-ID SPSS FOR SOCIAL SClENHülS i E i/> -o c o x M O •' E 2 o t/) 5 i V) (Q a C4 O O Fltiuru l.4o I .ilxi'.'inu u vnriable n ItWLH.PflJff! BjQlil H« ü««i*- U*»- ***— Ľ* ■ '.: ' »15) J2l _J M&J *il üJCil SIMS ^ Nvno ''i" »go (Numeric faci)K{ iNumerlc ■"■ Řk "i "'■' t. *eml ffcjmwc ymODOO Hurnenc Wlilili iDn.imaj »bal m i . .i' I.'i |i i:i.1.> ! "m.....i!11 K'ilty Al( «hol ui* V.ili.-. Ml "I Nnio jNom |1, .,., ni t* Non (i.Newil 99 i | | U'.*"-[ >Ap»*i /I..I /■.. ISec»! i i. «* ,! '. • ľ,.I .t. I To insuit additional inlorrnalíon on Ihn víifl.iblo. click on Ihe Label cell, lypo In the details, and press Um Enter or Tab koy Flpuio 1.41 Diilinlng Val V.ih» Lil-I* v*** I Va»*jL*<< |U<« /«*c*H ft* J ■ 1 '-1 "AiU" "■■■ ......' 2 1 5 Ftti.it i—i-i ■■o«.«- - ■ Cimk on fidd lo save ihe labols Click on OK when compla!« I.nim Dm villi in Fol tech i witty ■ ■ i ■ h " i 2-Aih. | *., |(||i | Viihitf I ,i|i,] Entoi 9 = NiitAp|>lli;iilil.. t: cj O ä of III I nportanl to identify tin- lMfjaílt| WnW Cod« fin SPSS (see ihr *r»tiun Mu» un ii k...... rali» -i I Hck on ihe Mlaaing Valuta col ■»! Ihe row i>f the required variable,.....w Ilia curvoi i<» il»- three dots In the ŕadod •.....n of tin col, and dkfc on« A window ItVe Plfliiľ« Lij; will come up. Enlci Ihd vdIubi which arc conaldod missing, click on iln* ok IhiIIimi in ,\.. bock lt> the Variable view window. It iv powlbk lo change any of Iht ehaiadctlrtk» (namif, width, type, label colurni..... Ist.ilr. ordinal or nominal)) in the V .mahle View window by clicking on Ihr -i | prO| ■ I e «II » M I «Me lo copy a fomut frnm 0M vamilJr lo another using Copy and Vartt III I .■ ., I which has been formatted, co|* f ■'" 1 For tins variable -i i mimbor o( drinks "Kond-Iho v.iiiin 99 Is iillociited loi iiiIkhIikj and 98 is nllociilod for not rolovaní (not a drinker). variable yon waul lo copy Ihe formal to. and paste the format ustni; liilil Panic. This is p,irliaiLtfly useful for entering labels from a o,ucstionn.nre will» Ihe tune values and labels lueh as Ukc i ' Onceyouluk.......iiurtlihedaiaanddefirwdttWvarlibli ponlbli r> view Ihe data with the lie» labels IHulrnd ol I In- luiiiinii víiIuľs. To view the Vlllll lutwll Of Ihfi tl.ilascl, go lo Hip d.ii.i Vlow formal in Ihn I '■<<•• Editor« open the pull-down menu view. And click on Vahio i.iiirls. ihr ippcwann "I Ihe grtd will change from ilmi ihowlng the n......rk codes patbi$t itsei/ lo chock for mor» BnTOfll »an be idenlificd by checking for uniilul»« memifúlfítl codes 13 5 SO SPSS FOR SOCIAL SCIENTISTS Figure 1.5b Drinh survoy dnlfl In Libel fcwrurt > n i— J? n Q. B» fl* V*" Dni" Iiwtlam ßnal/» £iflfJit liilini V/niTuw |jtb tf|u|a|q| - ^IM6!«M-iii 1 JV|Q$I^J| ■ ' tlir* -P . M nsnw ■ 1 sex V i-cuHy •tak v** | l^j 1 1 RobMij i > Mva*al[ 2 4Í> Soci* S Ad ; McttH - V»5 j Yes : 2 N.....i i í Fred 1 52 Scivncfl Í]T|\0*iiW.>v4 VlriBöoVtew7, ;'. —ii-r . [SPSS Píoeo.ioi im*J/ ; < A E L/, -o X u o "c o CO en oo a 00 OJ o o Ckttimg for invalid tedr* The most obvious validation ií lo check fof incorrect code* by seeking out impossible or invalid values. All possible come! code value* for a variable M specified. Thca if any codes exiil other than (he possible values, they must bo errors. For Instance, in our i,ic example from lhe Drinking questionnaire', the only possible value* .ire within the range I to 5 and 9. So. il you found a wro or a 6. 7 or 8 (or any other invalid v.iluo). It must be a coding error. These coding crroi« should be corrected before any analysis; Variable: fee. Faculty 0 3 ■ 1 Sooal soe/icin N 2 Arts IM 3 Socncc IJ 4 EngmooiifiQ 131 5 Oíŕier 1 6 < • 9 No! applicable :■< To:.