When I do:
> apc <- glm( D ~ ns( Ax, knots=seq(50,80,10), Bo=c(40,90) ) +
+ ns( Cx, knots=seq(1880,1940,20), Bo=c(1840,1960) ) +
+ ns( Px, knots=seq(1960,1980,10), Bo=c(1940,2000) ) +
+ offset( log( Y ) ),
+ family=poisson )
> pterm <- predict( apc, type="terms" )
> plink <- predict( apc, type="link" )
> ( apply( pterm, 1, sum ) + log( Y ) - plink )[1:10]
1 2 3 4 5 6 7 8 9
10
6.85047 6.85047 6.85047 6.85047 6.85047 6.85047 6.85047 6.85047 6.85047
6.85047
> coef( apc )[1]
(Intercept)
-13.61998
>From the help page for predict.glm I would have expected that the
constant 6.85
was -intercept.
What am I missing from predict.glm? (or from splines?)
Bendix Carstensen
----------------------
Bendix Carstensen
Senior Statistician
Steno Diabetes Center
Niels Steensens Vej 2
DK-2820 Gentofte
Denmark
tel: +45 44 43 87 38
mob: +45 30 75 87 38
fax: +45 44 43 07 06
[EMAIL PROTECTED]
www.biostat.ku.dk/~bxc
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