C Winship
Biographic Data
| ID | 1053 |
|---|---|
| NAME | C Winship |
| GIVEN NAMES | C |
| FAMILY NAME | Winship |
| SIGNATURE | WINSHIP C |
| AFFILIATIONS | Harvard University Press |
| ORCID | 0000-0002-0632-241X |
| VERIFIED | Yes |
| TOTAL WORKS | 55 |
| TOTAL CITATIONS | 1638 |
| AUTHOR COUNT | 55 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1977 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 16 |
Cross-Group Differences in Age, Period, and Cohort Effects: A Bounding Approach to the Gender Wage Gap
For decades, researchers have sought to understand the separate contributions of age, period, and cohort (APC) on a wide range of outcomes. However, a major challenge in these efforts is the linear dependence among the three time scales. Previous methods have been plagued by either arbitrary assumptions or extreme sensitivity to small variations in model specification. In this article, we present an alternative method that achieves partial identi…
The early years
Only recently have sociologists begun to examine the social origins of educational mismatches in more detail. This research not only repeatedly found, but also investigated why individuals from lower social origin more often have a higher level of education than required for their job (overeducation), and why individuals from a higher social origin more often realize high positions despite having a lower level of education than required for their…
Streetwork at the crossroads: An evaluation of a street gang outreach intervention and holistic appraisal of the research evidence
Spurred by the success of public health violence interventions, and accelerated by policy pressure to reduce violence without exacerbating overpolicing and mass incarceration, streetwork programs—those that provide anti‐violence services by neighborhood‐based workers who perform their work beyond the walls of parochial institutions—have positioned themselves as the most important non–law‐enforcement violence prevention option available to urban p…
The Anatomy of Cohort Analysis: Decomposing Comparative Cohort Careers
In a widely influential essay, Ryder argued that to understand social change, researchers should compare cohort careers, contrasting how different cohorts change over the life cycle with respect to some outcome. Ryder, however, provided few technical details on how to actually conduct a cohort analysis. In this article, the authors develop a framework for analyzing temporally structured data grounded in the construction, comparison, and decomposi…
Advances in mediation analysis
The extensive causal inference revolution in statistics, epidemiology and other social science fields based on Rubin's potential outcome model and Pearl's directed acyclic graphs (DAGs) has not penetrated the research of analytical sociologists as yet. In this chapter we introduce empirical examples, primarily relying on the Merton Award winning papers to demonstrate the value of these frameworks as a way of providing theoretical clarity for assu…
Analyzing Age-Period-Cohort Data: A Review and Critique
Age-period-cohort (APC) analysis has a long, controversial history in sociology and related fields. Despite the existence of hundreds, if not thousands, of articles and dozens of books, there is little agreement on how to adequately analyze APC data. This article begins with a brief overview of APC analysis, discussing how one can interpret APC effects in a causal way. Next, we review methods that obtain point identification of APC effects, such …
Bounding Analyses of Age-Period-Cohort Effects
For more than a century, researchers from a wide range of disciplines have sought to estimate the unique contributions of age, period, and cohort (APC) effects on a variety of outcomes. A key obstacle to these efforts is the linear dependence among the three time scales. Various methods have been proposed to address this issue, but they have suffered from either ad hoc assumptions or extreme sensitivity to small differences in model specification…
Methodological Challenges and Opportunities in Testing for Racial Discrimination in Policing
A large body of empirical research exists that attempts to determine whether or not police discriminate on the basis of race. We investigate whether the methods used typically produce valid inferences. We find that they often most likely do not and that results may diverge from reality in either direction, indicating discrimination when it is not present or alternatively indicating a lack of discrimination when it is in fact present. The reason f…
Moore–Penrose Estimators of Age–Period–Cohort Effects: Their Interrelationship and Properties
The intrinsic estimator (IE) has become a widely used tool for the analysis of age–period–cohort (APC) data in sociology, demography, and other fields. However, it has been recently recognized that the IE is a subtype of a larger class of estimators based on the Moore–Penrose generalized inverse (MP estimators) and that different estimators can lead to radically divergent estimates of the true, unknown APC effects. To clarify the differences and …
Redefine statistical significance
Causal Inference in Panel Data With Application to Estimating Race-of-Interviewer Effects in the General Social Survey
In this article, we review popular parametric models for analyzing panel data and introduce the latest advances in matching methods for panel data analysis. To the extent that the parametric models and the matching methods offer distinct advantages for drawing causal inference, we suggest using both to cross-validate the evidence. We demonstrate how to use these methods by examining race-of-interviewer effects (ROIE) in the 2006 to 2010 panel dat…
