\begin{Schunk}
\begin{Sinput}
 ## Play with tPowerSim.  
 ## I just "noodled" around a while
 ## You can be systematic :)
 ##
 ## Power analysis is the study of data group sizes
  
 cond.N <- c("30:30", "40:20", "100:100")
 cond.SD <- c("10:20", "15:15", "20:10")
 cond.M <- c("100:105")
 conds <- expand.grid(nReps = 1000, SD = cond.SD, N = cond.N,
              M = cond.M, stringsAsFactors = FALSE)
 tPowerSim(conds, var.equal = TRUE)
\end{Sinput}
\begin{Soutput}
        N    SD       M reject.05.mean reject.1.mean
1   30:30 10:20 100:105          0.234         0.335
2   40:20 10:20 100:105          0.285         0.375
3 100:100 10:20 100:105          0.618         0.716
4   30:30 15:15 100:105          0.226         0.348
5   40:20 15:15 100:105          0.238         0.350
6 100:100 15:15 100:105          0.644         0.774
7   30:30 20:10 100:105          0.213         0.326
8   40:20 20:10 100:105          0.113         0.203
9 100:100 20:10 100:105          0.621         0.725
\end{Soutput}
\begin{Sinput}
 tPowerSim(conds, var.equal = FALSE)
\end{Sinput}
\begin{Soutput}
        N    SD       M reject.05.mean reject.1.mean
1   30:30 10:20 100:105          0.218         0.319
2   40:20 10:20 100:105          0.178         0.268
3 100:100 10:20 100:105          0.622         0.724
4   30:30 15:15 100:105          0.220         0.343
5   40:20 15:15 100:105          0.210         0.317
6 100:100 15:15 100:105          0.657         0.751
7   30:30 20:10 100:105          0.220         0.338
8   40:20 20:10 100:105          0.247         0.363
9 100:100 20:10 100:105          0.612         0.726
\end{Soutput}
\begin{Sinput}
 cond.M <- c("100:106") 
 conds <- expand.grid(nReps = 1000, SD = cond.SD, N = cond.N, 
                       M = cond.M, stringsAsFactors = FALSE)
 tPowerSim(conds, var.equal = TRUE)
\end{Sinput}
\begin{Soutput}
        N    SD       M reject.05.mean reject.1.mean
1   30:30 10:20 100:106          0.336         0.447
2   40:20 10:20 100:106          0.347         0.446
3 100:100 10:20 100:106          0.753         0.840
4   30:30 15:15 100:106          0.305         0.433
5   40:20 15:15 100:106          0.298         0.412
6 100:100 15:15 100:106          0.784         0.869
7   30:30 20:10 100:106          0.297         0.429
8   40:20 20:10 100:106          0.183         0.299
9 100:100 20:10 100:106          0.746         0.833
\end{Soutput}
\begin{Sinput}
 tPowerSim(conds, var.equal = FALSE)
\end{Sinput}
\begin{Soutput}
        N    SD       M reject.05.mean reject.1.mean
1   30:30 10:20 100:106          0.302         0.425
2   40:20 10:20 100:106          0.232         0.359
3 100:100 10:20 100:106          0.746         0.842
4   30:30 15:15 100:106          0.341         0.459
5   40:20 15:15 100:106          0.272         0.396
6 100:100 15:15 100:106          0.803         0.875
7   30:30 20:10 100:106          0.278         0.396
8   40:20 20:10 100:106          0.344         0.459
9 100:100 20:10 100:106          0.758         0.846
\end{Soutput}
\begin{Sinput}
 cond.N <- c("100:100", "150:150", "150:100", "100:150")
 conds <- expand.grid(nReps = 1000, SD = cond.SD, N = cond.N, 
                       M = cond.M, stringsAsFactors = FALSE)
 tPowerSim(conds, var.equal = TRUE)
\end{Sinput}
\begin{Soutput}
         N    SD       M reject.05.mean reject.1.mean
1  100:100 10:20 100:106          0.734         0.827
2  150:150 10:20 100:106          0.899         0.944
3  150:100 10:20 100:106          0.851         0.906
4  100:150 10:20 100:106          0.821         0.905
5  100:100 15:15 100:106          0.809         0.891
6  150:150 15:15 100:106          0.922         0.955
7  150:100 15:15 100:106          0.875         0.928
8  100:150 15:15 100:106          0.874         0.922
9  100:100 20:10 100:106          0.739         0.837
10 150:150 20:10 100:106          0.908         0.956
11 150:100 20:10 100:106          0.810         0.884
12 100:150 20:10 100:106          0.847         0.905
\end{Soutput}
\begin{Sinput}
 tPowerSim(conds, var.equal = FALSE)
\end{Sinput}
\begin{Soutput}
         N    SD       M reject.05.mean reject.1.mean
1  100:100 10:20 100:106          0.763         0.865
2  150:150 10:20 100:106          0.902         0.936
3  150:100 10:20 100:106          0.766         0.851
4  100:150 10:20 100:106          0.883         0.932
5  100:100 15:15 100:106          0.804         0.871
6  150:150 15:15 100:106          0.935         0.968
7  150:100 15:15 100:106          0.865         0.922
8  100:150 15:15 100:106          0.864         0.907
9  100:100 20:10 100:106          0.766         0.852
10 150:150 20:10 100:106          0.885         0.939
11 150:100 20:10 100:106          0.902         0.950
12 100:150 20:10 100:106          0.795         0.874
\end{Soutput}
\begin{Sinput}
 cond.M <- c("100:110")
 conds <- expand.grid(nReps = 1000, SD = cond.SD, N = cond.N,
                       M = cond.M, stringsAsFactors = FALSE)
 tPowerSim(conds, var.equal = TRUE)
\end{Sinput}
\begin{Soutput}
         N    SD       M reject.05.mean reject.1.mean
1  100:100 10:20 100:110          0.998         1.000
2  150:150 10:20 100:110          1.000         1.000
3  150:100 10:20 100:110          0.995         0.998
4  100:150 10:20 100:110          1.000         1.000
5  100:100 15:15 100:110          0.997         0.999
6  150:150 15:15 100:110          1.000         1.000
7  150:100 15:15 100:110          0.999         0.999
8  100:150 15:15 100:110          0.999         0.999
9  100:100 20:10 100:110          0.995         0.998
10 150:150 20:10 100:110          1.000         1.000
11 150:100 20:10 100:110          0.998         1.000
12 100:150 20:10 100:110          0.996         0.999
\end{Soutput}
\end{Schunk}
