Marcel A Croon
Biographic Data
| ID | 314211 |
|---|---|
| NAME | Marcel A Croon |
| GIVEN NAMES | Marcel A |
| FAMILY NAME | Croon |
| SIGNATURE | CROON M A |
| AFFILIATIONS | Tilburg University |
| VERIFIED | No |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 267 |
| AUTHOR COUNT | 16 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2000 |
| LATEST PUBLICATION YEAR | 2015 |
| H-INDEX | 5 |
Stepwise Latent Class Models for Explaining Group-Level Outcomes Using Discrete Individual-Level Predictors
Explaining group-level outcomes from individual-level predictors requires aggregating the individual-level scores to the group level and correcting the group-level estimates for measurement errors in the aggregated scores. However, for discrete variables it is not clear how to perform the aggregation and correction. It is shown how stepwise latent class analysis can be used to do this. First, a latent class model is estimated in which the scores …
Evaluation of a recovery-oriented care training program for mental healthcare professionals: Effects on mental health consumer outcomes
OBJECTIVES: To examine the effects of a recovery-oriented care training program for mental healthcare professionals on mental health consumer outcomes. METHODS: The Mental Health Recovery Measure (MHRM) and the Recovery-Promoting Relationship Scale (RPRS) were administered to a sample of 142 consumers with severe mental illness. A repeated measurement design with six measurement occasions was used. ANALYSES: Separate analyses were performed for t…
Advancements in Marginal Modeling for Categorical Data
Very often the data collected by social scientists involve dependent observations, without, however, the investigators having any substantive interest in the nature of the dependencies. Although these dependencies are not important for the answers to the research questions concerned, they must still be taken into account in the analysis. Standard statistical estimation and testing procedures assume independent and identically distributed observat…
Standard Errors and Confidence Intervals for Scalability Coefficients in Mokken Scale Analysis Using Marginal Models
Mokken scale analysis is a popular method for scaling dichotomous and polytomous items. Whether or not items form a scale is determined by three types of scalability coefficients: (1) for pairs of items, (2) for items, and (3) for the entire scale. It has become standard practice to interpret the sample values of these scalability coefficients using Mokken’s guidelines, which have been available since the 1970s. For valid assessment of the scalab…
Micro-Macro Multilevel Analysis for Discrete Data: A Latent Variable Approach and an Application on Personal Network Data
A multilevel regression model is proposed in which discrete individual-level variables are used as predictors of discrete group-level outcomes. It generalizes the model proposed by Croon and van Veldhoven for analyzing micro-macro relations with continuous variables by making use of a specific type of latent class model. A first simulation study shows that this approach performs better than more traditional aggregation and disaggreagtion procedur…
Enriched job design, high involvement management and organizational performance: The mediating roles of job satisfaction and well-being
The relationship between organizational performance and two dimensions of the ‘high performance work system’ – enriched job design and high involvement management (HIM) – is widely assumed to be mediated by worker well-being. We outline the basis for three models: mutual-gains, in which employee involvement increases well-being and this mediates its positive relationship with performance; conflicting outcomes, which associates involvement with in…
Autonomy-connectedness, acculturation, and independence–interdependence among various cultural groups in a multicultural society
When and for whom does crying improve mood? A daily diary study of 1004 crying episodes
The Multiple Propensity Score as Control for Bias in the Comparison of More Than Two Treatment Arms: An Introduction From a Case Study in Mental Health
BACKGROUND AND OBJECTIVE: The propensity score method (PS) has proven to be an effective tool to reduce bias in nonrandomized studies, especially when the number of (potential) confounders is large and dimensionality problems arise. The PS method introduced by Rosenbaum and Rubin is described in detail for studies with 2 treatment options. Since in clinical practice we are often interested in the comparison of multiple interventions, there was a …
The roles of autonomy-connectedness and attachment styles in depression and anxiety
The present study examined how autonomy-connectedness and attachment styles relate to depression and anxiety among 69 clients at a primary mental health care institution and 105 non-clients. We expected poor autonomy-connectedness (i.e., low self-awareness, low capacity for managing new situations, and high sensitivity to others) and insecure attachment to predict depression and anxiety. Clients, compared with non-clients, differed on all study v…
Predicting group-level outcome variables from variables measured at the individual level: A latent variable multilevel model.
