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st: RE: RE: RE: how to construct a mean squared Euclidean measure?
From
Nick Cox <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: RE: RE: RE: how to construct a mean squared Euclidean measure?
Date
Thu, 17 Feb 2011 11:15:27 +0000
I don't know. My guess is that you may need to write your own Mata-based program.
Nick
[email protected]
[email protected]
thanks for your reply, Nick!
upon your suggestion, I tried various cluster options, but the variable is being constructed for the dissimilarity with respect to all other observations. I need to find an option to do it sorted by year and firm, but cluster doesn't allow a "by" option. Till now, I couldn't find a way to do it. Do you think its possible in cluster analysis?
Nick Cox
Not so; that is a root mean square distance. Did you check out the clustering stuff in [MV]?
[email protected]
I am using Stata 10.1. I want to create a variable which captures the dissimilarity measure of a member who exit from a work group, sorted by firm and year. The dissimilarity is calculated in terms of the member’s job tenure in the group with respect to other members’ job tenures. More precisely the measure I am trying to construct is the mean squared Euclidean distance of a focal member i from each incumbent team member j and is given as: √( ?(Xi ? Xj)2/(n-1)), where Xi is the tenure of the focal individual i, Xj is the tenure of incumbent j, with i not equal to j and n is the number of group members. Does anyone have an idea how to construct this measure using Stata? For more clarity, let me describe the data structure as below.
Observation ID
Year
Firm ID
Member ID
Tenure
1
1960
1
1
4
2
1960
1
2
2
3
1960
1
3
1
4
1960
2
4
2
5
1960
2
5
1
6
1961
1
1
4
7
1961
1
3
2
8
1961
2
2
0
9
1961
2
4
3
10
1961
2
5
2
This is a data structure with two firms over a two year observation period. For example, I want to construct a new variable for the distance measure of “Member ID: 1” in “Firm ID: 1” in the year 1960. In that case, the measure for the new variable for that observation would be:
√( ?(Xi ? Xj)2/(n-1)); where i=1; j=2,3; Xi=4; X2=2; X3=1.
= √{[(4-2)2+(4-1)2]/(3-1)} = √(13/2)
which gives a measure of that member’s distance from all other members of that firm in 1960. Similarly, I want to construct measures for each of the observations for the variable “Member ID”. If you have some idea how to go forward with this calculation, please help me.
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