The Interpretation of Coefficients in N-chotomous Qualitative Response Models

1998 ◽  
Author(s):  
Marc J. LeClere
Keyword(s):  
Response Models ◽  
Qualitative Response

An application and comparison of some flexible parametric and semiparametric qualitative-response models with heteroskedasticity

2000 ◽  
Vol 31 (1) ◽  
pp. 27-33 ◽  
Author(s):  
James B. Mcdonald ◽  
James V. Hansen
Keyword(s):  
Response Models ◽  
Qualitative Response

scholarly journals Qualitative Response Models

2014 ◽  
pp. 107-140
Author(s):  
Bernt P. Stigum
Keyword(s):  
Response Models ◽  
Qualitative Response

scholarly journals Qualitative Response Models

2007 ◽  
pp. 366-382 ◽  
Author(s):  
G.S. Maddala ◽  
A. Flores-Lagunes
Keyword(s):  
Response Models ◽  
Qualitative Response

scholarly journals Qualitative response models

1983 ◽  
pp. 1-38 ◽  
Author(s):  
Daniel McFadden
Keyword(s):  
Response Models ◽  
Qualitative Response

Application of qualitative response models in a relevance study of older adults' health depreciation and medical care demand

2016 ◽  
Vol 17 (4) ◽  
pp. 645-652
Author(s):  
Shuo-Chun Weng ◽  
Yu-Chi Chen ◽  
Ching-Yu Chen ◽  
Yuan-Yang Cheng ◽  
Yih-Jing Tang ◽  
...  
Keyword(s):  
Older Adults ◽  
Medical Care ◽  
Response Models ◽  
Qualitative Response

Ordered and unordered multinomial response models: an application to assess loblolly pine merchantability

1991 ◽  
Vol 21 (2) ◽  
pp. 261-268 ◽  
Author(s):  
Alexandros A. Arabatzis ◽  
Timothy G. Gregoire
Keyword(s):  
Loblolly Pine ◽  
Regression Models ◽  
Research Work ◽  
Future Research ◽  
Response Models ◽  
Multinomial Models ◽  
Qualitative Response ◽  
Dependent Variables ◽  
Pine Trees ◽  
Discrete Values

Qualitative response models constitute a class of regression models used to predict one of a discrete number of mutually exclusive outcomes. These models differ from continuous regression models in that the response variable takes only discrete values. In forestry applications, the use of such models has been largely confined to mortality studies where the dependent variable is dichotomous. However, it is common in forestry to deal with variables that are either naturally discrete or continuous but recorded discretely. Consequently, there is a need for models that are appropriate for polychotomous dependent variables. Two models that appear to be suitable for forestry applications are presented, namely the ordered and unordered multinomial models, with emphasis on their theoretical justification, statistical inference, and model selection criteria. Using permanent plot data from loblolly pine (Pinustaeda L.) plantations on cutover, site-prepared areas throughout the southern United States, these models were fitted to assess the merchantability of loblolly pine trees. The results demonstrate the potential of qualitative response models for meaningful implementation in a variety of forestry applications and, also, for suggested topics for future research work.

Racial Differences in Intersegment Mobility

1991 ◽  
Vol 20 (2) ◽  
pp. 23-43 ◽  
Author(s):  
Jeffrey Waddoups
Keyword(s):  
Human Capital ◽  
Labor Market ◽  
Racial Differences ◽  
Mobility Patterns ◽  
Market Conditions ◽  
Labor Market Conditions ◽  
Response Models ◽  
Qualitative Response ◽  
Segmented Labor Market

This article is an exploration of racial differences in the intersegment mobility process in a segmented labor market. To this end, a series of qualitative response models describing mobility of prime-age white and nonwhite males through a tripartite segmented labor market is constructed. It is found that demand variables representing labor market conditions, as well as traditional human capital variables are important predictors of intersegment mobility. It is also evident that there are striking racial differences in intersegment mobility patterns.

Sign in / Sign up

Export Citation Format

Share Document