To identify the causality between diseases, the proposed method includes two schemes: the first is the lexicon-based causality term strength, which provides the causal strength on a variety of causality terms based on lexicon analysis. The second is the frequency-based causality strength, which determines the direction and strength of causality based on document and clause frequencies in the literature. We applied the proposed method to 6,617,833 PubMed literature, and chose 195 diseases to construct a causal disease network. From all possible pairs of disease nodes in the network, 1011 causal pairs of 149 diseases were extracted. The resulting network was compared with that of a previous study. In terms of both coverage and quality, the proposed method showed outperforming results; it determined 2.7 times more causalities and showed higher correlation with associated diseases than the existing method. This research has novelty in which the proposed method circumvents the limitations of time and cost in applying all possible causalities in biological experiments and it is a more advanced text mining technique by defining the concepts of causality term strength.

  1. Dual Enrollment Programs: A Comparative Study of High School Students' College Academic Achievement at Different Settings

    ERIC Educational Resources Information Center

    Flores, Agnes L. Acker

    2012-01-01

    The "ex post facto" causal-comparative study examined the academic achievement of high school students who took their dual credit English or mathematics college credit-bearing course in two different environments, namely, the college setting and the high school setting. Due to non-experimental nature of the study, no causal inferences…

  2. Quantitative Causal-Comparative Relationship between Interactive Whiteboard Instruction and Student Science Proficiency

    ERIC Educational Resources Information Center

    Danelczyk, Ewa Krystyna

    2013-01-01

    The purpose of this quantitative causal-comparative study was to investigate the relationship between the instructional effects of the interactive whiteboard and students' proficiency levels in eighth-grade science as evidenced by the state FCAT scores. A total of 46 eighth-grade science teachers in a South Florida public school district completed…

  3. A Causal-Comparative Study of the Affects of Benchmark Assessments on Middle Grades Science Achievement Scores

    ERIC Educational Resources Information Center

    Galloway, Melissa Ritchie

    2016-01-01

    The purpose of this causal comparative study was to test the theory of assessment that relates benchmark assessments to the Georgia middle grades science Criterion Referenced Competency Test (CRCT) percentages, controlling for schools who do not administer benchmark assessments versus schools who do administer benchmark assessments for all middle…

  4. The Affordable Care Act and health insurance exchanges: effects on the pediatric dental benefit.

    PubMed

    Orynich, C Ashley; Casamassimo, Paul S; Seale, N Sue; Reggiardo, Paul; Litch, C Scott

    2015-01-01

    To examine the relationship between state health insurance Exchange selection and pediatric dental benefit design, regulation and cost. Medical and dental plans were analyzed across three types of state health insurance Exchanges: State-based (SB), State-partnered (SP), and Federally-facilitated (FF). Cost-analysis was completed for 10,427 insurance plans, and health policy expert interviews were conducted. One-way ANOVA compared the cost-sharing structure of stand-alone dental plans (SADP). T-test statistics compared differences in average total monthly pediatric premium costs. No causal relationships were identified between Exchange selection and the pediatric dental benefit's design, regulation or cost. Pediatric medical and dental coverage offered through the embedded plan design exhibited comparable average total monthly premium costs to aggregate cost estimates for the separately purchased SADP and traditional medical plan (P=0.11). Plan designs and regulatory policies demonstrated greater correlation between the SP and FF Exchanges, as compared to the SB Exchange. Parameters defining the pediatric dental benefit are complex and vary across states. Each state Exchange was subject to barriers in improving the quality of the pediatric dental benefit due to a lack of defined, standardized policy parameters and further legislative maturation is required.

  5. Estimating causal effects with a non-paranormal method for the design of efficient intervention experiments

    PubMed Central

    2014-01-01

    Background Knockdown or overexpression of genes is widely used to identify genes that play important roles in many aspects of cellular functions and phenotypes. Because next-generation sequencing generates high-throughput data that allow us to detect genes, it is important to identify genes that drive functional and phenotypic changes of cells. However, conventional methods rely heavily on the assumption of normality and they often give incorrect results when the assumption is not true. To relax the Gaussian assumption in causal inference, we introduce the non-paranormal method to test conditional independence in the PC-algorithm. Then, we present the non-paranormal intervention-calculus when the directed acyclic graph (DAG) is absent (NPN-IDA), which incorporates the cumulative nature of effects through a cascaded pathway via causal inference for ranking causal genes against a phenotype with the non-paranormal method for estimating DAGs. Results We demonstrate that causal inference with the non-paranormal method significantly improves the performance in estimating DAGs on synthetic data in comparison with the original PC-algorithm. Moreover, we show that NPN-IDA outperforms the conventional methods in exploring regulators of the flowering time in Arabidopsis thaliana and regulators that control the browning of white adipocytes in mice. Our results show that performance improvement in estimating DAGs contributes to an accurate estimation of causal effects. Conclusions Although the simplest alternative procedure was used, our proposed method enables us to design efficient intervention experiments and can be applied to a wide range of research purposes, including drug discovery, because of its generality. PMID:24980787

  6. Estimating causal effects with a non-paranormal method for the design of efficient intervention experiments.

    PubMed

    Teramoto, Reiji; Saito, Chiaki; Funahashi, Shin-ichi

    2014-06-30

    Knockdown or overexpression of genes is widely used to identify genes that play important roles in many aspects of cellular functions and phenotypes. Because next-generation sequencing generates high-throughput data that allow us to detect genes, it is important to identify genes that drive functional and phenotypic changes of cells. However, conventional methods rely heavily on the assumption of normality and they often give incorrect results when the assumption is not true. To relax the Gaussian assumption in causal inference, we introduce the non-paranormal method to test conditional independence in the PC-algorithm. Then, we present the non-paranormal intervention-calculus when the directed acyclic graph (DAG) is absent (NPN-IDA), which incorporates the cumulative nature of effects through a cascaded pathway via causal inference for ranking causal genes against a phenotype with the non-paranormal method for estimating DAGs. We demonstrate that causal inference with the non-paranormal method significantly improves the performance in estimating DAGs on synthetic data in comparison with the original PC-algorithm. Moreover, we show that NPN-IDA outperforms the conventional methods in exploring regulators of the flowering time in Arabidopsis thaliana and regulators that control the browning of white adipocytes in mice. Our results show that performance improvement in estimating DAGs contributes to an accurate estimation of causal effects. Although the simplest alternative procedure was used, our proposed method enables us to design efficient intervention experiments and can be applied to a wide range of research purposes, including drug discovery, because of its generality.

  7. Alternatives to the Randomized Controlled Trial

    PubMed Central

    West, Stephen G.; Duan, Naihua; Pequegnat, Willo; Gaist, Paul; Des Jarlais, Don C.; Holtgrave, David; Szapocznik, José; Fishbein, Martin; Rapkin, Bruce; Clatts, Michael; Mullen, Patricia Dolan

    2008-01-01

    Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment. In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented. PMID:18556609

  8. Modeling Piezoelectric Stack Actuators for Control of Micromanipulation

    NASA Technical Reports Server (NTRS)

    Goldfarb, Michael; Celanovic, Nikola

    1997-01-01

    A nonlinear lumped-parameter model of a piezoelectric stack actuator has been developed to describe actuator behavior for purposes of control system analysis and design, and, in particular, for microrobotic applications requiring accurate position and/or force control. In formulating this model, the authors propose a generalized Maxwell resistive capacitor as a lumped-parameter causal representation of rate-independent hysteresis. Model formulation is validated by comparing results of numerical simulations to experimental data. Validation is followed by a discussion of model implications for purposes of actuator control.

  9. Designing and Validating a Language Teacher Attribution Scale: A Structural Equation Modeling Approach

    ERIC Educational Resources Information Center

    Ghanizadeh, Afsaneh; Ghonsooly, Behzad

    2015-01-01

    Causal attributions constitute one of the most universal forms of analyzing reality, since they fulfill basic functions in motivation for action. As a theory of causal explanations for success and failure, attribution research has found a natural context in the academic domain. Despite this, it appears that teacher attribution, in particular…

  10. Learning to make things happen: Infants' observational learning of social and physical causal events.

    PubMed

    Waismeyer, Anna; Meltzoff, Andrew N

    2017-10-01

    Infants learn about cause and effect through hands-on experience; however, they also can learn about causality simply from observation. Such observational causal learning is a central mechanism by which infants learn from and about other people. Across three experiments, we tested infants' observational causal learning of both social and physical causal events. Experiment 1 assessed infants' learning of a physical event in the absence of visible spatial contact between the causes and effects. Experiment 2 developed a novel paradigm to assess whether infants could learn about a social causal event from third-party observation of a social interaction between two people. Experiment 3 compared learning of physical and social events when the outcomes occurred probabilistically (happening some, but not all, of the time). Infants demonstrated significant learning in all three experiments, although learning about probabilistic cause-effect relations was most difficult. These findings about infant observational causal learning have implications for children's rapid nonverbal learning about people, things, and their causal relations. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Identifying Causal Variants at Loci with Multiple Signals of Association

    PubMed Central

    Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar

    2014-01-01

    Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20–50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515

  12. Identifying causal variants at loci with multiple signals of association.

    PubMed

    Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar

    2014-10-01

    Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. Copyright © 2014 by the Genetics Society of America.

  13. Regression Discontinuity Designs in Epidemiology

    PubMed Central

    Moscoe, Ellen; Mutevedzi, Portia; Newell, Marie-Louise; Bärnighausen, Till

    2014-01-01

    When patients receive an intervention based on whether they score below or above some threshold value on a continuously measured random variable, the intervention will be randomly assigned for patients close to the threshold. The regression discontinuity design exploits this fact to estimate causal treatment effects. In spite of its recent proliferation in economics, the regression discontinuity design has not been widely adopted in epidemiology. We describe regression discontinuity, its implementation, and the assumptions required for causal inference. We show that regression discontinuity is generalizable to the survival and nonlinear models that are mainstays of epidemiologic analysis. We then present an application of regression discontinuity to the much-debated epidemiologic question of when to start HIV patients on antiretroviral therapy. Using data from a large South African cohort (2007–2011), we estimate the causal effect of early versus deferred treatment eligibility on mortality. Patients whose first CD4 count was just below the 200 cells/μL CD4 count threshold had a 35% lower hazard of death (hazard ratio = 0.65 [95% confidence interval = 0.45–0.94]) than patients presenting with CD4 counts just above the threshold. We close by discussing the strengths and limitations of regression discontinuity designs for epidemiology. PMID:25061922

  14. Causal reports: Context-dependent contributions of intuitive physics and visual impressions of launching.

    PubMed

    Vicovaro, Michele

    2018-05-01

    Everyday causal reports appear to be based on a blend of perceptual and cognitive processes. Causality can sometimes be perceived automatically through low-level visual processing of stimuli, but it can also be inferred on the basis of an intuitive understanding of the physical mechanism that underlies an observable event. We investigated how visual impressions of launching and the intuitive physics of collisions contribute to the formation of explicit causal responses. In Experiment 1, participants observed collisions between realistic objects differing in apparent material and hence implied mass, whereas in Experiment 2, participants observed collisions between abstract, non-material objects. The results of Experiment 1 showed that ratings of causality were mainly driven by the intuitive physics of collisions, whereas the results of Experiment 2 provide some support to the hypothesis that ratings of causality were mainly driven by visual impressions of launching. These results suggest that stimulus factors and experimental design factors - such as the realism of the stimuli and the variation in the implied mass of the colliding objects - may determine the relative contributions of perceptual and post-perceptual cognitive processes to explicit causal responses. A revised version of the impetus transmission heuristic provides a satisfactory explanation for these results, whereas the hypothesis that causal responses and intuitive physics are based on the internalization of physical laws does not. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Causality and headache triggers

    PubMed Central

    Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.

    2013-01-01

    Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872

  16. Functional Brain Networks and White Matter Underlying Theory-of-Mind in Autism

    PubMed Central

    Kana, Rajesh K.; Libero, Lauren E.; Hu, Christi P.; Deshpande, Hrishikesh D.; Colburn, Jeffrey S.

    2014-01-01

    Human beings constantly engage in attributing causal explanations to one’s own and to others’ actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism. PMID:22977198

  17. A Causal-Comparative Study of Third Grade Reading Achievement and the Use of Commercial Reading Programs to Promote Literacy

    ERIC Educational Resources Information Center

    McDonald, Wendy E.

    2013-01-01

    This quantitative, causal-comparative study examined the reading achievement of third grade students to ascertain the reading health of elementary students as measured through South Carolina's standardized assessment, the Palmetto Assessment of State Standards (PASS). The purpose of this study was to determine if there was a significant difference…

  18. Models and mosaics: investigating cross-cultural differences in risk perception and risk preference.

    PubMed

    Weber, E U; Hsee, C K

    1999-12-01

    In this article, we describe a multistudy project designed to explain observed cross-national differences in risk taking between respondents from the People's Republic of China and the United States. Using this example, we develop the following recommendations for cross-cultural investigations. First, like all psychological research, cross-cultural studies should be model based. Investigators should commit themselves to a model of the behavior under study that explicitly specifies possible causal constructs or variables hypothesized to influence the behavior, as well as the relationship between those variables, and allows for individual, group, or cultural differences in the value of these variables or in the relationship between them. This moves the focus from a simple demonstration of cross-national differences toward a prediction of the behavior, including its cross-national variation. Ideally, the causal construct hypothesized and shown to differ between cultures should be demonstrated to serve as a moderator or a mediator between culture and observed behavioral differences. Second, investigators should look for converging evidence for hypothesized cultural effects on behavior by looking at multiple dependent variables and using multiple methodological approaches. Thus, the data collection that will allow for the establishment of conclusive causal connections between a cultural variable and some target behavior can be compared with the creation of a mosaic.

  19. Separated at Birth: Statisticians, Social Scientists, and Causality in Health Services Research

    PubMed Central

    Dowd, Bryan E

    2011-01-01

    Objective Health services research is a field of study that brings together experts from a wide variety of academic disciplines. It also is a field that places a high priority on empirical analysis. Many of the questions posed by health services researchers involve the effects of treatments, patient and provider characteristics, and policy interventions on outcomes of interest. These are causal questions. Yet many health services researchers have been trained in disciplines that are reluctant to use the language of causality, and the approaches to causal questions are discipline specific, often with little overlap. How did this situation arise? This paper traces the roots of the division and some recent attempts to remedy the situation. Data Sources and Settings Existing literature. Study Design Review of the literature. PMID:21105867

  20. Does Causality Matter More Now? Increase in the Proportion of Causal Language in English Texts.

    PubMed

    Iliev, Rumen; Axelrod, Robert

    2016-05-01

    The vast majority of the work on culture and cognition has focused on cross-cultural comparisons, largely ignoring the dynamic aspects of culture. In this article, we provide a diachronic analysis of causal cognition over time. We hypothesized that the increased role of education, science, and technology in Western societies should be accompanied by greater attention to causal connections. To test this hypothesis, we compared word frequencies in English texts from different time periods and found an increase in the use of causal language of about 40% over the past two centuries. The observed increase was not attributable to general language effects or to changing semantics of causal words. We also found that there was a consistent difference between the 19th and the 20th centuries, and that the increase happened mainly in the 20th century. © The Author(s) 2016.

  1. Causal Inference in Educational Effectiveness Research: A Comparison of Three Methods to Investigate Effects of Homework on Student Achievement

    ERIC Educational Resources Information Center

    Gustafsson, Jan-Eric

    2013-01-01

    In educational effectiveness research, it frequently has proven difficult to make credible inferences about cause and effect relations. The article first identifies the main categories of threats to valid causal inference from observational data, and discusses designs and analytic approaches which protect against them. With the use of data from 22…

  2. Testing the Causal Links between School Climate, School Violence, and School Academic Performance: A Cross-Lagged Panel Autoregressive Model

    ERIC Educational Resources Information Center

    Benbenishty, Rami; Astor, Ron Avi; Roziner, Ilan; Wrabel, Stephani L.

    2016-01-01

    The present study explores the causal link between school climate, school violence, and a school's general academic performance over time using a school-level, cross-lagged panel autoregressive modeling design. We hypothesized that reductions in school violence and climate improvement would lead to schools' overall improved academic performance.…

  3. The Impact of Letter Grades on Student Effort, Course Selection, and Major Choice: A Regression-Discontinuity Analysis

    ERIC Educational Resources Information Center

    Main, Joyce B.; Ost, Ben

    2014-01-01

    The authors apply a regression-discontinuity design to identify the causal impact of letter grades on student effort within a course, subsequent credit hours taken, and the probability of majoring in economics. Their methodology addresses key issues in identifying the causal impact of letter grades: correlation with unobservable factors, such as…

  4. Intelligence, income, and education as potential influences on a child's home environment: A (maternal) sibling-comparison design.

    PubMed

    Hadd, Alexandria Ree; Rodgers, Joseph Lee

    2017-07-01

    The quality of the home environment, as a predictor, is related to health, education, and emotion outcomes. However, factors influencing the quality of the home environment, as an outcome, have been understudied-particularly how children construct their own environments. Further, most previous research on family processes and outcomes has implemented between-family designs, which limit claims of causality. The present study uses kinship data from the National Longitudinal Survey of Youth to construct a maternal sibling-comparison design to investigate how maternal and child traits predict the quality of home environment. Using a standard between-family analysis, we first replicate previous research showing a relationship between maternal intelligence and the quality of the home environment. Then, we reevaluate the link between maternal intelligence and the home environment using differences between maternal sisters on several characteristics to explain differences between home environments for their children. Following, we evaluate whether child intelligence differences are related to home environment differences in the presence of maternal characteristics. Results are compared with those from the between-family analysis. Past causal interpretations are challenged by our findings, and the role of child intelligence in the construction of the home environment emerges as a critical contributor that increases in importance with development. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  5. Comparison of weighting techniques for acoustic full waveform inversion

    NASA Astrophysics Data System (ADS)

    Jeong, Gangwon; Hwang, Jongha; Min, Dong-Joo

    2017-12-01

    To reconstruct long-wavelength structures in full waveform inversion (FWI), the wavefield-damping and weighting techniques have been used to synthesize and emphasize low-frequency data components in frequency-domain FWI. However, these methods have some weak points. The application of wavefield-damping method on filtered data fails to synthesize reliable low-frequency data; the optimization formula obtained introducing the weighting technique is not theoretically complete, because it is not directly derived from the objective function. In this study, we address these weak points and present how to overcome them. We demonstrate that the source estimation in FWI using damped wavefields fails when the data used in the FWI process does not satisfy the causality condition. This phenomenon occurs when a non-causal filter is applied to data. We overcome this limitation by designing a causal filter. Also we modify the conventional weighting technique so that its optimization formula is directly derived from the objective function, retaining its original characteristic of emphasizing the low-frequency data components. Numerical results show that the newly designed causal filter enables to recover long-wavelength structures using low-frequency data components synthesized by damping wavefields in frequency-domain FWI, and the proposed weighting technique enhances the inversion results.

  6. Cytochrome P450 2D-mediated metabolism is not necessary for tafenoquine and primaquine to eradicate the erythrocytic stages of Plasmodium berghei.

    PubMed

    Milner, Erin E; Berman, Jonathan; Caridha, Diana; Dickson, Samuel P; Hickman, Mark; Lee, Patricia J; Marcsisin, Sean R; Read, Lisa T; Roncal, Norma; Vesely, Brian A; Xie, Lisa H; Zhang, Jing; Zhang, Ping; Li, Qigui

    2016-12-07

    Due to the ability of the 8-aminoquinolines (8AQs) to kill different stages of the malaria parasite, primaquine (PQ) and tafenoquine (TQ) are vital for causal prophylaxis and the eradication of erythrocytic Plasmodium sp. parasites. Recognizing the potential role of cytochrome (CYP) 450 2D6 in the metabolism and subsequent hepatic efficacy of 8-aminoquinolines, studies were designed to explore whether CYP2D-mediated metabolism was related to the ability of single-dose PQ and TQ to eliminate the asexual and sexual erythrocytic stages of Plasmodium berghei. An IV P. berghei sporozoite murine challenge model was utilized to directly compare causal prophylactic and erythrocytic activity (asexual and sexual parasite stages) dose-response relationships in C57BL/6 wild-type (WT) mice and subsequently compare the erythrocytic activity of PQ and TQ in WT and CYP2D knock-out (KO) mice. Single-dose administration of either 25 mg/kg TQ or 40 mg/kg PQ eradicated the erythrocytic stages (asexual and sexual) of P. berghei in C57BL WT and CYP2D KO mice. In WT animals, the apparent elimination of hepatic infections occurs at lower doses of PQ than are required to eliminate erythrocytic infections. In contrast, the minimally effective dose of TQ needed to achieve causal prophylaxis and to eradicate erythrocytic parasites was analogous. The genetic deletion of the CYP2D cluster does not affect the ability of PQ or TQ to eradicate the blood stages (asexual and sexual) of P. berghei after single-dose administration.

  7. The nature and development of hypothetico-predictive argumentation with implications for science teaching

    NASA Astrophysics Data System (ADS)

    Lawson, Anton E.

    2003-11-01

    This paper explicates a pattern of scientific argumentation in which scientists respond to causal questions with the generation and test of alternative hypotheses through cycles of hypothetico-predictive argumentation. Hypothetico-predictive arguments are employed to test causal claims that exist on at least two levels (designated stage 4 in which the causal claims are perceptible, and stage 5 in which the causal claims are imperceptible). Origins of the ability to construct and comprehend hypothetico-predictive arguments at the highest level can be traced to pre-verbal reasoning of the sensory-motor child and the gradual internalization of verbally mediated arguments involving nominal, categorical, causal and, finally, theoretical propositions. Presumably, the ability to construct and comprehend hypothetico-predictive arguments (an aspect of procedural knowledge) is necessary for the construction of conceptual knowledge (an aspect of declarative knowledge) because such arguments are used during concept construction and conceptual change. Science instruction that focuses on the generation and debate of hypothetico-predictive arguments should improve students' conceptual understanding and their argumentative/reasoning skills.

  8. A general, multivariate definition of causal effects in epidemiology.

    PubMed

    Flanders, W Dana; Klein, Mitchel

    2015-07-01

    Population causal effects are often defined as contrasts of average individual-level counterfactual outcomes, comparing different exposure levels. Common examples include causal risk difference and risk ratios. These and most other examples emphasize effects on disease onset, a reflection of the usual epidemiological interest in disease occurrence. Exposure effects on other health characteristics, such as prevalence or conditional risk of a particular disability, can be important as well, but contrasts involving these other measures may often be dismissed as non-causal. For example, an observed prevalence ratio might often viewed as an estimator of a causal incidence ratio and hence subject to bias. In this manuscript, we provide and evaluate a definition of causal effects that generalizes those previously available. A key part of the generalization is that contrasts used in the definition can involve multivariate, counterfactual outcomes, rather than only univariate outcomes. An important consequence of our generalization is that, using it, one can properly define causal effects based on a wide variety of additional measures. Examples include causal prevalence ratios and differences and causal conditional risk ratios and differences. We illustrate how these additional measures can be useful, natural, easily estimated, and of public health importance. Furthermore, we discuss conditions for valid estimation of each type of causal effect, and how improper interpretation or inferences for the wrong target population can be sources of bias.

  9. Sedentary behaviour and adiposity in youth: a systematic review of reviews and analysis of causality.

    PubMed

    Biddle, Stuart J H; García Bengoechea, Enrique; Wiesner, Glen

    2017-03-28

    Sedentary behaviour (sitting time) has becoming a very popular topic for research and translation since early studies on TV viewing in children in the 1980s. The most studied area for sedentary behaviour health outcomes has been adiposity in young people. However, the literature is replete with inconsistencies. We conducted a systematic review of systematic reviews and meta-analyses to provide a comprehensive analysis of evidence and state-of-the-art synthesis on whether sedentary behaviours are associated with adiposity in young people, and to what extent any association can be considered 'causal'. Searches yielded 29 systematic reviews of over 450 separate papers. We analysed results by observational (cross-sectional and longitudinal) and intervention designs. Small associations were reported for screen time and adiposity from cross-sectional evidence, but associations were less consistent from longitudinal studies. Studies using objective accelerometer measures of sedentary behaviour yielded null associations. Most studies assessed BMI/BMI-z. Interventions to reduce sedentary behaviour produced modest effects for weight status and adiposity. Accounting for effects from sedentary behaviour reduction alone is difficult as many interventions included additional changes in behaviour, such as physical activity and dietary intake. Analysis of causality guided by the classic Bradford Hill criteria concluded that there is no evidence for a causal association between sedentary behaviour and adiposity in youth, although a small dose-response association exists. Associations between sedentary behaviour and adiposity in children and adolescents are small to very small and there is little to no evidence that this association is causal. This remains a complex field with different exposure and outcome measures and research designs. But claims for 'clear' associations between sedentary behaviour and adiposity in youth, and certainly for causality, are premature or misguided.

  10. Bayesian regression discontinuity designs: incorporating clinical knowledge in the causal analysis of primary care data.

    PubMed

    Geneletti, Sara; O'Keeffe, Aidan G; Sharples, Linda D; Richardson, Sylvia; Baio, Gianluca

    2015-07-10

    The regression discontinuity (RD) design is a quasi-experimental design that estimates the causal effects of a treatment by exploiting naturally occurring treatment rules. It can be applied in any context where a particular treatment or intervention is administered according to a pre-specified rule linked to a continuous variable. Such thresholds are common in primary care drug prescription where the RD design can be used to estimate the causal effect of medication in the general population. Such results can then be contrasted to those obtained from randomised controlled trials (RCTs) and inform prescription policy and guidelines based on a more realistic and less expensive context. In this paper, we focus on statins, a class of cholesterol-lowering drugs, however, the methodology can be applied to many other drugs provided these are prescribed in accordance to pre-determined guidelines. Current guidelines in the UK state that statins should be prescribed to patients with 10-year cardiovascular disease risk scores in excess of 20%. If we consider patients whose risk scores are close to the 20%  risk score threshold, we find that there is an element of random variation in both the risk score itself and its measurement. We can therefore consider the threshold as a randomising device that assigns statin prescription to individuals just above the threshold and withholds it from those just below. Thus, we are effectively replicating the conditions of an RCT in the area around the threshold, removing or at least mitigating confounding. We frame the RD design in the language of conditional independence, which clarifies the assumptions necessary to apply an RD design to data, and which makes the links with instrumental variables clear. We also have context-specific knowledge about the expected sizes of the effects of statin prescription and are thus able to incorporate this into Bayesian models by formulating informative priors on our causal parameters. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  11. Exploratory Causal Analysis in Bivariate Time Series Data

    NASA Astrophysics Data System (ADS)

    McCracken, James M.

    Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data sets, but little research exists of how these tools compare to each other in practice. This work introduces and defines exploratory causal analysis (ECA) to address this issue along with the concept of data causality in the taxonomy of causal studies introduced in this work. The motivation is to provide a framework for exploring potential causal structures in time series data sets. ECA is used on several synthetic and empirical data sets, and it is found that all of the tested time series causality tools agree with each other (and intuitive notions of causality) for many simple systems but can provide conflicting causal inferences for more complicated systems. It is proposed that such disagreements between different time series causality tools during ECA might provide deeper insight into the data than could be found otherwise.

  12. The discourse of causal explanations in school science

    NASA Astrophysics Data System (ADS)

    Slater, Tammy Jayne Anne

    Researchers and educators working from a systemic functional linguistic perspective have provided a body of work on science discourse which offers an excellent starting point for examining the linguistic aspects of the development of causal discourse in school science, discourse which Derewianka (1995) claimed is critical to success in secondary school. No work has yet described the development of causal language by identifying the linguistic features present in oral discourse or by comparing the causal discourse of native and non-native (ESL) speakers of English. The current research responds to this gap by examining the oral discourse collected from ESL and non-ESL students at the primary and high school grades. Specifically, it asks the following questions: (1) How do the teachers and students in these four contexts develop causal explanations and their relevant taxonomies through classroom interactions? (2) What are the causal discourse features being used by the students in these four contexts to construct oral causal explanations? The findings of the social practice analysis showed that the teachers in the four contexts differed in their approaches to teaching, with the primary school mainstream teacher focusing largely on the hands-on practice , the primary school ESL teacher moving from practice to theory, the high school mainstream teacher moving from theory to practice, and the high school ESL teacher relying primarily on theory. The findings from the quantitative, small corpus approach suggest that the developmental path of cause which has been identified in the writing of experts shows up not only in written texts but also in the oral texts which learners construct. Moreover, this move appears when the discourse of high school ESL and non-ESL students is compared, suggesting a developmental progression in the acquisition of these features by these students. The findings also reveal that the knowledge constructed, as shown by the concept maps created from the discourse, follows a developmental path similar to the linguistic causal path, from the concrete, hands-on, observable items to more abstract, theoretical concepts. This study is the first systemic functional comparison of the oral discourse of primary and secondary learners as well as the first to compare ESL and non-ESL speakers in this way, and as such it helps map general trends in causal discourse development. (Abstract shortened by UMI.)

  13. Kant on causal laws and powers.

    PubMed

    Henschen, Tobias

    2014-12-01

    The aim of the paper is threefold. Its first aim is to defend Eric Watkins's claim that for Kant, a cause is not an event but a causal power: a power that is borne by a substance, and that, when active, brings about its effect, i.e. a change of the states of another substance, by generating a continuous flow of intermediate states of that substance. The second aim of the paper is to argue against Watkins that the Kantian concept of causal power is not the pre-critical concept of real ground but the category of causality, and that Kant holds with Hume that causal laws cannot be inferred non-inductively (that he accordingly has no intention to show in the Second analogy or elsewhere that events fall under causal laws). The third aim of the paper is to compare the Kantian position on causality with central tenets of contemporary powers ontology: it argues that unlike the variants endorsed by contemporary powers theorists, the Kantian variants of these tenets are resistant to objections that neo-Humeans raise to these tenets.

  14. The causal effect of education on HIV stigma in Uganda: Evidence from a natural experiment.

    PubMed

    Tsai, Alexander C; Venkataramani, Atheendar S

    2015-10-01

    HIV is highly stigmatized in sub-Saharan Africa. This is an important public health problem because HIV stigma has many adverse effects that threaten to undermine efforts to control the HIV epidemic. The implementation of a universal primary education policy in Uganda in 1997 provided us with a natural experiment to test the hypothesis that education is causally related to HIV stigma. For this analysis, we pooled publicly available, population-based data from the 2011 Uganda Demographic and Health Survey and the 2011 Uganda AIDS Indicator Survey. The primary outcomes of interest were negative attitudes toward persons with HIV, elicited using four questions about anticipated stigma and social distance. Standard least squares estimates suggested a statistically significant, negative association between years of schooling and HIV stigma (each P < 0.001, with t-statistics ranging from 4.9 to 14.7). We then used a natural experiment design, exploiting differences in birth cohort exposure to universal primary education as an instrumental variable. Participants who were <13 years old at the time of the policy change had 1.36 additional years of schooling compared to those who were ≥13 years old. Adjusting for linear age trends before and after the discontinuity, two-stage least squares estimates suggested no statistically significant causal effect of education on HIV stigma (P-values ranged from 0.21 to 0.69). Three of the four estimated regression coefficients were positive, and in all cases the lower confidence limits convincingly excluded the possibility of large negative effect sizes. These instrumental variables estimates have a causal interpretation and were not overturned by several robustness checks. We conclude that, for young adults in Uganda, additional years of education in the formal schooling system driven by a universal primary school intervention have not had a causal effect on reducing negative attitudes toward persons with HIV. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. The causal effect of education on HIV stigma in Uganda: evidence from a natural experiment

    PubMed Central

    Tsai, Alexander C.; Venkataramani, Atheendar S.

    2015-01-01

    Rationale HIV is highly stigmatized in sub-Saharan Africa. This is an important public health problem because HIV stigma has many adverse effects that threaten to undermine efforts to control the HIV epidemic. Objective The implementation of a universal primary education policy in Uganda in 1997 provided us with a natural experiment to test the hypothesis that education is causally related to HIV stigma. Methods For this analysis, we pooled publicly available, population-based data from the 2011 Uganda Demographic and Health Survey and the 2011 Uganda AIDS Indicator Survey. The primary outcomes of interest were negative attitudes toward persons with HIV, elicited using four questions about anticipated stigma and social distance. Results Standard least squares estimates suggested a statistically significant, negative association between years of schooling and HIV stigma (each P<0.001, with t-statistics ranging from 4.9 to 14.7). We then used a natural experiment design, exploiting differences in birth cohort exposure to universal primary education as an instrumental variable. Participants who were <13 years old at the time of the policy change had 1.36 additional years of schooling compared to those who were ≥13 years old. Adjusting for linear age trends before and after the discontinuity, two-stage least squares estimates suggested no statistically significant causal effect of education on HIV stigma (P-values ranged from 0.21 to 0.69). Three of the four estimated regression coefficients were positive, and in all cases the lower confidence limits convincingly excluded the possibility of large negative effect sizes. These instrumental variables estimates have a causal interpretation and were not overturned by several robustness checks. Conclusion We conclude that, for young adults in Uganda, additional years of education in the formal schooling system driven by a universal primary school intervention have not had a causal effect on reducing negative attitudes toward persons with HIV. PMID:26282707

  16. ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework.

    PubMed

    Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing

    2011-07-01

    Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

  17. Preliminary Validation of the Perceived Locus of Causality Scale for Academic Motivation in the Context of University Studies (PLOC-U)

    ERIC Educational Resources Information Center

    Sánchez de Miguel, Manuel; Lizaso, Izarne; Hermosilla, Daniel; Alcover, Carlos-Maria; Goudas, Marios; Arranz-Freijó, Enrique

    2017-01-01

    Background: Research has shown that self-determination theory can be useful in the study of motivation in sport and other forms of physical activity. The Perceived Locus of Causality (PLOC) scale was originally designed to study both. Aim: The current research presents and validates the new PLOC-U scale to measure academic motivation in the…

  18. A review of covariate selection for non-experimental comparative effectiveness research.

    PubMed

    Sauer, Brian C; Brookhart, M Alan; Roy, Jason; VanderWeele, Tyler

    2013-11-01

    This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.

  19. Causal inference with missing exposure information: Methods and applications to an obstetric study.

    PubMed

    Zhang, Zhiwei; Liu, Wei; Zhang, Bo; Tang, Li; Zhang, Jun

    2016-10-01

    Causal inference in observational studies is frequently challenged by the occurrence of missing data, in addition to confounding. Motivated by the Consortium on Safe Labor, a large observational study of obstetric labor practice and birth outcomes, this article focuses on the problem of missing exposure information in a causal analysis of observational data. This problem can be approached from different angles (i.e. missing covariates and causal inference), and useful methods can be obtained by drawing upon the available techniques and insights in both areas. In this article, we describe and compare a collection of methods based on different modeling assumptions, under standard assumptions for missing data (i.e. missing-at-random and positivity) and for causal inference with complete data (i.e. no unmeasured confounding and another positivity assumption). These methods involve three models: one for treatment assignment, one for the dependence of outcome on treatment and covariates, and one for the missing data mechanism. In general, consistent estimation of causal quantities requires correct specification of at least two of the three models, although there may be some flexibility as to which two models need to be correct. Such flexibility is afforded by doubly robust estimators adapted from the missing covariates literature and the literature on causal inference with complete data, and by a newly developed triply robust estimator that is consistent if any two of the three models are correct. The methods are applied to the Consortium on Safe Labor data and compared in a simulation study mimicking the Consortium on Safe Labor. © The Author(s) 2013.

  20. A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research

    PubMed Central

    Sauer, Brian C.; Brookhart, Alan; Roy, Jason; Vanderweele, Tyler

    2014-01-01

    This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. PMID:24006330

  1. Comparison of six methods for the detection of causality in a bivariate time series

    NASA Astrophysics Data System (ADS)

    Krakovská, Anna; Jakubík, Jozef; Chvosteková, Martina; Coufal, David; Jajcay, Nikola; Paluš, Milan

    2018-04-01

    In this comparative study, six causality detection methods were compared, namely, the Granger vector autoregressive test, the extended Granger test, the kernel version of the Granger test, the conditional mutual information (transfer entropy), the evaluation of cross mappings between state spaces, and an assessment of predictability improvement due to the use of mixed predictions. Seven test data sets were analyzed: linear coupling of autoregressive models, a unidirectional connection of two Hénon systems, a unidirectional connection of chaotic systems of Rössler and Lorenz type and of two different Rössler systems, an example of bidirectionally connected two-species systems, a fishery model as an example of two correlated observables without a causal relationship, and an example of mediated causality. We tested not only 20 000 points long clean time series but also noisy and short variants of the data. The standard and the extended Granger tests worked only for the autoregressive models. The remaining methods were more successful with the more complex test examples, although they differed considerably in their capability to reveal the presence and the direction of coupling and to distinguish causality from mere correlation.

  2. Graphical Models for Quasi-Experimental Designs

    ERIC Educational Resources Information Center

    Kim, Yongnam; Steiner, Peter M.; Hall, Courtney E.; Su, Dan

    2016-01-01

    Experimental and quasi-experimental designs play a central role in estimating cause-effect relationships in education, psychology, and many other fields of the social and behavioral sciences. This paper presents and discusses the causal graphs of experimental and quasi-experimental designs. For quasi-experimental designs the authors demonstrate…

  3. The Effects of Affirmative Quality Feedback on Low Socio-Economic Students' Zone of Proximal Development Reading Gains (ZPDRL): A Causal-Comparative Study

    ERIC Educational Resources Information Center

    Prescott, Sharon H.

    2010-01-01

    The purpose of this study was to explore upper elementary reading classes in a low socio-economic area to determine the effects frequent praise, both academically and socially, have on the zone of proximal development in reading (ZPD[subscript RL], Renaissance Learning, 2006). A causal-comparative study was utilized by observing two groups of…

  4. Designing Better Scaffolding in Teaching Complex Systems with Graphical Simulations

    NASA Astrophysics Data System (ADS)

    Li, Na

    Complex systems are an important topic in science education today, but they are usually difficult for secondary-level students to learn. Although graphic simulations have many advantages in teaching complex systems, scaffolding is a critical factor for effective learning. This dissertation study was conducted around two complementary research questions on scaffolding: (1) How can we chunk and sequence learning activities in teaching complex systems? (2) How can we help students make connections among system levels across learning activities (level bridging)? With a sample of 123 seventh-graders, this study employed a 3x2 experimental design that factored sequencing methods (independent variable 1; three levels) with level-bridging scaffolding (independent variable 2; two levels) and compared the effectiveness of each combination. The study measured two dependent variables: (1) knowledge integration (i.e., integrating and connecting content-specific normative concepts and providing coherent scientific explanations); (2) understanding of the deep causal structure (i.e., being able to grasp and transfer the causal knowledge of a complex system). The study used a computer-based simulation environment as the research platform to teach the ideal gas law as a system. The ideal gas law is an emergent chemical system that has three levels: (1) experiential macro level (EM) (e.g., an aerosol can explodes when it is thrown into the fire); (2) abstract macro level (AM) (i.e., the relationships among temperature, pressure and volume); (3) micro level (Mi) (i.e., molecular activity). The sequencing methods of these levels were manipulated by changing the order in which they were delivered with three possibilities: (1) EM-AM-Mi; (2) Mi-AM-EM; (3) AM-Mi-EM. The level-bridging scaffolding variable was manipulated on two aspects: (1) inserting inter-level questions among learning activities; (2) two simulations dynamically linked in the final learning activity. Addressing the first research question, the Experiential macro-Abstract macro-Micro (EM-AM-Mi) sequencing method, following the "concrete to abstract" principle, produced better knowledge integration while the Micro-Abstract macro-Experiential macro (Mi-AM-EM) sequencing method, congruent with the causal direction of the emergent system, produced better understanding of the deep causal structure only when level-bridging scaffolding was provided. The Abstract macro-Micro-Experiential macro (AM-Mi-EM) sequencing method produced worse performance in general, because it did not follow the "concrete to abstract" principle, nor did it align with the causal structure of the emergent system. As to the second research question, the results showed that level-bridging scaffolding was important for both knowledge integration and understanding of the causal structure in learning the ideal gas law system.

  5. Supporting cognition in systems biology analysis: findings on users' processes and design implications.

    PubMed

    Mirel, Barbara

    2009-02-13

    Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.

  6. Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.

    PubMed

    Weed, Douglas L

    2018-05-01

    The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.

