C Heath Gauss
Biographic Data
| ID | 5541067 |
|---|---|
| NAME | C Heath Gauss |
| GIVEN NAMES | C Heath |
| FAMILY NAME | Gauss |
| SIGNATURE | GAUSS C H |
| AFFILIATIONS | University of Arkansas for Medical Sciences |
| ORCID | 0000-0001-9488-780X |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2012 |
| H-INDEX | 0 |
Evaluating the Effect of Hospital and Insurance Type on the Risk of 1-year Mortality of Very Low Birth Weight Infants
OBJECTIVES: We examined the effect of hospital type and medical coverage on the risk of 1-year mortality of very low birth weight (VLBW) infants while adjusting for possible selection bias. METHODS: The study population was limited to singleton live birth infants having birth weight between 500 and 1500 g with no congenital anomalies who were born in Arkansas hospitals between 2001 and 2007. Propensity score (PS) matching and PS covariate adjustm…
Purposeful selection of variables in logistic regression
BACKGROUND: The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covaria…
No prominent works on this page.
Purposeful selection of variables in logistic regression
BACKGROUND: The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covaria…
Evaluating the Effect of Hospital and Insurance Type on the Risk of 1-year Mortality of Very Low Birth Weight Infants
OBJECTIVES: We examined the effect of hospital type and medical coverage on the risk of 1-year mortality of very low birth weight (VLBW) infants while adjusting for possible selection bias. METHODS: The study population was limited to singleton live birth infants having birth weight between 500 and 1500 g with no congenital anomalies who were born in Arkansas hospitals between 2001 and 2007. Propensity score (PS) matching and PS covariate adjustm…
Logistic regression (2 works) · Absolute risk reduction (1 work) · Advanced Causal Inference Techniques (1 work) · Birth weight (1 work) · Computer Science (1 work) · Confidence interval (1 work) · Confounding (1 work) · Covariate (1 work) · Data mining (1 work) · Econometrics (1 work)