Daniel L Oberski
Dados Biográficos
| ID | 4168613 |
|---|---|
| NOME | Daniel L Oberski |
| PRENOMES | Daniel L |
| SOBRENOME | Oberski |
| ASSINATURA | OBERSKI D L |
| AFILIAÇÕES | Tilburg University |
| ORCID | 0000-0001-7467-2297 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 18 |
| TOTAL DE CITAÇÕES | 197 |
| TOTAL COMO AUTOR | 18 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2012 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 5 |
How Much Data Should I Request? Balancing Richness and Compliance in Digital Trace Data Donations
Digital trace “data donation” studies offer researchers a unique opportunity to collect high-quality behavioral data, but decisions about the scope of requested data can impact both dataset richness and participant compliance. This paper examines the tradeoffs between requesting larger data packages, which include more extensive historical records, and participants’ willingness to donate. In a randomized experiment with Facebook and Instagram dat…
The effect of measurement error on clustering
Clustering is a set of statistical techniques widely applied in the social sciences. While an important and useful tool, traditional clustering techniques tend to assume that the data are free from measurement error, which is often an unrealistic assumption. In this paper, we perform a Monte Carlo study to investigate the sensitivity of different clustering techniques to measurement error. We focus on three commonly used approaches: latent profil…
Estimating Measurement Error in Longitudinal Data Using the Longitudinal MultiTrait MultiError Approach
Longitudinal data makes it possible to investigate change in time and its causes. While this type of data is getting more popular there is limited knowledge regarding the measurement errors involved, their stability in time and how they bias estimates of change. In this paper we apply a new method to estimate multiple types of errors concurrently, called the MultiTrait MultiError approach, to longitudinal data. This method uses a combination of e…
Why Measurement Invariance is Important in Comparative Research. A Response to Welzel et al. (2021)
Welzel et al. (2021) claim that non-invariance of instruments is inconclusive and inconsequential in the field for cross-cultural value measurement. In this response, we contend that several key arguments on which Welzel et al. (2021) base their critique of invariance testing are conceptually and statistically incorrect. First, Welzel et al. (2021) claim that value measurement follows a formative rather than reflective logic. Yet they do not prov…
An open source machine learning framework for efficient and transparent systematic reviews
To help researchers conduct a systematic review or meta-analysis as efficiently and transparently as possible, we designed a tool to accelerate the step of screening titles and abstracts. For many tasks—including but not limited to systematic reviews and meta-analyses—the scientific literature needs to be checked systematically. Scholars and practitioners currently screen thousands of studies by hand to determine which studies to include in their…
Can’t see the wood for the trees? An assessment of street view- and satellite-derived greenness measures in relation to mental health
Greenness in the urban living environment is inconsistently associated with mental health. Satellite-derived measures of greenness may inadequately characterize how people encounter greenness visually on site, but systematic comparisons are lacking. We aimed 1) to compare associations between remotely sensed and street view (SV) greenness, and 2) to examine whether these greenness metrics are differently associated with mental health outcomes. We…
Big Five personality stability, change, and codevelopment across adolescence and early adulthood
Using data from 2 large and overlapping cohorts of Dutch adolescents, containing up to 7 waves of longitudinal data each (N = 2,230), the present study examined Big Five personality trait stability, change, and codevelopment in friendship and sibling dyads from age 12 to 22. Four findings stand out. First, the 1-year rank-order stability of personality traits was already substantial at age 12, increased strongly from early through middle adolesce…
Questionnaire Science
Some textbooks on questionnaire design claim it is an art. That would make the criterion for a “good” question entirely subjective—a worrying conclusion given that surveys are often used to discover important facts about people. Are our discoveries about people also entirely subjective? This chapter shows that it is possible to study what a “good” or a “bad” question is by experimentation. There is already a body of scientific evidence on questio…
Mixture Models
Hidden Markov Item Response Theory Models for Responses and Response Times
Current approaches to model responses and response times to psychometric tests solely focus on between-subject differences in speed and ability. Within subjects, speed and ability are assumed to be constants. Violations of this assumption are generally absorbed in the residual of the model. As a result, within-subject departures from the between-subject speed and ability level remain undetected. These departures may be of interest to the research…