Multicollinearity and Model Misspecification
Multicollinearity in linear regression is typically thought of as a problem of large standard errors due to near-linear dependencies among independent variables. This problem can be solved by more informative data, possibly in the form of a larger sample. We argue that this understanding of multicollinearity is only partly correct. The near collinearity of independent variables can also increase the sensitivity of regression estimates to small er…
Population Growth, Migration, and Changes in the Racial Differential in Imprisonment in the United States, 1940-1980
The proportion of U.S. prison inmates who were black increased dramatically between 1940 and 2000. While about two-thirds of the increase occurred between 1940 and 1970, most recent research analyzes the period after 1970, focusing on explanations such as the war on drugs, law-and-order politics, discrimination, inequality, and racial threat. We analyze the growth in the racial difference in incarceration between 1940 and 1980, focusing on the ro…
The Sensitivity of the Intrinsic Estimator to Coding Schemes: Comment on Yang, Schulhofer-Wohl, Fu, and Land
Ecometrics in the Age of Big Data: Measuring and Assessing “Broken Windows” Using Large-scale Administrative Records
The collection of large-scale administrative records in electronic form by many cities provides a new opportunity for the measurement and longitudinal tracking of neighborhood characteristics, but one that will require novel methodologies that convert such data into research-relevant measures. The authors illustrate these challenges by developing measures of “broken windows” from Boston’s constituent relationship management (CRM) system (aka 311 …
Counterfactuals and Causal Inference: Methods and Principles for Social Research
In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are p…
Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable
Endogenous selection bias is a central problem for causal inference. Recognizing the problem, however, can be difficult in practice. This article introduces a purely graphical way of characterizing endogenous selection bias and of understanding its consequences ( Hernán et al. 2004 ). We use causal graphs (direct acyclic graphs, or DAGs) to highlight that endogenous selection bias stems from conditioning (e.g., controlling, stratifying, or select…
Overview of: “Translating Causal Claims: Principles and Strategies for Policy‐Relevant Criminology”
Research Summary This article reviews the causal turn in the social sciences and accompanying efforts by criminologists to make policy claims more credible. Although there has been much progress in techniques for the estimation of causal effects, we find that the link between evidence and valid policy implications remains elusive. Drawing on criminological theory and research insights from disciplines such as sociology, economics, and statistics,…
Translating Causal Claims: Principles and Strategies for Policy‐Relevant Criminology
Research Summary\nThis article reviews the causal turn in the social sciences and accompanying efforts by criminologists to make policy claims more credible. Although there has been much progress in techniques for the estimation of causal effects, we find that the link between evidence and valid policy implications remains elusive. Drawing on criminological theory and research insights from disciplines such as sociology, economics, and statistics…
Participation in Context: Neighborhood Diversity and Organizational Involvement in Boston
We use unique data from the Boston Non–Profit Organizations Study, an innovative survey containing rich information on organizational participation across seven social domains in two Boston neighborhoods, to examine the relationship between ethnic diversity and participation in local organizations. In particular, we identify neighborhood–based social ties as a key mechanism mediating the initial negative association between diversity and particip…
Counterfactuals and Causal Inference: Methods and Principles for Social Research
Threshold Models of Social Influence
This article explores threshold models of social influence, with a particular focus on the consequences of simple heuristics in the context of social influence on collective decision-making processes. It first provides an overview of social-influence and threshold models before discussing influence cascades on complete and random networks. It then considers cascades in networks that emphasize the importance of social groups in the formation of in…
Ethnomethodology and Consequences: "Comment on Emirbayer and Maynard's "Pragmatism and Ethnomethodology
The Faculty-Student Low-Low Contract
What Is Required of Science? The ASA Amicus Brief in Wal-Mart v. Dukes
Sampling Weights and Regression Analysis
Most major population surveys used by social scientists are based on complex sampling designs where sampling units have different probabilities of being selected. Although sampling weights must generally be used to derive unbiased estimates of univariate population characteristics, the decision about their use in regression analysis is more complicated. Where sampling weights are solely a function of independent variables included in the model, u…
Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable
Endogenous selection bias is a central problem for causal inference. Recognizing the problem, however, can be difficult in practice. This article introduces a purely graphical way of characterizing endogenous selection bias and of understanding its consequences ( Hernán et al. 2004 ). We use causal graphs (direct acyclic graphs, or DAGs) to highlight that endogenous selection bias stems from conditioning (e.g., controlling, stratifying, or select…
