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C Heath Gauss

Biographic Data

ID5541067
NAMEC Heath Gauss
GIVEN NAMESC Heath
FAMILY NAMEGauss
SIGNATUREGAUSS C H
AFFILIATIONSUniversity of Arkansas for Medical Sciences
ORCID0000-0001-9488-780X
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2008
LATEST PUBLICATION YEAR2012
H-INDEX0
  • Evaluating the Effect of Hospital and Insurance Type on the Risk of 1-year Mortality of Very Low Birth Weight Infants

    Songthip Ounpraseuth, C Heath Gauss et al.•ARTICLE•Medical Care•2012•References: 30

    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

    Open Access•Zoran Bursac, C Heath Gauss et al.•ARTICLE•Source Code for Biology and…•2008

    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

    Open Access•Zoran Bursac, C Heath Gauss et al.•ARTICLE•Source Code for Biology and…•2008

    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

    Songthip Ounpraseuth, C Heath Gauss et al.•ARTICLE•Medical Care•2012•References: 30

    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)

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