Satoshi Usami
Biographic Data
| ID | 6629974 |
|---|---|
| NAME | Satoshi Usami |
| GIVEN NAMES | Satoshi |
| FAMILY NAME | Usami |
| SIGNATURE | USAMI S |
| AFFILIATIONS | The University of Tokyo |
| ORCID | 0000-0002-5670-2242 |
| VERIFIED | Yes |
| TOTAL WORKS | 17 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 17 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
A Two-Step Robust Estimation Approach for Inferring Within-Person Relations in Longitudinal Design
Psychological researchers have shown an interest in disaggregating within-person variability from between-person differences. This paper provides a tutorial, simulation, and illustrative example of a new approach proposed by Usami (Citation2023). This approach consists of a two-step procedure: within-person variability scores (WPVS) for each person, which are disaggregated from the stable traits of that person, are predicted using structural equa…
Confidence Interval-Based Determinations for Optimal Sample Sizes and Designs in a Random Intercept Panel Model
Adolescent psychotic experiences before and during the Covid ‐19 pandemic
BACKGROUND: Understanding the etiology of psychosis is essential to the development of preventive interventions. The COVID-19 pandemic provides a rare natural experiment that can expand our understanding of the role of social factors in the trajectories and etiology of psychosis across adolescence, particularly in Tokyo where the prevalence of actual COVID-19 infection remained low. We hypothesized that the likelihood of self-reporting psychotic …
Joint Effects in Cross-Lagged Panel Research Using Structural Nested Mean Models
A popular approach among psychological researchers for investigating causal relationships from panel data is cross-lagged panel modeling within the structural equation modeling (SEM) framework. However, SEM models are critiqued in the causal inference literature for relying on unnecessarily many parametric assumptions, increasing the risk of model misspecification and bias. Instead, the use of structural nested mean models (SNMMs) with G-estimati…
On the Differences between General Cross-Lagged Panel Model and Random-Intercept Cross-Lagged Panel Model
Many methods have been developed to infer reciprocal relations between longitudinally observed variables. Among them, the general cross-lagged panel model (GCLM) is the most recent development as a variant of the cross-lagged panel model (CLPM), while the random-intercept CLPM (RI-CLPM) has rapidly become a popular approach. In this article, we describe how common factors and cross-lagged parameters included in these models can be interpreted, us…
Longitudinal Bidirectional Relationships Between Maternal Depressive/Anxious Symptoms and Children's Tic Frequency in Early Adolescence
Background: Previous studies have revealed an association between maternal depressive/anxious symptoms and children's tics. However, the longitudinal relationships between these symptoms remain unclear. We examined the longitudinal relationships between maternal depressive/anxious symptoms and children's tic frequency in early adolescence with a population-based sample. Methods: The participants consisted of 3,171 children and their mothers from …
Factor Score Regression in Connected Measurement Models Containing Cross-Loadings
Factor Score Regression (FSR) methods have received increased interest in the quantitative literature, with Croon’s bias-correcting method gaining particular traction. By fixing measurement parameters in place in an initial step, FSR methods aim to stymie the proliferation of bias in larger structural models that may contain misspecification. Although Croon’s approach was originally derived for factor models exhibiting simple structure and condit…
A quasi‐cluster randomized controlled trial of a classroom‐based mental health literacy educational intervention to promote knowledge and help‐seeking/helping behavior in adolescents
INTRODUCTION: School-based education is a potentially effective approach for improving mental health literacy (MHL) in adolescents. This study evaluated the effects of the "Short MHL Program (SMHLP)", a brief (50 min), school teacher-led program, on MHL in adolescents in a quasi-cluster randomized controlled trial. METHODS: A total of 975 high school first graders (age 15-16) in Japan were allocated to classes such that gender and academic achiev…
Factor Score Regression in the Presence of Correlated Unique Factors
Recently, quantitative researchers have shown increased interest in two-step factor score regression (FSR) approaches to structural model estimation. A particularly promising approach proposed by Croon involves first extracting factor scores for each latent factor in a larger model, then correcting the variance−covariance matrix of the factor scores for bias before using this matrix as input data in a subsequent regression analysis or path model.…
Living in temporary housing and later psychological distress after the Great East Japan Earthquake of 2011
Living in temporary housing is a risk factor for psychological distress after a natural disaster. As temporary housing is an essential resource for those affected by disasters, investigation of factors which potentially mediate living in temporary housing and psychological distress is needed. This is a cohort study in general population of areas affected by the Great East Japan Earthquake in 2011. Data were obtained from self-report questionnaire…
Dog and Cat Ownership Predicts Adolescents’ Mental Well-Being
A potential association between pet ownership and mental well-being is suggested, but there is a shortage of high-quality longitudinal studies that consider probable differences among different species. We aimed to examine whether ownership of the most popular pets (dogs and cats) would predict mental well-being. The Tokyo Teen Cohort (TTC), a prospective population-based birth cohort study, had dog and cat ownership data at age 10 and mental wel…
A unified framework of longitudinal models to examine reciprocal relations.