--: I ■ ' ..... '■'» "■ -'-•..i.iii iiviV- Somettine«, a particular code or codes for one variable will moan that the codes for another variable must, or must not, fall within a certain range of values - that is, the codings of the two varlubles, while both are within the range ol possible cod«, may be IncOrutiklÜ with each other. I:r>r instance, you mighl do a consistency check with the 'I )i inking questionnaire' data to see wlii-lltci everyone coded as a I on the variable drink (that I», everyone who said they were a nun drinker) in*> has codings of zero lor the variables beer (units of Iwr/cidcr drank over the weekend), win* (units of wine) and spirit (units of spirit) Non-drinkers should not have drunk any unlti If it appears that a claimed non drinker docs have some units of alcoboJ consumed. .in uwiinmlrncy cxiils which should k rOOOJvod i Inn might NQjIftH r."'11^ hack I" the original source of the information in order to trace the rtaOOtl for the apparent orcoi ) If the DATA INPUT 51 ,,. i i ode can be established, the data grid can be edited to replace Ihe error. If a correct jj , annot be established, it may be necessary to declare the Inconsistent or incorrect code as J IIIWÍII.V <•"'<■<' ■Wřftrtir rf*w*< "" imuilid (oifts \ nu wil note lh.il tracking down the original sources ol invalid coding« or inconsistencies and letting (hem within the datasel can be a tedious and tune consuming operation. iH'thjp» requiring going all Ihe way back to the original source of Ihe data. It is possible to get HiHtixl this by tiling a specialist data entry package which is capable of performing checks for ^ alkl value» and for inconsistencies between variables nt llu pľuil of totting flie ihiht. The data is iihIcJ directly in and the package is continually checking for uut-of-iange and/or inconsistent value» .>* ihey *H! keyed in. If an invalid or inconnUtenl value Is entered. Ihe error is high-lluhWd 00 I ho *pot. This allows Ihe coder lo check the error agalml Ihe original source while Ihil UrtoJoftl lOWCO is in front of them and to repair Ihe damage i nuncii lately. Drilling with missing values hi WpHWlQTl 'missing values' may sound a bit odd to you, but there arc many instances ivhe'c, for only some variables for only some case*, data rnny be missing. Tor instance, our I )ilnkln| OUOltlonnaire' might have a second page where people are diked to lell us about the ill effect» t hoy suffer from drinking (hangovers). People who do not drink would nol need to amwti iImi '.<■< lion [rial :, often a variabli tvlt ml bo codtd fa M ta . nu because tha í W<- rtpf ii/'C'V *° Ihose cases. Another example coulil i v wlľ-ľ1 only people v/ho live .....led accommodation would answer the question about Unto "uuh ml do uoa pay? or where questions about a person's children would not apply lo people who have no children. brfn.....lion can of course be missing for other reasons The information may not be available Minply became it is not fci&vi. A person may nfua lo answer some questions on a questionnaire oi mi mi Interview. Respondents sometimes write lit illegible answers on a questionnaire or make simple mistakes like inadvertently skipping over some i|iientloni or even circling (UW answers when only one is required. Errors may have occurred in the coding or transcription of dala so lhal you know the code is incorrect but you cannot find out the correct code. fbjgatdlaai of cause, all types of missing data are nonnnlly dealt with in Ihe same manner; a special code or codes is applied to each instance of mU'im || fi rnuliOfl, Hor example, wilh fac i« the 'Dunking questionnaire', the code 9 was used to indicate those cases where the information on 'ftHuhu or diwson' was not known or did not apply for some reason. While any codes can be used to signify missing values, there are some rules of good practice with missing values which are advisable. 5r7 N o o OJ Slmfbrly, people often chtoose to use mos a, a „1(„„,v ,„,,,„ MÍfi While better tfuri Wanks this Is Ml» »nt «dvlMble. As* before, an «cideni.lly «nltrtd blank apt« con end up km« rMd ,,., „.,.