Davood Tofighi
Biographic Data
| ID | 3531518 |
|---|---|
| NAME | Davood Tofighi |
| GIVEN NAMES | Davood |
| FAMILY NAME | Tofighi |
| SIGNATURE | TOFIGHI D |
| AFFILIATIONS | University of New Mexico |
| ORCID | 0000-0001-8523-7776 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 7 |
| WORKS AS AUTHOR | 10 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2007 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 1 |
An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation
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 …
Language-Internal Reanalysis of Clitic Placement in Heritage Grammars Reduces the Cost of Computation
The study offers novel evidence on the grammar and processing of clitic placement in heritage languages. Building on earlier findings of divergent clitic placement in heritage European Portuguese and Serbian, this study extends this line of inquiry to Bulgarian, a language where clitic placement is subject to strong prosodic constraints. We found that, in heritage Bulgarian, clitic placement is processed and rated differently than in the baseline…
Latent Class Mediation
Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation s…
The association of infant temperament and maternal sensitivity in preterm and full‐term infants
Infants who experience sensitive caregiving are at lower risk for numerous adverse outcomes. This is especially true for infants born preterm, leading them to be more susceptible to risks associated with poorer quality caregiving. Some research suggests that preterm and full‐term infants differ on temperament, which may contribute to these findings. This study aimed to investigate associations between infant temperament (negative emotionality, po…
Indirect Effects in Sequential Mediation Models
Complex mediation models, such as a two-mediator sequential model, have become more prevalent in the literature. To test an indirect effect in a two-mediator model, we conducted a large-scale Monte Carlo simulation study of the Type I error, statistical power, and confidence interval coverage rates of 10 frequentist and Bayesian confidence/credible intervals (CIs) for normally and nonnormally distributed data. The simulation included never-studie…
Assessing Omitted Confounder Bias in Multilevel Mediation Models
To draw valid inference about an indirect effect in a mediation model, there must be no omitted confounders. No omitted confounders means that there are no common causes of hypothesized causal relationships. When the no-omitted-confounder assumption is violated, inference about indirect effects can be severely biased and the results potentially misleading. Despite the increasing attention to address confounder bias in single-level mediation, this…
Single-Level and Multilevel Mediation Analysis
Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural equation modeling (SEM) in estimating mediation models with multiple mediators and multiple outcomes. We…
Statistical Mediation Analysis
Hypotheses regarding how an independent variable affects a dependent variable via a mediating variable are widespread in both basic and applied psychology. This chapter focuses on statistical and design methods to investigate mediation relations rather than the substantive importance of mediation that is described elsewhere (MacKinnon, 2008). The chapter starts with detailed information on the single mediator model including covariance between es…
RMediation
Centering predictor variables in cross-sectional multilevel models
Appropriately centering Level 1 predictors is vital to the interpretation of intercept and slope parameters in multilevel models (MLMs). The issue of centering has been discussed in the literature, but it is still widely misunderstood. The purpose of this article is to provide a detailed overview of grand mean centering and group mean centering in the context of 2-level MLMs. The authors begin with a basic overview of centering and explore the di…
Single-Level and Multilevel Mediation Analysis
Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural equation modeling (SEM) in estimating mediation models with multiple mediators and multiple outcomes. We…
Language-Internal Reanalysis of Clitic Placement in Heritage Grammars Reduces the Cost of Computation
The study offers novel evidence on the grammar and processing of clitic placement in heritage languages. Building on earlier findings of divergent clitic placement in heritage European Portuguese and Serbian, this study extends this line of inquiry to Bulgarian, a language where clitic placement is subject to strong prosodic constraints. We found that, in heritage Bulgarian, clitic placement is processed and rated differently than in the baseline…
Centering predictor variables in cross-sectional multilevel models
Appropriately centering Level 1 predictors is vital to the interpretation of intercept and slope parameters in multilevel models (MLMs). The issue of centering has been discussed in the literature, but it is still widely misunderstood. The purpose of this article is to provide a detailed overview of grand mean centering and group mean centering in the context of 2-level MLMs. The authors begin with a basic overview of centering and explore the di…
RMediation
Statistical Mediation Analysis
Hypotheses regarding how an independent variable affects a dependent variable via a mediating variable are widespread in both basic and applied psychology. This chapter focuses on statistical and design methods to investigate mediation relations rather than the substantive importance of mediation that is described elsewhere (MacKinnon, 2008). The chapter starts with detailed information on the single mediator model including covariance between es…
Single-Level and Multilevel Mediation Analysis
Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural equation modeling (SEM) in estimating mediation models with multiple mediators and multiple outcomes. We…
Assessing Omitted Confounder Bias in Multilevel Mediation Models
To draw valid inference about an indirect effect in a mediation model, there must be no omitted confounders. No omitted confounders means that there are no common causes of hypothesized causal relationships. When the no-omitted-confounder assumption is violated, inference about indirect effects can be severely biased and the results potentially misleading. Despite the increasing attention to address confounder bias in single-level mediation, this…
Indirect Effects in Sequential Mediation Models
Complex mediation models, such as a two-mediator sequential model, have become more prevalent in the literature. To test an indirect effect in a two-mediator model, we conducted a large-scale Monte Carlo simulation study of the Type I error, statistical power, and confidence interval coverage rates of 10 frequentist and Bayesian confidence/credible intervals (CIs) for normally and nonnormally distributed data. The simulation included never-studie…
Latent Class Mediation
Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation s…
The association of infant temperament and maternal sensitivity in preterm and full‐term infants
Infants who experience sensitive caregiving are at lower risk for numerous adverse outcomes. This is especially true for infants born preterm, leading them to be more susceptible to risks associated with poorer quality caregiving. Some research suggests that preterm and full‐term infants differ on temperament, which may contribute to these findings. This study aimed to investigate associations between infant temperament (negative emotionality, po…
An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation
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 …
Language-Internal Reanalysis of Clitic Placement in Heritage Grammars Reduces the Cost of Computation
The study offers novel evidence on the grammar and processing of clitic placement in heritage languages. Building on earlier findings of divergent clitic placement in heritage European Portuguese and Serbian, this study extends this line of inquiry to Bulgarian, a language where clitic placement is subject to strong prosodic constraints. We found that, in heritage Bulgarian, clitic placement is processed and rated differently than in the baseline…
Computer Science (8 works) · Mathematics (8 works) · Statistics (8 works) · Econometrics (7 works) · Psychology (7 works) · Mediation (5 works) · Structural equation modeling (4 works) · Advanced Causal Inference Techniques (3 works) · Artificial Intelligence (3 works) · Multilevel model (3 works)