  7. Does partial Granger causality really eliminate the influence of exogenous inputs and latent variables?

    PubMed

    Roelstraete, Bjorn; Rosseel, Yves

    2012-04-30

    Partial Granger causality was introduced by Guo et al. (2008) who showed that it could better eliminate the influence of latent variables and exogenous inputs than conditional G-causality. In the recent literature we can find some reviews and applications of this type of Granger causality (e.g. Smith et al., 2011; Bressler and Seth, 2010; Barrett et al., 2010). These articles apparently do not take into account a serious flaw in the original work on partial G-causality, being the negative F values that were reported and even proven to be plausible. In our opinion, this undermines the credibility of the obtained results and thus the validity of the approach. Our study is aimed to further validate partial G-causality and to find an answer why negative partial Granger causality estimates were reported. Time series were simulated from the same toy model as used in the original paper and partial and conditional causal measures were compared in the presence of confounding variables. Inference was done parametrically and using non-parametric block bootstrapping. We counter the proof that partial Granger F values can be negative, but the main conclusion of the original article remains. In the presence of unknown latent and exogenous influences, it appears that partial G-causality will better eliminate their influence than conditional G-causality, at least when non-parametric inference is used. Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Causality Analysis of fMRI Data Based on the Directed Information Theory Framework.

    PubMed

    Wang, Zhe; Alahmadi, Ahmed; Zhu, David C; Li, Tongtong

    2016-05-01

    This paper aims to conduct fMRI-based causality analysis in brain connectivity by exploiting the directed information (DI) theory framework. Unlike the well-known Granger causality (GC) analysis, which relies on the linear prediction technique, the DI theory framework does not have any modeling constraints on the sequences to be evaluated and ensures estimation convergence. Moreover, it can be used to generate the GC graphs. In this paper, first, we introduce the core concepts in the DI framework. Second, we present how to conduct causality analysis using DI measures between two time series. We provide the detailed procedure on how to calculate the DI for two finite-time series. The two major steps involved here are optimal bin size selection for data digitization and probability estimation. Finally, we demonstrate the applicability of DI-based causality analysis using both the simulated data and experimental fMRI data, and compare the results with that of the GC analysis. Our analysis indicates that GC analysis is effective in detecting linear or nearly linear causal relationship, but may have difficulty in capturing nonlinear causal relationships. On the other hand, DI-based causality analysis is more effective in capturing both linear and nonlinear causal relationships. Moreover, it is observed that brain connectivity among different regions generally involves dynamic two-way information transmissions between them. Our results show that when bidirectional information flow is present, DI is more effective than GC to quantify the overall causal relationship.

  9. Genetic causal beliefs about obesity, self-efficacy for weight control, and obesity-related behaviours in a middle-aged female cohort

    PubMed Central

    Knerr, Sarah; Bowen, Deborah J.; Beresford, Shirley A.A.; Wang, Catharine

    2015-01-01

    Objective Obesity is a heritable condition with well-established risk-reducing behaviours. Studies have shown that beliefs about the causes of obesity are associated with diet and exercise behaviour. Identifying mechanisms linking causal beliefs and behaviours is important for obesity prevention and control. Design Cross-sectional multi-level regression analyses of self-efficacy for weight control as a possible mediator of obesity attributions (diet, physical activity, genetic) and preventive behaviours in 487 non-Hispanic White women from South King County, Washington. Main Outcome Measures Self-reported daily fruit and vegetable intake and weekly leisure-time physical activity. Results Diet causal beliefs were positively associated with fruit and vegetable intake, with self-efficacy for weight control partially accounting for this association. Self-efficacy for weight control also indirectly linked physical activity attributions and physical activity behaviour. Relationships between genetic causal beliefs, self-efficacy for weight control, and obesity-related behaviours differed by obesity status. Self-efficacy for weight control contributed to negative associations between genetic causal attributions and obesity-related behaviours in non-obese, but not obese, women. Conclusion Self-efficacy is an important construct to include in studies of genetic causal beliefs and behavioural self-regulation. Theoretical and longitudinal work is needed to clarify the causal nature of these relationships and other mediating and moderating factors. PMID:26542069

  10. Causal modelling applied to the risk assessment of a wastewater discharge.

    PubMed

    Paul, Warren L; Rokahr, Pat A; Webb, Jeff M; Rees, Gavin N; Clune, Tim S

    2016-03-01

    Bayesian networks (BNs), or causal Bayesian networks, have become quite popular in ecological risk assessment and natural resource management because of their utility as a communication and decision-support tool. Since their development in the field of artificial intelligence in the 1980s, however, Bayesian networks have evolved and merged with structural equation modelling (SEM). Unlike BNs, which are constrained to encode causal knowledge in conditional probability tables, SEMs encode this knowledge in structural equations, which is thought to be a more natural language for expressing causal information. This merger has clarified the causal content of SEMs and generalised the method such that it can now be performed using standard statistical techniques. As it was with BNs, the utility of this new generation of SEM in ecological risk assessment will need to be demonstrated with examples to foster an understanding and acceptance of the method. Here, we applied SEM to the risk assessment of a wastewater discharge to a stream, with a particular focus on the process of translating a causal diagram (conceptual model) into a statistical model which might then be used in the decision-making and evaluation stages of the risk assessment. The process of building and testing a spatial causal model is demonstrated using data from a spatial sampling design, and the implications of the resulting model are discussed in terms of the risk assessment. It is argued that a spatiotemporal causal model would have greater external validity than the spatial model, enabling broader generalisations to be made regarding the impact of a discharge, and greater value as a tool for evaluating the effects of potential treatment plant upgrades. Suggestions are made on how the causal model could be augmented to include temporal as well as spatial information, including suggestions for appropriate statistical models and analyses.

  11. Comparing the Cognitive Process of Circular Causality in Two Patients with Strokes through Qualitative Analysis.

    PubMed

    Derakhshanrad, Seyed Alireza; Piven, Emily; Ghoochani, Bahareh Zeynalzadeh

    2017-10-01

    Walter J. Freeman pioneered the neurodynamic model of brain activity when he described the brain dynamics for cognitive information transfer as the process of circular causality at intention, meaning, and perception (IMP) levels. This view contributed substantially to establishment of the Intention, Meaning, and Perception Model of Neuro-occupation in occupational therapy. As described by the model, IMP levels are three components of the brain dynamics system, with nonlinear connections that enable cognitive function to be processed in a circular causality fashion, known as Cognitive Process of Circular Causality (CPCC). Although considerable research has been devoted to study the brain dynamics by sophisticated computerized imaging techniques, less attention has been paid to study it through investigating the adaptation process of thoughts and behaviors. To explore how CPCC manifested thinking and behavioral patterns, a qualitative case study was conducted on two matched female participants with strokes, who were of comparable ages, affected sides, and other characteristics, except for their resilience and motivational behaviors. CPCC was compared by matrix analysis between two participants, using content analysis with pre-determined categories. Different patterns of thinking and behavior may have happened, due to disparate regulation of CPCC between two participants.

  12. Causal Learning in Gambling Disorder: Beyond the Illusion of Control.

    PubMed

    Perales, José C; Navas, Juan F; Ruiz de Lara, Cristian M; Maldonado, Antonio; Catena, Andrés

    2017-06-01

    Causal learning is the ability to progressively incorporate raw information about dependencies between events, or between one's behavior and its outcomes, into beliefs of the causal structure of the world. In spite of the fact that some cognitive biases in gambling disorder can be described as alterations of causal learning involving gambling-relevant cues, behaviors, and outcomes, general causal learning mechanisms in gamblers have not been systematically investigated. In the present study, we compared gambling disorder patients against controls in an instrumental causal learning task. Evidence of illusion of control, namely, overestimation of the relationship between one's behavior and an uncorrelated outcome, showed up only in gamblers with strong current symptoms. Interestingly, this effect was part of a more complex pattern, in which gambling disorder patients manifested a poorer ability to discriminate between null and positive contingencies. Additionally, anomalies were related to gambling severity and current gambling disorder symptoms. Gambling-related biases, as measured by a standard psychometric tool, correlated with performance in the causal learning task, but not in the expected direction. Indeed, performance of gamblers with stronger biases tended to resemble the one of controls, which could imply that anomalies of causal learning processes play a role in gambling disorder, but do not seem to underlie gambling-specific biases, at least in a simple, direct way.

  13. A Quantitative Causal-Comparative Study Examining the Effect of Block and Traditional Bell Schedules on Cognitive Load and Mathematics Academic Performance in High School Freshmen of the Southwestern USA

    ERIC Educational Resources Information Center

    Nogler, Tracey A.

    2017-01-01

    The purpose of this quantitative causal-comparative research was to examine if and to what extent there were differences in students' cognitive load and the subsequent academic performance based on block bell schedule and traditional bell schedule for freshmen in Algebra 1 in the Southwestern United States. This study included students from two…

  14. Single case design studies in music therapy: resurrecting experimental evidence in small group and individual music therapy clinical settings.

    PubMed

    Geist, Kamile; Hitchcock, John H

    2014-01-01

    The profession would benefit from greater and routine generation of causal evidence pertaining to the impact of music therapy interventions on client outcomes. One way to meet this goal is to revisit the use of Single Case Designs (SCDs) in clinical practice and research endeavors in music therapy. Given the appropriate setting and goals, this design can be accomplished with small sample sizes and it is often appropriate for studying music therapy interventions. In this article, we promote and discuss implementation of SCD studies in music therapy settings, review the meaning of internal study validity and by extension the notion of causality, and describe two of the most commonly used SCDs to demonstrate how they can help generate causal evidence to inform the field. In closing, we describe the need for replication and future meta-analysis of SCD studies completed in music therapy settings. SCD studies are both feasible and appropriate for use in music therapy clinical practice settings, particularly for testing effectiveness of interventions for individuals or small groups. © the American Music Therapy Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  15. COMPARATIVE IN VITRO CARDIAC TOXICITY OF PRIMARY COMBUSTION PARTICLES: IDENTIFICATION OF CAUSAL CONSTITUENTS AND MECHANISMS OF INJURY

    EPA Science Inventory

    Identification of causal particle characteristics and mechanisms of injury would allow linkage of particulate air pollution adverse health effects to sources. Research has examined the direct cardiovascular effects of air pollution particle constituents since previous studies dem...

  16. Preschool physics: Using the invisible property of weight in causal reasoning tasks

    PubMed Central

    Williamson, Rebecca A.; Meltzoff, Andrew N.

    2018-01-01

    Causal reasoning is an important aspect of scientific thinking. Even young human children can use causal reasoning to explain observations, make predictions, and design actions to bring about specific outcomes in the physical world. Weight is an interesting type of cause because it is an invisible property. Here, we tested preschool children with causal problem-solving tasks that assessed their understanding of weight. In an experimental setting, 2- to 5-year-old children completed three different tasks in which they had to use weight to produce physical effects—an object displacement task, a balance-scale task, and a tower-building task. The results showed that the children’s understanding of how to use object weight to produce specific object-to-object causal outcomes improved as a function of age, with 4- and 5-year-olds showing above-chance performance on all three tasks. The younger children’s performance was more variable. The pattern of results provides theoretical insights into which aspects of weight processing are particularly difficult for preschool children and why they find it difficult. PMID:29561840

  17. Preschool physics: Using the invisible property of weight in causal reasoning tasks.

    PubMed

    Wang, Zhidan; Williamson, Rebecca A; Meltzoff, Andrew N

    2018-01-01

    Causal reasoning is an important aspect of scientific thinking. Even young human children can use causal reasoning to explain observations, make predictions, and design actions to bring about specific outcomes in the physical world. Weight is an interesting type of cause because it is an invisible property. Here, we tested preschool children with causal problem-solving tasks that assessed their understanding of weight. In an experimental setting, 2- to 5-year-old children completed three different tasks in which they had to use weight to produce physical effects-an object displacement task, a balance-scale task, and a tower-building task. The results showed that the children's understanding of how to use object weight to produce specific object-to-object causal outcomes improved as a function of age, with 4- and 5-year-olds showing above-chance performance on all three tasks. The younger children's performance was more variable. The pattern of results provides theoretical insights into which aspects of weight processing are particularly difficult for preschool children and why they find it difficult.

  18. Non-causal spike filtering improves decoding of movement intention for intracortical BCIs

    PubMed Central

    Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

    2014-01-01

    Background Multiple types of neural signals are available for controlling assistive devices through brain-computer interfaces (BCIs). Intracortically-recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. Conclusions Non-causally filtering neural signals prior to extracting threshold crossing events may be a simple yet effective way to condition intracortically recorded neural activity for direct control of external devices through BCIs. PMID:25128256

  19. Econometric testing on linear and nonlinear dynamic relation between stock prices and macroeconomy in China

    NASA Astrophysics Data System (ADS)

    Borjigin, Sumuya; Yang, Yating; Yang, Xiaoguang; Sun, Leilei

    2018-03-01

    Many researchers have realized that there is a strong correlation between stock prices and macroeconomy. In order to make this relationship clear, a lot of studies have been done. However, the causal relationship between stock prices and macroeconomy has still not been well explained. A key point is that, most of the existing research adopts linear and stable models to investigate the correlation of stock prices and macroeconomy, while the real causality of that may be nonlinear and dynamic. To fill this research gap, we investigate the nonlinear and dynamic causal relationships between stock prices and macroeconomy. Based on the case of China's stock prices and acroeconomy measures from January 1992 to March 2017, we compare the linear Granger causality test models with nonlinear ones. Results demonstrate that the nonlinear dynamic Granger causality is much stronger than linear Granger causality. From the perspective of nonlinear dynamic Granger causality, China's stock prices can be viewed as "national economic barometer". On the one hand, this study will encourage researchers to take nonlinearity and dynamics into account when they investigate the correlation of stock prices and macroeconomy; on the other hand, our research can guide regulators and investors to make better decisions.

  20. Expert explanations of honeybee losses in areas of extensive agriculture in France: Gaucho® compared with other supposed causal factors

    NASA Astrophysics Data System (ADS)

    Maxim, L.; van der Sluijs, J. P.

    2010-01-01

    Debates on causality are at the core of controversies as regards environmental changes. The present paper presents a new method for analyzing controversies on causality in a context of social debate and the results of its empirical testing. The case study used is the controversy as regards the role played by the insecticide Gaucho®, compared with other supposed causal factors, in the substantial honeybee (Apis mellifera L.) losses reported to have occurred in France between 1994 and 2004. The method makes use of expert elicitation of the perceived strength of evidence regarding each of Bradford Hill's causality criteria, as regards the link between each of eight possible causal factors identified in attempts to explain each of five signs observed in honeybee colonies. These judgments are elicited from stakeholders and experts involved in the debate, i.e., representatives of Bayer Cropscience, of the Ministry of Agriculture, of the French Food Safety Authority, of beekeepers and of public scientists. We show that the intense controversy observed in confused and passionate public discourses is much less salient when the various arguments are structured using causation criteria. The contradictions between the different expert views have a triple origin: (1) the lack of shared definition and quantification of the signs observed in colonies; (2) the lack of specialist knowledge on honeybees; and (3) the strategic discursive practices associated with the lack of trust between experts representing stakeholders having diverging stakes in the case.

  1. Reprint of “Non-causal spike filtering improves decoding of movement intention for intracortical BCIs”☆

    PubMed Central

    Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

    2015-01-01

    Background Multiple types of neural signals are available for controlling assistive devices through brain–computer interfaces (BCIs). Intracortically recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. PMID:25681017

  2. Imputation of adverse drug reactions: Causality assessment in hospitals

    PubMed Central

    Mastroianni, Patricia de Carvalho

    2017-01-01

    Background & objectives Different algorithms have been developed to standardize the causality assessment of adverse drug reactions (ADR). Although most share common characteristics, the results of the causality assessment are variable depending on the algorithm used. Therefore, using 10 different algorithms, the study aimed to compare inter-rater and multi-rater agreement for ADR causality assessment and identify the most consistent to hospitals. Methods Using ten causality algorithms, four judges independently assessed the first 44 cases of ADRs reported during the first year of implementation of a risk management service in a medium complexity hospital in the state of Sao Paulo (Brazil). Owing to variations in the terminology used for causality, the equivalent imputation terms were grouped into four categories: definite, probable, possible and unlikely. Inter-rater and multi-rater agreement analysis was performed by calculating the Cohen´s and Light´s kappa coefficients, respectively. Results None of the algorithms showed 100% reproducibility in the causal imputation. Fair inter-rater and multi-rater agreement was found. Emanuele (1984) and WHO-UMC (2010) algorithms showed a fair rate of agreement between the judges (k = 0.36). Interpretation & conclusions Although the ADR causality assessment algorithms were poorly reproducible, our data suggest that WHO-UMC algorithm is the most consistent for imputation in hospitals, since it allows evaluating the quality of the report. However, to improve the ability of assessing the causality using algorithms, it is necessary to include criteria for the evaluation of drug-related problems, which may be related to confounding variables that underestimate the causal association. PMID:28166274

  3. The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

    PubMed Central

    Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

    2015-01-01

    The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

  4. Influence of school architecture and design on healthy eating: a review of the evidence.

    PubMed

    Frerichs, Leah; Brittin, Jeri; Sorensen, Dina; Trowbridge, Matthew J; Yaroch, Amy L; Siahpush, Mohammad; Tibbits, Melissa; Huang, Terry T-K

    2015-04-01

    We examined evidence regarding the influence of school physical environment on healthy-eating outcomes. We applied a systems perspective to examine multiple disciplines' theoretical frameworks and used a mixed-methods systematic narrative review method, considering both qualitative and quantitative sources (published through March 2014) for inclusion. We developed a causal loop diagram from 102 sources identified. We found evidence of the influence of many aspects of a school's physical environment on healthy-eating outcomes. The causal loop diagram highlights multilevel and interrelated factors and elucidates the specific roles of design and architecture in encouraging healthy eating within schools. Our review highlighted the gaps in current evidence and identified areas of research needed to refine and expand school architecture and design strategies for addressing healthy eating.

  5. Influence of School Architecture and Design on Healthy Eating: A Review of the Evidence

    PubMed Central

    Brittin, Jeri; Sorensen, Dina; Trowbridge, Matthew J.; Yaroch, Amy L.; Siahpush, Mohammad; Tibbits, Melissa; Huang, Terry T.-K.

    2015-01-01

    We examined evidence regarding the influence of school physical environment on healthy-eating outcomes. We applied a systems perspective to examine multiple disciplines’ theoretical frameworks and used a mixed-methods systematic narrative review method, considering both qualitative and quantitative sources (published through March 2014) for inclusion. We developed a causal loop diagram from 102 sources identified. We found evidence of the influence of many aspects of a school’s physical environment on healthy-eating outcomes. The causal loop diagram highlights multilevel and interrelated factors and elucidates the specific roles of design and architecture in encouraging healthy eating within schools. Our review highlighted the gaps in current evidence and identified areas of research needed to refine and expand school architecture and design strategies for addressing healthy eating. PMID:25713964

  6. Assessing the Power of Exome Chips.

    PubMed

    Page, Christian Magnus; Baranzini, Sergio E; Mevik, Bjørn-Helge; Bos, Steffan Daniel; Harbo, Hanne F; Andreassen, Bettina Kulle

    2015-01-01

    Genotyping chips for rare and low-frequent variants have recently gained popularity with the introduction of exome chips, but the utility of these chips remains unclear. These chips were designed using exome sequencing data from mainly American-European individuals, enriched for a narrow set of common diseases. In addition, it is well-known that the statistical power of detecting associations with rare and low-frequent variants is much lower compared to studies exclusively involving common variants. We developed a simulation program adaptable to any exome chip design to empirically evaluate the power of the exome chips. We implemented the main properties of the Illumina HumanExome BeadChip array. The simulated data sets were used to assess the power of exome chip based studies for varying effect sizes and causal variant scenarios. We applied two widely-used statistical approaches for rare and low-frequency variants, which collapse the variants into genetic regions or genes. Under optimal conditions, we found that a sample size between 20,000 to 30,000 individuals were needed in order to detect modest effect sizes (0.5% < PAR > 1%) with 80% power. For small effect sizes (PAR <0.5%), 60,000-100,000 individuals were needed in the presence of non-causal variants. In conclusion, we found that at least tens of thousands of individuals are necessary to detect modest effects under optimal conditions. In addition, when using rare variant chips on cohorts or diseases they were not originally designed for, the identification of associated variants or genes will be even more challenging.

  7. Robotics: Assessing Its Role in Improving Mathematics Skills for Grades 4 to 5

    ERIC Educational Resources Information Center

    Laughlin, Sara Rose

    2013-01-01

    Inspiring and motivating students to pursue science, technology, engineering, and mathematics education continues to be an important educational focus in the United States. Robotics programs are one strategy developed to accomplish this goal. This causal comparative study focused on investigating whether a causal relationship exists between…

  8. Time and Order Effects on Causal Learning

    ERIC Educational Resources Information Center

    Alvarado, Angelica; Jara, Elvia; Vila, Javier; Rosas, Juan M.

    2006-01-01

    Five experiments were conducted to explore trial order and retention interval effects upon causal predictive judgments. Experiment 1 found that participants show a strong effect of trial order when a stimulus was sequentially paired with two different outcomes compared to a condition where both outcomes were presented intermixed. Experiment 2…

  9. Participation in Athletics and Female Sexual Risk Behavior: The Evaluation of Four Causal Structures.

    ERIC Educational Resources Information Center

    Dodge, Tonya; Jaccard, James

    2002-01-01

    Compared sexual risk behavior of female athletes and nonathletes. Examined mediation, reverse mediation, spurious effects, and moderated causal models, using as potential mediators physical development, educational aspirations, self-esteem, attitudes toward pregnancy, involvement in a romantic relationship, age, ethnicity, and social class. Found…

  10. Rigor, vigor, and the study of health disparities

    PubMed Central

    Adler, Nancy; Bush, Nicole R.; Pantell, Matthew S.

    2012-01-01

    Health disparities research spans multiple fields and methods and documents strong links between social disadvantage and poor health. Associations between socioeconomic status (SES) and health are often taken as evidence for the causal impact of SES on health, but alternative explanations, including the impact of health on SES, are plausible. Studies showing the influence of parents’ SES on their children’s health provide evidence for a causal pathway from SES to health, but have limitations. Health disparities researchers face tradeoffs between “rigor” and “vigor” in designing studies that demonstrate how social disadvantage becomes biologically embedded and results in poorer health. Rigorous designs aim to maximize precision in the measurement of SES and health outcomes through methods that provide the greatest control over temporal ordering and causal direction. To achieve precision, many studies use a single SES predictor and single disease. However, doing so oversimplifies the multifaceted, entwined nature of social disadvantage and may overestimate the impact of that one variable and underestimate the true impact of social disadvantage on health. In addition, SES effects on overall health and functioning are likely to be greater than effects on any one disease. Vigorous designs aim to capture this complexity and maximize ecological validity through more complete assessment of social disadvantage and health status, but may provide less-compelling evidence of causality. Newer approaches to both measurement and analysis may enable enhanced vigor as well as rigor. Incorporating both rigor and vigor into studies will provide a fuller understanding of the causes of health disparities. PMID:23045672

  11. A DVE Time Management Simulation and Verification Platform Based on Causality Consistency Middleware

    NASA Astrophysics Data System (ADS)

    Zhou, Hangjun; Zhang, Wei; Peng, Yuxing; Li, Sikun

    During the course of designing a time management algorithm for DVEs, the researchers always become inefficiency for the distraction from the realization of the trivial and fundamental details of simulation and verification. Therefore, a platform having realized theses details is desirable. However, this has not been achieved in any published work to our knowledge. In this paper, we are the first to design and realize a DVE time management simulation and verification platform providing exactly the same interfaces as those defined by the HLA Interface Specification. Moreover, our platform is based on a new designed causality consistency middleware and might offer the comparison of three kinds of time management services: CO, RO and TSO. The experimental results show that the implementation of the platform only costs small overhead, and that the efficient performance of it is highly effective for the researchers to merely focus on the improvement of designing algorithms.

  12. The search for causal inferences: using propensity scores post hoc to reduce estimation error with nonexperimental research.

    PubMed

    Tumlinson, Samuel E; Sass, Daniel A; Cano, Stephanie M

    2014-03-01

    While experimental designs are regarded as the gold standard for establishing causal relationships, such designs are usually impractical owing to common methodological limitations. The objective of this article is to illustrate how propensity score matching (PSM) and using propensity scores (PS) as a covariate are viable alternatives to reduce estimation error when experimental designs cannot be implemented. To mimic common pediatric research practices, data from 140 simulated participants were used to resemble an experimental and nonexperimental design that assessed the effect of treatment status on participant weight loss for diabetes. Pretreatment participant characteristics (age, gender, physical activity, etc.) were then used to generate PS for use in the various statistical approaches. Results demonstrate how PSM and using the PS as a covariate can be used to reduce estimation error and improve statistical inferences. References for issues related to the implementation of these procedures are provided to assist researchers.

  13. Effectiveness of objectivist online instruction on graduate learners' knowledge and competence

    NASA Astrophysics Data System (ADS)

    Maryannakis, Artemios

    Online courses currently offered by aeronautical institutions are unstructured conversions of traditional courses into Web-based courses that lack the learning theory and instructional design principles framework, thus lacking the efficiency and effectiveness in dealing with the academic demands required to prepare aviation/aerospace professionals for the challenges of the technologically driven twenty-first century. The purpose of this study was to compare the effectiveness of two versions of an aeronautical online graduate course on research methods knowledge and competence: a comprehensive objectivist design and an unstructured design. Quantitative, causal comparative, quasi-experimental methodology was utilized. Using criteria derived from literature, criteria were established for the development and eventual online delivery of a comprehensive objectivist instructional design on graduate research methods learning. Results revealed that the comprehensive objectivist design was significantly more effective than its unstructured counterpart on graduate learners' competence in research methods, but found no significant difference in knowledge. It was recommended that aeronautical institutions (a) create programs with critical thinking and problem solving embedded in their curriculum for enhancing learner competence, and (b) thoroughly train every online instructor in the development and use of comprehensive online instruction.

  14. Optimizing Experimental Design for Comparing Models of Brain Function

    PubMed Central

    Daunizeau, Jean; Preuschoff, Kerstin; Friston, Karl; Stephan, Klaas

    2011-01-01

    This article presents the first attempt to formalize the optimization of experimental design with the aim of comparing models of brain function based on neuroimaging data. We demonstrate our approach in the context of Dynamic Causal Modelling (DCM), which relates experimental manipulations to observed network dynamics (via hidden neuronal states) and provides an inference framework for selecting among candidate models. Here, we show how to optimize the sensitivity of model selection by choosing among experimental designs according to their respective model selection accuracy. Using Bayesian decision theory, we (i) derive the Laplace-Chernoff risk for model selection, (ii) disclose its relationship with classical design optimality criteria and (iii) assess its sensitivity to basic modelling assumptions. We then evaluate the approach when identifying brain networks using DCM. Monte-Carlo simulations and empirical analyses of fMRI data from a simple bimanual motor task in humans serve to demonstrate the relationship between network identification and the optimal experimental design. For example, we show that deciding whether there is a feedback connection requires shorter epoch durations, relative to asking whether there is experimentally induced change in a connection that is known to be present. Finally, we discuss limitations and potential extensions of this work. PMID:22125485

  15. Knowledge Representation Standards and Interchange Formats for Causal Graphs

    NASA Technical Reports Server (NTRS)

    Throop, David R.; Malin, Jane T.; Fleming, Land

    2005-01-01

    In many domains, automated reasoning tools must represent graphs of causally linked events. These include fault-tree analysis, probabilistic risk assessment (PRA), planning, procedures, medical reasoning about disease progression, and functional architectures. Each of these fields has its own requirements for the representation of causation, events, actors and conditions. The representations include ontologies of function and cause, data dictionaries for causal dependency, failure and hazard, and interchange formats between some existing tools. In none of the domains has a generally accepted interchange format emerged. The paper makes progress towards interoperability across the wide range of causal analysis methodologies. We survey existing practice and emerging interchange formats in each of these fields. Setting forth a set of terms and concepts that are broadly shared across the domains, we examine the several ways in which current practice represents them. Some phenomena are difficult to represent or to analyze in several domains. These include mode transitions, reachability analysis, positive and negative feedback loops, conditions correlated but not causally linked and bimodal probability distributions. We work through examples and contrast the differing methods for addressing them. We detail recent work in knowledge interchange formats for causal trees in aerospace analysis applications in early design, safety and reliability. Several examples are discussed, with a particular focus on reachability analysis and mode transitions. We generalize the aerospace analysis work across the several other domains. We also recommend features and capabilities for the next generation of causal knowledge representation standards.

  16. Time, frequency, and time-varying Granger-causality measures in neuroscience.

    PubMed

    Cekic, Sezen; Grandjean, Didier; Renaud, Olivier

    2018-05-20

    This article proposes a systematic methodological review and an objective criticism of existing methods enabling the derivation of time, frequency, and time-varying Granger-causality statistics in neuroscience. The capacity to describe the causal links between signals recorded at different brain locations during a neuroscience experiment is indeed of primary interest for neuroscientists, who often have very precise prior hypotheses about the relationships between recorded brain signals. The increasing interest and the huge number of publications related to this topic calls for this systematic review, which describes the very complex methodological aspects underlying the derivation of these statistics. In this article, we first present a general framework that allows us to review and compare Granger-causality statistics in the time domain, and the link with transfer entropy. Then, the spectral and the time-varying extensions are exposed and discussed together with their estimation and distributional properties. Although not the focus of this article, partial and conditional Granger causality, dynamical causal modelling, directed transfer function, directed coherence, partial directed coherence, and their variant are also mentioned. Copyright © 2018 John Wiley & Sons, Ltd.

  17. Causal conditionals and counterfactuals

    PubMed Central

    Frosch, Caren A.; Byrne, Ruth M.J.

    2012-01-01

    Causal counterfactuals e.g., ‘if the ignition key had been turned then the car would have started’ and causal conditionals e.g., ‘if the ignition key was turned then the car started’ are understood by thinking about multiple possibilities of different sorts, as shown in six experiments using converging evidence from three different types of measures. Experiments 1a and 1b showed that conditionals that comprise enabling causes, e.g., ‘if the ignition key was turned then the car started’ primed people to read quickly conjunctions referring to the possibility of the enabler occurring without the outcome, e.g., ‘the ignition key was turned and the car did not start’. Experiments 2a and 2b showed that people paraphrased causal conditionals by using causal or temporal connectives (because, when), whereas they paraphrased causal counterfactuals by using subjunctive constructions (had…would have). Experiments 3a and 3b showed that people made different inferences from counterfactuals presented with enabling conditions compared to none. The implications of the results for alternative theories of conditionals are discussed. PMID:22858874

  18. The Implications of "Contamination" for Experimental Design in Education

    ERIC Educational Resources Information Center

    Rhoads, Christopher H.

    2011-01-01

    Experimental designs that randomly assign entire clusters of individuals (e.g., schools and classrooms) to treatments are frequently advocated as a way of guarding against contamination of the estimated average causal effect of treatment. However, in the absence of contamination, experimental designs that randomly assign intact clusters to…

  19. Testing the Developmental Origins of Health and Disease Hypothesis for Psychopathology Using Family-Based Quasi-Experimental Designs

    PubMed Central

    D’Onofrio, Brian M.; Class, Quetzal A.; Lahey, Benjamin B.; Larsson, Henrik

    2014-01-01

    The Developmental Origin of Health and Disease (DOHaD) hypothesis is a broad theoretical framework that emphasizes how early risk factors have a causal influence on psychopathology. Researchers have raised concerns about the causal interpretation of statistical associations between early risk factors and later psychopathology because most existing studies have been unable to rule out the possibility of environmental and genetic confounding. In this paper we illustrate how family-based quasi-experimental designs can test the DOHaD hypothesis by ruling out alternative hypotheses. We review the logic underlying sibling-comparison, co-twin control, offspring of siblings/twins, adoption, and in vitro fertilization designs. We then present results from studies using these designs focused on broad indices of fetal development (low birth weight and gestational age) and a particular teratogen, smoking during pregnancy. The results provide mixed support for the DOHaD hypothesis for psychopathology, illustrating the critical need to use design features that rule out unmeasured confounding. PMID:25364377

  20. Causal Structure Learning over Time: Observations and Interventions

    ERIC Educational Resources Information Center

    Rottman, Benjamin M.; Keil, Frank C.

    2012-01-01

    Seven studies examined how people learn causal relationships in scenarios when the variables are temporally dependent--the states of variables are stable over time. When people intervene on X, and Y subsequently changes state compared to before the intervention, people infer that X influences Y. This strategy allows people to learn causal…

  1. Episodic memory and the witness trump card.

    PubMed

    Henry, Jeremy; Craver, Carl

    2018-01-01

    We accept Mahr & Csibra's (M&C's) causal claim that episodic memory provides humans with the means for evaluating the veracity of reports about non-occurrent events. We reject their evolutionary argument that this is the proper function of episodic memory. We explore three intriguing implications of the causal claim, for cognitive neuropsychology, comparative psychology, and philosophy.

  2. Attributions for Pride, Anger, and Guilt among Incarcerated Minority Adolescents.

    ERIC Educational Resources Information Center

    Hudley-Paul, Cynthia A.

    Two studies investigate causal attributions among minority adolescents. The first investigates attributions for the emotions of anger, pride, and guilt among 26 incarcerated male adolescents. Relatively few causes are found for anger and guilt, and a larger variety of causes are cited for pride. A follow-up study then compares causal attributions…

  3. Causal Premise Semantics

    ERIC Educational Resources Information Center

    Kaufmann, Stefan

    2013-01-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal…

  4. Causal beliefs of the public and social acceptance of persons with mental illness: a comparative analysis of schizophrenia, depression and alcohol dependence.

    PubMed

    Schomerus, G; Matschinger, H; Angermeyer, M C

    2014-01-01

    There is an ongoing debate whether biological illness explanations improve tolerance towards persons with mental illness or not. Several theoretical models have been proposed to predict the relationship between causal beliefs and social acceptance. This study uses path models to compare different theoretical predictions regarding attitudes towards persons with schizophrenia, depression and alcohol dependence. In a representative population survey in Germany (n = 3642), we elicited agreement with belief in biogenetic causes, current stress and childhood adversities as causes of either disorder as described in an unlabelled case vignette. We further elicited potentially mediating attitudes related to different theories about the consequences of biogenetic causal beliefs (attribution theory: onset responsibility, offset responsibility; genetic essentialism: differentness, dangerousness; genetic optimism: treatability) and social acceptance. For each vignette condition, we calculated a multiple mediator path model containing all variables. Biogenetic beliefs were associated with lower social acceptance in schizophrenia and depression, and with higher acceptance in alcohol dependence. In schizophrenia and depression, perceived differentness and dangerousness mediated the largest indirect effects, the consequences of biogenetic causal explanations thus being in accordance with the predictions of genetic essentialism. Psychosocial causal beliefs had differential effects: belief in current stress as a cause was associated with higher acceptance in schizophrenia, while belief in childhood adversities resulted in lower acceptance of a person with depression. Biological causal explanations seem beneficial in alcohol dependence, but harmful in schizophrenia and depression. The negative correlates of believing in childhood adversities as a cause of depression merit further exploration.

  5. Objective Self Awareness, Self-Esteem and Causal Attributions for Success and Failure.

    DTIC Science & Technology

    2 (high vs. low self - esteem subjects) design was employed. Objective self -awareness was manipulated by exposing subjects to their image on a wall...The investigation has applied the theory of objective self awareness (Duval and Wicklund, 1972) to the study of causal attributions that actors make...for their past performance. A 2 (male vs. female subject) by 2 (success vs. failure) by 3 (objective self -awareness vs. control vs. time control) by

  6. Research on injury compensation and health outcomes: ignoring the problem of reverse causality led to a biased conclusion.

    PubMed

    Spearing, Natalie M; Connelly, Luke B; Nghiem, Hong S; Pobereskin, Louis

    2012-11-01

    This study highlights the serious consequences of ignoring reverse causality bias in studies on compensation-related factors and health outcomes and demonstrates a technique for resolving this problem of observational data. Data from an English longitudinal study on factors, including claims for compensation, associated with recovery from neck pain (whiplash) after rear-end collisions are used to demonstrate the potential for reverse causality bias. Although it is commonly believed that claiming compensation leads to worse recovery, it is also possible that poor recovery may lead to compensation claims--a point that is seldom considered and never addressed empirically. This pedagogical study compares the association between compensation claiming and recovery when reverse causality bias is ignored and when it is addressed, controlling for the same observable factors. When reverse causality is ignored, claimants appear to have a worse recovery than nonclaimants; however, when reverse causality bias is addressed, claiming compensation appears to have a beneficial effect on recovery, ceteris paribus. To avert biased policy and judicial decisions that might inadvertently disadvantage people with compensable injuries, there is an urgent need for researchers to address reverse causality bias in studies on compensation-related factors and health. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Human Papilloma Viruses and Breast Cancer - Assessment of Causality.

    PubMed

    Lawson, James Sutherland; Glenn, Wendy K; Whitaker, Noel James

    2016-01-01

    High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case-control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is "specificity." HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers.

  8. Human Papilloma Viruses and Breast Cancer – Assessment of Causality

    PubMed Central

    Lawson, James Sutherland; Glenn, Wendy K.; Whitaker, Noel James

    2016-01-01

    High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case–control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is “specificity.” HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers. PMID:27747193

  9. Atypicalities in Perceptual Adaptation in Autism Do Not Extend to Perceptual Causality

    PubMed Central

    Karaminis, Themelis; Turi, Marco; Neil, Louise; Badcock, Nicholas A.; Burr, David; Pellicano, Elizabeth

    2015-01-01

    A recent study showed that adaptation to causal events (collisions) in adults caused subsequent events to be less likely perceived as causal. In this study, we examined if a similar negative adaptation effect for perceptual causality occurs in children, both typically developing and with autism. Previous studies have reported diminished adaptation for face identity, facial configuration and gaze direction in children with autism. To test whether diminished adaptive coding extends beyond high-level social stimuli (such as faces) and could be a general property of autistic perception, we developed a child-friendly paradigm for adaptation of perceptual causality. We compared the performance of 22 children with autism with 22 typically developing children, individually matched on age and ability (IQ scores). We found significant and equally robust adaptation aftereffects for perceptual causality in both groups. There were also no differences between the two groups in their attention, as revealed by reaction times and accuracy in a change-detection task. These findings suggest that adaptation to perceptual causality in autism is largely similar to typical development and, further, that diminished adaptive coding might not be a general characteristic of autism at low levels of the perceptual hierarchy, constraining existing theories of adaptation in autism. PMID:25774507

  10. Stratified exact tests for the weak causal null hypothesis in randomized trials with a binary outcome.

    PubMed

    Chiba, Yasutaka

    2017-09-01

    Fisher's exact test is commonly used to compare two groups when the outcome is binary in randomized trials. In the context of causal inference, this test explores the sharp causal null hypothesis (i.e. the causal effect of treatment is the same for all subjects), but not the weak causal null hypothesis (i.e. the causal risks are the same in the two groups). Therefore, in general, rejection of the null hypothesis by Fisher's exact test does not mean that the causal risk difference is not zero. Recently, Chiba (Journal of Biometrics and Biostatistics 2015; 6: 244) developed a new exact test for the weak causal null hypothesis when the outcome is binary in randomized trials; the new test is not based on any large sample theory and does not require any assumption. In this paper, we extend the new test; we create a version of the test applicable to a stratified analysis. The stratified exact test that we propose is general in nature and can be used in several approaches toward the estimation of treatment effects after adjusting for stratification factors. The stratified Fisher's exact test of Jung (Biometrical Journal 2014; 56: 129-140) tests the sharp causal null hypothesis. This test applies a crude estimator of the treatment effect and can be regarded as a special case of our proposed exact test. Our proposed stratified exact test can be straightforwardly extended to analysis of noninferiority trials and to construct the associated confidence interval. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Causal inference and longitudinal data: a case study of religion and mental health.

    PubMed

    VanderWeele, Tyler J; Jackson, John W; Li, Shanshan

    2016-11-01

    We provide an introduction to causal inference with longitudinal data and discuss the complexities of analysis and interpretation when exposures can vary over time. We consider what types of causal questions can be addressed with the standard regression-based analyses and what types of covariate control and control for the prior values of outcome and exposure must be made to reason about causal effects. We also consider newer classes of causal models, including marginal structural models, that can assess questions of the joint effects of time-varying exposures and can take into account feedback between the exposure and outcome over time. Such feedback renders cross-sectional data ineffective for drawing inferences about causation. The challenges are illustrated by analyses concerning potential effects of religious service attendance on depression, in which there may in fact be effects in both directions with service attendance preventing the subsequent depression, but depression itself leading to lower levels of the subsequent religious service attendance. Longitudinal designs, with careful control for prior exposures, outcomes, and confounders, and suitable methodology, will strengthen research on mental health, religion and health, and in the biomedical and social sciences generally.

  12. [Social determinants of odontalgia in epidemiological studies: theoretical review and proposed conceptual model].