- Inlroduclnö an error- Also, the va W u,0 cm. oft«, be o genuine code. For «amp]B „ m-onle or« «k«l to «tale b-0" rtuiny *s a deliberate cod» (so it cannot appear by accidcnl a> a tao o, M.inV could). , Sumct.mcs people use m^re than one nrnsmg vah* COtle *o Hut tky ein keep track of why the value is ml»inp, For instance, one might UK different mi»lng value codes hi distinguish bitwecn: 'rifUifti '- •<»W"'- »"J* WW «"W «"*WiW, etc. Whether one chooses lo uSe more Hum on« missing value code depend, upon whether knowing the reason for dala kin« missing is nf importance. {Tor msUmce, it my k Important to know il people refuse lo answer ,t tcilmn question.) The convention many r^eople-follow w.....ni«.mg value» U lo use lhe highest possible V.lllKM ,l..lll'V,l'' . ,, , Pot instance, «»h our cx*>mple of facwhwe 1 to 3 are legiknate cod«, one might ušt-íto mean Tfr/W'; » >o mean * Decs not w*/: and 7 to mean 'Mrwg /.« M«w «rffter mw,,-: Variable: rac, Faculty 1 Social ssrtrncuB 9Q 2 Arts I'- 3 Seiet** ll 4 Engjjnsertwn 1M 5 Oth« 4 7 MsJtlO. Oflr»ř nMSOn 3 8 Doôsmíippfy 1 j Rtimi .'j ■:,!.,! sou If mi variable takes up two columns, uy. 'Nuinki of children', you could maintain this practical of using the highest values to Signify mining valu«« for e*nmple. 97. 9* anJ 99 or 77 »8 and** People iWgM have O. I.2..M... maybe even some with 10, II, 12 I «hildrert but no one would have 77. M. 97. W or» cMdrenl ťor three-digit variables. <-« could use 777, MS. 997. 99Ä or 999; 7777. «0». 9907. 999», 9999 for four-digit variables: and so on lor five digit variables, etc C o CC cd LJ I k« IrnpOrtWI« of specifying missing value codes gOM beyond juM Ik cosmetic r«-.isons of having Ihcm clearly displayed as imsing values in tabulation. When certain co.lcs for a variable air identified for SPSS as müsäg values', time code. wdl k excluded automatically f.om any mathematical calculations thai are carried out on the MnWcfl. If thb w», not the C H completely misleading results would occur for inriancc. taking the example of a uxle for •Number of children' where the missing values codes of 97, 98 .iikI 99 have bee» wed If the DATA INPUT S3 i number ol children was calculated for the dalasrl with even a vinili proportion of niKoInt) * *«• co*'es ^~- 98 "n^ 9^ 'M?in8 •1Vť,"K<-''' I" wlh the true codes of 0. I. 2, 3. etc. the r|((|| awrAKO would he grossly inflated. Once these missing value« have been specified to mnjc,, iioivcw. |,H,y wi" Pl*y no P3tl in liie calculnllon ind ti mliltadlng rssull will be avoided. '. Ml|>(|,ii (Aample of how SPSS would exclude missing values can k seen il we look al the | i i triable fac with the numbers i» i-.uh l.-.-.r.ir^.l<■ category being given as a . tv.eoM he whole Variante: fac. Faculty N I Social sciences 89 116 ? Arts U.I M.3 3 Science 07 ZO.Q 4 Englnooring 131 27.7 5 Olher I 0,1 7 Missing, clhsr reason 3 - r -'-- -.-• s.-'f . i 9 Re/used 23 Too 500 100.0 77 cases are missing values Conclusion In the end. onir • Ik data have been entered • .ibles and their values have been labelled" and defined fully • misalnsj values are specified fully • and the data have been "cleaned" by checking tYu valid ranges ol values and Internal Ľoniujtency you have a fully operational mid self-suppo'inis éůaut, ready for onalysl., 110 lhe SPSS (UlatVl has ken created and dala ha* ken pul Inln II. llw lesulting grid will IihiL hke Figure 1.3a. vhich shows the cases from our 'I I n I. nralnŕ. SfMia up* • ' ■. ,'iřur file frequently as you enter the data. Do not wait until you have enlercd all ol the data - Save your file every 15 minut«*, 'lhal way, you will hlVC a permanent copy of most ol your data even if something goes wrong while yoii'rp working. • Make a lin'iuf» ii>pjr (an extra copy) of Ik data lo use in case your original data file is i how lost or destroyed. Since disks can k damaged, pul Ik backup copy on a ilijfnni} fbflkrt dfafc If Ik dala arc important, k sure lo label the backup floppy diskettes clearly and put them in a safe place • Uw Ik pull-down Help menu on the toolbar and the tulurial (or lurtlirr advice