Constrained and Unconstrained Maximum Likelihood Estimation of a Variance Components Model of Cross- Sections Pooled Over Time
| dc.creator | Tuma, Nancy | |
| dc.creator | Young, Alice A | |
| dc.date.accessioned | 2015-08-15T23:03:39Z | |
| dc.date.available | 2015-08-15T23:03:39Z | |
| dc.date.issued | 2015-08-15 | |
| dc.description.abstract | The authors report on simulations on the quality of parameter estimates of regression coefficients with lagged variables. Results showed that the quality of estimates varied with the amount of serial error correlation and with the relative strength of effects of lagged variables. Estimates of the coefficient of an exogenous variable should be very similar by maximum likelihood estimates and modified generalized least squares. If they are not close to identical, an investigator should suspect misspecification of the model. | en |
| dc.identifier.uri | https://hdl.handle.net/1969.1/154801 | |
| dc.language.iso | en_US | |
| dc.relation.ispartofseries | Technical Report Stanford Sociology;#60 | |
| dc.rights | Attribution 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | |
| dc.subject | lagged variables | en |
| dc.subject | error correlation | en |
| dc.subject | maximum likelihood estimation | en |
| dc.subject | modified generalized least squares | en |
| dc.title | Constrained and Unconstrained Maximum Likelihood Estimation of a Variance Components Model of Cross- Sections Pooled Over Time | en |
| dc.type | Technical Report | en |
| local.department | Sociology | en |
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