> -----Original Message----- > From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of Tara > Wernsing > Sent: Thursday, January 04, 2007 8:22 AM > To: SAS-L@LISTSERV.UGA.EDU > Subject: FW: Calculating differences between team members > > one more complexity to this---I need it to produce an individual level > score > for each person (for each ID in my data), not team level score. > So this score will differ for each person on the team. Below is an > excerpt > from an article that used this measure that explains this in words: > > ********************** > Tsui, Egan, Oreilly 1989. Being Different. Administration Science > Quarterly. > > > The relational demography score is the difference between an individual > and > all other individuals in the work unit (i.e., the sample) on a specific > demographic attribute, using a formula similar to that used by O'Reilly, > Caldwell, and Barnett (1989) and by Tsui and O'Reilly (1989). It is the > square root of the summed squared differences between an individual S,'s > value on a specific demographic variable and the value on the same > variable > for every other individual Si in the sample for the work unit, divided by > the total number of respondents in the unit (n). The following formula was > used for this calculation: > > SQRT of (1/n)*[SUM (Si - Sj)**2] > > i=target individual member > J=each other team members > > A relational measure was derived for each demographic variable. > Differences > in age, company tenure, and education were measured in years. Differences > in > gender and race were measured by a score ranging from zero to approaching > but never reaching 1.00. For example, a man in a work unit of two men and > three women would have a relational score of .77 on gender, 0 for being > the > same as the other man and 3 for being different from each of the three > women. We would then divide the score of 3 by 5 and take the square root > of > the result. Each of the two women, in turn, would have a relational score > of > .63. A score of .999 could be obtained by someone who is the sole minority > member (on either gender or race) in an extremely large group .4 > > The relational score on race was computed by considering the differences > among all the racial groups in the work unit. In a work unit with one > African-American, one Asian, and two whites, the relational score for the > African-American and the Asian, respectively, would be 3 (1 for being > different from each other and 2 for being different from each of the two > whites), 2 for each of the two whites (1 for being different from the > African-American, 1 for being different from the Asian, and 0 for being > different from each other). > > All the relational measures were scaled in such a way that a large value > always connotes a large difference. The individual with a large score on a > relational measure differs more, in terms of that-specific demographic > attribute, from other individuals in the work unit (i.e., the sample) than > another individual with a small score. The actual scores observed on the > relational age and tenure measures ranged from zero to 30 and on the > relational education measure ranged from zero to 15. The actual scores > ranged from zero to .99 for both the relational gender and race measures. > > > -----Original Message----- > From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of toby > dunn > Sent: Thursday, January 04, 2007 9:04 AM > To: SAS-L@LISTSERV.UGA.EDU > Subject: Re: Calculating differences between team members > > Data Have ; > Infile Cards ; > Input ID Team Member Attitude ; > Cards ; > 1 1 1 4 > 2 1 2 5 > 3 1 3 5 > 4 2 1 3 > 5 2 2 4 > 6 2 3 2 > ; > Run ; > > Data Need ( Drop = Lastatt ) ; > Set Have ; > By Team ; > Retain Sum ; > > LastAtt = Lag( Attitude ) ; > > If Not First.Team Then Do ; > Sum = Sum + ( Attitude - LastAtt )**2 ; End ; > > If Last.Team Then Do ; > Output ; > Sum = 0 ; > End ; > > Run ; > > > Proc Print > Data = Need ; > Run ; > > > > Toby Dunn > > To sensible men, every day is a day of reckoning. ~John W. Gardner > > The important thing is this: To be able at any moment to sacrifice that > which we are for what we could become. ~Charles DuBois > > Don't get your knickers in a knot. Nothing is solved and it just makes you > walk funny. ~Kathryn Carpenter > > > > > > > From: Tara Wernsing <twernsing@YAHOO.COM> > Reply-To: Tara Wernsing <twernsing@YAHOO.COM> > To: SAS-L@LISTSERV.UGA.EDU > Subject: Re: Calculating differences between team members > Date: Thu, 4 Jan 2007 08:50:21 -0600 > > Yes, of couse. Here is sample layout: > > ID team member attitude > 1 1 1 4 > 2 1 2 5 > 3 1 3 5 > 4 2 1 3 > 5 2 2 4 > 6 2 3 2 > > > -----Original Message----- > From: Jack Clark [mailto:JClark@chpdm.umbc.edu] > Sent: Thursday, January 04, 2007 8:44 AM > To: 'Tara Wernsing'; SAS-L@LISTSERV.UGA.EDU > Subject: RE: Calculating differences between team members > > Tara, > > Could you provide some sample data to the list? > > The suggested solutions will vary depending on the layout of your data. > For > example, does a single observation represent the team or an individual > person? > > > Jack Clark > Research Analyst > Center for Health Program Development and Management University of > Maryland, > Baltimore County > > > > -----Original Message----- > From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of Tara > Wernsing > Sent: Thursday, January 04, 2007 9:09 AM > To: SAS-L@LISTSERV.UGA.EDU > Subject: Calculating differences between team members > > Hi all~ > I am trying to calculate a formula where I need the sum of the squared > differences between 3 people on a team (I have 24 teams of 3 people) for > the > same variable. > > so for example, for attitude toward a team project, I need to calculate > the > value of one team member's attitude score subtracted from the second > member, > and then subtracted from the third member. > then square each difference, and sum up all three sq differences. > > I can figure out the latter part, but having trouble figuring out how I > can > hold the first person's value in memory, while getting the second person's > value (could use _point ?) and doing the subtraction but then also a > needing > the third person's value (can I use another _point--can't seem to figure > out > how in the same do loop)? > > any ideas are appreciated! thanks, Tara > > Tara Wernsing > Doctoral Candidate > University of Nebraska-Lincoln > Gallup Leadership Institute > <http://www.gli.unl.edu/> www.gli.unl.edu > -- > "People take different roads seeking fulfillment and happiness. Just > because > they're not on your road doesn't mean they have gotten lost." ~Cesare di > Bonesana Beccaria >

Tara,

I'm not sure from the description whether the divisor should be 2 or 3 (I chose 3). Does the code below do what you want?

data have; input ID team member attitude; cards; 1 1 1 4 2 1 2 5 3 1 3 5 4 2 1 3 5 2 2 4 6 2 3 2 ;run; data want; do i=1 to 3; set have; array team_a[3] _temporary_; team_a[i]=attitude; end; do i=1 to 3; score = ((team_a[i]-team_a[1])**2 + (team_a[i]-team_a[2])**2 + (team_a[i]-team_a[3])**2) / 3; member = i; attitude=team_a[i]; output; end; run; proc print; run;

Hope this is helpful,

Dan

Daniel J. Nordlund Research and Data Analysis Washington State Department of Social and Health Services Olympia, WA 98504-5204