Question

Just a quick question on how to handle outputs of different lengths using ldply from the plyr package. Here is a simple version of the code I am using and the error I am getting:

# function to collect the coefficients from the regression models:
> SecreatWeapon <- dlply(merged1,~country.x, function(df) {
+     lm(log(child_mortality) ~ log(IHME_usd_gdppc)+ hiv_prev,data=df)
+ })
> 
# functions to extract the output of interest
> extract.coefs <- function(mod) c(extract.coefs = summary(mod)$coefficients[,1])
> extract.se.coefs <- function(mod) c(extract.se.coefs = summary(mod)$coefficients[,2])
> 
# function to combine the extracted output
> res <- ldply(SecreatWeapon, extract.coefs)
Error in list_to_dataframe(res, attr(.data, "split_labels")) : 
 Results do not have equal lengths

Here the error is due to the fact that some models will contain NA values so that:

> SecreatWeapon[[1]]

Call:
lm(formula = log(child_mortality) ~ log(IHME_usd_gdppc) + hiv_prev, 
    data = df)

Coefficients:
       (Intercept)  log(IHME_usd_gdppc)             hiv_prev  
           -4.6811               0.5195                   NA  

and therefore the following output won’t have the same length; for example:

> summary(SecreatWeapon[[1]])$coefficients
                  Estimate Std. Error   t value     Pr(>|t|)
(Intercept)         -4.6811000  0.6954918 -6.730633 6.494799e-08
log(IHME_usd_gdppc)  0.5194643  0.1224292  4.242977 1.417349e-04

but for the other one I get

> summary(SecreatWeapon[[10]])$coefficients
                   Estimate  Std. Error    t value     Pr(>|t|)
(Intercept)           18.612698   1.7505236  10.632646 1.176347e-12
log(IHME_usd_gdppc)   -2.256465   0.1773498 -12.723244 6.919009e-15
hiv_prev            -272.558951 160.3704493  -1.699558 9.784053e-02

Any easy fixes? Thank you very much,

Antonio Pedro.

Answer 1

The summary.lm( . ) function accessed with $coefficients gives different output than the coef would with an lm argument for any lm-object with an NA “coefficient”. Would you be satisfied with using something like this:

coef.se <- function(mod) {
      extract.coefs <- function(mod) coef(mod) # lengths all the same
      extract.se.coefs <- function(mod) { summary(mod)$coefficients[,2]}
return( merge( extract.coefs(mod), extract.se.coefs(mod), by='row.names', all=TRUE) ) 
             }

With Roland’s example it gives:

> coef.se(fit)
    Row.names          x         y
1 (Intercept) -0.3606557 0.1602034
2          x1  2.2131148 0.1419714
3          x2         NA        NA

You could rename the x as coef and the y as se.coef