Compute power for Multiple Regression with up to Five Predictors Example code below for three predictors. Expand as needed for four or five
MRC(ry1 = NULL, ry2 = NULL, ry3 = NULL, ry4 = NULL, ry5 = NULL, r12 = NULL, r13 = NULL, r14 = NULL, r15 = NULL, r23 = NULL, r24 = NULL, r25 = NULL, r34 = NULL, r35 = NULL, r45 = NULL, n = NULL, alpha = 0.05)
Correlation between DV (y) and first predictor (1)
Correlation between DV (y) and second predictor (2)
Correlation between DV (y) and third predictor (3)
Correlation between DV (y) and fourth predictor (4)
Correlation between DV (y) and fifth predictor (5)
Correlation between first (1) and second predictor (2)
Correlation between first (1) and third predictor (3)
Correlation between first (1) and fourth predictor (4)
Correlation between first (1) and fifth predictor (5)
Correlation between second (2) and third predictor (3)
Correlation between second (2) and fourth predictor (4)
Correlation between second (2) and fifth predictor (5)
Correlation between third (3) and fourth predictor (4)
Correlation between third (3) and fifth predictor (5)
Correlation between fourth (4) and fifth predictor (5)
Sample size
Type I error (default is .05)
Power for Multiple Regression with Two to Five Predictors
# NOT RUN { MRC(ry1=.40,ry2=.40, r12=-.15,n=30) MRC(ry1=.40,ry2=.40,ry3=-.40, r12=-.15, r13=-.60,r23=.25,n=24) # }
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