summary.fit.synds  R Documentation 
Combines the results of models fitted to each of the m
synthetic data sets.
## S3 method for class 'fit.synds' summary(object, population.inference = FALSE, msel = NULL, real.varcov = NULL, incomplete = NULL, ...) ## S3 method for class 'summary.fit.synds' print(x, ...)
object 
an object of class 
population.inference 
a logical value indicating whether inference
should be made to population quantities. If 
msel 
index or indices of the synthetic datasets ( 
real.varcov 
the estimated variancecovariance matrix of the fit of the
model to the original data. This parameter is used in the function

incomplete 
Logical variable as to whether population inference for
incomplete synthesis is to be used. If this is left at a 
... 
additional parameters. 
x 
an object of class 
The mean of the estimates from each of the m synthetic data sets yields asymptotically unbiased estimates of the coefficients if the observed data conform to the distribution used for synthesis. The standard errors are estimated differently depending whether inference is made for the results that we would expect to obtain from the observed data or for the parameters of the population that we assume the observed data are sampled from. The standard errors also differ according to whether synthetic data were produced using simple or proper synthesis (for details see Raab et al. (2017)).
An object of class summary.fit.synds
which is a list with the
following components:
call 
the original call to 
proper 
a logical value indicating whether synthetic data were generated using proper synthesis. 
population.inference 
a logical value indicating whether inference is made to population coefficients or to the results that would be expected from an analysis of the original data (see above). 
incomplete 
a logical value indicating whether the dependent variable
in the model was not synthesised. It is derived in the synthpop
implementation of the fitting functions ( 
fitting.function 
function used to fit the model. 
m 
the number of synthetic versions of the original (observed) data. 
coefficients 
a matrix with combined estimates. If inference is
required to the results that would be obtained from an analysis of the
original data, ( 
n 
a number of cases in the original data. 
k 
the number of cases in the synthesised data. Note that if 
analyses 

msel 
index or indices of synthetic data copies for which summaries
of fitted models are produced. If 
Nowok, B., Raab, G.M and Dibben, C. (2016). synthpop: Bespoke creation of synthetic data in R. Journal of Statistical Software, 74(11), 126. doi: 10.18637/jss.v074.i11.
Raab, G.M., Nowok, B. and Dibben, C. (2017). Practical data synthesis for large samples. Journal of Privacy and Confidentiality, 7(3), 6797. Available at: https://journalprivacyconfidentiality.org/index.php/jpc/article/view/407
Reiter, J.P. (2003) Inference for partially synthetic, public use microdata sets. Survey Methodology, 29, 181188.
compare.fit.synds
, summary
, print
ods < SD2011[1:1000,c("sex","age","edu","ls","smoke")] ### simple synthesis s1 < syn(ods, m = 5) f1 < glm.synds(smoke ~ sex + age + edu + ls, data = s1, family = "binomial") summary(f1) summary(f1, population.inference = TRUE) ### proper synthesis s2 < syn(ods, m = 5, method = "parametric", proper = TRUE) f2 < glm.synds(smoke ~ sex + age + edu + ls, data = s2, family = "binomial") summary(f2) summary(f2, population.inference = TRUE)
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