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Causal Effects (causal + effects)
Selected AbstractsUntangling the Causal Effects of Sex on JudgingAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 2 2010Christina L. Boyd We explore the role of sex in judging by addressing two questions of long-standing interest to political scientists: whether and in what ways male and female judges decide cases distinctly,"individual effects",and whether and in what ways serving with a female judge causes males to behave differently,"panel effects." While we attend to the dominant theoretical accounts of why we might expect to observe either or both effects, we do not use the predominant statistical tools to assess them. Instead, we deploy a more appropriate methodology: semiparametric matching, which follows from a formal framework for causal inference. Applying matching methods to 13 areas of law, we observe consistent gender effects in only one,sex discrimination. For these disputes, the probability of a judge deciding in favor of the party alleging discrimination decreases by about 10 percentage points when the judge is a male. Likewise, when a woman serves on a panel with men, the men are significantly more likely to rule in favor of the rights litigant. These results are consistent with an informational account of gendered judging and are inconsistent with several others. [source] Estimating the Causal Effects of Media Coverage on Policy-Specific KnowledgeAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 1 2009Jason Barabas Policy facts are among the most relevant forms of knowledge in a democracy. Although the mass media seem like an obvious source of policy-specific information, past research in this area has been plagued by design and methodological problems that have hindered causal inferences. Moreover, few studies include measures of media content, preventing researchers from being able to say what it is about media coverage that influences learning. We advance the literature by employing a simple but underutilized approach for estimating the causal effects of news coverage. Drawing upon a unique collection of cross-sectional survey data, we make within-survey/within-subjects comparisons under conditions of high and low media coverage. We show how the volume, breadth, and prominence of news media coverage increase policy-specific knowledge above and beyond common demographic factors. [source] Identifiability and Estimation of Causal Effects in Randomized Trials with Noncompliance and Completely Nonignorable Missing DataBIOMETRICS, Issue 3 2009Hua Chen Summary In this article, we first study parameter identifiability in randomized clinical trials with noncompliance and missing outcomes. We show that under certain conditions the parameters of interest are identifiable even under different types of completely nonignorable missing data: that is, the missing mechanism depends on the outcome. We then derive their maximum likelihood and moment estimators and evaluate their finite-sample properties in simulation studies in terms of bias, efficiency, and robustness. Our sensitivity analysis shows that the assumed nonignorable missing-data model has an important impact on the estimated complier average causal effect (CACE) parameter. Our new method provides some new and useful alternative nonignorable missing-data models over the existing latent ignorable model, which guarantees parameter identifiability, for estimating the CACE in a randomized clinical trial with noncompliance and missing data. [source] Discussion of "Identifiability and Estimation of Causal Effects in Randomized Trials with Noncompliance and Completely Nonignorable Missing Data"BIOMETRICS, Issue 3 2009Dylan S. Small First page of article [source] Estimation of the Causal Effects on Survival of Two-Stage Nonrandomized Treatment Sequences for Recurrent DiseasesBIOMETRICS, Issue 3 2006Xuelin Huang Summary In the treatment of cancer, patients commonly receive a variety of sequential treatments. The initial treatments administered following diagnosis can vary, as well as subsequent salvage regimens given after disease recurrence. This article considers the situation where neither initial treatments nor salvage treatments are randomized. Assuming there are no unmeasured confounders, we estimate the joint causal effects on survival of initial and salvage treatments, that is, the effects of two-stage treatment sequences. For each individual treatment sequence, we estimate the survival distribution function and the mean restricted survival time. Different treatment sequences are then compared using these estimates and their corresponding covariances. Simulation studies were conducted to evaluate the performance of the methods, including their sensitivity to the violation of the assumption of no unmeasured confounders. The methods are illustrated by a retrospective study of patients with soft tissue sarcoma, which motivated this research. [source] THE CONTEXT OF MARRIAGE AND CRIME: GENDER, THE PROPENSITY TO MARRY, AND OFFENDING IN EARLY ADULTHOOD,CRIMINOLOGY, Issue 1 2007RYAN D. KING Marriage is central to theoretical debates over stability and change in criminal