Inferring reciprocal effects or causality between variables is a central aim of behavioral and psychological research. To address reciprocal effects, a variety of longitudinal models that include cross-lagged relations have been proposed in different contexts and disciplines. However, the relations between these cross-lagged models have not been systematically discussed in the literature. This lack of insight makes it difficult for researchers to…
Time-specific Errors in Growth Curve Modeling
Growth curve modeling (GCM) has been one of the most popular statistical methods to examine participants' growth trajectories using longitudinal data. In spite of the popularity of GCM, little attention has been paid to the possible influence of time-specific errors, which influence all participants at each timepoint. In this article, we demonstrate that the failure to take into account such time-specific errors in GCM produces considerable infla…
Trends in psychological distress and alcoholism after The Great East Japan Earthquake of 2011
Psychological distress deteriorated 2 years after the huge natural disaster, compared with 1 year after the disaster. Long-term mental health care is needed for those affected by natural disasters, particularly those who have suffered loss
On the Mathematical Relationship Between Latent Change Score and Autoregressive Cross-Lagged Factor Approaches
The present paper focuses on the relationship between latent change score (LCS) and autoregressive cross-lagged (ARCL) factor models in longitudinal designs. These models originated from different theoretical traditions for different analytic purposes, yet they share similar mathematical forms. In this paper, we elucidate the mathematical relationship between these models and show that the LCS model is reduced to the ARCL model when fixed effects…
Constrained k ‐means on cluster proportion and distances among clusters for longitudinal data analysis
Clustering individuals by measures of similarity or dissimilarity at trajectories of changes in longitudinal data enables determination of typical patterns of development and growth. The present research proposes a new constrained k ‐means method with lower bound constraints on cluster proportions and distances among clusters at focused variables and time points to fulfill various needs in clustering longitudinal data. The method assumes a large …
Generalized graded unfolding model with structural equation for subject parameters
The generalized graded unfolding model (GGUM) is capable of analyzing polytomous scored, unfolding data such as agree‐disagree responses to attitude statements. In the present study, we proposed a GGUM with structural equation for subject parameters, which enabled us to evaluate the relation between subject parameters and covariates and/or latent variables simultaneously, in order to avoid the influence of attenuation. Additionally, an algorithm …
Joint Effects in Cross-Lagged Panel Research Using Structural Nested Mean Models
A popular approach among psychological researchers for investigating causal relationships from panel data is cross-lagged panel modeling within the structural equation modeling (SEM) framework. However, SEM models are critiqued in the causal inference literature for relying on unnecessarily many parametric assumptions, increasing the risk of model misspecification and bias. Instead, the use of structural nested mean models (SNMMs) with G-estimati…
Generalized graded unfolding model with structural equation for subject parameters
The generalized graded unfolding model (GGUM) is capable of analyzing polytomous scored, unfolding data such as agree‐disagree responses to attitude statements. In the present study, we proposed a GGUM with structural equation for subject parameters, which enabled us to evaluate the relation between subject parameters and covariates and/or latent variables simultaneously, in order to avoid the influence of attenuation. Additionally, an algorithm …
Constrained k ‐means on cluster proportion and distances among clusters for longitudinal data analysis
Clustering individuals by measures of similarity or dissimilarity at trajectories of changes in longitudinal data enables determination of typical patterns of development and growth. The present research proposes a new constrained k ‐means method with lower bound constraints on cluster proportions and distances among clusters at focused variables and time points to fulfill various needs in clustering longitudinal data. The method assumes a large …
On the Mathematical Relationship Between Latent Change Score and Autoregressive Cross-Lagged Factor Approaches
The present paper focuses on the relationship between latent change score (LCS) and autoregressive cross-lagged (ARCL) factor models in longitudinal designs. These models originated from different theoretical traditions for different analytic purposes, yet they share similar mathematical forms. In this paper, we elucidate the mathematical relationship between these models and show that the LCS model is reduced to the ARCL model when fixed effects…
Trends in psychological distress and alcoholism after The Great East Japan Earthquake of 2011
Psychological distress deteriorated 2 years after the huge natural disaster, compared with 1 year after the disaster. Long-term mental health care is needed for those affected by natural disasters, particularly those who have suffered loss
Time-specific Errors in Growth Curve Modeling
Growth curve modeling (GCM) has been one of the most popular statistical methods to examine participants' growth trajectories using longitudinal data. In spite of the popularity of GCM, little attention has been paid to the possible influence of time-specific errors, which influence all participants at each timepoint. In this article, we demonstrate that the failure to take into account such time-specific errors in GCM produces considerable infla…
A unified framework of longitudinal models to examine reciprocal relations.
