R Under development (unstable) (2024-09-30 r87204 ucrt) -- "Unsuffered Consequences"
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> library( "urbin" )
> 
> # Example
> eff6a <- urbinEffInt( allCoef = c( 0.33, 0.22, 0.05, 0.6 ),
+   allXVal = c( 1, NA, 0.16, 0.13 ),
+   xPos = 2, 
+   refBound = c( 8, 12 ), intBound = c( 13, 15 ), model = "logit" )
> eff6a
   effect     stdEr 
0.0386895        NA 
> 
> eff6b <- urbinEffInt( allCoef = c( 0.33, 0.22, 0.05, 0.6 ),
+   allXVal = c( 1, NA, 0.16, 0.13 ),
+   xPos = 2, 
+   refBound = c( 8, 12 ), intBound = c( 13, 15 ), 
+   allCoefVcov = c( 0.003, 0.045, 0.007, 0.009 ), model = "logit" )
> eff6b
    effect      stdEr 
0.03868950 0.01057185 
> 
> # Example
> eff7a <- urbinEffInt( allCoef = c( 0.33, 0.022, 0.005, 0.6 ),
+   allXVal = c( 1, NA, NA, 0.0004 ),
+   xPos = c( 2, 3 ), 
+   refBound = c( 8, 12 ), intBound = c( 13, 15 ), model = "logit" )
> eff7a
   effect     stdEr 
0.0926833        NA 
> 
> eff7b <- urbinEffInt( allCoef = c( 0.33, 0.022, 0.005, 0.6 ),
+   allXVal = c( 1, NA, NA, 0.13 ),
+   xPos = c( 2, 3 ), 
+   refBound = c( 8, 12 ), intBound = c( 13, 15 ), 
+   allCoefVcov = c( 0.003, 0.011, 0.0025, 0.009 ), model = "logit" )
Warning message:
In urbinEffInt(allCoef = c(0.33, 0.022, 0.005, 0.6), allXVal = c(1, NA, NA, 0.13), xPos = c(2, 3), refBound = c(8, 12), intBound = c(13, 15), model = "logit", allCoefVcov = c(0.003, 0.011, 0.0025, 0.009)) :
  the returned standard error is likely largely upward biased and, thus, in most cases meaningless; you can provide the full covariance matrix via argument 'allCoefVcov' to avoid this bias or use argument 'xMeanSd' to substantially reduce this bias 
> eff7b
    effect      stdEr 
0.08853066 0.01757014 
> 
> #Example
> eff8a <- urbinEffInt( allCoef = c( -2.5, 0.3, 0.5, -0.2, 0.03, 0.6 ), 
+   allXVal = c( 1, NA, 0.12 ), 
+   xPos = 2, 
+   refBound = c( 8, 12 ), intBound = c( 13, 15 ),
+   yCat = 2, model = "mlogit" )
> eff8a
    effect      stdEr 
-0.1372913         NA 
> 
> eff8b <- urbinEffInt( allCoef = c( -2.5, 0.3, 0.5, -0.2, 0.03, 0.6 ), 
+   allXVal = c( 1, NA, 0.12 ), 
+   xPos = 2, 
+   refBound = c( 8, 12 ), intBound = c( 13, 15 ),
+   yCat = 2, 
+   allCoefVcov = c( 0.003, 0.045, 0.007, 0.009, 0.0008, 0.9 ),
+   model = "mlogit" )
> eff8b
     effect       stdEr 
-0.13729127  0.01564281 
> 
> #Example
> eff9a <- urbinEffInt( allCoef = c( 0.2, 0.03, 0.005, -0.2, 0.03, 0.006 ), 
+   allXVal = c( 1, NA, NA ), 
+   xPos = c( 2, 3 ), 
+   refBound = c( 1, 12 ), intBound = c( 13, 25 ),
+   yCat = 2, model = "mlogit" )
> eff9a
   effect     stdEr 
0.1584863        NA 
> 
> eff9b <- urbinEffInt( allCoef = c( 0.2, 0.03, 0.005, -0.2, 0.03, 0.006 ), 
+   allXVal = c( 1, NA, NA ), 
+   xPos = c( 2, 3 ), 
+   refBound = c( 1, 12 ), intBound = c( 13, 25 ),
+   yCat = 2, 
+   allCoefVcov = c( 0.03, 0.025, 0.0007, 0.009, 0.008, 0.0009 ),
+   model = "mlogit" )
Warning message:
In urbinEffInt(allCoef = c(0.2, 0.03, 0.005, -0.2, 0.03, 0.006), allXVal = c(1, NA, NA), xPos = c(2, 3), refBound = c(1, 12), intBound = c(13, 25), model = "mlogit", allCoefVcov = c(0.03, 0.025, 7e-04, 0.009, 0.008, 9e-04), yCat = 2) :
  the returned standard error is likely largely upward biased and, thus, in most cases meaningless; you can provide the full covariance matrix via argument 'allCoefVcov' to avoid this bias or use argument 'xMeanSd' to substantially reduce this bias 
> eff9b
   effect     stdEr 
0.1584863 0.1297677 
> 
> proc.time()
   user  system elapsed 
   0.17    0.01    0.17