Sentence examples for multivariable regression techniques from inspiring English sources

Exact(8)

An accurate and consistent extraction technique is developed to extract the values of various important parameters based on non-linear and multivariable regression techniques for the first time.

Multivariable regression techniques were used to investigate associations between canter, training gallop and race distances accumulated in the 30 days prior to each race and the odds of winning the race, earning prize money and the amount of prize money won.

The Centers for Disease Control and Prevention CDCC) received de-identified study data in aggregate, so multivariable regression techniques to adjust for co-factors beyond HIV prevalence at laboratories, which were related to pregnancy and false-positive HIV EIA test results, could not be performed.

This capability gives neural networks, at least potentially, an advantage over traditional statistical multivariable regression techniques [ 12].

We used multivariable regression techniques to adjust for these differences in relevant preoperative characteristics between the two care groups.

However, when the outcome of mortality is studied using advanced multivariable regression techniques to control for multiple known confounders, an improved odds of survival has been repeatedly demonstrated.

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Similar(52)

Imputation was performed by chained equations utilising switching regression, an iterative multivariable regression technique [ 16].

Missing data were imputed using an iterative multivariable regression technique in Stata[ 29].

Effects were estimated using Bayesian path analysis, a multivariable regression technique, and expressed using standardized regression coefficients.

Missing data on confounders were imputed using switching regression, an iterative multivariable regression technique which retains an element of random variation in the estimates.

To impute missing data we used switching regression, an iterative multivariable regression technique which retains an element of random variation in the estimates.

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