David P Mackinnon | Arizona State University (original) (raw)

Papers by David P Mackinnon

Cogntiive and Behavioral Psychotherapy, 2013

Background-Cognitive-behavioural therapy (CBT) has proven to be effective for anxietybased school... more Background-Cognitive-behavioural therapy (CBT) has proven to be effective for anxietybased school refusal, but it is still unknown how CBT for school refusal works, or through which mechanisms. Aims-Innovative statistical approaches for analyzing small uncontrolled samples were used to investigate the role of self-efficacy in mediating CBT outcomes for anxiety-based school refusal. Method-Participants were 19 adolescents (12 to 17 years) who completed a manual-based cognitive-behavioural treatment. Primary outcomes (school attendance; school-related fear; anxiety) and secondary outcomes (depression; internalizing problems) were assessed at posttreatment and 2-month follow-up. Results-Post-treatment increases in school attendance and decreases in fear about attending school the next day were found to be mediated by self-efficacy. Mediating effects were not observed at 2-month follow-up. Conclusions-These findings provide partial support for the role of self-efficacy in mediating the outcome of CBT for school refusal. They contribute to a small body of literature suggesting that cognitive change enhances CBT outcomes for young people with internalizing problems. Regarding methodology, the product of coefficient test appears to be a valuable way to study mediation in outcome studies involving small samples.

Much of the existing longitudinal mediation literature focuses on panel data where relatively few... more Much of the existing longitudinal mediation literature focuses on panel data where relatively few repeated measures are collected over a relatively broad timespan. However, technological advances in data collection (e.g., smartphones, wearables) have led to a proliferation of short duration, densely collected longitudinal data in behavioral research. These intensive longitudinal data differ in structure and focus relative to traditionally collected panel data. As a result, existing methodological resources do not necessarily extend to nuances present in the recent influx of intensive longitudinal data and designs. In this tutorial, we first cover potential limitations of traditional longitudinal mediation models to accommodate unique characteristics of intensive longitudinal data. Then, we discuss how recently developed dynamic structural equation models (DSEM) may be well-suited for mediation modeling with intensive longitudinal data and can overcome some of the limitations associa...

Multivariate Behavioral Research, 2021

The literature on latent change score models does not discuss the importance of using a precise t... more The literature on latent change score models does not discuss the importance of using a precise time metric when structuring the data. This study examined the influence of time metric precision on model estimation, model interpretation, and parameter estimate accuracy in bivariate LCS (BLCS) models through simulation. Longitudinal data were generated with a panel study where assessments took place during a given time window with variation in start time and measurement lag. The data were analyzed using precise time metric, where variation in time was accounted for, and then analyzed using coarse time metric indicating only that the assessment took place during the time window. Results indicated that models estimated using the coarse time metric resulted in biased parameter estimates as well as larger standard errors and larger variances and covariances for intercept and slope. In particular, the coupling parameter estimates-which are unique to BLCS models-were biased with larger standard errors. An illustrative example of longitudinal bivariate relations between math and reading achievement in a nationally representative survey of children is then used to demonstrate how results and conclusions differ when using time metrics of varying precision. Implications and future directions are discussed.

Multiple Sclerosis and Related Disorders, 2021

OBJECTIVE To determine whether improvements in protective stepping experienced after repeated sup... more OBJECTIVE To determine whether improvements in protective stepping experienced after repeated support surface translations generalize to a different balance challenge in people with multiple sclerosis (PwMS) BACKGROUND: MS affects almost 1 million people in the United States and impairs balance and mobility. Perturbation practice can improve aspects of protective stepping in PwMS, but whether these improvements generalize is unknown. METHODS Fourteen PwMS completed two visits, 24hrs apart. The balance tasks included tether-release trials and support surface translations on a treadmill eliciting backward protective stepping. Margin of stability, step length, and step latency were calculated. Generalization was assessed via multilevel mediation models (MLMM) with bootstrapping to produce percentile and bias corrected confidence intervals RESULTS: There were no mediated effects for margin of stability or step latency; however, mediation was observed for step length, indicating that participants increased step length throughout the treadmill trials, and this generalized to tether-release trials DISCUSSION: MLMM may be useful for evaluating generalization of motor training to novel balance situations, particularly in small sample sizes. Using these analyses, we observed PwMS generalized improvements in step length, suggesting that aspects of protective step training may translate to improvements in other reactive balance tasks in PwMS.

