Running examples in 'synthpop-Ex.R' failed
The error most likely occurred in:

> ### Name: summary.fit.synds
> ### Title: Inference from synthetic data
> ### Aliases: summary.fit.synds print.summary.fit.synds
> 
> ### ** Examples
> 
> ods <- SD2011[1:1000,c("sex","age","edu","ls","smoke")]
>   
> ### simple synthesis
> s1 <- syn(ods, m = 5)
Synthesis number 1
--------------------
 sex age edu ls smoke
Synthesis number 2
--------------------
 sex age edu ls smoke
Synthesis number 3
--------------------
 sex age edu ls smoke
Synthesis number 4
--------------------
 sex age edu ls smoke
Synthesis number 5
--------------------
 sex age edu ls smoke
> f1 <- glm.synds(smoke ~ sex + age + edu + ls, data = s1, family = "binomial")
> summary(f1)
Warning: Note that all these results depend on the synthesis model being correct.

Fit to synthetic data set with 5 syntheses.
Inference to coefficients and standard errors that
would be obtained from the observed data.

Call:
glm.synds(formula = smoke ~ sex + age + edu + ls, family = "binomial", 
    data = s1)

Combined estimates:
                            xpct(Beta) xpct(se.Beta) xpct(z) Pr(>|xpct(z)|)  
(Intercept)                  0.9288522     0.5425090  1.7121        0.08687 .
sexFEMALE                    0.2189769     0.1549944  1.4128        0.15771  
age                          0.0087368     0.0045055  1.9392        0.05248 .
eduVOCATIONAL/GRAMMAR       -0.5028417     0.2441901 -2.0592        0.03947 *
eduSECONDARY                 0.2555937     0.2633673  0.9705        0.33181  
eduPOST-SECONDARY OR HIGHER  0.2443995     0.2922933  0.8361        0.40307  
lsPLEASED                    0.0078953     0.4454170  0.0177        0.98586  
lsMOSTLY SATISFIED          -0.3428399     0.4479459 -0.7654        0.44406  
lsMIXED                     -0.3679618     0.4696456 -0.7835        0.43334  
lsMOSTLY DISSATISFIED       -1.0772409     0.5151428 -2.0912        0.03651 *
lsUNHAPPY                   -0.7457760     0.9339376 -0.7985        0.42456  
lsTERRIBLE                  -1.4925502     1.0037574 -1.4870        0.13702  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> summary(f1, population.inference = TRUE)
Warning: Note that all these results depend on the synthesis model being correct.

Fit to synthetic data set with 5 syntheses.
Inference to population coefficients.

Call:
glm.synds(formula = smoke ~ sex + age + edu + ls, family = "binomial", 
    data = s1)

Combined estimates:
                              Beta.syn se.Beta.syn   z.syn Pr(>|z.syn|)  
(Intercept)                  0.9288522   0.5942888  1.5630      0.11806  
sexFEMALE                    0.2189769   0.1697879  1.2897      0.19715  
age                          0.0087368   0.0049355  1.7702      0.07669 .
eduVOCATIONAL/GRAMMAR       -0.5028417   0.2674969 -1.8798      0.06013 .
eduSECONDARY                 0.2555937   0.2885044  0.8859      0.37566  
eduPOST-SECONDARY OR HIGHER  0.2443995   0.3201913  0.7633      0.44529  
lsPLEASED                    0.0078953   0.4879298  0.0162      0.98709  
lsMOSTLY SATISFIED          -0.3428399   0.4907001 -0.6987      0.48476  
lsMIXED                     -0.3679618   0.5144709 -0.7152      0.47447  
lsMOSTLY DISSATISFIED       -1.0772409   0.5643107 -1.9090      0.05627 .
lsUNHAPPY                   -0.7457760   1.0230774 -0.7290      0.46603  
lsTERRIBLE                  -1.4925502   1.0995612 -1.3574      0.17465  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>   
> ### proper synthesis
> s2 <- syn(ods, m = 5, method = "parametric", proper = TRUE)
Error in `[<-.data.frame`(`*tmp*`, is.na(data[, j]), (ncol(predictor.matrix) -  : 
  replacement has 1 row, data has 0
Calls: syn -> padModel.syn -> [<- -> [<-.data.frame
Execution halted