Affinely invariant matching methods with discriminant mixtures of proportional ellipsoidally symmetric distributions

In observational studies designed to estimate the effects of interventions or exposures, such as cigarette smoking, it is desirable to try to control background differences between the treated group (e.g., current smokers) and the control group (e.g., never smokers) on covariates $X$ (e.g., age, education). Matched sampling attempts to effect this control by selecting subsets of the treated and control groups with similar distributions of such covariates. This paper examines the consequences of matching using affinely invariant methods when the covariate distributions are ``discriminant mixtures of proportional ellipsoidally symmetric'' (DMPES) distributions, a class herein defined, which generalizes the ellipsoidal symmetry class of Rubin and Thomas [Ann. Statist. 20 (1992) 1079--1093]. The resulting generalized results help indicate why earlier results hold quite well even when the simple assumption of ellipsoidal symmetry is not met [e.g., Biometrics 52 (1996) 249--264]. Extensions to conditionally affinely invariant matching with conditionally DMPES distributions are also discussed.Comment: Published at http://dx.doi.org/10.1214/009053606000000407 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn

The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements -- effect definitions with causal interpretation, clarification of assumptions required for effect identification, and an expanding array of options for effect estimation. However, the literature on these results is fast-growing and complex, which may be confusing to researchers unfamiliar with causal inference or unfamiliar with mediation. The goal of this paper is to help ease the understanding and adoption of causal mediation analysis. It starts by highlighting a key difference between the causal inference and traditional approaches to mediation analysis and making a case for the need for explicit causal thinking and the causal inference approach in mediation analysis. It then explains in as-plain-as-possible language existing effect types, paying special attention to motivating these effects with different types of research questions, and using concrete examples for illustration. This presentation differentiates two perspectives (or purposes of analysis): the explanatory perspective (aiming to explain the total effect) and the interventional perspective (asking questions about hypothetical interventions on the exposure and mediator, or hypothetically modified exposures). For the latter perspective, the paper proposes tapping into a general class of interventional effects that contains as special cases most of the usual effect types -- interventional direct and indirect effects, controlled direct effects and also a generalized interventional direct effect type, as well as the total effect and overall effect. This general class allows flexible effect definitions which better match many research questions than the standard interventional direct and indirect effects

Matching Methods for Causal Inference: A Review and a Look Forward

When estimating causal effects using observational data, it is desirable to replicate a randomized experiment as closely as possible by obtaining treated and control groups with similar covariate distributions. This goal can often be achieved by choosing well-matched samples of the original treated and control groups, thereby reducing bias due to the covariates. Since the 1970s, work on matching methods has examined how to best choose treated and control subjects for comparison. Matching methods are gaining popularity in fields such as economics, epidemiology, medicine and political science. However, until now the literature and related advice has been scattered across disciplines. Researchers who are interested in using matching methods---or developing methods related to matching---do not have a single place to turn to learn about past and current research. This paper provides a structure for thinking about matching methods and guidance on their use, coalescing the existing research (both old and new) and providing a summary of where the literature on matching methods is now and where it should be headed.Comment: Published in at http://dx.doi.org/10.1214/09-STS313 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

MatchIt: Nonparametric Preprocessing for Parametric Causal Inference

MatchIt implements the suggestions of Ho, Imai, King, and Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching methods. MatchIt implements a wide range of sophisticated matching methods, making it possible to greatly reduce the dependence of causal inferences on hard-to-justify, but commonly made, statistical modeling assumptions. The software also easily fits into existing research practices since, after preprocessing data with MatchIt, researchers can use whatever parametric model they would have used without MatchIt, but produce inferences with substantially more robustness and less sensitivity to modeling assumptions. MatchIt is an R program, and also works seamlessly with Zelig.

Multienergy vector modelling of a Scottish energy system : transitions and technology implications

The Scottish Government's commitment for 100% of electricity consumed in Scotland to be from renewable, zero-carbon sources by 2020 continues to drive change in the energy system alongside European and UK targets. The growth of renewables in Scotland is being seen at many scales including industrial, domestic and community generation. In these latter two cases a transition from the current 'top down' energy distribution system to a newer approach is emerging. The work of this paper will look at a 'bottom up' view that sees community led distributed energy at its centre. This paper uses the modelling tool HESA to investigate high penetrations of Distributed Generation (DG) in the Angus Region of Scotland. Installations of DG will follow Thousand Flowers transition pathway trajectory which sees more than 50% of electricity demand being supplied by DG by 2050. From this, insights around the technological and socio-political feasibility, consequences and implications of high penetrations of DG in the UK energy system are presented. Results demonstrate the influence that system change will have on regional and local emission levels under four separate scenarios. It is shown that the penetration of DG requires supplementary installations of reliable and long term storage alongside utilisation of transmission and transportation infrastructures to maximise the potential of distributed generation and maximise whole system benefits. Importantly, there must be a level of coordination and support to realise a shift to a highly distributed energy future to ensure there is a strong economic case with a reliable policy backing

