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Confidence limits for the indirect effect: Distribution of the product and resampling methods
 Multivariate Behavioral Research
, 2004
"... The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on cri ..."
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Cited by 229 (3 self)
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The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the biascorrected bootstrap the best method overall. An indirect effect implies a causal hypothesis whereby an independent variable causes a mediating variable which, in turn, causes a dependent
When moderation is mediated and mediation is moderated
 Journal of Personality and Social Psychology
, 2005
"... Procedures for examining whether treatment effects on an outcome are mediated and/or moderated have been well developed and are routinely applied. The mediation question focuses on the intervening mechanism that produces the treatment effect. The moderation question focuses on factors that affect th ..."
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Cited by 191 (3 self)
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Procedures for examining whether treatment effects on an outcome are mediated and/or moderated have been well developed and are routinely applied. The mediation question focuses on the intervening mechanism that produces the treatment effect. The moderation question focuses on factors that affect the magnitude of the treatment effect. It is important to note that these two processes may be combined in informative ways, such that moderation is mediated or mediation is moderated. Although some prior literature has discussed these possibilities, their exact definitions and analytic procedures have not been completely articulated. The purpose of this article is to define precisely both mediated moderation and moderated mediation and provide analytic strategies for assessing each.
Existing knowledge, knowledge creation capability, and the rate of new product introduction in hightechnology firms
 Academy of Management Journal
, 2005
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Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: new procedures and recommendations
 Psychological Methods
, 2006
"... The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances ..."
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Cited by 65 (3 self)
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The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects. Simulations show that the estimates are unbiased under most conditions. Confidence intervals based on a normal approximation or a simulated sampling distribution perform well when the random effects are normally distributed but less so when they are nonnormally distributed. These methods are further developed to address hypotheses of moderated mediation in the multilevel context. An example demonstrates the feasibility and usefulness of the proposed methods.
Causal inference in statistics: An Overview
, 2009
"... This review presents empirical researcherswith recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all ca ..."
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Cited by 61 (12 self)
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This review presents empirical researcherswith recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: (1) queries about the effects of potential interventions, (also called “causal effects ” or “policy evaluation”) (2) queries about probabilities of counterfactuals, (including assessment of “regret, ” “attribution” or “causes of effects”) and (3) queries about direct and indirect effects (also known as “mediation”). Finally, the paper defines the formal and conceptual relationships between the structural and potentialoutcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both.
Attachment, social competencies, social support and interpersonal process in psychotherapy
 Psychotherapy Research
, 2000
"... In this survey study of 430 undergraduates, elements of the social competencies and interpersonal processes model (B. Mallinckrodt, 2000) were tested. Two social competencies were hypothesized to mediate the direct effects of 2 independent variables, attachment anxiety and avoidance, on 2 outcomes, ..."
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Cited by 52 (8 self)
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In this survey study of 430 undergraduates, elements of the social competencies and interpersonal processes model (B. Mallinckrodt, 2000) were tested. Two social competencies were hypothesized to mediate the direct effects of 2 independent variables, attachment anxiety and avoidance, on 2 outcomes, psychological distress and perceived social support. Social selfefficacy was expected to be a significant mediator only for attachment anxiety. Emotional awareness, construed as low levels of alexithymia, was expected to be a significant mediator only for attachment avoidance. A bootstrap method was used to estimate the significance of indirect effects. Structural equation analyses suggested that, instead of specialized significant parings of one mediator with one independent variable, both social selfefficacy and emotional awareness served as significant mediators for both attachment anxiety and attachment avoidance.
Two replicable suppressor situations in personality research
 Multivariate Behavioral Research
, 2004
"... Suppressor situations occur when the addition of a new predictor improves the validity of a predictor variable already in the equation. A common allegation is that suppressor effects rarely replicate and have little substantive import. We present substantive examples from two established research do ..."
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Cited by 45 (6 self)
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Suppressor situations occur when the addition of a new predictor improves the validity of a predictor variable already in the equation. A common allegation is that suppressor effects rarely replicate and have little substantive import. We present substantive examples from two established research domains to counter this skepticism. In the first domain, we show how measures of guilt and shame act consistently as mutual suppressors: Adding shame into a regression equation increases the negative association between guilt and aggression, whereas adding guilt increases the positive association between shame and aggression. In the second domain, we show how the effects of selfesteem and narcissism operate consistently as mutual suppressors: That is, adding narcissism into a regression equation increases the negative association between selfesteem and antisocial behavior, whereas adding selfesteem increases the positive association between narcissism and antisocial behavior. Discussion addresses the different implications for suppressors in theoretical and variable selection applications.
Yes, But What’s the Mechanism? (Don’t Expect an Easy Answer)
"... Psychologists increasingly recommend experimental analysis of mediation. This is a step in the right direction because mediation analyses based on nonexperimental data are likely to be biased and because experiments, in principle, provide a sound basis for causal inference. But even experiments cann ..."
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Cited by 44 (0 self)
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Psychologists increasingly recommend experimental analysis of mediation. This is a step in the right direction because mediation analyses based on nonexperimental data are likely to be biased and because experiments, in principle, provide a sound basis for causal inference. But even experiments cannot overcome certain threats to inference that arise chiefly or exclusively in the context of mediation analysis—threats that have received little attention in psychology. The authors describe 3 of these threats and suggest ways to improve the exposition and design of mediation tests. Their conclusion is that inference about mediators is far more difficult than previous research suggests and is best tackled by an experimental research program that is specifically designed to address the challenges of mediation analysis.
Maladaptive perfectionism as a mediator and moderator between attachment and negative mood
 Journal of Counseling Psychology
, 2004
"... This study examined maladaptive perfectionism (concern over mistakes, doubts about one’s ability to accomplish tasks, and failure to meet high standards) as both a mediator and a moderator between adult attachment (anxiety and avoidance) and depressive mood (depression and hopelessness). Survey data ..."
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Cited by 43 (14 self)
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This study examined maladaptive perfectionism (concern over mistakes, doubts about one’s ability to accomplish tasks, and failure to meet high standards) as both a mediator and a moderator between adult attachment (anxiety and avoidance) and depressive mood (depression and hopelessness). Survey data were collected from 310 undergraduates and analyzed using structural equation modeling (SEM) methods. Results indicated that maladaptive perfectionism partially mediated the relationship between attachment anxiety and depressive mood and fully mediated the relationship between attachment avoidance and depressive mood. Bootstrap methods were used to assess the magnitude of the indirect effects. Significant moderator effects were also found with SEM methods. The association between attachment anxiety and depressive mood was stronger as perfectionism increased. Perfectionism was not a significant moderator for attachment avoidance and depressive mood. Throughout the past decade, there has been a growing interest among counseling psychologists in applying Bowlby’s (1973, 1980, 1988) attachment theory to understanding adult development and the counseling process (Lopez, 1995; Lopez & Brennan, 2000; Mallinckrodt, 2000). The initial formulations of adult attachment