Salvatore J Gallicchio
Biographic Data
| ID | 4270654 |
|---|---|
| NAME | Salvatore J Gallicchio |
| GIVEN NAMES | Salvatore J |
| FAMILY NAME | Gallicchio |
| SIGNATURE | GALLICCHIO S J |
| AFFILIATIONS | Social Security Administration |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1985 |
| LATEST PUBLICATION YEAR | 1987 |
| H-INDEX | 1 |
Estimation of Discrete Choice Models in Retrospective Samples
The estimation of the parameters of discrete choice models in retrospective samples is often more complex than in prospective studies. In prospective studies estimation usually employs classical maximum likelihood techniques; however, when samples are stratified on the outcome variable, classical maximum likelihood estimators are often biased in large samples. A number of alternative consistent estimators have been proposed by Manski and McFadden…
Multiple-Indicator, Multiple-Cause Models for a Single Latent Variable with Ordinal Indicators
A MIMIC model is developed that contains a one-dimensional latent variable measured by ordinal indicators. The latent variable can be either discrete and ordered or continuous. Parameters for both the measurement and structural components of the model are estimated simultaneously using the EM algorithm. An example of a sociological application is presented
Estimation of Discrete Choice Models in Retrospective Samples
The estimation of the parameters of discrete choice models in retrospective samples is often more complex than in prospective studies. In prospective studies estimation usually employs classical maximum likelihood techniques; however, when samples are stratified on the outcome variable, classical maximum likelihood estimators are often biased in large samples. A number of alternative consistent estimators have been proposed by Manski and McFadden…
Multiple-Indicator, Multiple-Cause Models for a Single Latent Variable with Ordinal Indicators
A MIMIC model is developed that contains a one-dimensional latent variable measured by ordinal indicators. The latent variable can be either discrete and ordered or continuous. Parameters for both the measurement and structural components of the model are estimated simultaneously using the EM algorithm. An example of a sociological application is presented
Estimation of Discrete Choice Models in Retrospective Samples
The estimation of the parameters of discrete choice models in retrospective samples is often more complex than in prospective studies. In prospective studies estimation usually employs classical maximum likelihood techniques; however, when samples are stratified on the outcome variable, classical maximum likelihood estimators are often biased in large samples. A number of alternative consistent estimators have been proposed by Manski and McFadden…
Computer Science (2 works) · Econometrics (2 works) · Mathematics (2 works) · Statistical Methods and Bayesian Inference (2 works) · Statistics (2 works) · Advanced Statistical Methods and Models (1 works) · Bayesian Modeling and Causal Inference (1 works) · Context (archaeology) (1 works) · Economic and Environmental Valuation (1 works) · Estimation (1 works)