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| DC Field | Value | Language |
|---|---|---|
| dc.creator | Spiess, Martin | - |
| dc.creator | Tutz, Gerhard | - |
| dc.date | 2002 | - |
| dc.date.accessioned | 2013-10-16T06:59:14Z | - |
| dc.date.available | 2013-10-16T06:59:14Z | - |
| dc.date.issued | 2013-10-16 | - |
| dc.identifier | http://hdl.handle.net/10419/18275 | - |
| dc.identifier | ppn:354866583 | - |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/10419/18275 | - |
| dc.description | In this paper R2-type measures of the explanatory power of multivariate linear and categorical probit models proposed in the literature are reviewed and their deficiencies are discussed. It is argued that a measure of the explanatory power should take into account the components which are explicitely modeled when a regression model is estimated while it should be indifferent to components not explicitely modeled. Based on this view three different measures for multivariate probit models are proposed. Results of a simulation study are presented designed to compare two measures in various situations and evaluate the BCa bootstrap technique for testing the hypothesis that the corresponding measure is zero and to calculate approximate confidence intervals. The BCa bootstrap technique turned out to work quite well for a wide range of situations, but may lead to misleading results if the true values of the corresponding measure is close to zero. | - |
| dc.description | In diesem Beitrag werden in der Literatur vorgeschlagene R2-artige Maße der Erklärungskraft multivariater linearer und kategorialer Probitmodelle dargestellt und deren Nachteile diskutiert. Ausgehend von der Bedingung, dass ein solches Maß modellierte Komponenten eines Regressionsmodells berücksichtigen aber gleichzeitig indifferent gegenüber nicht modellierten Komponenten sein sollte, werden drei unterschiedliche Masse für multivariate Probitmodelle vorgeschlagen. Es werden Ergebnisse eines Simulationsexperimentes präsentiert, bei dem zwei der drei vorgeschlagenen Masse in verschiedenen Situationen verglichen werden und die BCa Bootstrap-Methode zur Testung der Hypothese, dass das entsprechende Maß gleich null ist und zur Berechnung approximativer Konfidenzintervalle evaluiert wird. Es zeigt sich, dass die BCa-Methode im Allgemeinen ordentliche Ergebnisse liefert, aber zu irreführenden Ergebnissen führen kann, wenn der "wahre" Wert des entsprechenden Maßes nahe bei null liegt. | - |
| dc.language | eng | - |
| dc.publisher | Deutsches Institut für Wirtschaftsforschung (DIW) Berlin | - |
| dc.relation | DIW-Diskussionspapiere 291 | - |
| dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | - |
| dc.subject | C52 | - |
| dc.subject | C35 | - |
| dc.subject | C33 | - |
| dc.subject | C15 | - |
| dc.subject | ddc:330 | - |
| dc.subject | Pseudo-R2 | - |
| dc.subject | Measure of explanatory power | - |
| dc.subject | Multivariate probit model | - |
| dc.subject | Panel model | - |
| dc.subject | Simulation study | - |
| dc.subject | Bootstrap confidence intervals | - |
| dc.subject | Probit-Modell | - |
| dc.subject | Schätztheorie | - |
| dc.subject | Statistischer Test | - |
| dc.subject | Theorie | - |
| dc.title | Alternative measures of the explanatory power of multivariate probit models with continuous or ordinal responses | - |
| dc.type | doc-type:workingPaper | - |
| Appears in Collections: | EconStor | |
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