data Experiment1; infile '\\Client\C:\Guilty by Association Experiment 1 data.txt' missover; options linesize=68; array resp{156} resp1-resp156; array rt{156} rt1-rt156; input subject 1-3 CBFaces $4 CBDay 5 Sex $6 Sleep $7 Age 8-9 Ethnicity $10 Language $11 Night1 12-13 Rest1 14-15 Night2 16-17 Rest2 18-19 SleepCheck 20 Busy 21 Relax 22 Nap 23 Know $24 TVA $25; ***GroupGender (Counterbalancing) --> A1/A2 all women thus coded as 'A'; ***B1/B2 all men thus coded as 'B'; do i =1 to 156 by 1; input resp {i} 1 rt {i}; if rt{i} < 200 then rt{i} ='200'; if resp{i} > 7 then resp{i} ='7'; if resp{i} < 1 then resp{i} ='.'; end; if know = 'Y' then delete; If Nap = 1 then delete; *removes subs who napped in NS condition; *****Condition Codes*****; ***B1/B2 are all male targets with learned and novel switched***; ***A1/A2 are all female targets with learned and novel targets switched***; *** A group - negative; *** B group - positive; *** TVA: counterbalancing order of DVs; ** T = traits first; ** V = valence first; if TVA = 'T' then order = 1; if TVA = 'V' then order = 0; **Codes for counterbalanced conditions; do; if CBFaces = 'A' and CBDay = 1 then condition = 'A1'; if CBFaces = 'A' and CBDay = 2 then condition = 'A2'; if CBFaces = 'B' and CBDay = 1 then condition = 'B1'; if CBFaces = 'B' and CBDay = 2 then condition = 'B2'; end; **Gender of Learned Targets; if CBFaces = 'A' then targender = 'F'; if CBFaces = 'B' then targender = 'M'; **Ethnicity codes; if ethnicity = 'M' then ethnicity = 'L'; if ethnicity = 'A' then ethnicity = 'L'; if ethnicity = 'Y' then ethnicity = 'A'; *****1-7 LIKERT TYPE SCALE RATING DEPENDENT VARIABLES*****; *1 - Not at all/Negative; *7 - Extremely/Positive; ***Trait Rating Aggregates for Learned Individuated Targets***; TRLearnedIndNegative = mean(resp1, resp7); TRLearnedIndONegative = mean(resp2, resp8); TRLearnedIndOppPos = mean(resp4, resp5, resp10, resp11); *opposite means positive traits learned with the negative targets; *O = other trait of same valence; TRLearnedIndNOrtPos = mean(resp6, resp12); TRLearnedIndNOrtNeg = mean(resp3, resp9); TRLearnedIndPositive = mean(resp15, resp21); TRLearnedIndOPositive = mean(resp13, resp19); TRLearnedIndOppNeg = mean(resp16, resp17, resp22, resp23); TRLearnedIndPOrtNeg = mean(resp18, resp24); TRLearnedIndPOrtPos = mean (resp14, resp20); TRLearned = mean(TRLearnedIndNegative, TRLearnedIndPositive); TRLearnedIndNegative1 = resp1; TRLearnedIndNegative2 = resp7; TRLearnedIndPositive1 = resp15; TRLearnedIndPositive2 = resp21; TRLearnedNonIndNegative1 = resp25; TRLearnedNonIndNegative2 = resp26; TRLearnedNonIndNegative3 = resp31; TRLearnedNonIndNegative4 = resp32; TRLearnedNonIndNegative5 = resp37; TRLearnedNonIndNegative6 = resp38; TRLearnedNonIndNegative7 = resp43; TRLearnedNonIndNegative8 = resp44; TRLearnedNonIndPositive1 = resp50; TRLearnedNonIndPositive2 = resp51; TRLearnedNonIndPositive3 = resp56; TRLearnedNonIndPositive4 = resp57; TRLearnedNonIndPositive5 = resp62; TRLearnedNonIndPositive6 = resp63; TRLearnedNonIndPositive7 = resp68; TRLearnedNonIndPositive8 = resp69; ***These aggregates reflect both target-specific learned traits (cold) and the other learned traits that were the same in respect to valence (cruel)***; TRLearnedSPOPos = mean(TRLearnedIndPositive, TRLearnedIndOPositive); TRLearnedSPONeg = mean(TRLearnedIndNegative, TRLearnedIndONegative); ***These aggregates are for Targets they learned ONLY group info