[R] interpreting an LME regression result...

[Johan Jackson]

Any help would be most appreciated.  (Don't make me get down on my
hands and knees and beg for help, cause I'll do it!!) My boss has me
learning R and doing nested regression with the report due Mon (Friday
night statistics...fun. ). Anyway, here's my problem:

In a regression equation not accounting for the fact that people are
nested in families, the result for Z variable is VERY strong (beta =
-4511), but this result  is much weaker when I use lme and account for
people nested in families (beta = -2613). I'm struggling with a verbal
interpretation of this result. Is it because the effect of Z within
families is not very strong, but between family variation is high?




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If my R syntax would be helpful, it's below:

BIG EFFECT OF Z (using lm)
summary(lm(Y ~ X + Z + age ,data=pharma.data ,na.action='na.omit'))

            Estimate Std. Error t value Pr(>|t|)
(Intercept)   102.27      24.98    4.09    7e-05 ***
X     -629.76     267.87   -2.35    0.020 *
Z    -4511.96    2032.39   -2.22    0.028 *
age             1.88       1.42    1.32    0.188


SMALLER EFFECT OF Z (using lme)
summary(lme(Y ~ X + Z +  age,  random = ~1|Family.ID,
data=pharma.data, method="ML", na.action='na.omit'))

              Value Std.Error DF t-value p-value
(Intercept)   103.9      20.0 85   5.200  0.0000
X.   -417.3     179.3 85  -2.327  0.0223
Z   -2613.0    1845.1 85  -1.416  0.1604
age             1.3       1.2 85   1.126  0.2632