    PubMed

    Bastos, João Luiz Dornelles; Gigante, Denise Petrucci; Peres, Karen Glazer; Nedel, Fúlvio Borges

    2007-01-01

    The epidemiological literature has been limited by the absence of a theoretical framework reflecting the complexity of causal mechanisms for the occurrence of health phenomena / disease conditions. In the field of oral epidemiology, such lack of theory also prevails, since dental caries the leading topic in oral research has been often studied through a biological and reductionist viewpoint. One of the most important consequences of dental caries is dental pain (odontalgia), which has received little attention in studies with sophisticated theoretical models and powerful designs to establish causal relationships. The purpose of this study is to review the scientific literature on the determinants of odontalgia and to discuss theories proposed for the explanation of the phenomenon. Conceptual models and emerging theories on the social determinants of oral health are revised, in an attempt to build up links with the bio-psychosocial pain model, proposing a more elaborate causal model for odontalgia. The framework suggests causal pathways between social structure and oral health through material, psychosocial and behavioral pathways. Aspects of the social structure are highlighted in order to relate them to odontalgia, stressing their importance in discussions of causal relationships in oral health research.

  13. Multivariate causal attribution and cost-effectiveness of a national mass media campaign in the Philippines.

    PubMed

    Kincaid, D Lawrence; Do, Mai Phuong

    2006-01-01

    Cost-effectiveness analysis is based on a simple formula. A dollar estimate of the total cost to conduct a program is divided by the number of people estimated to have been affected by it in terms of some intended outcome. The direct, total costs of most communication campaigns are usually available. Estimating the amount of effect that can be attributed to the communication alone, however is problematical in full-coverage, mass media campaigns where the randomized control group design is not feasible. Single-equation, multiple regression analysis controls for confounding variables but does not adequately address the issue of causal attribution. In this article, multivariate causal attribution (MCA) methods are applied to data from a sample survey of 1,516 married women in the Philippines to obtain a valid measure of the number of new adopters of modern contraceptives that can be causally attributed to a national mass media campaign and to calculate its cost-effectiveness. The MCA analysis uses structural equation modeling to test the causal pathways and to test for endogeneity, biprobit analysis to test for direct effects of the campaign and endogeneity, and propensity score matching to create a statistically equivalent, matched control group that approximates the results that would have been obtained from a randomized control group design. The MCA results support the conclusion that the observed, 6.4 percentage point increase in modern contraceptive use can be attributed to the national mass media campaign and to its indirect effects on attitudes toward contraceptives. This net increase represented 348,695 new adopters in the population of married women at a cost of U.S. $1.57 per new adopter.

  14. Assessing the causal role of adiposity on disordered eating in childhood, adolescence, and adulthood: a Mendelian randomization analysis

    PubMed Central

    2017-01-01

    Background: Observational studies have shown that higher body mass index (BMI) is associated with increased risk of developing disordered eating patterns. However, the causal direction of this relation remains ambiguous. Objective: We used Mendelian randomization (MR) to infer the direction of causality between BMI and disordered eating in childhood, adolescence, and adulthood. Design: MR analyses were conducted with a genetic score as an instrumental variable for BMI to assess the causal effect of BMI at age 7 y on disordered eating patterns at age 13 y with the use of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 4473). To examine causality in the reverse direction, MR analyses were used to estimate the effect of the same disordered eating patterns at age 13 y on BMI at age 17 y via a split-sample approach in the ALSPAC. We also investigated the causal direction of the association between BMI and eating disorders (EDs) in adults via a two-sample MR approach and publically available genome-wide association study data. Results: MR results indicated that higher BMI at age 7 y likely causes higher levels of binge eating and overeating, weight and shape concerns, and weight-control behavior patterns in both males and females and food restriction in males at age 13 y. Furthermore, results suggested that higher levels of binge eating and overeating in males at age 13 y likely cause higher BMI at age 17 y. We showed no evidence of causality between BMI and EDs in adulthood in either direction. Conclusions: This study provides evidence to suggest a causal effect of higher BMI in childhood and increased risk of disordered eating at age 13 y. Furthermore, higher levels of binge eating and overeating may cause higher BMI in later life. These results encourage an exploration of the ways to break the causal chain between these complex phenotypes, which could inform and prevent disordered eating problems in adolescence. PMID:28747331

  15. Assessing the causal role of adiposity on disordered eating in childhood, adolescence, and adulthood: a Mendelian randomization analysis.

    PubMed

    Reed, Zoe E; Micali, Nadia; Bulik, Cynthia M; Davey Smith, George; Wade, Kaitlin H

    2017-09-01

    Background: Observational studies have shown that higher body mass index (BMI) is associated with increased risk of developing disordered eating patterns. However, the causal direction of this relation remains ambiguous. Objective: We used Mendelian randomization (MR) to infer the direction of causality between BMI and disordered eating in childhood, adolescence, and adulthood. Design: MR analyses were conducted with a genetic score as an instrumental variable for BMI to assess the causal effect of BMI at age 7 y on disordered eating patterns at age 13 y with the use of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) ( n = 4473). To examine causality in the reverse direction, MR analyses were used to estimate the effect of the same disordered eating patterns at age 13 y on BMI at age 17 y via a split-sample approach in the ALSPAC. We also investigated the causal direction of the association between BMI and eating disorders (EDs) in adults via a two-sample MR approach and publically available genome-wide association study data. Results: MR results indicated that higher BMI at age 7 y likely causes higher levels of binge eating and overeating, weight and shape concerns, and weight-control behavior patterns in both males and females and food restriction in males at age 13 y. Furthermore, results suggested that higher levels of binge eating and overeating in males at age 13 y likely cause higher BMI at age 17 y. We showed no evidence of causality between BMI and EDs in adulthood in either direction. Conclusions: This study provides evidence to suggest a causal effect of higher BMI in childhood and increased risk of disordered eating at age 13 y. Furthermore, higher levels of binge eating and overeating may cause higher BMI in later life. These results encourage an exploration of the ways to break the causal chain between these complex phenotypes, which could inform and prevent disordered eating problems in adolescence.

  16. Progress in high-level exploratory vision

    NASA Astrophysics Data System (ADS)

    Brand, Matthew

    1993-08-01

    We have been exploring the hypothesis that vision is an explanatory process, in which causal and functional reasoning about potential motion plays an intimate role in mediating the activity of low-level visual processes. In particular, we have explored two of the consequences of this view for the construction of purposeful vision systems: Causal and design knowledge can be used to (1) drive focus of attention, and (2) choose between ambiguous image interpretations. An important result of visual understanding is an explanation of the scene's causal structure: How action is originated, constrained, and prevented, and what will happen in the immediate future. In everyday visual experience, most action takes the form of motion, and most causal analysis takes the form of dynamical analysis. This is even true of static scenes, where much of a scene's interest lies in how possible motions are arrested. This paper describes our progress in developing domain theories and visual processes for the understanding of various kinds of structured scenes, including structures built out of children's constructive toys and simple mechanical devices.

  17. Evaluating ritual efficacy: evidence from the supernatural.

    PubMed

    Legare, Cristine H; Souza, André L

    2012-07-01

    Rituals pose a cognitive paradox: although widely used to treat problems, rituals are causally opaque (i.e., they lack a causal explanation for their effects). How is the efficacy of ritual action evaluated in the absence of causal information? To examine this question using ecologically valid content, three studies (N=162) were conducted in Brazil, a cultural context in which rituals called simpatias are used to treat a great variety of problems ranging from asthma to infidelity. Using content from existing simpatias, experimental simpatias were designed to manipulate the kinds of information that influences perceptions of efficacy. A fourth study (N=68) with identical stimuli was conducted with a US sample to assess the generalizability of the findings across two different cultural contexts. The results provide evidence that information reflecting intuitive causal principles (i.e., repetition of procedures, number of procedural steps) and transcendental influence (i.e., presence of religious icons) affects how people evaluate ritual efficacy. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Packet Randomized Experiments for Eliminating Classes of Confounders

    PubMed Central

    Pavela, Greg; Wiener, Howard; Fontaine, Kevin R.; Fields, David A.; Voss, Jameson D.; Allison, David B.

    2014-01-01

    Background Although randomization is considered essential for causal inference, it is often not possible to randomize in nutrition and obesity research. To address this, we develop a framework for an experimental design—packet randomized experiments (PREs), which improves causal inferences when randomization on a single treatment variable is not possible. This situation arises when subjects are randomly assigned to a condition (such as a new roommate) which varies in one characteristic of interest (such as weight), but also varies across many others. There has been no general discussion of this experimental design, including its strengths, limitations, and statistical properties. As such, researchers are left to develop and apply PREs on an ad hoc basis, limiting its potential to improve causal inferences among nutrition and obesity researchers. Methods We introduce PREs as an intermediary design between randomized controlled trials and observational studies. We review previous research that used the PRE design and describe its application in obesity-related research, including random roommate assignments, heterochronic parabiosis, and the quasi-random assignment of subjects to geographic areas. We then provide a statistical framework to control for potential packet-level confounders not accounted for by randomization. Results PREs have successfully been used to improve causal estimates of the effect of roommates, altitude, and breastfeeding on weight outcomes. When certain assumptions are met, PREs can asymptotically control for packet-level characteristics. This has the potential to statistically estimate the effect of a single treatment even when randomization to a single treatment did not occur. Conclusions Applying PREs to obesity-related research will improve decisions about clinical, public health, and policy actions insofar as it offers researchers new insight into cause and effect relationships among variables. PMID:25444088

  19. Recognising discourse causality triggers in the biomedical domain.

    PubMed

    Mihăilă, Claudiu; Ananiadou, Sophia

    2013-12-01

    Current domain-specific information extraction systems represent an important resource for biomedical researchers, who need to process vast amounts of knowledge in a short time. Automatic discourse causality recognition can further reduce their workload by suggesting possible causal connections and aiding in the curation of pathway models. We describe here an approach to the automatic identification of discourse causality triggers in the biomedical domain using machine learning. We create several baselines and experiment with and compare various parameter settings for three algorithms, i.e. Conditional Random Fields (CRF), Support Vector Machines (SVM) and Random Forests (RF). We also evaluate the impact of lexical, syntactic, and semantic features on each of the algorithms, showing that semantics improves the performance in all cases. We test our comprehensive feature set on two corpora containing gold standard annotations of causal relations, and demonstrate the need for more gold standard data. The best performance of 79.35% F-score is achieved by CRFs when using all three feature types.

  20. What Works Clearinghouse Standards and Generalization of Single-Case Design Evidence

    ERIC Educational Resources Information Center

    Hitchcock, John H.; Kratochwill, Thomas R.; Chezan, Laura C.

    2015-01-01

    A recent review of existing rubrics designed to help researchers evaluate the internal and external validity of single-case design (SCD) studies found that the various options yield consistent results when examining causal arguments. The authors of the review, however, noted considerable differences across the rubrics when addressing the…

  1. How Can Comparison Groups Strengthen Regression Discontinuity Designs?

    ERIC Educational Resources Information Center

    Wing, Coady; Cook, Thomas D.

    2011-01-01

    In this paper, the authors examine some of the ways that different types of non-equivalent comparison groups can be used to strengthen causal inferences based on regression discontinuity design (RDD). First, they consider a design that incorporates pre-test data on assignment scores and outcomes that were collected either before the treatment…

  2. Developing a (Non-Linear) Practice of Design Thinking

    ERIC Educational Resources Information Center

    Teal, Randall

    2010-01-01

    Design thinking can be a powerful way to engage the world, allowing interactive understandings that are both analytic and experiential. When fully functioning, design thinking necessarily calls upon faculties often considered a-rational, a-causal and a-logical. Unfortunately, such faculties often give rise to academic suspicion. That is to say,…

  3. Causal inferences on the effectiveness of complex social programs: Navigating assumptions, sources of complexity and evaluation design challenges.

    PubMed

    Chatterji, Madhabi

    2016-12-01

    This paper explores avenues for navigating evaluation design challenges posed by complex social programs (CSPs) and their environments when conducting studies that call for generalizable, causal inferences on the intervention's effectiveness. A definition is provided of a CSP drawing on examples from different fields, and an evaluation case is analyzed in depth to derive seven (7) major sources of complexity that typify CSPs, threatening assumptions of textbook-recommended experimental designs for performing impact evaluations. Theoretically-supported, alternative methodological strategies are discussed to navigate assumptions and counter the design challenges posed by the complex configurations and ecology of CSPs. Specific recommendations include: sequential refinement of the evaluation design through systems thinking, systems-informed logic modeling; and use of extended term, mixed methods (ETMM) approaches with exploratory and confirmatory phases of the evaluation. In the proposed approach, logic models are refined through direct induction and interactions with stakeholders. To better guide assumption evaluation, question-framing, and selection of appropriate methodological strategies, a multiphase evaluation design is recommended. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Using causal loop diagrams for the initialization of stakeholder engagement in soil salinity management in agricultural watersheds in developing countries: a case study in the Rechna Doab watershed, Pakistan.

    PubMed

    Inam, Azhar; Adamowski, Jan; Halbe, Johannes; Prasher, Shiv

    2015-04-01

    Over the course of the last twenty years, participatory modeling has increasingly been advocated as an integral component of integrated, adaptive, and collaborative water resources management. However, issues of high cost, time, and expertise are significant hurdles to the widespread adoption of participatory modeling in many developing countries. In this study, a step-wise method to initialize the involvement of key stakeholders in the development of qualitative system dynamics models (i.e. causal loop diagrams) is presented. The proposed approach is designed to overcome the challenges of low expertise, time and financial resources that have hampered previous participatory modeling efforts in developing countries. The methodological framework was applied in a case study of soil salinity management in the Rechna Doab region of Pakistan, with a focus on the application of qualitative modeling through stakeholder-built causal loop diagrams to address soil salinity problems in the basin. Individual causal loop diagrams were developed by key stakeholder groups, following which an overall group causal loop diagram of the entire system was built based on the individual causal loop diagrams to form a holistic qualitative model of the whole system. The case study demonstrates the usefulness of the proposed approach, based on using causal loop diagrams in initiating stakeholder involvement in the participatory model building process. In addition, the results point to social-economic aspects of soil salinity that have not been considered by other modeling studies to date. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Combining Propensity Score Methods and Complex Survey Data to Estimate Population Treatment Effects

    ERIC Educational Resources Information Center

    Stuart, Elizabeth A.; Dong, Nianbo; Lenis, David

    2016-01-01

    Complex surveys are often used to estimate causal effects regarding the effects of interventions or exposures of interest. Propensity scores (Rosenbaum & Rubin, 1983) have emerged as one popular and effective tool for causal inference in non-experimental studies, as they can help ensure that groups being compared are similar with respect to a…

  6. Compared to What? The Effectiveness of Synthetic Control Methods for Causal Inference in Educational Assessment

    ERIC Educational Resources Information Center

    Johnson, Clay Stephen

    2013-01-01

    Synthetic control methods are an innovative matching technique first introduced within the economics and political science literature that have begun to find application in educational research as well. Synthetic controls create an aggregate-level, time-series comparison for a single treated unit of interest for causal inference with observational…

  7. A Discordant Monozygotic Twin Design Shows Blunted Cortisol Reactivity Among Bullied Children

    PubMed Central

    Ouellet-Morin, Isabelle; Danese, Andrea; Bowes, Lucy; Shakoor, Sania; Ambler, Antony; Pariante, Carmine M.; Papadopoulos, Andrew S.; Caspi, Avshalom; Moffitt, Terrie E.; Arseneault, Louise

    2013-01-01

    Objective Childhood adverse experiences are known to engender persistent changes in stress-related systems and brain structures involved in mood, cognition, and behavior in animal models. Uncertainty remains about the causal effect of early stressful experiences on physiological response to stress in human beings, as the impact of these experiences has rarely been investigated while controlling for both genetic and shared environmental influences. Method We tested whether bullying victimization, a repeated adverse experience in childhood, influences cortisol responses to a psychosocial stress test (PST) using a discordant monozygotic (MZ) twin design. Thirty pairs (43.3% males) of 12-year-old MZ twins discordant for bullying victimization were identified in the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative 1994–1995 cohort of families with twins. Results Bullied and nonbullied MZ twins showed distinct patterns of cortisol secretion after the PST. Specifically, bullied twins exhibited a blunted cortisol response compared with their nonbullied MZ co-twins, who showed the expected increase. This difference in cortisol response to stress could not be attributed to children's genetic makeup, their familial environments, pre-existing and concomitant individual factors, or the perception of stress and emotional response to the PST. Conclusion Results from this natural experiment provide support for a causal effect of adverse childhood experiences on the neuroendocrine response to stress. PMID:21621141

  8. Evaluating distance learning in health informatics education.

    PubMed

    Russell, Barbara L; Barefield, Amanda C; Turnbull, Diane; Leibach, Elizabeth; Pretlow, Lester

    2008-04-24

    The purpose of this study was to compare academic performance between distance-learning and on-campus health informatics students. A quantitative causal-comparative research design was utilized, and academic performance was measured by final GPA scores and Registered Health Information Administrator certification exam scores. Differences in previous academic performance between the two groups were also determined by comparing overall admission GPA and math/science admission GPA. The researchers found no difference in academic performance between the two groups when final GPA scores and total certification scores were compared. However, there were statistically significant differences between the two groups in 4 of the 17 sub-domains of the certification examination, with the on-campus students scoring slightly higher than the distance students. Correlation studies were also performed, and the researchers found significant correlations between overall admission GPA, math/science admission GPA, final GPA, and certification scores.

  9. Design of trials for interrupting the transmission of endemic pathogens.

    PubMed

    Silkey, Mariabeth; Homan, Tobias; Maire, Nicolas; Hiscox, Alexandra; Mukabana, Richard; Takken, Willem; Smith, Thomas A

    2016-06-06

    Many interventions against infectious diseases have geographically diffuse effects. This leads to contamination between arms in cluster-randomized trials (CRTs). Pathogen elimination is the goal of many intervention programs against infectious agents, but contamination means that standard CRT designs and analyses do not provide inferences about the potential of interventions to interrupt pathogen transmission at maximum scale-up. A generic model of disease transmission was used to simulate infections in stepped wedge cluster-randomized trials (SWCRTs) of a transmission-reducing intervention, where the intervention has spatially diffuse effects. Simulations of such trials were then used to examine the potential of such designs for providing generalizable causal inferences about the impact of such interventions, including measurements of the contamination effects. The simulations were applied to the geography of Rusinga Island, Lake Victoria, Kenya, the site of the SolarMal trial on the use of odor-baited mosquito traps to eliminate Plasmodium falciparum malaria. These were used to compare variants in the proposed SWCRT designs for the SolarMal trial. Measures of contamination effects were found that could be assessed in the simulated trials. Inspired by analyses of trials of insecticide-treated nets against malaria when applied to the geography of the SolarMal trial, these measures were found to be robust to different variants of SWCRT design. Analyses of the likely extent of contamination effects supported the choice of cluster size for the trial. The SWCRT is an appropriate design for trials that assess the feasibility of local elimination of a pathogen. The effects of incomplete coverage can be estimated by analyzing the extent of contamination between arms in such trials, and the estimates also support inferences about causality. The SolarMal example illustrates how generic transmission models incorporating spatial smoothing can be used to simulate such trials for a power calculation and optimization of cluster size and randomization strategies. The approach is applicable to a range of infectious diseases transmitted via environmental reservoirs or via arthropod vectors.

  10. Bayesian networks improve causal environmental ...

    EPA Pesticide Factsheets

    Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

  11. Narrative review of yoga intervention clinical trials including weight-related outcomes.

    PubMed

    Rioux, Jennifer Grace; Ritenbaugh, Cheryl

    2013-01-01

    Medical authorities have identified obesity as a causal factor in the development of diabetes, hypertension, and cardiovascular disease (CVD), and more broadly, of metabolic syndrome/insulin resistance syndrome. To provide solutions that can modify this risk factor, researchers need to identify methods of effective risk reduction and primary prevention of obesity. Research on the effectiveness of yoga as a treatment for obesity is limited, and studies vary in overall quality and methodological rigor. This narrative review assessed the quantity and quality of clinical trials of yoga as an intervention for weight loss or as a means of risk reduction or treatment for obesity and diseases in which obesity is a causal factor. This review summarized the studies' research designs and evaluated the efficacy of yoga for weight loss via the current evidence base. The research team evaluated published studies to determine the appropriateness of research designs, comparability of programs' intervention elements, and standardization of outcome measures. The research team's literature search used the key terms yoga and obesity or yoga and weight loss in three primary medical-literature databases (PubMed, PsychInfo, and Web of Science). The study excluded clinical trials with no quantitative obesity related measure. Extracted data included each study's (1) design; (2) setting and population; (3) nature, duration, and frequency of interventions; (4) comparison groups; (5) recruitment strategies; (6) outcome measures; (7) data analysis and presentation; and (8) results and conclusions. The research team developed an overall evaluation parameter to compare disparate trials. The research team reviewed each study to determine its key features, each worth a specified number of points, with a maximum total of 20 points. The features included a study's (1) duration, (2) frequency of yoga practice, (3) intensity of (length of) each practice, (4) number of yogic elements, (5) inclusion of dietary modification, (6) inclusion of a residential component, (7) the number of weight-related outcome measures, and (8) a discussion of the details of the yogic elements. Overall, therapeutic yoga programs are frequently effective in promoting weight loss and/or improvements in body composition. The effectiveness of yoga for weight loss is related to the following key features: (1) an increased frequency of practice; (2) a longer intervention duration (3) a yogic dietary component; (4) a residential component; (5) the comprehensive inclusion of yogic components; (5) and a home-practice component. Yoga appears to be an appropriate and potentially successful intervention for weight maintenance, prevention of obesity, and risk reduction for diseases in which obesity plays a significant causal role.

  12. Using Qualitative Comparative Analysis of Key Informant Interviews in Health Services Research: Enhancing a Study of Adjuvant Therapy Use in Breast Cancer Care.

    PubMed

    McAlearney, Ann Scheck; Walker, Daniel; Moss, Alexandra D; Bickell, Nina A

    2016-04-01

    Qualitative comparative analysis (QCA) is a methodology created to address causal complexity in social sciences research by preserving the objectivity of quantitative data analysis without losing detail inherent in qualitative research. However, its use in health services research (HSR) is limited, and questions remain about its application in this context. To explore the strengths and weaknesses of using QCA for HSR. Using data from semistructured interviews conducted as part of a multiple case study about adjuvant treatment underuse among underserved breast cancer patients, findings were compared using qualitative approaches with and without QCA to identify strengths, challenges, and opportunities presented by QCA. Ninety administrative and clinical key informants interviewed across 10 NYC area safety net hospitals. Transcribed interviews were coded by 3 investigators using an iterative and interactive approach. Codes were calibrated for QCA, as well as examined using qualitative analysis without QCA. Relative to traditional qualitative analysis, QCA strengths include: (1) addressing causal complexity, (2) results presentation as pathways as opposed to a list, (3) identification of necessary conditions, (4) the option of fuzzy-set calibrations, and (5) QCA-specific parameters of fit that allow researchers to compare outcome pathways. Weaknesses include: (1) few guidelines and examples exist for calibrating interview data, (2) not designed to create predictive models, and (3) unidirectionality. Through its presentation of results as pathways, QCA can highlight factors most important for production of an outcome. This strength can yield unique benefits for HSR not available through other methods.

  13. Causal transfer function analysis to describe closed loop interactions between cardiovascular and cardiorespiratory variability signals.

    PubMed

    Faes, L; Porta, A; Cucino, R; Cerutti, S; Antolini, R; Nollo, G

    2004-06-01

    Although the concept of transfer function is intrinsically related to an input-output relationship, the traditional and widely used estimation method merges both feedback and feedforward interactions between the two analyzed signals. This limitation may endanger the reliability of transfer function analysis in biological systems characterized by closed loop interactions. In this study, a method for estimating the transfer function between closed loop interacting signals was proposed and validated in the field of cardiovascular and cardiorespiratory variability. The two analyzed signals x and y were described by a bivariate autoregressive model, and the causal transfer function from x to y was estimated after imposing causality by setting to zero the model coefficients representative of the reverse effects from y to x. The method was tested in simulations reproducing linear open and closed loop interactions, showing a better adherence of the causal transfer function to the theoretical curves with respect to the traditional approach in presence of non-negligible reverse effects. It was then applied in ten healthy young subjects to characterize the transfer functions from respiration to heart period (RR interval) and to systolic arterial pressure (SAP), and from SAP to RR interval. In the first two cases, the causal and non-causal transfer function estimates were comparable, indicating that respiration, acting as exogenous signal, sets an open loop relationship upon SAP and RR interval. On the contrary, causal and traditional transfer functions from SAP to RR were significantly different, suggesting the presence of a considerable influence on the opposite causal direction. Thus, the proposed causal approach seems to be appropriate for the estimation of parameters, like the gain and the phase lag from SAP to RR interval, which have a large clinical and physiological relevance.

  14. Drug- and Herb-Induced Liver Injury in Clinical and Translational Hepatology: Causality Assessment Methods, Quo Vadis?

    PubMed Central

    Eickhoff, Axel; Schulze, Johannes

    2013-01-01

    Drug-induced liver injury (DILI) and herb-induced liver injury (HILI) are typical diseases of clinical and translational hepatology. Their diagnosis is complex and requires an experienced clinician to translate basic science into clinical judgment and identify a valid causality algorithm. To prospectively assess causality starting on the day DILI or HILI is suspected, the best approach for physicians is to use the Council for International Organizations of Medical Sciences (CIOMS) scale in its original or preferably its updated version. The CIOMS scale is validated, liver-specific, structured, and quantitative, providing final causality grades based on scores of specific items for individual patients. These items include latency period, decline in liver values after treatment cessation, risk factors, co-medication, alternative diagnoses, hepatotoxicity track record of the suspected product, and unintentional re-exposure. Provided causality is established as probable or highly probable, data of the CIOMS scale with all individual items, a short clinical report, and complete raw data should be transmitted to the regulatory agencies, manufacturers, expert panels, and possibly to the scientific community for further refinement of the causality evaluation in a setting of retrospective expert opinion. Good-quality case data combined with thorough CIOMS-based assessment as a standardized approach should avert subsequent necessity for other complex causality assessment methods that may have inter-rater problems because of poor-quality data. In the future, the CIOMS scale will continue to be the preferred tool to assess causality of DILI and HILI cases and should be used consistently, both prospectively by physicians, and retrospectively for subsequent expert opinion if needed. For comparability and international harmonization, all parties assessing causality in DILI and HILI cases should attempt this standardized approach using the updated CIOMS scale. PMID:26357608

  15. Understanding and Using Mediators and Moderators

    ERIC Educational Resources Information Center

    Wu, Amery D.; Zumbo, Bruno D.

    2008-01-01

    Mediation and moderation are two theories for refining and understanding a causal relationship. Empirical investigation of mediators and moderators requires an integrated research design rather than the data analyses driven approach often seen in the literature. This paper described the conceptual foundation, research design, data analysis, as…

  16. Clinical Research Methodology 2: Observational Clinical Research.

    PubMed

    Sessler, Daniel I; Imrey, Peter B

    2015-10-01

    Case-control and cohort studies are invaluable research tools and provide the strongest feasible research designs for addressing some questions. Case-control studies usually involve retrospective data collection. Cohort studies can involve retrospective, ambidirectional, or prospective data collection. Observational studies are subject to errors attributable to selection bias, confounding, measurement bias, and reverse causation-in addition to errors of chance. Confounding can be statistically controlled to the extent that potential factors are known and accurately measured, but, in practice, bias and unknown confounders usually remain additional potential sources of error, often of unknown magnitude and clinical impact. Causality-the most clinically useful relation between exposure and outcome-can rarely be definitively determined from observational studies because intentional, controlled manipulations of exposures are not involved. In this article, we review several types of observational clinical research: case series, comparative case-control and cohort studies, and hybrid designs in which case-control analyses are performed on selected members of cohorts. We also discuss the analytic issues that arise when groups to be compared in an observational study, such as patients receiving different therapies, are not comparable in other respects.

  17. Revisiting causal neighborhood effects on individual ischemic heart disease risk: a quasi-experimental multilevel analysis among Swedish siblings.

    PubMed

    Merlo, Juan; Ohlsson, Henrik; Chaix, Basile; Lichtenstein, Paul; Kawachi, Ichiro; Subramanian, S V

    2013-01-01

    Neighborhood socioeconomic disadvantage is associated to increased individual risk of ischemic heart disease (IHD). However, the value of this association for causal inference is uncertain. Moreover, neighborhoods are often defined by available administrative boundaries without evaluating in which degree these boundaries embrace a relevant socio-geographical context that condition individual differences in IHD risk. Therefore, we performed an analysis of variance, and also compared the associations obtained by conventional multilevel analyses and by quasi-experimental family-based design that provides stronger evidence for causal inference. Linking the Swedish Multi-Generation Register to several other national registers, we analyzed 184,931 families embracing 415,540 full brothers 45-64 years old in 2004, and residing in 8408 small-area market statistics (SAMS) considered as "neighborhoods" in our study. We investigated the association between low neighborhood income (categorized in groups by deciles) and IHD risk in the next four years. We distinguished between family mean and intrafamilial-centered low neighborhood income, which allowed us to investigate both unrelated individuals from different families and full brothers within families. We applied multilevel logistic regression techniques to obtain odds ratios (OR), variance partition coefficients (VPC) and 95% credible intervals (CI). In unrelated individuals a decile unit increase of low neighborhood income increased individual IHD risk (OR = 1.04, 95% CI: 1.03-1.07). In the intrafamilial analysis this association was reduced (OR = 1.02, 95% CI: 1.02-1.04). Low neighborhood income seems associated with IHD risk in middle-aged men. However, despite the family-based design, we cannot exclude residual confounding by genetic and non-shared environmental factors. Besides, the low neighborhood level VPC = 1.5% suggest that the SAMS are a rather inappropriate construct of the socio-geographic context that conditions individual variance in IHD risk. In contrast the high family level VPC = 20.1% confirms the relevance of the family context for understanding IHD risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Evidence for the effectiveness of minimum pricing of alcohol: a systematic review and assessment using the Bradford Hill criteria for causality

    PubMed Central

    Scannell, Jack W; Marlow, Sally

    2017-01-01

    Objectives To assess the evidence for price-based alcohol policy interventions to determine whether minimum unit pricing (MUP) is likely to be effective. Design Systematic review and assessment of studies according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, against the Bradford Hill criteria for causality. Three electronic databases were searched from inception to February 2017. Additional articles were found through hand searching and grey literature searches. Criteria for selecting studies We included any study design that reported on the effect of price-based interventions on alcohol consumption or alcohol-related morbidity, mortality and wider harms. Studies reporting on the effects of taxation or affordability and studies that only investigated price elasticity of demand were beyond the scope of this review. Studies with any conflict of interest were excluded. All studies were appraised for methodological quality. Results Of 517 studies assessed, 33 studies were included: 26 peer-reviewed research studies and seven from the grey literature. All nine of the Bradford Hill criteria were met, although different types of study satisfied different criteria. For example, modelling studies complied with the consistency and specificity criteria, time series analyses demonstrated the temporality and experiment criteria, and the analogy criterion was fulfilled by comparing the findings with the wider literature on taxation and affordability. Conclusions Overall, the Bradford Hill criteria for causality were satisfied. There was very little evidence that minimum alcohol prices are not associated with consumption or subsequent harms. However the overall quality of the evidence was variable, a large proportion of the evidence base has been produced by a small number of research teams, and the quantitative uncertainty in many estimates or forecasts is often poorly communicated outside the academic literature. Nonetheless, price-based alcohol policy interventions such as MUP are likely to reduce alcohol consumption, alcohol-related morbidity and mortality. PMID:28588106

  19. [Eco-epidemiology: towards epidemiology of complexity].

    PubMed

    Bizouarn, Philippe

    2016-05-01

    In order to solve public health problems posed by the epidemiology of risk factors centered on the individual and neglecting the causal processes linking the risk factors with the health outcomes, Mervyn Susser proposed a multilevel epidemiology called eco-epidemiology, addressing the interdependence of individuals and their connection with molecular, individual, societal, environmental levels of organization participating in the causal disease processes. The aim of this epidemiology is to integrate more than a level of organization in design, analysis and interpretation of health problems. After presenting the main criticisms of risk-factor epidemiology focused on the individual, we will try to show how eco-epidemiology and its development could help to understand the need for a broader and integrative epidemiology, in which studies designed to identify risk factors would be balanced by studies designed to answer other questions equally vital to public health. © 2016 médecine/sciences – Inserm.

  20. Skeletal Muscle Pump Drives Control of Cardiovascular and Postural Systems

    NASA Astrophysics Data System (ADS)

    Verma, Ajay K.; Garg, Amanmeet; Xu, Da; Bruner, Michelle; Fazel-Rezai, Reza; Blaber, Andrew P.; Tavakolian, Kouhyar

    2017-03-01

    The causal interaction between cardio-postural-musculoskeletal systems is critical in maintaining postural stability under orthostatic challenge. The absence or reduction of such interactions could lead to fainting and falls often experienced by elderly individuals. The causal relationship between systolic blood pressure (SBP), calf electromyography (EMG), and resultant center of pressure (COPr) can quantify the behavior of cardio-postural control loop. Convergent cross mapping (CCM) is a non-linear approach to establish causality, thus, expected to decipher nonlinear causal cardio-postural-musculoskeletal interactions. Data were acquired simultaneously from young participants (25 ± 2 years, n = 18) during a 10-minute sit-to-stand test. In the young population, skeletal muscle pump was found to drive blood pressure control (EMG → SBP) as well as control the postural sway (EMG → COPr) through the significantly higher causal drive in the direction towards SBP and COPr. Furthermore, the effect of aging on muscle pump activation associated with blood pressure regulation was explored. Simultaneous EMG and SBP were acquired from elderly group (69 ± 4 years, n = 14). A significant (p = 0.002) decline in EMG → SBP causality was observed in the elderly group, compared to the young group. The results highlight the potential of causality to detect alteration in blood pressure regulation with age, thus, a potential clinical utility towards detection of fall proneness.

  1. A short educational intervention diminishes causal illusions and specific paranormal beliefs in undergraduates.

    PubMed

    Barberia, Itxaso; Tubau, Elisabet; Matute, Helena; Rodríguez-Ferreiro, Javier

    2018-01-01

    Cognitive biases such as causal illusions have been related to paranormal and pseudoscientific beliefs and, thus, pose a real threat to the development of adequate critical thinking abilities. We aimed to reduce causal illusions in undergraduates by means of an educational intervention combining training-in-bias and training-in-rules techniques. First, participants directly experienced situations that tend to induce the Barnum effect and the confirmation bias. Thereafter, these effects were explained and examples of their influence over everyday life were provided. Compared to a control group, participants who received the intervention showed diminished causal illusions in a contingency learning task and a decrease in the precognition dimension of a paranormal belief scale. Overall, results suggest that evidence-based educational interventions like the one presented here could be used to significantly improve critical thinking skills in our students.

  2. Psychogenic Explanations of Physical Illness: Time to Examine the Evidence.

    PubMed

    Wilshire, Carolyn E; Ward, Tony

    2016-09-01

    In some patients with chronic physical complaints, detailed examination fails to reveal a well-recognized underlying disease process. In this situation, the physician may suspect a psychological cause. In this review, we critically evaluated the evidence for this causal claim, focusing on complaints presenting as neurological disorders. There were four main conclusions. First, patients with these complaints frequently exhibit psychopathology but not consistently more often than patients with a comparable "organic" diagnosis, so a causal role cannot be inferred. Second, these patients report a high incidence of adverse life experiences, but again, there is insufficient evidence to indicate a causal role for any particular type of experience. Third, although psychogenic illnesses are believed to be more responsive to psychological interventions than comparable "organic" illnesses, there is currently no evidence to support this claim. Finally, recent evidence suggests that biological and physical factors play a much greater causal role in these illnesses than previously believed. We conclude that there is currently little evidential support for psychogenic theories of illness in the neurological domain. In future research, researchers need to take a wider view concerning the etiology of these illnesses. © The Author(s) 2016.

  3. Regression Discontinuity Designs: A Guide to Practice. NBER Working Paper No. 13039

    ERIC Educational Resources Information Center

    Imbens, Guido; Lemieux, Thomas

    2007-01-01

    In Regression Discontinuity (RD) designs for evaluating causal effects of interventions, assignment to a treatment is determined at least partly by the value of an observed covariate lying on either side of a fixed threshold. These designs were first introduced in the evaluation literature by Thistlewaite and Campbell (1960). With the exception of…

  4. What Is Design-Based Causal Inference for RCTs and Why Should I Use It? NCEE 2017-4025

    ERIC Educational Resources Information Center

    Schochet, Peter Z.

    2017-01-01

    Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and…

  5. New Estimates of Design Parameters for Clustered Randomization Studies: Findings from North Carolina and Florida. Working Paper 43

    ERIC Educational Resources Information Center

    Xu, Zeyu; Nichols, Austin

    2010-01-01

    The gold standard in making causal inference on program effects is a randomized trial. Most randomization designs in education randomize classrooms or schools rather than individual students. Such "clustered randomization" designs have one principal drawback: They tend to have limited statistical power or precision. This study aims to…

  6. Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

    PubMed

    Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

    2015-01-01

    The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

  7. Globally conditioned Granger causality in brain–brain and brain–heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study

    PubMed Central

    Passamonti, Luca; Wald, Lawrence L.; Barbieri, Riccardo

    2016-01-01

    The causal, directed interactions between brain regions at rest (brain–brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain–heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain–brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain–brain and brain–heart interactions reflecting central modulation of ANS outflow. PMID:27044985

  8. Causality in cancer research: a journey through models in molecular epidemiology and their philosophical interpretation.

    PubMed

    Vineis, Paolo; Illari, Phyllis; Russo, Federica

    2017-01-01

    In the last decades, Systems Biology (including cancer research) has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making different traditions of thought compatible: (a) causality in epidemiology and in philosophical theorizing-notably, the "sufficient-component-cause framework" and the "mark transmission" approach; (b) new acquisitions about disease pathogenesis, e.g. the "branched model" in cancer, and the role of biomarkers in this process; (c) the burgeoning of omics research, with a large number of "signals" and of associations that need to be interpreted. In the paper we summarize first the current views on carcinogenesis, and then explore the relevance of current philosophical interpretations of "cancer causes". We try to offer a unifying framework to incorporate biomarkers and omic data into causal models, referring to a position called "evidential pluralism". According to this view, causal reasoning is based on both "evidence of difference-making" (e.g. associations) and on "evidence of underlying biological mechanisms". We conceptualize the way scientists detect and trace signals in terms of information transmission , which is a generalization of the mark transmission theory developed by philosopher Wesley Salmon. Our approach is capable of helping us conceptualize how heterogeneous factors such as micro and macro-biological and psycho-social-are causally linked. This is important not only to understand cancer etiology, but also to design public health policies that target the right causal factors at the macro-level.

  9. Herbal hepatotoxicity: Challenges and pitfalls of causality assessment methods

    PubMed Central

    Teschke, Rolf; Frenzel, Christian; Schulze, Johannes; Eickhoff, Axel

    2013-01-01

    The diagnosis of herbal hepatotoxicity or herb induced liver injury (HILI) represents a particular clinical and regulatory challenge with major pitfalls for the causality evaluation. At the day HILI is suspected in a patient, physicians should start assessing the quality of the used herbal product, optimizing the clinical data for completeness, and applying the Council for International Organizations of Medical Sciences (CIOMS) scale for initial causality assessment. This scale is structured, quantitative, liver specific, and validated for hepatotoxicity cases. Its items provide individual scores, which together yield causality levels of highly probable, probable, possible, unlikely, and excluded. After completion by additional information including raw data, this scale with all items should be reported to regulatory agencies and manufacturers for further evaluation. The CIOMS scale is preferred as tool for assessing causality in hepatotoxicity cases, compared to numerous other causality assessment methods, which are inferior on various grounds. Among these disputed methods are the Maria and Victorino scale, an insufficiently qualified, shortened version of the CIOMS scale, as well as various liver unspecific methods such as the ad hoc causality approach, the Naranjo scale, the World Health Organization (WHO) method, and the Karch and Lasagna method. An expert panel is required for the Drug Induced Liver Injury Network method, the WHO method, and other approaches based on expert opinion, which provide retrospective analyses with a long delay and thereby prevent a timely assessment of the illness in question by the physician. In conclusion, HILI causality assessment is challenging and is best achieved by the liver specific CIOMS scale, avoiding pitfalls commonly observed with other approaches. PMID:23704820

  10. Causality Assessment in Drug-Induced Liver Injury Using a Structured Expert Opinion Process: Comparison to the Roussel-Uclaf Causality Assessment Method

    PubMed Central

    Rockey, Don C.; Seeff, Leonard B.; Rochon, James; Freston, James; Chalasani, Naga; Bonacini, Maurizio; Fontana, Robert J.; Hayashi, Paul H.