In multilevel modeling, one often distinguishes between macro-micro and micro-macro situations. In a macro-micro multilevel situation, a dependent variable measured at the lower level is predicted or explained by variables measured at that lower or a higher level. In a micro-macro multilevel situation, a dependent variable defined at the higher group level is predicted or explained on the basis of independent variables measured at the lower indiv…
Personality, psychological stress, and self-reported influenza symptomatology
Elderly and socially inhibited persons tend to report less ILI as compared to their younger and less socially inhibited counterparts. In contrast, asthma, trait negative affectivity, and perceived stress were associated with higher self-report of ILI. Our results demonstrate the importance of including trait markers in future studies examining the relation between stress and self-report symptom measures
The Romance of Leadership Scale: Cross-cultural Testing and Refinement
The Romance of Leadership Scale (RLS) has been used in various studies in different countries and contexts. However, to date, the structure of the scale has been a subject of discussion, making it difficult to compare results over different studies. In this study, using student as well as organization samples from two countries, we want to clarify the factor structure of the RLS. In order to do so, we used a hypothetical factor matrix into which …
Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators
We study the properties of a three-step approach to estimating the parameters of a latent structure model for categorical data and propose a simple correction for a common source of bias. Such models have a measurement part (essentially the latent class model) and a structural (causal) part (essentially a system of logit equations). In the three-step approach, a stand-alone measurement model is first defined and its parameters are estimated. Indi…
Analyzing Change in Categorical Variables by Generalized Log-Linear Models
This article discusses how several hypotheses about change in discrete variables can be tested on data obtained in a longitudinal study. A first class of hypotheses pertain to the invariance of certain characteristics of marginal distributions. A second class of hypotheses derive from assumptions about the causal relations between the variables. In this article, the authors show how all these hypotheses can be tested by means of a generalization …
Estimating True Changes when Categorical Panel Data are Affected by Uncorrelated and Correlated Classification Errors: An Application to Unemployment Data
Conclusions about changes in categorical characteristics based on observed panel data can be incorrect when (even a small amount of) measurement error is present. Random measurement errors, referred to as independent classification errors, usually lead to over-estimation of the total amount of gross change, whereas systematic, correlated errors usually cause underestimation of the transitions. Furthermore, the patterns of true change may be serio…
Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators
We study the properties of a three-step approach to estimating the parameters of a latent structure model for categorical data and propose a simple correction for a common source of bias. Such models have a measurement part (essentially the latent class model) and a structural (causal) part (essentially a system of logit equations). In the three-step approach, a stand-alone measurement model is first defined and its parameters are estimated. Indi…
Enriched job design, high involvement management and organizational performance: The mediating roles of job satisfaction and well-being
The relationship between organizational performance and two dimensions of the ‘high performance work system’ – enriched job design and high involvement management (HIM) – is widely assumed to be mediated by worker well-being. We outline the basis for three models: mutual-gains, in which employee involvement increases well-being and this mediates its positive relationship with performance; conflicting outcomes, which associates involvement with in…
Estimating True Changes when Categorical Panel Data are Affected by Uncorrelated and Correlated Classification Errors: An Application to Unemployment Data
Conclusions about changes in categorical characteristics based on observed panel data can be incorrect when (even a small amount of) measurement error is present. Random measurement errors, referred to as independent classification errors, usually lead to over-estimation of the total amount of gross change, whereas systematic, correlated errors usually cause underestimation of the transitions. Furthermore, the patterns of true change may be serio…
