. egen ntotal = count(dres)<\/code><\/p>\nThere are plenty ways to generate various variables containing sample statistics. As for the centered variable, use<\/p>\n
. gen cdres = dres - dresavg<\/code><\/p>\nor without even generating the variable containing the mean:<\/p>\n
. sum dres
\n. gen cdres = dres - r(mean)<\/code><\/p>\nPASW 18 (SPSS, you know)<\/strong><\/p>\nBeware, long syntax ahead. Before you despair, there’s a simpler (but less flexible) solution below. The complicated approach starts with exporting the variable mean into a new data set. This data set is then merged with the master data set; a variable containing the mean for every observation will be attached.<\/p>\n
* Open the data set containing dres.
\n* Depending on your operating system and your preferences you might have to change the paths.
\n*.
\nGET FILE='D:\\master01.sav'.
\nDATASET NAME master WINDOW=FRONT.
\n*.
\n* OMS will send (specified) output into a new file.
\n* In this case the new file is a SPSS data set named killme.sav.
\n* Set VIEWER = NO to omit the table being shown in the output window.
\n*
\n* The mean of dres is computed via DESCRIPTIVES.
\n* NB: You can adapt the statistics, changing or adding statistics (e.g., SUM);
\n* you might need to adapt some of the following stuff, though
\n* (e.g., add Summe to the Mittelwert in the \/KEEP option when saving).
\n*
\n* OMSEND will stop the sending.
\n*.
\nOMS
\n\/SELECT TABLES
\n\/DESTINATION FORMAT=SAV OUTFILE = 'D:\\killme.sav' VIEWER = YES
\n\/IF COMMANDS = ['descriptives'] subtypes = ['descriptive statistics'].
\nDESCRIPTIVES VARIABLES=dres
\n\/STATISTICS=MEAN.
\nOMSEND.
\n*.
\n* A new data set containing the descriptive statistics has been created.
\n* Time to close the master data set for the time being.
\n*.
\nDATASET CLOSE master.
\n*.
\n* Open the new small data set.
\n*.
\nGET FILE='D:\\killme.sav'.
\nDATASET NAME zwischenhalt WINDOW=FRONT.
\n*.
\n* I suggest you take a look at the data.
\n* The number of interest is in the variable Mittelwert.
\n* NB: I'm using a German version of the software; other version will give it other names.
\n*
\n* There's an additional line with the number of total observations
\n* and if there's missing values maybe even more lines.
\n* Let's get rid of them! NB: This assumes that the mean is, well not a very large negative number.
\n* I know that's an ugly way to do it, but so far I couldn't get a statement like ~=SYSMIS(Mittelwert) working.
\n*.
\nFILTER OFF.
\nUSE ALL.
\nSELECT IF (Mittelwert > -66666666666).
\nEXECUTE.
\n*.
\n* A (constant) key variable is required for the upcoming merging procedure.
\n*.
\nCOMPUTE cons = 1 .
\nEXECUTE .
\n*.
\n* Key variables must be sorted.
\n*.
\nSORT CASES BY cons(A).
\n*.
\n* Save the small data set, keeping only the key variable and the data of interest.
\n* NB: Here N (i.e., the number of observations) is kept as well mirroring the Stata procedures shown above.
\n*.
\nSAVE OUTFILE='D:\\killme.sav'
\n\/KEEP=N Mittelwert cons
\n\/COMPRESSED.
\n*.
\n* SPSS saves the specified data set, but the other variables remain there in the open data set.
\n* Closing and re-opening solves this problem.
\n*.
\nDATASET CLOSE zwischenhalt.
\n*.
\nGET FILE='D:\\killme.sav'.
\nDATASET NAME zwischenhalt WINDOW=FRONT.
\n*.
\n* Open the master data set, as well.
\n*.
\nGET FILE='D:\\master01.sav'.
\nDATASET NAME master WINDOW=FRONT.
\n*.
\n* Add the key variable here, as well; then sort it.
\n*.
\nCOMPUTE cons = 1 .
\nEXECUTE .
\n*.
\nSORT CASES BY cons(A).
\n*.
\n* Now for the big one: the data set currently in front (master, here simply *) is merged with the other data set.
\n* Using the \/TABLES option allows to attach the one line of values to every line (observation) in the master data set.
