glm.mids {mice} | R Documentation |
Applies glm()
to a multiply imputed data set
## S3 method for class 'mids' glm(formula, family = gaussian, data, ...)
formula |
a formula expression as for other regression models, of the form
response ~ predictors. See the documentation
of |
family |
The family of the glm model |
data |
An object of type |
... |
Additional parameters passed to |
This function is included for backward compatibility with V1.0. The function is
superseeded by with.mids
.
An objects of class mira
, which stands for 'multiply imputed repeated analysis'.
This object contains data$m
distinct glm.objects
, plus some descriptive information.
Stef van Buuren, Karin Groothuis-Oudshoorn, 2000
Van Buuren, S., Groothuis-Oudshoorn, C.G.M. (2000) Multivariate Imputation by Chained Equations: MICE V1.0 User's manual. Leiden: TNO Quality of Life. http://www.stefvanbuuren.nl/publications/MICE V1.0 Manual TNO00038 2000.pdf
imp <- mice(nhanes) glm.mids((hyp==2)~bmi+chl, data=imp) # fit # $call: # glm.mids(formula = (hyp == 2) ~ bmi + chl, data = imp) # # $call1: # mice(data = nhanes) # # $nmis: # age bmi hyp chl # 0 9 8 10 # # $analyses: # $analyses[[1]]: # Call: # glm(formula = formula, data = data.i) # # Coefficients: # (Intercept) bmi chl # -0.4746337 -0.01565534 0.005417846 # # Degrees of Freedom: 25 Total; 22 Residual # Residual Deviance: 2.323886 # # $analyses[[2]]: # Call: # glm(formula = formula, data = data.i) # # Coefficients: # (Intercept) bmi chl # -0.1184695 -0.02885779 0.006090282 # # Degrees of Freedom: 25 Total; 22 Residual # Residual Deviance: 3.647927 #