Psychothérapie interpersonnelle (PTI) et Counseling interpersonnel (CIP) pour le traitement de la dépression post-partum

La dépression périnatale est un trouble prévalent qui comporte un degré élevé de morbidité à la fois chez la mère et chez le nourrisson. De nos jours, on dispose de traitements validés empiriquement pour traiter tant la dépression post-partum que la dépression pendant la grossesse. Parmi ces traitements, la psychothérapie interpersonnelle (PTI) a démontré son efficacité à traiter la dépression post-partum, qu’elle soit légère ou grave. En fait, l’évidence limitée des preuves de l’efficacité de la médication et les préoccupations au sujet de ses effets secondaires ont porté certaines personnes à proposer que la PTI soit la première option retenue pour traiter les femmes souffrant de dépression et qui allaitent. Des préoccupations semblables persistent au sujet de l’usage de médicaments pendant la grossesse. De récentes expériences et recherches cliniques portent à croire que le counseling interpersonnel (CIP) pourrait aussi s’avérer efficace chez certaines femmes en dépression post-partum. Forme abrégée de la PTI, le CIP semble être efficace pour traiter la dépression légère à modérée, et a l’avantage potentiel d’être plus facile à dispenser dans le cadre des soins primaires ou des milieux obstétricaux.Perinatal depression is a prevalent disorder with a high degree of morbidity for both mother and infant. There are now empirically validated treatments for both postpartum depression and depression during pregnancy. Among these is Interpersonal Psychotherapy (IPT), which has been shown to be effective for postpartum depression across the spectrum of mild to severe depression. In fact, the limited evidence of efficacy for medication and concern about medication side effects have led some to suggest that IPT should be the first line treatment for depressed breastfeeding women. There are similar concerns about medication usage during pregnancy. Recent clinical and research experience also suggest that Interpersonal Counseling (IPC) may be effective for selected postpartum women as well. IPC, an abbreviated form of IPT, appears to be effective for mild to moderate depression, and has the potential advantage of being more amenable to delivery in primary care or OB settings.La depresión perinatal es un trastorno prevaleciente que conlleva un grado elevado de morbilidad a la vez en la madre y el bebé lactante. Actualmente existen tratamientos validados empíricamente para tratar tanto la depresión posparto como la depresión durante el embarazo. Entre estos tratamientos, la psicoterapia interpersonal (PTI) ha demostrado su eficacia para tratar la depresión posparto, ya sea ligera o grave. De hecho, la evidencia limitada de las pruebas de eficacia de la medicación y las preocupaciones al respecto de sus efectos secundarios han llevado a algunas personas a proponer que la PTI sea la primera opción elegida para tratar a las mujeres que sufren de depresión posparto y que amamantan. Preocupaciones similares persisten al respecto del uso de medicamentos durante el embarazo. Recientes experimentos e investigaciones clínicas sugieren que el consejo interpersonal (CIP) podría también ser eficaz en algunas mujeres en depresión posparto. Una forma abreviada de la PTI, el CIP parece ser eficaz para tratar la depresión ligera o moderada y tiene la ventaja potencial de ser más fácil de dispensar en el marco de los cuidados primarios o del medio de la obstetricia.A depressão perinatal é um transtorno dominante que comporta um grau elevado de morbidade ao mesmo tempo na mãe e no bebê. Atualmente, dispõe-se de tratamentos empiricamente validados para tratar tanto a depressão pós-parto quanto a depressão durante a gravidez. Entre estes tratamentos, a psicoterapia interpessoal (TIP) demonstrou sua eficácia para tratar a depressão pós-parto, seja ela leve ou grave. De fato, a evidência limitada das provas da eficácia da medicação e as preocupações a respeito de seus efeitos colaterais levaram algumas pessoas a propor que a TIP seja a primeira opção escolhida para tratar as mulheres que sofrem de depressão e que amamentam. Preocupações semelhantes persistem a respeito do uso de medicamentos durante a gravidez. Recentes experiências e pesquisas clínicas levam a crer que o aconselhamento interpessoal (AIP) poderia também ser eficaz em algumas mulheres em depressão pós-parto. Forma resumida da TIP, o AIP demonstra ser eficaz para tratar a depressão leve a moderada, e tem a vantagem potencial de ser mais fácil a disponibilizar no quadro dos cuidados primários ou dos meios obstétricos