Structural Equation Modeling: A Multidisciplinary Journal, 2020

Multivariate Behavioral Research, 2020

Abstract In psychology, there have been vast creative efforts in proposing new constructs and dev... more Abstract In psychology, there have been vast creative efforts in proposing new constructs and developing measures to assess them. Less effort has been spent in investigating construct overlap to prevent bifurcated literatures, wasted research efforts, and jingle-jangle fallacies. For example, researchers could gather validity evidence to evaluate if two measures with the same label actually assess different constructs (jingle fallacy), or if two measures with different labels actually assess the same construct (jangle fallacy). In this paper, we discuss the concept of extrinsic convergent validity, a source of validity evidence demonstrated when two measures of the same construct, or two measures of seemingly different constructs, have comparable correlations with external criteria. We introduce a formal approach to obtain extrinsic convergent validity evidence using tests of dependent correlations and evaluate the tests using Monte Carlo simulations. Also, we illustrate the methods by examining the overlap between the self-control and grit constructs, and the overlap among seven seemingly different measures of the connectedness to nature construct. Finally, we discuss how extrinsic convergent validity evidence supplements other sources of evidence that support validity arguments of construct overlap.

Multivariate Behavioral Research, 2019

Religion makes unique claims (e.g., the existence of supernatural agents) not found in other beli... more Religion makes unique claims (e.g., the existence of supernatural agents) not found in other belief systems, but is religion itself psychologically special? Furthermore, religion is related to many domains of psychological interest, such as morality, health and well-being, self-control, meaning, and death anxiety. Does religion act on these domains via special mechanisms that are unlike secular mechanisms? These could include mechanisms such as beliefs in supernatural agents, providing ultimate meaning, and providing literal immortality. We apply a critical eye to these questions of specialness and conclude that although it is clear that religion is psychologically important, there is not yet strong evidence that it is psychologically special, with the possible exception of its effects on health. We highlight what would be required of future research aimed at convincingly demonstrating that religion is indeed psychologically special, including careful definitions of religion and car...

Structural Equation Modeling: A Multidisciplinary Journal, 2022

Mechanisms of behavior change are the processes through which interventions are hypothesized to c... more Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

Evaluation & the Health Professions, 2022

In response to the importance of individual-level effects, the purpose of this paper is to descri... more In response to the importance of individual-level effects, the purpose of this paper is to describe the new randomization permutation (RP) test for a mediation mechanism for a single subject. We extend seminal work on permutation tests for individual-level data by proposing a test for mediation for one person. The method requires random assignment to the levels of the treatment variable at each measurement occasion, and repeated measures of the mediator and outcome from one subject. If several assumptions are met, the process by which a treatment changes an outcome can be statistically evaluated for a single subject, using the permutation mediation test method and the permutation confidence interval method for residuals. A simulation study evaluated the statistical properties of the new method suggesting that at least eight repeated measures are needed to control Type I error rates and larger sample sizes are needed for power approaching .8 even for large effects. The RP mediation t...

Journal of Clinical Psychology, 2020

MethodTwo hundred Hispanic emerging adults from Arizona (n = 99) and Florida (n = 101) completed ... more MethodTwo hundred Hispanic emerging adults from Arizona (n = 99) and Florida (n = 101) completed a cross‐sectional survey, and data were analyzed using hierarchical multiple regression and moderation analyses.ResultsHigher social media discrimination was associated with higher symptoms of depression and generalized anxiety. Moderation analyses indicated that higher social media discrimination was only associated with symptoms of depression and generalized anxiety among men, but not women.ConclusionThis is likely the first study on social media discrimination and mental health among emerging adults; thus, expanding this emerging field of research to a distinct developmental period.