offending over the life course. Yet, unlike other social ties such as employment, marriage is distinct in that it cannot be randomly assigned in survey research to more definitively assess causal effects of marriage on offending. As a result, key questions remain as to whether different individual propensities toward marriage shape its salience as a deterrent institution. Building on these issues, the current research has three objectives. First, we use a propensity score matching approach to estimate causal effects of marriage on crime in early adulthood. Second, we assess sex differences in the effects of marriage on offending. Although both marriage and offending are highly gendered phenomena, prior work typically focuses on males. Third, we examine whether one's propensity to marry conditions the deterrent capacity of marriage. Results show that marriage suppresses offending for males, even when accounting for their likelihood to marry. Furthermore, males who are least likely to marry seem to benefit most from this institution. The influence of marriage on crime is less robust for females, where marriage reduces crime only for those with moderate propensities to marry. We discuss these findings in the context of recent debates concerning gender, criminal offending, and the life course. [source] Marijuana use and depression among adults: testing for causal associationsADDICTION, Issue 10 2006Valerie S. Harder ABSTRACT Aim To determine whether marijuana use predicts later development of depression after accounting for differences between users and non-users of marijuana. Design An ongoing longitudinal survey of 12 686 men and women beginning in 1979. Setting The National Longitudinal Survey of Youth of 1979, a nationally representative sample from the United States. Participants A total of 8759 adults (age range 29,37 years) interviewed in 1994 had complete data on past-year marijuana use and current depression. Measurements Self-reported past-year marijuana use was tested as an independent predictor of later adult depression using the Center for Epidemiologic Studies,Depression questionnaire. Individual's propensity to use marijuana was calculated using over 50 baseline covariates. Findings Before adjusting for group differences, the odds of current depression among past-year marijuana users is 1.4 times higher (95% CI: 1.1, 1.9) than the odds of depression among the non-using comparison group. After adjustment, the odds of current depression among past-year marijuana users is only 1.1 times higher than the comparison group (95% CI: 0.8, 1.7). Similarly, adjustment eliminates significant associations between marijuana use and depression in four additional analyses: heavy marijuana use as the risk factor, stratifying by either gender or age, and using a 4-year lag-time between marijuana use and depression. Conclusions After adjusting for differences in baseline risk factors of marijuana use and depression, past-year marijuana use does not significantly predict later development of depression. These findings are discussed in terms of their relevance for understanding possible causal effects of marijuana use on depression. [source] Right-wing authoritarianism and social dominance orientation and the dimensions of generalized prejudice: A longitudinal testEUROPEAN JOURNAL OF PERSONALITY, Issue 4 2010Frank Asbrock Abstract A Dual Process Model (DPM) approach to prejudice proposes that there should be at least two dimensions of generalized prejudice relating to outgroup stratification and social perception, which should be differentially predicted by Right-Wing Authoritarianism (RWA) and Social Dominance Orientation (SDO). The current study assessed the causal effects of SDO and RWA on three dimensions of prejudice using a full cross-lagged longitudinal sample (N,=,127). As expected, RWA, but not SDO, predicted prejudice towards ,dangerous' groups, SDO, but not RWA, predicted prejudice towards ,derogated' groups, and both RWA and SDO predicted prejudice towards ,dissident' groups. Results support previously untested causal predictions derived from the DPM and indicate that different forms of prejudice result from different SDO- and RWA-based motivational processes. Copyright © 2009 John Wiley & Sons, Ltd. [source] Estimating causal effects from observational data with a model for multiple biasINTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, Issue 2 2007Michael Höfler Abstract Conventional analyses of observational data may be biased due to confounding, sampling and measurement, and may yield interval estimates that are much too narrow because they do not take into account uncertainty about unknown bias parameters, such as misclassification probabilities. We used a simple, multiple bias adjustment method to estimate the causal effect of social anxiety disorder (SAD) on subsequent depression. A Monte Carlo sensitivity analysis was applied to data from the Early Developmental Stages of Psychiatry (EDSP) study, and bias due to confounding, sampling and measurement was modelled. With conventional logistic regression analysis, the risk for depression was elevated in the presence of SAD only in the older cohort (age 17,24 