K Yamaguchi
Biographic Data
| ID | 1098 |
|---|---|
| NAME | K Yamaguchi |
| GIVEN NAMES | K |
| FAMILY NAME | Yamaguchi |
| SIGNATURE | YAMAGUCHI K |
| AFFILIATIONS | University of Chicago |
| ORCID | 0000-0002-9921-6412 |
| VERIFIED | Yes |
| TOTAL WORKS | 20 |
| TOTAL CITATIONS | 116 |
| AUTHOR COUNT | 20 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1983 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 5 |
Multivariate Multinomial Logit Models with Associations among Dependent Variables
The authors introduce a new group of multinomial logit models with special contrasts to identify covariate effects on multiple categorical dependent variables that are strongly associated with each other. The authors first develop the method for a case with two dependent variables and then extend the method to a case with three dependent variables. The model can account for both nominal and ordinal scales of categorical dependent variables. The a…
Awareness Context and Social Recognition: Reconsidering a Case Study of “Dialogue” between Different Ethnic Persons in Japan
This study incorporates Honneth’s social recognition into awareness context theory by reconsidering a case study of the dialogue between Zainichi Korean and Japanese people in Japan. It revitalizes the theoretical significance of Strauss’ symbolic interactionism in terms of its focus on power dynamics and conflicts between the majority and minorities that differ in the cultural or ethnic background in modern global society. Incorporating critical…
Full Issue
This special issue of the Humboldt Journal of Social Relations visits one of the most polarizing policy debates in the US. In 2012, voters in Washington and Colorado passed initiatives that legalized the recreational use of marijuana. In fact, there were about 75,000 more votes cast in support of marijuana legalization in Colorado than were given to reelect President Obama. Yet according to a recent poll conducted by the Pew Research Center, Demo…
A New RCM Approach to Survival Analysis: The Conditional-Incidence-Rate Model
This article introduces a new causal analytic method for survival analysis that retains the framework of Rubin’s causal model as an alternative to the marginal structural model (MSM). The major limitation of the MSM is a systematic bias in the effects of past treatments when the method is applied to the hazard rate analysis of nonrepeatable events in the presence of unobserved heterogeneity. This systematic bias is demonstrated in the article. Th…
Multigroup Segregation Analyses with Covariates
The author introduces methods for the decomposition analysis of multigroup segregation measured by the index of dissimilarity, the squared coefficient of variation, and Theil’s entropy measure. Using a new causal framework, the author takes a unified approach to the decomposition analysis by specifying conditions that must be satisfied to decompose segregation into unexplained and explained components. Here, the unexplained component represents t…
Decomposition Analysis of Segregation
Although substantive studies on segregation, such as residential or school segregation by race and occupational segregation by gender, are many in sociology, the analytical methodology is almost exclusively focused on measurement issues. The author introduces a set of two statistical models for the decomposition analysis of segregation. These models can be regarded as a tool to analyze whether one dimension of racial or gender inequality is relat…
Decomposition of Gender or Racial Inequality with Endogenous Intervening Covariates: An Extension of the DiNardo-Fortin-Lemieux Method
This paper begins by clarifying that propensity-score weighting in the DiNardo-Fortin-Lemieux (DFL) decomposition analysis—unlike propensity-score weighting in Rubin’s causal model, in which confounding covariates can be endogenous—may generate biased estimates for the decomposition of inequality into “direct” and “indirect” components when intervening variables are endogenous. The paper also clarifies that the Blinder-Oaxaca method confounds the…
Log-linear Causal Analysis of Cross-classified Categorical Data
Although log-linear and log-multiplicative analysis of association between variables is useful, its major limitation has been a lack of association with causal analysis. The objective of this article is to introduce a causal analysis on the basis of an adjusted cross-classified frequency table having such counterfactual odds ratios between a treatment variable X and its dependent variable Y that would be realized if the effects of confounding cov…
Decomposition of Inequality among Groups by Counterfactual Modeling: An Analysis of the Gender Wage Gap in Japan
This paper introduces a new method for decomposing group differences in the mean of a variable into various within-group and between-group components with respect to group categories of intermediary variables. This is accomplished by considering counterfactual outcomes that would be realized by social interventions that change the relationship among variables. Because such a change does not by itself determine the counterfactual outcome, the pape…
Black–white differences in social mobility in the past 30 years: A latent-class regression analysis
Four Useful Finite Mixture Models for Regression Analyses of Panel Data with a Categorical Dependent Variable
This paper describes and contrasts two useful ways to employ a latent class variable as a mixture variable in regression analyses of panel data with a categorical dependent variable. One way is to model unobserved heterogeneity in the trajectory, or change in the distribution, of the dependent variable. Two models that accomplish this are the latent trajectory model and latent growth curve model for a categorical dependent variable having ordered…
The structural and behavioral characteristics of the smallest-world phenomenon: Minimum distance networks
Regression Models with Parametrically Weighted Explanatory Variables
This paper describes linear regression models with parametrically weighted explanatory variables and related logistic regression models that estimate parameters characterizing (1) the effects of weighted variables on the dependent variable and (2) weights for the components of weighted variables. The models also characterize parsimoniously the interaction effects between weighted variables and covariates on the dependent variable by the use of va…
A New Model for Information Diffusion in Heterogeneous Social Networks
This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information dur…
The flow of information through social networks: Diagonal-free measures of inefficiency and the structural determinants of inefficiency
From beer to crack: Developmental patterns of drug involvement
OBJECTIVES. Prior research has identified developmental stages in drug use in adolescence, from substances that are legal for adults to illicit drugs. The position of crack in patterns of drug involvement remains to be established. METHODS. The analyses are based on a sample (n = 1108) representative of 12th graders attending New York State public and private schools. From reported ages of first use of five classes of drugs (alcoholic beverages, …
Stages of progression in drug involvement from adolescence to adulthood: Further evidence for the gateway theory.