about (non-individuated); TRLearnedNonIndNegative = mean(resp25, resp26, resp31, resp32, resp37, resp38, resp43, resp44); TRLearnedNonIndOppPos = mean(resp28, resp29, resp34, resp35, resp40, resp41, resp46, resp47); TRLearnedNonIndNOrtNeg = mean(resp27, resp33, resp39, resp45); TRLearnedNonIndNOrtPos = mean(resp30, resp36, resp42, resp48); TRLearnedNonIndPositive = mean(resp50, resp51, resp56, resp57, resp62, resp63, resp68, resp69); TRLearnedNonIndOppNeg = mean(resp52, resp53, resp58, resp59, resp64, resp65, resp70, resp71); TRLearnedNonIndPOrtPos = mean(resp49, resp55, resp61, resp67); TRLearnedNonIndPOrtNeg = mean(resp54, resp60, resp66, resp72); TRLearnedNonInd = mean(TRLearnedNonIndNegative, TRLearnedNonIndPositive); TRposnegtargets = mean(TRLearnedNonIndNegative, TRLearnedNonIndPositive,TRLearnedIndNegative,TRLearnedIndPositive); ***Trait Rating Aggregates for Novel Targets Paired With Group Label***; if condition = 'A2' or condition = 'B2' or condition = 'B1' then do; TRNovelNegGroupNeg = mean(resp87, resp88, resp93, resp94, resp99, resp100, resp105, resp106, resp111, resp112, resp116, resp117); TRNovelPosGroupPos = mean(resp126, resp127, resp132, resp133, resp138, resp139, resp143, resp144, resp149, resp150, resp155, resp156); TRNovelNegGroupPos = mean(resp91, resp92, resp97, resp98, resp103, resp104, resp109, resp110, resp114, resp115, resp120, resp121); TRNovelPosGroupNeg = mean(resp122, resp123, resp128, resp129, resp134, resp135, resp140, resp141, resp145, resp146, resp151, resp152); TRNovelNegGroupNeg1 = resp87; TRNovelNegGroupNeg2 = resp88; TRNovelNegGroupNeg3 = resp93; TRNovelNegGroupNeg4 = resp94; TRNovelNegGroupNeg5 = resp99; TRNovelNegGroupNeg6 = resp100; TRNovelNegGroupNeg7 = resp105; TRNovelNegGroupNeg8 = resp106; TRNovelNegGroupNeg9 = resp111; TRNovelNegGroupNeg10 = resp112; TRNovelNegGroupNeg11 = resp116; TRNovelNegGroupNeg12 = resp117; TRNovelPosGroupPos1 = resp126; TRNovelPosGroupPos2 = resp127; TRNovelPosGroupPos3 = resp132; TRNovelPosGroupPos4 = resp133; TRNovelPosGroupPos5 = resp138; TRNovelPosGroupPos6 = resp139; TRNovelPosGroupPos7 = resp143; TRNovelPosGroupPos8 = resp144; TRNovelPosGroupPos9 = resp149; TRNovelPosGroupPos10 = resp150; TRNovelPosGroupPos11 = resp155; TRNovelPosGroupPos12 = resp156; TRNovelNegGroupOrtLAZY = mean(resp85, resp89, resp95, resp101, resp107, resp118); TRNovelNegGroupOrtINTELLIGENT = mean(resp90, resp96, resp102, resp108, resp113, resp119); TRNovelPosGroupOrtLAZY = mean(resp124, resp130, resp136, resp142, resp147, resp153); TRNovelPosGroupOrtINTELLIGENT = mean(resp86, resp125, resp131, resp137, resp148, resp154);end; if condition = 'A1' then do; TRNovelNegGroupNeg = mean(resp85, resp86, resp91, resp92, resp97, resp98, resp103, resp104, resp109, resp110, resp115, resp116); TRNovelPosGroupPos = mean(resp125, resp126, resp131, resp132, resp137, resp138, resp143, resp144, resp149, resp150, resp155, resp156); TRNovelNegGroupPos = mean(resp89,resp90, resp95, resp96, resp101, resp102, resp107, resp108, resp113, resp114, resp119, resp120); TRNovelPosGroupNeg = mean(resp121, resp122, resp127, resp128, resp133, resp134, resp139, resp140, resp145, resp146, resp151, resp152); TRNovelNegGroupNeg1 = resp85; TRNovelNegGroupNeg2 = resp86; TRNovelNegGroupNeg3 = resp91; TRNovelNegGroupNeg4 = resp92; TRNovelNegGroupNeg5 = resp97; TRNovelNegGroupNeg6 = resp98; TRNovelNegGroupNeg7 = resp103; TRNovelNegGroupNeg8 = resp104; TRNovelNegGroupNeg9 = resp109; TRNovelNegGroupNeg10 = resp110; TRNovelNegGroupNeg11 = resp115; TRNovelNegGroupNeg12 = resp116; TRNovelPosGroupPos1 = resp125; TRNovelPosGroupPos2 = resp126; TRNovelPosGroupPos3 = resp131; TRNovelPosGroupPos4 = resp132; TRNovelPosGroupPos5 = resp137; TRNovelPosGroupPos6 = resp138; TRNovelPosGroupPos7 = resp143; TRNovelPosGroupPos8 = resp144; TRNovelPosGroupPos9 = resp149; TRNovelPosGroupPos10 = resp150; TRNovelPosGroupPos11 = resp155; TRNovelPosGroupPos12 = resp156; TRNovelNegGroupOrtLAZY = mean(resp87, resp93, resp99, resp105, resp111, resp117); TRNovelNegGroupOrtINTELLIGENT = mean(resp88, resp94, resp100, resp106, resp112, resp118); TRNovelPosGroupOrtLAZY = mean(resp123, resp129, resp135, resp141, resp147, resp153); TRNovelPosGroupOrtINTELLIGENT = mean(resp124, resp130, resp136, resp142, resp148, resp154);end; **Valence Ratings for Learned Individuated Targets; VALearnedIndNegative = mean(resp73, resp74); VALearnedIndPositive = mean(resp75, resp76); VALearnedIndNegative1 = resp73; VALearnedIndNegative2 = resp74; VALearnedIndPositive1 = resp75; VALearnedIndPositive2 = resp76; **Valence Ratings for Non-Individuated Targets; VALearnedNonIndNegative = mean(resp77, resp78, resp79, resp80); VALearnedNonIndPositive = mean(resp81, resp82, resp83, resp84); VALearnedNonIndNegative1 = resp77; VALearnedNonIndNegative2 = resp78; VALearnedNonIndNegative3 = resp79; VALearnedNonIndNegative4 = resp80; VALearnedNonIndPositive1 = resp81; VALearnedNonIndPositive2 = resp82; VALearnedNonIndPositive3 = resp83; VALearnedNonIndPositive4 = resp84; **RTs for each response; ***RTs for Trait Ratings for Learned Individuated Targets***; TRLearnedIndNegativeRT = mean(rt1, rt7); TRLearnedIndONegativeRT = mean(rt2, rt8); TRLearnedIndOppPosRT = mean(rt4, rt5, rt10, rt11); TRLearnedIndNOrtPosRT = mean(rt6, rt12); TRLearnedIndNOrtNegRT = mean(rt3, rt9); TRLearnedIndPositiveRT = mean(rt15, rt21); TRLearnedIndOPositiveRT = mean(rt13, rt19); TRLearnedIndOppNegRT = mean(rt16, rt17, rt22, rt23); TRLearnedIndPOrtNegRT = mean(rt18, rt24); TRLearnedIndPOrtPosRT = mean (rt14, rt20); TRLearnedRT = mean(TRLearnedIndNegativeRT, TRLearnedIndPositiveRT); ***These aggregates reflect both target-specific learned traits (cold) and the other learned traits that were the same in respect to valence (cruel)***; TRLearnedSPOPosRT = mean(TRLearnedIndPositiveRT, TRLearnedIndOPositiveRT); TRLearnedSPONegRT = mean(TRLearnedIndNegativeRT, TRLearnedIndONegativeRT); ***These aggregates are for Targets they learned ONLY group info about (non-individuated); TRLearnedNonIndNegativeRT = mean(rt25, rt26, rt31, rt32, rt37, rt38, rt43, rt44); TRLearnedNonIndOppPosRT = mean(rt28, rt29, rt34, rt35, rt40, rt41, rt46, rt47); TRLearnedNonIndNOrtNegRT = mean(rt27, rt33, rt39, rt45); TRLearnedNonIndNOrtPosRT = mean(rt30, rt36, rt42, rt48); TRLearnedNonIndPositiveRT = mean(rt50, rt51, rt56, rt57, rt62, rt63, rt68, rt69); TRLearnedNonIndOppNegRT = mean(rt52, rt53, rt58, rt59, rt64, rt65, rt70, rt71); TRLearnedNonIndPOrtPosRT = mean(rt49, rt55, rt61, rt67); TRLearnedNonIndPOrtNegRT = mean(rt54, rt60, rt66, rt72); ***RTs for Trait Rating Aggregates for Novel Targets Paired With Group Label***; if condition = 'A2' or condition = 'B2' or condition = 'B1' then do; TRNovelNegGroupNegRT = mean(rt87, rt88, rt93, rt94, rt99, rt100, rt105, rt106, rt111, rt112, rt116, rt117); TRNovelPosGroupPosRT = mean(rt126, rt127, rt132, rt133, rt138, rt139, rt143, rt144, rt149, rt150, rt155, rt156); TRNovelNegGroupPosRT = mean(rt91, rt92, rt97, rt98, rt103, rt104, rt109, rt110, rt114, rt115, rt120, rt121); TRNovelPosGroupNegRT = mean(rt122, rt123, rt128, rt129, rt134, rt135, rt140, rt141, rt145, rt146, rt151, rt152); TRNovelNegGroupOrtLAZYRT = mean(rt85, rt89, rt95, rt101, rt107, rt118); TRNovelNegGroupOrtINTELLIGENTRT = mean(rt90, rt96, rt102, rt108, rt113, rt119); TRNovelPosGroupOrtLAZYRT = mean(rt124, rt130, rt136, rt142, rt147, rt153); TRNovelPosGroupOrtINTELLIGENTRT = mean(rt86, rt125, rt131, rt137, rt148, rt154);end; if condition = 'A1' then do; TRNovelNegGroupNegRT = mean(rt85, rt86, rt91, rt92, rt97, rt98, rt103, rt104, rt109, rt110, rt115, rt116); TRNovelPosGroupPosRT = mean(rt125, rt126, rt131, rt132, rt137, rt138, rt143, rt144, rt149, rt150, rt155, rt156); TRNovelNegGroupPosRT = mean(rt89,rt90, rt95, rt96, rt101, rt102, rt107, rt108, rt113, rt114, rt119, rt120); TRNovelPosGroupNegRT = mean(rt121, rt122, rt127, rt128, rt133, rt134, rt139, rt140, rt145, rt146, rt151, rt152); TRNovelNegGroupOrtLAZY = mean(rt87, rt93, rt99, rt105, rt111, rt117); TRNovelNegGroupOrtINTELLIGENT = mean(rt88, rt94, rt100, rt106, rt112, rt118); TRNovelPosGroupOrtLAZY = mean(rt123, rt129, rt135, rt141, rt147, rt153); TRNovelPosGroupOrtINTELLIGENT = mean(rt124, rt130, rt136, rt142, rt148, rt154);end; **RTs for Valence Ratings for Learned Individuated Targets; VALearnedIndNegativeRT = mean(rt73, rt74); VALearnedIndPositiveRT = mean(rt75, rt76); **RTs for Valence Ratings for Non-Individuated Targets; VALearnedNonIndNegativeRT = mean(rt77, rt78, rt79, rt80); VALearnedNonIndPositiveRT = mean(rt81, rt82, rt83, rt84); if ethnicity = 'L'; cards; **Trait Ratings; proc glm; class sleep tva targender sex; model TRLearnedNonIndNegative TRLearnedIndNegative TRLearnedNonIndPositive TRLearnedIndPositive = sleep| tva| targender |sex /solution; repeated posneg 2, targettype 2; means sleep ; run; proc glm; class sleep; model TRLearnedNonIndNegative TRLearnedIndNegative TRLearnedNonIndPositive TRLearnedIndPositive = sleep /solution; repeated posneg 2, targettype 2; means sleep ; run; proc sort; by sleep; proc reg; model TRLearnedNonIndNegative = TRLearnedIndNegative /stb ; by sleep; run; proc reg; model TRLearnedNonIndPositive= TRLearnedIndPositive /stb ; by sleep; run; proc glm; class sleep; model TRNovelNegGroupNeg = sleep|TRLearnedIndNegative /solution; means sleep; run; proc glm; class sleep; model TRNovelPosGroupPos = sleep|TRLearnedIndPositive /solution; means sleep; run; **Valence ratings; proc glm; class sleep targender tva sex; model VALearnedNonIndNegative VALearnedIndNegative VALearnedNonIndPositive VALearnedIndPositive = sleep |targender |tva |sex /solution; repeated posneg 2, targettype 2; means sleep; run; proc glm; class sleep; model VALearnedNonIndNegative VALearnedIndNegative VALearnedNonIndPositive VALearnedIndPositive = sleep /solution; repeated posneg 2, targettype 2; means sleep; run; proc glm; class sleep ; model VALearnedNonIndNegative VALearnedIndNegative = sleep /solution; repeated targettype 2; means sleep; lsmeans sleep /tdiff pdiff; run; proc glm; class sleep ; model VALearnedNonIndPositive VALearnedIndPositive = sleep /solution; repeated targettype 2; means sleep; run; proc sort; by sleep; proc reg; model VALearnedNonIndNegative = VALearnedIndNegative /stb ; by sleep; run; proc reg; model VALearnedNonIndPositive = VALearnedIndPositive /stb ; by sleep; run;