years at baseline assessment); odds ratio (OR) = 3.06, 95% confidence interval (CI) 1.64,5.70, adjusted for sex and age. The bias-adjusted estimate was 2.01 with interval limits of 0.61 and 9.71. Thus, given the data and the bias model used, there was considerably more uncertainty about the real effect, but the probability that SAD increases the risk for subsequent depression (OR > 1) was 88.6% anyway. Multiple bias modelling, if properly used, reveals the necessity for a better understanding of bias, suggesting a need to conduct larger and more adequate validation studies on instruments that are used to diagnose mental disorders. Copyright © 2007 John Wiley & Sons, Ltd. [source] Correlations between physiology and lifespan , two widely ignored problems with comparative studiesAGING CELL, Issue 4 2005John R. Speakman Summary Comparative differences between species provide a powerful source of information that may inform our understanding of the aging process. However, two problems regularly attend such analyses. The co-variation of traits with body mass is frequently ignored, along with the lack of independence of the data due to a shared phylogenetic history. These problems undermine the use of simple correlations between various factors and maximum lifespan potential (MLSP) across different species as evidence that the factors in question have causal effects on aging. Both of these problems have been widely addressed by comparative biologists working in fields other than aging research, and statistical solutions to these issues are available. Using these statistical approaches, of making analyses of residual traits with the effects of body mass removed, and deriving phylogenetically independent contrasts, will allow analyses of the relationships between physiology and maximum lifespan potential to proceed unhindered by these difficulties, potentially leading to many useful insights into the aging process. [source] Differential effects of high-quality child careJOURNAL OF POLICY ANALYSIS AND MANAGEMENT, Issue 4 2002Jennifer Hill In policy research a frequent aim is to estimate treatment effects separately by subgroups. This endeavor becomes a methodological challenge when the subgroups are defined by post-treatment, rather than pre-treatment, variables because if analyses are performed in the same way as with pre-treatment variables, causal interpretations are no longer valid. The authors illustrate a new approach to this challenge within the context of the Infant Health and Development Program, a multisite randomized study that provided at-risk children with intensive, center-based child care. This strategy is used to examine the differential causal effects of access to high-quality child care for children who would otherwise have participated in one of three child care options: no non-maternal care, home-based non-maternal care, and center-based care. Results of this study indicate that children participating in the first two types of care would have gained the most from high-quality center-based care and, moreover, would have more consistently retained the bulk of these positive benefits over time. These results may have implications for policy, particularly with regard to the debate about the potential implications of providing universal child care. © 2002 by the Association for Public Policy Analysis and Management. [source] Modelling method effects as individual causal effectsJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2008Steffi Pohl Summary., Method effects often occur when different methods are used for measuring the same construct. We present a new approach for modelling this kind of phenomenon, consisting of a definition of method effects and a first model, the method effect model, that can be used for data analysis. This model may be applied to multitrait,multimethod data or to longitudinal data where the same construct is measured with at least two methods at all occasions. In this new approach, the definition of the method effects is based on the theory of individual causal effects by Neyman and Rubin. Method effects are accordingly conceptualized as the individual effects of applying measurement method j instead of k. They are modelled as latent difference scores in structural equation models. A reference method needs to be chosen against which all other methods are compared. The model fit is invariant to the choice of the reference method. The model allows the estimation of the average of the individual method effects, their variance, their correlation with the traits (and other latent variables) and the correlation of different method effects among each other. Furthermore, since the definition of the method effects is in line with the theory of causality, the method effects may (under certain conditions) be interpreted as causal effects of the method. The method effect model is compared with traditional multitrait,multimethod models. An example illustrates the application of the model to longitudinal data analysing the effect of negatively (such as ,feel bad') as compared with positively formulated items (such as ,feel good') measuring mood states. [source] Teaching and Learning Guide for: