Sorry, maybe I am just dumb, but I do not see how that makes any
sense. Here is what does not compute with me (not saying its wrong,
just does not make sense)

1. None of the followups include the same people. For example, the
first follow up does not include data from parents.
2. Beyond the first follow-up it seems they added new people to the study
3. The 3rd follow up only includes about 15,000 people or so, while
the base year included about 34,000 (students, teachers, parents, etc)
(a decrease of about 56%). How accurate can the results be when the
last stage includes less than half of the original sample?

This is why I hate statistics, its like Calvin-ball. You make up the
rules as you go along, usually to make the numbers say what you want
them to say.

Lastly, you originally said this study was over 14 years with 50,000
children and took place in Chicago? The link you provided indicates it
was about 25,000 students, over 6 years and does not really indicate
where they were from - except that some were from 'Vermont,
Connecticut, New York and Washington'. Maybe I missed something in
between?


On Wed, Jul 21, 2010 at 11:56 AM, Larry C. Lyons <larrycly...@gmail.com> wrote:
>
> OK Scott last thing.
>
> This is the 4th follow up technical report on the methodology:
> http://nces.ed.gov/pubs95/95426.pdf
>
> On Wed, Jul 21, 2010 at 11:47 AM, Larry C. Lyons <larrycly...@gmail.com> 
> wrote:
>> Also I found some more detail explanation of the followups for the
>> survey which ended in the late 80's. From what I understand the same
>> methodology was used.
>> http://cloud9.norc.uchicago.edu/faqs/nels.htm
>>
>> On Wed, Jul 21, 2010 at 11:40 AM, Larry C. Lyons <larrycly...@gmail.com> 
>> wrote:
>>> Here Scott, this is a very brief explanation of longitudinal research:
>>> http://en.wikipedia.org/wiki/Longitudinal_study
>>>
>>> To get how the researchers did the actual assessments, you'll need to
>>> troll the NORC site's methodology sections for how they handled
>>> attrition etc.
>>>
>>>
>>> On Wed, Jul 21, 2010 at 8:31 AM, Scott Stroz <boyz...@gmail.com> wrote:
>>>>
>>>> Why do you seem to be taking that personally?
>>>>
>>>> I am just curious how following some kids for 1 year and some for 14
>>>> years can yield consistent data. As I said, a lot can happen to people
>>>> in 14 years. In 14 years you can go from 2nd grade to college
>>>> graduate. Or from 6th grade to being a doctor. I understand that it
>>>> would be difficult to follow all the children for the same period of
>>>> time, but it just seems like a pretty wide disparity, especially with
>>>> children. A lot happens in 14 years with children.
>>>>
>>>> Maybe I am just an idiot, but I cannot seem to find anything at the
>>>> link you post even linking to the study you mentioned.
>>>>
>>>> On Wed, Jul 21, 2010 at 8:18 AM, Larry C. Lyons <larrycly...@gmail.com> 
>>>> wrote:
>>>>>
>>>>> Its still legitimate. The longitudinal sampling techniques took such
>>>>> into account. Go to the site and look at how they do that sort of
>>>>> research. I'm pretty satisfied with their methodology, as is the
>>>>> entire field. You need to do your own research about it. I don't see
>>>>> why I ought to provide freebies when I charge a consulting fee for
>>>>> doing such.
>>>>>
>>>>> On Tue, Jul 20, 2010 at 5:04 PM, Scott Stroz <boyz...@gmail.com> wrote:
>>>>>>
>>>>>> 1-14 years? That seems to be a pretty big disparity for some kids
>>>>>> compared to another. A lot of shit (good and bad) can happen to a
>>>>>> person in 14 years. How can those numbers even be remotely accurate?.
>>>>>>
>>>>>> On Tue, Jul 20, 2010 at 4:10 PM, Larry C. Lyons <larrycly...@gmail.com> 
>>>>>> wrote:
>>>>>>>
>>>>>>> No its simply a fact, not an excuse. For instance take the NORC
>>>>>>> dataset (see http://www.norc.org/homepage.htm) - this data is the
>>>>>>> result of a 20 year longitudinal study of all the children in the
>>>>>>> Chicago region school systems, including urban, suburban and rural
>>>>>>> systems. The children were followed throughout their school career. In
>>>>>>> the end over 50,000 children were followed for about 1 to 14 years.
>>>>>>> Not only was school achievement assess, but socioeconomic status,
>>>>>>> parental involvement, etc.
>>>>>>>
>>>>>>> The shared variance (or r squared value) between race and economic
>>>>>>> status was over 40%, meaning that the two factors (race and SES) were
>>>>>>> strongly related. To such an extent that you cannot statistically
>>>>>>> remove the effect of poverty from ethnicity effects nor can you
>>>>>>> eliminate the effects of race on effects due to socio-economic status.
>>>>>>>
>>>>>>> Similar results are found in the census data and in other very large
>>>>>>> datasets. Its not saying that one group is better than the other, its
>>>>>>> saying that this strong relationship exists and has to be taken into
>>>>>>> account in any statistical model you create.
>>>>>>>
>>>>>>> On Tue, Jul 20, 2010 at 3:31 PM, Jerry Barnes <critic...@gmail.com> 
>>>>>>> wrote:
>>>>>>>>
>>>>>>>> "Race and poverty are real close. Real close. Really really close. So 
>>>>>>>> close
>>>>>>>> together that its really really really difficult to remove the effects 
>>>>>>>> of
>>>>>>>> one from the other."
>>>>>>>>
>>>>>>>>
>>>>>>>> One of the most racist ideas I have heard or read.  It's that 
>>>>>>>> sentiment that
>>>>>>>> gives people an excuse for failure.  I can't succeed because my skin 
>>>>>>>> color
>>>>>>>> is [fill in the blank].
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> J
>>>>>>>>
>>>>>>>> -
>>>>>>>>
>>>>>>>> No greater injury can be done to any youth than to let him feel that 
>>>>>>>> because
>>>>>>>> he belongs to this or that race he will be advanced in life regardless 
>>>>>>>> of
>>>>>>>> his own merits or efforts. - Booker T. Washington
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>
>>>>
>
> 

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