Prevention Science, 2021

Third-variable effects, such as mediation and confounding, are core concepts in prevention scienc... more Third-variable effects, such as mediation and confounding, are core concepts in prevention science, providing the theoretical basis for investigating how risk factors affect behavior and how interventions change behavior. Another third variable, the collider, is not commonly considered but is also important for prevention science. This paper describes the importance of the collider effect as well as the similarities and differences between these three third-variable effects. The single mediator model in which the third variable (T) is a mediator of the independent variable (X) to dependent variable (Y) effect is used to demonstrate how to estimate each third-variable effect. We provide difference in coefficients and product of coefficients estimators of the effects and demonstrate how to calculate these values with real data. Suppression effects are defined for each type of third-variable effect. Future directions and implications of these results are discussed.

Structural Equation Modeling: A Multidisciplinary Journal, 2021

Multivariate Behavioral Research, 2020

Levine's Guide to SPSS for Analysis of Variance, 2003

Structural Equation Modeling: A Multidisciplinary Journal, 2015

One challenge in mediation analysis is to generate a confidence interval (CI) with high coverage ... more One challenge in mediation analysis is to generate a confidence interval (CI) with high coverage and power that maintains a nominal significance level for any well-defined function of indirect and direct effects in the general context of structural equation modeling (SEM). This study discusses a proposed Monte Carlo extension that finds the CIs for any well-defined function of the coefficients of SEM such as the product of k coefficients and the ratio of the contrasts of indirect effects, using the Monte Carlo method. Finally, we conduct a small-scale simulation study to compare CIs produced by the Monte Carlo, nonparametric bootstrap, and asymptotic-delta methods. Based on our simulation study, we recommend researchers use the Monte Carlo method to test a complex function of indirect effects.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 1998

Cogntiive and Behavioral Psychotherapy, 2013

Background-Cognitive-behavioural therapy (CBT) has proven to be effective for anxietybased school... more Background-Cognitive-behavioural therapy (CBT) has proven to be effective for anxietybased school refusal, but it is still unknown how CBT for school refusal works, or through which mechanisms. Aims-Innovative statistical approaches for analyzing small uncontrolled samples were used to investigate the role of self-efficacy in mediating CBT outcomes for anxiety-based school refusal. Method-Participants were 19 adolescents (12 to 17 years) who completed a manual-based cognitive-behavioural treatment. Primary outcomes (school attendance; school-related fear; anxiety) and secondary outcomes (depression; internalizing problems) were assessed at posttreatment and 2-month follow-up. Results-Post-treatment increases in school attendance and decreases in fear about attending school the next day were found to be mediated by self-efficacy. Mediating effects were not observed at 2-month follow-up. Conclusions-These findings provide partial support for the role of self-efficacy in mediating the outcome of CBT for school refusal. They contribute to a small body of literature suggesting that cognitive change enhances CBT outcomes for young people with internalizing problems. Regarding methodology, the product of coefficient test appears to be a valuable way to study mediation in outcome studies involving small samples.

Much of the existing longitudinal mediation literature focuses on panel data where relatively few... more Much of the existing longitudinal mediation literature focuses on panel data where relatively few repeated measures are collected over a relatively broad timespan. However, technological advances in data collection (e.g., smartphones, wearables) have led to a proliferation of short duration, densely collected longitudinal data in behavioral research. These intensive longitudinal data differ in structure and focus relative to traditionally collected panel data. As a result, existing methodological resources do not necessarily extend to nuances present in the recent influx of intensive longitudinal data and designs. In this tutorial, we first cover potential limitations of traditional longitudinal mediation models to accommodate unique characteristics of intensive longitudinal data. Then, we discuss how recently developed dynamic structural equation models (DSEM) may be well-suited for mediation modeling with intensive longitudinal data and can overcome some of the limitations associa...

