Troublesome Items on the PSYC 7431 Midterm Exam, Winter/Spring, 2018 %C is the percentage of students who correctly answered the item. D is the difference between %C for the top-scoring students and the bottom-scoring students. PB is 100 x the point-biserial correlation between getting the item correct and score on the remaining items on the exam. What do you get when you sum across predictors the sequential squared semipartial correlation coefficients? The answer is the full model R2. I hope the Venn diagrams below make this clear. %C = 21, D = 60, PB = 45. = .45 With unique sums of squares, Redundancy = ? = .15 The sum of the squared semipartials will be less than the R2 unless is no redundancy. = .45 With sequential sums of squares, entering X1 first, Notice that with sequential statistics, the semipartials sum to equal R2. = .45 With sequential sums of squares, entering X2 first, Again, notice that with sequential statistics, the semipartials sum to equal R2. xx. R2 for Y.1234 = .85, for Y.123 = .80, for Y.124 = .75, for Y.134 = .69, and Y.234 = .83. What is the semipartial correlation coefficient for X2? %C = 21, D = 60, PB = 42. The squared semipartial for Xi is the amount by which R2 drops when Xi is removed from the model. For X2 that is .85 - .69 = .16. The semipartial is the square root of the squared semipartial, that is, .40.
Troublesome Items on the PSYC 7431 Midterm Exam, Winter/Spring, 2018 %C is the percentage of students who correctly answered the item. D is the difference between %C for the top-scoring students and the bottom-scoring students. PB is 100 x the point-biserial correlation between getting the item correct and score on the remaining items on the exam. What do you get when you sum across predictors the sequential squared semipartial correlation coefficients? The answer is the full model R2. I hope the Venn diagrams below make this clear. %C = 21, D = 60, PB = 45. = .45 With unique sums of squares, Redundancy = ? = .15 The sum of the squared semipartials will be less than the R2 unless is no redundancy. = .45 With sequential sums of squares, entering X1 first, Notice that with sequential statistics, the semipartials sum to equal R2. = .45 With sequential sums of squares, entering X2 first, Again, notice that with sequential statistics, the semipartials sum to equal R2. xx. R2 for Y.1234 = .85, for Y.123 = .80, for Y.124 = .75, for Y.134 = .69, and Y.234 = .83. What is the semipartial correlation coefficient for X2? %C = 21, D = 60, PB = 42. The squared semipartial for Xi is the amount by which R2 drops when Xi is removed from the model. For X2 that is .85 - .69 = .16. The semipartial is the square root of the squared semipartial, that is, .40.
Midterm-Remediation_7431_Spring-2018.docx