View source: R/Assumptions_resample.R
| Assumptions_resample | R Documentation | 
Compute power for Multiple Regression with Violated assumptions using Resamples
Assumptions_resample( 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, sy = NULL, s1 = NULL, s2 = NULL, s3 = NULL, s4 = NULL, s5 = NULL, ky = NULL, k1 = NULL, k2 = NULL, k3 = NULL, k4 = NULL, k5 = NULL, n = NULL, alpha = 0.05, test = "boot", reps = 200, boots = 500 )
| ry1 | Correlation between DV (y) and first predictor (1) | 
| ry2 | Correlation between DV (y) and second predictor (2) | 
| ry3 | Correlation between DV (y) and third predictor (3) | 
| ry4 | Correlation between DV (y) and fourth predictor (4) | 
| ry5 | Correlation between DV (y) and fifth predictor (5) | 
| r12 | Correlation between first (1) and second predictor (2) | 
| r13 | Correlation between first (1) and third predictor (3) | 
| r14 | Correlation between first (1) and fourth predictor (4) | 
| r15 | Correlation between first (1) and fifth predictor (5) | 
| r23 | Correlation between second (2) and third predictor (3) | 
| r24 | Correlation between second (2) and fourth predictor (4) | 
| r25 | Correlation between second (2) and fifth predictor (5) | 
| r34 | Correlation between third (3) and fourth predictor (4) | 
| r35 | Correlation between third (3) and fifth predictor (5) | 
| r45 | Correlation between fourth (4) and fifth predictor (5) | 
| sy | Skew of outcome variable | 
| s1 | Skew of first predictor | 
| s2 | Skew of second predictor | 
| s3 | Skew of third predictor | 
| s4 | Skew of fourth predictor | 
| s5 | Skew of fifth predictor | 
| ky | Kurtosis of outcome variable | 
| k1 | Kurtosis of first predictor | 
| k2 | Kurtosis of second predictor | 
| k3 | Kurtosis of third predictor | 
| k4 | Kurtosis of fourth predictor | 
| k5 | Kurtosis of fifth predictor | 
| n | Sample size | 
| alpha | Type I error (default is .05) | 
| test | type of test ("boot","jack","perm") | 
| reps | number of replications, default is 200 - use larger for final analyses | 
| boots | number of bootstrap samples. Default is 500. Use larger for final. | 
Power for Multiple Regression with Non Normal Variables via resample
Assumptions_resample(ry1=.0,ry2=.3,r12=.3,sy=1,s1=2,s2=2,ky=1,k1=1,k2=1,n=100)
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