* Encoding: UTF-8. * Encoding: . * Encoding: . * Encoding: . * Encoding: . * Encoding: . *CREATING COMPOSITES, SUMMING ACROSS IMAGE ITEMS; 1 = image choice so higher # inidicate higher # of image choices selected* DATASET ACTIVATE DataSet1. COMPUTE message_emoji = SUM(message_1, message_2, message_3). EXECUTE. *COMPUTING RATIO, the summed variable divided by the total. gives percentage of image choices (or abstract choices) selected* COMPUTE message_emoji_ratio = message_emoji / 3. EXECUTE. EXAMINE VARIABLES=message_emoji /PLOT BOXPLOT STEMLEAF /COMPARE GROUPS /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. EXAMINE VARIABLES=message_emoji BY motivation /PLOT BOXPLOT STEMLEAF /COMPARE GROUPS /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. *MAIN EFFECTS* GLM message_emoji message_emoji_ratio BY motivation /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(motivation) /EMMEANS = TABLES(motivation) COMPARE (motivation) /PRINT=DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN=motivation. *scales* DATASET ACTIVATE DataSet1. RELIABILITY /VARIABLES=misunderstanding misinterpreting confidence_r /SCALE('misinterpret') ALL /MODEL=ALPHA. *alpha=.897 DATASET ACTIVATE DataSet1. RELIABILITY /VARIABLES=safe comfortable risky_r /SCALE('risky') ALL /MODEL=ALPHA. *alpha = .9 COMPUTE misinterpret_S = mean(misunderstanding, misinterpreting, confidence_r). COMPUTE comfort_S = mean(safe, comfortable, risky_r). CORRELATIONS /VARIABLES=misinterpret_S comfort_S message_emoji /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE. *MAIN EFFECTS* GLM misinterpret_S comfort_S BY motivation /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(motivation) /EMMEANS = TABLES(motivation) COMPARE (motivation) /PRINT=DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN=motivation. *supplment - item by item* CROSSTABS /TABLES=motivation BY message_1 /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW /COUNT ROUND CELL. CROSSTABS /TABLES=motivation BY message_2 /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW /COUNT ROUND CELL. CROSSTABS /TABLES=motivation BY message_3 /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW /COUNT ROUND CELL. *MAIN EFFECTS without outliers - doesn't change* compute outlier=0. execute. if (message_emoji=3) outlier=1. if(message_emoji>0 & motivation=0) outlier=1. execute. USE ALL. COMPUTE filter_$=(outlier =0). VARIABLE LABELS filter_$ 'outlier =0 (FILTER)'. VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. FORMATS filter_$ (f1.0). FILTER BY filter_$. EXECUTE. GLM message_emoji message_emoji_ratio BY motivation /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(motivation) /EMMEANS = TABLES(motivation) COMPARE (motivation) /PRINT=DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN=motivation. CROSSTABS /TABLES=motivation BY message_emoji /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW /COUNT ROUND CELL. *scales* DATASET ACTIVATE DataSet1. RELIABILITY /VARIABLES=misunderstanding misinterpreting confidence_r /SCALE('misinterpret') ALL /MODEL=ALPHA. *alpha=.897 DATASET ACTIVATE DataSet1. RELIABILITY /VARIABLES=safe comfortable risky_r /SCALE('risky') ALL /MODEL=ALPHA. *alpha = .9 COMPUTE misinterpret_S = mean(misunderstanding, misinterpreting, confidence_r). COMPUTE comfort_S = mean(safe, comfortable, risky_r). CORRELATIONS /VARIABLES=misinterpret_S comfort_S message_emoji /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE. *MAIN EFFECTS* GLM misinterpret_S comfort_S BY motivation /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(motivation) /EMMEANS = TABLES(motivation) COMPARE (motivation) /PRINT=DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN=motivation. *supplment - item by item* CROSSTABS /TABLES=motivation BY message_1 /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW /COUNT ROUND CELL. CROSSTABS /TABLES=motivation BY message_2 /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW /COUNT ROUND CELL. CROSSTABS /TABLES=motivation BY message_3 /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT ROW /COUNT ROUND CELL.