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

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.

Author(s)

Milan Bimali

References

None

See Also

rnbinom

Examples

#--------------------------------------------------
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)

Example output

  Power.Expected Mean.Null Effect.Size Disp.Par Type.I.Error N.est Power.est
1            0.7         3           2        2          0.1    22      0.77
2            0.8         3           2        2          0.1    29      0.82
3            0.7         3           3        2          0.1    10      0.74
4            0.8         3           3        2          0.1    15      0.84
  Std.Err
1   0.042
2   0.038
3   0.044
4   0.037

RSPS documentation built on May 1, 2019, 10:17 p.m.