Example 0: Rating scale data: The Liking for Science data |
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Rather than attempting to construct a control file from scratch, it is usually easier to find one of these examples that is similar to your analysis, and modify it.
Control and data file, Example0.txt, for the Liking for Science data (see RSA) contains the responses of 75 children to 25 rating-scale items. The responses are 0-dislike, 1-neutral, 2-like. To analyze these data, start WINSTEPS, then:
Control file name?:
"Files" pull-down menu
"Control file name"
"Examples" folder
Example0.txt
Open
Report output file: (Enter) |
press Enter for a temporary file. |
Extra specifications:(Enter) |
press Enter because there are no extra specifications |
; This is file "example0.txt" - ";" starts a comment
TITLE= 'LIKING FOR SCIENCE (Wright & Masters p.18)'
NI= 25 ; 25 items
ITEM1= 1 ; responses start in column 1 of the data
NAME1= 30 ; person-label starts in column 30 of the data
ITEM= ACT ; items are called "activities"
PERSON= KID ; persons are called "kids"
CODES= 012 ; valid response codes (ratings) are 0, 1, 2
CLFILE= * ; label the response categories
0 Dislike ; names of the response categories
1 Neutral
2 Like
* ; "*" means the end of a list
&END ; this ends the control specifications
; These are brief descriptions of the 25 items
WATCH BIRDS
READ BOOKS ON ANIMALS
READ BOOKS ON PLANTS
WATCH GRASS CHANGE
FIND BOTTLES AND CANS
LOOK UP STRANGE ANIMAL OR PLANT
WATCH ANIMAL MOVE
LOOK IN SIDEWALK CRACKS
LEARN WEED NAMES
LISTEN TO BIRD SING
FIND WHERE ANIMAL LIVES
GO TO MUSEUM
GROW GARDEN
LOOK AT PICTURES OF PLANTS
READ ANIMAL STORIES
MAKE A MAP
WATCH WHAT ANIMALS EAT
GO ON PICNIC
GO TO ZOO
WATCH BUGS
WATCH BIRD MAKE NEST
FIND OUT WHAT ANIMALS EAT
WATCH A RAT
FIND OUT WHAT FLOWERS LIVE ON
TALK W/FRIENDS ABOUT PLANTS
END NAMES ;this follows the item names: - the data follow:
