glm.analysis.G: Fits a Generalized Linear Model
In agaye/ESPRESSO.G: Power Analysis and Sample Size Calculation for a model with a main effect genetic covariate
Description
Usage
Arguments
Value
Author(s)
Description
This function fits a conventional unconditional logistic
regression model on the observed outcome and exposure data.
In a Typical ESPRESSO the function is called at each
iteration and the estimates stored.
Usage
1
glm.analysis.G(pheno.model = 0, observed.data = NULL)
Arguments
pheno.model
outcome type: binary=0 and normal=1.
observed.data
a dataframe that contains the
observerd outcome and covariate data.
Value
a vector that holds the beta, standard-error and
z-statistic of each of the covariates.
Author(s)
Gaye A.
agaye/ESPRESSO.G documentation built on May 10, 2019, 7:31 a.m.
R Package Documentation
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Description Usage Arguments Value Author(s)
Description
This function fits a conventional unconditional logistic regression model on the observed outcome and exposure data. In a Typical ESPRESSO the function is called at each iteration and the estimates stored.
Usage
1 | glm.analysis.G(pheno.model = 0, observed.data = NULL)
|
Arguments
pheno.model |
outcome type: binary=0 and normal=1. |
observed.data |
a dataframe that contains the observerd outcome and covariate data. |
Value
a vector that holds the beta, standard-error and z-statistic of each of the covariates.
Author(s)
Gaye A.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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