Generalized modeling approaches to risk adjustment of skewed outcomes data.
نویسندگان
چکیده
There are two broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., ordinary least square (OLS) on ln(y)); and (2) alternative weighting approaches based on exponential conditional models (ECM) and generalized linear model (GLM) approaches. In this paper, we encompass these two classes of models using the three parameter generalized Gamma (GGM) distribution, which includes several of the standard alternatives as special cases-OLS with a normal error, OLS for the log-normal, the standard Gamma and exponential with a log link, and the Weibull. Using simulation methods, we find the tests of identifying distributions to be robust. The GGM also provides a potentially more robust alternative estimator to the standard alternatives. An example using inpatient expenditures is also analyzed.
منابع مشابه
Estimation of Value at Risk (VaR) Based On Lévy-GARCH Models: Evidence from Tehran Stock Exchange
This paper aims to estimate the Value-at-Risk (VaR) using GARCH type models with improved return distribution. Value at Risk (VaR) is an essential benchmark for measuring the risk of financial markets quantitatively. The parametric method, historical simulation, and Monte Carlo simulation have been proposed in several financial mathematics and engineering studies to calculate VaR, that each of ...
متن کاملFirms’ Characteristics and Adjustment Speed of Dividend Payout Ratio: System-GMM and Differenced-GMM Approaches
Since paying over or not paying dividends can cause the firms to face financial crises, firms are always looking for discovery and using a target (optimal) dividend payout ratio. It should be noted that a dividend ratio is a dynamic number and a variety of factors affect it over time. The movement speed of the dividend payout ratio towards the target depends on several factors. This paper inves...
متن کاملModeling In Vitro Fertilization Data Considering Multiple Outcomes Observed among Iranian Infertile Women
Objective Women undergoing IVF cycles should go successfully through multiple points during the procedure (i.e., implantation, clinical pregnancy, no spontaneous abortion and delivery) to achieve live births. On the other there is a need to consider previous reproductive outcomes and as well as the current cycle. In this study, data on multiple cycles and multiple points during the IVF cycle ar...
متن کاملRegression Modeling for Spherical Data via Non-parametric and Least Square Methods
Introduction Statistical analysis of the data on the Earth's surface was a favorite subject among many researchers. Such data can be related to animal's migration from a region to another position. Then, statistical modeling of their paths helps biological researchers to predict their movements and estimate the areas that are most likely to constitute the presence of the animals. From a geome...
متن کاملAlternative regression models to assess increase in childhood BMI
BACKGROUND Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations. METHODS Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs), quantile regression and General...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Journal of health economics
دوره 24 3 شماره
صفحات -
تاریخ انتشار 2005