Inferring reciprocal effects or causality between variables is a central aim of behavioral and psychological research. To address reciprocal effects, a variety of longitudinal models that include cross-lagged relations have been proposed in different contexts and disciplines. However, the relations between these cross-lagged models have not been systematically discussed in the literature. This lack of insight makes it difficult for researchers to…
Factor Score Regression in Connected Measurement Models Containing Cross-Loadings
Factor Score Regression (FSR) methods have received increased interest in the quantitative literature, with Croon’s bias-correcting method gaining particular traction. By fixing measurement parameters in place in an initial step, FSR methods aim to stymie the proliferation of bias in larger structural models that may contain misspecification. Although Croon’s approach was originally derived for factor models exhibiting simple structure and condit…
A quasi‐cluster randomized controlled trial of a classroom‐based mental health literacy educational intervention to promote knowledge and help‐seeking/helping behavior in adolescents
INTRODUCTION: School-based education is a potentially effective approach for improving mental health literacy (MHL) in adolescents. This study evaluated the effects of the "Short MHL Program (SMHLP)", a brief (50 min), school teacher-led program, on MHL in adolescents in a quasi-cluster randomized controlled trial. METHODS: A total of 975 high school first graders (age 15-16) in Japan were allocated to classes such that gender and academic achiev…
Factor Score Regression in the Presence of Correlated Unique Factors
Recently, quantitative researchers have shown increased interest in two-step factor score regression (FSR) approaches to structural model estimation. A particularly promising approach proposed by Croon involves first extracting factor scores for each latent factor in a larger model, then correcting the variance−covariance matrix of the factor scores for bias before using this matrix as input data in a subsequent regression analysis or path model.…
Living in temporary housing and later psychological distress after the Great East Japan Earthquake of 2011
Living in temporary housing is a risk factor for psychological distress after a natural disaster. As temporary housing is an essential resource for those affected by disasters, investigation of factors which potentially mediate living in temporary housing and psychological distress is needed. This is a cohort study in general population of areas affected by the Great East Japan Earthquake in 2011. Data were obtained from self-report questionnaire…
Dog and Cat Ownership Predicts Adolescents’ Mental Well-Being
A potential association between pet ownership and mental well-being is suggested, but there is a shortage of high-quality longitudinal studies that consider probable differences among different species. We aimed to examine whether ownership of the most popular pets (dogs and cats) would predict mental well-being. The Tokyo Teen Cohort (TTC), a prospective population-based birth cohort study, had dog and cat ownership data at age 10 and mental wel…
On the Differences between General Cross-Lagged Panel Model and Random-Intercept Cross-Lagged Panel Model
Many methods have been developed to infer reciprocal relations between longitudinally observed variables. Among them, the general cross-lagged panel model (GCLM) is the most recent development as a variant of the cross-lagged panel model (CLPM), while the random-intercept CLPM (RI-CLPM) has rapidly become a popular approach. In this article, we describe how common factors and cross-lagged parameters included in these models can be interpreted, us…
Longitudinal Bidirectional Relationships Between Maternal Depressive/Anxious Symptoms and Children's Tic Frequency in Early Adolescence
Background: Previous studies have revealed an association between maternal depressive/anxious symptoms and children's tics. However, the longitudinal relationships between these symptoms remain unclear. We examined the longitudinal relationships between maternal depressive/anxious symptoms and children's tic frequency in early adolescence with a population-based sample. Methods: The participants consisted of 3,171 children and their mothers from …
Adolescent psychotic experiences before and during the Covid ‐19 pandemic
BACKGROUND: Understanding the etiology of psychosis is essential to the development of preventive interventions. The COVID-19 pandemic provides a rare natural experiment that can expand our understanding of the role of social factors in the trajectories and etiology of psychosis across adolescence, particularly in Tokyo where the prevalence of actual COVID-19 infection remained low. We hypothesized that the likelihood of self-reporting psychotic …
Joint Effects in Cross-Lagged Panel Research Using Structural Nested Mean Models
A popular approach among psychological researchers for investigating causal relationships from panel data is cross-lagged panel modeling within the structural equation modeling (SEM) framework. However, SEM models are critiqued in the causal inference literature for relying on unnecessarily many parametric assumptions, increasing the risk of model misspecification and bias. Instead, the use of structural nested mean models (SNMMs) with G-estimati…
Confidence Interval-Based Determinations for Optimal Sample Sizes and Designs in a Random Intercept Panel Model
A Two-Step Robust Estimation Approach for Inferring Within-Person Relations in Longitudinal Design
Psychological researchers have shown an interest in disaggregating within-person variability from between-person differences. This paper provides a tutorial, simulation, and illustrative example of a new approach proposed by Usami (Citation2023). This approach consists of a two-step procedure: within-person variability scores (WPVS) for each person, which are disaggregated from the stable traits of that person, are predicted using structural equa…
Mathematics (9 works) · Statistics (9 works) · Econometrics (7 works) · Psychology (7 works) · Medicine (6 works) · Psychometric Methodologies and Testing (6 works) · Advanced Causal Inference Techniques (5 works) · Clinical Psychology (5 works) · Computer Science (5 works) · Population (5 works)