The Estimation of Causal Effects From Observational Data
When experimental designs are infeasible, researchers must resort to the use of observational data from surveys, censuses, and administrative records. Because assignment to the independent variables of observational data is usually nonrandom, the challenge of estimating causal effects with observational data can be formidable. In this chapter, we review the large literature produced primarily by statisticians and econometricians in the past two d…
Regression Models with Ordinal Variables
Most discussions of ordinal variables in the sociological literature debate the suitability of linear regression and structural equation methods when some variables are ordinal. Largely ignored in these discussions are methods for ordinal variables that are natural extensions of probit and logit models for dichotomous variables. If ordinal variables are discrete realizations of unmeasured continuous variables, these methods allow one to include o…
Redefine statistical significance
The Paradox of Lessening Racial Inequality and Joblessness among Black Youth: Enrollment, Enlistment, and Employment, 1964-1981
Ecometrics in the Age of Big Data: Measuring and Assessing “Broken Windows” Using Large-scale Administrative Records
The collection of large-scale administrative records in electronic form by many cities provides a new opportunity for the measurement and longitudinal tracking of neighborhood characteristics, but one that will require novel methodologies that convert such data into research-relevant measures. The authors illustrate these challenges by developing measures of “broken windows” from Boston’s constituent relationship management (CRM) system (aka 311 …
Structural Equations and Path Analysis for Discrete Data
This article proposes a solution to the long-standing methodological problem of incorporating discrete variables inoto causal models of social phenomena. Only a subset of the variety of ways in which discrete data arise in empirical social research can be satisfactorily modeled by conventional log-linear or logit approaches. Drawing on the insights of several literatures, this article exposits a general approach to causal models in which some or …
A Mechanism-Based Approach to the Identification of Age-Period-Cohort Models
This article offers a new approach to the identification of age-period-cohort (APC) models that builds on Pearl's work on nonparametric causal models, in particular his front-door criterion for the identification of causal effects. The goal is to specify the mechanisms through which the age, period, and cohort variables affect the outcome and in doing so identify the model. This approach allows for a broader set of identification strategies than …
A Revaluation of Indexes of Residential Segregation
Journal Article A Revaluation of Indexes of Residential Segregation Get access Christopher Winship Christopher Winship Harvard University Search for other works by this author on: Oxford Academic Google Scholar Social Forces, Volume 55, Issue 4, June 1977, Pages 1058–1066, https://doi.org/10.1093/sf/55.4.1058 Published: 01 June 1977
Methodological Challenges and Opportunities in Testing for Racial Discrimination in Policing
A large body of empirical research exists that attempts to determine whether or not police discriminate on the basis of race. We investigate whether the methods used typically produce valid inferences. We find that they often most likely do not and that results may diverge from reality in either direction, indicating discrimination when it is not present or alternatively indicating a lack of discrimination when it is in fact present. The reason f…
Participation in Context: Neighborhood Diversity and Organizational Involvement in Boston
We use unique data from the Boston Non–Profit Organizations Study, an innovative survey containing rich information on organizational participation across seven social domains in two Boston neighborhoods, to examine the relationship between ethnic diversity and participation in local organizations. In particular, we identify neighborhood–based social ties as a key mechanism mediating the initial negative association between diversity and particip…
Translating Causal Claims: Principles and Strategies for Policy‐Relevant Criminology
Research Summary\nThis article reviews the causal turn in the social sciences and accompanying efforts by criminologists to make policy claims more credible. Although there has been much progress in techniques for the estimation of causal effects, we find that the link between evidence and valid policy implications remains elusive. Drawing on criminological theory and research insights from disciplines such as sociology, economics, and statistics…
Black students' graduation from elite colleges: Institutional characteristics and between-institution differences
The Transition from Youth to Adult: Understanding the Age Pattern of Employment
This article examines the growth in probabilities of employment for American men between the ages of 16 and 29. A young man's probability of employment is strongly affected by his other roles, statuses, and activities, and a cohort's employment growth depends on its age distribution of these traits. This article considers two important activities in the lives of young men-school enrollment and enlistment in the armed forces-and examines mechanism…
Bounding Analyses of Age-Period-Cohort Effects