Locutionary, Illocutionary, PerlocutionaryLINGUISTICS & LANGUAGE COMPASS (ELECTRONIC), Issue 9 2010Mikhail Kissine This guide accompanies the following article: Mikhail Kissine, ,Locutionary, Illocutionary, Perlocutionary', Language and Linguistics Compass 2/6 (2008) pp. 1189,1202. DOI: 10.1111/j.1749-818x.2008.00093.x. The terms locutionary act, illocutionary act and perlocutionary act originate from Austin's classical How to do with words. The corresponding notions, however, prove difficult to define. Yet, lack of careful delineating of each level can lead to important theoretical confusions. This Teaching and Learning Guide explains why proper understanding of Austin's trichotomy is crucial for semantics and pragmatics. Author's Introduction Most contemporary discussions in semantics and pragmatics employ , implicitly or explicitly , some or all of the concepts of locutionary,illocutionary or perlocutionary acts. These notions originate from Austin's posthumous and notoriously intricate book, How to do things with words. The point of interest for the linguist, however, is not so much the exegesis of Austin's ideas, as the precise delimitation of these levels of meaning. First, it is important to characterise the locutionary level , which falls short of any illocutionary force , to avoid contaminating analyses of utterance meanings with matters relative to the illocutionary level, viz. to the speech act performed. Second, the precise definition of illocutionary acts is an extremely difficult matter. However, the first, imperative step must be a clear demarcation between perlocutionary acts , relative to causal effects of the utterances , and the utterance's illocutionary force. Third, to assess theories of illocutionary forces, one must take into account the requirements for psychological and empirical plausibility. For instance, classical Gricean theories of illocutionary force attribution link it with the cognitive capacity to perform complex multi-layered mental state attributions, which is incompatible with the data available on the pragmatic and cognitive functioning of young children. In sum, gaining better understanding of the tripartite distinction between the locutionary, illocutionary and perlocutionary levels is not a taxonomical exercise, but a prerequisite for anyone willing to tackle semantic and/or pragmatic issues with the right tools. Suggested Reading Austin, J.L. (1975) How to do things with words, Second edition, Oxford, Oxford University Press. Lecture VIII. Difficult reading, but essential to understand Austin's intuitions and the origin of the debate. Strawson, P.F. (1964) "Intention and convention in speech acts", Philosophical Review, 73, 439,60. Classical criticism of Austin's claim abut the conventionality of illocutionary acts and first formulation of a Gricean theory of speech acts. Strawson, P.F. (1973) "Austin and ,Locutionary meaning'", in I. Berlin et al. (eds.) Essays on J.L. Austin, Oxford, Clarendon Press, 46,68. This equally classical paper sheds light onto the difficult notions of rhetic and locutionary acts; it paves the way for using these concepts interchangeably. Recanati, F. (1987) Meaning and Force. The pragmatics of performative utterances, Cambridge, Cambridge University Press. Chapter 9. This is a lucid discussion and elaboration of Strawson's conception of the locuitonary act as a potential for the illocutionary level. Wilson, D. and Sperber, D. (1988) "Mood and the analysis of non-declarative sentences", in J. Dancy et al. (eds.) Human Agency, Language, Duty and Value. Philosophical essayes in honour of J.O. Urmson, Stanford, Stanford University Press, 77,101. This paper gives important reasons for not confusing the analysis of mood , of the locutionary level , with the analysis of speech acts. Kissine, M. (2009) "Illocutionary forces and what is said", Mind and Language, 24, 122,38. Provides a definition of locutionary acts as linguistic representations of mental states, and lays grounds for a theory of speech acts as reasons to believe or to act. Bach, K. (1994) "Conversational impliciture", Mind and Language, 9, 124,62. An important defence of the distinction between illocutionary and locutionary acts. However, the reader should be warned that Bach conceives of locutionary acts as context-independent propositional radicals, which is not a self-evident position. Alston (2000) Illocutionary Acts and Sentence Meaning, Ithaca, Cornell University Press, Chapter 2. Contains a clear and lucid criticism of theories that confuse illocutionary and perlocutionary levels. Dominicy, M. (2008) "Epideictic rhetoric and the representation of human decision and choice", in K. Korta and J. Garmendia (eds.) Meaning, Intentions, and Argumentation, Stanford, CSLI, 179,207. This paper contains a useful test for distinguishing verbs that describe illocutionary acts form those that describe perlocutionary acts. It is also the first proposal to formulate the illocutionary/perlocutionary divide in Davidsonian terms. Focus Questions 1,What kind of philosophy of action is called for by the distinction between locutions, perlocutions and illocutions? 2,Should the locutionary level be always fully propositional? 