Micro-Macro Multilevel Analysis for Discrete Data: A Latent Variable Approach and an Application on Personal Network Data
A multilevel regression model is proposed in which discrete individual-level variables are used as predictors of discrete group-level outcomes. It generalizes the model proposed by Croon and van Veldhoven for analyzing micro-macro relations with continuous variables by making use of a specific type of latent class model. A first simulation study shows that this approach performs better than more traditional aggregation and disaggreagtion procedur…
The roles of autonomy-connectedness and attachment styles in depression and anxiety
The present study examined how autonomy-connectedness and attachment styles relate to depression and anxiety among 69 clients at a primary mental health care institution and 105 non-clients. We expected poor autonomy-connectedness (i.e., low self-awareness, low capacity for managing new situations, and high sensitivity to others) and insecure attachment to predict depression and anxiety. Clients, compared with non-clients, differed on all study v…
Standard Errors and Confidence Intervals for Scalability Coefficients in Mokken Scale Analysis Using Marginal Models
Mokken scale analysis is a popular method for scaling dichotomous and polytomous items. Whether or not items form a scale is determined by three types of scalability coefficients: (1) for pairs of items, (2) for items, and (3) for the entire scale. It has become standard practice to interpret the sample values of these scalability coefficients using Mokken’s guidelines, which have been available since the 1970s. For valid assessment of the scalab…
When and for whom does crying improve mood? A daily diary study of 1004 crying episodes
The Romance of Leadership Scale: Cross-cultural Testing and Refinement
The Romance of Leadership Scale (RLS) has been used in various studies in different countries and contexts. However, to date, the structure of the scale has been a subject of discussion, making it difficult to compare results over different studies. In this study, using student as well as organization samples from two countries, we want to clarify the factor structure of the RLS. In order to do so, we used a hypothetical factor matrix into which …
Analyzing Change in Categorical Variables by Generalized Log-Linear Models
This article discusses how several hypotheses about change in discrete variables can be tested on data obtained in a longitudinal study. A first class of hypotheses pertain to the invariance of certain characteristics of marginal distributions. A second class of hypotheses derive from assumptions about the causal relations between the variables. In this article, the authors show how all these hypotheses can be tested by means of a generalization …
Autonomy-connectedness, acculturation, and independence–interdependence among various cultural groups in a multicultural society
Analyzing Change in Categorical Variables by Generalized Log-Linear Models
This article discusses how several hypotheses about change in discrete variables can be tested on data obtained in a longitudinal study. A first class of hypotheses pertain to the invariance of certain characteristics of marginal distributions. A second class of hypotheses derive from assumptions about the causal relations between the variables. In this article, the authors show how all these hypotheses can be tested by means of a generalization …
Estimating True Changes when Categorical Panel Data are Affected by Uncorrelated and Correlated Classification Errors: An Application to Unemployment Data
Conclusions about changes in categorical characteristics based on observed panel data can be incorrect when (even a small amount of) measurement error is present. Random measurement errors, referred to as independent classification errors, usually lead to over-estimation of the total amount of gross change, whereas systematic, correlated errors usually cause underestimation of the transitions. Furthermore, the patterns of true change may be serio…
Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators
We study the properties of a three-step approach to estimating the parameters of a latent structure model for categorical data and propose a simple correction for a common source of bias. Such models have a measurement part (essentially the latent class model) and a structural (causal) part (essentially a system of logit equations). In the three-step approach, a stand-alone measurement model is first defined and its parameters are estimated. Indi…
Predicting group-level outcome variables from variables measured at the individual level: A latent variable multilevel model.
