# negbin.samp: Estimates sample sizes for desired power using simulation... In RSPS: RNA-Seq Power Simulation

## Description

The function provides estimate of sample size for given power when there is over-dispersion. The data is simulated from Negative Binomial distribution.

## Usage

 `1` ```negbin.samp(power, lambda1, k, disp, alpha, seed, numsim, sig) ```

## Arguments

 `power` A vector of values between 0 and 1 representing desired power. `lambda1` Mean count under the null distribution. It can be a vector. `k` Fold change desired under the alternative distribution. It can be a vector. `disp` The over-dispersion parameter. 1 represent no pver-dispersion and values above one represent over-dispersion. `alpha` Type I error rate: a value between 0 and 1. It can be a vector. `seed` Value of seed to ensure reproducibility of results. `numsim` Number of simulations. 1000 is recommended. `sig` Number of significant digits after decimal.

## Details

The test statistic used is the scaled difference. Please contact the authors for more details on algorithm.

## Value

 ` Power.Expected ` Desired Power. ` Mean.Null ` Mean Count under Null distribution. ` Effect.Size ` Fold Change Under the alternate hypothesis. ` Disp.Par ` Over-dispersion parameter. ` N.est ` Estimated sample size. ` Power.est ` Estimated Power. ` Std.Err ` Standard Error.

## Note

The alternative ecological parameterization is used for Negative binomial distribution.

Milan Bimali

## References

None

 ``` 1 2 3 4 5 6 7 8 9 10``` ```#-------------------------------------------------- power = c(0.7,0.8);lambda1=3;k=c(2,3); disp=2;alpha=0.1;seed = 20;numsim=100 sample.negbin <- negbin.samp(power,lambda1,k,disp,alpha,seed,numsim) head(sample.negbin) # Another example (takes longer to run) #power = seq(0.7,0.95,0.05);lambda1=3;k=c(2,2.5,3); #disp=2;alpha=0.005;seed = 20;numsim=1000 #sample.negbin <- negbin.samp(power,lambda1,k,disp,alpha,seed,numsim) #head(sample.negbin) ```