Goodness-of-fit of Multilevel Latent Class Models for Categorical Data
In the context of multilevel latent class models, the goodness-of-fit depends on multiple aspects, among which are two local independence assumptions. However, because of the lack of local fit statistics, the model and any issues relating to model fit can only be inspected jointly through global fit statistics. This hinders the search for model improvements, as it cannot be determined where misfit originates and which of the many model adjustment…
Places and Preferences
Contextual theories of political behaviour assert that the contexts in which people live influence their political beliefs and vote choices. Most studies, however, fail to distinguish contextual influence from self-selection of individuals into areas. This article advances understanding of this controversy by tracking the left–right position and party identification of thousands of individuals over an eighteen-year period in England before and af…
Testing for Measurement Invariance by Detecting Local Misspecification and an Illustration Across Online and Paper-and-Pencil Samples
Political scientists often need to evaluate whether samples are comparable, for example, when analysing different countries or time points or when comparing data collected using different methods. A necessary condition for conducting such meaningful cross-group comparisons is the establishment of measurement invariance. One of the most frequently used procedures for establishing measurement invariance is the multigroup confirmatory factor analysi…
Evaluating Measurement Invariance in Categorical Data Latent Variable Models with the EPC-Interest
Many variables crucial to the social sciences are not directly observed but instead are latent and measured indirectly. When an external variable of interest affects this measurement, estimates of its relationship with the latent variable will then be biased. Such violations of “measurement invariance” may, for example, confound true differences across countries in postmaterialism with measurement differences. To deal with this problem, researche…
Lavaan.survey
This paper introduces the R package lavaan.survey, a user-friendly interface to design-based complex survey analysis of structural equation models (SEMs). By leveraging existing code in the lavaan and survey packages, the lavaan.survey package allows for SEM analyses of stratified, clustered, and weighted data, as well as multiply imputed complex survey data. lavaan.survey provides several features such as SEMs with replicate weights, a variety o…
Relating Latent Class Assignments to External Variables
Latent class analysis is used in the political science literature in both substantive applications and as a tool to estimate measurement error. Many studies in the social and political sciences relate estimated class assignments from a latent class model to external variables. Although common, such a “three-step” procedure effectively ignores classification error in the class assignments; Vermunt (2010, “Latent class modeling with covariates: Two…
Evaluating Sensitivity of Parameters of Interest to Measurement Invariance in Latent Variable Models
Latent variable models can only be compared across groups when these groups exhibit measurement equivalence or “invariance,” since otherwise substantive differences may be confounded with measurement differences. This article suggests examining directly whether measurement differences present could confound substantive analyses, by examining the expected parameter change (EPC)-interest. The EPC-interest approximates the change in parameters of in…
Personality and Political Participation
Personality and Political Participation
Places and Preferences
Contextual theories of political behaviour assert that the contexts in which people live influence their political beliefs and vote choices. Most studies, however, fail to distinguish contextual influence from self-selection of individuals into areas. This article advances understanding of this controversy by tracking the left–right position and party identification of thousands of individuals over an eighteen-year period in England before and af…
Evaluating Sensitivity of Parameters of Interest to Measurement Invariance in Latent Variable Models
Latent variable models can only be compared across groups when these groups exhibit measurement equivalence or “invariance,” since otherwise substantive differences may be confounded with measurement differences. This article suggests examining directly whether measurement differences present could confound substantive analyses, by examining the expected parameter change (EPC)-interest. The EPC-interest approximates the change in parameters of in…
Big Five personality stability, change, and codevelopment across adolescence and early adulthood
Using data from 2 large and overlapping cohorts of Dutch adolescents, containing up to 7 waves of longitudinal data each (N = 2,230), the present study examined Big Five personality trait stability, change, and codevelopment in friendship and sibling dyads from age 12 to 22. Four findings stand out. First, the 1-year rank-order stability of personality traits was already substantial at age 12, increased strongly from early through middle adolesce…