In multilevel modeling, one often distinguishes between macro-micro and micro-macro situations. In a macro-micro multilevel situation, a dependent variable measured at the lower level is predicted or explained by variables measured at that lower or a higher level. In a micro-macro multilevel situation, a dependent variable defined at the higher group level is predicted or explained on the basis of independent variables measured at the lower indiv…
Personality, psychological stress, and self-reported influenza symptomatology
Elderly and socially inhibited persons tend to report less ILI as compared to their younger and less socially inhibited counterparts. In contrast, asthma, trait negative affectivity, and perceived stress were associated with higher self-report of ILI. Our results demonstrate the importance of including trait markers in future studies examining the relation between stress and self-report symptom measures
The Romance of Leadership Scale: Cross-cultural Testing and Refinement
The Romance of Leadership Scale (RLS) has been used in various studies in different countries and contexts. However, to date, the structure of the scale has been a subject of discussion, making it difficult to compare results over different studies. In this study, using student as well as organization samples from two countries, we want to clarify the factor structure of the RLS. In order to do so, we used a hypothetical factor matrix into which …
The Multiple Propensity Score as Control for Bias in the Comparison of More Than Two Treatment Arms: An Introduction From a Case Study in Mental Health
BACKGROUND AND OBJECTIVE: The propensity score method (PS) has proven to be an effective tool to reduce bias in nonrandomized studies, especially when the number of (potential) confounders is large and dimensionality problems arise. The PS method introduced by Rosenbaum and Rubin is described in detail for studies with 2 treatment options. Since in clinical practice we are often interested in the comparison of multiple interventions, there was a …
The roles of autonomy-connectedness and attachment styles in depression and anxiety
The present study examined how autonomy-connectedness and attachment styles relate to depression and anxiety among 69 clients at a primary mental health care institution and 105 non-clients. We expected poor autonomy-connectedness (i.e., low self-awareness, low capacity for managing new situations, and high sensitivity to others) and insecure attachment to predict depression and anxiety. Clients, compared with non-clients, differed on all study v…
Autonomy-connectedness, acculturation, and independence–interdependence among various cultural groups in a multicultural society
When and for whom does crying improve mood? A daily diary study of 1004 crying episodes
Enriched job design, high involvement management and organizational performance: The mediating roles of job satisfaction and well-being
The relationship between organizational performance and two dimensions of the ‘high performance work system’ – enriched job design and high involvement management (HIM) – is widely assumed to be mediated by worker well-being. We outline the basis for three models: mutual-gains, in which employee involvement increases well-being and this mediates its positive relationship with performance; conflicting outcomes, which associates involvement with in…
Advancements in Marginal Modeling for Categorical Data
Very often the data collected by social scientists involve dependent observations, without, however, the investigators having any substantive interest in the nature of the dependencies. Although these dependencies are not important for the answers to the research questions concerned, they must still be taken into account in the analysis. Standard statistical estimation and testing procedures assume independent and identically distributed observat…
Standard Errors and Confidence Intervals for Scalability Coefficients in Mokken Scale Analysis Using Marginal Models
Mokken scale analysis is a popular method for scaling dichotomous and polytomous items. Whether or not items form a scale is determined by three types of scalability coefficients: (1) for pairs of items, (2) for items, and (3) for the entire scale. It has become standard practice to interpret the sample values of these scalability coefficients using Mokken’s guidelines, which have been available since the 1970s. For valid assessment of the scalab…
Micro-Macro Multilevel Analysis for Discrete Data: A Latent Variable Approach and an Application on Personal Network Data
A multilevel regression model is proposed in which discrete individual-level variables are used as predictors of discrete group-level outcomes. It generalizes the model proposed by Croon and van Veldhoven for analyzing micro-macro relations with continuous variables by making use of a specific type of latent class model. A first simulation study shows that this approach performs better than more traditional aggregation and disaggreagtion procedur…
Stepwise Latent Class Models for Explaining Group-Level Outcomes Using Discrete Individual-Level Predictors
Explaining group-level outcomes from individual-level predictors requires aggregating the individual-level scores to the group level and correcting the group-level estimates for measurement errors in the aggregated scores. However, for discrete variables it is not clear how to perform the aggregation and correction. It is shown how stepwise latent class analysis can be used to do this. First, a latent class model is estimated in which the scores …
Evaluation of a recovery-oriented care training program for mental healthcare professionals: Effects on mental health consumer outcomes
OBJECTIVES: To examine the effects of a recovery-oriented care training program for mental healthcare professionals on mental health consumer outcomes. METHODS: The Mental Health Recovery Measure (MHRM) and the Recovery-Promoting Relationship Scale (RPRS) were administered to a sample of 142 consumers with severe mental illness. A repeated measurement design with six measurement occasions was used. ANALYSES: Separate analyses were performed for t…
Mathematics (9 works) · Psychology (9 works) · Statistics (9 works) · Computer Science (8 works) · Econometrics (8 works) · Social Psychology (6 works) · Advanced Causal Inference Techniques (5 works) · Social Psychology (5 works) · Artificial Intelligence (4 works) · Artificial Intelligence (4 works)