3,Can illocutionary acts be characterised in terms of prototypical perlocutional effects? 4,Should illocutionary acts be divided in conventional (institutional) and non-conventional (non-insitutional) ones? 5,Are there good reasons for singling out a locutionary level? 6,,Does the attribution of illocutionary forces presuppose a complex mindreading process? Connexion with to Related Material in Lectures or Discussions 1,The distinction between the locutionary and illocutionary levels is crucial for any discussion about the semantics/pragmatics interface. Many scholars hastily characterise semantics as related to sentence-meaning and pragmatics as concerning the speech act performed. However, one should not take for granted that any level where the meaning is context-dependant is necessarily that of the illocutionary act performed. 2,This distinction can also be relevant for the discussions about the meaning of moods. For instance, the imperative mood is often analysed in terms of the directive illocutionary force. However, there are cases where utterances of imperative sentences do not correspond to a directive speech act. 3,The distinction between perlocutionary and illocutionary acts remains central for any attempt to classify or to define illocutionary forces. 4,Different conceptions of illocutionary acts are important for discussions about the ontogeny and phylogeny of the pragmatic dimension(s) of linguistic competence. [source] Mendelian randomization in nutritional epidemiologyNUTRITION REVIEWS, Issue 8 2009Lu Qi 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 proxies for environmental exposures of interest. Associations derived from Mendelian 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. [source] Update: Effects of Antioxidant and Non-Antioxidant Vitamin Supplementation on Immune FunctionNUTRITION REVIEWS, Issue 5 2007Aimee L. Webb PhD The purpose of this manuscript is to review the impact of supplementation with vitamins E and C, carotenoids, and the B vitamins on parameters of innate and adaptive immune function as reported from clinical trials in humans. There is evidence to support causal effects of supplementation with vitamins E and C and the carotenoids singly and in combination on selected aspects of immunity, including the functional capacity of innate immune cells, lymphocyte proliferation, and the delayed-type hypersensitivity (DTH) response. Controlled intervention trials of B vitamin-containing multivitamin supplements suggest beneficial effects on immune parameters and clinical outcomes in HIV-positive individuals [source] Choosing the Best Training Programme: Is there a Case for Statistical Treatment Rules?,OXFORD BULLETIN OF ECONOMICS & STATISTICS, Issue 2 2010Jonas Staghøj Abstract When treatment effects of active labour market programmes (ALMPs) are heterogeneous in an observable way across the population, the allocation of the unemployed into different programmes becomes particularly important. In this article, we present a statistical model that can be used to allocate unemployed into different ALMPs. The model presented is a duration model that uses the timing-of-events framework to identify causal effects. We compare different assignment rules, and the results suggest that a significant reduction in the average duration of unemployment may result if a statistical treatment rule is introduced. [source] Kontrolliert und repräsentativ: Beispiele zur Komplementarität von Labor- und FelddatenPERSPEKTIVEN DER WIRTSCHAFTSPOLITIK, Issue 2009Armin Falk Experiments offer highly controlled environments that allow precise testing and causal inferences. Survey and field data on the other hand provide information on large and representative samples of people interacting in their natural environment. We discuss several concrete examples how to combine lab and field data and how to exploit potential complementarities. One example describes an experiment, which is run with a representative sample to guarantee control and representativeness. The second example is based on the idea to experimentally validate survey instruments to ensure behavioral validity of instruments that can be used in existing panel data sets. The third example describes the possibility to use the lab to identify causal effects, which are tested in large data sets. Topics discussed in this article comprise the relation of cognitive skills (IQ) and risk and time preferences, determinants, prevalence and economic consequences of risk attitudes, selection into incentive schemes and the impact of unfair pay on stress. [source] Causal Inference with Differential Measurement Error: Nonparametric Identification and Sensitivity AnalysisAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 2 2010Kosuke Imai Political scientists have long been concerned about the validity of survey measurements. Although many have studied classical measurement error in linear regression models where the error is assumed to arise completely at random, in a number of situations the error may be correlated with the outcome. We analyze the impact of differential measurement error on causal estimation. The proposed nonparametric identification analysis