Add to ORKGThis paper develops stochastic search variable selection (SSVS) for zero-inflated count models which are commonly used in health economics. This allows for either model averaging or model selection in situations with many potential regressors. The proposed techniques are applied to a data set from Germany considering the demand for health care. A package for the free statistical software environment R is provided
The zero inflated models are usually used in modeling count data with excess zeros where the existen...
Response variables that are scored as counts and that present a large number of zeros often arise in...
In this paper is proposed a straightforward model selection approach that indicates the most suitabl...
This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which...
This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which...
In health services and outcome research, count outcomes are frequently encountered and often have a ...
When count data exhibit excess zero, that is more zero counts than a simpler parametric distribution...
This study is concerned with the estimation of microeconometric models of health care utilisation. T...
This study is concerned with the estimation of microeconometric models of health care utilisation.Th...
The performance of several models under different conditions of zero-inflation and dispersion are ev...
The performance of several models under different conditions of zero-inflation and dispersion are ev...
Zero inflation and over-dispersion issues can significantly affect the predicted probabilities as we...
Zero‐inflated count data are very common in health surveys. This study develops new variable selecti...
Applications of zero-inflated count data models have proliferated in health economics. However, zero...
Background: Zero-inflated models are generally aimed to addressing the problem that arises from havi...
The zero inflated models are usually used in modeling count data with excess zeros where the existen...
Response variables that are scored as counts and that present a large number of zeros often arise in...
In this paper is proposed a straightforward model selection approach that indicates the most suitabl...
This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which...
This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which...
In health services and outcome research, count outcomes are frequently encountered and often have a ...
When count data exhibit excess zero, that is more zero counts than a simpler parametric distribution...
This study is concerned with the estimation of microeconometric models of health care utilisation. T...
This study is concerned with the estimation of microeconometric models of health care utilisation.Th...
The performance of several models under different conditions of zero-inflation and dispersion are ev...
The performance of several models under different conditions of zero-inflation and dispersion are ev...
Zero inflation and over-dispersion issues can significantly affect the predicted probabilities as we...
Zero‐inflated count data are very common in health surveys. This study develops new variable selecti...
Applications of zero-inflated count data models have proliferated in health economics. However, zero...
Background: Zero-inflated models are generally aimed to addressing the problem that arises from havi...
The zero inflated models are usually used in modeling count data with excess zeros where the existen...
Response variables that are scored as counts and that present a large number of zeros often arise in...
In this paper is proposed a straightforward model selection approach that indicates the most suitabl...