    2011-01-01

    Drug-induced liver injury (DILI) is largely a diagnosis of exclusion and is therefore challenging. The US Drug-Induced Liver Injury Network (DILIN) prospective study used two methods to assess DILI causality: a structured expert opinion process and the Roussel-Uclaf Causality Assessment Method (RUCAM). Causality assessment focused on detailed clinical and laboratory data from patients with suspected DILI. The adjudication process used standardized numerical and descriptive definitions and scored cases as definite, highly likely, probable, possible, or unlikely. Results of the structured expert opinion procedure were compared with those derived by the RUCAM approach. Among 250 patients with suspected DILI, the expert opinion adjudication process scored 78 patients (31%) as definite, 102 (41%) as highly likely, 37 (15%) as probable, 25 (10%) as possible, and 8 (3%) as unlikely. Among 187 enrollees who had received a single implicated drug, initial complete agreement was reached for 50 (27%) with the expert opinion process and for 34 (19%) with a five-category RUCAM scale (P = 0.08), and the two methods demonstrated a modest correlation with each other (Spearman's r = 0.42, P = 0.0001). Importantly, the RUCAM approach substantially shifted the causality likelihood toward lower probabilities in comparison with the DILIN expert opinion process. Conclusion The structured DILIN expert opinion process produced higher agreement rates and likelihood scores than RUCAM in assessing causality, but there was still considerable interobserver variability in both. Accordingly, a more objective, reliable, and reproducible means of assessing DILI causality is still needed. PMID:20512999

  11. What Can Causal Networks Tell Us about Metabolic Pathways?

    PubMed Central

    Blair, Rachael Hageman; Kliebenstein, Daniel J.; Churchill, Gary A.

    2012-01-01

    Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies. PMID:22496633

  12. Design of fuzzy cognitive maps using neural networks for predicting chaotic time series.

    PubMed

    Song, H J; Miao, C Y; Shen, Z Q; Roel, W; Maja, D H; Francky, C

    2010-12-01

    As a powerful paradigm for knowledge representation and a simulation mechanism applicable to numerous research and application fields, Fuzzy Cognitive Maps (FCMs) have attracted a great deal of attention from various research communities. However, the traditional FCMs do not provide efficient methods to determine the states of the investigated system and to quantify causalities which are the very foundation of the FCM theory. Therefore in many cases, constructing FCMs for complex causal systems greatly depends on expert knowledge. The manually developed models have a substantial shortcoming due to model subjectivity and difficulties with accessing its reliability. In this paper, we propose a fuzzy neural network to enhance the learning ability of FCMs so that the automatic determination of membership functions and quantification of causalities can be incorporated with the inference mechanism of conventional FCMs. In this manner, FCM models of the investigated systems can be automatically constructed from data, and therefore are independent of the experts. Furthermore, we employ mutual subsethood to define and describe the causalities in FCMs. It provides more explicit interpretation for causalities in FCMs and makes the inference process easier to understand. To validate the performance, the proposed approach is tested in predicting chaotic time series. The simulation studies show the effectiveness of the proposed approach. Copyright © 2010 Elsevier Ltd. All rights reserved.

  13. Maternal age at first birth and offspring criminality: Using the children-of-twins design to test causal hypotheses

    PubMed Central

    Coyne, Claire A; Långström, Niklas; Rickert, Martin E; Lichtenstein, Paul; D’Onofrio, Brian M

    2013-01-01

    Teenage childbirth is a risk factor for poor offspring outcomes, particularly offspring antisocial behaviour. It is not clear if maternal age at first birth (MAFB) is causally associated with offspring antisocial behavior or if this association is due to selection factors that influence both the likelihood that a young woman gives birth early and that her offspring engage in antisocial behavior. The current study addresses the limitations of previous research by using longitudinal data from Swedish national registries and children-of-siblings and children-of-twins comparisons to identify the extent to which the association between MAFB and offspring criminal convictions is consistent with a causal influence and confounded by genetic or environmental factors that make cousins similar. We found offspring born to mothers who began childbearing earlier were more likely to be convicted of a crime than offspring born to mothers who delayed childbearing. The results from comparisons of differentially exposed cousins, especially born to discordant MZ twin sisters, provide support for a causal association between MAFB and offspring criminal convictions. The analyses also found little evidence for genetic confounding due to passive gene-environment correlation. Future studies are needed to replicate these findings and to identify environmental risk factors that mediate this causal association. PMID:23398750

  14. Relations between causal attributions for stuttering and psychological well-being in adults who stutter.

    PubMed

    Boyle, Michael

    2016-02-01

    This study attempted to understand the relationship between causal attributions for stuttering and psychological well-being in adults who stutter. The study employed a cross-sectional design using a web survey distribution mode to gain information related to causal attributions and psychological well-being of 348 adults who stutter. Correlation analyses were conducted to determine relationships between participants' causal attributions (i.e. locus of causality, external control, personal control, stability, biological attributions, non-biological attributions) for stuttering and various measures of psychological well-being including self-stigma, self-esteem/self-efficacy, hope, anxiety and depression. Results indicated that higher perceptions of external control of stuttering were related to significantly lower ratings of hope and self-esteem/self-efficacy and higher ratings of anxiety and depression. Higher perceptions of personal control of stuttering were related to significantly lower ratings of self-stigma and higher ratings of hope and self-esteem/self-efficacy. Increased biological attributions were significantly related to higher ratings of permanency and unchangeableness of stuttering and lower ratings of personal control of stuttering. The findings demonstrate the importance of instilling a sense of control in PWS regarding their ability to manage their stuttering. Findings also raise questions regarding the benefits of educating PWS about the biological underpinnings of stuttering.

  15. Maternal age at first birth and offspring criminality: using the children of twins design to test causal hypotheses.

    PubMed

    Coyne, Claire A; Långström, Niklas; Rickert, Martin E; Lichtenstein, Paul; D'Onofrio, Brian M

    2013-02-01

    Teenage childbirth is a risk factor for poor offspring outcomes, particularly offspring antisocial behavior. It is not clear, however, if maternal age at first birth (MAFB) is causally associated with offspring antisocial behavior or if this association is due to selection factors that influence both the likelihood that a young woman gives birth early and that her offspring engage in antisocial behavior. The current study addresses the limitations of previous research by using longitudinal data from Swedish national registries and children of siblings and children of twins comparisons to identify the extent to which the association between MAFB and offspring criminal convictions is consistent with a causal influence and confounded by genetic or environmental factors that make cousins similar. We found offspring born to mothers who began childbearing earlier were more likely to be convicted of a crime than offspring born to mothers who delayed childbearing. The results from comparisons of differentially exposed cousins, especially born to discordant monozygotic twin sisters, provide support for a causal association between MAFB and offspring criminal convictions. The analyses also found little evidence for genetic confounding due to passive gene-environment correlation. Future studies are needed to replicate these findings and to identify environmental risk factors that mediate this causal association.

  16. Causal premise semantics.

    PubMed

    Kaufmann, Stefan

    2013-08-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal semantic analysis of conditionals, Kratzer-style premise semantics, allows for a straightforward implementation of the crucial ideas and insights of Pearl-style causal networks. I spell out the details of such an implementation, focusing especially on the notions of intervention on a network and backtracking interpretations of counterfactuals. Copyright © 2013 Cognitive Science Society, Inc.

  17. Comparative quantification of health risks: Conceptual framework and methodological issues

    PubMed Central

    Murray, Christopher JL; Ezzati, Majid; Lopez, Alan D; Rodgers, Anthony; Vander Hoorn, Stephen

    2003-01-01

    Reliable and comparable analysis of risks to health is key for preventing disease and injury. Causal attribution of morbidity and mortality to risk factors has traditionally been conducted in the context of methodological traditions of individual risk factors, often in a limited number of settings, restricting comparability. In this paper, we discuss the conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines. The issues include: comparing the burden of disease due to the observed exposure distribution in a population with the burden from a hypothetical distribution or series of distributions, rather than a single reference level such as non-exposed; considering the multiple stages in the causal network of interactions among risk factor(s) and disease outcome to allow making inferences about some combinations of risk factors for which epidemiological studies have not been conducted, including the joint effects of multiple risk factors; calculating the health loss due to risk factor(s) as a time-indexed "stream" of disease burden due to a time-indexed "stream" of exposure, including consideration of discounting; and the sources of uncertainty. PMID:12780936

  18. Causal impulse response for circular sources in viscous media

    PubMed Central

    Kelly, James F.; McGough, Robert J.

    2008-01-01

    The causal impulse response of the velocity potential for the Stokes wave equation is derived for calculations of transient velocity potential fields generated by circular pistons in viscous media. The causal Green’s function is numerically verified using the material impulse response function approach. The causal, lossy impulse response for a baffled circular piston is then calculated within the near field and the far field regions using expressions previously derived for the fast near field method. Transient velocity potential fields in viscous media are computed with the causal, lossy impulse response and compared to results obtained with the lossless impulse response. The numerical error in the computed velocity potential field is quantitatively analyzed for a range of viscous relaxation times and piston radii. Results show that the largest errors are generated in locations near the piston face and for large relaxation times, and errors are relatively small otherwise. Unlike previous frequency-domain methods that require numerical inverse Fourier transforms for the evaluation of the lossy impulse response, the present approach calculates the lossy impulse response directly in the time domain. The results indicate that this causal impulse response is ideal for time-domain calculations that simultaneously account for diffraction and quadratic frequency-dependent attenuation in viscous media. PMID:18397018

  19. A short educational intervention diminishes causal illusions and specific paranormal beliefs in undergraduates

    PubMed Central

    Tubau, Elisabet; Matute, Helena

    2018-01-01

    Cognitive biases such as causal illusions have been related to paranormal and pseudoscientific beliefs and, thus, pose a real threat to the development of adequate critical thinking abilities. We aimed to reduce causal illusions in undergraduates by means of an educational intervention combining training-in-bias and training-in-rules techniques. First, participants directly experienced situations that tend to induce the Barnum effect and the confirmation bias. Thereafter, these effects were explained and examples of their influence over everyday life were provided. Compared to a control group, participants who received the intervention showed diminished causal illusions in a contingency learning task and a decrease in the precognition dimension of a paranormal belief scale. Overall, results suggest that evidence-based educational interventions like the one presented here could be used to significantly improve critical thinking skills in our students. PMID:29385184

  20. Bulk viscous cosmology with causal transport theory

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Piattella, Oliver F.; Fabris, Júlio C.; Zimdahl, Winfried, E-mail: oliver.piattella@gmail.com, E-mail: fabris@pq.cnpq.br, E-mail: winfried.zimdahl@pq.cnpq.br

    2011-05-01

    We consider cosmological scenarios originating from a single imperfect fluid with bulk viscosity and apply Eckart's and both the full and the truncated Müller-Israel-Stewart's theories as descriptions of the non-equilibrium processes. Our principal objective is to investigate if the dynamical properties of Dark Matter and Dark Energy can be described by a single viscous fluid and how such description changes when a causal theory (Müller-Israel-Stewart's, both in its full and truncated forms) is taken into account instead of Eckart's non-causal one. To this purpose, we find numerical solutions for the gravitational potential and compare its behaviour with the corresponding ΛCDMmore » case. Eckart's and the full causal theory seem to be disfavoured, whereas the truncated theory leads to results similar to those of the ΛCDM model for a bulk viscous speed in the interval 10{sup −11} || cb{sup 2} ∼< 10{sup −8}.« less

  1. Functional clustering of time series gene expression data by Granger causality

    PubMed Central

    2012-01-01

    Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

  2. Differences in Causal Estimates from Longitudinal Analyses of Residualized versus Simple Gain Scores: Contrasting Controls for Selection and Regression Artifacts

    ERIC Educational Resources Information Center

    Larzelere, Robert E.; Ferrer, Emilio; Kuhn, Brett R.; Danelia, Ketevan

    2010-01-01

    This study estimates the causal effects of six corrective actions for children's problem behaviors, comparing four types of longitudinal analyses that correct for pre-existing differences in a cohort of 1,464 4- and 5-year-olds from Canadian National Longitudinal Survey of Children and Youth (NLSCY) data. Analyses of residualized gain scores found…

  3. Content Analysis of Teenaged Interviews for Designing Drug Programs.

    ERIC Educational Resources Information Center

    Bell, Edward V.

    1980-01-01

    Analyses of the data and youths' prescriptions concerning prevention of abuse yielded 12 program recommendations. These programs can create the awareness that led to concerted programs to stop the war and pollution. When designing educational-information programs, one must be aware of the total system of causal factors. (Author/BEF)

  4. Rebar: Reinforcing a Matching Estimator with Predictions from High-Dimensional Covariates

    ERIC Educational Resources Information Center

    Sales, Adam C.; Hansen, Ben B.; Rowan, Brian

    2018-01-01

    In causal matching designs, some control subjects are often left unmatched, and some covariates are often left unmodeled. This article introduces "rebar," a method using high-dimensional modeling to incorporate these commonly discarded data without sacrificing the integrity of the matching design. After constructing a match, a researcher…

  5. Optimal Design for Regression Discontinuity Studies with Clustering

    ERIC Educational Resources Information Center

    Rhoads, Christopher; Dye, Charles

    2014-01-01

    Recent years have seen an increased interest in quantitative educational research studies that use random assignment (RA) to evaluate the causal impacts of educational interventions (Angrist, 2004). The multi-level structure of the public education system in the United States often leads to experimental designs where naturally occurring clusters…

  6. Should herbs take all the blame? Causality assessment of a serious thrombocytopenia event.

    PubMed

    Lai, Jung-Nien; Hsieh, Shu-Ching; Chen, Pau-Chung; Chen, Huey-Jen; Wang, Jung-Der

    2010-11-01

    With the increasing use of herbal medicines, the causality assessment of adverse drug-related reactions becomes more complicated because of the concomitant use of herbs and conventional medications. Epidemiological causal inference can be a central feature of such judgment but may be insufficient. Other scientific considerations include study design, bias, confounding, and measurement issues. The approach of this study is to establish an active safety surveillance system for finished herbal products (FHPs) and to review each adverse event regularly. A single case of serious thrombocytopenia was found in 136 subjects taking FHPs on a clinical trial for 12 weeks, for which the cause was sought. Because at the end of the first month the patient's platelet counts were normal and the thrombocytopenia developed after the co-medication with conventional drugs, it was suspected that the thrombocytopenia might not be attributed to the use of FHP. This report summarizes the criteria of causality assessment under mixed use of herbs and conventional medicine and recommends a feasible process for careful evaluation of adverse drug reactions related to all herbal medicine.

  7. Exceptionalist naturalism: Human agency and the causal order.

    PubMed

    Turri, John

    2018-02-01

    This paper addresses a fundamental question in folk metaphysics: How do we ordinarily view human agency? According to the transcendence account, we view human agency as standing outside of the causal order and imbued with exceptional powers. According to a naturalistic account, we view human agency as subject to the same physical laws as other objects and completely open to scientific investigation. According to exceptionalist naturalism, the truth lies somewhere in between: We view human agency as fitting broadly within the causal order while still being exceptional in important respects. In this paper, I report seven experiments designed to decide between these three competing theories. Across a variety of contexts and types of action, participants agreed that human agents can resist outcomes described as inevitable, guaranteed, and causally determined. Participants viewed non-human animal agents similarly, whereas they viewed computers, robots, and simple inanimate objects differently. At the same time, participants judged that human actions are caused by many things, including psychological, neurological, and social events. Overall, in folk metaphysics, human and non-human animals are viewed as exceptional parts of the natural world.

  8. Alpha Oscillations Are Causally Linked to Inhibitory Abilities in Ageing.

    PubMed

    Borghini, Giulia; Candini, Michela; Filannino, Cristina; Hussain, Masud; Walsh, Vincent; Romei, Vincenzo; Zokaei, Nahid; Cappelletti, Marinella

    2018-05-02

    Aging adults typically show reduced ability to ignore task-irrelevant information, an essential skill for optimal performance in many cognitive operations, including those requiring working memory (WM) resources. In a first experiment, young and elderly human participants of both genders performed an established WM paradigm probing inhibitory abilities by means of valid, invalid, and neutral retro-cues. Elderly participants showed an overall cost, especially in performing invalid trials, whereas younger participants' general performance was comparatively higher, as expected.Inhibitory abilities have been linked to alpha brain oscillations but it is yet unknown whether in aging these oscillations (also typically impoverished) and inhibitory abilities are causally linked. To probe this possible causal link in aging, we compared in a second experiment parietal alpha-transcranial alternating current stimulation (tACS) with either no stimulation (Sham) or with two control stimulation frequencies (theta- and gamma-tACS) in the elderly group while performing the same WM paradigm. Alpha- (but not theta- or gamma-) tACS selectively and significantly improved performance (now comparable to younger adults' performance in the first experiment), particularly for invalid cues where initially elderly showed the highest costs. Alpha oscillations are therefore causally linked to inhibitory abilities and frequency-tuned alpha-tACS interventions can selectively change these abilities in the elderly. SIGNIFICANCE STATEMENT Ignoring task-irrelevant information, an ability associated to rhythmic brain activity in the alpha frequency band, is fundamental for optimal performance. Indeed, impoverished inhibitory abilities contribute to age-related decline in cognitive functions like working memory (WM), the capacity to briefly hold information in mind. Whether in aging adults alpha oscillations and inhibitory abilities are causally linked is yet unknown. We experimentally manipulated frequency-tuned brain activity using transcranial alternating current stimulation (tACS), combined with a retro-cue paradigm assessing WM and inhibition. We found that alpha-tACS induced a significant improvement in target responses and misbinding errors, two indexes of inhibition. We concluded that in aging alpha oscillations are causally linked to inhibitory abilities, and that despite being impoverished, these abilities are still malleable. Copyright © 2018 the authors 0270-6474/18/384419-12$15.00/0.

  9. Interactions among poverty, gender, and health systems affect women's participation in services to prevent HIV transmission from mother to child: A causal loop analysis.

    PubMed

    Yourkavitch, Jennifer; Hassmiller Lich, Kristen; Flax, Valerie L; Okello, Elialilia S; Kadzandira, John; Katahoire, Anne Ruhweza; Munthali, Alister C; Thomas, James C

    2018-01-01

    Retention in care remains an important issue for prevention of mother-to-child transmission (PMTCT) programs according to WHO guidelines, formerly called the "Option B+" approach. The objective of this study was to examine how poverty, gender, and health system factors interact to influence women's participation in PMTCT services. We used qualitative research, literature, and hypothesized variable connections to diagram causes and effects in causal loop models. We found that many factors, including antiretroviral therapy (ART) use, service design and quality, stigma, disclosure, spouse/partner influence, decision-making autonomy, and knowledge about PMTCT, influence psychosocial health, which in turn affects women's participation in PMTCT services. Thus, interventions to improve psychosocial health need to address many factors to be successful. We also found that the design of PMTCT services, a modifiable factor, is important because it affects several other factors. We identified 66 feedback loops that may contribute to policy resistance-that is, a policy's failure to have its intended effect. Our findings point to the need for a multipronged intervention to encourage women's continued participation in PMTCT services and for longitudinal research to quantify and test our causal loop model.

  10. Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

    PubMed Central

    2016-01-01

    Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower–visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based systems for knowledge discovery in biodiversity and ecosystem informatics. PMID:27851814

  11. Does High Tobacco Consumption Cause Psychological Distress? A Mendelian Randomization Study.

    PubMed

    Skov-Ettrup, Lise S; Nordestgaard, Børge G; Petersen, Christina B; Tolstrup, Janne S

    2017-01-01

    Increasing evidence suggests that smoking influences mental health negatively. This study investigated whether high tobacco consumption is causally related to psychological distress in a Mendelian randomization design, using a variant in the nicotine acetylcholine receptor gene CHRNA3-known to influence individual tobacco consumption-as instrumental variable for tobacco consumption. Data from 90 108 participants in the Copenhagen General Population Study was used. Exposures included self-reported cigarettes/day and pack years and the CHRNA3 rs1051730 genotype as instrumental variable for tobacco consumption. Three dimensions of psychological distress were studied: Stress, fatigue, and hopelessness. Analyses with the CHRNA3 genotype were stratified by smoking status. Self-reported amount of smoking was associated with all three dimensions of psychological distress. For instance among participants smoking 30 cigarettes/day or more, the odds ratio (OR) for stress was 1.67 (95% confidence interval [CI] 1.47-1.89) compared to never-smokers. Corresponding ORs for fatigue and hopelessness were 2.18 (95% CI 1.92-2.47) and 3.08 (95% CI 2.62-3.62). Among current smokers, homozygotes and heterozygotes for the CHRNA3 genotype had higher tobacco consumption than noncarriers. Nevertheless, the CHRNA3 genotype was not associated with psychological distress neither in current nor in former or never-smokers. For instance among current smokers, the OR for stress was 1.02 (95% CI 0.91-1.15) among homozygotes compared to noncarriers of the CHRNA3 genotype. Though a strong association between tobacco consumption and psychological distress was found, there was no clear evidence that high tobacco consumption was causally related to psychological distress. Smoking is associated with several mental health outcomes and smoking cessation is associated with improved mental health. Causality in the association between smoking and mental health is difficult to establish using observational data. Using a genotype known to influence tobacco consumption as instrumental variable for amount of smoking, we found no clear evidence of a direct causal path between high tobacco consumption and psychological distress. Whatever causes the strong association between tobacco consumption and psychological distress, the co-occurrence is important to consider both in interventions for smoking prevention and cessation. © The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Statistical Theory for the "RCT-YES" Software: Design-Based Causal Inference for RCTs. NCEE 2015-4011

    ERIC Educational Resources Information Center

    Schochet, Peter Z.

    2015-01-01

    This report presents the statistical theory underlying the "RCT-YES" software that estimates and reports impacts for RCTs for a wide range of designs used in social policy research. The report discusses a unified, non-parametric design-based approach for impact estimation using the building blocks of the Neyman-Rubin-Holland causal…

  13. The influence of anticipated pride and guilt on pro-environmental decision making.

    PubMed

    Schneider, Claudia R; Zaval, Lisa; Weber, Elke U; Markowitz, Ezra M

    2017-01-01

    The present research explores the relationship between anticipated emotions and pro-environmental decision making comparing two differently valenced emotions: anticipated pride and guilt. In an experimental design, we examined the causal effects of anticipated pride versus guilt on pro-environmental decision making and behavioral intentions by making anticipated emotions (i.e. pride and guilt) salient just prior to asking participants to make a series of environmental decisions. We find evidence that anticipating one's positive future emotional state from green action just prior to making an environmental decision leads to higher pro-environmental behavioral intentions compared to anticipating one's negative emotional state from inaction. This finding suggests a rethinking in the domain of environmental and climate change messaging, which has traditionally favored inducing negative emotions such as guilt to promote pro-environmental action. Furthermore, exploratory results comparing anticipated pride and guilt inductions to baseline behavior point toward a reactance eliciting effect of anticipated guilt.

  14. Research review: the importance of callous-unemotional traits for developmental models of aggressive and antisocial behavior.

    PubMed

    Frick, Paul J; White, Stuart F

    2008-04-01

    The current paper reviews research suggesting that the presence of a callous and unemotional interpersonal style designates an important subgroup of antisocial and aggressive youth. Specifically, callous-unemotional (CU) traits (e.g., lack of guilt, absence of empathy, callous use of others) seem to be relatively stable across childhood and adolescence and they designate a group of youth with a particularly severe, aggressive, and stable pattern of antisocial behavior. Further, antisocial youth with CU traits show a number of distinct emotional, cognitive, and personality characteristics compared to other antisocial youth. These characteristics of youth with CU traits have important implications for causal models of antisocial and aggressive behavior, for methods used to study antisocial youth, and for assessing and treating antisocial and aggressive behavior in children and adolescents.

  15. Entanglement entropy in causal set theory

    NASA Astrophysics Data System (ADS)

    Sorkin, Rafael D.; Yazdi, Yasaman K.

    2018-04-01

    Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (arXiv:1205.2953)) which, for a Gaussian scalar field, expresses the entropy of a spacetime region in terms of the field’s correlation function within that region (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1  +  1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.

  16. Frequency distribution of causal connectivity in rat sensorimotor network: resting-state fMRI analyses.

    PubMed

    Shim, Woo H; Baek, Kwangyeol; Kim, Jeong Kon; Chae, Yongwook; Suh, Ji-Yeon; Rosen, Bruce R; Jeong, Jaeseung; Kim, Young R

    2013-01-01

    Resting-state functional MRI (fMRI) has emerged as an important method for assessing neural networks, enabling extensive connectivity analyses between multiple brain regions. Among the analysis techniques proposed, partial directed coherence (PDC) provides a promising tool to unveil causal connectivity networks in the frequency domain. Using the MRI time series obtained from the rat sensorimotor system, we applied PDC analysis to determine the frequency-dependent causality networks. In particular, we compared in vivo and postmortem conditions to establish the statistical significance of directional PDC values. Our results demonstrate that two distinctive frequency populations drive the causality networks in rat; significant, high-frequency causal connections clustered in the range of 0.2-0.4 Hz, and the frequently documented low-frequency connections <0.15 Hz. Frequency-dependence and directionality of the causal connection are characteristic between sensorimotor regions, implying the functional role of frequency bands to transport specific resting-state signals. In particular, whereas both intra- and interhemispheric causal connections between heterologous sensorimotor regions are robust over all frequency levels, the bilaterally homologous regions are interhemispherically linked mostly via low-frequency components. We also discovered a significant, frequency-independent, unidirectional connection from motor cortex to thalamus, indicating dominant cortical inputs to the thalamus in the absence of external stimuli. Additionally, to address factors underlying the measurement error, we performed signal simulations and revealed that the interactive MRI system noise alone is a likely source of the inaccurate PDC values. This work demonstrates technical basis for the PDC analysis of resting-state fMRI time series and the presence of frequency-dependent causality networks in the sensorimotor system.

  17. Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality.

    PubMed

    Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt

    2016-01-01

    Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling.

  18. Effect of Alcohol on Risk of Coronary Heart Disease and Stroke: Causality, Bias, or a Bit of Both?

    PubMed Central

    Emberson, Jonathan R; Bennett, Derrick A

    2006-01-01

    Epidemiological studies of middle-aged populations generally find the relationship between alcohol intake and the risk of coronary heart disease (CHD) and stroke to be either U- or J-shaped. This review describes the extent that these relationships are likely to be causal, and the extent that they may be due to specific methodological weaknesses in epidemiological studies. The consistency in the vascular benefit associated with moderate drinking (compared with non-drinking) observed across different studies, together with the existence of credible biological pathways, strongly suggests that at least some of this benefit is real. However, because of biases introduced by: choice of reference categories; reverse causality bias; variations in alcohol intake over time; and confounding, some of it is likely to be an artefact. For heavy drinking, different study biases have the potential to act in opposing directions, and as such, the true effects of heavy drinking on vascular risk are uncertain. However, because of the known harmful effects of heavy drinking on non-vascular mortality, the problem is an academic one. Studies of the effects of alcohol consumption on health outcomes should recognise the methodological biases they are likely to face, and design, analyse and interpret their studies accordingly. While regular moderate alcohol consumption during middle-age probably does reduce vascular risk, care should be taken when making general recommendations about safe levels of alcohol intake. In particular, it is likely that any promotion of alcohol for health reasons would do substantially more harm than good. PMID:17326330

  19. Non-linear Heart Rate and Blood Pressure Interaction in Response to Lower-Body Negative Pressure

    PubMed Central

    Verma, Ajay K.; Xu, Da; Garg, Amanmeet; Cote, Anita T.; Goswami, Nandu; Blaber, Andrew P.; Tavakolian, Kouhyar

    2017-01-01

    Early detection of hemorrhage remains an open problem. In this regard, blood pressure has been an ineffective measure of blood loss due to numerous compensatory mechanisms sustaining arterial blood pressure homeostasis. Here, we investigate the feasibility of causality detection in the heart rate and blood pressure interaction, a closed-loop control system, for early detection of hemorrhage. The hemorrhage was simulated via graded lower-body negative pressure (LBNP) from 0 to −40 mmHg. The research hypothesis was that a significant elevation of causal control in the direction of blood pressure to heart rate (i.e., baroreflex response) is an early indicator of central hypovolemia. Five minutes of continuous blood pressure and electrocardiogram (ECG) signals were acquired simultaneously from young, healthy participants (27 ± 1 years, N = 27) during each LBNP stage, from which heart rate (represented by RR interval), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) were derived. The heart rate and blood pressure causal interaction (RR↔SBP and RR↔MAP) was studied during the last 3 min of each LBNP stage. At supine rest, the non-baroreflex arm (RR→SBP and RR→MAP) showed a significantly (p < 0.001) higher causal drive toward blood pressure regulation compared to the baroreflex arm (SBP→RR and MAP→RR). In response to moderate category hemorrhage (−30 mmHg LBNP), no change was observed in the traditional marker of blood loss i.e., pulse pressure (p = 0.10) along with the RR→SBP (p = 0.76), RR→MAP (p = 0.60), and SBP→RR (p = 0.07) causality compared to the resting stage. Contrarily, a significant elevation in the MAP→RR (p = 0.004) causality was observed. In accordance with our hypothesis, the outcomes of the research underscored the potential of compensatory baroreflex arm (MAP→RR) of the heart rate and blood pressure interaction toward differentiating a simulated moderate category hemorrhage from the resting stage. Therefore, monitoring baroreflex causality can have a clinical utility in making triage decisions to impede hemorrhage progression. PMID:29114227

  20. The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

    PubMed

    Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

    2017-12-28

    Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set.

  1. An Introduction to Causal Inference

    DTIC Science & Technology

    2009-11-02

    Introduction The questions that motivate most studies in the health, social and behavioral sciences are not associational but causal in nature. For example...what is the efficacy of a given drug in a given population? Whether data can prove an employer guilty of hiring discrimination? What fraction of past...a unifying theory, called “structural,” within which most (if not all) aspects of causation can be formulated, analyzed and compared, thirdly

  2. Anger Elicitation in Tonga and Germany: The Impact of Culture on Cognitive Determinants of Emotions

    PubMed Central

    Bender, Andrea; Spada, Hans; Rothe-Wulf, Annelie; Traber, Simone; Rauss, Karsten

    2012-01-01

    The cognitive appraisal of an event is crucial for the elicitation and differentiation of emotions, and causal attributions are an integral part of this process. In an interdisciplinary project comparing Tonga and Germany, we examined how cultural differences in attribution tendencies affect emotion assessment and elicitation. Data on appraising causality and responsibility and on emotional responses were collected through questionnaires based on experimentally designed vignettes, and were related to culture-specific values, norms, and the prevailing self-concept. The experimental data support our hypothesis that – driven by culturally defined self-concepts and corresponding attribution tendencies – members of the two cultures cognitively appraise events in diverging manners and consequently differ in their emotional responses. Ascription of responsibility to self and/or circumstances, in line with a more interdependent self-concept, co-varies with higher ratings of shame, guilt, and sadness, whereas ascription of responsibility to others, in line with a less interdependent self-concept, co-varies with higher ratings of anger. These findings support the universal contingency hypothesis and help to explain cultural differences in this domain on a fine-grained level. PMID:23112780

  3. The relationship between urinary tract infection during pregnancy and preeclampsia: causal, confounded or spurious?

    PubMed

    Karmon, Anatte; Sheiner, Eyal

    2008-06-01

    Preeclampsia is a major cause of maternal morbidity, although its precise etiology remains elusive. A number of studies suggest that urinary tract infection (UTI) during the course of gestation is associated with elevated risk for preeclampsia, while others have failed to prove such an association. In our medical center, pregnant women who were exposed to at least one UTI episode during pregnancy were 1.3 times more likely to have mild preeclampsia and 1.8 times more likely to have severe preeclampsia as compared to unexposed women. Our results are based on univariate analyses and are not adjusted for potential confounders. This editorial aims to discuss the relationship between urinary tract infection and preeclampsia, as well as examine the current problems regarding the interpretation of this association. Although the relationship between UTI and preeclampsia has been demonstrated in studies with various designs, carried-out in a variety of settings, the nature of this association is unclear. By taking into account timeline, dose-response effects, treatment influences, and potential confounders, as well as by neutralizing potential biases, future studies may be able to clarify the relationship between UTI and preeclampsia by determining if it is causal, confounded, or spurious.

  4. [Causal analysis approaches in epidemiology].

    PubMed

    Dumas, O; Siroux, V; Le Moual, N; Varraso, R

    2014-02-01

    Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the formulation of causal hypotheses, which will be a basis for all methodological choices. Beyond this step, statistical analysis tools recently developed offer new possibilities to delineate complex relationships, in particular in life course epidemiology. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  5. Assessing the independent contribution of maternal educational expectations to children's educational attainment in early adulthood: a propensity score matching analysis.

    PubMed

    Pingault, Jean Baptiste; Côté, Sylvana M; Petitclerc, Amélie; Vitaro, Frank; Tremblay, Richard E

    2015-01-01

    Parental educational expectations have been associated with children's educational attainment in a number of long-term longitudinal studies, but whether this relationship is causal has long been debated. The aims of this prospective study were twofold: 1) test whether low maternal educational expectations contributed to failure to graduate from high school; and 2) compare the results obtained using different strategies for accounting for confounding variables (i.e. multivariate regression and propensity score matching). The study sample included 1,279 participants from the Quebec Longitudinal Study of Kindergarten Children. Maternal educational expectations were assessed when the participants were aged 12 years. High school graduation—measuring educational attainment—was determined through the Quebec Ministry of Education when the participants were aged 22-23 years. Findings show that when using the most common statistical approach (i.e. multivariate regressions to adjust for a restricted set of potential confounders) the contribution of low maternal educational expectations to failure to graduate from high school was statistically significant. However, when using propensity score matching, the contribution of maternal expectations was reduced and remained statistically significant only for males. The results of this study are consistent with the possibility that the contribution of parental expectations to educational attainment is overestimated in the available literature. This may be explained by the use of a restricted range of potential confounding variables as well as the dearth of studies using appropriate statistical techniques and study designs in order to minimize confounding. Each of these techniques and designs, including propensity score matching, has its strengths and limitations: A more comprehensive understanding of the causal role of parental expectations will stem from a convergence of findings from studies using different techniques and designs.

  6. Regression Discontinuity Design in Gifted and Talented Education Research

    ERIC Educational Resources Information Center

    Matthews, Michael S.; Peters, Scott J.; Housand, Angela M.

    2012-01-01

    This Methodological Brief introduces the reader to the regression discontinuity design (RDD), which is a method that when used correctly can yield estimates of research treatment effects that are equivalent to those obtained through randomized control trials and can therefore be used to infer causality. However, RDD does not require the random…

  7. Using Epidemiologic Methods to Test Hypotheses regarding Causal Influences on Child and Adolescent Mental Disorders

    ERIC Educational Resources Information Center

    Lahey, Benjamin B.; D'Onofrio, Brian M.; Waldman, Irwin D.

    2009-01-01

    Epidemiology uses strong sampling methods and study designs to test refutable hypotheses regarding the causes of important health, mental health, and social outcomes. Epidemiologic methods are increasingly being used to move developmental psychopathology from studies that catalogue correlates of child and adolescent mental health to designs that…

  8. Design Issues and Inference in Experimental L2 Research

    ERIC Educational Resources Information Center

    Hudson, Thom; Llosa, Lorena

    2015-01-01

    Explicit attention to research design issues is essential in experimental second language (L2) research. Too often, however, such careful attention is not paid. This article examines some of the issues surrounding experimental L2 research and its relationships to causal inferences. It discusses the place of research questions and hypotheses,…

  9. Evidence-Based Practices in a Changing World: Reconsidering the Counterfactual in Education Research

    ERIC Educational Resources Information Center

    Lemons, Christopher J.; Fuchs, Douglas; Gilbert, Jennifer K.; Fuchs, Lynn S.

    2014-01-01

    Experimental and quasi-experimental designs are used in educational research to establish causality and develop effective practices. These research designs rely on a counterfactual model that, in simple form, calls for a comparison between a treatment group and a control group. Developers of educational practices often assume that the population…

  10. The Functional and Developmental Organization of Cognitive Developmental Sequences

    ERIC Educational Resources Information Center

    Demetriou, Andreas; Kyriakides, Leonidas

    2006-01-01

    This study examines the organization and development of 5 domains of reasoning (categorical, quantitative, spatial, causal, and propositional) and the construct validity of a test designed to measure development from early adolescence to early adulthood. The theory underlying the test is first summarized and the conceptual design of the test is…

  11. The Study Review Process. WWC Process Brief

    ERIC Educational Resources Information Center

    What Works Clearinghouse, 2017

    2017-01-01

    Many studies of education interventions make claims about impacts on students' outcomes. Some studies have designs that enable readers to make causal inferences about the effects of an intervention but others have designs that do not permit these types of conclusions. To help policymakers, practitioners, and others make sense of study results, the…

  12. Relationships between infant mortality, birth spacing and fertility in Matlab, Bangladesh.

    PubMed

    van Soest, Arthur; Saha, Unnati Rani

    2018-01-01

    Although research on the fertility response to childhood mortality is widespread in demographic literature, very few studies focused on the two-way causal relationships between infant mortality and fertility. Understanding the nature of such relationships is important in order to design effective policies to reduce child mortality and improve family planning. In this study, we use dynamic panel data techniques to analyse the causal effects of infant mortality on birth intervals and fertility, as well as the causal effects of birth intervals on mortality in rural Bangladesh, accounting for unobserved heterogeneity and reverse causality. Simulations based upon the estimated model show whether (and to what extent) mortality and fertility can be reduced by breaking the causal links between short birth intervals and infant mortality. We find a replacement effect of infant mortality on total fertility of about 0.54 children for each infant death in the comparison area with standard health services. Eliminating the replacement effect would lengthen birth intervals and reduce the total number of births, resulting in a fall in mortality by 2.45 children per 1000 live births. These effects are much smaller in the treatment area with extensive health services and information on family planning, where infant mortality is smaller, birth intervals are longer, and total fertility is lower. In both areas, we find evidence of boy preference in family planning.

  13. Relationships between infant mortality, birth spacing and fertility in Matlab, Bangladesh

    PubMed Central

    van Soest, Arthur

    2018-01-01

    Although research on the fertility response to childhood mortality is widespread in demographic literature, very few studies focused on the two-way causal relationships between infant mortality and fertility. Understanding the nature of such relationships is important in order to design effective policies to reduce child mortality and improve family planning. In this study, we use dynamic panel data techniques to analyse the causal effects of infant mortality on birth intervals and fertility, as well as the causal effects of birth intervals on mortality in rural Bangladesh, accounting for unobserved heterogeneity and reverse causality. Simulations based upon the estimated model show whether (and to what extent) mortality and fertility can be reduced by breaking the causal links between short birth intervals and infant mortality. We find a replacement effect of infant mortality on total fertility of about 0.54 children for each infant death in the comparison area with standard health services. Eliminating the replacement effect would lengthen birth intervals and reduce the total number of births, resulting in a fall in mortality by 2.45 children per 1000 live births. These effects are much smaller in the treatment area with extensive health services and information on family planning, where infant mortality is smaller, birth intervals are longer, and total fertility is lower. In both areas, we find evidence of boy preference in family planning. PMID:29702692

  14. Identifying direct miRNA-mRNA causal regulatory relationships in heterogeneous data.

    PubMed

    Zhang, Junpeng; Le, Thuc Duy; Liu, Lin; Liu, Bing; He, Jianfeng; Goodall, Gregory J; Li, Jiuyong

    2014-12-01

    Discovering the regulatory relationships between microRNAs (miRNAs) and mRNAs is an important problem that interests many biologists and medical researchers. A number of computational methods have been proposed to infer miRNA-mRNA regulatory relationships, and are mostly based on the statistical associations between miRNAs and mRNAs discovered in observational data. The miRNA-mRNA regulatory relationships identified by these methods can be both direct and indirect regulations. However, differentiating direct regulatory relationships from indirect ones is important for biologists in experimental designs. In this paper, we present a causal discovery based framework (called DirectTarget) to infer direct miRNA-mRNA causal regulatory relationships in heterogeneous data, including expression profiles of miRNAs and mRNAs, and miRNA target information. DirectTarget is applied to the Epithelial to Mesenchymal Transition (EMT) datasets. The validation by experimentally confirmed target databases suggests that the proposed method can effectively identify direct miRNA-mRNA regulatory relationships. To explore the upstream regulators of miRNA regulation, we further identify the causal feedforward patterns (CFFPs) of TF-miRNA-mRNA to provide insights into the miRNA regulation in EMT. DirectTarget has the potential to be applied to other datasets to elucidate the direct miRNA-mRNA causal regulatory relationships and to explore the regulatory patterns. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Estimating the causal effects of smoking.

    PubMed

    Rubin, D B

    An important application of statistics in recent years has been to address the causal effects of smoking. There is little doubt that there are health risks associated with smoking. However, more general issues concern the causal effects due to the alleged misconduct of the tobacco industry or due to programmes designed to curtail tobacco use. To address any such causal question, assumptions must be made. Although some of the issues are well known in the statistical and epidemiological literature, there does not appear to be a unified treatment that provides prescriptive guidance on the estimation of these causal effects with explication of the needed assumptions. A 'conduct attributable fraction' is derived, which allows for arbitrary changes in smoking and non-smoking health care expenditure related factors in a counterfactual world without the alleged misconduct, and therefore generalizes the traditional 'smoking attributable fraction'. The formulation presented here, although described for the problem of estimating excess health care expenditures due to the alleged misconduct of the tobacco industry, is more general. It can be applied to any outcome, such as mortality, morbidity, or income from excise taxes, as well as to any situation in which consequences due to alleged misconduct (for example, of two entities, such as the tobacco and the asbestos industries) or due to hypothetical programmes (for example, extra smoking reduction initiatives) are to be estimated. Copyright 2001 John Wiley & Sons, Ltd.

