# depcorr0: Compute Power for Comparing Two Dependent Correlations, No... In pwr2ppl: Power Analyses for Common Designs (Power to the People)

## Description

Compute Power for Comparing Two Dependent Correlations, No Variables in Common Takes correlations and range of values. First variable in each pair is termed predictor, second is DV

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```depcorr0( r12, rxy, r1x, r1y, r2x, r2y, nlow, nhigh, alpha = 0.05, tails = 2, by = 1 ) ```

## Arguments

 `r12` Correlation between the predictor and DV (first set of measures) `rxy` Correlation between the predictor and DV (second set of measures) `r1x` Correlation between the predictor (first measure) and the predictor variable (first measure) `r1y` Correlation between the predictor (first measure) and the dependent variable (second measure) `r2x` Correlation between the DV (first measure) and the predictor variable (first measure) `r2y` Correlation between the DV (first measure) and the dependent variable (second measure) `nlow` Starting sample size `nhigh` Ending sample size `alpha` Type I error (default is .05) `tails` one or two-tailed tests (default is 2) `by` Incremental increase in sample size from low to high

## Value

Power for Comparing Two Dependent Correlations, No Variables in Common

## Examples

 `1` ```depcorr0(r12=.4,rxy=.7,r1x=.3,r1y=.1,r2x=.45,r2y=.35,nlow=20,nhigh=200,by=10, tails=2) ```

### Example output

```     n  Power
1   20 0.2593
2   30 0.3808
3   40 0.4918
4   50 0.5893
5   60 0.6726
6   70 0.7421
7   80 0.7989
8   90 0.8447
9  100 0.8810
10 110 0.9096
11 120 0.9317
12 130 0.9488
13 140 0.9618
14 150 0.9717
15 160 0.9791
16 170 0.9846
17 180 0.9887
18 190 0.9918
19 200 0.9940
```

pwr2ppl documentation built on April 4, 2021, 9:06 a.m.