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1. Main effect of Sex of Model: 2. Main effect of View of Face: 3. Interaction effect: 4. Which effect explains the most variability in gender identifications (effect size)? 5. Post-Hoc interpretation a. Fill in the information for each of the 3 pairwise comparisons for View of Face: Comparison M difference p-value Sig? YIN 1. Eyes Only vs Full View 2. Eyes Only vs Mouth Only 3. Full View vs Mouth Only b. Interpret the significance of the results of each post hoc comparison (in words only) in terms of the mean accuracy of gender identifications, in a complete and accurate sentence or two. Include the marginal mean and standard error (SE) for each view of face condition upon first mention. 7. Paste the plot from your JASP output and interpret the significant interaction(s) in a couple of sentences:
Within Subjects Effects Cases Sum of Squares Mean Square F Sex of Model 108.025 108.025 45.743 Residuals 443.975 2.362 View of Face 681.053 371.900* 340.526 0.916 Residuals 344.280 Sex of Model * View of Face 162.679 81.340 70.255 Residuals 435.321 376 1.158 Note. Type Ill Sum of Squares *Mauchly's test of sphericity indicates that the assumption of sphericity is violated (p<.05). Between Subjects Effects Cases Sum of Squares df Mean Square F P Residuals 242.095 188 1.288 Note Type Ill Sum of Squares Descriptives Descriptives Mean SD 6.979 1.134 6.392 1214 7.413 0.887 6.931 1.032 4.704 1.577 7.296 0.836 View of Face Sex of Model View of Face Female Eyes Mouth Full Male Eyes Mouth Full Descriptives plots 8.5 8.0 7.5 J 7.0 6.5 6.0 5.5- 5.0 4.5 www. Accuracy of Gender Identificati Femaldale Eyes Mouth! Full df 1 188 2 376 2¹ N 189 159 189 189 189 189 P <.001 <<.001 <<.001" n² 0.050 0.313 0.075
Post Hoc Tests Pholm Post Hoc Comparisons - Sex of Model Mean Difference SE Female Male 0.617 0.091 **p<.001 Note. Results are averaged over the levels of: View of Face 6.763 <.001 Post Hoc Comparisons - View of Face Mean Difference SE Photo 20.220 -5.739 <.001 <.001 Eyes Mouth 1.407 0.070 Full -0.399 0.070 Mouth Full -1.807 0.070 ***p<.001 Nore. P-value adjusted for comparing a family of 3 Note. Results are averaged over the levels of: Sex of Model -25.960 <.001 SE Phim 0.371 5.607 0.128 0.105 0.123 0.105 0.123 -4.142 -2574 Post Hoc Comparisons - Sex of Madel View of Face Mean Difference Female, Eyes Male, Eyes 0.048 Female, Mouth 0.587 Male, Mouth 2.275 Female, Full -0.434 Male, Full -0.312 Male, Eyes Female, Mouth 0.540 Male, Mouth 2228 Female, Full -0.481 Male, Full -0.365 Female. Mouth Male, Mouth 1688 Female, Full -1.022 Male, Full -0.905 Male, Mouth Female Full -2.709 Male Full -2.593 Female Full Male, Full 0.115 Note: P-value adjusted for comparing a family of 15 p<.05. 01. ***p.001 0.123 0.105 0.123 0.105 4375 21 267 -3.903 -3.486 0.730 001 <.001 < 001 0.0311 C.001 <.001 <.001 0.002 <.001 < .001 <.001 <.001 <.001 0.730 0.128 0.105 6.12 13.141 -9.750 -7335 -21.963 -24.750 0.905 0.123 0.105 01128 Marginal Means Marginal Means - Sex of Model 95% CI for Mean Difference Lower Upper SE Sex of Model Marginal Mean 6.928 6310 6.511 Female Male 2012 6.420 0.058 GLOSS 6201
*** Marginal Means - View of Face View of Face Marginal Meani 6.955 6.849 Eyes Mouth Full 5.548 5.431 7.354 7.270 Marginal Means - Sex of Model View of Face Sex of Model View of Face Marginal Mean Eyes 6.979 Female Male 6.931 Female Mouth 6.392 Male 4.704 Full 7.413 Female Male 7.296 95% CI for Mean Difference Lower Upper SE 7.061 0.054 5.664 0.059 7.439 0.043 95% CI for Mean Difference Lower Upper 6.816 7.142 6.783 7.079 6.217 6.566 4.477 4,930 7.285 2.540 7.176 7.416 SE 0.083 0.075 0.088 0.115 0.064 0.061
Both children and adults often report that they base their judgments of sex (male or female) on features such as hair length, posture, clothing, etc. However, these variables may not be sex- specific: for example, hair length can be long or short on a man or a woman, and both men and а women sometimes wear similar types of clothing. This study investigated whether people can reliably categorize individuals as male or female in the absence of information about hair, clothing, posture, etc., specifically, what is the role of facial features in cueing gender classification? Participants were presented with photographs of male and female faces (with their hair and neck covered) presented in three conditions: 1) eyes only - only the eye and brow region were visible, or 2) mouth only - only the mouth and chin regions were visible, and 3) full view - both eyes and mouth showing (see figure below for example photos). Participants were then asked to identify the correct sex of the model in each photograph. Both independent variables (sex and view) are dependent-samples (repeated measures) creating six different within-subjects conditions. Each participant was presented with 8 photographs in each of the 6 conditions making a total of 48 randomly presented trials. The dependent variable is the accuracy in identification of the sex of the 8