  16. Adding Design Elements to Improve Time Series Designs: No Child Left behind as an Example of Causal Pattern-Matching

    ERIC Educational Resources Information Center

    Wong, Manyee; Cook, Thomas D.; Steiner, Peter M.

    2015-01-01

    Some form of a short interrupted time series (ITS) is often used to evaluate state and national programs. An ITS design with a single treatment group assumes that the pretest functional form can be validly estimated and extrapolated into the postintervention period where it provides a valid counterfactual. This assumption is problematic. Ambiguous…

  17. Conflict: Operational Realism versus Analytical Rigor in Defense Modeling and Simulation

    DTIC Science & Technology

    2012-06-14

    Campbell, Experimental and Quasi- Eperimental Designs for Generalized Causal Inference, Boston: Houghton Mifflin Company, 2002. [7] R. T. Johnson, G...experimentation? In order for an experiment to be considered rigorous, and the results valid, the experiment should be designed using established...addition to the interview, the pilots were administered a written survey, designed to capture their reactions regarding the level of realism present

  18. When a checklist is not enough: How to improve them and what else is needed.

    PubMed

    Raman, Jaishankar; Leveson, Nancy; Samost, Aubrey Lynn; Dobrilovic, Nikola; Oldham, Maggie; Dekker, Sidney; Finkelstein, Stan

    2016-08-01

    Checklists are being introduced to enhance patient safety, but the results have been mixed. The goal of this research is to understand why time-outs and checklists are sometimes not effective in preventing surgical adverse events and to identify additional measures needed to reduce these events. A total of 380 consecutive patients underwent complex cardiac surgery over a 24-month period between November 2011 and November 2013 at an academic medical center, out of a total of 529 cardiac cases. Elective isolated aortic valve replacements, mitral valve repairs, and coronary artery bypass graft surgical procedures (N = 149) were excluded. A time-out was conducted in a standard fashion in all patients in accordance with the World Health Organization surgical checklist protocol. Adverse events were classified as anything that resulted in an operative delay, nonavailability of equipment, failure of drug administration, or unexpected adverse clinical outcome. These events and their details were collected every week and analyzed using a systemic causal analysis technique using a technique called CAST (causal analysis based on systems theory). This analytic technique evaluated the sociotechnical system to identify the set of causal factors involved in the adverse events and the causal factors explored to identify reasons. Recommendations were made for the improvement of checklists and the use of system design changes that could prevent such events in the future. Thirty events were identified. The causal analysis of these 30 adverse events was carried out and actionable events classified. There were important limitations in the use of standard checklists as a stand-alone patient safety measure in the operating room setting, because of multiple factors. Major categories included miscommunication between staff, medication errors, missing instrumentation, missing implants, and improper handling of equipment or instruments. An average of 3.9 recommendations were generated for each adverse event scenario. Time-outs and checklists can prevent some types of adverse events, but they need to be carefully designed. Additional interventions aimed at improving safety controls in the system design are needed to augment the use of checklists. Customization of checklists for specialized surgical procedures may reduce adverse events. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  19. A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard.

    PubMed

    Azadmanjir, Zahra; Torabi, Mashallah; Safdari, Reza; Bayat, Maryam; Golmahi, Fatemeh

    2015-08-01

    management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard. the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified. the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers. the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process.

  20. Predicting What Will Happen When You Intervene.

    PubMed

    Cartwright, Nancy; Hardie, Jeremy

    2017-01-01

    This paper offers some rules of thumb that practicing social workers can use for case studies that aim to construct, albeit not fully and never entirely reliably, models designed to help predict what will happen if they intervene in specific ways to help this particular client, here and now. We call these 'ex ante case-specific causal models'. 'Ex ante' because they are for before-the-fact prediction of what the likely effects of proposed actions are. 'Case-specific' because we are not concerned with studies that provide evidence for some general conclusion but rather with using what general and local knowledge one can get to predict what will happen to a specific client in the real settings in which they live. 'Causal' because this kind of case study aims to trace out as best possible the web of causal processes that will be responsible for what happens. In this sense our case studies resemble post facto realist evaluations.

  1. Mendelian randomization in nutritional epidemiology

    PubMed Central

    Qi, Lu

    2013-01-01

    Nutritional epidemiology aims to identify dietary and lifestyle causes for human diseases. Causality inference in nutritional epidemiology is largely based on evidence from studies of observational design, and may be distorted by unmeasured or residual confounding and reverse causation. Mendelian randomization is a recently developed methodology that combines genetic and classical epidemiological analysis to infer causality for environmental exposures, based on the principle of Mendel’s law of independent assortment. Mendelian randomization uses genetic variants as proxiesforenvironmentalexposuresofinterest.AssociationsderivedfromMendelian randomization analysis are less likely to be affected by confounding and reverse causation. During the past 5 years, a body of studies examined the causal effects of diet/lifestyle factors and biomarkers on a variety of diseases. The Mendelian randomization approach also holds considerable promise in the study of intrauterine influences on offspring health outcomes. However, the application of Mendelian randomization in nutritional epidemiology has some limitations. PMID:19674341

  2. Steady flow on to a conveyor belt - Causal viscosity and shear shocks

    NASA Technical Reports Server (NTRS)

    Syer, D.; Narayan, Ramesh

    1993-01-01

    Some hydrodynamical consequences of the adoption of a causal theory of viscosity are explored. Causality is introduced into the theory by letting the coefficient of viscosity go to zero as the flow velocity approaches a designated propagation speed for viscous signals. Consideration is given to a model of viscosity which has a finite propagation speed of shear information, and it is shown that it produces two kinds of shear shock. A 'pure shear shock' corresponds to a transition from a superviscous to a subviscous state with no discontinuity in the velocity. A 'mixed shear shock' has a shear transition occurring at the same location as a normal adiabatic or radiative shock. A generalized version of the Rankine-Hugoniot conditions for mixed shear shocks is derived, and self-consistent numerical solutions to a model 2D problem in which an axisymmetric radially infalling stream encounters a spinning star are presented.

  3. Reasoning about Causal Relationships: Inferences on Causal Networks

    PubMed Central

    Rottman, Benjamin Margolin; Hastie, Reid

    2013-01-01

    Over the last decade, a normative framework for making causal inferences, Bayesian Probabilistic Causal Networks, has come to dominate psychological studies of inference based on causal relationships. The following causal networks—[X→Y→Z, X←Y→Z, X→Y←Z]—supply answers for questions like, “Suppose both X and Y occur, what is the probability Z occurs?” or “Suppose you intervene and make Y occur, what is the probability Z occurs?” In this review, we provide a tutorial for how normatively to calculate these inferences. Then, we systematically detail the results of behavioral studies comparing human qualitative and quantitative judgments to the normative calculations for many network structures and for several types of inferences on those networks. Overall, when the normative calculations imply that an inference should increase, judgments usually go up; when calculations imply a decrease, judgments usually go down. However, two systematic deviations appear. First, people’s inferences violate the Markov assumption. For example, when inferring Z from the structure X→Y→Z, people think that X is relevant even when Y completely mediates the relationship between X and Z. Second, even when people’s inferences are directionally consistent with the normative calculations, they are often not as sensitive to the parameters and the structure of the network as they should be. We conclude with a discussion of productive directions for future research. PMID:23544658

  4. On the factorial and construct validity of the Intrinsic Motivation Inventory: conceptual and operational concerns.

    PubMed

    Markland, D; Hardy, L

    1997-03-01

    The Intrinsic Motivation Inventory (IMI) has been gaining acceptance in the sport and exercise domain since the publication of research by McAuley, Duncan, and Tammen (1989) and McAuley, Wraith, and Duncan (1991), which reported confirmatory support for the factorial validity of a hierarchical model of intrinsic motivation. Authors of the present study argue that the results of these studies did not conclusively support the hierarchical model and that the model did not accurately reflect the tenets of cognitive evaluation theory (Deci & Ryan, 1985) from which the IMI is drawn. It is also argued that a measure of perceived locus of causality is required to model intrinsic motivation properly. The development of a perceived locus of causality for exercise scale is described, and alternative models, in which perceived competence and perceived locus of causality are held to have causal influences on intrinsic motivation, are compared with an oblique confirmatory factor analytic model in which the constructs are held at the same conceptual level. Structural equation modeling showed support for a causal model in which perceived locus of causality mediates the effects of perceived competence on pressure-tension, interest-enjoyment, and effort-importance. It is argued that conceptual and operational problems with the IMI, as currently used, should be addressed before it becomes established as the instrument of choice for assessing levels of intrinsic motivation.

  5. Data-driven confounder selection via Markov and Bayesian networks.

    PubMed

    Häggström, Jenny

    2018-06-01

    To unbiasedly estimate a causal effect on an outcome unconfoundedness is often assumed. If there is sufficient knowledge on the underlying causal structure then existing confounder selection criteria can be used to select subsets of the observed pretreatment covariates, X, sufficient for unconfoundedness, if such subsets exist. Here, estimation of these target subsets is considered when the underlying causal structure is unknown. The proposed method is to model the causal structure by a probabilistic graphical model, for example, a Markov or Bayesian network, estimate this graph from observed data and select the target subsets given the estimated graph. The approach is evaluated by simulation both in a high-dimensional setting where unconfoundedness holds given X and in a setting where unconfoundedness only holds given subsets of X. Several common target subsets are investigated and the selected subsets are compared with respect to accuracy in estimating the average causal effect. The proposed method is implemented with existing software that can easily handle high-dimensional data, in terms of large samples and large number of covariates. The results from the simulation study show that, if unconfoundedness holds given X, this approach is very successful in selecting the target subsets, outperforming alternative approaches based on random forests and LASSO, and that the subset estimating the target subset containing all causes of outcome yields smallest MSE in the average causal effect estimation. © 2017, The International Biometric Society.

  6. Bayesian Networks Improve Causal Environmental Assessments for Evidence-Based Policy.

    PubMed

    Carriger, John F; Barron, Mace G; Newman, Michael C

    2016-12-20

    Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on valued ecological resources. These aspects are demonstrated through hypothetical problem scenarios that explore some major benefits of using Bayesian networks for reasoning and making inferences in evidence-based policy.

  7. Understanding bias in relationships between the food environment and diet quality: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

    PubMed

    Rummo, Pasquale E; Guilkey, David K; Ng, Shu Wen; Meyer, Katie A; Popkin, Barry M; Reis, Jared P; Shikany, James M; Gordon-Larsen, Penny

    2017-12-01

    The relationship between food environment exposures and diet behaviours is unclear, possibly because the majority of studies ignore potential residual confounding. We used 20 years (1985-1986, 1992-1993 2005-2006) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study across four US cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California) and instrumental variables (IV) regression to obtain causal estimates of longitudinal associations between the percentage of neighbourhood food outlets (per total food outlets within 1 km network distance of respondent residence) and an a priori diet quality score, with higher scores indicating higher diet quality. To assess the presence and magnitude of bias related to residual confounding, we compared results from causal models (IV regression) to non-causal models, including ordinary least squares regression, which does not account for residual confounding at all and fixed-effects regression, which only controls for time-invariant unmeasured characteristics. The mean diet quality score across follow-up was 63.4 (SD=12.7). A 10% increase in fast food restaurants (relative to full-service restaurants) was associated with a lower diet quality score over time using IV regression (β=-1.01, 95% CI -1.99 to -0.04); estimates were attenuated using non-causal models. The percentage of neighbourhood convenience and grocery stores (relative to supermarkets) was not associated with diet quality in any model, but estimates from non-causal models were similarly attenuated compared with causal models. Ignoring residual confounding may generate biased estimated effects of neighbourhood food outlets on diet outcomes and may have contributed to weak findings in the food environment literature. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  8. A Simulation Study of Threats to Validity in Quasi-Experimental Designs: Interrelationship between Design, Measurement, and Analysis.

    PubMed

    Holgado-Tello, Fco P; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana; Pérez-Gil, José A

    2016-01-01

    The Campbellian tradition provides a conceptual framework to assess threats to validity. On the other hand, different models of causal analysis have been developed to control estimation biases in different research designs. However, the link between design features, measurement issues, and concrete impact estimation analyses is weak. In order to provide an empirical solution to this problem, we use Structural Equation Modeling (SEM) as a first approximation to operationalize the analytical implications of threats to validity in quasi-experimental designs. Based on the analogies established between the Classical Test Theory (CTT) and causal analysis, we describe an empirical study based on SEM in which range restriction and statistical power have been simulated in two different models: (1) A multistate model in the control condition (pre-test); and (2) A single-trait-multistate model in the control condition (post-test), adding a new mediator latent exogenous (independent) variable that represents a threat to validity. Results show, empirically, how the differences between both the models could be partially or totally attributed to these threats. Therefore, SEM provides a useful tool to analyze the influence of potential threats to validity.

  9. A Simulation Study of Threats to Validity in Quasi-Experimental Designs: Interrelationship between Design, Measurement, and Analysis

    PubMed Central

    Holgado-Tello, Fco. P.; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana; Pérez-Gil, José A.

    2016-01-01

    The Campbellian tradition provides a conceptual framework to assess threats to validity. On the other hand, different models of causal analysis have been developed to control estimation biases in different research designs. However, the link between design features, measurement issues, and concrete impact estimation analyses is weak. In order to provide an empirical solution to this problem, we use Structural Equation Modeling (SEM) as a first approximation to operationalize the analytical implications of threats to validity in quasi-experimental designs. Based on the analogies established between the Classical Test Theory (CTT) and causal analysis, we describe an empirical study based on SEM in which range restriction and statistical power have been simulated in two different models: (1) A multistate model in the control condition (pre-test); and (2) A single-trait-multistate model in the control condition (post-test), adding a new mediator latent exogenous (independent) variable that represents a threat to validity. Results show, empirically, how the differences between both the models could be partially or totally attributed to these threats. Therefore, SEM provides a useful tool to analyze the influence of potential threats to validity. PMID:27378991

  10. The mutual causality analysis between the stock and futures markets

    NASA Astrophysics Data System (ADS)

    Yao, Can-Zhong; Lin, Qing-Wen

    2017-07-01

    In this paper we employ the conditional Granger causality model to estimate the information flow, and find that the improved model outperforms the Granger causality model in revealing the asymmetric correlation between stocks and futures in the Chinese market. First, we find that information flows estimated by Granger causality tests from futures to stocks are greater than those from stocks to futures. Additionally, average correlation coefficients capture some important characteristics between stock prices and information flows over time. Further, we find that direct information flows estimated by conditional Granger causality tests from stocks to futures are greater than those from futures to stocks. Besides, the substantial increases of information flows and direct information flows exhibit a certain degree of synchronism with the occurrences of important events. Finally, the comparative analysis with the asymmetric ratio and the bootstrap technique demonstrates the slight asymmetry of information flows and the significant asymmetry of direct information flows. It reveals that the information flows from futures to stocks are slightly greater than those in the reverse direction, while the direct information flows from stocks to futures are significantly greater than those in the reverse direction.

  11. Within-subject mediation analysis for experimental data in cognitive psychology and neuroscience.

    PubMed

    Vuorre, Matti; Bolger, Niall

    2017-12-15

    Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and neuroscience. One reason for the scarcity of applications is that these areas of psychology commonly employ within-subjects designs, and mediation models for within-subjects data are considerably more complicated than for between-subjects data. Here, we draw attention to the importance and ubiquity of mediational hypotheses in within-subjects designs, and we present a general and flexible software package for conducting Bayesian within-subjects mediation analyses in the R programming environment. We use experimental data from cognitive psychology to illustrate the benefits of within-subject mediation for theory testing and comparison.

  12. Causal relationships among academic delay of gratification, motivation, and self-regulated learning in elementary school children.

    PubMed

    Zhang, Lili; Maruno, Shun'ichi

    2010-10-01

    Academic delay of gratification refers to the postponement of immediate rewards by students and the pursuit of more important, temporally remote academic goals. A path model was designed to identify the causal relationships among academic delay of gratification and motivation, self-regulated learning strategies (as specified in the Motivated Strategies for Learning Questionnaire), and grades among 386 Chinese elementary school children. Academic delay of gratification was found to be positively related to motivation and metacognition. Cognitive strategy, resource management, and grades mediated these two factors and were indirectly related to academic delay of gratification.

  13. Expanding the basic science debate: the role of physics knowledge in interpreting clinical findings.

    PubMed

    Goldszmidt, Mark; Minda, John Paul; Devantier, Sarah L; Skye, Aimee L; Woods, Nicole N

    2012-10-01

    Current research suggests a role for biomedical knowledge in learning and retaining concepts related to medical diagnosis. However, learning may be influenced by other, non-biomedical knowledge. We explored this idea using an experimental design and examined the effects of causal knowledge on the learning, retention, and interpretation of medical information. Participants studied a handout about several respiratory disorders and how to interpret respiratory exam findings. The control group received the information in standard "textbook" format and the experimental group was presented with the same information as well as a causal explanation about how sound travels through lungs in both the normal and disease states. Comprehension and memory of the information was evaluated with a multiple-choice exam. Several questions that were not related to the causal knowledge served as control items. Questions related to the interpretation of physical exam findings served as the critical test items. The experimental group outperformed the control group on the critical test items, and our study shows that a causal explanation can improve a student's memory for interpreting clinical details. We suggest an expansion of which basic sciences are considered fundamental to medical education.

  14. Hindsight bias doesn't always come easy: causal models, cognitive effort, and creeping determinism.

    PubMed

    Nestler, Steffen; Blank, Hartmut; von Collani, Gernot

    2008-09-01

    Creeping determinism, a form of hindsight bias, refers to people's hindsight perceptions of events as being determined or inevitable. This article proposes, on the basis of a causal-model theory of creeping determinism, that the underlying processes are effortful, and hence creeping determinism should disappear when individuals lack the cognitive resources to make sense of an outcome. In Experiments 1 and 2, participants were asked to read a scenario while they were under either low or high processing load. Participants who had the cognitive resources to make sense of the outcome perceived it as more probable and necessary than did participants under high processing load or participants who did not receive outcome information. Experiment 3 was designed to separate 2 postulated subprocesses and showed that the attenuating effect of processing load on hindsight bias is not due to a disruption of the retrieval of potential causal antecedents but to a disruption of their evaluation. Together the 3 experiments show that the processes underlying creeping determinism are effortful, and they highlight the crucial role of causal reasoning in the perception of past events. (c) 2008 APA, all rights reserved.

  15. Selective effects of explanation on learning during early childhood.

    PubMed

    Legare, Cristine H; Lombrozo, Tania

    2014-10-01

    Two studies examined the specificity of effects of explanation on learning by prompting 3- to 6-year-old children to explain a mechanical toy and comparing what they learned about the toy's causal and non-causal properties with children who only observed the toy, both with and without accompanying verbalization. In Study 1, children were experimentally assigned to either explain or observe the mechanical toy. In Study 2, children were classified according to whether the content of their response to an undirected prompt involved explanation. Dependent measures included whether children understood the toy's functional-mechanical relationships, remembered perceptual features of the toy, effectively reconstructed the toy, and (for Study 2) generalized the function of the toy when constructing a new one. Results demonstrate that across age groups, explanation promotes causal learning and generalization but does not improve (and in younger children can even impair) memory for causally irrelevant perceptual details. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Evaluating Candidate Principal Surrogate Endpoints

    PubMed Central

    Gilbert, Peter B.; Hudgens, Michael G.

    2009-01-01

    Summary Frangakis and Rubin (2002, Biometrics 58, 21–29) proposed a new definition of a surrogate endpoint (a “principal” surrogate) based on causal effects. We introduce an estimand for evaluating a principal surrogate, the causal effect predictiveness (CEP) surface, which quantifies how well causal treatment effects on the biomarker predict causal treatment effects on the clinical endpoint. Although the CEP surface is not identifiable due to missing potential outcomes, it can be identified by incorporating a baseline covariate(s) that predicts the biomarker. Given case–cohort sampling of such a baseline predictor and the biomarker in a large blinded randomized clinical trial, we develop an estimated likelihood method for estimating the CEP surface. This estimation assesses the “surrogate value” of the biomarker for reliably predicting clinical treatment effects for the same or similar setting as the trial. A CEP surface plot provides a way to compare the surrogate value of multiple biomarkers. The approach is illustrated by the problem of assessing an immune response to a vaccine as a surrogate endpoint for infection. PMID:18363776

  17. Identifying causal linkages between environmental variables and African conflicts

    NASA Astrophysics Data System (ADS)

    Nguy-Robertson, A. L.; Dartevelle, S.

    2017-12-01

    Environmental variables that contribute to droughts, flooding, and other natural hazards are often identified as factors contributing to conflict; however, few studies attempt to quantify these causal linkages. Recent research has demonstrated that the environment operates within a dynamical system framework and the influence of variables can be identified from convergent cross mapping (CCM) between shadow manifolds. We propose to use CCM to identify causal linkages between environmental variables and incidences of conflict. This study utilizes time series data from Climate Forecast System ver. 2 and MODIS satellite sensors processed using Google Earth Engine to aggregate country and regional trends. These variables are then compared to Armed Conflict Location & Event Data Project observations at similar scales. Results provide relative rankings of variables and their linkage to conflict. Being able to identify which factors contributed more strongly to a conflict can allow policy makers to prepare solutions to mitigate future crises. Knowledge of the primary environmental factors can lead to the identification of other variables to examine in the causal network influencing conflict.

  18. Underweight as a risk factor for respiratory death in the Whitehall cohort study: exploring reverse causality using a 45-year follow-up.

    PubMed

    Kivimäki, Mika; Shipley, Martin J; Bell, Joshua A; Brunner, Eric J; Batty, G David; Singh-Manoux, Archana

    2016-01-01

    Underweight adults have higher rates of respiratory death than the normal weight but it is unclear whether this association is causal or reflects illness-induced weight loss (reverse causality). Evidence from a 45-year follow-up of underweight participants for respiratory mortality in the Whitehall study (N=18 823; 2139 respiratory deaths) suggests that excess risk among the underweight is attributable to reverse causality. The age-adjusted and smoking-adjusted risk was 1.55-fold (95% CI 1.32 to 1.83) higher among underweight compared with normal weight participants, but attenuated in a stepwise manner to 1.14 (95% CI 0.76 to 1.71) after serial exclusions of deaths during the first 5-35 years of follow-up (P(trend)<0.001). Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  19. Bulk viscosity and relaxation time of causal dissipative relativistic fluid dynamics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Huang Xuguang; Rischke, Dirk H.; Institut fuer Theoretische Physik, J.W. Goethe-Universitaet, D-60438 Frankfurt am Main

    2011-02-15

    The microscopic formulas of the bulk viscosity {zeta} and the corresponding relaxation time {tau}{sub {Pi}} in causal dissipative relativistic fluid dynamics are derived by using the projection operator method. In applying these formulas to the pionic fluid, we find that the renormalizable energy-momentum tensor should be employed to obtain consistent results. In the leading-order approximation in the chiral perturbation theory, the relaxation time is enhanced near the QCD phase transition, and {tau}{sub {Pi}} and {zeta} are related as {tau}{sub {Pi}={zeta}}/[{beta}{l_brace}(1/3-c{sub s}{sup 2})({epsilon}+P)-2({epsilon}-3P)/9{r_brace}], where {epsilon}, P, and c{sub s} are the energy density, pressure, and velocity of sound, respectively. The predictedmore » {zeta} and {tau}{sub {Pi}} should satisfy the so-called causality condition. We compare our result with the results of the kinetic calculation by Israel and Stewart and the string theory, and confirm that all three approaches are consistent with the causality condition.« less

  20. Abnormal Visual Motion Processing is not a Cause of Dyslexia

    PubMed Central

    Olulade, Olumide A.; Napoliello, Eileen M.; Eden, Guinevere F.

    2013-01-01

    SUMMARY Developmental dyslexia is a reading disorder, yet deficits also manifest in the magnocellular-dominated dorsal visual system. Uncertainty about whether visual deficits are causal or consequential to reading disability encumbers accurate identification and appropriate treatment of this common learning disability. Using fMRI, we demonstrate in typical readers a relationship between reading ability and activity in area V5/MT during visual motion processing and, as expected, also found lower V5/MT activity for dyslexic children compared to age-matched controls. However, when dyslexics were matched to younger controls on reading ability, no differences emerged, suggesting that weakness in V5/MT may not be causal to dyslexia. To further test for causality, dyslexics underwent a phonological-based reading intervention. Surprisingly, V5/MT activity increased along with intervention-driven reading gains, demonstrating that activity here is mobilized through reading. Our results provide strong evidence that visual magnocellular dysfunction is not causal to dyslexia, but may instead be consequential to impoverished reading. PMID:23746630

  1. Attributional "Tunnel Vision" in Patients With Borderline Personality Disorder.

    PubMed

    Schilling, Lisa; Moritz, Steffen; Schneider, Brooke; Bierbrodt, Julia; Nagel, Matthias

    2015-12-01

    We aimed to examine the profile of interpersonal attributions in BPD. We hypothesized that patients show more mono-causal and internal attributions than healthy controls. A revised version of the Internal, Personal, Situational and Attributions Questionnaire was assessed in 30 BPD patients and 30 healthy controls. BPD patients and controls differed significantly in their attributional pattern. Patients displayed more mono-causal inferences, that is, they had difficulties considering alternative explanatory factors. For negative events, patients made more internal attributions compared to healthy controls. We concluded that mono-causal "trapped" thinking might contribute to (interpersonal) problems in BPD patients by fostering impulsive consequential behaviors, for example, harming one's self or others. A self-blaming tendency likely promotes depressive symptoms and low self-esteem.

  2. Increased alcohol consumption as a cause of alcoholism, without similar evidence for depression: a Mendelian randomization study.

    PubMed

    Wium-Andersen, Marie Kim; Ørsted, David Dynnes; Tolstrup, Janne Schurmann; Nordestgaard, Børge Grønne

    2015-04-01

    Increased alcohol consumption has been associated with depression and alcoholism, but whether these associations are causal remains unclear. We tested whether alcohol consumption is causally associated with depression and alcoholism. We included 78,154 men and women aged 20-100 years randomly selected in 1991-2010 from the general population of Copenhagen, Denmark, and genotyped 68,486 participants for two genetic variants in two alcohol dehydrogenase (ADH) genes, ADH-1B (rs1229984) and ADH-1C (rs698). We performed observational and causal analyses using a Mendelian randomization design with antidepressant medication use and hospitalization/death, with depression and alcoholism as outcomes. In prospective analyses, the multifactorially adjusted hazard ratio for participants reporting >6 drinks/day vs participants reporting 0.1-1 drinks/day was 1.28 (95% confidence interval, 1.00-1.65) for prescription antidepressant use, with a corresponding hazard ratio of 0.80 (0.45-1.45) for hospitalization/death with depression and of 11.7 (8.77-15.6) for hospitalization/death with alcoholism. For hospitalization/death with alcoholism, instrumental variable analysis yielded a causal odds ratio of 28.6 (95 % confidence interval 6.47-126) for an increase of 1 drink/day estimated from the combined genotype combination, whereas the corresponding multifactorially adjusted observational odds ratio was 1.28 (1.25-1.31). Corresponding odds ratios were 1.11 (0.67-1.83) causal and 1.04 (1.03-1.06) observational for prescription antidepressant use, and 4.52 (0.99-20.5) causal and 0.98 (0.94-1.03) observational for hospitalization/death with depression. These data indicate that the association between increased alcohol consumption and alcoholism is causal, without similar strong evidence for depression. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

  3. Towards non-conventional methods of designing register-based epidemiological studies: An application to pediatric research.

    PubMed

    Gong, Tong; Brew, Bronwyn; Sjölander, Arvid; Almqvist, Catarina

    2017-07-01

    Various epidemiological designs have been applied to investigate the causes and consequences of fetal growth restriction in register-based observational studies. This review seeks to provide an overview of several conventional designs, including cohort, case-control and more recently applied non-conventional designs such as family-based designs. We also discuss some practical points regarding the application and interpretation of family-based designs. Definitions of each design, the study population, the exposure and the outcome measures are briefly summarised. Examples of study designs are taken from the field of low birth-weight research for illustrative purposes. Also examined are relative advantages and disadvantages of each design in terms of assumptions, potential selection and information bias, confounding and generalisability. Kinship data linkage, statistical models and result interpretation are discussed specific to family-based designs. When all information is retrieved from registers, there is no evident preference of the case-control design over the cohort design to estimate odds ratios. All conventional designs included in the review are prone to bias, particularly due to residual confounding. Family-based designs are able to reduce such bias and strengthen causal inference. In the field of low birth-weight research, family-based designs have been able to confirm a negative association not confounded by genetic or shared environmental factors between low birth weight and the risk of asthma. We conclude that there is a broader need for family-based design in observational research as evidenced by the meaningful contributions to the understanding of the potential causal association between low birth weight and subsequent outcomes.

  4. Development and Evaluation of a Career Continuance Model for Company Grade Officers in the United States Army

    DTIC Science & Technology

    2011-03-01

    causal inference (e.g., longitudinal designs , training designs that include matched control groups ). Given the importance of time in our model... quantitative results. We did, of course, do qualitative research as part of this project in the form of focus groups and interviews. There are a... nonequivalent group designs . In T. D. Cook & D. T. Campbell, D. T. Quasi-experimentation: Design and Analysis Issues for Field Settings. (pp. 147-205

  5. A Case-Based Approach to Creative Design

    DTIC Science & Technology

    1993-10-05

    for solving the sometimes causal (e.g., the operation of ping-pong ball problem. Each time, the designer has different cues shooter 8) and sometimes...In addi- dance (15) is used to quickly communicate the struc- tion to the desired behavior, prominent visual cues may ture of a design alternative...and vague, incomplete havior. specifications. For example, Si’s mental picture of Structural cues describing the proposed solution, or a submarine

  6. Quasi-experimental study designs series-paper 2: complementary approaches to advancing global health knowledge.

    PubMed

    Geldsetzer, Pascal; Fawzi, Wafaie

    2017-09-01

    Quasi-experiments have been infrequently used in the health sciences. Focusing on health systems implementation research, this article details key advantages of quasi-experiments and argues that they can complement (but not replace) randomized evaluations. Specifically, it may be possible to use a quasi-experiment to study the causal effect of an intervention that cannot feasibly be randomized or that would be unethical (e.g., because the intervention has become the standard of care) to test in a randomized controlled trial (RCT). In addition, because they usually take advantage of routinely collected data, quasi-experiments may be feasible when it is too costly (either financially or in terms of the required time) to carry out a RCT - an important advantage in research on health systems, which vary widely between settings. Nonetheless, we argue that RCTs will continue to be indispensable for implementation research because i) the assumptions needed to establish causality with a quasi-experiment are often unverifiable, ii) available data frequently do not allow for a rigorous quasi-experiment, and iii) randomized designs tend to lend themselves more to informing policy makers of causal effects prior to (or during) the full-scale rollout of an intervention than quasi-experiments. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Beyond a series of security nets: Applying STAMP & STPA to port security

    DOE PAGES

    Williams, Adam D.

    2015-11-17

    Port security is an increasing concern considering the significant role of ports in global commerce and today’s increasingly complex threat environment. Current approaches to port security mirror traditional models of accident causality -- ‘a series of security nets’ based on component reliability and probabilistic assumptions. Traditional port security frameworks result in isolated and inconsistent improvement strategies. Recent work in engineered safety combines the ideas of hierarchy, emergence, control and communication into a new paradigm for understanding port security as an emergent complex system property. The ‘System-Theoretic Accident Model and Process (STAMP)’ is a new model of causality based on systemsmore » and control theory. The associated analysis process -- System Theoretic Process Analysis (STPA) -- identifies specific technical or procedural security requirements designed to work in coordination with (and be traceable to) overall port objectives. This process yields port security design specifications that can mitigate (if not eliminate) port security vulnerabilities related to an emphasis on component reliability, lack of coordination between port security stakeholders or economic pressures endemic in the maritime industry. As a result, this article aims to demonstrate how STAMP’s broader view of causality and complexity can better address the dynamic and interactive behaviors of social, organizational and technical components of port security.« less

  8. Self-organizing map analysis using multivariate data from theophylline powders predicted by a thin-plate spline interpolation.

    PubMed

    Yasuda, Akihito; Onuki, Yoshinori; Kikuchi, Shingo; Takayama, Kozo

    2010-11-01

    The quality by design concept in pharmaceutical formulation development requires establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline powders were prepared based on the standard formulation. The angle of repose, compressibility, cohesion, and dispersibility were measured as the response variables. These responses were predicted quantitatively on the basis of a nonlinear TPS. A large amount of data on these powders was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the powders could be classified into several distinctive clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and powder characteristics. For instance, the quantities of microcrystalline cellulose (MCC) and magnesium stearate (Mg-St) were classified distinctly into each cluster, indicating that the quantities of MCC and Mg-St were crucial for determining the powder characteristics. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline powder formulations. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

  9. Beyond a series of security nets: Applying STAMP & STPA to port security

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Williams, Adam D.

    Port security is an increasing concern considering the significant role of ports in global commerce and today’s increasingly complex threat environment. Current approaches to port security mirror traditional models of accident causality -- ‘a series of security nets’ based on component reliability and probabilistic assumptions. Traditional port security frameworks result in isolated and inconsistent improvement strategies. Recent work in engineered safety combines the ideas of hierarchy, emergence, control and communication into a new paradigm for understanding port security as an emergent complex system property. The ‘System-Theoretic Accident Model and Process (STAMP)’ is a new model of causality based on systemsmore » and control theory. The associated analysis process -- System Theoretic Process Analysis (STPA) -- identifies specific technical or procedural security requirements designed to work in coordination with (and be traceable to) overall port objectives. This process yields port security design specifications that can mitigate (if not eliminate) port security vulnerabilities related to an emphasis on component reliability, lack of coordination between port security stakeholders or economic pressures endemic in the maritime industry. As a result, this article aims to demonstrate how STAMP’s broader view of causality and complexity can better address the dynamic and interactive behaviors of social, organizational and technical components of port security.« less

  10. A review of human-automation interaction and lessons learned

    DOT National Transportation Integrated Search

    2006-10-01

    This report reviews 37 accidents in aviation, other vehicles, process control and other complex systems where human-automation interaction is involved. Implications about causality with respect to design, procedures, management and training are drawn...

  11. Estimating Causal Effects of Education Interventions Using a Two-Rating Regression Discontinuity Design: Lessons from a Simulation Study

    ERIC Educational Resources Information Center

    Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Robinson-Cimpian, Joseph P.

    2014-01-01

    A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…

  12. To stage or not to stage? That is the question: (with apologies to Shakespeare).

    PubMed

    Kitchener, Henry C

    2010-10-01

    The International Federation of Gynecology and Obstetrics staging rules for endometrial cancer require pelvic and para-aortic node dissection to define the extent of disease. Retrospective studies have reported improved survival in women who underwent lymphadenectomy compared with those who did not. This association may not be causally related because of bias. Recently reported prospective randomized trials of pelvic lymphadenectomy have failed to demonstrate a survival benefit. Critics of these trials remain skeptical because of perceived limitations in design, particularly the inclusion of non-high-risk women and the lack of full para-aortic lymphadenectomy. Until new trial evidence is produced to the contrary, routine lymphadenectomy cannot be recommended for endometrial cancer.

  13. Behavioral Implications of Piezoelectric Stack Actuators for Control of Micromanipulation

    NASA Technical Reports Server (NTRS)

    Goldfarb, Michael; Celanovic, Nikola

    1996-01-01

    A lumped-parameter model of a piezoelectric stack actuator has been developed to describe actuator behavior for purposes of control system analysis and design, and in particular for microrobotic applications requiring accurate position and/or force control. In addition to describing the input-output dynamic behavior, the proposed model explains aspects of non-intuitive behavioral phenomena evinced by piezoelectric actuators, such as the input-output rate-independent hysteresis and the change in mechanical stiffness that results from altering electrical load. The authors incorporate a generalized Maxwell resistive capacitor as a lumped-parameter causal representation of rate-independent hysteresis. Model formulation is validated by comparing results of numerical simulations to experimental data.

  14. Social welfare support and homicide: longitudinal analyses of European countries from 1994 to 2010.

    PubMed

    McCall, Patricia L; Brauer, Jonathan R

    2014-11-01

    The purpose of this research is to explore the extent to which retrenchment in welfare support is related to homicide trends across European countries between 1994 and 2010. Using a longitudinal decomposition design that allows for stronger causal inferences compared to typical cross-sectional designs, we examine these potential linkages between social support spending and homicide with data collected from a heterogeneous sample of European nations, including twenty Western nations and nine less frequently analyzed East-Central nations, during recent years in which European nations generally witnessed substantial changes in homicide rates as well as both economic prosperity and fiscal crisis. Results suggest that even incremental, short-term changes in welfare support spending are associated with short-term reductions in homicide-specifically, impacting homicide rates within two to three years for this sample of European nations. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Assessing the Effectiveness of Cumulative Sum Normal- and Poisson-Based Tests for Detecting Rare Diseases

    DTIC Science & Technology

    2010-12-01

    The Francisella tularensis is one of these and is the causal agent of the tularemia disease. Tularemia is used as the motivating problem to evaluate...PAGES 79 14. SUBJECT TERMS Biosurveillance, Rare Disease, Tularemia , Cumulative Sum, CUSUM 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...is one of these, and is the causal agent of the tularemia disease. Tularemia is used as the motivating problem to evaluate and compare the

  16. Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals

    PubMed Central

    Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.

    2014-01-01

    This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437

  17. Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles

    PubMed Central

    Zanos, Theodoros P.; Courellis, Spiros H.; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.

    2009-01-01

    The increasing availability of multiunit recordings gives new urgency to the need for effective analysis of “multidimensional” time-series data that are derived from the recorded activity of neuronal ensembles in the form of multiple sequences of action potentials—treated mathematically as point-processes and computationally as spike-trains. Whether in conditions of spontaneous activity or under conditions of external stimulation, the objective is the identification and quantification of possible causal links among the neurons generating the observed binary signals. A multiple-input/multiple-output (MIMO) modeling methodology is presented that can be used to quantify the neuronal dynamics of causal interrelationships in neuronal ensembles using spike-train data recorded from individual neurons. These causal interrelationships are modeled as transformations of spike-trains recorded from a set of neurons designated as the “inputs” into spike-trains recorded from another set of neurons designated as the “outputs.” The MIMO model is composed of a set of multiinput/single-output (MISO) modules, one for each output. Each module is the cascade of a MISO Volterra model and a threshold operator generating the output spikes. The Laguerre expansion approach is used to estimate the Volterra kernels of each MISO module from the respective input–output data using the least-squares method. The predictive performance of the model is evaluated with the use of the receiver operating characteristic (ROC) curve, from which the optimum threshold is also selected. The Mann–Whitney statistic is used to select the significant inputs for each output by examining the statistical significance of improvements in the predictive accuracy of the model when the respective inputs is included. Illustrative examples are presented for a simulated system and for an actual application using multiunit data recordings from the hippocampus of a behaving rat. PMID:18701382

  18. Causal Inference for fMRI Time Series Data with Systematic Errors of Measurement in a Balanced On/Off Study of Social Evaluative Threat.

    PubMed

    Sobel, Michael E; Lindquist, Martin A

    2014-07-01

    Functional magnetic resonance imaging (fMRI) has facilitated major advances in understanding human brain function. Neuroscientists are interested in using fMRI to study the effects of external stimuli on brain activity and causal relationships among brain regions, but have not stated what is meant by causation or defined the effects they purport to estimate. Building on Rubin's causal model, we construct a framework for causal inference using blood oxygenation level dependent (BOLD) fMRI time series data. In the usual statistical literature on causal inference, potential outcomes, assumed to be measured without systematic error, are used to define unit and average causal effects. However, in general the potential BOLD responses are measured with stimulus dependent systematic error. Thus we define unit and average causal effects that are free of systematic error. In contrast to the usual case of a randomized experiment where adjustment for intermediate outcomes leads to biased estimates of treatment effects (Rosenbaum, 1984), here the failure to adjust for task dependent systematic error leads to biased estimates. We therefore adjust for systematic error using measured "noise covariates" , using a linear mixed model to estimate the effects and the systematic error. Our results are important for neuroscientists, who typically do not adjust for systematic error. They should also prove useful to researchers in other areas where responses are measured with error and in fields where large amounts of data are collected on relatively few subjects. To illustrate our approach, we re-analyze data from a social evaluative threat task, comparing the findings with results that ignore systematic error.

