I'm sorry, no clue how I did not see that. Thank you!


On 12 February 2013 15:21, Uwe Ligges <ligges@statistik.tu-dortmund.de>wrote:

>
>
> On 12.02.2013 15:15, Torvon wrote:
>
>> The code is quite long because I am running a WLS regression instead of an
>> OLS regression (due to heteroscedasticity). First, I get mean structure,
>> then get mean/SD relationship, then improve the variance structure by
>> using
>> weights proportional to 1/variance.
>>
>> I am quite sure this is not relevant, so I will only post the rest of the
>> code. Let me know if you need that part, too. I appreciate the help Uwe!
>>
>> Best,
>> T.
>>
>>
>> m3 = lm(s8_1234_m~ Sex + HisDep + FamHis + ZNeuro + ZEFE + Zwh_1234_m +
>>    Zale_1234_m+t0s8, weights=W, data=D)
>>
>>
>>  summary(m3)
>>>
>>
>> Call:
>> lm(formula = s8_1234_m ~ Sex + HisDep + FamHis + ZNeuro + ZEFE +
>>      Zwh_1234_m + Zale_1234_m + t0s8, data = D, weights = W)
>>
>> Residuals:
>>      Min      1Q  Median      3Q     Max
>> -1.3691 -0.5453 -0.4104  0.2606  7.0111
>>
>> Coefficients:
>>              Estimate Std. Error t value Pr(>|t|)
>> (Intercept)  0.20961    0.01681  12.472  < 2e-16 ***
>> Sex         -0.02321    0.01708  -1.359  0.17435
>> HisDep       0.02544    0.01987   1.281  0.20052
>> FamHis      -0.02183    0.01798  -1.215  0.22478
>> ZNeuro       0.07939    0.01007   7.882 6.87e-15 ***
>> ZEFE         0.02243    0.01056   2.124  0.03385 *
>> Zwh_1234_m   0.04265    0.00814   5.240 1.88e-07 ***
>> Zale_1234_m  0.02877    0.00975   2.951  0.00323 **
>> t0s8         0.38980    0.06504   5.993 2.67e-09 ***
>> ---
>> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>>
>> Residual standard error: 0.9321 on 1280 degrees of freedom
>> Multiple R-squared: 0.1282, Adjusted R-squared: 0.1228
>> F-statistic: 23.54 on 8 and 1280 DF,  p-value: < 2.2e-16
>>
>>  coef(summary(m1))[,4]
>>>
>>   (Intercept)          Sex       HisDep       FamHis       ZNeuro
>> ZEFE   Zwh_1234_m  Zale_1234_m
>> 3.042584e-23 2.146371e-01 2.769561e-01 9.988154e-01 5.682278e-13
>> 5.243800e-03 2.599513e-07 3.116738e-02
>>          t0s8
>> 1.741608e-17
>>
>
> So you are comparing results from m3 with those from m1????
>
>
> Uwe Ligges
>
>
>
>>
>>
>> On 12 February 2013 15:07, Uwe Ligges <ligges@statistik.tu-dortmund.**de<ligges@statistik.tu-dortmund.de>
>> >wrote:
>>
>>
>>>
>>> On 12.02.2013 14:44, Torvon wrote:
>>>
>>>
>>>>
>>>> Thank you, Uwe.
>>>>
>>>> summary(m1) gives me p-value estimates of:
>>>> (Intercept) 2e-16
>>>> x1 6.9e-15
>>>> x2 1.9e-07
>>>> x3 2.7e-09
>>>>
>>>> While coef(summary(m1))[,4] gives me:
>>>> (Intercept) 3.0e-23
>>>> x1 5.7e-13
>>>> x2 2.6e-07
>>>> x3 1.7e-17
>>>>
>>>> While the first one confirms my suspicion (-23 instead of -16), the
>>>> latter one vary drastically (especially x3 from -09 to -17). Why is
>>>> that?
>>>>
>>>>
>>>
>>> Can you show the complete code and output?
>>>
>>> Uwe Ligges
>>>
>>>   Thank you!
>>>
>>>> T.
>>>>
>>>>
>>>>
>>>>
>>         [[alternative HTML version deleted]]
>>
>>
>>
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>>
>>

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