Sequential stages of involvement in alcohol and/or cigarettes, marijuana, other illicit drugs and medically prescribed psychoactive drugs from adolescence to adulthood are investigated in a longitudinal cohort that has been followed from ages 15 to 35. Alternative models of progression are tested for their goodness of fit. Four stages are identified: that of legal drugs, alcohol or cigarettes; marijuana; illicit drugs other than marijuana; and me…
Patterns of drug use from adolescence to young adulthood: II. Sequences of progression
Major pathways of progression among legal, illegal, and medically prescribed psychoactive drugs from adolescence to young adulthood are described. The data are based on a follow-up cohort of former adolescents representative of high school students in grades 10 and 11 in New York State who were reinterviewed nine years later at ages 24-25. Various models of progression are tested for their goodness of fit. The patterns formerly observed in adoles…
Patterns of drug use from adolescence to young adulthood: III. Predictors of progression
Possible linkages of influence among classes of drugs in the observed sequential progression from adolescence to young adulthood are investigated through event history analyses. Three stages are examined: initiation to marijuana, to the use of other illicit drugs, and to prescribed psychoactive drugs. The data are based on a follow-up cohort of former adolescents representative of high school students in grade 10 and 11 in New York State who were…
Impermeability and Distance: A Method for the Analysis of Some Structural Characteristics Underlying Social Processes
Patterns of drug use from adolescence to young adulthood: III. Predictors of progression
Possible linkages of influence among classes of drugs in the observed sequential progression from adolescence to young adulthood are investigated through event history analyses. Three stages are examined: initiation to marijuana, to the use of other illicit drugs, and to prescribed psychoactive drugs. The data are based on a follow-up cohort of former adolescents representative of high school students in grade 10 and 11 in New York State who were…
Patterns of drug use from adolescence to young adulthood: II. Sequences of progression
Major pathways of progression among legal, illegal, and medically prescribed psychoactive drugs from adolescence to young adulthood are described. The data are based on a follow-up cohort of former adolescents representative of high school students in grades 10 and 11 in New York State who were reinterviewed nine years later at ages 24-25. Various models of progression are tested for their goodness of fit. The patterns formerly observed in adoles…
A New Model for Information Diffusion in Heterogeneous Social Networks
This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information dur…
From beer to crack: Developmental patterns of drug involvement
OBJECTIVES. Prior research has identified developmental stages in drug use in adolescence, from substances that are legal for adults to illicit drugs. The position of crack in patterns of drug involvement remains to be established. METHODS. The analyses are based on a sample (n = 1108) representative of 12th graders attending New York State public and private schools. From reported ages of first use of five classes of drugs (alcoholic beverages, …
Regression Models with Parametrically Weighted Explanatory Variables
This paper describes linear regression models with parametrically weighted explanatory variables and related logistic regression models that estimate parameters characterizing (1) the effects of weighted variables on the dependent variable and (2) weights for the components of weighted variables. The models also characterize parsimoniously the interaction effects between weighted variables and covariates on the dependent variable by the use of va…
Decomposition of Inequality among Groups by Counterfactual Modeling: An Analysis of the Gender Wage Gap in Japan
This paper introduces a new method for decomposing group differences in the mean of a variable into various within-group and between-group components with respect to group categories of intermediary variables. This is accomplished by considering counterfactual outcomes that would be realized by social interventions that change the relationship among variables. Because such a change does not by itself determine the counterfactual outcome, the pape…
Log-linear Causal Analysis of Cross-classified Categorical Data