  19. Too much sitting and all-cause mortality: is there a causal link?

    PubMed

    Biddle, Stuart J H; Bennie, Jason A; Bauman, Adrian E; Chau, Josephine Y; Dunstan, David; Owen, Neville; Stamatakis, Emmanuel; van Uffelen, Jannique G Z

    2016-07-26

    Sedentary behaviours (time spent sitting, with low energy expenditure) are associated with deleterious health outcomes, including all-cause mortality. Whether this association can be considered causal has yet to be established. Using systematic reviews and primary studies from those reviews, we drew upon Bradford Hill's criteria to consider the likelihood that sedentary behaviour in epidemiological studies is likely to be causally related to all-cause (premature) mortality. Searches for systematic reviews on sedentary behaviours and all-cause mortality yielded 386 records which, when judged against eligibility criteria, left eight reviews (addressing 17 primary studies) for analysis. Exposure measures included self-reported total sitting time, TV viewing time, and screen time. Studies included comparisons of a low-sedentary reference group with several higher sedentary categories, or compared the highest versus lowest sedentary behaviour groups. We employed four Bradford Hill criteria: strength of association, consistency, temporality, and dose-response. Evidence supporting causality at the level of each systematic review and primary study was judged using a traffic light system depicting green for causal evidence, amber for mixed or inconclusive evidence, and red for no evidence for causality (either evidence of no effect or no evidence reported). The eight systematic reviews showed evidence for consistency (7 green) and temporality (6 green), and some evidence for strength of association (4 green). There was no evidence for a dose-response relationship (5 red). Five reviews were rated green overall. Twelve (67 %) of the primary studies were rated green, with evidence for strength and temporality. There is reasonable evidence for a likely causal relationship between sedentary behaviour and all-cause mortality based on the epidemiological criteria of strength of association, consistency of effect, and temporality.

  20. Identification of causal genes for complex traits

    PubMed Central

    Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

    2015-01-01

    Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider ‘causal variants’ as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. Results: In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Availability and implementation: Software is freely available for download at genetics.cs.ucla.edu/caviar. Contact: eeskin@cs.ucla.edu PMID:26072484

  1. Identification of causal genes for complex traits.

    PubMed

    Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

    2015-06-15

    Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Software is freely available for download at genetics.cs.ucla.edu/caviar. © The Author 2015. Published by Oxford University Press.

  2. Use of Causal Diagrams to Inform the Design and Interpretation of Observational Studies: An Example from the Study of Heart and Renal Protection (SHARP).

    PubMed

    Staplin, Natalie; Herrington, William G; Judge, Parminder K; Reith, Christina A; Haynes, Richard; Landray, Martin J; Baigent, Colin; Emberson, Jonathan

    2017-03-07

    Observational studies often seek to estimate the causal relevance of an exposure to an outcome of interest. However, many possible biases can arise when estimating such relationships, in particular bias because of confounding. To control for confounding properly, careful consideration of the nature of the assumed relationships between the exposure, the outcome, and other characteristics is required. Causal diagrams provide a simple graphic means of displaying such relationships, describing the assumptions made, and allowing for the identification of a set of characteristics that should be taken into account ( i.e. , adjusted for) in any analysis. Furthermore, causal diagrams can be used to identify other possible sources of bias (such as selection bias), which if understood from the outset, can inform the planning of appropriate analyses. In this article, we review the basic theory of causal diagrams and describe some of the methods available to identify which characteristics need to be taken into account when estimating the total effect of an exposure on an outcome. In doing so, we review the concept of collider bias and show how it is inappropriate to adjust for characteristics that may be influenced, directly or indirectly, by both the exposure and the outcome of interest. A motivating example is taken from the Study of Heart and Renal Protection, in which the relevance of smoking to progression to ESRD is considered. Copyright © 2017 by the American Society of Nephrology.

  3. A stitch in time saves nine? A repeated cross-sectional case study on the implementation of the intersectoral community approach Youth At a Healthy Weight.

    PubMed

    van der Kleij, Rianne M J J; Crone, Mathilde R; Paulussen, Theo G W M; van de Gaar, Vivan M; Reis, Ria

    2015-10-08

    The implementation of programs complex in design, such as the intersectoral community approach Youth At a Healthy Weight (JOGG), often deviates from their application as intended. There is limited knowledge of their implementation processes, making it difficult to formulate sound implementation strategies. For two years, we performed a repeated cross-sectional case study on the implementation of a JOGG fruit and water campaign targeting children age 0-12. Semi-structured observations, interviews, field notes and professionals' logs entries were used to evaluate implementation process. Data was analyzed via a framework approach; within-case and cross-case displays were formulated and key determinants identified. Principles from Qualitative Comparative Analysis (QCA) were used to identify causal configurations of determinants per sector and implementation phase. Implementation completeness differed, but was highest in the educational and health care sector, and higher for key than additional activities. Determinants and causal configurations of determinants were mostly sector- and implementation phase specific. High campaign ownership and possibilities for campaign adaptation were most frequently mentioned as facilitators. A lack of reinforcement strategies, low priority for campaign use and incompatibility of own goals with campaign goals were most often indicated as barriers. We advise multiple 'stitches in time'; tailoring implementation strategies to specific implementation phases and sectors using both the results from this study and a mutual adaptation strategy in which professionals are involved in the development of implementation strategies. The results of this study show that the implementation process of IACOs is complex and sustainable implementation is difficult to achieve. Moreover, this study reveals that the implementation process is influenced by predominantly sector and implementation phase specific (causal configurations of) determinants.

  4. Delayed enhancement of multitasking performance: Effects of anodal transcranial direct current stimulation on the prefrontal cortex

    PubMed Central

    Hsu, Wan-Yu; Zanto, Theodore P.; Anguera, Joaquin A.; Lin, Yung-Yang; Gazzaley, Adam

    2015-01-01

    Background The dorsolateral prefrontal cortex (DLPFC) has been proposed to play an important role in neural processes that underlie multitasking performance. However, this claim is underexplored in terms of direct causal evidence. Objective The current study aimed to delineate the causal involvement of the DLPFC during multitasking by modulating neural activity with transcranial direct current stimulation (tDCS) prior to engagement in a demanding multitasking paradigm. Methods The study is a single-blind, crossover, sham-controlled experiment. Anodal tDCS or sham tDCS was applied over left DLPFC in forty-one healthy young adults (aged 18–35 years) immediately before they engaged in a 3-D video game designed to assess multitasking performance. Participants were separated into three subgroups: real-sham (i.e., real tDCS in the first session, followed by sham tDCS in the second session one hour later), sham-real (sham tDCS first session, real tDCS second session), and sham-sham (sham tDCS in both sessions). Results The real-sham group showed enhanced multitasking performance and decreased multitasking cost during the second session, compared to first session, suggesting delayed cognitive benefits of tDCS. Interestingly, performance benefits were observed only for multitasking and not on a single-task version of the game. No significant changes were found between the first and second sessions for either the sham-real or the sham-sham groups. Conclusions These results suggest a causal role of left prefrontal cortex in facilitating the simultaneous performance of more than one task, or multitasking. Moreover, these findings reveal that anodal tDCS may have delayed benefits that reflect an enhanced rate of learning. PMID:26073148

  5. Delayed enhancement of multitasking performance: Effects of anodal transcranial direct current stimulation on the prefrontal cortex.

    PubMed

    Hsu, Wan-Yu; Zanto, Theodore P; Anguera, Joaquin A; Lin, Yung-Yang; Gazzaley, Adam

    2015-08-01

    The dorsolateral prefrontal cortex (DLPFC) has been proposed to play an important role in neural processes that underlie multitasking performance. However, this claim is underexplored in terms of direct causal evidence. The current study aimed to delineate the causal involvement of the DLPFC during multitasking by modulating neural activity with transcranial direct current stimulation (tDCS) prior to engagement in a demanding multitasking paradigm. The study is a single-blind, crossover, sham-controlled experiment. Anodal tDCS or sham tDCS was applied over left DLPFC in forty-one healthy young adults (aged 18-35 years) immediately before they engaged in a 3-D video game designed to assess multitasking performance. Participants were separated into three subgroups: real-sham (i.e., real tDCS in the first session, followed by sham tDCS in the second session 1 h later), sham-real (sham tDCS first session, real tDCS second session), and sham-sham (sham tDCS in both sessions). The real-sham group showed enhanced multitasking performance and decreased multitasking cost during the second session, compared to first session, suggesting delayed cognitive benefits of tDCS. Interestingly, performance benefits were observed only for multitasking and not on a single-task version of the game. No significant changes were found between the first and second sessions for either the sham-real or the sham-sham groups. These results suggest a causal role of left prefrontal cortex in facilitating the simultaneous performance of more than one task, or multitasking. Moreover, these findings reveal that anodal tDCS may have delayed benefits that reflect an enhanced rate of learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Parental depression and offspring psychopathology: a children of twins study.

    PubMed

    Singh, A L; D'Onofrio, B M; Slutske, W S; Turkheimer, E; Emery, R E; Harden, K P; Heath, A C; Madden, P A F; Statham, D J; Martin, N G

    2011-07-01

    Associations between parental depression and offspring affective and disruptive disorders are well documented. Few genetically informed studies have explored the processes underlying intergenerational associations. A semi-structured interview assessing DSM-III-R psychiatric disorders was administered to twins (n=1296) from the Australian Twin Register (ATR), their spouses (n=1046) and offspring (n=2555). We used the Children of Twins (CoT) design to delineate the extent to which intergenerational associations were consistent with a causal influence or due to genetic confounds. In between-family analyses, parental depression was associated significantly with offspring depression [hazard ratio (HR) 1.52, 95% confidence interval (CI) 1.20-1.93] and conduct disorder (CD; HR 2.27, CI 1.31-3.93). Survival analysis indicated that the intergenerational transmission of depression is consistent with a causal (environmental) inference, with a significant intergenerational association in offspring of discordant monozygotic (MZ) twin pairs (HR 1.39, CI 1.00-1.94). Logistic regression analysis suggested that the parental depression-offspring CD association was due to shared genetic liability in the parents and offspring. No intergenerational association was found when comparing the offspring of discordant MZ twins [odds ratio (OR) 1.41, CI 0.63-3.14], but offspring of discordant dizygotic (DZ) twins differed in their rates of CD (OR 2.53, CI 0.95-6.76). All findings remained after controlling for several measured covariates, including history of depression and CD in the twins' spouses. The mechanisms underlying associations between parental depression and offspring psychopathology seem to differ depending on the outcome. The results are consistent with a causal environmental role of parental depression in offspring depression whereas common genetic factors account for the association of parental depression and offspring CD.

  7. Instantaneous and causal connectivity in resting state brain networks derived from functional MRI data.

    PubMed

    Deshpande, Gopikrishna; Santhanam, Priya; Hu, Xiaoping

    2011-01-15

    Most neuroimaging studies of resting state networks have concentrated on functional connectivity (FC) based on instantaneous correlation in a single network. In this study we investigated both FC and effective connectivity (EC) based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data - default mode network (DMN), hippocampal cortical memory network (HCMN), dorsal attention network (DAN) and fronto-parietal control network (FPCN). A method called correlation-purged Granger causality analysis was used, not only enabling the simultaneous evaluation of FC and EC of all networks using a single multivariate model, but also accounting for the interaction between them resulting from the smoothing of neuronal activity by hemodynamics. FC was visualized using a force-directed layout upon which causal interactions were overlaid. FC results revealed that DAN is very tightly coupled compared to the other networks while the DMN forms the backbone around which the other networks amalgamate. The pattern of bidirectional causal interactions indicates that posterior cingulate and posterior inferior parietal lobule of DMN act as major hubs. The pattern of unidirectional causal paths revealed that hippocampus and anterior prefrontal cortex (aPFC) receive major inputs, likely reflecting memory encoding/retrieval and cognitive integration, respectively. Major outputs emanating from anterior insula and middle temporal area, which are directed at aPFC, may carry information about interoceptive awareness and external environment, respectively, into aPFC for integration, supporting the hypothesis that aPFC-seeded FPCN acts as a control network. Our findings indicate the following. First, regions whose activities are not synchronized interact via time-delayed causal influences. Second, the causal interactions are organized such that cingulo-parietal regions act as hubs. Finally, segregation of different resting state networks is not clear cut but only by soft boundaries. Copyright © 2010 Elsevier Inc. All rights reserved.

  8. Design of an optimal preview controller for linear discrete-time descriptor systems with state delay

    NASA Astrophysics Data System (ADS)

    Cao, Mengjuan; Liao, Fucheng

    2015-04-01

    In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.

  9. The psychophysics of comic: Effects of incongruity in causality and animacy.

    PubMed

    Parovel, Giulia; Guidi, Stefano

    2015-07-01

    According to several theories of humour (see Berger, 2012; Martin, 2007), incongruity - i.e., the presence of two incompatible meanings in the same situation - is a crucial condition for an event being evaluated as comical. The aim of this research was to test with psychophysical methods the role of incongruity in visual perception by manipulating the causal paradigm (Michotte, 1946/1963) to get a comic effect. We ran three experiments. In Experiment 1, we tested the role of speed ratio between the first and the second movement, and the effect of animacy cues (i.e. frog-like and jumping-like trajectories) in the second movement; in Experiment 2, we manipulated the temporal delay between the movements to explore the relationship between perceptual causal contingencies and comic impressions; in Experiment 3, we compared the strength of the comic impressions arising from incongruent trajectories based on animacy cues with those arising from incongruent trajectories not based on animacy cues (bouncing and rotating) in the second part of the causal event. General findings showed that the paradoxical juxtaposition of a living behaviour in the perceptual causal paradigm is a powerful factor in eliciting comic appreciations, coherently with the Bergsonian perspective in particular (Bergson, 2003), and with incongruity theories in general. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Revisiting the effect of colonial institutions on comparative economic development

    PubMed Central

    Regele, Matthew

    2017-01-01

    European settler mortality has been proposed as an instrument to predict the causal effect of colonial institutions on differences in economic development. We examine the relationship between mortality, temperature, and economic development in former European colonies in Asia, Africa, and the Americas. We find that (i) European settler mortality rates increased with regional temperatures and (ii) economic output decreased with regional temperatures. Conditioning on the continent of settlement and accounting for colonies that were not independent as of 1900 undermines the causal effect of colonial institutions on comparative economic development. Our findings run counter to the institutions hypothesis of economic development, showing instead that geography affected both historic mortality rates and present-day economic output. PMID:28481920

  11. The Prekindergarten Age-Cutoff Regression-Discontinuity Design: Methodological Issues and Implications for Application

    ERIC Educational Resources Information Center

    Lipsey, Mark W.; Weiland, Christina; Yoshikawa, Hirokazu; Wilson, Sandra Jo; Hofer, Kerry G.

    2015-01-01

    Much of the currently available evidence on the causal effects of public prekindergarten programs on school readiness outcomes comes from studies that use a regression-discontinuity design (RDD) with the age cutoff to enter a program in a given year as the basis for assignment to treatment and control conditions. Because the RDD has high internal…

  12. Estimating Causal Effects of Education Interventions Using a Two-Rating Regression Discontinuity Design: Lessons from a Simulation Study and an Application

    ERIC Educational Resources Information Center

    Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Cimpian, Joseph R.

    2017-01-01

    A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…

  13. Developing Year 2 Students' Theory of Biology with Concepts of the Gene and DNA

    ERIC Educational Resources Information Center

    Venville, Grady; Donovan, Jenny

    2007-01-01

    This paper presents a case study of a teaching intervention designed to enrich Year 2 students' theory of biology through the introduction of causal mechanisms of inheritance such as the gene and DNA. The researchers worked collaboratively with the classroom teacher to design the intervention based on the students' prior knowledge of living things…

  14. Rationale and design of the vitamin D and type 2 diabetes (D2d) study: a diabetes prevention trial

    USDA-ARS?s Scientific Manuscript database

    OBJECTIVE: Observational studies suggest that vitamin D may lower the risk of type 2 diabetes. However, data from long-term trials are lacking. The Vitamin D and Type 2 Diabetes (D2d) study is a randomized clinical trial designed to examine whether a causal relationship exists between vitamin D supp...

  15. Evaluating Math Recovery: Assessing the Causal Impact of a Diagnostic Tutoring Program on Student Achievement

    ERIC Educational Resources Information Center

    Smith, Thomas M.; Cobb, Paul; Farran, Dale C.; Cordray, David S.; Munter, Charles

    2013-01-01

    Mathematics Recovery (MR) is designed to identify first graders who are struggling in mathematics and provide them with intensive one-to-one tutoring. We report findings from a 2-year evaluation of MR conducted in 20 elementary schools across five districts in two states. The design allowed for the estimation of the counterfactual growth…

  16. Why an Active Comparison Group Makes a Difference and What to Do about It

    ERIC Educational Resources Information Center

    Datta, Lois-ellin

    2007-01-01

    The Randomized Control Trials (RCT) design and its quasi-experimental kissing cousin, the Comparison Group Trials (CGT), are golden to some and not even silver to others. At the center of the affection, at the vortex of the discomfort, are beliefs about what it takes to establish causality. These designs are considered primarily when the purpose…

  17. Understanding by Design (UbD) in EFL Teaching: Teachers' Professional Development and Students' Achievement

    ERIC Educational Resources Information Center

    Yurtseven, Nihal; Altun, Sertel

    2017-01-01

    Concepts such as teachers' professional development and students' achievement act as the driving force for the development of each in a causal relationship in EFL teaching, as in many other disciplines. The purpose of this study is to investigate the change Understanding by Design (UbD) made on teachers' professional development and students'…

  18. Quasi-experimental study designs series-paper 1: introduction: two historical lineages.

    PubMed

    Bärnighausen, Till; Røttingen, John-Arne; Rockers, Peter; Shemilt, Ian; Tugwell, Peter

    2017-09-01

    The objective of this study was to contrast the historical development of experiments and quasi-experiments and provide the motivation for a journal series on quasi-experimental designs in health research. A short historical narrative, with concrete examples, and arguments based on an understanding of the practice of health research and evidence synthesis. Health research has played a key role in developing today's gold standard for causal inference-the randomized controlled multiply blinded trial. Historically, allocation approaches developed from convenience and purposive allocation to alternate and, finally, to random allocation. This development was motivated both by concerns for manipulation in allocation as well as statistical and theoretical developments demonstrating the power of randomization in creating counterfactuals for causal inference. In contrast to the sequential development of experiments, quasi-experiments originated at very different points in time, from very different scientific perspectives, and with frequent and long interruptions in their methodological development. Health researchers have only recently started to recognize the value of quasi-experiments for generating novel insights on causal relationships. While quasi-experiments are unlikely to replace experiments in generating the efficacy and safety evidence required for clinical guidelines and regulatory approval of medical technologies, quasi-experiments can play an important role in establishing the effectiveness of health care practice, programs, and policies. The papers in this series describe and discuss a range of important issues in utilizing quasi-experimental designs for primary research and quasi-experimental results for evidence synthesis. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. HIV infection in the etiology of lung cancer: confounding, causality, and consequences.

    PubMed

    Kirk, Gregory D; Merlo, Christian A

    2011-06-01

    Persons infected with HIV have an elevated risk of lung cancer, but whether the increase simply reflects a higher smoking prevalence continues to be debated. This review summarizes existing data on the association of HIV infection and lung cancer, with particular attention to study design and adjustment for cigarette smoking. Potential mechanisms by which HIV infection may lead to lung cancer are discussed. Finally, irrespective of causality and mechanisms, lung cancer represents an important and growing problem confronting HIV-infected patients and their providers. Substantial efforts are needed to promote smoking cessation and to control lung cancer among HIV-infected populations.

  20. Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

    PubMed

    Corbin, Laura J; Tan, Vanessa Y; Hughes, David A; Wade, Kaitlin H; Paul, Dirk S; Tansey, Katherine E; Butcher, Frances; Dudbridge, Frank; Howson, Joanna M; Jallow, Momodou W; John, Catherine; Kingston, Nathalie; Lindgren, Cecilia M; O'Donavan, Michael; O'Rahilly, Stephen; Owen, Michael J; Palmer, Colin N A; Pearson, Ewan R; Scott, Robert A; van Heel, David A; Whittaker, John; Frayling, Tim; Tobin, Martin D; Wain, Louise V; Smith, George Davey; Evans, David M; Karpe, Fredrik; McCarthy, Mark I; Danesh, John; Franks, Paul W; Timpson, Nicholas J

    2018-02-19

    Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.

  1. Effect of change in coding rules on recording diabetes in hospital administrative datasets.

    PubMed

    Assareh, Hassan; Achat, Helen M; Guevarra, Veth M; Stubbs, Joanne M

    2016-10-01

    During 2008-2011 Australian Coding Standards mandated a causal relationship between diabetes and inpatient care as a criterion for recording diabetes as a comorbidity in hospital administrative datasets. We aim to measure the effect of the causality mandate on recorded diabetes and associated inter-hospital variations. For patients with diabetes, all admissions between 2004 and 2013 to all New South Wales acute public hospitals were investigated. Poisson mixed models were employed to derive adjusted rates and variations. The non-recorded diabetes incidence rate was 20.7%. The causality mandate increased the incidence rate four fold during the change period, 2008-2011, compared to the pre- or post-change periods (32.5% vs 8.4% and 6.9%). The inter-hospital variation was also higher, with twice the difference in the non-recorded rate between hospitals with the highest and lowest rates (50% vs 24% and 27% risk gap). The variation decreased during the change period (29%), while the rate continued to rise (53%). Admission characteristics accounted for over 44% of the variation compared with at most two per cent attributable to patient or hospital characteristics. Contributing characteristics explained less of the variation within the change period compared to pre- or post-change (46% vs 58% and 53%). Hospital relative performance was not constant over time. The causality mandate substantially increased the non-recorded diabetes rate and associated inter-hospital variation. Longitudinal accumulation of clinical information at the patient level, and the development of appropriate adoption protocols to achieve comprehensive and timely implementation of coding changes are essential to supporting the integrity of hospital administrative datasets. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  2. A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard

    PubMed Central

    Azadmanjir, Zahra; Torabi, Mashallah; Safdari, Reza; Bayat, Maryam; Golmahi, Fatemeh

    2015-01-01

    Introduction: management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard. Methods: the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified. Results: the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers. Conclusion: the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process. PMID:26483593

  3. Tests of a Direct Effect of Childhood Abuse on Adult Borderline Personality Disorder Traits: A Longitudinal Discordant Twin Design

    PubMed Central

    Bornovalova, Marina A.; Huibregtse, Brooke M.; Hicks, Brian M.; Keyes, Margaret; McGue, Matt; Iacono, William

    2012-01-01

    We used a longitudinal twin design to examine the causal association between sexual, emotional, and physical abuse in childhood (before age 18) and borderline personality disorder (BPD) traits at age 24 using a discordant twin design and biometric modeling. Additionally, we examined the mediating and moderating effects of symptoms of childhood externalizing and internalizing disorders on the link between childhood abuse and BPD traits. Although childhood abuse, BPD traits, and internalizing and externalizing symptoms were all correlated, the discordant twin analyses and biometric modeling showed little to no evidence that consistent with a causal effect of childhood abuse on BPD traits. Instead, our results indicate that the association between childhood abuse and BPD traits stems from common genetic influences that, in some cases, also overlap with internalizing and externalizing disorders. These findings are inconsistent with the widely held assumption that childhood abuse causes BPD, and suggests that BPD traits in adulthood are better accounted for by heritable vulnerabilities to internalizing and externalizing disorders. PMID:22686871

  4. Chronometric Electrical Stimulation of Right Inferior Frontal Cortex Increases Motor Braking

    PubMed Central

    Conner, Christopher R.; Aron, Adam R.; Tandon, Nitin

    2013-01-01

    The right inferior frontal cortex (rIFC) is important for stopping responses. Recent research shows that it is also activated when response emission is slowed down when stopping is anticipated. This suggests that rIFC also functions as a goal-driven brake. Here, we investigated the causal role of rIFC in goal-driven braking by using computer-controlled, event-related (chronometric), direct electrical stimulation (DES). We compared the effects of rIFC stimulation on trials in which responses were made in the presence versus absence of a stopping-goal (“Maybe Stop” [MS] vs “No Stop” [NS]). We show that DES of rIFC slowed down responses (compared with control-site stimulation) and that rIFC stimulation induced more slowing when motor braking was required (MS) compared with when it was not (NS). Our results strongly support a causal role of a rIFC-based network in inhibitory motor control. Importantly, the results extend this causal role beyond externally driven stopping to goal-driven inhibitory control, which is a richer model of human self-control. These results also provide the first demonstration of double-blind chronometric DES of human prefrontal cortex, and suggest that—in the case of rIFC—this could lead to augmentation of motor braking. PMID:24336725

  5. A new quantitative approach to measure perceived work-related stress in Italian employees.

    PubMed

    Cevenini, Gabriele; Fratini, Ilaria; Gambassi, Roberto

    2012-09-01

    We propose a method for a reliable quantitative measure of subjectively perceived occupational stress applicable in any company to enhance occupational safety and psychosocial health, to enable precise prevention policies and intervention and to improve work quality and efficiency. A suitable questionnaire was telephonically administered to a stratified sample of the whole Italian population of employees. Combined multivariate statistical methods, including principal component, cluster and discriminant analyses, were used to identify risk factors and to design a causal model for understanding work-related stress. The model explained the causal links of stress through employee perception of imbalance between job demands and resources for responding appropriately, by supplying a reliable U-shaped nonlinear stress index, expressed in terms of values of human systolic arterial pressure. Low, intermediate and high values indicated demotivation (or inefficiency), well-being and distress, respectively. Costs for stress-dependent productivity shortcomings were estimated to about 3.7% of national income from employment. The method identified useful structured information able to supply a simple and precise interpretation of employees' well-being and stress risk. Results could be compared with estimated national benchmarks to enable targeted intervention strategies to protect the health and safety of workers, and to reduce unproductive costs for firms.

  6. Transcutaneous vagus nerve stimulation (tVNS) enhances divergent thinking.

    PubMed

    Colzato, Lorenza S; Ritter, Simone M; Steenbergen, Laura

    2018-03-01

    Creativity is one of the most important cognitive skills in our complex and fast-changing world. Previous correlative evidence showed that gamma-aminobutyric acid (GABA) is involved in divergent but not convergent thinking. In the current study, a placebo/sham-controlled, randomized between-group design was used to test a causal relation between vagus nerve and creativity. We employed transcutaneous vagus nerve stimulation (tVNS), a novel non-invasive brain stimulation technique to stimulate afferent fibers of the vagus nerve and speculated to increase GABA levels, in 80 healthy young volunteers. Creative performance was assessed in terms of divergent thinking (Alternate Uses Task) and convergent thinking tasks (Remote Associates Test, Creative Problem Solving Task, Idea Selection Task). Results demonstrate active tVNS, compared to sham stimulation, enhanced divergent thinking. Bayesian analysis reported the data to be inconclusive regarding a possible effect of tVNS on convergent thinking. Therefore, our findings corroborate the idea that the vagus nerve is causally involved in creative performance. Even thought we did not directly measure GABA levels, our results suggest that GABA (likely to be increased in active tVNS condition) supports the ability to select among competing options in high selection demand (divergent thinking) but not in low selection demand (convergent thinking). Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  7. Perceiving and Confronting Sexism: The Causal Role of Gender Identity Salience.

    PubMed

    Wang, Katie; Dovidio, John F

    2017-03-01

    Although many researchers have explored the relations among gender identification, discriminatory attributions, and intentions to challenge discrimination, few have examined the causal impact of gender identity salience on women's actual responses to a sexist encounter. In the current study, we addressed this question by experimentally manipulating the salience of gender identity and assessing its impact on women's decision to confront a sexist comment in a simulated online interaction. Female participants ( N = 114) were randomly assigned to complete a short measure of either personal or collective self-esteem, which was designed to increase the salience of personal versus gender identity. They were then given the opportunity to confront a male interaction partner who expressed sexist views. Compared to those who were primed to focus on their personal identity, participants who were primed to focus on their gender identity perceived the interaction partner's remarks as more sexist and were more likely to engage in confrontation. By highlighting the powerful role of subtle contextual cues in shaping women's perceptions of, and responses to, sexism, our findings have important implications for the understanding of gender identity salience as an antecedent of prejudice confrontation. Online slides for instructors who want to use this article for teaching are available on PWQ's website at http://journals.sagepub.com/page/pwq/suppl/index.

  8. The influence of anticipated pride and guilt on pro-environmental decision making

    PubMed Central

    Zaval, Lisa; Weber, Elke U.; Markowitz, Ezra M.

    2017-01-01

    The present research explores the relationship between anticipated emotions and pro-environmental decision making comparing two differently valenced emotions: anticipated pride and guilt. In an experimental design, we examined the causal effects of anticipated pride versus guilt on pro-environmental decision making and behavioral intentions by making anticipated emotions (i.e. pride and guilt) salient just prior to asking participants to make a series of environmental decisions. We find evidence that anticipating one’s positive future emotional state from green action just prior to making an environmental decision leads to higher pro-environmental behavioral intentions compared to anticipating one’s negative emotional state from inaction. This finding suggests a rethinking in the domain of environmental and climate change messaging, which has traditionally favored inducing negative emotions such as guilt to promote pro-environmental action. Furthermore, exploratory results comparing anticipated pride and guilt inductions to baseline behavior point toward a reactance eliciting effect of anticipated guilt. PMID:29190758

  9. Exploring the relationship between child physical abuse and adult dating violence using a causal inference approach in an emerging adult population in South Korea.

    PubMed

    Jennings, Wesley G; Park, MiRang; Richards, Tara N; Tomsich, Elizabeth; Gover, Angela; Powers, Ráchael A

    2014-12-01

    Child maltreatment is one of the most commonly examined risk factors for violence in dating relationships. Often referred to as the intergenerational transmission of violence or cycle of violence, a fair amount of research suggests that experiencing abuse during childhood significantly increases the likelihood of involvement in violent relationships later, but these conclusions are primarily based on correlational research designs. Furthermore, the majority of research linking childhood maltreatment and dating violence has focused on samples of young people from the United States. Considering these limitations, the current study uses a rigorous, propensity score matching approach to estimate the causal effect of experiencing child physical abuse on adult dating violence among a large sample of South Korean emerging adults. Results indicate that the link between child physical abuse and adult dating violence is spurious rather than causal. Study limitations and implications are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Lending to Parents and Insuring Children: Is There a Role for Microcredit in Complementing Health Insurance in Rural China?

    PubMed

    You, Jing

    2016-05-01

    This paper assesses the causal impact on child health of borrowing formal microcredit for Chinese rural households by exploiting a panel dataset (2000 and 2004) in a poor northwest province. Endogenous borrowing is controlled for in a dynamic regression-discontinuity design creating a quasi-experimental environment for causal inferences. There is causal relationship running from formal microcredit to improved child health in the short term, while past borrowing behaviour has no protracted impact on subsequent child health outcomes. Moreover, formal microcredit appears to be a complement to health insurance in improving child health through two mechanisms-it enhances affordability for out-of-pocket health care expenditure and helps buffer consumption against adverse health shocks and financial risk incurred by current health insurance arrangements. Government efforts in expanding health insurance for rural households would be more likely to achieve its optimal goals of improving child health outcomes if combined with sufficient access to formal microcredit. Copyright © 2015 John Wiley & Sons, Ltd.

  11. Alcohol Use Predicts Sexual Decision-Making: A Systematic Review and Meta-Analysis of the Experimental Literature

    PubMed Central

    Scott-Sheldon, Lori A. J.; Carey, Kate B.; Cunningham, Karlene; Johnson, Blair T.; Carey, Michael P.

    2015-01-01

    Alcohol is associated with HIV and other sexually transmitted infections through increased sexual risk-taking behavior. Establishing a causal link between alcohol and sexual behavior has been challenging due to methodological limitations (e.g., reliance on cross-sectional designs). Experimental methods can be used to establish causality. The purpose of this meta-analysis was to evaluate the effects of alcohol consumption on unprotected sex intentions. We searched electronic bibliographic databases for records with relevant keywords; 26 manuscripts (k = 30 studies) met inclusion criteria. Results indicate that alcohol consumption is associated with greater intentions to engage in unprotected sex (d+s = 0.24, 0.35). The effect of alcohol on unprotected sex intentions was greater when sexual arousal was heightened. Alcohol consumption is causally linked to theoretical antecedents of sexual risk behavior, consistent with the alcohol myopia model. Addressing alcohol consumption as a determinant of unprotected sex intentions may lead to more effective HIV interventions. PMID:26080689

  12. Understanding social forces involved in diabetes outcomes: a systems science approach to quality-of-life research.

    PubMed

    Lounsbury, David W; Hirsch, Gary B; Vega, Chawntel; Schwartz, Carolyn E

    2014-04-01

    The field of quality-of-life (QOL) research would benefit from learning about and integrating systems science approaches that model how social forces interact dynamically with health and affect the course of chronic illnesses. Our purpose is to describe the systems science mindset and to illustrate the utility of a system dynamics approach to promoting QOL research in chronic disease, using diabetes as an example. We build a series of causal loop diagrams incrementally, introducing new variables and their dynamic relationships at each stage. These causal loop diagrams demonstrate how a common set of relationships among these variables can generate different disease and QOL trajectories for people with diabetes and also lead to a consideration of non-clinical (psychosocial and behavioral) factors that can have implications for program design and policy formulation. The policy implications of the causal loop diagrams are discussed, and empirical next steps to validate the diagrams and quantify the relationships are described.

  13. Distinguishing Mediational Models and Analyses in Clinical Psychology: Atemporal Associations Do Not Imply Causation.

    PubMed

    Winer, E Samuel; Cervone, Daniel; Bryant, Jessica; McKinney, Cliff; Liu, Richard T; Nadorff, Michael R

    2016-09-01

    A popular way to attempt to discern causality in clinical psychology is through mediation analysis. However, mediation analysis is sometimes applied to research questions in clinical psychology when inferring causality is impossible. This practice may soon increase with new, readily available, and easy-to-use statistical advances. Thus, we here provide a heuristic to remind clinical psychological scientists of the assumptions of mediation analyses. We describe recent statistical advances and unpack assumptions of causality in mediation, underscoring the importance of time in understanding mediational hypotheses and analyses in clinical psychology. Example analyses demonstrate that statistical mediation can occur despite theoretical mediation being improbable. We propose a delineation of mediational effects derived from cross-sectional designs into the terms temporal and atemporal associations to emphasize time in conceptualizing process models in clinical psychology. The general implications for mediational hypotheses and the temporal frameworks from within which they may be drawn are discussed. © 2016 Wiley Periodicals, Inc.

  14. Causal Relationships between the Psychological Acceptance Process of Athletic Injury and Athletic Rehabilitation Behavior

    PubMed Central

    Tatsumi, Tomonori; Takenouchi, Takashi

    2014-01-01

    [Purpose] The purpose of this study was to examine the causal relationships between the psychological acceptance process of athletic injury and athletic-rehabilitation behavior. [Subjects] One hundred forty-four athletes who had injury experiences participated in this study, and 133 (mean age = 20.21 years, SD = 1.07; mean weeks without playing sports = 7.97 weeks, SD = 11.26) of them provided valid questionnaire responses which were subjected to analysis. [Methods] The subjects were asked to answer our originally designed questionnaire, the Psychosocial Recovery Factor Scale (PSRF-S), and two other pre-existing scales, the Athletic Injury Psychological Acceptance Scale and the Athletic-Rehabilitation Dedication Scale. [Results] The results of factor analysis indicate “emotional stability”, “social competence in the team”, “temporal perspective”, and “communication with the teammates” are factors of the PSRF-S. Lastly, the causal model in which psychosocial recovery factors are mediated by psychological acceptance of athletic injury, and influence on rehabilitation behaviors, was examined using structural equation modeling (SEM). The results of SEM indicate that the factors of emotional stability and temporal perspective are mediated by the psychological acceptance of the injury, which positively influences athletic-rehabilitation dedication. [Conclusion] The causal model was confirmed to be valid. PMID:25202190

  15. Effect of science teaching on the young child's concept of piagetian physical causality: Animism and dynamism

    NASA Astrophysics Data System (ADS)

    Wolfinger, Donna M.

    The purpose of this research was to determine whether the young child's understanding of physical causality is affected by school science instruction. Sixty-four subjects, four and one-half through seven years of age, received 300 min of instruction designed to affect the subject's conception of causality as reflected in animism and dynamism. Instruction took place for 30 min per day on ten successive school days. Pretesting was done to allow a stratified random sample to be based on vocabulary level and developmental stage as well as on age and gender. Post-testing consisted of testing of developmental level and level within the causal relations of animism and dynamism. Significant differences (1.05 level) were found between the experimental and control groups for animism. Within the experimental group, males differed significantly (1.001 level) from females. The elimination of animism appeared to have occurred. For dynamism, significant differences (0.05 level) were found only between concrete operational subjects in the experimental and control groups, indicating a concrete level of operations was necessary if dynamism was to be affected. However, a review of interview protocols indicated that subjects classified as nonanimistic had learned to apply a definition rather than to think in a nonanimistic manner.

  16. Predictions of the causal entropic principle for environmental conditions of the universe

    NASA Astrophysics Data System (ADS)

    Cline, James M.; Frey, Andrew R.; Holder, Gilbert

    2008-03-01

    The causal entropic principle has been proposed as an alternative to the anthropic principle for understanding the magnitude of the cosmological constant. In this approach, the probability to create observers is assumed to be proportional to the entropy production ΔS in a maximal causally connected region—the causal diamond. We improve on the original treatment by better quantifying the entropy production due to stars, using an analytic model for the star formation history which accurately accounts for changes in cosmological parameters. We calculate the dependence of ΔS on the density contrast Q=δρ/ρ, and find that our universe is much closer to the most probable value of Q than in the usual anthropic approach and that probabilities are relatively weakly dependent on this amplitude. In addition, we make first estimates of the dependence of ΔS on the baryon fraction and overall matter abundance. Finally, we also explore the possibility that decays of dark matter, suggested by various observed gamma ray excesses, might produce a comparable amount of entropy to stars.

  17. Actors, observers, and causal attributions of homelessness: Differences in attribution for the causes of homelessness among domiciled and homeless people in Madrid (Spain).

    PubMed

    Vázquez, José Juan; Panadero, Sonia; Zúñiga, Claudia

    2017-01-01

    The study analyzes the differences in causal attributions of homelessness and attributions of responsibility among the members of 3 groups: homeless group, consisting of a representative sample of homeless people in Madrid, Spain (n = 188); domiciled service-users group, consisting of people at risk of homelessness (n = 164); and domiciled nonservice-users group, consisting of people at no imminent risk of homelessness (n = 180). The domiciled service-users group and domiciled nonservice-users group were matched to the homeless group or sex, age, and nationality. The article also analyzes homeless people's causal attributions as regards their own situation. The results show that compared with the domiciled nonservice-users group, a higher percentage of members of the homeless group and domiciled service-users group attributed homelessness to individualistic causes and they blamed homeless people for their situation to a greater extent. The results also show that there was no "actor-observer bias" in causal attributions for homelessness in Madrid. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  18. T. rex, the Crater of Doom, and the Nature of Scientific Discovery

    NASA Astrophysics Data System (ADS)

    Lawson, Antone

    Working from the 1970s to the early 1990s, Walter Alvarez and his research team sought the cause of the mass extinction that claimed the dinosaurs 65 million years ago. The present paper discusses that research in terms of eight puzzling observations, eight episodes of hypothetico-predictive reasoning, enumerative induction, and Jung's interrogative theory of scientific discovery. The Alvarez case history paints scientific discovery as a process in which causal questions are raised and answered through the creative use of analogical reasoning followed by an equally creative process of hypothesis testing in which predicted and observed results are compared. According to this account, puzzling observations, causal hypotheses, and imagined tests drive investigations and the search for evidence. Two implications follow. The first concerns the education of new scientists and science education researchers and the need to more clearly differentiate hypotheses from predictions in the research process. The second concerns standard science classroom instruction that should more frequently engage students in open inquiries that raise causal questions and encourage the generation of alternative causal hypotheses, which can then be explicitly tested in a hypothetico-predictive fashion.

  19. Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

    ERIC Educational Resources Information Center

    Johnson, Samuel G. B.; Ahn, Woo-kyoung

    2015-01-01

    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge--an interconnected causal "network," where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms--causal "islands"--such that events in different…

  20. An Ex-Post Facto Examination of Relationships among the Developmental Designs Professional Development Model/Classroom Management Approach, School Leadership, Climate, Student Achievement, Attendance, and Behavior in High Poverty, Middle Grades Schools

    ERIC Educational Resources Information Center

    Hough, David L.; Schmitt, Vicki L.