For more than a century, researchers from a wide range of disciplines have sought to estimate the unique contributions of age, period, and cohort (APC) effects on a variety of outcomes. A key obstacle to these efforts is the linear dependence among the three time scales. Various methods have been proposed to address this issue, but they have suffered from either ad hoc assumptions or extreme sensitivity to small differences in model specification…
Roles and Positions: A Critique and Extension of the Blockmodeling Approach
Introduction: Sociological and Economic Approaches to the Analysis of Social Structure
The Welfare Approach to Measuring Inequality
The work on this chapter was done while Joseph Schwartz was a graduate student at Harvard University (with support from National Science Foundation Grant SOC76-24394, Harrison White, principal investigator) and Christopher Winship was a research associate at the Institute for Research on Poverty. This research was supported in part by funds granted to the Institute for Research on Poverty at the University of Wisconsin-Madison by the Department o…
The Sensitivity of the Intrinsic Estimator to Coding Schemes: Comment on Yang, Schulhofer-Wohl, Fu, and Land
Streetwork at the crossroads: An evaluation of a street gang outreach intervention and holistic appraisal of the research evidence
Spurred by the success of public health violence interventions, and accelerated by policy pressure to reduce violence without exacerbating overpolicing and mass incarceration, streetwork programs—those that provide anti‐violence services by neighborhood‐based workers who perform their work beyond the walls of parochial institutions—have positioned themselves as the most important non–law‐enforcement violence prevention option available to urban p…
The Anatomy of Cohort Analysis: Decomposing Comparative Cohort Careers
In a widely influential essay, Ryder argued that to understand social change, researchers should compare cohort careers, contrasting how different cohorts change over the life cycle with respect to some outcome. Ryder, however, provided few technical details on how to actually conduct a cohort analysis. In this article, the authors develop a framework for analyzing temporally structured data grounded in the construction, comparison, and decomposi…
Moore–Penrose Estimators of Age–Period–Cohort Effects: Their Interrelationship and Properties
The intrinsic estimator (IE) has become a widely used tool for the analysis of age–period–cohort (APC) data in sociology, demography, and other fields. However, it has been recently recognized that the IE is a subtype of a larger class of estimators based on the Moore–Penrose generalized inverse (MP estimators) and that different estimators can lead to radically divergent estimates of the true, unknown APC effects. To clarify the differences and …
Causal Inference in Panel Data With Application to Estimating Race-of-Interviewer Effects in the General Social Survey
In this article, we review popular parametric models for analyzing panel data and introduce the latest advances in matching methods for panel data analysis. To the extent that the parametric models and the matching methods offer distinct advantages for drawing causal inference, we suggest using both to cross-validate the evidence. We demonstrate how to use these methods by examining race-of-interviewer effects (ROIE) in the 2006 to 2010 panel dat…
The Desirability of Using the Index of Dissimilarity or Any Adjustment of It for Measuring Segregation: Reply to Falk, Cortese, and Cohen
Christopher Winship, The Desirability of Using the Index of Dissimilarity or Any Adjustment of It for Measuring Segregation: Reply to Falk, Cortese, and Cohen, Social Forces, Vol. 57, No. 2, Special Issue (Dec., 1978), pp. 717-720
A Revaluation of Indexes of Residential Segregation
Journal Article A Revaluation of Indexes of Residential Segregation Get access Christopher Winship Christopher Winship Harvard University Search for other works by this author on: Oxford Academic Google Scholar Social Forces, Volume 55, Issue 4, June 1977, Pages 1058–1066, https://doi.org/10.1093/sf/55.4.1058 Published: 01 June 1977
A distance model for sociometric structure
The conceptual and mathematical framework of a general model for distance within sociometric structure is described. The model characterizes “balance” in terms of the triangle inequality, in which the distance between two people (A and C) should be less than or equal to the sum of the distances to a third person (B), i.e., d (A,C) ≤ d (A,B) + d (B,C). The notion of addition of distances is developed. Different ways of adding distances result in d…
The Allocation of Time among Individuals
For most of us time is a scarce resource. In our daily lives we are constantly allocating time among various activities and people. Allocating time among people is different from allocating it among activities. In allocating time among activities I need only consider my own preferences. In allocating my time among people I need to consider my own preferences and the willingness of others to spend time with me. People's decisions about whom they a…
The Desirability of Using the Index of Dissimilarity or Any Adjustment of It for Measuring Segregation: Reply to Falk, Cortese, and Cohen
Christopher Winship, The Desirability of Using the Index of Dissimilarity or Any Adjustment of It for Measuring Segregation: Reply to Falk, Cortese, and Cohen, Social Forces, Vol. 57, No. 2, Special Issue (Dec., 1978), pp. 717-720
The Welfare Approach to Measuring Inequality
The work on this chapter was done while Joseph Schwartz was a graduate student at Harvard University (with support from National Science Foundation Grant SOC76-24394, Harrison White, principal investigator) and Christopher Winship was a research associate at the Institute for Research on Poverty. This research was supported in part by funds granted to the Institute for Research on Poverty at the University of Wisconsin-Madison by the Department o…