Although log-linear and log-multiplicative analysis of association between variables is useful, its major limitation has been a lack of association with causal analysis. The objective of this article is to introduce a causal analysis on the basis of an adjusted cross-classified frequency table having such counterfactual odds ratios between a treatment variable X and its dependent variable Y that would be realized if the effects of confounding cov…
Decomposition Analysis of Segregation
Although substantive studies on segregation, such as residential or school segregation by race and occupational segregation by gender, are many in sociology, the analytical methodology is almost exclusively focused on measurement issues. The author introduces a set of two statistical models for the decomposition analysis of segregation. These models can be regarded as a tool to analyze whether one dimension of racial or gender inequality is relat…
Decomposition of Gender or Racial Inequality with Endogenous Intervening Covariates: An Extension of the DiNardo-Fortin-Lemieux Method
This paper begins by clarifying that propensity-score weighting in the DiNardo-Fortin-Lemieux (DFL) decomposition analysis—unlike propensity-score weighting in Rubin’s causal model, in which confounding covariates can be endogenous—may generate biased estimates for the decomposition of inequality into “direct” and “indirect” components when intervening variables are endogenous. The paper also clarifies that the Blinder-Oaxaca method confounds the…
Black–white differences in social mobility in the past 30 years: A latent-class regression analysis
Four Useful Finite Mixture Models for Regression Analyses of Panel Data with a Categorical Dependent Variable
This paper describes and contrasts two useful ways to employ a latent class variable as a mixture variable in regression analyses of panel data with a categorical dependent variable. One way is to model unobserved heterogeneity in the trajectory, or change in the distribution, of the dependent variable. Two models that accomplish this are the latent trajectory model and latent growth curve model for a categorical dependent variable having ordered…
Multivariate Multinomial Logit Models with Associations among Dependent Variables
The authors introduce a new group of multinomial logit models with special contrasts to identify covariate effects on multiple categorical dependent variables that are strongly associated with each other. The authors first develop the method for a case with two dependent variables and then extend the method to a case with three dependent variables. The model can account for both nominal and ordinal scales of categorical dependent variables. The a…
A New RCM Approach to Survival Analysis: The Conditional-Incidence-Rate Model
This article introduces a new causal analytic method for survival analysis that retains the framework of Rubin’s causal model as an alternative to the marginal structural model (MSM). The major limitation of the MSM is a systematic bias in the effects of past treatments when the method is applied to the hazard rate analysis of nonrepeatable events in the presence of unobserved heterogeneity. This systematic bias is demonstrated in the article. Th…
Impermeability and Distance: A Method for the Analysis of Some Structural Characteristics Underlying Social Processes
Patterns of drug use from adolescence to young adulthood: II. Sequences of progression
Major pathways of progression among legal, illegal, and medically prescribed psychoactive drugs from adolescence to young adulthood are described. The data are based on a follow-up cohort of former adolescents representative of high school students in grades 10 and 11 in New York State who were reinterviewed nine years later at ages 24-25. Various models of progression are tested for their goodness of fit. The patterns formerly observed in adoles…
Patterns of drug use from adolescence to young adulthood: III. Predictors of progression
Possible linkages of influence among classes of drugs in the observed sequential progression from adolescence to young adulthood are investigated through event history analyses. Three stages are examined: initiation to marijuana, to the use of other illicit drugs, and to prescribed psychoactive drugs. The data are based on a follow-up cohort of former adolescents representative of high school students in grade 10 and 11 in New York State who were…
Stages of progression in drug involvement from adolescence to adulthood: Further evidence for the gateway theory.