    2011-01-01

    This study reports finding from an ex post facto causal-comparison study utilizing data from a multifaceted program evaluation of a professional development approach to classroom management known as Development Designs 1 and Developmental Designs 2 (DD1 & D2). Data from this program evaluation indicate that teachers implement a number of classroom…

  1. Impact of National Ambient Air Quality Standards Nonattainment Designations on Particulate Pollution and Health.

    PubMed

    Zigler, Corwin M; Choirat, Christine; Dominici, Francesca

    2018-03-01

    Despite dramatic air quality improvement in the United States over the past decades, recent years have brought renewed scrutiny and uncertainty surrounding the effectiveness of specific regulatory programs for continuing to improve air quality and public health outcomes. We employ causal inference methods and a spatial hierarchical regression model to characterize the extent to which a designation of "nonattainment" with the 1997 National Ambient Air Quality Standard for ambient fine particulate matter (PM2.5) in 2005 causally affected ambient PM2.5 and health outcomes among over 10 million Medicare beneficiaries in the Eastern United States in 2009-2012. We found that, on average across all retained study locations, reductions in ambient PM2.5 and Medicare health outcomes could not be conclusively attributed to the nonattainment designations against the backdrop of other regional strategies that impacted the entire Eastern United States. A more targeted principal stratification analysis indicates substantial health impacts of the nonattainment designations among the subset of areas where the designations are estimated to have actually reduced ambient PM2.5 beyond levels achieved by regional measures, with noteworthy reductions in all-cause mortality, chronic obstructive pulmonary disorder, heart failure, ischemic heart disease, and respiratory tract infections. These findings provide targeted evidence of the effectiveness of local control measures after nonattainment designations for the 1997 PM2.5 air quality standard.

  2. Self-organizing map analysis using multivariate data from theophylline tablets predicted by a thin-plate spline interpolation.

    PubMed

    Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Yamamoto, Rie; Takayama, Kozo

    2013-01-01

    The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared based on a standard formulation. The tensile strength, disintegration time, and stability of these variables were measured as response variables. These responses were predicted quantitatively based on nonlinear TPS. A large amount of data on these tablets was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the tablets were classified into several distinct clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and tablet characteristics. The results of this study suggest that increasing the proportion of microcrystalline cellulose (MCC) improved the tensile strength and the stability of tensile strength of these theophylline tablets. In addition, the proportion of MCC has an optimum value for disintegration time and stability of disintegration. Increasing the proportion of magnesium stearate extended disintegration time. Increasing the compression force improved tensile strength, but degraded the stability of disintegration. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulations.

  3. A Children of Twins Study of parental divorce and offspring psychopathology.

    PubMed

    D'Onofrio, Brian M; Turkheimer, Eric; Emery, Robert E; Maes, Hermine H; Silberg, Judy; Eaves, Lindon J

    2007-07-01

    Although parental divorce is associated with increased substance use and internalizing problems, experiencing the separation of one's parents may not cause these outcomes. The relations may be due to genetic or environmental selection factors, characteristics that lead to both marital separation and offspring functioning. We used the Children of Twins (CoT) Design to explore whether unmeasured genetic or environmental factors related to the twin parent, and measured characteristics of both parents, account for the association between parental divorce and offspring substance use and internalizing problems. The association between parental divorce and offspring substance use problems remained robust when controlling for genetic and environmental risk from the twin parent associated with parental divorce, and measured characteristics of both parents. The results do not prove, but are consistent with, a causal connection. In contrast, the analyses suggest that shared genetic liability in parents and their offspring accounts for the increased risk of internalizing problems in adult offspring from divorced families. The study illustrates that unmeasured genetic and environmental selection factors must be considered when studying parental divorce. In explaining associations between parental divorce and young-adult adjustment, our evidence suggests that selection versus causal mechanisms may operate differently for substance abuse (a causal relation) and internalizing problems (an artifact of selection). The CoT design only controls for the genetic and environmental characteristics of one parent; thus, additional genetically informed analyses are needed.

  4. Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data

    PubMed Central

    Havlicek, Martin; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

    2015-01-01

    Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided. PMID:20561919

  5. Evaluation of naranjo adverse drug reactions probability scale in causality assessment of drug-induced liver injury.

    PubMed

    García-Cortés, M; Lucena, M I; Pachkoria, K; Borraz, Y; Hidalgo, R; Andrade, R J

    2008-05-01

    Causality assessment in hepatotoxicity is challenging. The current standard liver-specific Council for International Organizations of Medical Sciences/Roussel Uclaf Causality Assessment Method scale is complex and difficult to implement in daily practice. The Naranjo Adverse Drug Reactions Probability Scale is a simple and widely used nonspecific scale, which has not been specifically evaluated in drug-induced liver injury. To compare the Naranjo method with the standard liver-specific Council for International Organizations of Medical Sciences/Roussel Uclaf Causality Assessment Method scale in evaluating the accuracy and reproducibility of Naranjo Adverse Drug Reactions Probability Scale in the diagnosis of hepatotoxicity. Two hundred and twenty-five cases of suspected hepatotoxicity submitted to a national registry were evaluated by two independent observers and assessed for between-observer and between-scale differences using percentages of agreement and the weighted kappa (kappa(w)) test. A total of 249 ratings were generated. Between-observer agreement was 45% with a kappa(w) value of 0.17 for the Naranjo Adverse Drug Reactions Probability Scale, while there was a higher agreement when using the Council for International Organizations of Medical Sciences/Roussel Uclaf Causality Assessment Method scale (72%, kappa(w): 0.71). Concordance between the two scales was 24% (kappa(w): 0.15). The Naranjo Adverse Drug Reactions Probability Scale had low sensitivity (54%) and poor negative predictive value (29%) and showed a limited capability to distinguish between adjacent categories of probability. The Naranjo scale lacks validity and reproducibility in the attribution of causality in hepatotoxicity.

  6. IDEF3 formalization report

    NASA Technical Reports Server (NTRS)

    Menzel, Christopher; Mayer, Richard J.; Edwards, Douglas D.

    1991-01-01

    The Process Description Capture Method (IDEF3) is one of several Integrated Computer-Aided Manufacturing (ICAM) DEFinition methods developed by the Air Force to support systems engineering activities, and in particular, to support information systems development. These methods have evolved as a distillation of 'good practice' experience by information system developers and are designed to raise the performance level of the novice practitioner to one comparable with that of an expert. IDEF3 is meant to serve as a knowledge acquisition and requirements definition tool that structures the user's understanding of how a given process, event, or system works around process descriptions. A special purpose graphical language accompanying the method serves to highlight temporal precedence and causality relationships relative to the process or event being described.

  7. The efficacy of student-centered instruction in supporting science learning.

    PubMed

    Granger, E M; Bevis, T H; Saka, Y; Southerland, S A; Sampson, V; Tate, R L

    2012-10-05

    Transforming science learning through student-centered instruction that engages students in a variety of scientific practices is central to national science-teaching reform efforts. Our study employed a large-scale, randomized-cluster experimental design to compare the effects of student-centered and teacher-centered approaches on elementary school students' understanding of space-science concepts. Data included measures of student characteristics and learning and teacher characteristics and fidelity to the instructional approach. Results reveal that learning outcomes were higher for students enrolled in classrooms engaging in scientific practices through a student-centered approach; two moderators were identified. A statistical search for potential causal mechanisms for the observed outcomes uncovered two potential mediators: students' understanding of models and evidence and the self-efficacy of teachers.

  8. Final Report for Dynamic Models for Causal Analysis of Panel Data. Methods for Temporal Analysis. Part I, Chapter 1.

    ERIC Educational Resources Information Center

    Hannan, Michael T.; Tuma, Nancy Brandon

    This document is part of a series of chapters described in SO 011 759. Working from the premise that temporal analysis is indispensable for the study of change, the document examines major alternatives in research design of this nature. Five sections focus on the features, advantages, and limitations of temporal analysis. Four designs which…

  9. Associations between childhood ADHD, gender, and adolescent alcohol and marijuana involvement: A causally informative design.

    PubMed

    Elkins, Irene J; Saunders, Gretchen R B; Malone, Stephen M; Keyes, Margaret A; McGue, Matt; Iacono, William G

    2018-03-01

    We report whether the etiology underlying associations of childhood ADHD with adolescent alcohol and marijuana involvement is consistent with causal relationships or shared predispositions, and whether it differs by gender. In three population-based twin samples (N = 3762; 64% monozygotic), including one oversampling females with ADHD, regressions were conducted with childhood inattentive or hyperactive-impulsive symptoms predicting alcohol and marijuana outcomes by age 17. To determine whether ADHD effects were consistent with causality, twin difference analyses divided effects into those shared between twins in the pair and those differing within pairs. Adolescents with more severe childhood ADHD were more likely to initiate alcohol and marijuana use earlier, escalate to frequent or heavy use, and develop symptoms. While risks were similar across genders, females with more hyperactivity-impulsivity had higher alcohol consumption and progressed further toward daily marijuana use than did males. Monozygotic twins with more severe ADHD than their co-twins did not differ significantly on alcohol or marijuana outcomes, however, suggesting a non-causal relationship. When co-occurring use of other substances and conduct/oppositional defiant disorders were considered, hyperactivity-impulsivity remained significantly associated with both substances, as did inattention with marijuana, but not alcohol. Childhood ADHD predicts when alcohol and marijuana use are initiated and how quickly use escalates. Shared familial environment and genetics, rather than causal influences, primarily account for these associations. Stronger relationships between hyperactivity-impulsivity and heavy drinking/frequent marijuana use among adolescent females than males, as well as the greater salience of inattention for marijuana, merit further investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Disentangling the causal relationships between work-home interference and employee health.

    PubMed

    van Hooff, Madelon L M; Geurts, Sabine A E; Taris, Toon W; Kompier, Michiel A J; Dikkers, Josje S E; Houtman, Irene L D; van den Heuvel, Floor M M

    2005-02-01

    The present study was designed to investigate the causal relationships between (time- and strain-based) work-home interference and employee health. The effort-recovery theory provided the theoretical basis for this study. Two-phase longitudinal data (with a 1-year time lag) were gathered from 730 Dutch police officers to test the following hypotheses with structural equation modeling: (i) work-home interference predicts health deterioration, (ii) health complaints precede increased levels of such interference, and (iii) both processes operate. The relationship between stable and changed levels of work-home interference across time and their relationships with the course of health were tested with a group-by-time analysis of variance. Four subgroups were created that differed in starting point and the development of work-home interference across time. The normal causal model, in which strain-based (but not time-based) work-home interference was longitudinally related to increased health complaints 1 year later, fit the data well and significantly better than the reversed causal model. Although the reciprocal model also provided a good fit, it was less parsimonious than the normal causal model. In addition, both an increment in (strain-based) work-home interference across time and a long-lasting experience of high (strain-based) work-home interference were associated with a deterioration in health. It was concluded that (strain-based) work-home interference acts as a precursor of health impairment and that different patterns of (strain-based) work-home interference across time are related to different health courses. Particularly long-term experience of (strain-based) work-home interference seems responsible for an accumulation of health complaints.

  11. Quantifying the causal effects of 20mph zones on road casualties in London via doubly robust estimation.

    PubMed

    Li, Haojie; Graham, Daniel J

    2016-08-01

    This paper estimates the causal effect of 20mph zones on road casualties in London. Potential confounders in the key relationship of interest are included within outcome regression and propensity score models, and the models are then combined to form a doubly robust estimator. A total of 234 treated zones and 2844 potential control zones are included in the data sample. The propensity score model is used to select a viable control group which has common support in the covariate distributions. We compare the doubly robust estimates with those obtained using three other methods: inverse probability weighting, regression adjustment, and propensity score matching. The results indicate that 20mph zones have had a significant causal impact on road casualty reduction in both absolute and proportional terms. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Semmelweis's methodology from the modern stand-point: intervention studies and causal ontology.

    PubMed

    Persson, Johannes

    2009-09-01

    Semmelweis's work predates the discovery of the power of randomization in medicine by almost a century. Although Semmelweis would not have consciously used a randomized controlled trial (RCT), some features of his material-the allocation of patients to the first and second clinics-did involve what was in fact a randomization, though this was not realised at the time. This article begins by explaining why Semmelweis's methodology, nevertheless, did not amount to the use of a RCT. It then shows why it is descriptively and normatively interesting to compare what he did with the modern approach using RCTs. The argumentation centres on causal inferences and the contrast between Semmelweis's causal concept and that deployed by many advocates of RCTs. It is argued that Semmelweis's approach has implications for matters of explanation and medical practice.

  13. Causal Analysis of Self-tracked Time Series Data Using a Counterfactual Framework for N-of-1 Trials.

    PubMed

    Daza, Eric J

    2018-02-01

    Many of an individual's historically recorded personal measurements vary over time, thereby forming a time series (e.g., wearable-device data, self-tracked fitness or nutrition measurements, regularly monitored clinical events or chronic conditions). Statistical analyses of such n-of-1 (i.e., single-subject) observational studies (N1OSs) can be used to discover possible cause-effect relationships to then self-test in an n-of-1 randomized trial (N1RT). However, a principled way of determining how and when to interpret an N1OS association as a causal effect (e.g., as if randomization had occurred) is needed.Our goal in this paper is to help bridge the methodological gap between risk-factor discovery and N1RT testing by introducing a basic counterfactual framework for N1OS design and personalized causal analysis.We introduce and characterize what we call the average period treatment effect (APTE), i.e., the estimand of interest in an N1RT, and build an analytical framework around it that can accommodate autocorrelation and time trends in the outcome, effect carryover from previous treatment periods, and slow onset or decay of the effect. The APTE is loosely defined as a contrast (e.g., difference, ratio) of averages of potential outcomes the individual can theoretically experience under different treatment levels during a given treatment period. To illustrate the utility of our framework for APTE discovery and estimation, two common causal inference methods are specified within the N1OS context. We then apply the framework and methods to search for estimable and interpretable APTEs using six years of the author's self-tracked weight and exercise data, and report both the preliminary findings and the challenges we faced in conducting N1OS causal discovery.Causal analysis of an individual's time series data can be facilitated by an N1RT counterfactual framework. However, for inference to be valid, the veracity of certain key assumptions must be assessed critically, and the hypothesized causal models must be interpretable and meaningful. Schattauer GmbH.

  14. Final Technical Report on Quantifying Dependability Attributes of Software Based Safety Critical Instrumentation and Control Systems in Nuclear Power Plants

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Smidts, Carol; Huang, Funqun; Li, Boyuan

    With the current transition from analog to digital instrumentation and control systems in nuclear power plants, the number and variety of software-based systems have significantly increased. The sophisticated nature and increasing complexity of software raises trust in these systems as a significant challenge. The trust placed in a software system is typically termed software dependability. Software dependability analysis faces uncommon challenges since software systems’ characteristics differ from those of hardware systems. The lack of systematic science-based methods for quantifying the dependability attributes in software-based instrumentation as well as control systems in safety critical applications has proved itself to be amore » significant inhibitor to the expanded use of modern digital technology in the nuclear industry. Dependability refers to the ability of a system to deliver a service that can be trusted. Dependability is commonly considered as a general concept that encompasses different attributes, e.g., reliability, safety, security, availability and maintainability. Dependability research has progressed significantly over the last few decades. For example, various assessment models and/or design approaches have been proposed for software reliability, software availability and software maintainability. Advances have also been made to integrate multiple dependability attributes, e.g., integrating security with other dependability attributes, measuring availability and maintainability, modeling reliability and availability, quantifying reliability and security, exploring the dependencies between security and safety and developing integrated analysis models. However, there is still a lack of understanding of the dependencies between various dependability attributes as a whole and of how such dependencies are formed. To address the need for quantification and give a more objective basis to the review process -- therefore reducing regulatory uncertainty -- measures and methods are needed to assess dependability attributes early on, as well as throughout the life-cycle process of software development. In this research, extensive expert opinion elicitation is used to identify the measures and methods for assessing software dependability. Semi-structured questionnaires were designed to elicit expert knowledge. A new notation system, Causal Mechanism Graphing, was developed to extract and represent such knowledge. The Causal Mechanism Graphs were merged, thus, obtaining the consensus knowledge shared by the domain experts. In this report, we focus on how software contributes to dependability. However, software dependability is not discussed separately from the context of systems or socio-technical systems. Specifically, this report focuses on software dependability, reliability, safety, security, availability, and maintainability. Our research was conducted in the sequence of stages found below. Each stage is further examined in its corresponding chapter. Stage 1 (Chapter 2): Elicitation of causal maps describing the dependencies between dependability attributes. These causal maps were constructed using expert opinion elicitation. This chapter describes the expert opinion elicitation process, the questionnaire design, the causal map construction method and the causal maps obtained. Stage 2 (Chapter 3): Elicitation of the causal map describing the occurrence of the event of interest for each dependability attribute. The causal mechanisms for the “event of interest” were extracted for each of the software dependability attributes. The “event of interest” for a dependability attribute is generally considered to be the “attribute failure”, e.g. security failure. The extraction was based on the analysis of expert elicitation results obtained in Stage 1. Stage 3 (Chapter 4): Identification of relevant measurements. Measures for the “events of interest” and their causal mechanisms were obtained from expert opinion elicitation for each of the software dependability attributes. The measures extracted are presented in this chapter. Stage 4 (Chapter 5): Assessment of the coverage of the causal maps via measures. Coverage was assessed to determine whether the measures obtained were sufficient to quantify software dependability, and what measures are further required. Stage 5 (Chapter 6): Identification of “missing” measures and measurement approaches for concepts not covered. New measures, for concepts that had not been covered sufficiently as determined in Stage 4, were identified using supplementary expert opinion elicitation as well as literature reviews. Stage 6 (Chapter 7): Building of a detailed quantification model based on the causal maps and measurements obtained. Ability to derive such a quantification model shows that the causal models and measurements derived from the previous stages (Stage 1 to Stage 5) can form the technical basis for developing dependability quantification models. Scope restrictions have led us to prioritize this demonstration effort. The demonstration was focused on a critical system, i.e. the reactor protection system. For this system, a ranking of the software dependability attributes by nuclear stakeholders was developed. As expected for this application, the stakeholder ranking identified safety as the most critical attribute to be quantified. A safety quantification model limited to the requirements phase of development was built. Two case studies were conducted for verification. A preliminary control gate for software safety for the requirements stage was proposed and applied to the first case study. The control gate allows a cost effective selection of the duration of the requirements phase.« less

  15. Designing Incentives for Marine Corps Cyber Workforce Retention

    DTIC Science & Technology

    2014-12-01

    transformation, which Burke and Litwin (1992) describe as distinct sets of organizational dynamics that are required for genuine change in...information- security-analysts.htm . Burke, W. Warner, and George H. Litwin . 1992. “A Causal Model of Organizational Performance and Change.” Journal

  16. Comparing the Effects of Elementary Music and Visual Arts Lessons on Standardized Mathematics Test Scores

    ERIC Educational Resources Information Center

    King, Molly Elizabeth

    2016-01-01

    The purpose of this quantitative, causal-comparative study was to compare the effect elementary music and visual arts lessons had on third through sixth grade standardized mathematics test scores. Inferential statistics were used to compare the differences between test scores of students who took in-school, elementary, music instruction during the…

  17. Introductory Statistics Students' Conceptual Understanding of Study Design and Conclusions

    NASA Astrophysics Data System (ADS)

    Fry, Elizabeth Brondos

    Recommended learning goals for students in introductory statistics courses include the ability to recognize and explain the key role of randomness in designing studies and in drawing conclusions from those studies involving generalizations to a population or causal claims (GAISE College Report ASA Revision Committee, 2016). The purpose of this study was to explore introductory statistics students' understanding of the distinct roles that random sampling and random assignment play in study design and the conclusions that can be made from each. A study design unit lasting two and a half weeks was designed and implemented in four sections of an undergraduate introductory statistics course based on modeling and simulation. The research question that this study attempted to answer is: How does introductory statistics students' conceptual understanding of study design and conclusions (in particular, unbiased estimation and establishing causation) change after participating in a learning intervention designed to promote conceptual change in these areas? In order to answer this research question, a forced-choice assessment called the Inferences from Design Assessment (IDEA) was developed as a pretest and posttest, along with two open-ended assignments, a group quiz and a lab assignment. Quantitative analysis of IDEA results and qualitative analysis of the group quiz and lab assignment revealed that overall, students' mastery of study design concepts significantly increased after the unit, and the great majority of students successfully made the appropriate connections between random sampling and generalization, and between random assignment and causal claims. However, a small, but noticeable portion of students continued to demonstrate misunderstandings, such as confusion between random sampling and random assignment.

  18. Comparative Logic Modeling for Policy Analysis: The Case of HIV Testing Policy Change at the Department of Veterans Affairs

    PubMed Central

    Langer, Erika M; Gifford, Allen L; Chan, Kee

    2011-01-01

    Objective Logic models have been used to evaluate policy programs, plan projects, and allocate resources. Logic Modeling for policy analysis has been used rarely in health services research but can be helpful in evaluating the content and rationale of health policies. Comparative Logic Modeling is used here on human immunodeficiency virus (HIV) policy statements from the Department of Veterans Affairs (VA) and Centers for Disease Control and Prevention (CDC). We created visual representations of proposed HIV screening policy components in order to evaluate their structural logic and research-based justifications. Data Sources and Study Design We performed content analysis of VA and CDC HIV testing policy documents in a retrospective case study. Data Collection Using comparative Logic Modeling, we examined the content and primary sources of policy statements by the VA and CDC. We then quantified evidence-based causal inferences within each statement. Principal Findings VA HIV testing policy structure largely replicated that of the CDC guidelines. Despite similar design choices, chosen research citations did not overlap. The agencies used evidence to emphasize different components of the policies. Conclusion Comparative Logic Modeling can be used by health services researchers and policy analysts more generally to evaluate structural differences in health policies and to analyze research-based rationales used by policy makers. PMID:21689094

  19. Income and obesity: what is the direction of the relationship? A systematic review and meta-analysis

    PubMed Central

    Kim, Tae Jun; von dem Knesebeck, Olaf

    2018-01-01

    Objective It was repeatedly shown that lower income is associated with higher risks for subsequent obesity. However, the perspective of a potential reverse causality is often neglected, in which obesity is considered a cause for lower income, when obese people drift into lower-income jobs due to labour–market discrimination and public stigmatisation. This review was performed to explore the direction of the relation between income and obesity by specifically assessing the importance of social causation and reverse causality. Design Systematic review and meta-analysis. Methods A systematic literature search was conducted in January 2017. The databases Medline, PsycINFO, Sociological Abstracts, International Bibliography of Social Sciences and Sociological Index were screened to identify prospective cohort studies with quantitative data on the relation between income and obesity. Meta-analytic methods were applied using random-effect models, and the quality of studies assessed with the Newcastle-Ottawa Scale. Results In total, 21 studies were eligible for meta-analysis. All included studies originated from either the USA (n=16), the UK (n=3) or Canada (n=2). From these, 14 studies on causation and 7 studies on reverse causality were found. Meta-analyses revealed that lower income is associated with subsequent obesity (OR 1.27, 95% CI 1.10 to 1.47; risk ratio 1.52, 95% CI 1.08 to 2.13), though the statistical significance vanished once adjusted for publication bias. Studies on reverse causality indicated a more consistent relation between obesity and subsequent income, even after taking publication bias into account (standardised mean difference −0.15, 95% CI −0.30 to 0.01). Sensitivity analyses implied that the association is influenced by obesity measurement, gender, length of observation and study quality. Conclusions Findings suggest that there is more consistent evidence for reverse causality. Therefore, there is a need to examine reverse causality processes in more detail to understand the relation between income and obesity. PROSPERO registration number 42016041296. PMID:29306894

  20. Automated interviews on clinical case reports to elicit directed acyclic graphs.

    PubMed

    Luciani, Davide; Stefanini, Federico M

    2012-05-01

    Setting up clinical reports within hospital information systems makes it possible to record a variety of clinical presentations. Directed acyclic graphs (Dags) offer a useful way of representing causal relations in clinical problem domains and are at the core of many probabilistic models described in the medical literature, like Bayesian networks. However, medical practitioners are not usually trained to elicit Dag features. Part of the difficulty lies in the application of the concept of direct causality before selecting all the causal variables of interest for a specific patient. We designed an automated interview to tutor medical doctors in the development of Dags to represent their understanding of clinical reports. Medical notions were analyzed to find patterns in medical reasoning that can be followed by algorithms supporting the elicitation of causal Dags. Clinical relevance was defined to help formulate only relevant questions by driving an expert's attention towards variables causally related to nodes already inserted in the graph. Key procedural features of the proposed interview are described by four algorithms. The automated interview comprises questions on medical notions, phrased in medical terms. The first elicitation session produces questions concerning the patient's chief complaints and the outcomes related to diseases serving as diagnostic hypotheses, their observable manifestations and risk factors. The second session focuses on questions that refine the initial causal paths by considering syndromes, dysfunctions, pathogenic anomalies, biases and effect modifiers. A case study concerning a gastro-enterological problem and one dealing with an infected patient illustrate the output produced by the algorithms, depending on the answers provided by the doctor. The proposed elicitation framework is characterized by strong consistency with medical background and by a progressive introduction of relevant medical topics. Revision and testing of the subjectively elicited Dag is performed by matching the collected answers with the evidence included in accepted sources of biomedical knowledge. Copyright © 2011 Elsevier B.V. All rights reserved.

  1. Assessing the Impact of Drug Use and Drug Selling on Violent Offending in a Panel of Delinquent Youth

    PubMed Central

    Phillips, Matthew D.

    2016-01-01

    Despite a vast number of empirical studies arguing for or against a causal relationship between illegal drug use and selling and violent behavior, the debate continues. In part this is due to methodological weaknesses of previous research. Using data from the Rochester Youth Development Study, the current study seeks to improve on prior research designs to allow for a more precise examination of the mechanisms that lead from an individual’s drug use (chiefly, marijuana use in the current sample) and drug selling to violent action. Results will allow for greater confidence in making causal inference regarding a long-standing concern in the discipline. PMID:26889079

  2. Has reducing fine particulate matter and ozone caused reduced mortality rates in the United States?

    PubMed

    Cox, Louis Anthony Tony; Popken, Douglas A

    2015-03-01

    Between 2000 and 2010, air pollutant levels in counties throughout the United States changed significantly, with fine particulate matter (PM2.5) declining over 30% in some counties and ozone (O3) exhibiting large variations from year to year. This history provides an opportunity to compare county-level changes in average annual ambient pollutant levels to corresponding changes in all-cause (AC) and cardiovascular disease (CVD) mortality rates over the course of a decade. Past studies have demonstrated associations and subsequently either interpreted associations causally or relied on subjective judgments to infer causation. This article applies more quantitative methods to assess causality. This article examines data from these "natural experiments" of changing pollutant levels for 483 counties in the 15 most populated US states using quantitative methods for causal hypothesis testing, such as conditional independence and Granger causality tests. We assessed whether changes in historical pollution levels helped to predict and explain changes in CVD and AC mortality rates. A causal relation between pollutant concentrations and AC or CVD mortality rates cannot be inferred from these historical data, although a statistical association between them is well supported. There were no significant positive associations between changes in PM2.5 or O3 levels and corresponding changes in disease mortality rates between 2000 and 2010, nor for shorter time intervals of 1 to 3 years. These findings suggest that predicted substantial human longevity benefits resulting from reducing PM2.5 and O3 may not occur or may be smaller than previously estimated. Our results highlight the potential for heterogeneity in air pollution health effects across regions, and the high potential value of accountability research comparing model-based predictions of health benefits from reducing air pollutants to historical records of what actually occurred. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. In search of causality: a systematic review of the relationship between the built environment and physical activity among adults

    PubMed Central

    2011-01-01

    Background Empirical evidence suggests that an association between the built environment and physical activity exists. This evidence is mostly derived from cross-sectional studies that do not account for other causal explanations such as neighborhood self-selection. Experimental and quasi-experimental designs can be used to isolate the effect of the built environment on physical activity, but in their absence, statistical techniques that adjust for neighborhood self-selection can be used with cross-sectional data. Previous reviews examining the built environment-physical activity relationship have not differentiated among findings based on study design. To deal with self-selection, we synthesized evidence regarding the relationship between objective measures of the built environment and physical activity by including in our review: 1) cross-sectional studies that adjust for neighborhood self-selection and 2) quasi-experiments. Method In September 2010, we searched for English-language studies on built environments and physical activity from all available years in health, leisure, transportation, social sciences, and geographical databases. Twenty cross-sectional and 13 quasi-experimental studies published between 1996 and 2010 were included in the review. Results Most associations between the built environment and physical activity were in the expected direction or null. Land use mix, connectivity and population density and overall neighborhood design were however, important determinants of physical activity. The built environment was more likely to be associated with transportation walking compared with other types of physical activity including recreational walking. Three studies found an attenuation in associations between built environment characteristics and physical activity after accounting for neighborhood self-selection. Conclusion More quasi-experiments that examine a broader range of environmental attributes in relation to context-specific physical activity and that measure changes in the built environment, neighborhood preferences and their effect on physical activity are needed. PMID:22077952

  4. Assessing the Independent Contribution of Maternal Educational Expectations to Children’s Educational Attainment in Early Adulthood: A Propensity Score Matching Analysis

    PubMed Central

    Pingault, Jean Baptiste; Côté, Sylvana M.; Petitclerc, Amélie; Vitaro, Frank; Tremblay, Richard E.

    2015-01-01

    Background Parental educational expectations have been associated with children’s educational attainment in a number of long-term longitudinal studies, but whether this relationship is causal has long been debated. The aims of this prospective study were twofold: 1) test whether low maternal educational expectations contributed to failure to graduate from high school; and 2) compare the results obtained using different strategies for accounting for confounding variables (i.e. multivariate regression and propensity score matching). Methodology/Principal Findings The study sample included 1,279 participants from the Quebec Longitudinal Study of Kindergarten Children. Maternal educational expectations were assessed when the participants were aged 12 years. High school graduation – measuring educational attainment – was determined through the Quebec Ministry of Education when the participants were aged 22–23 years. Findings show that when using the most common statistical approach (i.e. multivariate regressions to adjust for a restricted set of potential confounders) the contribution of low maternal educational expectations to failure to graduate from high school was statistically significant. However, when using propensity score matching, the contribution of maternal expectations was reduced and remained statistically significant only for males. Conclusions/Significance The results of this study are consistent with the possibility that the contribution of parental expectations to educational attainment is overestimated in the available literature. This may be explained by the use of a restricted range of potential confounding variables as well as the dearth of studies using appropriate statistical techniques and study designs in order to minimize confounding. Each of these techniques and designs, including propensity score matching, has its strengths and limitations: A more comprehensive understanding of the causal role of parental expectations will stem from a convergence of findings from studies using different techniques and designs. PMID:25803867

  5. Opportunities and Problems of Comparative Higher Education Research: The Daily Life of Research

    ERIC Educational Resources Information Center

    Teichler, Ulrich

    2014-01-01

    Higher education had a predominant national and institutional focus for a long time. In Europe, supra-national political activities played a major role for increasing the interest in comparative research. Comparative perspectives are important in order to deconstruct the often national perspective of causal reasoning, for proving benchmarks, for…

  6. Comparing the Perceptions of Inclusion between General Education and Special Education Teachers

    ERIC Educational Resources Information Center

    Bruster, Debra Dungan

    2014-01-01

    This causal-comparative, quantitative study compared the perceptions of inclusion of students with disabilities in the mainstream classroom that are held by high school general education teachers and high school special education teachers that teach in inclusive settings. The study determined there is a difference between the perceptions of…

  7. Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.

    PubMed

    Johnson, Samuel G B; Ahn, Woo-kyoung

    2015-09-01

    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make transitive judgments about causal chains by inferring, given A causes B and B causes C, that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links ((Experiments 1-3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4 and 5). Copyright © 2015 Cognitive Science Society, Inc.

  8. Estimating the Variance of Design Parameters

    ERIC Educational Resources Information Center

    Hedberg, E. C.; Hedges, L. V.; Kuyper, A. M.

    2015-01-01

    Randomized experiments are generally considered to provide the strongest basis for causal inferences about cause and effect. Consequently randomized field trials have been increasingly used to evaluate the effects of education interventions, products, and services. Populations of interest in education are often hierarchically structured (such as…

  9. Dairy consumption, systolic blood pressure, and risk of hypertension: Mendelian randomization study

    USDA-ARS?s Scientific Manuscript database

    Objective: To examine whether previous observed inverse associations of dairy intake with systolic blood pressure and risk of hypertension were causal. Design: Mendelian randomization study using the single nucleotide polymorphism rs4988235 related to lactase persistence as an instrumental variable...

  10. Two logics of policy intervention in immigrant integration: an institutionalist framework based on capabilities and aspirations.

    PubMed

    Lutz, Philipp

    2017-01-01

    The effectiveness of immigrant integration policies has gained considerable attention across Western democracies dealing with ethnically and culturally diverse societies. However, the findings on what type of policy produces more favourable integration outcomes remain inconclusive. The conflation of normative and analytical assumptions on integration is a major challenge for causal analysis of integration policies. This article applies actor-centered institutionalism as a new framework for the analysis of immigrant integration outcomes in order to separate two different mechanisms of policy intervention. Conceptualising integration outcomes as a function of capabilities and aspirations allows separating assumptions on the policy intervention in assimilation and multiculturalism as the two main types of policy approaches. The article illustrates that assimilation is an incentive-based policy and primarily designed to increase immigrants' aspirations, whereas multiculturalism is an opportunity-based policy and primarily designed to increase immigrants' capabilities. Conceptualising causal mechanisms of policy intervention clarifies the link between normative concepts of immigrant integration and analytical concepts of policy effectiveness.

  11. Teacher knowledge, instructional expertise, and the development of reading proficiency.

    PubMed

    Reid Lyon, G; Weiser, Beverly

    2009-01-01

    Teacher knowledge and instructional expertise have been found in correlational and pre- and posttest studies to be related to student reading achievement. This article summarizes data presented in this special issue and additional research to address four questions: (a) What do expert reading teachers know? (b) Why do teachers need to acquire this knowledge? (c) Do teachers believe they have this knowledge? and (d) Are teachers being adequately prepared to teach reading? Well-designed studies relevant to this topic have been sparse with a noticeable lack of attention given to identifying specific causal links between teacher knowledge, teaching expertise, and student reading achievement. Until the appropriate research designs and methodologies are applied to address the question of causal effects, conclusions about the specific content that teachers must know and the instructional practices that are most beneficial in presenting this content are preliminary at best. Future studies of the effect of essential reading content knowledge must be extended beyond word-level skills to vocabulary, reading comprehension, and writing.

  12. Comparison and Causal Explanation

    ERIC Educational Resources Information Center

    Ringer, Fritz

    2006-01-01

    Since the classical authors of the nineteenth century, the explanation of macro-social phenomena has been considered as the essential epistemic achievement, hence the "raison d'etre," of comparative analysis in the social sciences. In practice, however, the claims of comparative social enquiry for providing convincing explanations are…

  13. The relationship between the belief in a genetic cause for breast cancer and bilateral mastectomy.

    PubMed

    Petrie, Keith J; Myrtveit, Solbjørg Makalani; Partridge, Ann H; Stephens, Melika; Stanton, Annette L

    2015-05-01

    Most women develop causal beliefs following diagnosis with breast cancer and these beliefs can guide decisions around their care and management. Bilateral mastectomy rates are increasing, although the benefits of this surgery are only established in a small percentage of women. In this study we investigated the relationship between causal beliefs and the decision to have a bilateral mastectomy. Women (N = 2,269) from the Army of Women's breast cancer research registry completed an online survey. Women were asked what they believed caused their cancer and responses were coded into 8 causal categories. Participants were also asked about the type of surgery they underwent following their breast cancer diagnosis. The odds ratios for having a double mastectomy were calculated for each causal category using random/bad luck as a referent category. Hormonal factors (22%) and genetics (19%) were the most common causal belief, followed by don't know (19%), environmental toxins (11%), negative emotions (9%), poor health behavior (8%), other (6%) and random/bad luck (6%). Compared with the referent category, the odds ratio of having a bilateral mastectomy was significantly higher in both the genetics and hormonal causal belief groups (OR = 2.36, 95% CI [1.38, 4.02] and OR = 1.98, 95% CI [1.16, 3.38], respectively). Beliefs in a genetic cause for breast cancer are common and are associated with high rates of bilateral mastectomy. This is despite evidence that the actual genetic contribution to breast cancer is much lower than perceived and that bilateral mastectomy is, in most cases, unlikely to improve survival. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  14. Exploring Causality between TV Viewing and Weight Change in Young and Middle-Aged Adults. The Cardiovascular Risk in Young Finns Study

    PubMed Central

    Helajärvi, Harri; Rosenström, Tom; Pahkala, Katja; Kähönen, Mika; Lehtimäki, Terho; Heinonen, Olli J.; Oikonen, Mervi; Tammelin, Tuija; Viikari, Jorma S. A.; Raitakari, Olli T.

    2014-01-01

    Background Television viewing time (TV time) is associated with increased weight and obesity, but it is unclear whether this relation is causal. Methods and Results We evaluated changes in TV time, waist circumference (waist) and body mass index (BMI) in participants of the population-based Cardiovascular Risk in Young Finns study (761 women, 626 men aged 33–50 years in 2011). Waist and BMI were measured, and TV time was self-reported in 2001, 2007, and 2011. Changes in waist and BMI between 2001 and 2011 were studied a) for the whole group, b) in groups with constantly low (≤1 h/d), moderate (1–3 h/d), or high (≥3 h/d) TV time, and c) in groups with ≥1 hour in-/decrease in daily TV time between 2001 and 2011. BMIs in 1986 were also evaluated. We explored the causal relationship of TV time with waist and BMI by classical temporality criterion and recently introduced causal-discovery algorithms (pairwise causality measures). Both methods supported the hypothesis that TV time is causative to weight gain, and no evidence was found for reverse or bidirectional causality. Constantly low TV time was associated with less pronounced increase in waist and BMI, and waist and BMI increase was lower with decreased TV time (P<0.05). The increase in waist and BMI was at least 2-fold in the high TV time group compared to the low TV time group (P<0.05). Adjustment for age, sex, BMI/waist in 2001, physical activity, energy intake, or smoking did not change the results. Conclusions In young and middle-aged adults, constantly high TV time is temporally antecedent to BMI and waist increase. PMID:25028965

  15. Functional ability loss in sensory impaired and sensory unimpaired very old adults: analyzing causal relations with positive affect across four years.

    PubMed

    Wahl, Hans-Werner; Drapaniotis, Philipp M; Heyl, Vera

    2014-11-01

    This paper focuses on the relationship between functional ability (FA) and positive affect (PA), a major component of well-being, in sensory impaired very old adults (SI) compared with sensory unimpaired individuals (UI). Previous research mostly suggests a robust causal impact of FA on PA. However, some research, drawing from Fredrickson's broaden-and-build theory, also points to the possibility of an inverse causality between FA and PA. We examine in this paper both of these causal directions in SI as well as UI individuals across a 4year observation period. Additionally, we checked for the role of negative affect (NA). The T1-T2 sample comprised 81 out of 237 SI individuals (visually or hearing impaired) assessed at T1, with a mean age at T1 of 81.8years, and 87 UI individuals out of 150 assessed at T1, with a mean age at T1 of 81.5years. Established scales were used to assess FA, PA, and NA. Using cross-lagged panel analysis to examine the direction of causality, our findings indicate that FA has significant impact on PA in both the SI and the UI group, whereas the alternative causal pathway was not confirmed. Both cross-lagged relationships between FA and NA were non-significant. No group differences in path strengths between SI and UI were present. Our study provides evidence that FA is a key competence for successful emotional aging in vulnerable groups of very old adults such as SI as well as in UI adults in advanced old age. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Exploring causality between TV viewing and weight change in young and middle-aged adults. The Cardiovascular Risk in Young Finns study.

    PubMed

    Helajärvi, Harri; Rosenström, Tom; Pahkala, Katja; Kähönen, Mika; Lehtimäki, Terho; Heinonen, Olli J; Oikonen, Mervi; Tammelin, Tuija; Viikari, Jorma S A; Raitakari, Olli T

    2014-01-01

    Television viewing time (TV time) is associated with increased weight and obesity, but it is unclear whether this relation is causal. We evaluated changes in TV time, waist circumference (waist) and body mass index (BMI) in participants of the population-based Cardiovascular Risk in Young Finns study (761 women, 626 men aged 33-50 years in 2011). Waist and BMI were measured, and TV time was self-reported in 2001, 2007, and 2011. Changes in waist and BMI between 2001 and 2011 were studied a) for the whole group, b) in groups with constantly low (≤ 1 h/d), moderate (1-3 h/d), or high (≥ 3 h/d) TV time, and c) in groups with ≥ 1 hour in-/decrease in daily TV time between 2001 and 2011. BMIs in 1986 were also evaluated. We explored the causal relationship of TV time with waist and BMI by classical temporality criterion and recently introduced causal-discovery algorithms (pairwise causality measures). Both methods supported the hypothesis that TV time is causative to weight gain, and no evidence was found for reverse or bidirectional causality. Constantly low TV time was associated with less pronounced increase in waist and BMI, and waist and BMI increase was lower with decreased TV time (P<0.05). The increase in waist and BMI was at least 2-fold in the high TV time group compared to the low TV time group (P<0.05). Adjustment for age, sex, BMI/waist in 2001, physical activity, energy intake, or smoking did not change the results. In young and middle-aged adults, constantly high TV time is temporally antecedent to BMI and waist increase.

