Description Usage Arguments Value Author(s) References See Also Examples
Calculates the power for the prior predictive check
1 2 3 | power.calc(n.r,posterior,g.m,p.sd,
statistic,Amat=0L,exact=0L,difmin=0L,effectsize=FALSE,
alpha=.05)
|
n.r |
vector with the sample size per group (i.e., n_jr) for new study (i.e., y_r). |
posterior |
matrix (e.g., the output of Gibbs.ANOVA) with samples from the posterior based on the original data (i.e., y_o). |
g.m |
vector; the population values the alternative distribution. To calculate the power to reject replication if the means are equal specify the grand mean of the study variables in the original dataset. |
p.sd |
integer; the population value for the pooled standard deviation in the alternative distribution. We advice to specify the pooled standard deviation for the study variables in the original dataset. |
statistic |
the type of hypothesis to be evaluated: "ineq" for inequality constrained means, "dif" for inequality constraints plus minimum differences between means, "exact" for specific values for the means. |
Amat |
p by q matrix, where p is the number of means in the ANOVA model, and q is the number of constraints to be imposed on the model. Each row represents one constraint where the parameter with the lower value according to the constraint receives the value -1, and the parameter with the higher value according to the constraint receives the value 1. Other parameters within the same row obtain the value 0. The create_matrices function can be used to obtain Amat. |
exact |
vector of length p, where p is the number of means in the ANOVA model, with the exact values of the constrained hypothesis. |
difmin |
vector of length q with the minimum difference per constraint as specified in |
effectsize |
logical; If TRUE the values in |
alpha |
integer; the level of alpha that should be taken into account while calculating the required sample size. |
power |
The acquired power given the input |
rejection.value |
The 1-alpha'th percentile of the null distribution. The proportion of H1 larger than this value constitues power. |
M. A. J. Zondervan-Zwijnenburg, H. Hoijtink
Zondervan-Zwijnenburg, M.A.J., Van de Schoot, R., & Hoijtink, H. (2017). Testing ANOVA replication by means of the prior predictive p-value.
See also runShiny
, Gibbs.ANOVA
, Fbar.ineq
, Fbar.dif
, and Fbar.exact
, create_matrices
, prior.predictive.check
, sample.size.calc
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | #analysis original data
data_o <- data.frame(y=ChickWeight$weight,g=ChickWeight$Diet)
g.m <- rep(mean(data_o$y),3)
#compute pooled sd
sd.g <- aggregate(data_o$y,by=list(data_o$g),sd)[,2]
n.g <- table(data_o$g)
p.sd<- pooled.sd(data_o)
means <- aggregate(data_o$y,by=list(data_o$g),mean)[,2]
post <- Gibbs.ANOVA(data_o)
power.calc(n.r=c(20,21,22,23),posterior=post$posterior,g.m=g.m,p.sd=p.sd,
statistic="exact",exact=means,alpha=.05)
|
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