Roles and Positions: A Critique and Extension of the Blockmodeling Approach
Modeling the Distribution and Intergenerational Transmission of Wealth. James D. Smith
Capital and the Distribution of Labor Earnings.Michael Sattinger
Structural Equations and Path Analysis for Discrete Data
This article proposes a solution to the long-standing methodological problem of incorporating discrete variables inoto causal models of social phenomena. Only a subset of the variety of ways in which discrete data arise in empirical social research can be satisfactorily modeled by conventional log-linear or logit approaches. Drawing on the insights of several literatures, this article exposits a general approach to causal models in which some or …
The Economic Theory of Social Institutions.Andrew Schotter
Regression Models with Ordinal Variables
Most discussions of ordinal variables in the sociological literature debate the suitability of linear regression and structural equation methods when some variables are ordinal. Largely ignored in these discussions are methods for ordinal variables that are natural extensions of probit and logit models for dichotomous variables. If ordinal variables are discrete realizations of unmeasured continuous variables, these methods allow one to include o…
The Paradox of Lessening Racial Inequality and Joblessness among Black Youth: Enrollment, Enlistment, and Employment, 1964-1981
The Transition from Youth to Adult: Understanding the Age Pattern of Employment
This article examines the growth in probabilities of employment for American men between the ages of 16 and 29. A young man's probability of employment is strongly affected by his other roles, statuses, and activities, and a cohort's employment growth depends on its age distribution of these traits. This article considers two important activities in the lives of young men-school enrollment and enlistment in the armed forces-and examines mechanism…
Mathematical Models in the Social and Behavioral Sciences
Heterogeneity and Interdependence: A Test Using Survival Models
This research was supported by grants from the National Science Foundation and the National Institute on Aging. I am particularly grateful to Ian Domowitz, who provided many important and insightful comments on an earlier draft. Many others provided useful comments: James Coleman, Robert Mare, Lars Muus, Larry Radbill, Nancy Tuma, and an anonymous reviewer. Jean Mitchell and Nancy Winship helped with the editing. Any mistakes that remain are of c…
Blacks and Whites: Narrowing the Gap?Reynolds Farley
Thoughts about roles and relations: An old document revisited
Introduction: Sociological and Economic Approaches to the Analysis of Social Structure
Loglinear Models with Missing Data: A Latent Class Approach
This article discusses latent class models as an approach to categorical data analysis when some variables have missing data. In contrast to standard latent class models in which each variable is either latent or observed for all sample observations our models include variables that are latent (missing) for some observations and manifest (not missing) for others. Particular attention is devoted to models in which the probability that an observati…
Loglinear Models for Reciprocal and Other Simultaneous Effects
This paper presents new models for simultaneous relationships among endogenous categorical variables. Previous investigators have argued that the loglinearllogit framework is insufficiently rich for the development of simultaneous equation models and that only models that postulate latent continuous variables (e.g. multivariate probit models) can represent simultaneous relationships among categorical variables. This paper shows that by using late…
Models for Sample Selection Bias
When observations in social research are selected so that they are not independent of the outcome variables in a study, sample selection leads to biased inferences about social processes. Nonrandom selection is both a source of bias in empirical research and a fundamental aspect of many social processes. This chapter reviews models that attempt to take account of sample selection and their applications in research on labor markets, schooling, leg…
Race, Poverty, and The American Occupational Structure
Sampling Weights and Regression Analysis
Most major population surveys used by social scientists are based on complex sampling designs where sampling units have different probabilities of being selected. Although sampling weights must generally be used to derive unbiased estimates of univariate population characteristics, the decision about their use in regression analysis is more complicated. Where sampling weights are solely a function of independent variables included in the model, u…
The dangers of "strong" causal reasoning in social policy
The Estimation of Causal Effects From Observational Data
When experimental designs are infeasible, researchers must resort to the use of observational data from surveys, censuses, and administrative records. Because assignment to the independent variables of observational data is usually nonrandom, the challenge of estimating causal effects with observational data can be formidable. In this chapter, we review the large literature produced primarily by statisticians and econometricians in the past two d…
Sociology (31 works) · Mathematics (28 works) · Psychology (28 works) · Computer Science (27 works) · Econometrics (22 works) · Statistics (22 works) · Economics (18 works) · Political science (17 works) · Epistemology (10 works) · Advanced Causal Inference Techniques (9 works)