avoids arbitrary modeling decisions and formally characterizes the roles of different assumptions. We show the serious consequences of differential misclassification and offer a new sensitivity analysis that allows researchers to evaluate the robustness of their conclusions. Our methods are motivated by a field experiment on democratic deliberations, in which one set of estimates potentially suffers from differential misclassification. We show that an analysis ignoring differential measurement error may considerably overestimate the causal effects. This finding contrasts with the case of classical measurement error, which always yields attenuation bias. [source] Portents of Pluralism: How Hybrid Regimes Affect Democratic TransitionsAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 3 2009Jason Brownlee The original studies of "competitive authoritarianism" and "hegemonic authoritarianism" inspected the occurrence of hybrid regimes during the 1990s but stopped short of testing their propensity for democratic change. This article assesses the causal effects of hybrid regimes, and the post,cold war period itself, on regime breakdown and democratization. Using a dataset of 158 regimes from 1975 to 2004, and a discrete measure for transitions to electoral democracy, I find that competitive authoritarian regimes are not especially prone to losing power but are significantly more likely to be followed by electoral democracy: vigorous electoral contestation does not independently subvert authoritarianism, yet it bodes well for democratic prospects once incumbents are overthrown. [source] Estimating the Causal Effects of Media Coverage on Policy-Specific KnowledgeAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 1 2009Jason Barabas Policy facts are among the most relevant forms of knowledge in a democracy. Although the mass media seem like an obvious source of policy-specific information, past research in this area has been plagued by design and methodological problems that have hindered causal inferences. Moreover, few studies include measures of media content, preventing researchers from being able to say what it is about media coverage that influences learning. We advance the literature by employing a simple but underutilized approach for estimating the causal effects of news coverage. Drawing upon a unique collection of cross-sectional survey data, we make within-survey/within-subjects comparisons under conditions of high and low media coverage. We show how the volume, breadth, and prominence of news media coverage increase policy-specific knowledge above and beyond common demographic factors. [source] Active labour market policy in East GermanyTHE ECONOMICS OF TRANSITION, Issue 4 2009Waiting for the economy to take off Matching estimation; causal effects; programme evaluation; panel data Abstract We investigate the effects of the most important East German active labour market programmes on the labour market outcomes of their participants. The analysis is based on a large and informative individual database derived from administrative data sources. Using matching methods, we find that over a horizon of 2.5 years after the start of the programmes, they fail to increase the employment chances of their participants in the regular labour market. However, the programmes may have other effects for their participants that may be considered important in the especially difficult situation experienced in the East German labour market. [source] Inpatient treatment in child and adolescent psychiatry , a prospective study of health gain and costsTHE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 12 2007Jonathan Green Background:, Inpatient treatment is a complex intervention for the most serious mental health disorders in child and adolescent psychiatry. This is the first large-scale study into its effectiveness and costs. Previous studies have been criticised for methodological weaknesses. Methods:, A prospective cohort study, including economic evaluation, conducted in 8 UK units (total n = 150) with one year follow-up after discharge. Patients acted as their own controls. Outcome measurement was the clinician-rated Childhood Global Assessment Scale (CGAS); researcher-rated health needs assessment; parent- and teacher-rated symptomatology. Results:, We found a significant (p < .001) and clinically meaningful 12-point improvement in CGAS following mean 16.6 week admission (effect size .92); this improvement was sustained at 1 year follow-up. Comparatively, during the mean 16.4 week pre-admission period there was a 3.7-point improvement (effect size .27). Health needs assessment showed similar gain (p < .001, effect size 1.25), as did teacher- and parent-rated symptoms. Improvement was found across all diagnoses. Longer stays, positive therapeutic alliance and better premorbid family functioning independently predicted better outcome. Mean cost of admission was £24,100; pre-admission and post-discharge support costs were similar. Conclusions:, Inpatient treatment is associated with substantive sustained health gain across a range of diagnoses. Lack of intensive outpatient-treatment alternatives limits any unqualified inference