synthpop: glm.synds – R documentation

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glm.synds

Fitting (generalized) linear models to synthetic data

Description

Fits generalized linear models or simple linear models to the synthesised data set(s) using glm and lm function respectively.

Usage

glm.synds(formula, family = "binomial", data,  ...)
lm.synds(formula, data, ...)

## S3 method for class 'fit.synds'
print(x, msel = NULL, ...)

Arguments

`formula`	a symbolic description of the model to be estimated. A typical model has the form `response ~ predictors`. See the documentation of `glm` and `formula` for details.
`family`	a description of the error distribution and link function to be used in the model. See the documentation of `glm` and `family` for details.
`data`	an object of class `synds`, which stands for 'synthesised data set'. It is typically created by function `syn` and it includes `data$m` synthesised data set(s).
`...`	additional parameters passed to `glm` or `lm`.
`x`	an object of class `fit.synds`.
`msel`	index or indices of synthetic data copies for which coefficient estimates are to be displayed. If `NULL` (default) the combined (average) coefficient estimates are printed.

Value

The summary function (summary.fit.synds) can be used to obtain the combined results of models fitted to each of the m synthetic data sets.

An object of class fit.synds. It is a list with the following components:

`call`	the original call to `glm.synds` or `lm.synds`.
`mcoefavg`	combined (average) coefficient estimates.
`mvaravg`	combined (average) variance estimates of `mcoef`.
`analyses`	`summary.glm` or `summary.lm` object respectively or a list of `m` such objects.
`fitting.function`	function used to fit the model.
`n`	a number of cases in the original data.
`k`	a number of cases in the synthesised data.
`proper`	a logical value indicating whether synthetic data were generated using proper synthesis.
`m`	the number of synthetic versions of the observed data.
`method`	a vector of synthesising methods applied to each variable in the saved synthesised data.
`incomplete`	a logical value indicating whether any of the variables in the model were not synthesised.
`mcoef`	a matrix of coefficients estimates from all `m` syntheses.
`mvar`	a matrix of variance estimates from all `m` syntheses.

Examples

### Logit model 
ods <- SD2011[1:1000, c("sex", "age", "edu", "marital", "ls", "smoke")]
s1 <- syn(ods, m = 3)
f1 <- glm.synds(smoke ~ sex + age + edu + marital + ls, data = s1, family = "binomial")
f1
print(f1, msel = 1:2)
  
### Linear model
ods <- SD2011[1:1000,c("sex", "age", "income", "marital", "depress")]
ods$income[ods$income == -8] <- NA
s2 <- syn(ods, m = 3)
f2 <- lm.synds(depress ~ sex + age + log(income) + marital, data = s2)
f2
print(f2,1:3)

synthpop

Generating Synthetic Versions of Sensitive Microdata for Statistical Disclosure Control

v1.6-0

GPL-2 | GPL-3

Authors

Beata Nowok [aut, cre], Gillian M Raab [aut], Chris Dibben [ctb], Joshua Snoke [ctb], Caspar van Lissa [ctb]

Initial release

2020-09-03