Dear friends,
can explain me how can create one variable from factor scores. I know that Spss have posibilities but I don`t understand. I read this expresion: variables x was create like factor scores from variables a, variables b, variables c ... thanks, Dan |
You can simply use the SAVE subcommand in the FACTOR command, and this will
create one new variable for the factor scores of each extracted factor from which you want a variable to be created. SPSS will assign them a standard rootname by default unless you specify another standard rootname. If your rootname is FACSCORE, the various factor score variables will be called FACSCORE1, FACSCORE2, FACSCORE3, etc. On the other hand, in the FACTOR command output there is a factor score coefficient matrix showing the weight of each observed variable (in standardized z-score form) in the calculation of each factor score. This way you can reconstruct each factor score as a linear combination of observed variables. Each factor score is itself a z-score variable, i.e. a variable with zero mean and unit standard deviation. Hector -----Mensaje original----- De: SPSSX(r) Discussion [mailto:[hidden email]] En nombre de danl Enviado el: Wednesday, August 30, 2006 12:06 PM Para: [hidden email] Asunto: variables fro factor scores Dear friends, can explain me how can create one variable from factor scores. I know that Spss have posibilities but I don`t understand. I read this expresion: variables x was create like factor scores from variables a, variables b, variables c ... thanks, Dan -- View this message in context: http://www.nabble.com/variables-fro-factor-scores-tf2190526.html#a6060890 Sent from the SPSSX Discussion forum at Nabble.com. |
In reply to this post by danl
Stephen Brand
www.statisticsdoc.com Dan, Following the procedure that Hector outlined in his reply earlier today, SPSS will allow you to compute and save factor scores using the SAVE subcommand under FACTOR. You have some choices about the exact manner in which the factor score estimates are computed (bear in mind that the scores are estimates, the estimated scores contain error, and there are different ways to estimate). Your options are to estimate scores using Regression (the default), Bartlett, and Anderson-Rubin. A lot can be said about the different methods, but in a nutshell, regression estimates assume that the factor scores are normally distributed, while Bartlett and Anderson Rubin estimates do not. The core idea in regression estimates is to minimize the discrepancy between the predicted and true factor scores. The regression method is the most common and is the default method in SPSS. If you use this estimate method, check to see that the regression weights resemble the factor pattern, so your estimated factors have similar conceptual meaning. Anderson-Rubin is a modification of the Bartlett procedure that seeks to ensure that the estimated factors are orthogonal. A case can also be made for simply computing the sum of all the items that load on a given factor, giving each item unit weight. While this may seem like a very crude way to estimate factor scores, the case can be made that factor weights can be quite sample specific, and so a simple linear combination of items may be more robust than a weighted combination of items. Check on the internal consistency (Cronbach's alpha) of the combination. HTH, Stephen Brand For personalized and professional consultation in statistics and research design, visit www.statisticsdoc.com -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of danl Sent: Wednesday, August 30, 2006 11:06 AM To: [hidden email] Subject: variables fro factor scores Dear friends, can explain me how can create one variable from factor scores. I know that Spss have posibilities but I don`t understand. I read this expresion: variables x was create like factor scores from variables a, variables b, variables c ... thanks, Dan -- View this message in context: http://www.nabble.com/variables-fro-factor-scores-tf2190526.html#a6060890 Sent from the SPSSX Discussion forum at Nabble.com. |
Does SPSS have the ability to create matched groups using propensity scores?
Todd --------------------------------- How low will we go? Check out Yahoo! Messengers low PC-to-Phone call rates. |
Hi Todd..I'm accessing my memory bank here as it has been awhile since I created propensity scores, but there isn't an automatic procedure per se in SPSS to create propensity scores, but I recall using the logistic regression procedure (outcome: tx vs control) and based on the covariates of interest (e.g., age, cortisol, etc.) created/saved predicted probability scores and used that as the propensity score....however, I will defer to those who use those more frequently than I.............
Dale Todd McDonald <[hidden email]> wrote: Does SPSS have the ability to create matched groups using propensity scores? Todd --------------------------------- How low will we go? Check out Yahoo! Messengers low PC-to-Phone call rates. Dale Glaser, Ph.D. Principal--Glaser Consulting Lecturer--SDSU/USD/CSUSM/AIU 3115 4th Avenue San Diego, CA 92103 phone: 619-220-0602 fax: 619-220-0412 email: [hidden email] website: www.glaserconsult.com |
In reply to this post by Todd McDonald
Hi Todd,
I do this all the time and use syntax. See reference below. --Adam Painter, J. (2004). Propensity matching via SPSS. Syntax for the SPSS software package. Available online at: http://www.unc.edu/~painter/SPSSsyntax/propen.txt _____________________________ Adam B. Troy, Ph.D. Director of Research GoalQuest, Inc. ----- Original Message ----- From: Todd McDonald <[hidden email]> Date: Thursday, August 31, 2006 1:12 pm Subject: propensity scoring > Does SPSS have the ability to create matched groups using > propensity scores? > > Todd > > > > > > --------------------------------- > How low will we go? Check out Yahoo! Messengers low PC-to-Phone > call rates. > |
In reply to this post by Todd McDonald
Sometimes stratification, covariate, or weighting make more sense than
matching. * Here we save the propensity score (CDp), modeling assignment to the College Dreams program (CD=1 for tx group and 0 for comparison). LOGISTIC Vars= CD with Male LowInc Minority NonTrad Transfer Absences HighRisk GPA5 AvgAch /Save=PRED(CDp) /Classplot /External . * Here we calculate quintiles (CDq) on the propensity score for use in stratification and evaluating overlap of the group distributions . RANK CDp /NTiles(5) INTO CDq . * Here we compute the inverse probability of treatment weights (IPTW) based on the estimated propensity score . DO IF (CD=1) . + COMPUTE iCDp = 1 / CDp . ELSE . + COMPUTE iCDp = 1 / (1-CDp) . END IF . * Here we apply the weights in an outcome analysis predicting the odds of HS graduation for treated vs untreated students . WEIGHT BY iCDp . LOGISTIC Vars= Graduation with CD Male GPA5 HighRisk /Save= Pred(GradP) /Classplot /External . WEIGHT OFF . There is more to good propensity score analysis but the syntax is straightforward - at least when using the PS to define strata, covariate, or weights. Matching is more complicated. Dennis Deck, PhD RMC Research Corporation [hidden email] -----Original Message----- From: Todd McDonald [mailto:[hidden email]] Sent: Thursday, August 31, 2006 10:13 AM Subject: propensity scoring Does SPSS have the ability to create matched groups using propensity scores? Todd --------------------------------- How low will we go? Check out Yahoo! Messenger's low PC-to-Phone call rates. |
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