Ita G G Kreft
Biographic Data
| ID | 4136695 |
|---|---|
| NAME | Ita G G Kreft |
| GIVEN NAMES | Ita G G |
| FAMILY NAME | Kreft |
| SIGNATURE | KREFT I G G |
| AFFILIATIONS | University of California, Los Angeles |
| VERIFIED | No |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 124 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1991 |
| LATEST PUBLICATION YEAR | 2004 |
| H-INDEX | 4 |
The Effect of Interviewer and Respondent Characteristics on the Quality of Survey Data: A Multilevel Model
This chapter contains sections titled: Review of Previous Research Multilevel Models for Interviewer Effects Data Collection Results Summary and Discussion
Introducing Multilevel Modeling
The Effect of Different Forms of Centering in Hierarchical Linear Models
Multilevel models are becoming increasingly used in applied educational social and economic research for the analysis of hierarchically nested data. In these random coefficient regression models the parameters are allowed to differ over the groups in which the observations are nested. For computational ease in deriving parameter estimates, predictors are often centered around the mean. In nested or grouped data, the option of centering around the…
The Gender Gap in Earnings: A Two-Way Nested Multiple Regression Analysis with Random Effects
The gender income gap is a much debated subject both at an analytical and economic level. This article considers both, but emphasizes the different ways the data can be analyzed. The authors show that a hierarchical linear model is the best way to evaluate male-female wage differentials. Both interindustry and intraindustry wage disparities between men and women are measured by using a technique that assumes that observations within the same indu…
Multilevel Analysis Methods
This special issue of SMR is about the analysis of data collected at different levels of observation, such as groups and individuals within these groups, and about the methodological problems that are present when natural experimentation and observations nested within existing social groups are the object of study. The methodological problems are summarized in the term multilevel problems. A multilevel problem is a problem that inquires into the …
Using Multilevel Analysis to Assess School Effectiveness: A Study of Dutch Secondary Schools
This article is divided into three parts to show separate but related developments in the new generation of research on school effectiveness. The first part presents a historical overview of the development of this research from a narrow individualistic input-out approach to a more holistic approach that evaluates within-school processes. The second part reviews two competing theories of school effectiveness and the search for an appropriate anal…
The Analysis of Factorial Surveys
Factorial surveys constitute a specific technique for introducing experimental designs in sample surveys. Respondents are presented with descriptions (vignettes) of a constructed world in which important factors are built in experimentally. Using balanced designs well known from the multivariate experimental tradition, it is possible to build in a relatively large number of factors and levels. Within this context, the normal hypothesis is that re…
Multilevel Analysis Methods
This special issue of SMR is about the analysis of data collected at different levels of observation, such as groups and individuals within these groups, and about the methodological problems that are present when natural experimentation and observations nested within existing social groups are the object of study. The methodological problems are summarized in the term multilevel problems. A multilevel problem is a problem that inquires into the …
The Analysis of Factorial Surveys
Factorial surveys constitute a specific technique for introducing experimental designs in sample surveys. Respondents are presented with descriptions (vignettes) of a constructed world in which important factors are built in experimentally. Using balanced designs well known from the multivariate experimental tradition, it is possible to build in a relatively large number of factors and levels. Within this context, the normal hypothesis is that re…
Using Multilevel Analysis to Assess School Effectiveness: A Study of Dutch Secondary Schools
This article is divided into three parts to show separate but related developments in the new generation of research on school effectiveness. The first part presents a historical overview of the development of this research from a narrow individualistic input-out approach to a more holistic approach that evaluates within-school processes. The second part reviews two competing theories of school effectiveness and the search for an appropriate anal…
The Gender Gap in Earnings: A Two-Way Nested Multiple Regression Analysis with Random Effects
The gender income gap is a much debated subject both at an analytical and economic level. This article considers both, but emphasizes the different ways the data can be analyzed. The authors show that a hierarchical linear model is the best way to evaluate male-female wage differentials. Both interindustry and intraindustry wage disparities between men and women are measured by using a technique that assumes that observations within the same indu…
The Analysis of Factorial Surveys
Factorial surveys constitute a specific technique for introducing experimental designs in sample surveys. Respondents are presented with descriptions (vignettes) of a constructed world in which important factors are built in experimentally. Using balanced designs well known from the multivariate experimental tradition, it is possible to build in a relatively large number of factors and levels. Within this context, the normal hypothesis is that re…
Using Multilevel Analysis to Assess School Effectiveness: A Study of Dutch Secondary Schools
This article is divided into three parts to show separate but related developments in the new generation of research on school effectiveness. The first part presents a historical overview of the development of this research from a narrow individualistic input-out approach to a more holistic approach that evaluates within-school processes. The second part reviews two competing theories of school effectiveness and the search for an appropriate anal…
The Gender Gap in Earnings: A Two-Way Nested Multiple Regression Analysis with Random Effects
The gender income gap is a much debated subject both at an analytical and economic level. This article considers both, but emphasizes the different ways the data can be analyzed. The authors show that a hierarchical linear model is the best way to evaluate male-female wage differentials. Both interindustry and intraindustry wage disparities between men and women are measured by using a technique that assumes that observations within the same indu…
Multilevel Analysis Methods
This special issue of SMR is about the analysis of data collected at different levels of observation, such as groups and individuals within these groups, and about the methodological problems that are present when natural experimentation and observations nested within existing social groups are the object of study. The methodological problems are summarized in the term multilevel problems. A multilevel problem is a problem that inquires into the …
The Effect of Different Forms of Centering in Hierarchical Linear Models
Multilevel models are becoming increasingly used in applied educational social and economic research for the analysis of hierarchically nested data. In these random coefficient regression models the parameters are allowed to differ over the groups in which the observations are nested. For computational ease in deriving parameter estimates, predictors are often centered around the mean. In nested or grouped data, the option of centering around the…
Introducing Multilevel Modeling
The Effect of Interviewer and Respondent Characteristics on the Quality of Survey Data: A Multilevel Model
This chapter contains sections titled: Review of Previous Research Multilevel Models for Interviewer Effects Data Collection Results Summary and Discussion
Multilevel model (5 works) · Computer Science (4 works) · Mathematics (4 works) · Statistics (4 works) · Econometrics (3 works) · Psychology (3 works) · Respondent (2 works) · Sociology (2 works) · Survey data collection (2 works) · Academic achievement (1 works)