about causal effects, but the rigour of measurement here gives the strongest indication to date of the positive impact of admission for complex mental health problems in young people. [source] Ultrasonography and Sex Ratios in ChinaASIAN ECONOMIC POLICY REVIEW, Issue 1 2009Hongbin LI J13; J16; O10 This paper directly measures the causal effects of sex-selective abortions on the sex ratio at birth by exploiting the exogenous county-level variation in the availability of B-ultrasound machines. Using data from the 1990 Census of Fujian Province and local records on the introduction time of B-ultrasound machines, we find that the availability of B-ultrasound machines increases the sex ratio at birth by 0.025 in rural areas and 0.117 in urban areas. The rise of sex ratio is especially significant for second births in rural areas when the first birth is a girl. [source] Structural Nested Mean Models for Assessing Time-Varying Effect ModerationBIOMETRICS, Issue 1 2010Daniel Almirall Summary This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect.,Intermediate causal effects,that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias,variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study. [source] Estimation of the Causal Effects on Survival of Two-Stage Nonrandomized Treatment Sequences for Recurrent DiseasesBIOMETRICS, Issue 3 2006Xuelin Huang Summary In the treatment of cancer, patients commonly receive a variety of sequential treatments. The initial treatments administered following diagnosis can vary, as well as subsequent salvage regimens given after disease recurrence. This article considers the situation where neither initial treatments nor salvage treatments are randomized. Assuming there are no unmeasured confounders, we estimate the joint causal effects on survival of initial and salvage treatments, that is, the effects of two-stage treatment sequences. For each individual treatment sequence, we estimate the survival distribution function and the mean restricted survival time. Different treatment sequences are then compared using these estimates and their corresponding covariances. Simulation studies were conducted to evaluate the performance of the methods, including their sensitivity to the violation of the assumption of no unmeasured confounders. The methods are illustrated by a retrospective study of patients with soft tissue sarcoma, which motivated this research. [source] Analysis of Times to Repeated Events in Two-Arm Randomized Trials with Noncompliance and Dependent CensoringBIOMETRICS, Issue 4 2004Shigeyuki Matsui Summary This article develops randomization-based methods for times to repeated events in two-arm randomized trials with noncompliance and dependent censoring. Structural accelerated failure time models are assumed to capture causal effects on repeated event times and dependent censoring time, but the dependence structure among repeated event times and dependent censoring time is unspecified. Artificial censoring techniques to accommodate nonrandom noncompliance and dependent censoring are proposed. Estimation of the acceleration parameters are based on rank-based estimating functions. A simulation study is conducted to evaluate the performance of the developed methods. An illustration of the methods using data from an acute myeloid leukemia trial is provided. [source] Principal Stratification in Causal InferenceBIOMETRICS, Issue 1 2002Constantine E. Frangakis Summary. 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 under 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 formulate estimands based on principal stratification and principal causal effects and show their superiority. [source] Utilizing Propensity Scores to Estimate Causal Treatment Effects with Censored Time-Lagged DataBIOMETRICS, Issue 4 2001Kevin J. Anstrom Summary. Observational studies frequently are conducted to compare long-term effects of treatments. Without randomization, patients receiving one treatment are not guaranteed to be prognostically comparable to those receiving another treatment. Furthermore, the response of interest may be right-censored because of incomplete follow-up. Statistical methods that do not account for censoring and confounding may lead to biased estimates. This article presents a method for estimating treatment effects in nonrandomized studies with right-censored responses. We review the assumptions required to estimate average causal effects and derive an estimator for comparing two treatments by applying inverse weights to the complete cases. The weights are determined according to the estimated probability of receiving treatment conditional on covariates and the estimated treatment-specific censoring distribution. By utilizing martingale representations, the estimator is shown to be asymptotically normal and an estimator for the asymptotic variance is derived. Simulation results are presented to evaluate the properties of the estimator. These methods are applied to an observational data set of acute coronary syndrome patients from Duke University Medical Center to estimate the effect of a treatment strategy on the mean 5-year medical cost. [source] | |||||||||||||||||||||||||