1211102012222021122021020 ROSSNER, MARC DANIEL
2222222222222222222222222 ROSSNER, LAWRENCE F.
2211011012222122122121111 ROSSNER, TOBY G.
1010010122122111122021111 ROSSNER, MICHAEL T.
1010101001111001122111110 ROSSNER, REBECCA A.
1011211011121010122101210 ROSSNER, TR CAT
2220022202222222222222222 WRIGHT, BENJAMIN
2210021022222020122022022 LAMBERT, MD., ROSS W.
0110100112122001121120211 SCHULZ, MATTHEW
2100010122221121122011021 HSIEH, DANIEL SEB
2220011102222220222022022 HSIEH, PAUL FRED
0100220101210011021000101 LIEBERMAN, DANIEL
1211000102121121122111000 LIEBERMAN, BENJAMIN
2110020212022100022000120 HWA, NANCY MARIE
1111111111111111112211111 DYSON, STEPHIE NINA
2221121122222222222122022 BUFF, MARGE BABY
2222022222222222222222122 SCHATTNER, GAIL
2222021022222221222122022 ERNST, RICHARD MAX
2221011002222211122020022 FONTANILLA, HAMES
1100010002122212122020022 ANGUIANO, ROB
1111011112122111122021011 EISEN, NORM L.
1211111112222121122121121 HOGAN, KATHLEEN
2211112112222121222122122 VROOM, JEFF
1221012102222110122021022 TOZER, AMY ELIZABETH
2221120222222221222122022 SEILER, KAREN
1111111111111111111111111 NEIMAN, RAYMOND
1110011101122111022120221 DENNY, DON
2211102002122121022012011 ALLEN, PETER
1000101001110000022110200 LANDMAN, ALAN
1000000002122000022012100 NORDGREN, JAN SWEDE
2211011112221011122121111 SABILE, JACK
1210010011222110121022021 ROSSNER, JACK
2212021212222220222022021 ROSSNER, BESS
2222122222222222222222122 PASTER, RUTH
1110211011122111122011111 RINZLER, JAMES
1110201001122111122011111 AMIRAULT, ZIPPY
1210010012122111122012021 AIREHEAD, JOHN
2211021112222121122222121 MOOSE, BULLWINKLE
2221022112222122222122022 SQURREL, ROCKY J.
2221011022222221222122022 BADENOV, BORIS
2222222222222222222222122 FATALE, NATASHA
2121011112122221122011021 LEADER, FEARLESS
2220112022222121222022021 MAN, SPIDER
1210021012212211022011021 CIANCI, BUDDY
2221022222222222222222022 MCLOUGHLIN, BILLY
2200020002222000222122010 MULLER, JEFF
1110220112212111022010000 VAN DAM, ANDY
2221022222222221222122022 CHAZELLE, BERNIE
1100110101110112111111210 BAUDET, GERARD
2222121222222222222122122 DOEPPNER, TOM
1210021022222221122021022 REISS, STEVE
1111111111111111122111111 STULTZ, NEWELL
0100101010110011021010000 SABOL, ANDREW
1111021121122112122021011 BABBOO, BABOO
1010010011122112222111110 DRISKEL, MICHAEL
2221012012222222222122022 EASTWOOD, CLINT
2220022022222222222022022 CLAPP, CHARLIE
1221010122222221222021021 CLAPP, DOCENT
2221021122222221222022222 CLAPP, LB
1221111122222121122121021 SQUILLY, MICHAEL
2111010022122111122011022 SQUILLY, BAY OF
2220000022222220222020000 BEISER, ED
1211010122222122222122010 BECKER, SELWIN
2210022112222121222122011 CORLEONE, VITO
1211211002222012122121200 CORLEONE, MICHAEL
1201010012222120222022021 PINHEAD, ZIPPY
1211001001212121222121012 MALAPROP, MRS.
1200010102120120022001010 BOND, JAMES
1210010122222122222021021 BLOFELD, VILLAIN
2222022012222122222022021 KENT, CLARK
2201222001220022220222201 STOLLER, DAVE
1001000100011010021200201 JACKSON, SOLOMON
2012010122210201102202022 SANDBERG, RYNE
2220022002222222222022012 PATRIARCA, RAY
1200110112122221022020010 PAULING, LINUS
When analysis completes, use the "Output Tables"pull-down menu to examine the measures and quality-control fit statistics. Start with Table 1, which gives you a quick summary. Here are the Science Activity items in measure order, Table 13. The hierachy of item labels, in the right-hand column, defines the construct that has been measured. "Go on picnic" is easiest to like. "Find bottles" is hardest to like.
ACT STATISTICS: MEASURE ORDER
+-------------------------------------------------------------------------------------------------+
|ENTRY RAW MODEL| INFIT | OUTFIT |PTMEA| |
|NUMBER SCORE COUNT MEASURE S.E. |MNSQ ZSTD|MNSQ ZSTD|CORR.| ACT |
|------------------------------------+----------+----------+-----+--------------------------------|
| 5 35 74 2.42 .22|2.30 5.6|3.62 7.3| .05| FIND BOTTLES AND CANS |
| 23 40 74 2.18 .21|2.41 6.3|4.11 9.0| .00| WATCH A RAT |
| 20 48 74 1.83 .20|1.33 2.0|1.82 3.7| .42| WATCH BUGS |
| 4 50 74 1.75 .20| .89 -.7| .91 -.4| .60| WATCH GRASS CHANGE |
| 8 52 74 1.67 .20|1.10 .7|1.21 1.2| .51| LOOK IN SIDEWALK CRACKS |
| 7 67 74 1.10 .19| .97 -.1|1.01 .1| .59| WATCH ANIMAL MOVE |
| 9 78 74 .71 .19|1.18 1.3|1.17 1.0| .53| LEARN WEED NAMES |
| 16 81 74 .60 .19| .97 -.2| .95 -.3| .51| MAKE A MAP |
| 25 83 74 .53 .19| .80 -1.5| .74 -1.6| .66| TALK W/FRIENDS ABOUT PLANTS |
| 3 86 74 .42 .19| .57 -3.5| .54 -3.0| .72| READ BOOKS ON PLANTS |
| 14 86 74 .42 .19| .82 -1.3| .75 -1.4| .62| LOOK AT PICTURES OF PLANTS |
| 6 89 74 .31 .19| .81 -1.4| .76 -1.4| .61| LOOK UP STRANGE ANIMAL OR PLANT|
| 17 93 74 .16 .19| .65 -2.7| .59 -2.4| .70| WATCH WHAT ANIMALS EAT |
| 22 95 74 .08 .19| .83 -1.2| .74 -1.4| .63| FIND OUT WHAT ANIMALS EAT |
| 24 105 74 -.31 .20| .90 -.6| .79 -.9| .60| FIND OUT WHAT FLOWERS LIVE ON |
| 1 107 74 -.40 .21| .55 -3.5| .49 -2.5| .64| WATCH BIRDS |
| 15 109 74 -.48 .21| .78 -1.5| .64 -1.6| .61| READ ANIMAL STORIES |
| 2 114 74 -.71 .22| .93 -.4| .72 -1.0| .58| READ BOOKS ON ANIMALS |
| 21 117 74 -.85 .22| .84 -.9| .65 -1.3| .58| WATCH BIRD MAKE NEST |
| 11 119 74 -.96 .23| .63 -2.4| .49 -1.9| .59| FIND WHERE ANIMAL LIVES |
| 13 125 74 -1.29 .25|1.22 1.1| .94 .0| .47| GROW GARDEN |
| 10 128 74 -1.49 .26| .78 -1.1| .57 -1.1| .50| LISTEN TO BIRD SING |
| 12 135 74 -2.04 .31| .70 -1.2| .51 -1.0| .45| GO TO MUSEUM |
| 19 139 74 -2.48 .36|1.08 .4|1.10 .4| .30| GO TO ZOO |
| 18 143 74 -3.15 .47|1.50 1.2|1.23 .5| .14| GO ON PICNIC |
|------------------------------------+----------+----------+-----+--------------------------------|
| MEAN 93.0 74.0 .00 .23|1.02 -.2|1.08 .0| | |
| S.D. 30.9 .0 1.41 .06| .45 2.3| .87 2.8| | |
+-------------------------------------------------------------------------------------------------+