\n*.
\nMATCH FILES \/FILE=*
\n\/TABLE='zwischenhalt'
\n\/BY cons.
\nEXECUTE.
\n*.
\n* Don't need the small data set anymore.
\n*.
\nDATASET CLOSE zwischenhalt.
\n*.
\n* Out of sight, but still on your computer. I'm afraid you have to manually delete it.
\n* The file name killme suggests what to with it, eventually (a tip I got from Prof. Schnell).
\n*
\n* The variables that were attached have weird German names. Let's make them clearer:
\n*.
\nRENAME VARIABLES (N Mittelwert = ntotal dresavg).
\nEXECUTE.
\n*.
\n* It doesn't hurt to label the new variables - but I assume you'd already thought of this yourself.
\n*
\n* Phew, now there's the variables needed for centering. So let's center!
\n*.
\nCOMPUTE cdres = dres - cdresavg.
\nEXECUTE.
\n*.
\n* There was no immediate need for save commands in the Stata examples.
\n* For the sake of completity (and to drop the no longer needed key variable): save and close.
\n*.
\nSAVE OUTFILE='D:\\master01.sav'
\n\/DROP=cons \/COMPRESSED.
\n*.
\nDATASET CLOSE master.<\/code><\/p>\nSo far, so complex. I promised an easier solution. You can (ab)use the regression command to achieve the same results in terms of mean variables. Just run a regression through the origin with dres as dependent variable and a constant as predictor. The predicted values (which are saved in a new variable specified in the last line of syntax) then correspond to the mean of dres.<\/p>\n
COMPUTE cons = 1 .
\nEXECUTE .
\n*.
\nREGRESSION
\n\/MISSING LISTWISE
\n\/STATISTICS R
\n\/CRITERIA=PIN(.05) POUT(.10)
\n\/ORIGIN
\n\/DEPENDENT dres
\n\/METHOD=ENTER cons
\n\/SAVE PRED(dresavg).
\n*
\n* Let's center!
\n*.
\nCOMPUTE cdres = dres - cdresavg.
\nEXECUTE.<\/code><\/p>\nA final remark to those frightened by the extensive solution with the OMS command: It should be possible to get a variable containing the number of observation by assigning case numbers, sorting, and then using the lag function (repeatedly?), but I haven’t figured out how, yet. And who knows, maybe there’s an obvious simple way I just overlooked all the time. For the time being I’m happy to have a working solution in SPSS. The easiest way is, of course, to use Stata.<\/p>\n
Update<\/strong> (an hour later): Thanks to the helpful comment below I can present another simple solution for SPSS:<\/p>\nCOMPUTE cons = 1 .
\nEXECUTE .
\n*.
\nAGGREGATE
\n \/OUTFILE=* MODE=ADDVARIABLES
\n \/BREAK=cons
\n \/dresavg=MEAN(dres)
\n \/ntotal=N.<\/code><\/p>\n","protected":false},"excerpt":{"rendered":"My current research requires meta-analytic procedures where variables that contain another variable’s mean come in very handy. Centering Variables is also something very reasonable to do when analysing regressions with an interaction term between a continuous variable and a dummy variable. Centering variables sounds like an easy task. It is if you use Stata but […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[349,350,351,131,348,347,346,130,134,353,352],"class_list":["post-908","post","type-post","status-publish","format-standard","hentry","category-data-analysis","tag-average","tag-centered","tag-centering","tag-data-management","tag-mean","tag-pasw","tag-spss","tag-stata","tag-statistics","tag-syntax","tag-variables"],"_links":{"self":[{"href":"https:\/\/www.jutze.com\/index.php?rest_route=\/wp\/v2\/posts\/908","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.jutze.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.jutze.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.jutze.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.jutze.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=908"}],"version-history":[{"count":5,"href":"https:\/\/www.jutze.com\/index.php?rest_route=\/wp\/v2\/posts\/908\/revisions"}],"predecessor-version":[{"id":911,"href":"https:\/\/www.jutze.com\/index.php?rest_route=\/wp\/v2\/posts\/908\/revisions\/911"}],"wp:attachment":[{"href":"https:\/\/www.jutze.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=908"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.jutze.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=908"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.jutze.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=908"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}