Optimization Methods
Mediation
This paper discusses the uses and benefits of moderation an mediation analysis in health related studies.
In both intervention and observational research, mediation analyses are central to testing these theories because they describe how or why an effect occurs. The purpose of this chapter is to outline these new developments in four major areas: (1) significance testing and confidence interval estimation of the mediated effect, (2) mediation analysis in groups, (3) assumptions of and approaches to causal inference for assessing mediation, and (4) longitudinal mediation models.
In this journal article, our lab demonstrates why normal theory confidence intervals for indirect effects are often less accurate than those obtained from the asymmetric distribution of the product or from bootstrapping.
In this paper, we compare and contrast three different methods for assessing sensitivity to confounding and describes the graphical depiction of these methods.
This article discusses the conditions under which mediation may be present when an intervention effect does not have a statistically significant effect and why mediation should always be considered important.
This article presents the necessary sample sizes for six of the most common and the most recommended tests of mediation for various combinations of parameters, to provide a guide for researchers when designing studies or applying for grants.
In this paper, authors discuss ways of increasing power in mediation model without increasing sample size. They discuss implications for health researchers using these methods.
This article proposes and evaluates a method to test for mediation in multilevel data sets formed when an intervention administered to intact groups is designed to produce change in individual mediator and outcome variables.
The purpose of this article is to describe mediating variables and moderating variables and provide reasons for integrating them in outcome studies. Separate sections describe examples of moderating and mediating variables and the simplest statistical model for investigating each variable.
This study introduces principles of direction dependence which can be used to empirically evaluate competing explanatory theories. Researchers show that, under certain conditions, third higher moments of variables (i.e., skewness and co-skewness) can be used to uniquely identify the direction of a mediator-outcome relation.
In this study from IEL, we describe methods to estimate causal direct and indirect effects and reports the results of a large Monte Carlo simulation study on the performance of the ordinary regression and modern causal mediation analysis methods, including a previously untested doubly robust sequential g-estimation method, when there are confounders of the mediator-to-outcome relation.
The purpose of the present study was to systematically examine the impact of mediator noninvariance on the Type I error rates, statistical power, and relative bias in parameter estimates of the mediated effect in the single mediator model. The results of a large simulation study indicated that, in general, the mediated effect was robust to violations of invariance in loadings.
In this study, we assess the impact of an autism teacher training program being implemented in 11 cities across North-East Turkey. The study aims to answer for whom the training works the best, and identify the mechanisms of change in order to achieve the most cost and outcome-effective version of the training program.
In this study, we employ an actor-partner interdependence mediation model to examine how parents’ justifying attitudes towards violence against women relate to their own (actor effects) and their partners’ (partner effects) level of parental involvement, which then influence their preschool children’s early development using a large data set from low and middle income countries.
In this study we focus on short term educational sojourn of Western students in a Majority World country and examine the effect of personal characteristics and cultural evaluation of the sojourners on their experience.
In this paper, the authors examined mediators and moderators of change in conduct problems, in a multiagency randomized trial of the Incredible Years parenting program.
Using the Early Childhood Longitudinal Study, Kindergarten Class of 1998–1999 (N = 21,255), this study examined dual components of family income and material hardship along with parent mediators of stress, positive parenting, and investment as predictors of 6-year-old children’s cognitive skills and social – emotional competence.
Using a sample of 731 families receiving services from a national food supplement and nutrition program, this study examined whether reductions in maternal depression serve as a mediator in relation to changes associated with a family-based intervention.
This study examines whether, and to which extent, the associations between conflict intensity and children’s and early adolescents’ functioning problems are mediated through parental harsh discipline in a post-armed conflict setting which is Iraq.
This book chapter describes examples of mediation that form the backbone of drug prevention theory and quantitative mediation analysis in drug prevention research.
The purpose of this paper is to present data on moderators and mediators of treatment response from the Multimodal Treatment Study of Children With ADHD (MTA).
Factorial Design
An investigator who plans to conduct an experiment with multiple independent variables must decide whether to use a complete or reduced factorial design. This article advocates a resource management perspective on making this decision, in which the investigator seeks a strategic balance between service to scientific objectives and economy.
In this article, the authors describe the methods of a novel factorial design study to aid the development of a positive psychology-based intervention for acute coronary syndrome patients and aim to provide preliminary feasibility data on study implementation.
Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components especially in clinical psychology. This article provides insights on implementing clinical research using factorial designs.
The factorial survey is an experimental technique that allows testing hypotheses about causal relations. The article focuses on the application of the factorial survey design to social- psychological studies.
Subgroup/Moderator Analysis
This work proposes a methodology for analyzing the impacts of social programs on previously unexamined subgroups. Rather than using a single trait to define subgroups—which is currently the dominant method of subgroup analysis—the proposed approach estimates the impact of programs on subgroups identified by a post-treatment choice while still maintaining the integrity of the experimental research design.
The purpose of this article is to describe mediating variables and moderating variables and provide reasons for integrating them in outcome studies. Separate sections describe examples of moderating and mediating variables and the simplest statistical model for investigating each variable.
This editorial piece discusses the benefits and uses of subgroup analysis for prevention and intervention research.
This study examines the efficacy of a school-based mindfulness intervention on mental health and emotion regulation outcomes among adolescents in a wait-list controlled trial. The study also explores mediators and moderators of intervention effects.
Using data from the Multimodal Treatment Study of Children With ADHD (MTA), the authors investigate Moderators and mediators of treatment outcome to understanding for whom and how interventions work.
Latent Profile Analysis
The present guide provides a practical guide to conducting latent profile analysis (LPA) in the Mplus software system. This guide is intended for researchers familiar with some latent variable modeling but not LPA specifically. A general procedure for conducting LPA is provided in six steps.
This article shows a demonstration of latent class analysis as an alternative perspective on subgroup analysis in prevention and treatment using data from the National Longitudinal Survey of Adolescent Health.
This study uses latent profile approach to examine the developmental precursors of different health profiles in a representative sample of 443 African American youths living in the rural South.
The current study aims to explore if subgroups of youth, identified by applying latent profile analysis to parent-reported symptoms, age, and gender, are better served by specific usual care services using archival data.
This study examines the individual variability in parenting profiles and predictors of change and establish the effects of an intervention with disadvantaged mothers using latent class analysis which is a similar method to latent profile analysis. While latent profile analysis applies to continuous response variables, latent class analysis applies to categorical ones.