Multivariate Behavioral Research, 2021

The literature on latent change score models does not discuss the importance of using a precise t... more The literature on latent change score models does not discuss the importance of using a precise time metric when structuring the data. This study examined the influence of time metric precision on model estimation, model interpretation, and parameter estimate accuracy in bivariate LCS (BLCS) models through simulation. Longitudinal data were generated with a panel study where assessments took place during a given time window with variation in start time and measurement lag. The data were analyzed using precise time metric, where variation in time was accounted for, and then analyzed using coarse time metric indicating only that the assessment took place during the time window. Results indicated that models estimated using the coarse time metric resulted in biased parameter estimates as well as larger standard errors and larger variances and covariances for intercept and slope. In particular, the coupling parameter estimates-which are unique to BLCS models-were biased with larger standard errors. An illustrative example of longitudinal bivariate relations between math and reading achievement in a nationally representative survey of children is then used to demonstrate how results and conclusions differ when using time metrics of varying precision. Implications and future directions are discussed.

Multiple Sclerosis and Related Disorders, 2021

OBJECTIVE To determine whether improvements in protective stepping experienced after repeated sup... more OBJECTIVE To determine whether improvements in protective stepping experienced after repeated support surface translations generalize to a different balance challenge in people with multiple sclerosis (PwMS) BACKGROUND: MS affects almost 1 million people in the United States and impairs balance and mobility. Perturbation practice can improve aspects of protective stepping in PwMS, but whether these improvements generalize is unknown. METHODS Fourteen PwMS completed two visits, 24hrs apart. The balance tasks included tether-release trials and support surface translations on a treadmill eliciting backward protective stepping. Margin of stability, step length, and step latency were calculated. Generalization was assessed via multilevel mediation models (MLMM) with bootstrapping to produce percentile and bias corrected confidence intervals RESULTS: There were no mediated effects for margin of stability or step latency; however, mediation was observed for step length, indicating that participants increased step length throughout the treadmill trials, and this generalized to tether-release trials DISCUSSION: MLMM may be useful for evaluating generalization of motor training to novel balance situations, particularly in small sample sizes. Using these analyses, we observed PwMS generalized improvements in step length, suggesting that aspects of protective step training may translate to improvements in other reactive balance tasks in PwMS.

Structural Equation Modeling: A Multidisciplinary Journal, 2020

Multivariate Behavioral Research, 2020

Abstract In psychology, there have been vast creative efforts in proposing new constructs and dev... more Abstract In psychology, there have been vast creative efforts in proposing new constructs and developing measures to assess them. Less effort has been spent in investigating construct overlap to prevent bifurcated literatures, wasted research efforts, and jingle-jangle fallacies. For example, researchers could gather validity evidence to evaluate if two measures with the same label actually assess different constructs (jingle fallacy), or if two measures with different labels actually assess the same construct (jangle fallacy). In this paper, we discuss the concept of extrinsic convergent validity, a source of validity evidence demonstrated when two measures of the same construct, or two measures of seemingly different constructs, have comparable correlations with external criteria. We introduce a formal approach to obtain extrinsic convergent validity evidence using tests of dependent correlations and evaluate the tests using Monte Carlo simulations. Also, we illustrate the methods by examining the overlap between the self-control and grit constructs, and the overlap among seven seemingly different measures of the connectedness to nature construct. Finally, we discuss how extrinsic convergent validity evidence supplements other sources of evidence that support validity arguments of construct overlap.

