Ordered Logit Regression Modeling of the Self-Rated Health in Hawai‘i, With Comparisons to the OLS Model
نویسنده
چکیده
Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.
منابع مشابه
Ordered Logit Regression Modeling of the Self-Rated Health in Hawaiâ•Ÿi, With Comparisons to the OLS Model
Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.
متن کاملComparison of the Performance of Geographically Weighted Regression and Ordinary Least Squares for modeling of Sea surface temperature in Oman Sea
In Marine discussions, the study of sea surface temperature (SST) and study of its spatial relationships with other ocean parameters are of particular importance, in such a way that the accurate recognition of the SST relationships with other parameters allows the study of many ocean and atmospheric processes. Therefore, in this study, spatial relations modeling of SST with Surface Wind Speed (...
متن کاملEstimating heterogeneous choice models with oglm
When a binary or ordinal regression model incorrectly assumes that error variances are the same for all cases, the standard errors are wrong and (unlike OLS regression) the parameter estimates are biased. Heterogeneous choice (also known as location-scale or heteroskedastic ordered) models explicitly specify the determinants of heteroskedasticity in an attempt to correct for it. Such models are...
متن کاملoglmx: A Package for Estimation of Ordered Generalized Linear Models
Ordered discrete dependent variable models such as ordered probit and ordered logit are frequently used across the social sciences to study outcomes including health status, happiness, wealth and educational attainment. Unlike in the case of OLS, unaccounted for heteroskedasticity in these models can lead to biased parameter estimates. This paper introduces the oglmx package for the R statistic...
متن کاملOn Rank-Ordered Nested Multinomial Logit Model and D-Optimal Design for this Model
In contrast to the classical discrete choice experiment, the respondent in a rank-order discrete choice experiment, is asked to rank a number of alternatives instead of the preferred one. In this paper, we study the information matrix of a rank order nested multinomial logit model (RO.NMNL) and introduce local D-optimality criterion, then we obtain Locally D-optimal design for RO.NMNL models in...
متن کامل