  17. The relationship between awareness of intellectual disability, causal and intervention beliefs and social distance in Kuwait and the UK.

    PubMed

    Scior, Katrina; Hamid, Aseel; Mahfoudhi, Abdessatar; Abdalla, Fauzia

    2013-11-01

    Evidence on lay beliefs and stigma associated with intellectual disability in an Arab context is almost non-existent. This study examined awareness of intellectual disability, causal and intervention beliefs and social distance in Kuwait. These were compared to a UK sample to examine differences in lay conceptions across cultures. 537 university students in Kuwait and 571 students in the UK completed a web-based survey asking them to respond to a diagnostically unlabelled vignette of a man presenting with symptoms of mild intellectual disability. They rated their agreement with 22 causal items as possible causes for the difficulties depicted in the vignette, the perceived helpfulness of 22 interventions, and four social distance items using a 7-point Likert scale. Only 8% of Kuwait students, yet 33% of UK students identified possible intellectual disability in the vignette. Medium to large differences between the two samples were observed on seven of the causal items, and 10 of the intervention items. Against predictions, social distance did not differ. Causal beliefs mediated the relationship between recognition of intellectual disability and social distance, but their mediating role differed by sample. The findings are discussed in relation to cultural practices and values, and in relation to attribution theory. In view of the apparent positive effect of awareness of the symptoms of intellectual disability on social distance, both directly and through the mediating effects of causal beliefs, promoting increased awareness of intellectual disability and inclusive practices should be a priority, particularly in countries such as Kuwait where it appears to be low. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. A Unifying Theory of Biological Function.

    PubMed

    van Hateren, J H

    2017-01-01

    A new theory that naturalizes biological function is explained and compared with earlier etiological and causal role theories. Etiological (or selected effects) theories explain functions from how they are caused over their evolutionary history. Causal role theories analyze how functional mechanisms serve the current capacities of their containing system. The new proposal unifies the key notions of both kinds of theories, but goes beyond them by explaining how functions in an organism can exist as factors with autonomous causal efficacy. The goal-directedness and normativity of functions exist in this strict sense as well. The theory depends on an internal physiological or neural process that mimics an organism's fitness, and modulates the organism's variability accordingly. The structure of the internal process can be subdivided into subprocesses that monitor specific functions in an organism. The theory matches well with each intuition on a previously published list of intuited ideas about biological functions, including intuitions that have posed difficulties for other theories.

  19. In defence of story-telling.

    PubMed

    Currie, Adrian; Sterelny, Kim

    2017-04-01

    We argue that narratives are central to the success of historical reconstruction. Narrative explanation involves tracing causal trajectories across time. The construction of narrative, then, often involves postulating relatively speculative causal connections between comparatively well-established events. But speculation is not always idle or harmful: it also aids in overcoming local underdetermination by forming scaffolds from which new evidence becomes relevant. Moreover, as our understanding of the past's causal milieus become richer, the constraints on narrative plausibility become increasingly strict: a narrative's admissibility does not turn on mere logical consistency with background data. Finally, narrative explanation and explanation generated by simple, formal models complement one another. Where models often achieve isolation and precision at the cost of simplification and abstraction, narratives can track complex changes in a trajectory over time at the cost of simplicity and precision. In combination both allow us to understand and explain highly complex historical sequences. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Causal inference as an emerging statistical approach in neurology: an example for epilepsy in the elderly.

    PubMed

    Moura, Lidia Mvr; Westover, M Brandon; Kwasnik, David; Cole, Andrew J; Hsu, John

    2017-01-01

    The elderly population faces an increasing number of cases of chronic neurological conditions, such as epilepsy and Alzheimer's disease. Because the elderly with epilepsy are commonly excluded from randomized controlled clinical trials, there are few rigorous studies to guide clinical practice. When the elderly are eligible for trials, they either rarely participate or frequently have poor adherence to therapy, thus limiting both generalizability and validity. In contrast, large observational data sets are increasingly available, but are susceptible to bias when using common analytic approaches. Recent developments in causal inference-analytic approaches also introduce the possibility of emulating randomized controlled trials to yield valid estimates. We provide a practical example of the application of the principles of causal inference to a large observational data set of patients with epilepsy. This review also provides a framework for comparative-effectiveness research in chronic neurological conditions.

  1. Life Strain, Social Control, Social Learning, and Delinquency: The Effects of Gender, Age, and Family SES Among Chinese Adolescents.

    PubMed

    Bao, Wan-Ning; Haas, Ain; Xie, Yunping

    2016-09-01

    Very few studies have examined the pathways to delinquency and causal factors for demographic subgroups of adolescents in a different culture. This article explores the effects of gender, age, and family socioeconomic status (SES) in an integrated model of strain, social control, social learning, and delinquency among a sample of Chinese adolescents. ANOVA is used to check for significant differences between categories of demographic groups on the variables in the integrated model, and the differential effects of causal factors in the theoretical path models are examined. Further tests of interaction effects are conducted to compare path coefficients between "high-risk" youths (i.e., male, mid-teen, and low family SES adolescents) and other subgroups. The findings identified similar pathways to delinquency across subgroups and clarified the salience of causal factors for male, mid-teen, and low SES adolescents in a different cultural context. © The Author(s) 2015.

  2. Inside out: meet the operators inside the horizon. On bulk reconstruction behind causal horizons

    NASA Astrophysics Data System (ADS)

    Almheiri, Ahmed; Anous, Tarek; Lewkowycz, Aitor

    2018-01-01

    Based on the work of Heemskerk, Marolf, Polchinski and Sully (HMPS), we study the reconstruction of operators behind causal horizons in time dependent geometries obtained by acting with shockwaves on pure states or thermal states. These geometries admit a natural basis of gauge invariant operators, namely those geodesically dressed to the boundary along geodesics which emanate from the bifurcate horizon at constant Rindler time. We outline a procedure for obtaining operators behind the causal horizon but inside the entanglement wedge by exploiting the equality between bulk and boundary time evolution, as well as the freedom to consider the operators evolved by distinct Hamiltonians. This requires we carefully keep track of how the operators are gravitationally dressed and that we address issues regarding background dependence. We compare this procedure to reconstruction using modular flow, and illustrate some formal points in simple cases such as AdS2 and AdS3.

  3. Clinical knee findings in floor layers with focus on meniscal status.

    PubMed

    Rytter, Søren; Jensen, Lilli Kirkeskov; Bonde, Jens Peter

    2008-10-22

    The aim of this study was to examine the prevalence of self-reported and clinical knee morbidity among floor layers compared to a group of graphic designers, with special attention to meniscal status. We obtained information about knee complaints by questionnaire and conducted a bilateral clinical and radiographic knee examination in 134 male floor layers and 120 male graphic designers. After the exclusion of subjects with reports of earlier knee injuries the odds ratio (OR) with 95% confidence intervals (CI) of knee complaints and clinical findings were computed among floor layers compared to graphic designers, using logistic regression. Estimates were adjusted for effects of body mass index, age and knee straining sports. Using radiographic evaluations, we conducted side-specific sensitivity analyses regarding clinical signs of meniscal lesions after the exclusion of participants with tibiofemoral (TF) osteoarthritis (OA). Reports of knee pain (OR = 2.7, 95% CI = 1.5-4.6), pain during stair walking (OR = 2.2, 95% CI = 1.3-3.9) and symptoms of catching of the knee joint (OR = 2.9, 95% CI = 1.4-5.7) were more prevalent among floor layers compared to graphic designers. Additionally, significant more floor layers than graphic designers had clinical signs suggesting possible meniscal lesions: a positive McMurray test (OR = 2.4, 95% CI = 1.1-5.0) and TF joint line tenderness (OR = 5.4, 95% CI = 2.4-12.0). Excluding floor layers (n = 22) and graphic designers (n = 15) with radiographic TF OA did not alter this trend between the two study groups: a positive McMurray test (OR = 2.2, 95% CI = 1.0-4.9), TF joint line tenderness (OR = 5.0, 95% CI = 2.0-12.5). Results indicate that floor layers have a high prevalence of both self-reported and clinical knee morbidity. Clinical knee findings suggesting possible meniscal lesions were significant more prevalent among floor layers compared to a group of low-level exposed graphic designers and an association with occupational kneeling could be possible. However, causality cannot be confirmed due to the cross-sectional study design.

  4. Genetics of Triglycerides and the Risk of Atherosclerosis.

    PubMed

    Dron, Jacqueline S; Hegele, Robert A

    2017-07-01

    Plasma triglycerides are routinely measured with a lipid profile, and elevated plasma triglycerides are commonly encountered in the clinic. The confounded nature of this trait, which is correlated with numerous other metabolic perturbations, including depressed high-density lipoprotein cholesterol (HDL-C), has thwarted efforts to directly implicate triglycerides as causal in atherogenesis. Human genetic approaches involving large-scale populations and high-throughput genomic assessment under a Mendelian randomization framework have undertaken to sort out questions of causality. We review recent large-scale meta-analyses of cohorts and population-based sequencing studies designed to address whether common and rare variants in genes whose products are determinants of plasma triglycerides are also associated with clinical cardiovascular endpoints. The studied loci include genes encoding lipoprotein lipase and proteins that interact with it, such as apolipoprotein (apo) A-V, apo C-III and angiopoietin-like proteins 3 and 4, and common polymorphisms identified in genome-wide association studies. Triglyceride-raising variant alleles of these genes showed generally strong associations with clinical cardiovascular endpoints. However, in most cases, a second lipid disturbance-usually depressed HDL-C-was concurrently associated. While the findings collectively shift our understanding towards a potential causal role for triglycerides, we still cannot rule out the possibilities that triglycerides are a component of a joint phenotype with low HDL-C or that they are but markers of deeper causal metabolic disturbances that are not routinely measured in epidemiological-scale genetic studies.

  5. Dynamic relationship between CO2 emissions, energy consumption and economic growth in three North African countries

    NASA Astrophysics Data System (ADS)

    Kais, Saidi; Ben Mbarek, Mounir

    2017-10-01

    This paper investigated the causal relationship between energy consumption (EC), carbon dioxide (CO2) emissions and economic growth for three selected North African countries. It uses a panel co-integration analysis to determine this econometric relationship using data during 1980-2012. Recently developed tests for panel unit root and co-integration tests are applied. In order to test the Granger causality, a panel Vector Error Correction Model is used. The conservation hypothesis is found; the short run panel results show that there is a unidirectional relationship from economic growth to EC. In addition, there is a unidirectional causality running from economic growth to CO2 emissions. A unidirectional relationship from EC to CO2 emissions is detected. Findings shown that there is a big interdependence between EC and economic growth in the long run, which indicates the level of economic activity and EC mutually influence each other in that a high level of economic growth leads to a high level of EC and vice versa. Similarly, a unidirectional causal relationship from EC to CO2 emissions is detected. This study opens up new insights for policy-makers to design comprehensive economic, energy and environmental policy to keep the economic green and a sustainable environment, implying that these three variables could play an important role in the adjustment process as the system changes from the long run equilibrium.

  6. A Analysis of the Development of Weather Concepts

    NASA Astrophysics Data System (ADS)

    Mroz, Paul John

    Weather information in all forms is poorly understood and often misinterpreted by the general public. Weather literacy is necessary for everyone if critical weather messages, designed to save lives and protect property, are to be effective. The purpose of this study was to seek content and causal evidence for a developmental concept of Weather Information Processing that was consistent with Piagetian Cognitive Stages of Development. Three ordinal Content Stages Of Weather Information Processing (phenomena, process and mechanism) and three ordinal Causal Explanation Stages Of Weather Information Processing (non-real, natural, and scientifically valid abstract ideas) were explored for their relationship with Piaget's Pre-Operational, Concrete and Formal Stages of Development. One hundred and fifty -five elementary and secondary school students from two school districts were administered a written Piagetian exam. Commonly available television weather programs were categorized, randomly assigned and viewed by 42 randomly selected students who were administered three Piagetian tasks. Students were clinically interviewed for the level of content information and causal explanations (reasoning). Results indicated that content information and causal reasoning of students to televised weather information is significantly related (p <.01) to age, and Piagetian Cognitive Stages of Development. Two Piagetian logic operations (seriation and correlation) were established as significantly different (p <.05) when related to age. These findings support a developmental concept of Weather Information Processing and have implications for teaching and presenting weather information to the public.

  7. Application of systems and control theory-based hazard analysis to radiation oncology.

    PubMed

    Pawlicki, Todd; Samost, Aubrey; Brown, Derek W; Manger, Ryan P; Kim, Gwe-Ya; Leveson, Nancy G

    2016-03-01

    Both humans and software are notoriously challenging to account for in traditional hazard analysis models. The purpose of this work is to investigate and demonstrate the application of a new, extended accident causality model, called systems theoretic accident model and processes (STAMP), to radiation oncology. Specifically, a hazard analysis technique based on STAMP, system-theoretic process analysis (STPA), is used to perform a hazard analysis. The STPA procedure starts with the definition of high-level accidents for radiation oncology at the medical center and the hazards leading to those accidents. From there, the hierarchical safety control structure of the radiation oncology clinic is modeled, i.e., the controls that are used to prevent accidents and provide effective treatment. Using STPA, unsafe control actions (behaviors) are identified that can lead to the hazards as well as causal scenarios that can lead to the identified unsafe control. This information can be used to eliminate or mitigate potential hazards. The STPA procedure is demonstrated on a new online adaptive cranial radiosurgery procedure that omits the CT simulation step and uses CBCT for localization, planning, and surface imaging system during treatment. The STPA procedure generated a comprehensive set of causal scenarios that are traced back to system hazards and accidents. Ten control loops were created for the new SRS procedure, which covered the areas of hospital and department management, treatment design and delivery, and vendor service. Eighty three unsafe control actions were identified as well as 472 causal scenarios that could lead to those unsafe control actions. STPA provides a method for understanding the role of management decisions and hospital operations on system safety and generating process design requirements to prevent hazards and accidents. The interaction of people, hardware, and software is highlighted. The method of STPA produces results that can be used to improve safety and prevent accidents and warrants further investigation.

  8. Playing the electric light orchestra—how electrical stimulation of visual cortex elucidates the neural basis of perception

    PubMed Central

    Cicmil, Nela; Krug, Kristine

    2015-01-01

    Vision research has the potential to reveal fundamental mechanisms underlying sensory experience. Causal experimental approaches, such as electrical microstimulation, provide a unique opportunity to test the direct contributions of visual cortical neurons to perception and behaviour. But in spite of their importance, causal methods constitute a minority of the experiments used to investigate the visual cortex to date. We reconsider the function and organization of visual cortex according to results obtained from stimulation techniques, with a special emphasis on electrical stimulation of small groups of cells in awake subjects who can report their visual experience. We compare findings from humans and monkeys, striate and extrastriate cortex, and superficial versus deep cortical layers, and identify a number of revealing gaps in the ‘causal map′ of visual cortex. Integrating results from different methods and species, we provide a critical overview of the ways in which causal approaches have been used to further our understanding of circuitry, plasticity and information integration in visual cortex. Electrical stimulation not only elucidates the contributions of different visual areas to perception, but also contributes to our understanding of neuronal mechanisms underlying memory, attention and decision-making. PMID:26240421

  9. A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

    PubMed

    Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz

    2016-01-01

    Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

  10. Causal knowledge and the development of inductive reasoning.

    PubMed

    Bright, Aimée K; Feeney, Aidan

    2014-06-01

    We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey→predator) or diagnostic (predator→prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Optimal causal inference: estimating stored information and approximating causal architecture.

    PubMed

    Still, Susanne; Crutchfield, James P; Ellison, Christopher J

    2010-09-01

    We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.

  12. Functional neural circuits that underlie developmental stuttering

    PubMed Central

    Zhao, Guihu; Huo, Yuankai; Herder, Carl L.; Sikora, Chamonix O.; Peterson, Bradley S.

    2017-01-01

    The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca’s area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS. PMID:28759567

  13. What causes breast cancer? A systematic review of causal attributions among breast cancer survivors and how these compare to expert-endorsed risk factors.

    PubMed

    Dumalaon-Canaria, Jo Anne; Hutchinson, Amanda D; Prichard, Ivanka; Wilson, Carlene

    2014-07-01

    The aim of this paper was to review published research that analyzed causal attributions for breast cancer among women previously diagnosed with breast cancer. These attributions were compared with risk factors identified by published scientific evidence in order to determine the level of agreement between cancer survivors' attributions and expert opinion. A comprehensive search for articles, published between 1982 and 2012, reporting studies on causal attributions for breast cancer among patients and survivors was undertaken. Of 5,135 potentially relevant articles, 22 studies met the inclusion criteria. Two additional articles were sourced from reference lists of included studies. Results indicated a consistent belief among survivors that their own breast cancer could be attributed to family history, environmental factors, stress, fate, or chance. Lifestyle factors were less frequently identified, despite expert health information highlighting the importance of these factors in controlling and modifying cancer risk. This review demonstrated that misperceptions about the contribution of modifiable lifestyle factors to the risk of breast cancer have remained largely unchanged over the past 30 years. The findings of this review indicate that beliefs about the causes of breast cancer among affected women are not always consistent with the judgement of experts. Breast cancer survivors did not regularly identify causal factors supported by expert consensus such as age, physical inactivity, breast density, alcohol consumption, and reproductive history. Further research examining psychological predictors of attributions and the impact of cancer prevention messages on adjustment and well-being of cancer survivors is warranted.

  14. Functional neural circuits that underlie developmental stuttering.

    PubMed

    Qiao, Jianping; Wang, Zhishun; Zhao, Guihu; Huo, Yuankai; Herder, Carl L; Sikora, Chamonix O; Peterson, Bradley S

    2017-01-01

    The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca's area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS.

  15. Does sufficient evidence exist to support a causal association between vitamin D status and cardiovascular disease risk? An assessment using Hill's criteria for causality.

    PubMed

    Weyland, Patricia G; Grant, William B; Howie-Esquivel, Jill

    2014-09-02

    Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill's criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor.

  16. Belief beyond the evidence: using the proposed effect of breakfast on obesity to show 2 practices that distort scientific evidence1234

    PubMed Central

    Brown, Andrew W; Bohan Brown, Michelle M

    2013-01-01

    Background: Various intentional and unintentional factors influence beliefs beyond what scientific evidence justifies. Two such factors are research lacking probative value (RLPV) and biased research reporting (BRR). Objective: We investigated the prevalence of RLPV and BRR in research about the proposition that skipping breakfast causes weight gain, which is called the proposed effect of breakfast on obesity (PEBO) in this article. Design: Studies related to the PEBO were synthesized by using a cumulative meta-analysis. Abstracts from these studies were also rated for the improper use of causal language and biased interpretations. In separate analyses, articles that cited an observational study about the PEBO were rated for the inappropriate use of causal language, and articles that cited a randomized controlled trial (RCT) about the PEBO were rated for misleadingly citing the RCT. Results: The current body of scientific knowledge indicates that the PEBO is only presumed true. The observational literature on the PEBO has gratuitously established the association, but not the causal relation, between skipping breakfast and obesity (final cumulative meta-analysis P value <10−42), which is evidence of RLPV. Four examples of BRR are evident in the PEBO literature as follows: 1) biased interpretation of one's own results, 2) improper use of causal language in describing one's own results, 3) misleadingly citing others’ results, and 4) improper use of causal language in citing others’ work. Conclusions: The belief in the PEBO exceeds the strength of scientific evidence. The scientific record is distorted by RLPV and BRR. RLPV is a suboptimal use of collective scientific resources. PMID:24004890

  17. Effects of a Body Image Challenge on Smoking Motivation Among College Females

    PubMed Central

    Lopez, Elena N.; Drobes, David J.; Thompson, J. Kevin; Brandon, Thomas H.

    2014-01-01

    Objective Previous correlational and quasi-experimental research has established that weight concerns and negative body image are associated with tobacco smoking, cessation, and relapse, particularly among young women. This study examined the causal influence of body image upon smoking motivation by merging methodologies from the addiction and body image literatures. Design Using a cue-reactivity paradigm, the study tested whether an experimental manipulation designed to challenge women’s body image—specifically, their weight dissatisfaction—influenced their motivation to smoke. Female college smokers (N = 62) were included in a 2 × 2 factorial, within-subjects design (body image cues X smoking cues). Main Outcome Measures Self-reported urge to smoke was the primary dependent measure, with skin conductance as a secondary measure. Results As hypothesized, the presentation of smoking images and thin model images produced greater urges to smoke than control images. Additionally, trait weight concerns moderated the effect of the body image manipulation such that those women with greater weight concerns produced greater craving to the thin model image (when smoking cues were not present). Conclusion These findings provide initial evidence that situational challenges to body image are causally related to smoking motivation. PMID:18979977

  18. The selective power of causality on memory errors.

    PubMed

    Marsh, Jessecae K; Kulkofsky, Sarah

    2015-01-01

    We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.

  19. Learning to learn causal models.

    PubMed

    Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B

    2010-09-01

    Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.

  20. Spillover effects in epidemiology: parameters, study designs and methodological considerations

    PubMed Central

    Benjamin-Chung, Jade; Arnold, Benjamin F; Berger, David; Luby, Stephen P; Miguel, Edward; Colford Jr, John M; Hubbard, Alan E

    2018-01-01

    Abstract Many public health interventions provide benefits that extend beyond their direct recipients and impact people in close physical or social proximity who did not directly receive the intervention themselves. A classic example of this phenomenon is the herd protection provided by many vaccines. If these ‘spillover effects’ (i.e. ‘herd effects’) are present in the same direction as the effects on the intended recipients, studies that only estimate direct effects on recipients will likely underestimate the full public health benefits of the intervention. Causal inference assumptions for spillover parameters have been articulated in the vaccine literature, but many studies measuring spillovers of other types of public health interventions have not drawn upon that literature. In conjunction with a systematic review we conducted of spillovers of public health interventions delivered in low- and middle-income countries, we classified the most widely used spillover parameters reported in the empirical literature into a standard notation. General classes of spillover parameters include: cluster-level spillovers; spillovers conditional on treatment or outcome density, distance or the number of treated social network links; and vaccine efficacy parameters related to spillovers. We draw on high quality empirical examples to illustrate each of these parameters. We describe study designs to estimate spillovers and assumptions required to make causal inferences about spillovers. We aim to advance and encourage methods for spillover estimation and reporting by standardizing spillover parameter nomenclature and articulating the causal inference assumptions required to estimate spillovers. PMID:29106568

  1. A Children of Twins Study of parental divorce and offspring psychopathology

    PubMed Central

    D'Onofrio, Brian M.; Turkheimer, Eric; Emery, Robert E.; Maes, Hermine H.; Silberg, Judy; Eaves, Lindon J.

    2010-01-01

    Background Although parental divorce is associated with increased substance use and internalizing problems, experiencing the separation of one's parents may not cause these outcomes. The relations may be due to genetic or environmental selection factors, characteristics that lead to both marital separation and offspring functioning. Method We used the Children of Twins (CoT) Design to explore whether unmeasured genetic or environmental factors related to the twin parent, and measured characteristics of both parents, account for the association between parental divorce and offspring substance use and internalizing problems. Results The association between parental divorce and offspring substance use problems remained robust when controlling for genetic and environmental risk from the twin parent associated with parental divorce, and measured characteristics of both parents. The results do not prove, but are consistent with, a causal connection. In contrast, the analyses suggest that shared genetic liability in parents and their offspring accounts for the increased risk of internalizing problems in adult offspring from divorced families. Conclusions The study illustrates that unmeasured genetic and environmental selection factors must be considered when studying parental divorce. In explaining associations between parental divorce and young-adult adjustment, our evidence suggests that selection versus causal mechanisms may operate differently for substance abuse (a causal relation) and internalizing problems (an artifact of selection). The CoT design only controls for the genetic and environmental characteristics of one parent; thus, additional genetically informed analyses are needed. PMID:17593147

  2. Some (But Not Much) Progress Toward Understanding Teenage Childbearing: A Review of Research From the Past Decade

    PubMed Central

    Coyne, Claire A.; D’Onofrio, Brian M.

    2013-01-01

    In the decade and a half since Coley & Chase-Lansdale’s (1998) review of teenage childbearing there have been a number of studies investigating teenage childbearing from a developmental psychological perspective. Many of these studies have focused primarily on identifying individual, familial, and socioeconomic risk factors in childhood and adolescence that are highly correlated with teenage sexual behavior and teenage childbearing. We have an emerging understanding of teenage childbearing as the culmination of a complex cascade of experiences and decisions that overlap greatly with the risks for antisocial behavior. Much of this research, however, is limited by its reliance on correlational and cross-sectional research designs, which are not able to rigorously test causal inferences or to identify mechanisms associated with teenage childbearing. Innovative studies using large, nationally representative samples with quasi-experimental and longitudinal designs can expand on such descriptive studies. In particular, quasi-experimental studies can help answer questions about which risk factors are causally associated with teenage childbearing and suggest potential mechanisms that can explain how teenage childbearing is associated with poor outcomes. Future studies also will need to incorporate more precise measures of developmental processes and explore heterogeneity among adolescent mothers. Although advances have been made in the psychological study of teenage childbearing, more research is needed in order to answer important questions about which psychological processes are causally related to teenage childbearing and how teenage childbearing is associated with poor outcomes for young mothers and their offspring. PMID:22675905

  3. The Introductory Sociology Survey

    ERIC Educational Resources Information Center

    Best, Joel

    1977-01-01

    The Introductory Sociology Survey (ISS) is designed to teach introductory students basic skills in developing causal arguments and in using a computerized statistical package to analyze survey data. Students are given codebooks for survey data and asked to write a brief paper predicting the relationship between at least two variables. (Author)

  4. Internal Validity: A Must in Research Designs

    ERIC Educational Resources Information Center

    Cahit, Kaya

    2015-01-01

    In experimental research, internal validity refers to what extent researchers can conclude that changes in dependent variable (i.e. outcome) are caused by manipulations in independent variable. The causal inference permits researchers to meaningfully interpret research results. This article discusses (a) internal validity threats in social and…

  5. Model Ambiguities in Configurational Comparative Research

    ERIC Educational Resources Information Center

    Baumgartner, Michael; Thiem, Alrik

    2017-01-01

    For many years, sociologists, political scientists, and management scholars have readily relied on Qualitative Comparative Analysis (QCA) for the purpose of configurational causal modeling. However, this article reveals that a severe problem in the application of QCA has gone unnoticed so far: model ambiguities. These arise when multiple causal…

  6. Professional Development Urban Schools: What Do Teachers Say?

    ERIC Educational Resources Information Center

    Green, Tanya R.; Allen, Mishaleen

    2015-01-01

    This quantitative causal-comparative study compared perceptions of professional development opportunities between high-achieving and low-achieving elementary-middle school teachers in an urban school district using the Standards Assessment Inventory (SAI). A total of 271 teachers participated including 134 (n = 134) teachers from high-achieving…

  7. Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling

    USGS Publications Warehouse

    Irvine, Kathryn M.; Miller, Scott; Al-Chokhachy, Robert K.; Archer, Erik; Roper, Brett B.; Kershner, Jeffrey L.

    2015-01-01

    Conceptual models are an integral facet of long-term monitoring programs. Proposed linkages between drivers, stressors, and ecological indicators are identified within the conceptual model of most mandated programs. We empirically evaluate a conceptual model developed for a regional aquatic and riparian monitoring program using causal models (i.e., Bayesian path analysis). We assess whether data gathered for regional status and trend estimation can also provide insights on why a stream may deviate from reference conditions. We target the hypothesized causal pathways for how anthropogenic drivers of road density, percent grazing, and percent forest within a catchment affect instream biological condition. We found instream temperature and fine sediments in arid sites and only fine sediments in mesic sites accounted for a significant portion of the maximum possible variation explainable in biological condition among managed sites. However, the biological significance of the direct effects of anthropogenic drivers on instream temperature and fine sediments were minimal or not detected. Consequently, there was weak to no biological support for causal pathways related to anthropogenic drivers’ impact on biological condition. With weak biological and statistical effect sizes, ignoring environmental contextual variables and covariates that explain natural heterogeneity would have resulted in no evidence of human impacts on biological integrity in some instances. For programs targeting the effects of anthropogenic activities, it is imperative to identify both land use practices and mechanisms that have led to degraded conditions (i.e., moving beyond simple status and trend estimation). Our empirical evaluation of the conceptual model underpinning the long-term monitoring program provided an opportunity for learning and, consequently, we discuss survey design elements that require modification to achieve question driven monitoring, a necessary step in the practice of adaptive monitoring. We suspect our situation is not unique and many programs may suffer from the same inferential disconnect. Commonly, the survey design is optimized for robust estimates of regional status and trend detection and not necessarily to provide statistical inferences on the causal mechanisms outlined in the conceptual model, even though these relationships are typically used to justify and promote the long-term monitoring of a chosen ecological indicator. Our application demonstrates a process for empirical evaluation of conceptual models and exemplifies the need for such interim assessments in order for programs to evolve and persist.

  8. A quantum causal discovery algorithm

    NASA Astrophysics Data System (ADS)

    Giarmatzi, Christina; Costa, Fabio

    2018-03-01

    Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.

  9. Do people reason rationally about causally related events? Markov violations, weak inferences, and failures of explaining away.

    PubMed

    Rottman, Benjamin M; Hastie, Reid

    2016-06-01

    Making judgments by relying on beliefs about the causal relationships between events is a fundamental capacity of everyday cognition. In the last decade, Causal Bayesian Networks have been proposed as a framework for modeling causal reasoning. Two experiments were conducted to provide comprehensive data sets with which to evaluate a variety of different types of judgments in comparison to the standard Bayesian networks calculations. Participants were introduced to a fictional system of three events and observed a set of learning trials that instantiated the multivariate distribution relating the three variables. We tested inferences on chains X1→Y→X2, common cause structures X1←Y→X2, and common effect structures X1→Y←X2, on binary and numerical variables, and with high and intermediate causal strengths. We tested transitive inferences, inferences when one variable is irrelevant because it is blocked by an intervening variable (Markov Assumption), inferences from two variables to a middle variable, and inferences about the presence of one cause when the alternative cause was known to have occurred (the normative "explaining away" pattern). Compared to the normative account, in general, when the judgments should change, they change in the normative direction. However, we also discuss a few persistent violations of the standard normative model. In addition, we evaluate the relative success of 12 theoretical explanations for these deviations. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. CaSPIAN: A Causal Compressive Sensing Algorithm for Discovering Directed Interactions in Gene Networks

    PubMed Central

    Emad, Amin; Milenkovic, Olgica

    2014-01-01

    We introduce a novel algorithm for inference of causal gene interactions, termed CaSPIAN (Causal Subspace Pursuit for Inference and Analysis of Networks), which is based on coupling compressive sensing and Granger causality techniques. The core of the approach is to discover sparse linear dependencies between shifted time series of gene expressions using a sequential list-version of the subspace pursuit reconstruction algorithm and to estimate the direction of gene interactions via Granger-type elimination. The method is conceptually simple and computationally efficient, and it allows for dealing with noisy measurements. Its performance as a stand-alone platform without biological side-information was tested on simulated networks, on the synthetic IRMA network in Saccharomyces cerevisiae, and on data pertaining to the human HeLa cell network and the SOS network in E. coli. The results produced by CaSPIAN are compared to the results of several related algorithms, demonstrating significant improvements in inference accuracy of documented interactions. These findings highlight the importance of Granger causality techniques for reducing the number of false-positives, as well as the influence of noise and sampling period on the accuracy of the estimates. In addition, the performance of the method was tested in conjunction with biological side information of the form of sparse “scaffold networks”, to which new edges were added using available RNA-seq or microarray data. These biological priors aid in increasing the sensitivity and precision of the algorithm in the small sample regime. PMID:24622336

  11. Structure and Strength in Causal Induction

    ERIC Educational Resources Information Center

    Griffiths, Thomas L.; Tenenbaum, Joshua B.

    2005-01-01

    We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…

  12. Perceiving and Confronting Sexism: The Causal Role of Gender Identity Salience

    PubMed Central

    Wang, Katie; Dovidio, John F.

    2017-01-01

    Although many researchers have explored the relations among gender identification, discriminatory attributions, and intentions to challenge discrimination, few have examined the causal impact of gender identity salience on women’s actual responses to a sexist encounter. In the current study, we addressed this question by experimentally manipulating the salience of gender identity and assessing its impact on women’s decision to confront a sexist comment in a simulated online interaction. Female participants (N = 114) were randomly assigned to complete a short measure of either personal or collective self-esteem, which was designed to increase the salience of personal versus gender identity. They were then given the opportunity to confront a male interaction partner who expressed sexist views. Compared to those who were primed to focus on their personal identity, participants who were primed to focus on their gender identity perceived the interaction partner’s remarks as more sexist and were more likely to engage in confrontation. By highlighting the powerful role of subtle contextual cues in shaping women’s perceptions of, and responses to, sexism, our findings have important implications for the understanding of gender identity salience as an antecedent of prejudice confrontation. Online slides for instructors who want to use this article for teaching are available on PWQ’s website at http://journals.sagepub.com/page/pwq/suppl/index. PMID:29051685

  13. Dose response and structural injury in the disability of spinal injury.

    PubMed

    Patel, Mohammed Shakil; Sell, Philip

    2013-03-01

    In traumatic injury there is a clear relationship between the dose of energy involved, structural tissue damage and resultant disability after recovery. This relationship is often absent in cases of non-specific chronic low back pain that is perceived by patients as attributed to a workplace injury. There are many studies assessing risk factors for non-specific low back pain. However, studies addressing causality of back pain are deficient. To establish whether there exists a causal relationship between structural injury, low back pain and spinal disability. Retrospective analysis of prospectively gathered validated spinal outcome measures [Oswestry disability index (ODI), low back outcome score (LBO), modified somatic perception (MSP), modified Zung depression index (MZD)] between patients with healed high energy thoracolumbar spinal fractures and patients with self-perceived work-related low back pain. Causality was established according to two of Bradford Hill's criteria of medical causality, temporal and dose-response relationships. Twenty-three patients with spinal fractures (group 1) of average age 44 years were compared to 19 patients with self-reported back pain in the workplace pursuing claims for compensation (group 2) of average age 48 years. Both groups were comparable in terms of age and sex. The average ODI in group 1 was 28 % (SD 19) compared to 42 % (SD 19) in group 2 (P < 0.05). Similarly, LBOS was 39.7 versus 24.3 (P < 0.05), MSP 4.3 versus 9.3 (P < 0.05) and MZD 20.2 versus 34.8 (P < 0.05) in groups 1 and 2, respectively. Despite high-energy trauma and significant structural damage to the spine, patients with the high energy injuries had better spinal outcome scores in all measures. There is no 'dose-response' relationship between structural injury, low back pain and spinal disability. This is the reverse of what would be anticipated if structural injury was the cause of disability in workplace reported onset of low back pain.

  14. Thinking aloud: effects on text comprehension by children with specific language impairment and their peers.

    PubMed

    McClintock, Brenna; Pesco, Diane; Martin-Chang, Sandra

    2014-11-01

    Many lines of evidence now suggest that inferencing plays a substantial role in text comprehension. However, inferencing appears to be difficult for children with language impairments, many of whom are also struggling readers. To assess the effects of a 'think-aloud' procedure on inference generation and narrative text comprehension by children with expressive-receptive specific language impairment (SLI) and age-matched peers with typical language development (TLD). An SLI group (n = 12; mean age = 10;5) and an age-matched TLD group (n = 12) participated in the study. Narrative passages were read silently by participants and simultaneously read aloud by the examiner in two conditions: (1) uninterrupted reading and (2) a think-aloud, in which children verbalized their understanding as the text was read. Following the passages in both conditions, children responded to comprehension questions requiring either literal or inferential information (specifically, 'informational' and 'causal' inferences). The children's comprehension scores were analysed by group, condition and question type. The statements children generated during the think-aloud were also compared by group and examined in relation to children's comprehension scores. The SLI group scored lower than the TLD group on all questions (literal, informational and causal), in both conditions. For both groups, however, comprehension scores on all three types of questions increased when the think-aloud procedure was implemented. During the think-aloud, the SLI group generated a comparable number of literal statements compared with the TLD group, but fewer informational and causal statements. The number of causal statements children made correlated with their scores on the inferential comprehension questions. Children with expressive-receptive SLI showed poorer comprehension of narrative texts than children with TLD, as expected. However, both groups' comprehension improved when participating in the think-aloud condition. While further investigation is warranted, the think-aloud procedure shows promise as a strategy to enhance narrative text comprehension in school-age children with, and without, language impairments. © 2014 Royal College of Speech and Language Therapists.

  15. People or systems? To blame is human. The fix is to engineer.

    PubMed

    Holden, Richard J

    2009-12-01

    Person-centered safety theories that place the burden of causality on human traits and actions have been largely dismissed in favor of systems-centered theories. Students and practitioners are now taught that accidents are caused by multiple factors and occur due to the complex interactions of numerous work system elements, human and non-human. Nevertheless, person-centered approaches to safety management still prevail. This paper explores the notion that attributing causality and blame to people persists because it is both a fundamental psychological tendency as well as an industry norm that remains strong in aviation, health care, and other industries. Consequences of that possibility are discussed and a case is made for continuing to invest in whole-system design and engineering solutions.

  16. Effects of task performance, helping, voice, and organizational loyalty on performance appraisal ratings.

    PubMed

    Whiting, Steven W; Podsakoff, Philip M; Pierce, Jason R

    2008-01-01

    Despite the fact that several studies have investigated the relationship between organizational citizenship behavior and performance appraisal ratings, the vast majority of these studies have been cross-sectional, correlational investigations conducted in organizational settings that do not allow researchers to establish the causal nature of this relationship. To address this lack of knowledge regarding causality, the authors conducted 2 studies designed to investigate the effects of task performance, helping behavior, voice, and organizational loyalty on performance appraisal evaluations. Findings demonstrated that each of these forms of behavior has significant effects on performance evaluation decisions and suggest that additional attention should be directed at both voice and organizational loyalty as important forms of citizenship behavior aimed at the organization. 2008 APA

  17. In Support of Clinical Case Reports: A System of Causality Assessment

    PubMed Central

    Hamre, Harald J.; Kienle, Gunver S.

    2013-01-01

    The usefulness of clinical research depends on an assessment of causality. This assessment determines what constitutes clinical evidence. Case reports are an example of evidence that is frequently overlooked because it is believed they cannot address causal links between treatment and outcomes. This may be a mistake. Clarity on the topic of causality and its assessment will be of benefit for researchers and clinicians. This article outlines an overall system of causality and causality assessment. The system proposed involves two dimensions: horizontal and vertical; each of these dimensions consists of three different types of causality and three corresponding types of causality assessment. Included in this system are diverse forms of case causality illustrated with examples from everyday life and clinical medicine. Assessing case causality can complement conventional clinical research in an era of personalized medicine. PMID:24416665

  18. Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach.

    PubMed

    Attiaoui, Imed; Toumi, Hassen; Ammouri, Bilel; Gargouri, Ilhem

    2017-05-01

    This research examines the causality (For the remainder of the paper, the notion of causality refers to Granger causality.) links among renewable energy consumption (REC), CO 2 emissions (CE), non-renewable energy consumption (NREC), and economic growth (GDP) using an autoregressive distributed lag model based on the pooled mean group estimation (ARDL-PMG) and applying Granger causality tests for a panel consisting of 22 African countries for the period between 1990 and 2011. There is unidirectional and irreversible short-run causality from CE to GDP. The causal direction between CE and REC is unobservable over the short-term. Moreover, we find unidirectional, short-run causality from REC to GDP. When testing per pair of variables, there are short-run bidirectional causalities among REC, CE, and GDP. However, if we add CE to the variables REC and NREC, the causality to GDP is observable, and causality from the pair REC and NREC to economic growth is neutral. Likewise, if we add NREC to the variables GDP and REC, there is causality. There are bidirectional long-run causalities among REC, CE, and GDP, which supports the feedback assumption. Causality from GDP to REC is not strong for the panel. If we test per pair of variables, the strong causality from GDP and CE to REC is neutral. The long-run PMG estimates show that NREC and gross domestic product increase CE, whereas REC decreases CE.

  19. A State Space Modeling Approach to Mediation Analysis

    ERIC Educational Resources Information Center

    Gu, Fei; Preacher, Kristopher J.; Ferrer, Emilio

    2014-01-01

    Mediation is a causal process that evolves over time. Thus, a study of mediation requires data collected throughout the process. However, most applications of mediation analysis use cross-sectional rather than longitudinal data. Another implicit assumption commonly made in longitudinal designs for mediation analysis is that the same mediation…

  20. Reducing animal sequencing redundancy by preferentially selecting animals with low-frequency haplotypes

    USDA-ARS?s Scientific Manuscript database

    Many studies leverage targeted whole genome sequencing (WGS) experiments in order to identify rare and causal variants within populations. As a natural consequence of experimental design, many of these surveys tend to sequence redundant haplotype segments due to high frequency in the base population...

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