Sequential stages of involvement in alcohol and/or cigarettes, marijuana, other illicit drugs and medically prescribed psychoactive drugs from adolescence to adulthood are investigated in a longitudinal cohort that has been followed from ages 15 to 35. Alternative models of progression are tested for their goodness of fit. Four stages are identified: that of legal drugs, alcohol or cigarettes; marijuana; illicit drugs other than marijuana; and me…
From beer to crack: Developmental patterns of drug involvement
OBJECTIVES. Prior research has identified developmental stages in drug use in adolescence, from substances that are legal for adults to illicit drugs. The position of crack in patterns of drug involvement remains to be established. METHODS. The analyses are based on a sample (n = 1108) representative of 12th graders attending New York State public and private schools. From reported ages of first use of five classes of drugs (alcoholic beverages, …
The flow of information through social networks: Diagonal-free measures of inefficiency and the structural determinants of inefficiency
A New Model for Information Diffusion in Heterogeneous Social Networks
This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information dur…
The structural and behavioral characteristics of the smallest-world phenomenon: Minimum distance networks
Regression Models with Parametrically Weighted Explanatory Variables
This paper describes linear regression models with parametrically weighted explanatory variables and related logistic regression models that estimate parameters characterizing (1) the effects of weighted variables on the dependent variable and (2) weights for the components of weighted variables. The models also characterize parsimoniously the interaction effects between weighted variables and covariates on the dependent variable by the use of va…
Four Useful Finite Mixture Models for Regression Analyses of Panel Data with a Categorical Dependent Variable
This paper describes and contrasts two useful ways to employ a latent class variable as a mixture variable in regression analyses of panel data with a categorical dependent variable. One way is to model unobserved heterogeneity in the trajectory, or change in the distribution, of the dependent variable. Two models that accomplish this are the latent trajectory model and latent growth curve model for a categorical dependent variable having ordered…
Black–white differences in social mobility in the past 30 years: A latent-class regression analysis
Decomposition of Inequality among Groups by Counterfactual Modeling: An Analysis of the Gender Wage Gap in Japan
This paper introduces a new method for decomposing group differences in the mean of a variable into various within-group and between-group components with respect to group categories of intermediary variables. This is accomplished by considering counterfactual outcomes that would be realized by social interventions that change the relationship among variables. Because such a change does not by itself determine the counterfactual outcome, the pape…
Log-linear Causal Analysis of Cross-classified Categorical Data
Although log-linear and log-multiplicative analysis of association between variables is useful, its major limitation has been a lack of association with causal analysis. The objective of this article is to introduce a causal analysis on the basis of an adjusted cross-classified frequency table having such counterfactual odds ratios between a treatment variable X and its dependent variable Y that would be realized if the effects of confounding cov…
Decomposition of Gender or Racial Inequality with Endogenous Intervening Covariates: An Extension of the DiNardo-Fortin-Lemieux Method
This paper begins by clarifying that propensity-score weighting in the DiNardo-Fortin-Lemieux (DFL) decomposition analysis—unlike propensity-score weighting in Rubin’s causal model, in which confounding covariates can be endogenous—may generate biased estimates for the decomposition of inequality into “direct” and “indirect” components when intervening variables are endogenous. The paper also clarifies that the Blinder-Oaxaca method confounds the…
Decomposition Analysis of Segregation
Although substantive studies on segregation, such as residential or school segregation by race and occupational segregation by gender, are many in sociology, the analytical methodology is almost exclusively focused on measurement issues. The author introduces a set of two statistical models for the decomposition analysis of segregation. These models can be regarded as a tool to analyze whether one dimension of racial or gender inequality is relat…
Multigroup Segregation Analyses with Covariates
The author introduces methods for the decomposition analysis of multigroup segregation measured by the index of dissimilarity, the squared coefficient of variation, and Theil’s entropy measure. Using a new causal framework, the author takes a unified approach to the decomposition analysis by specifying conditions that must be satisfied to decompose segregation into unexplained and explained components. Here, the unexplained component represents t…
Full Issue
This special issue of the Humboldt Journal of Social Relations visits one of the most polarizing policy debates in the US. In 2012, voters in Washington and Colorado passed initiatives that legalized the recreational use of marijuana. In fact, there were about 75,000 more votes cast in support of marijuana legalization in Colorado than were given to reelect President Obama. Yet according to a recent poll conducted by the Pew Research Center, Demo…
A New RCM Approach to Survival Analysis: The Conditional-Incidence-Rate Model
This article introduces a new causal analytic method for survival analysis that retains the framework of Rubin’s causal model as an alternative to the marginal structural model (MSM). The major limitation of the MSM is a systematic bias in the effects of past treatments when the method is applied to the hazard rate analysis of nonrepeatable events in the presence of unobserved heterogeneity. This systematic bias is demonstrated in the article. Th…
Awareness Context and Social Recognition: Reconsidering a Case Study of “Dialogue” between Different Ethnic Persons in Japan
This study incorporates Honneth’s social recognition into awareness context theory by reconsidering a case study of the dialogue between Zainichi Korean and Japanese people in Japan. It revitalizes the theoretical significance of Strauss’ symbolic interactionism in terms of its focus on power dynamics and conflicts between the majority and minorities that differ in the cultural or ethnic background in modern global society. Incorporating critical…
Multivariate Multinomial Logit Models with Associations among Dependent Variables
The authors introduce a new group of multinomial logit models with special contrasts to identify covariate effects on multiple categorical dependent variables that are strongly associated with each other. The authors first develop the method for a case with two dependent variables and then extend the method to a case with three dependent variables. The model can account for both nominal and ordinal scales of categorical dependent variables. The a…
Mathematics (13 works) · Econometrics (12 works) · Statistics (11 works) · Psychology (8 works) · Computer Science (6 works) · Covariate (6 works) · Economics (6 works) · Medicine (6 works) · Spatial and Panel Data Analysis (5 works) · Drug (4 works)