Relating Latent Class Assignments to External Variables
Latent class analysis is used in the political science literature in both substantive applications and as a tool to estimate measurement error. Many studies in the social and political sciences relate estimated class assignments from a latent class model to external variables. Although common, such a “three-step” procedure effectively ignores classification error in the class assignments; Vermunt (2010, “Latent class modeling with covariates: Two…
Evaluating Measurement Invariance in Categorical Data Latent Variable Models with the EPC-Interest
Many variables crucial to the social sciences are not directly observed but instead are latent and measured indirectly. When an external variable of interest affects this measurement, estimates of its relationship with the latent variable will then be biased. Such violations of “measurement invariance” may, for example, confound true differences across countries in postmaterialism with measurement differences. To deal with this problem, researche…
Testing for Measurement Invariance by Detecting Local Misspecification and an Illustration Across Online and Paper-and-Pencil Samples
Political scientists often need to evaluate whether samples are comparable, for example, when analysing different countries or time points or when comparing data collected using different methods. A necessary condition for conducting such meaningful cross-group comparisons is the establishment of measurement invariance. One of the most frequently used procedures for establishing measurement invariance is the multigroup confirmatory factor analysi…
Personality and Political Participation
Lavaan.survey
This paper introduces the R package lavaan.survey, a user-friendly interface to design-based complex survey analysis of structural equation models (SEMs). By leveraging existing code in the lavaan and survey packages, the lavaan.survey package allows for SEM analyses of stratified, clustered, and weighted data, as well as multiply imputed complex survey data. lavaan.survey provides several features such as SEMs with replicate weights, a variety o…
Relating Latent Class Assignments to External Variables
Latent class analysis is used in the political science literature in both substantive applications and as a tool to estimate measurement error. Many studies in the social and political sciences relate estimated class assignments from a latent class model to external variables. Although common, such a “three-step” procedure effectively ignores classification error in the class assignments; Vermunt (2010, “Latent class modeling with covariates: Two…
Evaluating Sensitivity of Parameters of Interest to Measurement Invariance in Latent Variable Models
Latent variable models can only be compared across groups when these groups exhibit measurement equivalence or “invariance,” since otherwise substantive differences may be confounded with measurement differences. This article suggests examining directly whether measurement differences present could confound substantive analyses, by examining the expected parameter change (EPC)-interest. The EPC-interest approximates the change in parameters of in…
Testing for Measurement Invariance by Detecting Local Misspecification and an Illustration Across Online and Paper-and-Pencil Samples
Political scientists often need to evaluate whether samples are comparable, for example, when analysing different countries or time points or when comparing data collected using different methods. A necessary condition for conducting such meaningful cross-group comparisons is the establishment of measurement invariance. One of the most frequently used procedures for establishing measurement invariance is the multigroup confirmatory factor analysi…
Evaluating Measurement Invariance in Categorical Data Latent Variable Models with the EPC-Interest
Many variables crucial to the social sciences are not directly observed but instead are latent and measured indirectly. When an external variable of interest affects this measurement, estimates of its relationship with the latent variable will then be biased. Such violations of “measurement invariance” may, for example, confound true differences across countries in postmaterialism with measurement differences. To deal with this problem, researche…
Questionnaire Science
Some textbooks on questionnaire design claim it is an art. That would make the criterion for a “good” question entirely subjective—a worrying conclusion given that surveys are often used to discover important facts about people. Are our discoveries about people also entirely subjective? This chapter shows that it is possible to study what a “good” or a “bad” question is by experimentation. There is already a body of scientific evidence on questio…
Mixture Models
Hidden Markov Item Response Theory Models for Responses and Response Times
Current approaches to model responses and response times to psychometric tests solely focus on between-subject differences in speed and ability. Within subjects, speed and ability are assumed to be constants. Violations of this assumption are generally absorbed in the residual of the model. As a result, within-subject departures from the between-subject speed and ability level remain undetected. These departures may be of interest to the research…
