[R] lm - significance disappears

Stuart Leask stuart.leask at nottingham.ac.uk
Mon Mar 8 09:57:26 CET 2004


Hi there.
I am trying to model the effect of "Age at onset of a condition" (AGEONSET)
upon IQ (ie. do they have more problems if they get ill younger?). I also
want to see if there is an interaction with the TYPE of test (reading &
maths).

I am struggling to understand why the effect of AGEONSET, so very
significant in the non-interaction models, ceases to be so in the
interacting model? Am I using lm() wrongly here?


Stuart

****************************

# Regress IQ on AGEONSET, AGEONSET + TYPE, & AGEONSET*TYPE.

> fit.f<-lm(IQ~AGEONSET)
> summary(fit.f)

Call:
lm(formula = IQ ~ AGEONSET)

Residuals:
     Min       1Q   Median       3Q      Max
-3.07434 -0.78350  0.04031  0.71869  2.82266

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.975267   0.077362 -12.607  < 2e-16 ***
AGEONSET     0.037158   0.006876   5.404 9.57e-08 ***
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 1.109 on 574 degrees of freedom
Multiple R-Squared: 0.04841,    Adjusted R-squared: 0.04675
F-statistic:  29.2 on 1 and 574 DF,  p-value: 9.571e-08


> fit.f<-lm(IQ~AGEONSET+TYPE)
> summary(fit.f)

Call:
lm(formula = IQ ~ AGEONSET + TYPE)

Residuals:
     Min       1Q   Median       3Q      Max
-3.03301 -0.80625  0.03662  0.72066  2.86379

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.852151   0.158755  -5.368 1.16e-07 ***
AGEONSET     0.037147   0.006877   5.401 9.71e-08 ***
TYPE        -0.082107   0.092447  -0.888    0.375
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 1.109 on 573 degrees of freedom
Multiple R-Squared: 0.04972,    Adjusted R-squared: 0.0464
F-statistic: 14.99 on 2 and 573 DF,  p-value: 4.513e-07


> fit.f<-lm(IQ~AGEONSET*TYPE)
> summary(fit.f)

Call:
lm(formula = IQ ~ AGEONSET * TYPE)

Residuals:
     Min       1Q   Median       3Q      Max
-3.04133 -0.80869  0.03557  0.72420  2.86796

Coefficients:
               Estimate Std. Error t value Pr(>|t|)
(Intercept)   -0.833399   0.244866  -3.403 0.000712 ***
AGEONSET       0.035070   0.021758   1.612 0.107555
TYPE          -0.094608   0.154887  -0.611 0.541562
AGEONSET:TYPE  0.001386   0.013767   0.101 0.919868
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 1.11 on 572 degrees of freedom
Multiple R-Squared: 0.04974,    Adjusted R-squared: 0.04475
F-statistic: 9.979 on 3 and 572 DF,  p-value: 2.026e-06




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