Multivariate Behavioral Research, 2019

Religion makes unique claims (e.g., the existence of supernatural agents) not found in other beli... more Religion makes unique claims (e.g., the existence of supernatural agents) not found in other belief systems, but is religion itself psychologically special? Furthermore, religion is related to many domains of psychological interest, such as morality, health and well-being, self-control, meaning, and death anxiety. Does religion act on these domains via special mechanisms that are unlike secular mechanisms? These could include mechanisms such as beliefs in supernatural agents, providing ultimate meaning, and providing literal immortality. We apply a critical eye to these questions of specialness and conclude that although it is clear that religion is psychologically important, there is not yet strong evidence that it is psychologically special, with the possible exception of its effects on health. We highlight what would be required of future research aimed at convincingly demonstrating that religion is indeed psychologically special, including careful definitions of religion and car...

Structural Equation Modeling: A Multidisciplinary Journal, 2022

Mechanisms of behavior change are the processes through which interventions are hypothesized to c... more Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

Evaluation & the Health Professions, 2022

In response to the importance of individual-level effects, the purpose of this paper is to descri... more In response to the importance of individual-level effects, the purpose of this paper is to describe the new randomization permutation (RP) test for a mediation mechanism for a single subject. We extend seminal work on permutation tests for individual-level data by proposing a test for mediation for one person. The method requires random assignment to the levels of the treatment variable at each measurement occasion, and repeated measures of the mediator and outcome from one subject. If several assumptions are met, the process by which a treatment changes an outcome can be statistically evaluated for a single subject, using the permutation mediation test method and the permutation confidence interval method for residuals. A simulation study evaluated the statistical properties of the new method suggesting that at least eight repeated measures are needed to control Type I error rates and larger sample sizes are needed for power approaching .8 even for large effects. The RP mediation t...

Journal of Clinical Psychology, 2020

MethodTwo hundred Hispanic emerging adults from Arizona (n = 99) and Florida (n = 101) completed ... more MethodTwo hundred Hispanic emerging adults from Arizona (n = 99) and Florida (n = 101) completed a cross‐sectional survey, and data were analyzed using hierarchical multiple regression and moderation analyses.ResultsHigher social media discrimination was associated with higher symptoms of depression and generalized anxiety. Moderation analyses indicated that higher social media discrimination was only associated with symptoms of depression and generalized anxiety among men, but not women.ConclusionThis is likely the first study on social media discrimination and mental health among emerging adults; thus, expanding this emerging field of research to a distinct developmental period.

Prevention Science, 2021

Third-variable effects, such as mediation and confounding, are core concepts in prevention scienc... more Third-variable effects, such as mediation and confounding, are core concepts in prevention science, providing the theoretical basis for investigating how risk factors affect behavior and how interventions change behavior. Another third variable, the collider, is not commonly considered but is also important for prevention science. This paper describes the importance of the collider effect as well as the similarities and differences between these three third-variable effects. The single mediator model in which the third variable (T) is a mediator of the independent variable (X) to dependent variable (Y) effect is used to demonstrate how to estimate each third-variable effect. We provide difference in coefficients and product of coefficients estimators of the effects and demonstrate how to calculate these values with real data. Suppression effects are defined for each type of third-variable effect. Future directions and implications of these results are discussed.

Structural Equation Modeling: A Multidisciplinary Journal, 2021

Multivariate Behavioral Research, 2020

Levine's Guide to SPSS for Analysis of Variance, 2003

Structural Equation Modeling: A Multidisciplinary Journal, 2015

One challenge in mediation analysis is to generate a confidence interval (CI) with high coverage ... more One challenge in mediation analysis is to generate a confidence interval (CI) with high coverage and power that maintains a nominal significance level for any well-defined function of indirect and direct effects in the general context of structural equation modeling (SEM). This study discusses a proposed Monte Carlo extension that finds the CIs for any well-defined function of the coefficients of SEM such as the product of k coefficients and the ratio of the contrasts of indirect effects, using the Monte Carlo method. Finally, we conduct a small-scale simulation study to compare CIs produced by the Monte Carlo, nonparametric bootstrap, and asymptotic-delta methods. Based on our simulation study, we recommend researchers use the Monte Carlo method to test a complex function of indirect effects.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 1998