Goodness-of-fit of Multilevel Latent Class Models for Categorical Data
In the context of multilevel latent class models, the goodness-of-fit depends on multiple aspects, among which are two local independence assumptions. However, because of the lack of local fit statistics, the model and any issues relating to model fit can only be inspected jointly through global fit statistics. This hinders the search for model improvements, as it cannot be determined where misfit originates and which of the many model adjustment…
Places and Preferences
Contextual theories of political behaviour assert that the contexts in which people live influence their political beliefs and vote choices. Most studies, however, fail to distinguish contextual influence from self-selection of individuals into areas. This article advances understanding of this controversy by tracking the left–right position and party identification of thousands of individuals over an eighteen-year period in England before and af…
Big Five personality stability, change, and codevelopment across adolescence and early adulthood
Using data from 2 large and overlapping cohorts of Dutch adolescents, containing up to 7 waves of longitudinal data each (N = 2,230), the present study examined Big Five personality trait stability, change, and codevelopment in friendship and sibling dyads from age 12 to 22. Four findings stand out. First, the 1-year rank-order stability of personality traits was already substantial at age 12, increased strongly from early through middle adolesce…
An open source machine learning framework for efficient and transparent systematic reviews
To help researchers conduct a systematic review or meta-analysis as efficiently and transparently as possible, we designed a tool to accelerate the step of screening titles and abstracts. For many tasks—including but not limited to systematic reviews and meta-analyses—the scientific literature needs to be checked systematically. Scholars and practitioners currently screen thousands of studies by hand to determine which studies to include in their…
Can’t see the wood for the trees? An assessment of street view- and satellite-derived greenness measures in relation to mental health
Greenness in the urban living environment is inconsistently associated with mental health. Satellite-derived measures of greenness may inadequately characterize how people encounter greenness visually on site, but systematic comparisons are lacking. We aimed 1) to compare associations between remotely sensed and street view (SV) greenness, and 2) to examine whether these greenness metrics are differently associated with mental health outcomes. We…
Estimating Measurement Error in Longitudinal Data Using the Longitudinal MultiTrait MultiError Approach
Longitudinal data makes it possible to investigate change in time and its causes. While this type of data is getting more popular there is limited knowledge regarding the measurement errors involved, their stability in time and how they bias estimates of change. In this paper we apply a new method to estimate multiple types of errors concurrently, called the MultiTrait MultiError approach, to longitudinal data. This method uses a combination of e…
Why Measurement Invariance is Important in Comparative Research. A Response to Welzel et al. (2021)
Welzel et al. (2021) claim that non-invariance of instruments is inconclusive and inconsequential in the field for cross-cultural value measurement. In this response, we contend that several key arguments on which Welzel et al. (2021) base their critique of invariance testing are conceptually and statistically incorrect. First, Welzel et al. (2021) claim that value measurement follows a formative rather than reflective logic. Yet they do not prov…
The effect of measurement error on clustering
Clustering is a set of statistical techniques widely applied in the social sciences. While an important and useful tool, traditional clustering techniques tend to assume that the data are free from measurement error, which is often an unrealistic assumption. In this paper, we perform a Monte Carlo study to investigate the sensitivity of different clustering techniques to measurement error. We focus on three commonly used approaches: latent profil…
How Much Data Should I Request? Balancing Richness and Compliance in Digital Trace Data Donations
Digital trace “data donation” studies offer researchers a unique opportunity to collect high-quality behavioral data, but decisions about the scope of requested data can impact both dataset richness and participant compliance. This paper examines the tradeoffs between requesting larger data packages, which include more extensive historical records, and participants’ willingness to donate. In a randomized experiment with Facebook and Instagram dat…
Computer Science (12 obras) · Mathematics (11 obras) · Econometrics (10 obras) · Statistics (10 obras) · Psychology (9 obras) · Latent variable (6 obras) · Structural equation modeling (6 obras) · Categorical variable (4 obras) · Confirmatory factor analysis (4 obras) · Latent class model (4 obras)